xlwings - Make Excel Fly!¶

xlwings (Open Source)¶

xlwings is a BSD-licensed Python library that makes it easy to call Python from Excel and vice versa:

Scripting: Automate/interact with Excel from Python using a syntax close to VBA.
Macros: Replace VBA macros with clean and powerful Python code.
UDFs: Write User Defined Functions (UDFs) in Python (Windows only).
REST API: Expose your Excel workbooks via REST API.

Numpy arrays and Pandas Series/DataFrames are fully supported. xlwings-powered workbooks are easy to distribute and work on Windows and Mac.

xlwings PRO¶

xlwings PRO offers access to additional functionality. All PRO features are marked with xlwings PRO in the docs.

See xlwings PRO Overview for more details.

Video course¶

Those who prefer a didactically structured video course over this documentation should have a look at our video course:

https://training.xlwings.org/p/xlwings

It’s also a great way to support the ongoing development of xlwings :)

Installation¶

Prerequisites¶

xlwings requires an installation of Excel and therefore only works on Windows and macOS. Note that macOS currently does not support UDFs.
xlwings requires at least Python 3.6.

Here are the last versions of xlwings to support:

Python 3.5: 0.19.5
Python 2.7: 0.16.6

Installation¶

xlwings comes pre-installed with

Anaconda (Windows and macOS)
WinPython (Windows only) Make sure not to take the dot version as this only contains Python.

If you are new to Python or have trouble installing xlwings, one of these distributions is highly recommended. Otherwise, you can also install it manually with pip:

pip install xlwings

or conda:

conda install xlwings

Note that the official conda package might be a few releases behind. You can, however, use the conda-forge channel (replace install with upgrade if xlwings is already installed):

conda install -c conda-forge xlwings

Note

When you are on macOS and are installing xlwings with conda (or use the version that comes with Anaconda), you’ll need to run $ xlwings runpython install once to enable the RunPython calls from VBA. This is done automatically if you install the addin via $ xlwings addin install.

Add-in¶

To install the add-in, run the following command:

xlwings addin install

To call Excel from Python, you don’t need an add-in. Also, you can use a single file VBA module (standalone workbook) instead of the add-in. For more details, see Add-in & Settings.

Note

The add-in needs to be the same version as the Python package. Make sure to re-install the add-in after upgrading the xlwings package.

Dependencies¶

Windows: pywin32
Mac: psutil, appscript

The dependencies are automatically installed via conda or pip.

How to activate xlwings PRO¶

xlwings PRO offers access to additional functionality. All PRO features are marked with xlwings PRO in the docs.

Note

To get access to the additional functionality of xlwings PRO, you need a license key and at least xlwings v0.19.0. Everything under the xlwings.pro subpackage is distributed under a commercial license. See xlwings PRO Overview for more details.

To activate the license key, run the following command:

xlwings license update -k LICENSE_KEY

Make sure to replace LICENSE_KEY with your personal key. This will store the license key under your xlwings.conf file (see User Config: Ribbon/Config File for where this is on your system). Alternatively, you can also store the license key as an environment variable with the name XLWINGS_LICENSE_KEY.

xlwings PRO requires additionally the cryptography and Jinja2 packages which come preinstalled with Anaconda and WinPython. Otherwise, install them via pip or conda.

With pip, you can also run pip install "xlwings[pro]" which will take care of the extra dependencies for xlwings PRO.

Optional Dependencies¶

NumPy
Pandas
Matplotlib
Pillow/PIL
Flask (for REST API)
cryptography (for xlwings.pro)
Jinja2 (for xlwings.pro.reports)
requests (for permissioning)

These packages are not required but highly recommended as they play very nicely with xlwings. They are all pre-installed with Anaconda. With pip, you can install xlwings with all optional dependencies as follows:

pip install "xlwings[all]"

Update¶

To update to the latest xlwings version, run the following in a command prompt:

pip install --upgrade xlwings

or:

conda update -c conda-forge xlwings

Make sure to keep your version of the Excel add-in in sync with your Python package by running the following (make sure to close Excel first):

xlwings addin install

Uninstall¶

To uninstall xlwings completely, first uninstall the add-in, then uninstall the xlwings package using the same method (pip or conda) that you used for installing it:

xlwings addin remove

Then

pip uninstall xlwings

or:

conda remove xlwings

Finally, manually remove the .xlwings directory in your home folder if it exists.

Quickstart¶

This guide assumes you have xlwings already installed. If that’s not the case, head over to Installation.

1. Interacting with Excel from a Jupyter notebook¶

If you’re just interested in getting a pandas DataFrame in and out of your Jupyter notebook, you can use the view and load functions, see Jupyter Notebooks: Interact with Excel.

2. Scripting: Automate/interact with Excel from Python¶

Establish a connection to a workbook:

>>> import xlwings as xw
>>> wb = xw.Book()  # this will create a new workbook
>>> wb = xw.Book('FileName.xlsx')  # connect to a file that is open or in the current working directory
>>> wb = xw.Book(r'C:\path\to\file.xlsx')  # on Windows: use raw strings to escape backslashes

If you have the same file open in two instances of Excel, you need to fully qualify it and include the app instance. You will find your app instance key (the PID) via xw.apps.keys():

>>> xw.apps[10559].books['FileName.xlsx']

Instantiate a sheet object:

>>> sht = wb.sheets['Sheet1']

Reading/writing values to/from ranges is as easy as:

>>> sht.range('A1').value = 'Foo 1'
>>> sht.range('A1').value
'Foo 1'

There are many convenience features available, e.g. Range expanding:

>>> sht.range('A1').value = [['Foo 1', 'Foo 2', 'Foo 3'], [10.0, 20.0, 30.0]]
>>> sht.range('A1').expand().value
[['Foo 1', 'Foo 2', 'Foo 3'], [10.0, 20.0, 30.0]]

Powerful converters handle most data types of interest, including Numpy arrays and Pandas DataFrames in both directions:

>>> import pandas as pd
>>> df = pd.DataFrame([[1,2], [3,4]], columns=['a', 'b'])
>>> sht.range('A1').value = df
>>> sht.range('A1').options(pd.DataFrame, expand='table').value
       a    b
0.0  1.0  2.0
1.0  3.0  4.0

Matplotlib figures can be shown as pictures in Excel:

>>> import matplotlib.pyplot as plt
>>> fig = plt.figure()
>>> plt.plot([1, 2, 3, 4, 5])
[<matplotlib.lines.Line2D at 0x1071706a0>]
>>> sht.pictures.add(fig, name='MyPlot', update=True)
<Picture 'MyPlot' in <Sheet [Workbook4]Sheet1>>

3. Macros: Call Python from Excel¶

You can call Python functions either by clicking the Run button (new in v0.16) in the add-in or from VBA using the RunPython function:

The Run button expects a function called main in a Python module with the same name as your workbook. The great thing about that approach is that you don’t need your workbooks to be macro-enabled, you can save it as xlsx.

If you want to call any Python function no matter in what module it lives or what name it has, use RunPython:

Sub HelloWorld()
    RunPython "import hello; hello.world()"
End Sub

Note

Per default, RunPython expects hello.py in the same directory as the Excel file with the same name, but you can change both of these things: if your Python file is an a different folder, add that folder to the PYTHONPATH in the config. If the file has a different name, change the RunPython command accordingly.

Refer to the calling Excel book by using xw.Book.caller():

# hello.py
import numpy as np
import xlwings as xw

def world():
    wb = xw.Book.caller()
    wb.sheets[0].range('A1').value = 'Hello World!'

To make this run, you’ll need to have the xlwings add-in installed or have the workbooks setup in the standalone mode. The easiest way to get everything set up is to use the xlwings command line client from either a command prompt on Windows or a terminal on Mac: xlwings quickstart myproject.

For details about the addin, see Add-in & Settings.

4. UDFs: User Defined Functions (Windows only)¶

Writing a UDF in Python is as easy as:

import xlwings as xw

@xw.func
def hello(name):
    return f'Hello {name}'

Converters can be used with UDFs, too. Again a Pandas DataFrame example:

import xlwings as xw
import pandas as pd

@xw.func
@xw.arg('x', pd.DataFrame)
def correl2(x):
    # x arrives as DataFrame
    return x.corr()

Import this function into Excel by clicking the import button of the xlwings add-in: for a step-by-step tutorial, see User Defined Functions (UDFs).

Connect to a Book¶

When reading/writing data to the active sheet, you don’t need a book object:

>>> import xlwings as xw
>>> xw.Range('A1').value = 'something'

Python to Excel¶

The easiest way to connect to a book is offered by xw.Book: it looks for the book in all app instances and returns an error, should the same book be open in multiple instances. To connect to a book in the active app instance, use xw.books and to refer to a specific app, use:

>>> app = xw.App()  # or something like xw.apps[10559] for existing apps, get the available PIDs via xw.apps.keys()
>>> app.books['Book1']

	xw.Book	xw.books
New book	`xw.Book()`	`xw.books.add()`
Unsaved book	`xw.Book('Book1')`	`xw.books['Book1']`
Book by (full)name	`xw.Book(r'C:/path/to/file.xlsx')`	`xw.books.open(r'C:/path/to/file.xlsx')`

Note

When specifying file paths on Windows, you should either use raw strings by putting an r in front of the string or use double back-slashes like so: C:\\path\\to\\file.xlsx.

Excel to Python (RunPython)¶

To reference the calling book when using RunPython in VBA, use xw.Book.caller(), see Call Python with “RunPython”. Check out the section about Debugging to see how you can call a script from both sides, Python and Excel, without the need to constantly change between xw.Book.caller() and one of the methods explained above.

User Defined Functions (UDFs)¶

Unlike RunPython, UDFs don’t need a call to xw.Book.caller(), see User Defined Functions (UDFs). You’ll usually use the caller argument which returns the xlwings range object from where you call the function.

Syntax Overview¶

The xlwings object model is very similar to the one used by VBA.

All code samples below depend on the following import:

>>> import xlwings as xw

Active Objects¶

# Active app (i.e. Excel instance)
>>> app = xw.apps.active

# Active book
>>> wb = xw.books.active  # in active app
>>> wb = app.books.active  # in specific app

# Active sheet
>>> sht = xw.sheets.active  # in active book
>>> sht = wb.sheets.active  # in specific book

# Range on active sheet
>>> xw.Range('A1')  # on active sheet of active book of active app

A Range can be instantiated with A1 notation, a tuple of Excel’s 1-based indices, a named range or two Range objects:

xw.Range('A1')
xw.Range('A1:C3')
xw.Range((1,1))
xw.Range((1,1), (3,3))
xw.Range('NamedRange')
xw.Range(xw.Range('A1'), xw.Range('B2'))

Full qualification¶

Round brackets follow Excel’s behavior (i.e. 1-based indexing), while square brackets use Python’s 0-based indexing/slicing. As an example, the following expressions all reference the same range:

xw.apps[763].books[0].sheets[0].range('A1')
xw.apps(10559).books(1).sheets(1).range('A1')
xw.apps[763].books['Book1'].sheets['Sheet1'].range('A1')
xw.apps(10559).books('Book1').sheets('Sheet1').range('A1')

Note that the apps keys are different for you as they are the process IDs (PID). You can get the list of your PIDs via xw.apps.keys().

Range indexing/slicing¶

Range objects support indexing and slicing, a few examples:

>>> rng = xw.Book().sheets[0].range('A1:D5')
>>> rng[0, 0]
 <Range [Workbook1]Sheet1!$A$1>
>>> rng[1]
 <Range [Workbook1]Sheet1!$B$1>
>>> rng[:, 3:]
<Range [Workbook1]Sheet1!$D$1:$D$5>
>>> rng[1:3, 1:3]
<Range [Workbook1]Sheet1!$B$2:$C$3>

Range Shortcuts¶

Sheet objects offer a shortcut for range objects by using index/slice notation on the sheet object. This evaluates to either sheet.range or sheet.cells depending on whether you pass a string or indices/slices:

>>> sht = xw.Book().sheets['Sheet1']
>>> sht['A1']
<Range [Book1]Sheet1!$A$1>
>>> sht['A1:B5']
<Range [Book1]Sheet1!$A$1:$B$5>
>>> sht[0, 1]
<Range [Book1]Sheet1!$B$1>
>>> sht[:10, :10]
<Range [Book1]Sheet1!$A$1:$J$10>

Object Hierarchy¶

The following shows an example of the object hierarchy, i.e. how to get from an app to a range object and all the way back:

>>> rng = xw.apps[10559].books[0].sheets[0].range('A1')
>>> rng.sheet.book.app
<Excel App 10559>

Data Structures Tutorial¶

This tutorial gives you a quick introduction to the most common use cases and default behaviour of xlwings when reading and writing values. For an in-depth documentation of how to control the behavior using the options method, have a look at Converters and Options.

All code samples below depend on the following import:

>>> import xlwings as xw

Single Cells¶

Single cells are by default returned either as float, unicode, None or datetime objects, depending on whether the cell contains a number, a string, is empty or represents a date:

>>> import datetime as dt
>>> sheet = xw.Book().sheets[0]
>>> sheet.range('A1').value = 1
>>> sheet.range('A1').value
1.0
>>> sheet.range('A2').value = 'Hello'
>>> sheet.range('A2').value
'Hello'
>>> sheet.range('A3').value is None
True
>>> sheet.range('A4').value = dt.datetime(2000, 1, 1)
>>> sheet.range('A4').value
datetime.datetime(2000, 1, 1, 0, 0)

Lists¶

1d lists: Ranges that represent rows or columns in Excel are returned as simple lists, which means that once they are in Python, you’ve lost the information about the orientation. If that is an issue, the next point shows you how to preserve this info:
```
>>> sheet = xw.Book().sheets[0]
>>> sheet.range('A1').value = [[1],[2],[3],[4],[5]]  # Column orientation (nested list)
>>> sheet.range('A1:A5').value
[1.0, 2.0, 3.0, 4.0, 5.0]
>>> sheet.range('A1').value = [1, 2, 3, 4, 5]
>>> sheet.range('A1:E1').value
[1.0, 2.0, 3.0, 4.0, 5.0]
```
To force a single cell to arrive as list, use:
```
>>> sheet.range('A1').options(ndim=1).value
[1.0]
```
Note

To write a list in column orientation to Excel, use transpose: sheet.range('A1').options(transpose=True).value = [1,2,3,4]

2d lists: If the row or column orientation has to be preserved, set ndim in the Range options. This will return the Ranges as nested lists (“2d lists”):

>>> sheet.range('A1:A5').options(ndim=2).value
[[1.0], [2.0], [3.0], [4.0], [5.0]]
>>> sheet.range('A1:E1').options(ndim=2).value
[[1.0, 2.0, 3.0, 4.0, 5.0]]

2 dimensional Ranges are automatically returned as nested lists. When assigning (nested) lists to a Range in Excel, it’s enough to just specify the top left cell as target address. This sample also makes use of index notation to read the values back into Python:
```
>>> sheet.range('A10').value = [['Foo 1', 'Foo 2', 'Foo 3'], [10, 20, 30]]
>>> sheet.range((10,1),(11,3)).value
[['Foo 1', 'Foo 2', 'Foo 3'], [10.0, 20.0, 30.0]]
```

Note

Try to minimize the number of interactions with Excel. It is always more efficient to do sheet.range('A1').value = [[1,2],[3,4]] than sheet.range('A1').value = [1, 2] and sheet.range('A2').value = [3, 4].

Range expanding¶

You can get the dimensions of Excel Ranges dynamically through either the method expand or through the expand keyword in the options method. While expand gives back an expanded Range object, options are only evaluated when accessing the values of a Range. The difference is best explained with an example:

>>> sheet = xw.Book().sheets[0]
>>> sheet.range('A1').value = [[1,2], [3,4]]
>>> rng1 = sheet.range('A1').expand('table')  # or just .expand()
>>> rng2 = sheet.range('A1').options(expand='table')
>>> rng1.value
[[1.0, 2.0], [3.0, 4.0]]
>>> rng2.value
[[1.0, 2.0], [3.0, 4.0]]
>>> sheet.range('A3').value = [5, 6]
>>> rng1.value
[[1.0, 2.0], [3.0, 4.0]]
>>> rng2.value
[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]

'table' expands to 'down' and 'right', the other available options which can be used for column or row only expansion, respectively.

Note

Using expand() together with a named Range as top left cell gives you a flexible setup in Excel: You can move around the table and change its size without having to adjust your code, e.g. by using something like sheet.range('NamedRange').expand().value.

NumPy arrays¶

NumPy arrays work similar to nested lists. However, empty cells are represented by nan instead of None. If you want to read in a Range as array, set convert=np.array in the options method:

>>> import numpy as np
>>> sheet = xw.Book().sheets[0]
>>> sheet.range('A1').value = np.eye(3)
>>> sheet.range('A1').options(np.array, expand='table').value
array([[ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  0.,  1.]])

Pandas DataFrames¶

>>> sheet = xw.Book().sheets[0]
>>> df = pd.DataFrame([[1.1, 2.2], [3.3, None]], columns=['one', 'two'])
>>> df
   one  two
0  1.1  2.2
1  3.3  NaN
>>> sheet.range('A1').value = df
>>> sheet.range('A1:C3').options(pd.DataFrame).value
   one  two
0  1.1  2.2
1  3.3  NaN
# options: work for reading and writing
>>> sheet.range('A5').options(index=False).value = df
>>> sheet.range('A9').options(index=False, header=False).value = df

Pandas Series¶

>>> import pandas as pd
>>> import numpy as np
>>> sheet = xw.Book().sheets[0]
>>> s = pd.Series([1.1, 3.3, 5., np.nan, 6., 8.], name='myseries')
>>> s
0    1.1
1    3.3
2    5.0
3    NaN
4    6.0
5    8.0
Name: myseries, dtype: float64
>>> sheet.range('A1').value = s
>>> sheet.range('A1:B7').options(pd.Series).value
0    1.1
1    3.3
2    5.0
3    NaN
4    6.0
5    8.0
Name: myseries, dtype: float64

Note

You only need to specify the top left cell when writing a list, a NumPy array or a Pandas DataFrame to Excel, e.g.: sheet.range('A1').value = np.eye(10)

Chunking: Read/Write big DataFrames etc.¶

When you read and write from or to big ranges, you may have to chunk them or you will hit a timeout or a memory error. The ideal chunksize will depend on your system and size of the array, so you will have to try out a few different chunksizes to find one that works well:

import pandas as pd
import numpy as np
sheet = xw.Book().sheets[0]
data = np.arange(75_000 * 20).reshape(75_000, 20)
df = pd.DataFrame(data=data)
sheet['A1'].options(chunksize=10_000).value = df

And the same for reading:

# As DataFrame
df = sheet['A1'].expand().options(pd.DataFrame, chunksize=10_000).value
# As list of list
df = sheet['A1'].expand().options(chunksize=10_000).value

Add-in & Settings¶

The xlwings add-in is the preferred way to be able to use the Run main button, RunPython or UDFs. Note that you don’t need an add-in if you just want to manipulate Excel by running a Python script.

Note

The ribbon of the add-in is compatible with Excel >= 2007 on Windows and >= 2016 on Mac. On Mac, all UDF related functionality is not available.

Note

The add-in is password protected with the password xlwings. For debugging or to add new extensions, you need to unprotect it. Alternatively, you can also install the add-in via xlwings addin install --unprotected.

Run main¶

New in version 0.16.0.

The Run main button is the easiest way to run your Python code: It runs a function called main in a Python module that has the same name as your workbook. This allows you to save your workbook as xlsx without enabling macros. The xlwings quickstart command will create a workbook that will automatically work with the Run button.

Installation¶

To install the add-in, use the command line client:

xlwings addin install

Technically, this copies the add-in from Python’s installation directory to Excel’s XLSTART folder. Then, to use RunPython or UDFs in a workbook, you need to set a reference to xlwings in the VBA editor, see screenshot (Windows: Tools > References..., Mac: it’s on the lower left corner of the VBA editor). Note that when you create a workbook via xlwings quickstart, the reference should already be set.

User Settings¶

When you install the add-in for the first time, it will get auto-configured and therefore, a quickstart project should work out of the box. For fine-tuning, here are the available settings:

Interpreter: This is the path to the Python interpreter. This works also with virtual or conda envs on Mac. If you use conda envs on Windows, then leave this empty and use Conda Path and Conda Env below instead. Examples: "C:\Python39\pythonw.exe" or "/usr/local/bin/python3.9". Note that in the settings, this is stored as Interpreter_Win or Interpreter_Mac, respectively, see below!
PYTHONPATH: If the source file of your code is not found, add the path to its directory here.
Conda Path: If you are on Windows and use Anaconda or Miniconda, then type here the path to your installation, e.g. C:\Users\Username\Miniconda3 or %USERPROFILE%\Anaconda. NOTE that you need at least conda 4.6! You also need to set Conda Env, see next point.
Conda Env: If you are on Windows and use Anaconda or Miniconda, type here the name of your conda env, e.g. base for the base installation or myenv for a conda env with the name myenv.
UDF Modules: Names of Python modules (without .py extension) from which the UDFs are being imported. Separate multiple modules by “;”. Example: UDF_MODULES = "common_udfs;myproject" The default imports a file in the same directory as the Excel spreadsheet with the same name but ending in .py.
Debug UDFs: Check this box if you want to run the xlwings COM server manually for debugging, see Debugging.
RunPython: Use UDF Server: Uses the same COM Server for RunPython as for UDFs. This will be faster, as the interpreter doesn’t shut down after each call.
Restart UDF Server: This restarts the UDF Server/Python interpreter.
Show Console: Check the box in the ribbon or set the config to TRUE if you want the command prompt to pop up. This currently only works on Windows.

Anaconda/Miniconda¶

If you use Anaconda or Miniconda on Windows, you will need to set your Conda Path and Conda Env settings, as you will otherwise get errors when using NumPy etc. In return, leave Interpreter empty.

Environment Variables¶

With environment variables, you can set dynamic paths e.g. to your interpreter or PYTHONPATH:

On Windows, you can use all environment variables like so: %USERPROFILE%\Anaconda.
On macOS, the following special variables are supported: $HOME, $APPLICATIONS, $DOCUMENTS, $DESKTOP.

User Config: Ribbon/Config File¶

The settings in the xlwings Ribbon are stored in a config file that can also be manipulated externally. The location is

Windows: .xlwings\xlwings.conf in your home folder, that is usually C:\Users\<username>
macOS: ~/Library/Containers/com.microsoft.Excel/Data/xlwings.conf

The format is as follows (currently the keys are required to be all caps) - note the OS specific Interpreter settings!

"INTERPRETER_WIN","C:\path\to\python.exe"
"INTERPRETER_MAC","/path/to/python"
"PYTHONPATH",""
"CONDA PATH",""
"CONDA ENV",""
"UDF MODULES",""
"DEBUG UDFS",""
"USE UDF SERVER",""
"SHOW CONSOLE",""
"ONEDRIVE_WIN",""
"ONEDRIVE_MAC",""

Note

The ONEDRIVE_WIN/_MAC setting has to be edited directly in the file, there is currently no possibility to edit it via the ribbon. Usually, it is only required if you are either on macOS or if your environment variables on Windows are not correctly set or if you have a private and corporate location and don’t want to go with the default one. ONEDRIVE_WIN/_MAC has to point to the root folder of your local OneDrive folder.

Workbook Directory Config: Config file¶

The global settings of the Ribbon/Config file can be overridden for one or more workbooks by creating a xlwings.conf file in the workbook’s directory.

Workbook Config: xlwings.conf Sheet¶

Workbook specific settings will override global (Ribbon) and workbook directory config files: Workbook specific settings are set by listing the config key/value pairs in a sheet with the name xlwings.conf. When you create a new project with xlwings quickstart, it’ll already have such a sheet but you need to rename it to xlwings.conf to make it active.

Alternative: Standalone VBA module¶

Sometimes, it might be useful to run xlwings code without having to install an add-in first. To do so, you need to use the standalone option when creating a new project: xlwings quickstart myproject --standalone.

This will add the content of the add-in as a single VBA module so you don’t need to set a reference to the add-in anymore. It will also include Dictionary.cls as this is required on macOS. It will still read in the settings from your xlwings.conf if you don’t override them by using a sheet with the name xlwings.conf.

RunPython¶

xlwings add-in¶

To get access to Run main (new in v0.16) button or the RunPython VBA function, you’ll need the xlwings addin (or VBA module), see Add-in & Settings.

For new projects, the easiest way to get started is by using the command line client with the quickstart command, see Command Line Client (CLI) for details:

$ xlwings quickstart myproject

Call Python with “RunPython”¶

In the VBA Editor (Alt-F11), write the code below into a VBA module. xlwings quickstart automatically adds a new module with a sample call. If you rather want to start from scratch, you can add a new module via Insert > Module.

Sub HelloWorld()
    RunPython "import hello; hello.world()"
End Sub

This calls the following code in hello.py:

# hello.py
import numpy as np
import xlwings as xw

def world():
    wb = xw.Book.caller()
    wb.sheets[0].range('A1').value = 'Hello World!'

You can then attach HelloWorld to a button or run it directly in the VBA Editor by hitting F5.

Note

Place xw.Book.caller() within the function that is being called from Excel and not outside as global variable. Otherwise it prevents Excel from shutting down properly upon exiting and leaves you with a zombie process when you use Use UDF Server = True.

Function Arguments and Return Values¶

While it’s technically possible to include arguments in the function call within RunPython, it’s not very convenient. Also, RunPython does not allow you to return values. To overcome these issues, use UDFs, see User Defined Functions (UDFs) - however, this is currently limited to Windows only.

User Defined Functions (UDFs)¶

This tutorial gets you quickly started on how to write User Defined Functions.

Note

UDFs are currently only available on Windows.
For details of how to control the behaviour of the arguments and return values, have a look at Converters and Options.
For a comprehensive overview of the available decorators and their options, check out the corresponding API docs: UDF decorators.

One-time Excel preparations¶

Enable Trust access to the VBA project object model under File > Options > Trust Center > Trust Center Settings > Macro Settings. You only need to do this once. Also, this is only required for importing the functions, i.e. end users won’t need to bother about this.
Install the add-in via command prompt: xlwings addin install (see Add-in & Settings).

Workbook preparation¶

The easiest way to start a new project is to run xlwings quickstart myproject on a command prompt (see Command Line Client (CLI)). This automatically adds the xlwings reference to the generated workbook.

A simple UDF¶

The default addin settings expect a Python source file in the way it is created by quickstart:

in the same directory as the Excel file
with the same name as the Excel file, but with a .py ending instead of .xlsm.

Alternatively, you can point to a specific module via UDF Modules in the xlwings ribbon.

Let’s assume you have a Workbook myproject.xlsm, then you would write the following code in myproject.py:

import xlwings as xw

@xw.func
def double_sum(x, y):
    """Returns twice the sum of the two arguments"""
    return 2 * (x + y)

Now click on Import Python UDFs in the xlwings tab to pick up the changes made to myproject.py.
Enter the formula =double_sum(1, 2) into a cell and you will see the correct result:
The docstring (in triple-quotes) will be shown as function description in Excel.

Note

You only need to re-import your functions if you change the function arguments or the function name.
Code changes in the actual functions are picked up automatically (i.e. at the next calculation of the formula, e.g. triggered by Ctrl-Alt-F9), but changes in imported modules are not. This is the very behaviour of how Python imports work. If you want to make sure everything is in a fresh state, click Restart UDF Server.
The @xw.func decorator is only used by xlwings when the function is being imported into Excel. It tells xlwings for which functions it should create a VBA wrapper function, otherwise it has no effect on how the functions behave in Python.

Array formulas: Get efficient¶

Calling one big array formula in Excel is much more efficient than calling many single-cell formulas, so it’s generally a good idea to use them, especially if you hit performance problems.

You can pass an Excel Range as a function argument, as opposed to a single cell and it will show up in Python as list of lists.

For example, you can write the following function to add 1 to every cell in a Range:

@xw.func
def add_one(data):
    return [[cell + 1 for cell in row] for row in data]

To use this formula in Excel,

Click on Import Python UDFs again
Fill in the values in the range A1:B2
Select the range D1:E2
Type in the formula =add_one(A1:B2)
Press Ctrl+Shift+Enter to create an array formula. If you did everything correctly, you’ll see the formula surrounded by curly braces as in this screenshot:

Number of array dimensions: ndim¶

The above formula has the issue that it expects a “two dimensional” input, e.g. a nested list of the form [[1, 2], [3, 4]]. Therefore, if you would apply the formula to a single cell, you would get the following error: TypeError: 'float' object is not iterable.

To force Excel to always give you a two-dimensional array, no matter whether the argument is a single cell, a column/row or a two-dimensional Range, you can extend the above formula like this:

@xw.func
@xw.arg('data', ndim=2)
def add_one(data):
    return [[cell + 1 for cell in row] for row in data]

Array formulas with NumPy and Pandas¶

Often, you’ll want to use NumPy arrays or Pandas DataFrames in your UDF, as this unlocks the full power of Python’s ecosystem for scientific computing.

To define a formula for matrix multiplication using numpy arrays, you would define the following function:

import xlwings as xw
import numpy as np

@xw.func
@xw.arg('x', np.array, ndim=2)
@xw.arg('y', np.array, ndim=2)
def matrix_mult(x, y):
    return x @ y

Note

If you are not on Python >= 3.5 with NumPy >= 1.10, use x.dot(y) instead of x @ y.

A great example of how you can put Pandas at work is the creation of an array-based CORREL formula. Excel’s version of CORREL only works on 2 datasets and is cumbersome to use if you want to quickly get the correlation matrix of a few time-series, for example. Pandas makes the creation of an array-based CORREL2 formula basically a one-liner:

import xlwings as xw
import pandas as pd

@xw.func
@xw.arg('x', pd.DataFrame, index=False, header=False)
@xw.ret(index=False, header=False)
def CORREL2(x):
    """Like CORREL, but as array formula for more than 2 data sets"""
    return x.corr()

@xw.arg and @xw.ret decorators¶

These decorators are to UDFs what the options method is to Range objects: they allow you to apply converters and their options to function arguments (@xw.arg) and to the return value (@xw.ret). For example, to convert the argument x into a pandas DataFrame and suppress the index when returning it, you would do the following:

@xw.func
@xw.arg('x', pd.DataFrame)
@xw.ret(index=False)
def myfunction(x):
   # x is a DataFrame, do something with it
   return x

For further details see the Converters and Options documentation.

Dynamic Array Formulas¶

Note

If your version of Excel supports the new native dynamic arrays, then you don’t have to do anything special, and you shouldn’t use the expand decorator! To check if your version of Excel supports it, see if you have the =UNIQUE() formula available. Native dynamic arrays were introduced in Office 365 Insider Fast at the end of September 2018.

As seen above, to use Excel’s array formulas, you need to specify their dimensions up front by selecting the result array first, then entering the formula and finally hitting Ctrl-Shift-Enter. In practice, it often turns out to be a cumbersome process, especially when working with dynamic arrays such as time series data. Since v0.10, xlwings offers dynamic UDF expansion:

This is a simple example that demonstrates the syntax and effect of UDF expansion:

import numpy as np

@xw.func
@xw.ret(expand='table')
def dynamic_array(r, c):
    return np.random.randn(int(r), int(c))

Note

Expanding array formulas will overwrite cells without prompting
Pre v0.15.0 doesn’t allow to have volatile functions as arguments, e.g. you cannot use functions like =TODAY() as arguments. Starting with v0.15.0, you can use volatile functions as input, but the UDF will be called more than 1x.
Dynamic Arrays have been refactored with v0.15.0 to be proper legacy arrays: To edit a dynamic array with xlwings >= v0.15.0, you need to hit Ctrl-Shift-Enter while in the top left cell. Note that you don’t have to do that when you enter the formula for the first time.

Docstrings¶

The following sample shows how to include docstrings both for the function and for the arguments x and y that then show up in the function wizard in Excel:

import xlwings as xw

@xw.func
@xw.arg('x', doc='This is x.')
@xw.arg('y', doc='This is y.')
def double_sum(x, y):
    """Returns twice the sum of the two arguments"""
    return 2 * (x + y)

The “caller” argument¶

You often need to know which cell called the UDF. For this, xlwings offers the reserved argument caller which returns the calling cell as xlwings range object:

@xw.func
def get_caller_address(caller):
    # caller will not be exposed in Excel, so use it like so:
    # =get_caller_address()
    return caller.address

Note that caller will not be exposed in Excel but will be provided by xlwings behind the scenes.

The “vba” keyword¶

By using the vba keyword, you can get access to any Excel VBA object in the form of a pywin32 object. For example, if you wanted to pass the sheet object in the form of its CodeName, you can do it as follows:

@xw.func
@xw.arg('sheet1', vba='Sheet1')
def get_name(sheet1):
    # call this function in Excel with:
    # =get_name()
    return sheet1.Name

Note that vba arguments are not exposed in the UDF but automatically provided by xlwings.

Macros¶

On Windows, as an alternative to calling macros via RunPython, you can also use the @xw.sub decorator:

import xlwings as xw

@xw.sub
def my_macro():
    """Writes the name of the Workbook into Range("A1") of Sheet 1"""
    wb = xw.Book.caller()
    wb.sheets[0].range('A1').value = wb.name

After clicking on Import Python UDFs, you can then use this macro by executing it via Alt + F8 or by binding it e.g. to a button. To do the latter, make sure you have the Developer tab selected under File > Options > Customize Ribbon. Then, under the Developer tab, you can insert a button via Insert > Form Controls. After drawing the button, you will be prompted to assign a macro to it and you can select my_macro.

Call UDFs from VBA¶

Imported functions can also be used from VBA. For example, for a function returning a 2d array:

Sub MySub()

Dim arr() As Variant
Dim i As Long, j As Long

    arr = my_imported_function(...)

    For j = LBound(arr, 2) To UBound(arr, 2)
        For i = LBound(arr, 1) To UBound(arr, 1)
            Debug.Print "(" & i & "," & j & ")", arr(i, j)
        Next i
    Next j

End Sub

Asynchronous UDFs¶

Note

This is an experimental feature

New in version v0.14.0.

xlwings offers an easy way to write asynchronous functions in Excel. Asynchronous functions return immediately with #N/A waiting.... While the function is waiting for its return value, you can use Excel to do other stuff and whenever the return value is available, the cell value will be updated.

The only available mode is currently async_mode='threading', meaning that it’s useful for I/O-bound tasks, for example when you fetch data from an API over the web.

You make a function asynchronous simply by giving it the respective argument in the function decorator. In this example, the time consuming I/O-bound task is simulated by using time.sleep:

import xlwings as xw
import time

@xw.func(async_mode='threading')
def myfunction(a):
    time.sleep(5)  # long running tasks
    return a

You can use this function like any other xlwings function, simply by putting =myfunction("abcd") into a cell (after you have imported the function, of course).

Note that xlwings doesn’t use the native asynchronous functions that were introduced with Excel 2010, so xlwings asynchronous functions are supported with any version of Excel.

Matplotlib & Plotly Charts¶

Matplotlib¶

Using pictures.add(), it is easy to paste a Matplotlib plot as picture in Excel.

Getting started¶

The easiest sample boils down to:

>>> import matplotlib.pyplot as plt
>>> import xlwings as xw

>>> fig = plt.figure()
>>> plt.plot([1, 2, 3])

>>> sht = xw.Book().sheets[0]
>>> sht.pictures.add(fig, name='MyPlot', update=True)

Note

If you set update=True, you can resize and position the plot on Excel: subsequent calls to pictures.add() with the same name ('MyPlot') will update the picture without changing its position or size.

Full integration with Excel¶

Calling the above code with RunPython and binding it e.g. to a button is straightforward and works cross-platform.

However, on Windows you can make things feel even more integrated by setting up a UDF along the following lines:

@xw.func
def myplot(n, caller):
    fig = plt.figure()
    plt.plot(range(int(n)))
    caller.sheet.pictures.add(fig, name='MyPlot', update=True)
    return 'Plotted with n={}'.format(n)

If you import this function and call it from cell B2, then the plot gets automatically updated when cell B1 changes:

Properties¶

Size, position and other properties can either be set as arguments within pictures.add(), or by manipulating the picture object that is returned, see xlwings.Picture().

For example:

>>> sht = xw.Book().sheets[0]
>>> sht.pictures.add(fig, name='MyPlot', update=True,
                     left=sht.range('B5').left, top=sht.range('B5').top)

or:

>>> plot = sht.pictures.add(fig, name='MyPlot', update=True)
>>> plot.height /= 2
>>> plot.width /= 2

Getting a Matplotlib figure¶

Here are a few examples of how you get a matplotlib figure object:

via PyPlot interface:

import matplotlib.pyplot as plt
fig = plt.figure()
plt.plot([1, 2, 3, 4, 5])

or:

import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4, 5])
fig = plt.gcf()

via object oriented interface:

from matplotlib.figure import Figure
fig = Figure(figsize=(8, 6))
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 4, 5])

via Pandas:

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
ax = df.plot(kind='bar')
fig = ax.get_figure()

Plotly static charts¶

This feature requires xlwings PRO.

Prerequisites¶

In addition to plotly you will need orca. The easiest way to get it is via conda:

$ conda install -c plotly plotly-orca psutil requests

For alternative ways of installation, see: https://plotly.com/python/static-image-export/

How to use¶

It works the same as with Matplotlib, however, rendering a Plotly chart takes slightly longer. Here is a sample:

import xlwings as xw
import plotly.express as px

# Plotly chart
df = px.data.iris()
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species")

# Add it to Excel
wb = xw.Book()
wb.sheets[0].pictures.add(fig, name='IrisScatterPlot', update=True)

Jupyter Notebooks: Interact with Excel¶

When you work with Jupyter notebooks, you may use Excel as an interactive data viewer or scratchpad from where you can load DataFrames. The two convenience functions view and load make this really easy.

Note

The view and load functions should exclusively be used for interactive work. If you write scripts, use the xlwings API as introduced under Quickstart and Syntax Overview.

The view function¶

The view function accepts pretty much any object of interest, whether that’s a number, a string, a nested list or a NumPy array or a pandas DataFrame. By default, it writes the data into an Excel table in a new workbook. If you wanted to reuse the same workbook, provide a sheet object, e.g. view(df, sheet=xw.sheets.active), for further options see view.

Changed in version 0.22.0: Earlier versions were not formatting the output as Excel table

The load function¶

To load in a range in an Excel sheet as pandas DataFrame, use the load function. If you only select one cell, it will auto-expand to cover the whole range. If, however, you select a specific range that is bigger than one cell, it will load in only the selected cells. If the data in Excel does not have an index or header, set them to False like this: xw.load(index=False), see also load.

New in version 0.22.0.

Command Line Client (CLI)¶

xlwings comes with a command line client. On Windows, type the commands into a Command Prompt or Anaconda Prompt, on Mac, type them into a Terminal. To get an overview of all commands, simply type xlwings and hit Enter:

addin               Run "xlwings addin install" to install the Excel add-
                    in (will be copied to the XLSTART folder). Instead of
                    "install" you can also use "update", "remove" or
                    "status". Note that this command may take a while. Use
                    the "--unprotected" flag to install the add-in without
                    password protection. You can install your custom add-
                    in by providing the name or path via the --file flag,
                    e.g. "xlwings add-in install --file custom.xlam"
                    (New in 0.6.0, the unprotected flag was added in 0.20.4)
quickstart          Run "xlwings quickstart myproject" to create a folder
                    called "myproject" in the current directory with an
                    Excel file and a Python file, ready to be used. Use
                    the "--standalone" flag to embed all VBA code in the
                    Excel file and make it work without the xlwings add-
                    in.
runpython           macOS only: run "xlwings runpython install" if you
                    want to enable the RunPython calls without installing
                    the add-in. This will create the following file:
                    ~/Library/Application
                    Scripts/com.microsoft.Excel/xlwings.applescript
                    (new in 0.7.0)
restapi             Use "xlwings restapi run" to run the xlwings REST API
                    via Flask dev server. Accepts "--host" and "--port" as
                    optional arguments.
license             xlwings PRO: Use "xlwings license update -k KEY" where
                    "KEY" is your personal (trial) license key. This will
                    update ~/.xlwings/xlwings.conf with the LICENSE_KEY
                    entry. If you have a paid license, you can run
                    "xlwings license deploy" to create a deploy key. This
                    is not available for trial keys.
config              Run "xlwings config create" to create the user config
                    file (~/.xlwings/xlwings.conf) which is where the
                    settings from the Ribbon add-in are stored. It will
                    configure the Python interpreter that you are running
                    this command with. To reset your configuration, run
                    this with the "--force" flag which will overwrite your
                    current configuration.
                    (New in 0.19.5)
code                Run "xlwings code embed" to embed all Python modules
                    of the workbook's dir in your active Excel file. Use
                    the "--file" flag to only import a single file by
                    providing its path. Requires xlwings PRO.
                    (Changed in 0.23.4)
permission          "xlwings permission cwd" prints a JSON string that can
                    be used to permission the execution of all modules in
                    the current working directory via GET request.
                    "xlwings permission book" does the same for code that
                    is embedded in the active workbook.
                    (New in 0.23.4)
release             Run "xlwings release" to configure your active
                    workbook to work with a one-click installer for easy
                    deployment. Requires xlwings PRO.
                    (New in 0.23.4)

Deployment¶

Zip files¶

New in version 0.15.2.

To make it easier to distribute, you can zip up your Python code into a zip file. If you use UDFs, this will disable the automatic code reload, so this is a feature meant for distribution, not development. In practice, this means that when your code is inside a zip file, you’ll have to click on re-import to get any changes.

If you name your zip file like your Excel file (but with .zip extension) and place it in the same folder as your Excel workbook, xlwings will automatically find it (similar to how it works with a single python file).

If you want to use a different directory, make sure to add it to the PYTHONPATH in your config (Ribbon or config file):

PYTHONPATH, "C:\path\to\myproject.zip"

RunFrozenPython¶

Changed in version 0.15.2.

You can use a freezer like PyInstaller, cx_Freeze, py2exe etc. to freeze your Python module into an executable so that the recipient doesn’t have to install a full Python distribution.

Note

This does not work with UDFs.
Currently only available on Windows, but support for Mac should be easy to add.
You need at least 0.15.2 to support arguments whereas the syntax changed in 0.15.6

Use it as follows:

Sub MySample()
    RunFrozenPython "C:\path\to\dist\myproject\myproject.exe", "arg1 arg2"
End Sub

Troubleshooting¶

Issue: dll not found¶

Solution:

xlwings32-<version>.dll and xlwings64-<version>.dll are both in the same directory as your python.exe. If not, something went wrong with your installation. Reinstall it with pip or conda, see Installation.
Check your Interpreter in the add-in or config sheet. If it is empty, then you need to be able to open a windows command prompt and type python to start an interactive Python session. If you get the error 'python' is not recognized as an internal or external command, operable program or batch file., then you have two options: Either add the path of where your python.exe lives to your Windows path (see https://www.computerhope.com/issues/ch000549.htm) or set the full path to your interpreter in the add-in or your config sheet, e.g. C:\Users\MyUser\anaconda\pythonw.exe

Issue: Couldn’t find the local location of your OneDrive or SharePoint¶

Solution:

On either the xlwings.conf sheet or on the xlwings.conf file under your home folder (for location see User Config: Ribbon/Config File), add the following setting:

"ONEDRIVE_WIN", "C:\path\to\OneDrive"

Note: Don’t use quotes on the xlwings.conf sheet and if you are on macOS, use ONEDRIVE_MAC instead. You need to use the ONEDRIVE setting, even if you use SharePoint.

Converters and Options¶

Introduced with v0.7.0, converters define how Excel ranges and their values are converted both during reading and writing operations. They also provide a consistent experience across xlwings.Range objects and User Defined Functions (UDFs).

Converters are explicitly set in the options method when manipulating Range objects or in the @xw.arg and @xw.ret decorators when using UDFs. If no converter is specified, the default converter is applied when reading. When writing, xlwings will automatically apply the correct converter (if available) according to the object’s type that is being written to Excel. If no converter is found for that type, it falls back to the default converter.

All code samples below depend on the following import:

>>> import xlwings as xw

Syntax:

	xw.Range	UDFs
reading	`xw.Range.options(convert=None, **kwargs).value`	`@arg('x', convert=None, **kwargs)`
writing	`xw.Range.options(convert=None, **kwargs).value = myvalue`	`@ret(convert=None, **kwargs)`

Note

Keyword arguments (kwargs) may refer to the specific converter or the default converter. For example, to set the numbers option in the default converter and the index option in the DataFrame converter, you would write:

xw.Range('A1:C3').options(pd.DataFrame, index=False, numbers=int).value

Default Converter¶

If no options are set, the following conversions are performed:

single cells are read in as floats in case the Excel cell holds a number, as unicode in case it holds text, as datetime if it contains a date and as None in case it is empty.
columns/rows are read in as lists, e.g. [None, 1.0, 'a string']
2d cell ranges are read in as list of lists, e.g. [[None, 1.0, 'a string'], [None, 2.0, 'another string']]

The following options can be set:

ndim

Force the value to have either 1 or 2 dimensions regardless of the shape of the range:

>>> import xlwings as xw
>>> sht = xw.Book().sheets[0]
>>> sht.range('A1').value = [[1, 2], [3, 4]]
>>> sht.range('A1').value
1.0
>>> sht.range('A1').options(ndim=1).value
[1.0]
>>> sht.range('A1').options(ndim=2).value
[[1.0]]
>>> sht.range('A1:A2').value
[1.0 3.0]
>>> sht.range('A1:A2').options(ndim=2).value
[[1.0], [3.0]]

numbers

By default cells with numbers are read as float, but you can change it to int:
```
>>> sht.range('A1').value = 1
>>> sht.range('A1').value
1.0
>>> sht.range('A1').options(numbers=int).value
1
```
Alternatively, you can specify any other function or type which takes a single float argument.

Using this on UDFs looks like this:
```
@xw.func
@xw.arg('x', numbers=int)
def myfunction(x):
    # all numbers in x arrive as int
    return x
```
Note: Excel always stores numbers internally as floats, which is the reason why the int converter rounds numbers first before turning them into integers. Otherwise it could happen that e.g. 5 might be returned as 4 in case it is represented as a floating point number that is slightly smaller than 5. Should you require Python’s original int in your converter, use raw int instead.
dates

By default cells with dates are read as datetime.datetime, but you can change it to datetime.date:
- Range:
```
>>> import datetime as dt
>>> sht.range('A1').options(dates=dt.date).value
```
- UDFs: @xw.arg('x', dates=dt.date)
Alternatively, you can specify any other function or type which takes the same keyword arguments as datetime.datetime, for example:
```
>>> my_date_handler = lambda year, month, day, **kwargs: "%04i-%02i-%02i" % (year, month, day)
>>> sht.range('A1').options(dates=my_date_handler).value
'2017-02-20'
```
empty

Empty cells are converted per default into None, you can change this as follows:
- Range: >>> sht.range('A1').options(empty='NA').value
- UDFs: @xw.arg('x', empty='NA')

transpose

This works for reading and writing and allows us to e.g. write a list in column orientation to Excel:

Range: sht.range('A1').options(transpose=True).value = [1, 2, 3]

UDFs:

@xw.arg('x', transpose=True)
@xw.ret(transpose=True)
def myfunction(x):
    # x will be returned unchanged as transposed both when reading and writing
    return x

expand

This works the same as the Range properties table, vertical and horizontal but is only evaluated when getting the values of a Range:

>>> import xlwings as xw
>>> sht = xw.Book().sheets[0]
>>> sht.range('A1').value = [[1,2], [3,4]]
>>> rng1 = sht.range('A1').expand()
>>> rng2 = sht.range('A1').options(expand='table')
>>> rng1.value
[[1.0, 2.0], [3.0, 4.0]]
>>> rng2.value
[[1.0, 2.0], [3.0, 4.0]]
>>> sht.range('A3').value = [5, 6]
>>> rng1.value
[[1.0, 2.0], [3.0, 4.0]]
>>> rng2.value
[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]

Note

The expand method is only available on Range objects as UDFs only allow to manipulate the calling cells.

chunksize

When you read and write from or to big ranges, you may have to chunk them or you will hit a timeout or a memory error. The ideal chunksize will depend on your system and size of the array, so you will have to try out a few different chunksizes to find one that works well:

import pandas as pd
import numpy as np
sheet = xw.Book().sheets[0]
data = np.arange(75_000 * 20).reshape(75_000, 20)
df = pd.DataFrame(data=data)
sheet['A1'].options(chunksize=10_000).value = df

And the same for reading:

# As DataFrame
df = sheet['A1'].expand().options(pd.DataFrame, chunksize=10_000).value
# As list of list
df = sheet['A1'].expand().options(chunksize=10_000).value

Built-in Converters¶

xlwings offers several built-in converters that perform type conversion to dictionaries, NumPy arrays, Pandas Series and DataFrames. These build on top of the default converter, so in most cases the options described above can be used in this context, too (unless they are meaningless, for example the ndim in the case of a dictionary).

It is also possible to write and register a custom converter for additional types, see below.

The samples below can be used with both xlwings.Range objects and UDFs even though only one version may be shown.

Dictionary converter¶

The dictionary converter turns two Excel columns into a dictionary. If the data is in row orientation, use transpose:

>>> sht = xw.sheets.active
>>> sht.range('A1:B2').options(dict).value
{'a': 1.0, 'b': 2.0}
>>> sht.range('A4:B5').options(dict, transpose=True).value
{'a': 1.0, 'b': 2.0}

Note: instead of dict, you can also use OrderedDict from collections.

Numpy array converter¶

options: dtype=None, copy=True, order=None, ndim=None

The first 3 options behave the same as when using np.array() directly. Also, ndim works the same as shown above for lists (under default converter) and hence returns either numpy scalars, 1d arrays or 2d arrays.

Example:

>>> import numpy as np
>>> sht = xw.Book().sheets[0]
>>> sht.range('A1').options(transpose=True).value = np.array([1, 2, 3])
>>> sht.range('A1:A3').options(np.array, ndim=2).value
array([[ 1.],
       [ 2.],
       [ 3.]])

Pandas Series converter¶

options: dtype=None, copy=False, index=1, header=True

The first 2 options behave the same as when using pd.Series() directly. ndim doesn’t have an effect on Pandas series as they are always expected and returned in column orientation.

index: int or Boolean: When reading, it expects the number of index columns shown in Excel.

When writing, include or exclude the index by setting it to True or False.
header: Boolean: When reading, set it to False if Excel doesn’t show either index or series names.

When writing, include or exclude the index and series names by setting it to True or False.

For index and header, 1 and True may be used interchangeably.

Example:

>>> sht = xw.Book().sheets[0]
>>> s = sht.range('A1').options(pd.Series, expand='table').value
>>> s
date
2001-01-01    1
2001-01-02    2
2001-01-03    3
2001-01-04    4
2001-01-05    5
2001-01-06    6
Name: series name, dtype: float64
>>> sht.range('D1', header=False).value = s

Pandas DataFrame converter¶

options: dtype=None, copy=False, index=1, header=1

The first 2 options behave the same as when using pd.DataFrame() directly. ndim doesn’t have an effect on Pandas DataFrames as they are automatically read in with ndim=2.

index: int or Boolean: When reading, it expects the number of index columns shown in Excel.

When writing, include or exclude the index by setting it to True or False.
header: int or Boolean: When reading, it expects the number of column headers shown in Excel.

When writing, include or exclude the index and series names by setting it to True or False.

For index and header, 1 and True may be used interchangeably.

Example:

>>> sht = xw.Book().sheets[0]
>>> df = sht.range('A1:D5').options(pd.DataFrame, header=2).value
>>> df
    a     b
    c  d  e
ix
10  1  2  3
20  4  5  6
30  7  8  9

# Writing back using the defaults:
>>> sht.range('A1').value = df

# Writing back and changing some of the options, e.g. getting rid of the index:
>>> sht.range('B7').options(index=False).value = df

The same sample for UDF (starting in Range('A13') on screenshot) looks like this:

@xw.func
@xw.arg('x', pd.DataFrame, header=2)
@xw.ret(index=False)
def myfunction(x):
   # x is a DataFrame, do something with it
   return x

xw.Range and ‘raw’ converters¶

Technically speaking, these are “no-converters”.

If you need access to the xlwings.Range object directly, you can do:
```
@xw.func
@xw.arg('x', 'range')
def myfunction(x):
   return x.formula
```
This returns x as xlwings.Range object, i.e. without applying any converters or options.

The raw converter delivers the values unchanged from the underlying libraries (pywin32 on Windows and appscript on Mac), i.e. no sanitizing/cross-platform harmonizing of values are being made. This might be useful in a few cases for efficiency reasons. E.g:

>>> sht.range('A1:B2').value
[[1.0, 'text'], [datetime.datetime(2016, 2, 1, 0, 0), None]]

>>> sht.range('A1:B2').options('raw').value  # or sht.range('A1:B2').raw_value
((1.0, 'text'), (pywintypes.datetime(2016, 2, 1, 0, 0, tzinfo=TimeZoneInfo('GMT Standard Time', True)), None))

Custom Converter¶

Here are the steps to implement your own converter:

Inherit from xlwings.conversion.Converter
Implement both a read_value and write_value method as static- or classmethod:
- In read_value, value is what the base converter returns: hence, if no base has been specified it arrives in the format of the default converter.
- In write_value, value is the original object being written to Excel. It must be returned in the format that the base converter expects. Again, if no base has been specified, this is the default converter.
The options dictionary will contain all keyword arguments specified in the xw.Range.options method, e.g. when calling xw.Range('A1').options(myoption='some value') or as specified in the @arg and @ret decorator when using UDFs. Here is the basic structure:
```
from xlwings.conversion import Converter

class MyConverter(Converter):

    @staticmethod
    def read_value(value, options):
        myoption = options.get('myoption', default_value)
        return_value = value  # Implement your conversion here
        return return_value

    @staticmethod
    def write_value(value, options):
        myoption = options.get('myoption', default_value)
        return_value = value  # Implement your conversion here
        return return_value
```
Optional: set a base converter (base expects a class name) to build on top of an existing converter, e.g. for the built-in ones: DictCoverter, NumpyArrayConverter, PandasDataFrameConverter, PandasSeriesConverter
Optional: register the converter: you can (a) register a type so that your converter becomes the default for this type during write operations and/or (b) you can register an alias that will allow you to explicitly call your converter by name instead of just by class name

The following examples should make it much easier to follow - it defines a DataFrame converter that extends the built-in DataFrame converter to add support for dropping nan’s:

from xlwings.conversion import Converter, PandasDataFrameConverter

class DataFrameDropna(Converter):

    base = PandasDataFrameConverter

    @staticmethod
    def read_value(builtin_df, options):
        dropna = options.get('dropna', False)  # set default to False
        if dropna:
            converted_df = builtin_df.dropna()
        else:
            converted_df = builtin_df
        # This will arrive in Python when using the DataFrameDropna converter for reading
        return converted_df

    @staticmethod
    def write_value(df, options):
        dropna = options.get('dropna', False)
        if dropna:
            converted_df = df.dropna()
        else:
            converted_df = df
        # This will be passed to the built-in PandasDataFrameConverter when writing
        return converted_df

Now let’s see how the different converters can be applied:

# Fire up a Workbook and create a sample DataFrame
sht = xw.Book().sheets[0]
df = pd.DataFrame([[1.,10.],[2.,np.nan], [3., 30.]])

Default converter for DataFrames:

# Write
sht.range('A1').value = df

# Read
sht.range('A1:C4').options(pd.DataFrame).value

DataFrameDropna converter:

# Write
sht.range('A7').options(DataFrameDropna, dropna=True).value = df

# Read
sht.range('A1:C4').options(DataFrameDropna, dropna=True).value

Register an alias (optional):

DataFrameDropna.register('df_dropna')

# Write
sht.range('A12').options('df_dropna', dropna=True).value = df

# Read
sht.range('A1:C4').options('df_dropna', dropna=True).value

Register DataFrameDropna as default converter for DataFrames (optional):

DataFrameDropna.register(pd.DataFrame)

# Write
sht.range('A13').options(dropna=True).value = df

# Read
sht.range('A1:C4').options(pd.DataFrame, dropna=True).value

These samples all work the same with UDFs, e.g.:

@xw.func
@arg('x', DataFrameDropna, dropna=True)
@ret(DataFrameDropna, dropna=True)
def myfunction(x):
    # ...
    return x

Note

Python objects run through multiple stages of a transformation pipeline when they are being written to Excel. The same holds true in the other direction, when Excel/COM objects are being read into Python.

Pipelines are internally defined by Accessor classes. A Converter is just a special Accessor which converts to/from a particular type by adding an extra stage to the pipeline of the default Accessor. For example, the PandasDataFrameConverter defines how a list of lists (as delivered by the default Accessor) should be turned into a Pandas DataFrame.

The Converter class provides basic scaffolding to make the task of writing a new Converter easier. If you need more control you can subclass Accessor directly, but this part requires more work and is currently undocumented.

Debugging¶

Since xlwings runs in every Python environment, you can use your preferred way of debugging.

RunPython: When calling Python through RunPython, you can set a mock_caller to make it easy to switch back and forth between calling the function from Excel and Python.
UDFs: For debugging User Defined Functions, xlwings offers a convenient debugging server

To begin with, Excel will show Python errors in a Message Box:

Note

On Mac, if the import of a module/package fails before xlwings is imported, the popup will not be shown and the StatusBar will not be reset. However, the error will still be logged in the log file (/Users/<User>/Library/Containers/com.microsoft.Excel/Data/xlwings.log).

RunPython¶

Consider the following sample code of your Python source code my_module.py:

# my_module.py
import os
import xlwings as xw

def my_macro():
    wb = xw.Book.caller()
    wb.sheets[0].range('A1').value = 1

if __name__ == '__main__':
    # Expects the Excel file next to this source file, adjust accordingly.
    xw.Book('myfile.xlsm').set_mock_caller()
    my_macro()

my_macro() can now easily be run from Python for debugging and from Excel via RunPython without having to change the source code:

Sub my_macro()
    RunPython "import my_module; my_module.my_macro()"
End Sub

UDF debug server¶

Windows only: To debug UDFs, just check the Debug UDFs in the Add-in & Settings, at the top of the xlwings VBA module. Then add the following lines at the end of your Python source file and run it. Depending on which IDE you use, you might need to run the code in “debug” mode (e.g. in case you’re using PyCharm or PyDev):

if __name__ == '__main__':
    xw.serve()

When you recalculate the Sheet (Ctrl-Alt-F9), the code will stop at breakpoints or output any print calls that you may have.

The following screenshot shows the code stopped at a breakpoint in the community version of PyCharm:

Note

When running the debug server from a command prompt, there is currently no gracious way to terminate it, but closing the command prompt will kill it.

Extensions¶

It’s easy to extend the xlwings add-in with own code like UDFs or RunPython macros, so that they can be deployed without end users having to import or write the functions themselves. Just add another VBA module to the xlwings addin with the respective code.

UDF extensions can be used from every workbook without having to set a reference.

In-Excel SQL¶

The xlwings addin comes with a built-in extension that adds in-Excel SQL syntax (sqlite dialect):

=sql(SQL Statement, table a, table b, ...)

As this extension uses UDFs, it’s only available on Windows right now.

Custom Add-ins¶

New in version 0.22.0.

Custom add-ins work on Windows and macOS and are white-labeled xlwings add-ins that include all your RunPython functions and UDFs (as usual, UDFs work on Windows only). You can build add-ins with and without an Excel ribbon.

The useful thing about add-in is that UDFs and RunPython calls will be available in all workbooks right out of the box without having to add any references via the VBA editor’s Tools > References.... You can also work with standard xlsx files rather than xlsm files. This tutorial assumes you’re familiar with how xlwings and its configuration works.

Quickstart¶

Start by running the following command on a command line (to create an add-in without a ribbon, you would leave away the --ribbon flag):

$ xlwings quickstart myproject --addin --ribbon

This will create the familiar quickstart folder with a Python file and an Excel file, but this time, the Excel file is in the xlam format.

Double-click the Excel add-in to open it in Excel
Add a new empty workbook (Ctrl+N on Windows or Command+N on macOS)

You should see a new ribbon tab called MyAddin like this:

The add-in and VBA project are currently always called myaddin, no matter what name you chose in the quickstart command. We’ll see towards the end of this tutorial how we can change that, but for now we’ll stick with it.

Compared to the xlwings add-in, the custom add-in offers an additional level of configuration: the configuration sheet of the add-in itself which is the easiest way to configure simple add-ins with a static configuration.

Let’s open the VBA editor by clicking on Alt+F11 (Windows) or Option+F11 (macOS). In our project, select ThisWorkbook, then change the Property IsAddin from True to False, see the following screenshot:

This will make the sheet _myaddin.conf visible (again, we’ll see how to change the name of myaddin at the end of this tutorial):

Activate the sheet config by renaming it from _myaddin.conf to myaddin.conf
Set your Interpreter_Win/_Mac or Conda settings (you may want to take them over from the xlwings settings for now)

Once done, switch back to the VBA editor, select ThisWorkbook again, and change IsAddin back to True before you save your add-in from the VBA editor. Switch back to Excel and click the Run button under the My Addin ribbon tab and if you’ve configured the Python interpreter correctly, it will print Hello xlwings! into cell A1 of the active workbook.

Importing UDFs¶

To import your UDFs into the custom add-in, run the ImportPythonUDFsToAddin Sub towards the end of the xlwings module (click into the Sub and hit F5). Remember, you only have to do this whenever you change the function name, argument or decorator, so your end users won’t have to deal with this.

If you are only deploying UDFs via your add-in, you probably don’t need a Ribbon menu and can leave away the --ribbon flag in the quickstart command.

Configuration¶

As mentioned before, configuration works the same as with xlwings, so you could have your users override the default configuration we did above by adding a myaddin.conf sheet on their workbook or you could use the myaddin.conf file in the user’s home directory. For details see Add-in & Settings.

Installation¶

If you want to permanently install your add-in, you can do so by using the xlwings CLI:

$ xlwings addin install --file C:\path\to\your\myproject.xlam

This, however, means that you will need to adjust the PYTHONPATH for it to find your Python code (or move your Python code to somewhere where Python looks for it—more about that below under deployment). The command will copy your add-in to the XLSTART folder, a special folder from where Excel will open all files everytime you start it.

Renaming your add-in¶

Admittedly, this part is a bit cumbersome for now. Let’s assume, we would like to rename the addin from MyAddin to Demo:

In the xlwings VBA module, change Public Const PROJECT_NAME As String = "myaddin" to Public Const PROJECT_NAME As String = "demo". You’ll find this line at the top, right after the Declare statements.
If you rely on the myaddin.conf sheet for your configuration, rename it to demo.conf
Right-click the VBA project, select MyAddin Properties... and rename the Project Name from MyAddin to Demo.
If you use the ribbon, you want to rename the RibbonMyAddin VBA module to RibbonDemo. To do this, select the module in the VBA editor, then rename it in the Properties window. If you don’t see the Properties window, hit F4.
Open the add-in in the Office RibbonX Editor (see above) and replace all occurrences of MyAddin with Demo in the XML code.

And finally, you may want to rename your myproject.xlam file in the Windows explorer, but I assume you have already run the quickstart command with the correct name, so this won’t be necessary.

Deployment¶

By far the easiest way to deploy your add-in to your end-users is to build an installer via the xlwings PRO offering. This will take care of everything and your end users literally just need to double-click the installer and they are all set (no existing Python installation required and no manual installation of the add-in or adjusting of settings required).

If you want it the free (but hard) way, you either need to build an installer yourself or you need your users to install Python and the add-in and take care of placing the Python code in the correct directory. This normally involves tweaking the following settings, for example in the myaddin.conf sheet:

Interpreter_Win/_Mac: if your end-users have a working version of Python, you can use environment variables to dynamically resolve to the correct path. For example, if they have Anaconda installed in the default location, you could use the following configuration:
```
Conda Path: %USERPROFILE%\anaconda3
Conda Env: base
Interpreter_Mac: $HOME/opt/anaconda3/bin/python
```
PYTHONPATH: since you can’t have your Python source code in the XLSTART folder next to the add-in, you’ll need to adjust the PYTHONPATH setting and add the folder to where the Python code will be. You could point this to a shared drive or again make use of environment variables so the users can place the file into a folder called MyAddin in their home directory, for example. However, you can also place your Python code where Python looks for it, for example by placing them in the site-packages directory of the Python distribution—an easy way to achieve this is to build a Python package that you can install via pip.

Threading and Multiprocessing¶

New in version 0.13.0.

Threading¶

While xlwings is not technically thread safe, it’s still easy to use it in threads as long as you have at least v0.13.0 and stick to a simple rule: Do not pass xlwings objects to threads. This rule isn’t a requirement on macOS, but it’s still recommended if you want your programs to be cross-platform.

Consider the following example that will NOT work:

import threading
from queue import Queue
import xlwings as xw

num_threads = 4


def write_to_workbook():
    while True:
        rng = q.get()
        rng.value = rng.address
        print(rng.address)
        q.task_done()


q = Queue()

for i in range(num_threads):
    t = threading.Thread(target=write_to_workbook)
    t.daemon = True
    t.start()

for cell in ['A1', 'A2', 'A3', 'A4', 'A5', 'A6', 'A7', 'A8', 'A9', 'A10']:
    # THIS DOESN'T WORK - passing xlwings objects to threads will fail!
    rng = xw.Book('Book1.xlsx').sheets[0].range(cell)
    q.put(rng)

q.join()

To make it work, you simply have to fully qualify the cell reference in the thread instead of passing a Book object:

import threading
from queue import Queue
import xlwings as xw

num_threads = 4


def write_to_workbook():
    while True:
        cell_ = q.get()
        xw.Book('Book1.xlsx').sheets[0].range(cell_).value = cell_
        print(cell_)
        q.task_done()


q = Queue()

for i in range(num_threads):
    t = threading.Thread(target=write_to_workbook)
    t.daemon = True
    t.start()

for cell in ['A1', 'A2', 'A3', 'A4', 'A5', 'A6', 'A7', 'A8', 'A9', 'A10']:
    q.put(cell)

q.join()

Multiprocessing¶

Note

Multiprocessing is only supported on Windows!

The same rules apply to multiprocessing as for threading, here’s a working example:

from multiprocessing import Pool
import xlwings as xw


def write_to_workbook(cell):
    xw.Book('Book1.xlsx').sheets[0].range(cell).value = cell
    print(cell)


if __name__ == '__main__':
    with Pool(4) as p:
        p.map(write_to_workbook,
              ['A1', 'A2', 'A3', 'A4', 'A5', 'A6', 'A7', 'A8', 'A9', 'A10'])

Missing Features¶

If you’re missing a feature in xlwings, do the following:

Most importantly, open an issue on GitHub. Adding functionality should be user driven, so only if you tell us about what you’re missing, it’s eventually going to find its way into the library. By the way, we also appreciate pull requests!
Workaround: in essence, xlwings is just a smart wrapper around pywin32 on Windows and appscript on Mac. You can access the underlying objects by calling the api property:
```
>>> sheet = xw.Book().sheets[0]
>>> sheet.api
<COMObject <unknown>>  # Windows/pywin32
app(pid=2319).workbooks['Workbook1'].worksheets[1]  # Mac/appscript
```
This works accordingly for the other objects like sheet.range('A1').api etc.

The underlying objects will offer you pretty much everything you can do with VBA, using the syntax of pywin32 (which pretty much feels like VBA) and appscript (which doesn’t feel like VBA). But apart from looking ugly, keep in mind that it makes your code platform specific (!), i.e. even if you go for option 2), you should still follow option 1) and open an issue so the feature finds it’s way into the library (cross-platform and with a Pythonic syntax).

Example: Workaround to use VBA’s `Range.WrapText`¶

# Windows
sheet.range('A1').api.WrapText = True

# Mac
sheet.range('A1').api.wrap_text.set(True)

xlwings with other Office Apps¶

xlwings can also be used to call Python functions from VBA within Office apps other than Excel (like Outlook, Access etc.).

Note

New in v0.12.0 and still in a somewhat early stage that involves a bit of manual work. Currently, this functionality is only available on Windows for UDFs. The RunPython functionality is currently not supported.

How To¶

As usual, write your Python function and import it into Excel (see User Defined Functions (UDFs)).
Press Alt-F11 to get into the VBA editor, then right-click on the xlwings_udfs VBA module and select Export File.... Save the xlwings_udfs.bas file somewhere.
Switch into the other Office app, e.g. Microsoft Access and click again Alt-F11 to get into the VBA editor. Right-click on the VBA Project and Import File..., then select the file that you exported in the previous step. Once imported, replace the app name in the first line to the one that you are using, i.e. Microsoft Access or Microsoft Outlook etc. so that the first line then reads: #Const App = "Microsoft Access"
Now import the standalone xlwings VBA module (xlwings.bas). You can find it in your xlwings installation folder. To know where that is, do:
```
>>> import xlwings as xw
>>> xlwings.__path__
```
And finally do the same as in the previous step and replace the App name in the first line with the name of the corresponding app that you are using. You are now able to call the Python function from VBA.

Config¶

The other Office apps will use the same global config file as you are editing via the Excel ribbon add-in. When it makes sense, you’ll be able to use the directory config file (e.g. you can put it next to your Access or Word file) or you can hardcode the path to the config file in the VBA standalone module, e.g. in the function GetDirectoryConfigFilePath (e.g. suggested when using Outlook that doesn’t really have the same concept of files like the other Office apps). NOTE: For Office apps without file concept, you need to make sure that the PYTHONPATH points to the directory with the Python source file. For details on the different config options, see Config.

xlwings PRO Overview¶

The purpose of xlwings PRO is to finance the continued maintenance and enhancement of xlwings. This will allow you to rely on the package without being left with the dreaded “this library currently has no active maintainers” message that happens to too many open-source packages after a couple of years.

xlwings PRO offers access to additional functionality. All PRO features are marked with xlwings PRO in the docs.

Note

To get access to the additional functionality of xlwings PRO, you need a (trial) license key and at least xlwings v0.19.0. Everything under the xlwings.pro subpackage is distributed under a commercial license. To make use of xlwings PRO functionality beyond the trial, you will need to subscribe to one of our paid plans.

PRO Features¶

One-click Installer: Easily build your own Python installer including all dependencies—your end users don’t need to know anything about Python.
Embedded code: Store your Python source code directly in Excel for easy deployment.
xlwings Reports: A template-based reporting mechanism, allowing business users to change the layout of the report without having to touch the Python code.
Markdown Formatting: Support for Markdown formatting of text in cells and shapes like e.g., text boxes.
Permissioning of Code Execution: Control which users can run which Python modules via xlwings.
Plotly static charts: Support for Plotly static charts.
Table.update(): An easy way to keep an Excel table in sync with a pandas DataFrame

More Infos¶

Pricing: https://www.xlwings.org/pricing
Trial license key: https://www.xlwings.org/trial

xlwings Reports¶

This feature requires xlwings PRO.

Quickstart¶

xlwings Reports is part of xlwings PRO and a solution for template-based Excel and PDF reporting. It allows business users without Python knowledge to create & maintain Excel templates without having to go back to a Python developer for every change: xlwings Reports separates the Python code (that gets and prepares all the data) from the Excel template (that defines which data goes where and how it should be formatted). See also the xlwings Reports homepage. You can render one sheet at the time via mysheet.render_template or use the higher-level convenience function xw.create_report which first copies the template workbook and then loops through all sheets.

Render Sheets¶

Let’s first look at how to render a single sheet. This is a workbook stored as Book1.xlsx:

Running the following code:

import xlwings as xw
wb = xw.Book('Book1.xlsx')
sheet = wb.sheets['template'].copy(name='report')
sheet.render_template(title='A Demo!', table=[[1, 2], [3, 4]])
wb.to_pdf()  # requires xlwings >=0.21.1

Leaves you with this:

Render Workbooks¶

If your template is a full workbook, you can use the create_report function. Start by creating the following Python script my_template.py:

from xlwings.pro.reports import create_report
import pandas as pd

df = pd.DataFrame(data=[[1,2],[3,4]])
wb = create_report('my_template.xlsx', 'my_report.xlsx', title='MyTitle', df=df)
wb.to_pdf()  # requires xlwings >=0.21.1

Then create the following Excel file called my_template.xlsx:

Now run the Python script:

python my_template.py

This will copy the template and create the following output by replacing the variables in double curly braces with the value from the Python variable:

The last line (wb.to_pdf()) will print the workbook as PDF, for more details on the options, see Book.to_pdf().

Apart from Strings and Pandas DataFrames, you can also use numbers, lists, simple dicts, NumPy arrays, Matplotlib figures and PIL Image objects that have a filename.

By default, xlwings Reports overwrites existing values in templates if there is not enough free space for your variable. If you want your rows to dynamically shift according to the height of your array, use Frames.

Frames¶

Frames are vertical containers in which content is being aligned according to their height. That is, within Frames:

Variables do not overwrite existing cell values as they do without Frames.
Formatting is applied dynamically, depending on the number of rows your object uses in Excel

To use Frames, insert <frame> into row 1 of your Excel template wherever you want a new dyanmic column to start. Row 1 will be removed automatically when creating the report. Frames go from one <frame> to the next <frame> or the right border of the used range.

How Frames behave is best demonstrated with an example: The following screenshot defines two frames. The first one goes from column A to column E and the second one goes from column F to column I, since this is the last column that is used.

You can define and format table-like objects by formatting exactly

one header and
one data row

as shown in the screenshot:

However, also make sure to check out how to use Excel Tables below, as they make the formatting easier.

Running the following code:

from xlwings.pro.reports import create_report
import pandas as pd

df1 = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
df2 = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12], [13, 14, 15]])

data = dict(df1=df1, df2=df2)

create_report('my_template.xlsx',
              'my_report.xlsx',
              **data)

will generate this report:

Excel Tables¶

Using Excel tables is the recommended way to format tables as the styling can be applied dynamically across columns and rows. You can also use themes and apply alternating colors to rows/columns. On top of that, they are the easiest way to make the source of a chart dynamic. Go to Insert > Table and make sure that you activate My table has headers before clicking on OK. Add the placeholder as usual on the top-left of your Excel table:

Running the following script:

from xlwings.pro.reports import create_report
import pandas as pd

nrows, ncols = 3, 3
df = pd.DataFrame(data=nrows * [ncols * ['test']],
                  columns=['col ' + str(i) for i in range(ncols)])

create_report('template.xlsx', 'output.xlsx', df=df.set_index('col 0'))

Will produce the following report:

Note

If you would like to exclude the DataFrame index, make sure to set the index to the first column e.g.: df.set_index('column_name').
At the moment, you can only assign pandas DataFrames to tables.
For Excel table support, you need at least version 0.21.0 and the index behavior was changed in 0.21.3

Excel Charts¶

Note: To use charts with a dynamic source, you’ll need at least xlwings version 0.22.1

To use Excel charts in your reports, follow this process:

Add some sample/dummy data to your Excel template:
If your data source is dynamic, turn it into an Excel Table (Insert > Table). Make sure you do this before adding the chart in the next step.
Add your chart and style it:
Reduce the Excel table to a 2 x 2 range and add the placeholder in the top-left corner (in our example chart_data) . You can leave in some dummy data or clear the values of the Excel table:

Assuming your file is called mytemplate.xlsx and your sheet template like on the previous screenshot, you can run the following code:

import xlwings as xw
import pandas as pd

df = pd.DataFrame(data={'Q1': [1000, 2000, 3000],
                        'Q2': [4000, 5000, 6000],
                        'Q3': [7000, 8000, 9000]},
                  index=['North', 'South', 'West'])

wb = xw.Book("mytemplate.xlsx")
sheet = wb.sheets['template'].copy(name='report')
sheet.render_template(chart_data=df)

This will produce the following report, with the chart source correctly adjusted:

Note: If you don’t want the source data on your report, you might want to place it on a separate sheet. It’s easiest if you add and design the chart on the separate sheet, before cutting the chart and pasting it on your report template.

Shape Text¶

New in version 0.21.4.

You can also use Shapes like Text Boxes or Rectangles with template text:

from xlwings.pro.reports import create_report

create_report('template.xlsx', 'output.xlsx', temperature=12.3)

This code turns this template:

into this report:

While this works for simple text, you will loose the formatting if you have any. To prevent that, use a Markdown object, see below.

Markdown¶

New in version 0.23.0.

You can format text in cells or shapes via Markdown syntax:

from xlwings.pro import Markdown, MarkdownStyle

mytext = """\
# Title

Text **bold** and *italic*

* A first bullet
* A second bullet

# Another Title

This paragraph has a line break.
Another line.
"""

# The first sheet requires a shape as shown on the screenshot
sheet = xw.Book("MyTemplate.xlsx").sheets[0]
sheet.render_template(myplaceholder=Markdown(mytext, style)

This will render this template with the placeholder in a cell and a shape:

Like this (this uses the default formatting):

For more on Markdown, especially how to change the styling, see Markdown Formatting.

Markdown Formatting¶

This feature requires xlwings PRO.

New in version 0.23.0.

Markdown offers an easy and intuitive way of styling text components in your cells and shapes. For an introduction to Markdown, see e.g., Mastering Markdown.

Markdown support is in an early stage and currently only supports:

First-level headings
Bold (i.e., strong)
Italic (i.e., emphasis)
Unordered lists

It doesn’t support nested objects yet such as 2nd-level headings, bold/italic within bullet points or nested bullet points.

Let’s go through an example to see how everything works!

from xlwings.pro import Markdown, MarkdownStyle

mytext = """\
# Title

Text **bold** and *italic*

* A first bullet
* A second bullet

# Another Title

This paragraph has a line break.
Another line.
"""

sheet = xw.Book("Book1.xlsx").sheets[0]

# Range
sheet['A1'].clear()
sheet['A1'].value = Markdown(mytext)

# Shape: The following expects a shape like a Rectangle on the sheet
sheet.shapes[0].text = ""
sheet.shapes[0].text = Markdown(mytext)

Running this code will give you this nicely formatted text:

But why not make things a tad more stylish? By providing a MarkdownStyle object, you can define your style. Let’s change the previous example like this:

from xlwings.pro import Markdown, MarkdownStyle

mytext = """\
# Title

Text **bold** and *italic*

* A first bullet
* A second bullet

# Another Title

This paragraph has a line break.
Another line.
"""

sheet = xw.Book("Book1.xlsx").sheets[0]

# Styling
style = MarkdownStyle()
style.h1.font.color = (255, 0, 0)
style.h1.font.size = 14
style.h1.font.name = 'Comic Sans MS'  # No, that's not a font recommendation...
style.h1.blank_lines_after = 0
style.unordered_list.bullet_character = '\N{heavy black heart}'  # Emojis are fun!

# Range
sheet['A1'].clear()
sheet['A1'].value = Markdown(mytext, style)  # <= provide your style object here

# Shape: The following expects a shape like a Rectangle on the sheet
sheet.shapes[0].text = ""
sheet.shapes[0].text = Markdown(mytext, style)

Here is the output of this:

You can override all properties, i.e., you can change the emphasis from italic to a red font or anything else you want:

>>> style.strong.bold = False
>>> style.strong.color = (255, 0, 0)
>>> style.strong
strong.color: (255, 0, 0)

Markdown objects can also be used with template-based reporting, see xlwings Reports.

Note

macOS currently doesn’t support the formatting (bold, italic, color etc.) of Markdown text due to a bug with AppleScript/Excel. The text will be rendered correctly though, including bullet points.

Releasing xlwings Tools¶

This feature requires xlwings PRO.

xlwings PRO offers a simple way to deploy your xlwings tools to your end users without the usual hassle that’s involved when installing and configuring Python and xlwings. End users don’t need to know anything about Python as they only need to:

Run an installer (one installer can power many different Excel workbooks)
Use the Excel workbook as if it was a normal macro-enabled workbook

Advantages:

Zero-config: The end user doesn’t have to configure anything throughout the whole process.
No add-in required: No installation of the xlwings add-in required.
Easy to update: If you want to deploy an update of your Python code, it’s often good enough to distribute a new version of your workbook.
No conflicts: The installer doesn’t touch any environment variables or registry keys and will therefore not conflict with any existing Python installations.
Deploy key: The release command will add a deploy key as your LICENSE_KEY. A deploy key won’t expire and end users won’t need a paid subscription.

You as a developer need to create the one-click installer and run the xlwings release command on the workbook. Let’s go through these two steps in detail!

Step 1: One-Click Installer¶

As a subscriber of one of our paid plans, you will get access to a private GitHub repository, where you can build your one-click installer:

Update your requirements.txt file with your dependencies: in your repository, start by clicking on the requirements.txt file. This will open the following screen where you can click on the pencil icon to edit the file (if you know your way around Git, you can also clone the repository and use your local commit/push workflow instead):

After you’re done with your edits, click on the green Commit changes button.

Note

If you are unsure about your dependencies, it’s best to work locally with a virtual or Conda environment. In the virtual/Conda environment, only install packages that you need, then run: pip freeze.

On the right-hand side of the landing page, click on Releases:

On the next screen, click on Draft a new release (note, the very first time, you will see a green button called Create a new release instead):

This will bring up the following screen, where you’ll only have to fill in a Tag version (e.g., 1.0.0), then click on the green button Publish release:

After 3-5 minutes (you can follow the progress under the Actions tab), you’ll find the installer ready for download under Releases (ignore the zip and tar.gz files):

Note

The one-click installer is a normal Python installation that you can use with multiple Excel workbooks. Hence, you don’t need to create a separate installer for each workbook as long as they all work with the same set of dependencies as defined by the requirements.txt file.

Step 2: Release Command (CLI)¶

The release command is part of the xlwings CLI (command-line client) and will prepare your Excel file to work with the one-click installer generated in the previous step. Before anything else:

Make sure that you have enabled Trust access to the VBA project object model under File > Options > Trust Center > Trust Center Settings > Macro Settings. You only need to do this once and since this is a developer setting, your end users won’t need to bother about this. This setting is needed so that xlwings can update the Excel file with the correct version of the VBA code.
Run the installer from the previous step. This will not interfere with your existing Python installation as it won’t touch your environment variables or registry. Instead, it will only write to the following folder: %LOCALAPPDATA%\<installer-name>.
Make sure that your local version of xlwings corresponds to the version of xlwings in the requirements.txt from the installer. The easiest way to double-check this is to run pip freeze on a Command Prompt or Anaconda Prompt. If your local version of xlwings differs, install the same version as the installer uses via: pip install xlwings==<version from installer>.

To work with the release command, you should have your workbook in the xlsm format and all the Python modules in the same folder:

myworkbook.xlsm
mymodule_one.py
mymodule_two.py
...

You currently can’t organize your code in directories, but you can easily import mymodule_two from mymodule_one.

Make sure that your Excel workbook is the active workbook, then run the following command on a Command/Anaconda Prompt:

xlwings release

If this is the first time you are running this command, you will be asked a few questions. If you are shown a [Y/n], you can hit Enter to accept the default as expressed by the capitalized letter:

Name of your one-click installer? Type in the name of your one-click installer. If you want to use a different Python distribution (e.g., Anaconda), you can leave this empty (but you will need to update the xlwings.conf sheet with the Conda settings once the release command has been run).
Embed your Python code? [Y/n] This will copy the Python code into the sheets of the Excel file. It will respect all Python files that are in the same folder as the Excel workbook.
Hide the config sheet? [Y/n] This will hide the xlwings.conf sheet.
Hide the sheets with the embedded Python code? [Y/n] If you embed your Python code, this will hide all sheets with a .py ending.
Allow your tool to run without the xlwings add-in? [Y/n] This will remove the VBA reference to xlwings and copy in the xlwings VBA modules so that the end users don’t need to have the xlwings add-in installed. Note that in this case, you will need to have your RunPython calls bound to a button as you can’t use the Ribbon’s Run main button anymore.

Whatever answers you pick, you can always change them later by editing the xlwings.conf sheet or by deleting the xlwings.conf sheet and re-running the xlwings release command. If you go with the defaults, you only need to provide your end users with the one-click installer and the Excel workbook, no external Python files are required.

Updating a Release¶

To edit your Python code, it’s easiest to work with external Python files and not with embedded code. To stop xlwings from using the embedded code, simply delete all sheets with a .py ending and the workbook will again use the external Python modules. Once you are done editing the files, simply run the xlwings release command again, which will embed the updated code. If you haven’t done any changes to your dependencies (i.e., you haven’t upgraded a package or introduced a new one), you only need to redeploy your Excel workbook to have the end users get the update.

If you did make changes to the requirements.txt and release a new one-click installer, you will need to have the users install the new version of the installer first.

Note

Every time you change the xlwings version in requirements.txt of your one-click installer, make sure to upgrade your local xlwings installatino to the same version and run xlwings release again!

Embedded Code Explained¶

When you run the xlwings release command, your code will be embedded automatically (except if you switch this behavior off). You can, however, also embed code directly: on a command line, run the following command:

xlwings code embed

This will import all Python files from the current directory and paste them into Excel sheets of the currently active workbook. Now, you can use RunPython as usual: RunPython "import mymodule;mymodule.myfunction()".

Note that you can have multiple Excel sheets and import them like normal Python files. Consider this example:

You can call the main function from VBA like so:

Sub RandomNumbers()
    RunPython "import random_numbers;random_numbers.main()"
End Sub

Note

UDFs modules don’t have to be added to the UDF Modules explicitly when using embedded code. However, in contrast to how it works with external files, you currently need to re-import the functions when you change them.
While you can hide your sheets with your code, they will be written to a temporary directory in clear text.

Permissioning of Code Execution¶

This feature requires xlwings PRO.

xlwings allows you to control which Python modules are allowed to run from Excel. In order to use this functionality, you need to run your own web server. You can choose between an HTTP POST and a GET request for the permissioning:

GET: This is the simpler option as you only need to host a static JSON file that you can generate via the xlwings CLI. You can use any web server that is capable of serving static files (e.g., nginx) or use a free external service like GitHub pages. However, every permission change requires you to update the JSON file on the server.
POST: This option relies on the web server to validate the incoming payload of the POST request. While this requires custom logic on your end, you are able to connect it with any internal system (such as a database or LDAP server) to dynamically decide whether a user should be able to run a specific Python module through xlwings.

Before looking at both of these options in more detail, let’s go through the prerequisites and configuration.

Note

This feature does not stop users from running arbitrary Python code through Python directly. Rather, think of it as a mechanism to prevent accidental execution of Python code from Excel via xlwings.

Prerequisites¶

This functionality requires every end user to have the requests and cryptography libraries installed. You can install them via pip:
```
pip install requests cryptography
```
or via Conda:
```
conda install requests cryptography
```
You need to have a LICENSE_KEY in the form of a trial key, a paid license key or a deploy key.

Configuration¶

While xlwings offers various ways to configure your workbook (see Configuration), it will only respect the permissioning settings in the config file in the user’s home folder (on Windows, this is %USERPROFILE%\.xlwings\xlwings.conf):

To prevent end users from overwriting xlwings.conf, you’ll need to make sure that the file is owned by the Administrator while giving end users read-only permissions.

Add the following settings while replacing the PERMISSION_CHECK_URL and PERMISSION_CHECK_METHOD (POST or GET) with the appropriate value for your case:

"LICENSE_KEY","YOUR_LICENSE_OR_DEPLOY_KEY"
"PERMISSION_CHECK_ENABLED","True"
"PERMISSION_CHECK_URL","https://myurl.com"
"PERMISSION_CHECK_METHOD","POST"

GET request¶

You can generate the static JSON file by using the xlwings CLI:

Print the JSON string for all Python modules in a certain folder:
```
cd myfolder
xlwings permission cwd
```
Print the JSON string for all embedded modules of the active workbook:
```
xlwings permission book
```

Both commands will print a JSON string similar to this one:

{
  "modules": [
    {
      "file_name": "myfile.py",
      "sha256": "cea259922207049a734c88930b5c09109deb6b55f692fd0832f4e57052d85896",
      "machine_names": [
        "DESKTOP-QQ27RP3"
      ]
    },
    {
      "file_name": "myfile2.py",
      "sha256": "355200bb9ae00fcec1d7b660e7dd95fb3dbf246a9db397a6daa2471458a8e6cb",
      "machine_names": [
        "DESKTOP-QQ27RP3"
      ]
    }
  ]
}

All you need to do at this point is:

Add additional machines names e.g., "machine_names: [""DESKTOP-QQ27RP3", "DESKTOP-XY12AS2"]. Alternatively, you can use the "*" wildcard if you want to allow the module to be used on all end user’s computers. In case of the wildcard, it will still make sure that the file’s content hasn’t been changed by looking at its sha256 hash. xlwings uses import socket;socket.gethostname() as the machine name.
Make this JSON file accessible via your web server and update the settings in the xlwings.conf file accordingly (see above).

POST request¶

If you work with POST requests, xlwings will post a payload similar to the following:

{
  "machine_name": "DESKTOP-QQ27RP3",
  "modules": [
    {
       "file_name": "myfile.py",
       "sha256": "cea259922207049a734c88930b5c09109deb6b55f692fd0832f4e57052d85896"
    },
    {
       "file_name": "myfile2.py",
       "sha256": "355200bb9ae00fcec1d7b660e7dd95fb3dbf246a9db397a6daa2471458a8e6cb"
    }
  ]
}

It is now up to you to validate this request and:

Return the HTTP status code 200 (“success”) if the user is allowed to run the code of these modules
Return the HTTP status code 403 (“forbidden”) if the user is not allowed to run the code of these modules

Note that xlwings only checks for HTTP status code 200, so any other status code will fail.

Implementation Details & Limitations¶

Currently, RunPython and user-defined functions (UDFs) are supported. RunFrozenPython is not supported.
Permissions checks are only done when the Python module is run via Excel/xlwings, it has no effect on Python code that is run from Python directly.
RunPython won’t allow you to run code that uses the from x import y syntax. Use import x;x.y instead.
The answer of the permissioning server is cached for the duration of the Python session. For UDFs, this means until the functions are re-imported or the Restart UDF Server button is clicked or until Excel is restarted. The same is true if you run RunPython with the Use UDF Server option. By default, however, RunPython starts a new Python session every time, so it will contact the server whenever you call RunPython.
Only top-level modules are checked, i.e. modules that are imported as UDFs or run via RunPython call. Any modules that are imported as dependencies of these modules are not checked.
RunPython with external Python source files depends on logic in the VBA part of xlwings. UDFs and RunPython calls that use embedded code will only rely on Python to perform the permissioning check.

What’s New¶

v0.23.4 (Jun 15, 2021)¶

[Bug Fix] Windows: Fixed the ImportUDFs function in the VBA standalone module (GH1601).
[Bug Fix] Fixed configuration hierarchy: if you have a setting with an empty value in the xlwings.conf sheet, it will not be overridden by the same key in the directory or user config file anymore. If you wanted it to be overridden, you’d have to get the key out of the “xlwings.conf” sheet (GH1617).
PRO [Feature] Added the ability to block the execution of Python modules based on the file hash and/or machine name (GH1586), see Permissioning of Code Execution.
PRO [Feature] Added the xlwings release command for an easy release management in connection with the one-click installer, see Releasing xlwings Tools. (GH1429).

v0.23.3 (May 17, 2021)¶

[Bug Fix] Windows: UDFs returning a pandas.NaT were causing a #VALUE! error (GH1590).

v0.23.2 (May 7, 2021)¶

[Feature] Added support for myrange.wrap_text (GH173).
[Enhancement] xlwings.view() and xlwings.load() now use chunking by default (GH1570).
[Bug Fix] Allow to save non-Excel file formats (GH1569)
[Bug Fix] Calculate formulas by default in the Function Wizard (GH1574).
PRO [Bug Fix] Properly embed code with unicode characters (GH1575).

v0.23.1 (Apr 19, 2021)¶

[Feature] You can now save your workbook in any format you want, simply by specifying its extension:
```
mybook.save('binaryfile.xlsb')
mybook.save('macroenabled.xlsm')
```

[Feature] Added support for the chunksize option: when you read and write from or to big ranges, you may have to chunk them or you will hit a timeout or a memory error. The ideal chunksize will depend on your system and size of the array, so you will have to try out a few different chunksizes to find one that works well (GH77):

import pandas as pd
import numpy as np
sheet = xw.Book().sheets[0]
data = np.arange(75_000 * 20).reshape(75_000, 20)
df = pd.DataFrame(data=data)
sheet['A1'].options(chunksize=10_000).value = df

And the same for reading:

# As DataFrame
df = sheet['A1'].expand().options(pd.DataFrame, chunksize=10_000).value
# As list of list
df = sheet['A1'].expand().options(chunksize=10_000).value

[Enhancement] xw.load() now expands to the current_region instead of relying on expand() (GH1565).
[Enhancement] The OneDrive setting has been split up into a Windows and macOS-specific paths: ONEDRIVE_WIN and ONEDRIVE_MAC (GH1556).
[Bug Fix] macOS: There are no more timeouts when opening or saving large workbooks that take longer than 60 seconds (GH618).
[Bug Fix] RunPython was failing when there was a & in the Excel file name (GH1557).

v0.23.0 (Mar 5, 2021)¶

PRO [Feature]: This release adds support for Markdown-based formatting of text, both in cells as well as in shapes, see Markdown Formatting for the details. This is also supported for template-based reports.

from xlwings.pro import Markdown, MarkdownStyle

mytext = """\
# Title

Text **bold** and *italic*

* A first bullet
* A second bullet

# Another Title

This paragraph has a line break.
Another line.
"""

sheet = xw.Book("Book1.xlsx").sheets[0]
sheet['A1'].value = Markdown(mytext)
sheet.shapes[0].text = Markdown(mytext)

Running this code will give you this nicely formatted text, but you can also define your own style to match your corporate style guide as explained under Markdown Formatting:

[Feature] Added support for the Font object via range or shape objects, see Font (GH897 and GH559).
[Feature] Added support for the Characters object via range or shape objects, see Characters.

v0.22.3 (Mar 3, 2021)¶

[Enhancement] As a convenience method, you can now directly export sheets to PDF instead of having to go through the book: mysheet.to_pdf() (GH1517).
PRO [Bug Fix] Running RunPython with embedded code was broken in 0.22.0 (GH1530).

v0.22.2 (Feb 8, 2021)¶

[Bug Fix] Windows: If the path of the Excel file included a single quote, UDFs were failing (GH1511).
[Bug Fix] macOS: Prevent Excel from showing up when using hidden Excel instances via xw.App(visible=False) (GH1508).

v0.22.1 (Feb 4, 2021)¶

PRO [Bug Fix]: Table.update has been fixed so it also works when the table is the data source of a chart (GH1507).
PRO [Docs]: New documentation about how to work with Excel charts in templates; see xlwings Reports.

v0.22.0 (Jan 29, 2021)¶

[Feature] While it’s always been possible to somehow create your own xlwings-based add-ins, this release adds a toolchain to make it a lot easier to create your own white-labeled add-in, see Custom Add-ins (GH1488).
[Enhancement] xw.view now formats the pandas DataFrames as Excel table and with the new xw.load function, you can easily load a DataFrame from your active workbook into a Jupyter notebook. See Jupyter Notebooks: Interact with Excel for a full tutorial (GH1487).
[Feature] New method mysheet.copy() (GH123).
PRO [Feature]: in addition to xw.create_report(), you can now also work within a workbook by using the new mysheet.render_template() method, see also xlwings Reports (GH1478).

Older Releases¶

v0.21.4 (Nov 23, 2020)¶

[Enhancement] New property Shape.text to read and write text to the text frame of shapes (GH1456).
PRO [Feature]: xlwings Reports now supports template text in shapes, see xlwings Reports.

v0.21.3 (Nov 22, 2020)¶

PRO Breaking Change: The Table.update method has been changed to treat the DataFrame’s index consistently whether or not it’s being written to an Excel table: by default, the index is now transferred to Excel in both cases.

v0.21.2 (Nov 15, 2020)¶

[Bug Fix] The default quickstart setup now also works when you store your workbooks on OneDrive (GH1275)
[Bug Fix] Excel files that have single quotes in their paths are now working correctly (GH1021)

v0.21.1 (Nov 13, 2020)¶

[Enhancement] Added new method Book.to_pdf() to easily export PDF reports. Needless to say, this integrates very nicely with xlwings Reports (GH1363).
[Enhancement] Added support for Sheet.visible (GH1459).

v0.21.0 (Nov 9, 2020)¶

[Enhancement] Added support for Excel tables, see: Table and Tables and range.table (GH47 and GH1364)
[Enhancement]: When using UDFs, you can now use 'range' for the convert argument where you would use before xw.Range. The latter will be removed in a future version (GH1455).
[Enhancement] Windows: The comtypes requirement has been dropped (GH1443).
PRO [Feature]: Table.update offers an easy way to keep your Excel tables in sync with your DataFrame source (GH1454).
PRO [Enhancement]: The reports package now supports Excel tables in the templates. This is e.g. helpful to style the tables with striped rows, see Excel Tables (GH1364).

v0.20.8 (Oct 18, 2020)¶

[Enhancement] Windows: With UDFs, you can now get easy access to the caller (an xlwings range object) by using caller as a function argument (GH1434). In that sense, caller is now a reserved argument by xlwings and if you have any existing arguments with this name, you’ll need to rename them:
```
@xw.func
def get_caller_address(caller):
    # caller will not be exposed in Excel, so use it like so:
    # =get_caller_address()
    return caller.address
```
[Bug Fix] Windows: The setting Show Console now also shows/hides the command prompt properly when using the UDF server with Conda. There is no more switching between python and pythonw required (GH1435 and GH1421).
[Bug Fix] Windows: Functions called via RunPython with Use UDF Server activated don’t require the xw.sub decorator anymore (GH1418).

v0.20.7 (Sep 3, 2020)¶

[Bug Fix] Windows: Fix a regression introduced with 0.20.0 that would cause an AttributeError: Range.CLSID with async and legacy dynamic array UDFs (GH1404).
[Enhancement]: Matplotlib figures are now converted to 300 dpi pictures for better quality when using them with pictures.add (GH1402).

v0.20.6 (Sep 1, 2020)¶

[Bug Fix] macOS: App(visible=False) has been fixed (GH652).
[Bug Fix] macOS: The regression with Book.fullname that was introduced with 0.20.1 has been fixed (GH1390).
[Bug Fix] Windows: The retry mechanism has been improved (GH1398).

v0.20.5 (Aug 27, 2020)¶

[Bug Fix] The conda version check was failing with spaces in the installation path (GH1396).
[Bug Fix] Windows: when running app.quit(), the application is now properly closed without leaving a zombie process behind (GH1397).

v0.20.4 (Aug 20, 2020)¶

[Enhancement] The add-in can now optionally be installed without the password protection: xlwings addin install --unprotected (GH1392).

v0.20.3 (Aug 15, 2020)¶

[Bug Fix] The conda version check was erroneously triggered when importing UDFs on systems without conda. (GH1389).

v0.20.2 (Aug 13, 2020)¶

PRO [Feature]: Code can now be embedded by calling the new xlwings code embed [--file] CLI command (GH1380).
[Bug Fix] Made the import UDFs functionality more robust to prevent an Automation 440 error that some users would see (GH1381).
[Enhancement] The standalone Excel file now includes all VBA dependencies to make it work on Windows and macOS (GH1349).
[Enhancement] xlwings now blocks the call if the Conda Path/Env settings are used with legacy Conda installations (GH1384).

v0.20.1 (Aug 7, 2020)¶

[Bug Fix] macOS: password-protected sheets caused an alert when calling xw.Book (GH1377).
[Bug Fix] macOS: calling wb.save('newname.xlsx') wasn’t updating the wb object properly and caused an alert (GH1129 and GH626 and GH957).

v0.20.0 (Jul 22, 2020)¶

This version drops support for Python 3.5

[Feature] New property xlwings.App.status_bar (GH1362).
[Enhancement] xlwings.view() now becomes the active window, making it easier to work with in interactive workflows (please speak up if you feel differently) (GH1353).
[Bug Fix] The UDF server has received a serious upgrade by njwhite, getting rid of the many issues that were around with using a combination of async functions and legacy dynamic arrays. You can now also call functions defined via async def, although for the time being they are still called synchronously from Excel (GH1010 and GH1164).

v0.19.5 (Jul 5, 2020)¶

[Enhancement] When you install the add-in via xlwings addin install, it autoconfigures the add-in if it can’t find an existing user config file (GH1322).
[Feature] New xlwings config create [--force] command that autogenerates the user config file with the Python settings from which you run the command. Can be used to reset the add-in settings with the --force option (GH1322).
[Feature]: There is a new option to show/hide the console window. Note that with Conda Path and Conda Env set, the console always pops up when using the UDF server. Currently only available on Windows (GH1182).
[Enhancement] The Interpreter setting has been deprecated in favor of platform-specific settings: Interpreter_Win and Interpreter_Mac, respectively. This allows you to use the sheet config unchanged on both platforms (GH1345).
[Enhancement] On macOS, you can now use a few environment-like variables in your settings: $HOME, $APPLICATIONS, $DOCUMENTS, $DESKTOP (GH615).
[Bug Fix]: Async functions sometimes caused an error on older Excel versions without dynamic arrays (GH1341).

v0.19.4 (May 20, 2020)¶

[Feature] xlwings addin install is now available on macOS. On Windows, it has been fixed so it should now work reliably (GH704).
[Bug Fix] Fixed a dll load failed issue with pywin32 when installed via pip on Python 3.8 (GH1315).

v0.19.3 (May 19, 2020)¶

PRO [Feature]: Added possibility to create deployment keys, see Deployment Key.

v0.19.2 (May 11, 2020)¶

[Feature] New methods xlwings.Shape.scale_height() and xlwings.Shape.scale_width() (GH311).
[Bug Fix] Using Pictures.add is not distorting the proportions anymore (GH311).
PRO [Feature]: Added support for Plotly static charts (GH1309).

v0.19.1 (May 4, 2020)¶

[Bug Fix] Fixed an issue with the xlwings PRO license key when there was no xlwings.conf file (GH1308).

v0.19.0 (May 2, 2020)¶

[Bug Fix] Native dynamic array formulas can now be used with async formulas (GH1277)
[Enhancement] Quickstart references the project’s name when run from Python instead of the active book (GH1307)

Breaking Change:

Conda Base has been renamed into Conda Path to reduce the confusion with the Conda Env called base. Please adjust your settings accordingly! (GH1194)

v0.18.0 (Feb 15, 2020)¶

[Feature] Added support for merged cells: xlwings.Range.merge_area, xlwings.Range.merge_cells, xlwings.Range.merge() xlwings.Range.unmerge() (GH21).
[Bug Fix] RunPython now works properly with files that have a URL as fullname, i.e. OneDrive and SharePoint (GH1253).
[Bug Fix] Fixed a bug with wb.names['...'].refers_to_range on macOS (GH1256).

v0.17.1 (Jan 31, 2020)¶

[Bug Fix] Handle np.float64('nan') correctly (GH1116).

v0.17.0 (Jan 6, 2020)¶

This release drops support for Python 2.7 in xlwings CE. If you still rely on Python 2.7, you will need to stick to v0.16.6.

v0.16.6 (Jan 5, 2020)¶

[Enhancement] CLI changes with respect to xlwings license (GH1227).

v0.16.5 (Dec 30, 2019)¶

[Enhancement] Improvements with regards to the Run main ribbon button (GH1207 and GH1222).

v0.16.4 (Dec 17, 2019)¶

[Enhancement] Added support for xlwings.Range.copy() (GH1214).
[Enhancement] Added support for xlwings.Range.paste() (GH1215).
[Enhancement] Added support for xlwings.Range.insert() (GH80).
[Enhancement] Added support for xlwings.Range.delete() (GH862).

v0.16.3 (Dec 12, 2019)¶

[Bug Fix] Sometimes, xlwings would show an error of a previous run. Moreover, 0.16.2 introduced an issue that would not show errors at all on non-conda setups (GH1158 and GH1206)
[Enhancement] The xlwings CLI now prints the version number (GH1200)

Breaking Change:

LOG FILE has been retired and removed from the configuration/add-in.

v0.16.2 (Dec 5, 2019)¶

[Bug Fix] RunPython can now be called in parallel from different Excel instances (GH1196).

v0.16.1 (Dec 1, 2019)¶

[Enhancement] xlwings.Book() and myapp.books.open() now accept parameters like update_links, password etc. (GH1189).
[Bug Fix] Conda Env now works correctly with base for UDFs, too (GH1110).
[Bug Fix] Conda Base now allows spaces in the path (GH1176).
[Enhacement] The UDF server timeout has been increased to 2 minutes (GH1168).

v0.16.0 (Oct 13, 2019)¶

This release adds a small but very powerful feature: There’s a new Run main button in the add-in. With that, you can run your Python scripts from standard xlsx files - no need to save your workbook as macro-enabled anymore!

The only condition to make that work is that your Python script has the same name as your workbook and that it contains a function called main, which will be called when you click the Run button. All settings from your config file or config sheet are still respected, so this will work even if you have the source file in a different directory than your workbook (as long as that directory is added to the PYTHONPATH in your config).

The xlwings quickstart myproject has been updated accordingly. It still produces an xlsm file at the moment but you can save it as xlsx file if you intend to run it via the new Run button.

v0.15.10 (Aug 31, 2019) ******************-

[Bug Fix] Fixed a Python 2.7 incompatibility introduced with 0.15.9.

v0.15.9 (Aug 31, 2019)¶

[Enhancement] The sql extension now uses the native dynamic arrays if available (GH1138).
[Enhancement] xlwings now support Path objects from pathlib for all file paths (GH1126).
[Bug Fix] Various bug fixes: (GH1118), (GH1131), (GH1102).

v0.15.8 (May 5, 2019)¶

[Bug Fix] Fixed an issue introduced with the previous release that always showed the command prompt when running UDFs, not just when using conda envs (GH1098).

v0.15.7 (May 5, 2019)¶

[Bug Fix] Conda Base and Conda Env weren’t stored correctly in the config file from the ribbon (GH1090).
[Bug Fix] UDFs now work correctly with Conda Base and Conda Env. Note, however, that currently there is no way to hide the command prompt in that configuration (GH1090).
[Enhancement] Restart UDF Server now actually does what it says: it stops and restarts the server. Previously it was only stopping the server and only when the first call to Python was made, it was started again (GH1096).

v0.15.6 (Apr 29, 2019)¶

[Feature] New default converter for OrderedDict (GH1068).
[Enhancement] Import Functions now restarts the UDF server to guarantee a clean state after importing. (GH1092)
[Enhancement] The ribbon now shows tooltips on Windows (GH1093)
[Bug Fix] RunPython now properly supports conda environments on Windows (they started to require proper activation with packages like numpy etc). Conda >=4.6. required. A fix for UDFs is still pending (GH954).

Breaking Change:

[Bug Fix] RunFronzenPython now accepts spaces in the path of the executable, but in turn requires to be called with command line arguments as a separate VBA argument. Example: RunFrozenPython "C:\path\to\frozen_executable.exe", "arg1 arg2" (GH1063).

v0.15.5 (Mar 25, 2019)¶

[Enhancement] wb.macro() now accepts xlwings objects as arguments such as range, sheet etc. when the VBA macro expects the corresponding Excel object (e.g. Range, Worksheet etc.) (GH784 and GH1084)

Breaking Change:

Cells that contain a cell error such as #DIV/0!, #N/A, #NAME?, #NULL!, #NUM!, #REF!, #VALUE! return now None as value in Python. Previously they were returned as constant on Windows (e.g. -2146826246) or k.missing_value on Mac.

v0.15.4 (Mar 17, 2019)¶

[Win] BugFix: The ribbon was not showing up in Excel 2007. (GH1039)
Enhancement: Allow to install xlwings on Linux even though it’s not a supported platform: export INSTALL_ON_LINUX=1; pip install xlwings (GH1052)

v0.15.3 (Feb 23, 2019)¶

Bug Fix release:

[Mac] RunPython was broken by the previous release. If you install via conda, make sure to run xlwings runpython install again! (GH1035)
[Win] Sometimes, the ribbon was throwing errors (GH1041)

v0.15.2 (Feb 3, 2019)¶

Better support and docs for deployment, see Deployment:

You can now package your python modules into a zip file for easier distribution (GH1016).
RunFrozenPython now allows to includes arguments, e.g. RunFrozenPython "C:\path\to\my.exe arg1 arg2" (GH588).

Breaking changes:

Accessing a not existing PID in the apps collection raises now a KeyError instead of an Exception (GH1002).

v0.15.1 (Nov 29, 2018)¶

Bug Fix release:

[Win] Calling Subs or UDFs from VBA was causing an error (GH998).

v0.15.0 (Nov 20, 2018)¶

Dynamic Array Refactor

While we’re all waiting for the new native dynamic arrays, it’s still going to take another while until the majority can use them (they are not yet part of Office 2019).

In the meantime, this refactor improves the current xlwings dynamic arrays in the following way:

Use of native (“legacy”) array formulas instead of having a normal formula in the top left cell and writing around it
It’s up to 2x faster
There’s no empty row/col required outside of the dynamic array anymore
It continues to overwrite existing cells (no change there)
There’s a small breaking change in the unlikely case that you were assigning values with the expand option: myrange.options(expand='table').value = [['b'] * 3] * 3. This was previously clearing contiguous cells to the right and bottom (or one of them depending on the option), now you have to do that explicitly.

Bug Fixes:

Importing multiple UDF modules has been fixed (GH991).

v0.14.1 (Nov 9, 2018)¶

This is a bug fix release:

[Win] Fixed an issue when the new async_mode was used together with numpy arrays (GH984)
[Mac] Fixed an issue with multiple arguments in RunPython (GH905)
[Mac] Fixed an issue with the config file (GH982)

v0.14.0 (Nov 5, 2018)¶

Features:

This release adds support for asynchronous functions (like all UDF related functionality, this is only available on Windows). Making a function asynchronous is as easy as:

import xlwings as xw
import time

@xw.func(async_mode='threading')
def myfunction(a):
    time.sleep(5)  # long running tasks
    return a

See Asynchronous UDFs for the full docs.

Bug Fixes:

See GH970 and GH973.

v0.13.0 (Oct 22, 2018)¶

Features:

This release adds a REST API server to xlwings, allowing you to easily expose your workbook over the internet, see REST API for all the details!

Enhancements:

Dynamic arrays are now more robust. Before, they often didn’t manage to write everything when there was a lot going on in the workbook (GH880)
Jagged arrays (lists of lists where not all rows are of equal length) now raise an error (GH942)
xlwings can now be used with threading, see the docs: Threading and Multiprocessing (GH759).
[Win] xlwings now enforces pywin32 224 when installing xlwings on Python 3.7 (GH959)
New xlwings.Sheet.used_range property (GH112)

Bug Fixes:

The current directory is now inserted in front of everything else on the PYTHONPATH (GH958)
The standalone files had an issue in the VBA module (GH960)

Breaking changes:

Members of the xw.apps collection are now accessed by key (=PID) instead of index, e.g.: xw.apps[12345] instead of xw.apps[0]. The apps collection also has a new xw.apps.keys() method. (GH951)

v0.12.1 (Oct 7, 2018)¶

[Py27] Bug Fix for a Python 2.7 glitch.

v0.12.0 (Oct 7, 2018)¶

Features:

This release adds support to call Python functions from VBA in all Office apps (e.g. Access, Outlook etc.), not just Excel. As this uses UDFs, it is only available on Windows. See the docs: xlwings with other Office Apps.

Breaking changes:

Previously, Python functions were always returning 2d arrays when called from VBA, no matter whether it was actually a 2d array or not. Now you get the proper dimensionality which makes it easier if the return value is e.g. a string or scalar as you don’t have to unpack it anymore.

Consider the following example using the VBA Editor’s Immediate Window after importing UDFs from a project created using by xlwings quickstart:

Old behaviour

?TypeName(hello("xlwings"))
Variant()
?hello("xlwings")(0,0)
hello xlwings

New behaviour

?TypeName(hello("xlwings"))
String
?hello("xlwings")
hello xlwings

Bug Fixes:

[Win] Support expansion of environment variables in config values (GH615)
Other bug fixes: GH889, GH939, GH940, GH943.

v0.11.8 (May 13, 2018)¶

[Win] pywin32 is now automatically installed when using pip (GH827)
xlwings.bas has been readded to the python package. This facilitates e.g. the use of xlwings within other addins (GH857)

v0.11.7 (Feb 5, 2018)¶

[Win] This release fixes a bug introduced with v0.11.6 that wouldn’t allow to open workbooks by name (GH804)

v0.11.6 (Jan 27, 2018)¶

Bug Fixes:

[Win] When constantly writing to a spreadsheet, xlwings now correctly resumes after clicking into cells, previously it was crashing. (GH587)
Options are now correctly applied when writing to a sheet (GH798)

v0.11.5 (Jan 7, 2018)¶

This is mostly a bug fix release:

Config files can now additionally be saved in the directory of the workbooks, overriding the global Ribbon config, see Environment Variables (GH772)
Reading Pandas DataFrames with a simple index was creating a MultiIndex with Pandas > 0.20 (GH786)
[Win] The xlwings dlls are now properly versioned, allowing to use pre 0.11 releases in parallel with >0.11 releases (GH743)
[Mac] Sheet.names.add() was always adding the names on workbook level (GH771)
[Mac] UDF decorators now don’t cause errors on Mac anymore (GH780)

v0.11.4 (Jul 23, 2017)¶

This release brings further improvements with regards to the add-in:

The add-in now shows the version on the ribbon. This makes it easy to check if you are using the correct version (GH724):
[Mac] On Mac Excel 2016, the ribbon now only shows the available functionality (GH723):
[Mac] Mac Excel 2011 is now supported again with the new add-in. However, since Excel 2011 doesn’t support the ribbon, the config file has been created/edited manually, see Environment Variables (GH714).

Also, some new docs:

[Win] How to use imported functions in VBA, see Call UDFs from VBA.
For more up-to-date installations via conda, use the conda-forge channel, see Installation.
A troubleshooting section: Troubleshooting.

v0.11.3 (Jul 14, 2017)¶

Bug Fix: When using the xlwings.conf sheet, there was a subscript out of range error (GH708)
Enhancement: The add-in is now password protected (pw: xlwings) to declutter the VBA editor (GH710)

You need to update your xlwings add-in to get the fixes!

v0.11.2 (Jul 6, 2017)¶

Bug Fix: The sql extension was sometimes not correctly assigning the table aliases (GH699)
Bug Fix: Permission errors during pip installation should be resolved now (GH693)

v0.11.1 (Jul 5, 2017)¶

Bug Fix: The sql extension installs now correctly (GH695)
Added migration guide for v0.11, see Migrate to v0.11 (Add-in)

v0.11.0 (Jul 2, 2017)¶

Big news! This release adds a full blown add-in! We also throw in a great In-Excel SQL Extension and a few bug fixes:

Add-in¶

A few highlights:

Settings don’t have to be manipulated in VBA code anymore, but can be either set globally via Ribbon/config file or for the workbook via a special worksheet
UDF server can be restarted directly from the add-in
You can still use a VBA module instead of the add-in, but the recommended way is the add-in
Get all the details here: Add-in & Settings

In-Excel SQL Extension¶

The add-in can be extended with own code. We throw in an sql function, that allows you to perform SQL queries on data in your spreadsheets. It’s pretty awesome, get the details here: Extensions.

Bug Fixes¶

[Win]: Running Debug > Compile is not throwing errors anymore (GH678)
Pandas deprecation warnings have been fixed (GH675 and GH664)
[Mac]: Errors are again shown correctly in a pop up (GH660)
[Mac]: Like Windows, Mac now also only shows errors in a popup. Before it was including stdout, too (GH666)

Breaking Changes¶

RunFrozenPython now requires the full path to the executable.
The xlwings CLI xlwings template functionality has been removed. Use quickstart instead.

Migrate to v0.11 (Add-in)¶

This migration guide shows you how you can start using the new xlwings add-in as opposed to the old xlwings VBA module (and the old add-in that consisted of just a single import button).

Upgrade the xlwings Python package¶

Check where xlwings is currently installed

>>> import xlwings
>>> xlwings.__path__

If you installed xlwings with pip, for once, you should first uninstall xlwings: pip uninstall xlwings
Check the directory that you got under 1): if there are any files left over, delete the xlwings folder and the remaining files manually
Install the latest xlwings version: pip install xlwings

Verify that you have >= 0.11 by doing

>>> import xlwings
>>> xlwings.__version__

Install the add-in¶

If you have the old xlwings addin installed, find the location and remove it or overwrite it with the new version (see next step). If you installed it via the xlwings command line client, you should be able to do: xlwings addin remove.
Close Excel. Run xlwings addin install from a command prompt. Reopen Excel and check if the xlwings Ribbon appears. If not, copy xlwings.xlam (from your xlwings installation folder under addin\xlwings.xlam manually into the XLSTART folder. You can find the location of this folder under Options > Trust Center > Trust Center Settings… > Trusted Locations, under the description Excel default location: User StartUp. Restart Excel and you should see the add-in.

Upgrade existing workbooks¶

Make a backup of your Excel file
Open the file and go to the VBA Editor (Alt-F11)
Remove the xlwings VBA module
Add a reference to the xlwings addin, see Installation
If you want to use workbook specific settings, add a sheet xlwings.conf, see Workbook Config: xlwings.conf Sheet

Note: To import UDFs, you need to have the reference to the xlwings add-in set!

v0.10.4 (Feb 19, 2017)¶

[Win] Bug Fix: v0.10.3 introduced a bug that imported UDFs by default with volatile=True, this has now been fixed. You will need to reimport your functions after upgrading the xlwings package.

v0.10.3 (Jan 28, 2017)¶

This release adds new features to User Defined Functions (UDFs):

categories
volatile option
suppress calculation in function wizard

Syntax:

import xlwings as xw
@xw.func(category="xlwings", volatile=False, call_in_wizard=True)
def myfunction():
    return ...

For details, check out the (also new) and comprehensive API docs about the decorators: UDF decorators

v0.10.2 (Dec 31, 2016)¶

[Win] Python 3.6 is now supported (GH592)

v0.10.1 (Dec 5, 2016)¶

Writing a Pandas Series with a MultiIndex header was not writing out the header (GH572)
[Win] Docstrings for UDF arguments are now working (GH367)
[Mac] Range.clear_contents() has been fixed (it was doing clear() instead) (GH576)
xw.Book(...) and xw.books.open(...) raise now the same error in case the file doesn’t exist (GH540)

v0.10.0 (Sep 20, 2016)¶

Dynamic Array Formulas¶

This release adds an often requested & powerful new feature to User Defined Functions (UDFs): Dynamic expansion for array formulas. While Excel offers array formulas, you need to specify their dimensions up front by selecting the result array first, then entering the formula and finally hitting Ctrl-Shift-Enter. While this makes sense from a data integrity point of view, in practice, it often turns out to be a cumbersome limitation, especially when working with dynamic arrays such as time series data.

This is a simple example that demonstrates the syntax and effect of UDF expansion:

import numpy as np

@xw.func
@xw.ret(expand='table')
def dynamic_array(r, c):
    return np.random.randn(int(r), int(c))

Note: Expanding array formulas will overwrite cells without prompting and leave an empty border around them, i.e. they will clear the row to the bottom and the column to the right of the array.

Bug Fixes¶

The int converter works now always as you would expect (e.g.: xw.Range('A1').options(numbers=int).value). Before, it could happen that the number was off by 1 due to floating point issues (GH554).

v0.9.3 (Aug 22, 2016)¶

[Win] App.visible wasn’t behaving correctly (GH551).
[Mac] Added support for the new 64bit version of Excel 2016 on Mac (GH549).
Unicode book names are again supported (GH546).
xlwings.Book.save() now supports relative paths. Also, when saving an existing book under a new name without specifying the full path, it’ll be saved in Python’s current working directory instead of in Excel’s default directory (GH185).

v0.9.2 (Aug 8, 2016)¶

Another round of bug fixes:

[Mac]: Sometimes, a column was referenced instead of a named range (GH545)
[Mac]: Python 2.7 was raising a LookupError: unknown encoding: mbcs (GH544)
Fixed docs regarding set_mock_caller (GH543)

v0.9.1 (Aug 5, 2016)¶

This is a bug fix release: As to be expected after a rewrite, there were some rough edges that have now been taken care of:

[Win] Opening a file via xw.Book() was causing an additional Book1 to be opened in case Excel was not running yet (GH531)
[Win] Some users were getting an ImportError (GH533)
[PY 2.7] RunPython was broken with Python 2.7 (GH537)
Some corrections in the docs (GH538 and GH536)

v0.9.0 (Aug 2, 2016)¶

Exciting times! v0.9.0 is a complete rewrite of xlwings with loads of syntax changes (hence the version jump). But more importantly, this release adds a ton of new features and bug fixes that would have otherwise been impossible. Some of the highlights are listed below, but make sure to check out the full migration guide for the syntax changes in details. Note, however, that the syntax for user defined functions (UDFs) did not change. At this point, the API is fairly stable and we’re expecting only smaller changes on our way towards a stable v1.0 release.

Active book instead of current book: xw.Range('A1') goes against the active sheet of the active book like you’re used to from VBA. Instantiating an explicit connection to a Book is not necessary anymore:
```
>>> import xlwings as xw
>>> xw.Range('A1').value = 11
>>> xw.Range('A1').value
11.0
```

Excel Instances: Full support of multiple Excel instances (even on Mac!)

>>> app1 = xw.App()
>>> app2 = xw.App()
>>> xw.apps
Apps([<Excel App 1668>, <Excel App 1644>])

New powerful object model based on collections and close to Excel’s original, allowing to fully qualify objects: xw.apps[0].books['MyBook.xlsx'].sheets[0].range('A1:B2').value

It supports both Python indexing (square brackets) and Excel indexing (round brackets):

xw.books[0].sheets[0] is the same as xw.books(1).sheets(1)

It also supports indexing and slicing of range objects:
```
>>> rng = xw.Range('A1:E10')
>>> rng[1]
<Range [Workbook1]Sheet1!$B$1>
>>> rng[:2, :2]
<Range [Workbook1]Sheet1!$A$1:$B$2>
```
For more details, see Syntax Overview.
UDFs can now also be imported from packages, not just modules (GH437)
Named Ranges: Introduction of full object model and proper support for sheet and workbook scope (GH256)
Excel doesn’t become the active window anymore so the focus stays on your Python environment (GH414)
When writing to ranges while Excel is busy, xlwings is now retrying until Excel is idle again (GH468)
xlwings.view() has been enhanced to accept an optional sheet object (GH469)
Objects like books, sheets etc. can now be compared (e.g. wb1 == wb2) and are properly hashable
Note that support for Python 2.6 has been dropped

Some of the new methods/properties worth mentioning are:

Bug Fixes¶

See here for details about which bugs have been fixed.

Migrate to v0.9¶

The purpose of this document is to enable you a smooth experience when upgrading to xlwings v0.9.0 and above by laying out the concept and syntax changes in detail. If you want to get an overview of the new features and bug fixes, have a look at the release notes. Note that the syntax for User Defined Functions (UDFs) didn’t change.

Full qualification: Using collections¶

The new object model allows to specify the Excel application instance if needed:

old: xw.Range('Sheet1', 'A1', wkb=xw.Workbook('Book1'))
new: xw.apps[0].books['Book1'].sheets['Sheet1'].range('A1')

See Syntax Overview for the details of the new object model.

Connecting to Books¶

old: xw.Workbook()
new: xw.Book() or via xw.books if you need to control the app instance.

See Connect to a Book for the details.

Active Objects¶

# Active app (i.e. Excel instance)
>>> app = xw.apps.active

# Active book
>>> wb = xw.books.active  # in active app
>>> wb = app.books.active  # in specific app

# Active sheet
>>> sht = xw.sheets.active  # in active book
>>> sht = wb.sheets.active  # in specific book

# Range on active sheet
>>> xw.Range('A1')  # on active sheet of active book of active app

Round vs. Square Brackets¶

Round brackets follow Excel’s behavior (i.e. 1-based indexing), while square brackets use Python’s 0-based indexing/slicing.

As an example, the following all reference the same range:

xw.apps[0].books[0].sheets[0].range('A1')
xw.apps(1).books(1).sheets(1).range('A1')
xw.apps[0].books['Book1'].sheets['Sheet1'].range('A1')
xw.apps(1).books('Book1').sheets('Sheet1').range('A1')

Access the underlying Library/Engine¶

old: xw.Range('A1').xl_range and xl_sheet etc.
new: xw.Range('A1').api, same for all other objects

This returns a pywin32 COM object on Windows and an appscript object on Mac.

Cheat sheet¶

Note that sht stands for a sheet object, like e.g. (in 0.9.0 syntax): sht = xw.books['Book1'].sheets[0]

	v0.9.0	v0.7.2
Active Excel instance	`xw.apps.active`	unsupported
New Excel instance	`app = xw.App()`	unsupported
Get app from book	`app = wb.app`	`app = xw.Application(wb)`
Target installation (Mac)	`app = xw.App(spec=...)`	`wb = xw.Workbook(app_target=...)`
Hide Excel Instance	`app = xw.App(visible=False)`	`wb = xw.Workbook(app_visible=False)`
Selected Range	`app.selection`	`wb.get_selection()`
Calculation mode	`app.calculation = 'manual'`	`app.calculation = xw.constants.Calculation.xlCalculationManual`
All books in app	`app.books`	unsupported

Fully qualified book	`app.books['Book1']`	unsupported
Active book in active app	`xw.books.active`	`xw.Workbook.active()`
New book in active app	`wb = xw.Book()`	`wb = xw.Workbook()`
New book in specific app	`wb = app.books.add()`	unsupported
All sheets in book	`wb.sheets`	`xw.Sheet.all(wb)`
Call a macro in an addin	`app.macro('MacroName')`	unsupported

First sheet of book wb	`wb.sheets[0]`	`xw.Sheet(1, wkb=wb)`
Active sheet	`wb.sheets.active`	`xw.Sheet.active(wkb=wb)` or `wb.active_sheet`
Add sheet	`wb.sheets.add()`	`xw.Sheet.add(wkb=wb)`
Sheet count	`wb.sheets.count` or `len(wb.sheets)`	`xw.Sheet.count(wb)`

Add chart to sheet	`chart = wb.sheets[0].charts.add()`	`chart = xw.Chart.add(sheet=1, wkb=wb)`
Existing chart	`wb.sheets['Sheet 1'].charts[0]`	`xw.Chart('Sheet 1', 1)`
Chart Type	`chart.chart_type = '3d_area'`	`chart.chart_type = xw.constants.ChartType.xl3DArea`

Add picture to sheet	`wb.sheets[0].pictures.add('path/to/pic')`	`xw.Picture.add('path/to/pic', sheet=1, wkb=wb)`
Existing picture	`wb.sheets['Sheet 1'].pictures[0]`	`xw.Picture('Sheet 1', 1)`
Matplotlib	`sht.pictures.add(fig, name='x', update=True)`	`xw.Plot(fig).show('MyPlot', sheet=sht, wkb=wb)`

Table expansion	`sht.range('A1').expand('table')`	`xw.Range(sht, 'A1', wkb=wb).table`
Vertical expansion	`sht.range('A1').expand('down')`	`xw.Range(sht, 'A1', wkb=wb).vertical`
Horizontal expansion	`sht.range('A1').expand('right')`	`xw.Range(sht, 'A1', wkb=wb).horizontal`

Set name of range	`sht.range('A1').name = 'name'`	`xw.Range(sht, 'A1', wkb=wb).name = 'name'`
Get name of range	`sht.range('A1').name.name`	`xw.Range(sht, 'A1', wkb=wb).name`

mock caller	`xw.Book('file.xlsm').set_mock_caller()`	`xw.Workbook.set_mock_caller('file.xlsm')`

v0.7.2 (May 18, 2016)¶

Bug Fixes¶

[Win] UDFs returning Pandas DataFrames/Series containing nan were failing (GH446).
[Win] RunFrozenPython was not finding the executable (GH452).
The xlwings VBA module was not finding the Python interpreter if PYTHON_WIN or PYTHON_MAC contained spaces (GH461).

v0.7.1 (April 3, 2016)¶

Enhancements¶

[Win]: User Defined Functions (UDFs) support now optional/default arguments (GH363)
[Win]: User Defined Functions (UDFs) support now multiple source files, see also under API changes below. For example (VBA settings): UDF_MODULES="common;myproject"

VBA Subs & Functions are now callable from Python:

As an example, this VBA function:

Function MySum(x, y)
    MySum = x + y
End Function

can be accessed like this:

>>> import xlwings as xw
>>> wb = xw.Workbook.active()
>>> my_sum = wb.macro('MySum')
>>> my_sum(1, 2)
3.0

New xw.view method: This opens a new workbook and displays an object on its first sheet. E.g.:

>>> import xlwings as xw
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
>>> xw.view(df)

New docs about Matplotlib & Plotly Charts and Custom Converter
New method: xlwings.Range.formula_array() (GH411)

API changes¶

VBA settings: PYTHON_WIN and PYTHON_MAC must now include the interpreter if you are not using the default (PYTHON_WIN = "") (GH289). E.g.:
```
PYTHON_WIN: "C:\Python35\pythonw.exe"
PYTHON_MAC: "/usr/local/bin/python3.5"
```
[Win]: VBA settings: UDF_PATH has been replaced with UDF_MODULES. The default behaviour doesn’t change though (i.e. if UDF_MODULES = "", then a Python source file with the same name as the Excel file, but with .py ending will be imported from the same directory as the Excel file).

New:
```
UDF_MODULES: "mymodule"
PYTHONPATH: "C:\path\to"
```
Old:
```
UDF_PATH: "C:\path\to\mymodule.py"
```

Bug Fixes¶

Numpy scalars issues were resolved (GH415)
[Win]: xlwings was failing with freezers like cx_Freeze (GH413)
[Win]: UDFs were failing if they were returning None or np.nan (GH390)
Multiindex Pandas Series have been fixed (GH383)
[Mac]: xlwings runpython install was failing (GH424)

v0.7.0 (March 4, 2016)¶

This version marks an important first step on our path towards a stable release. It introduces converters, a new and powerful concept that brings a consistent experience for how Excel Ranges and their values are treated both when reading and writing but also across xlwings.Range objects and User Defined Functions (UDFs).

As a result, a few highlights of this release include:

Pandas DataFrames and Series are now supported for reading and writing, both via Range object and UDFs
New Range converter options: transpose, dates, numbers, empty, expand
New dictionary converter
New UDF debug server
No more pyc files when using RunPython

Converters are accessed via the new options method when dealing with xlwings.Range objects or via the @xw.arg and @xw.ret decorators when using UDFs. As an introductory sample, let’s look at how to read and write Pandas DataFrames:

Range object:

>>> import xlwings as xw
>>> import pandas as pd
>>> wb = xw.Workbook()
>>> df = xw.Range('A1:D5').options(pd.DataFrame, header=2).value
>>> df
    a     b
    c  d  e
ix
10  1  2  3
20  4  5  6
30  7  8  9

# Writing back using the defaults:
>>> Range('A1').value = df

# Writing back and changing some of the options, e.g. getting rid of the index:
>>> Range('B7').options(index=False).value = df

UDFs:

This is the same sample as above (starting in Range('A13') on screenshot). If you wanted to return a DataFrame with the defaults, the @xw.ret decorator can be left away.

@xw.func
@xw.arg('x', pd.DataFrame, header=2)
@xw.ret(index=False)
def myfunction(x):
   # x is a DataFrame, do something with it
   return x

Enhancements¶

Dictionary (dict) converter:

>>> Range('A1:B2').options(dict).value
{'a': 1.0, 'b': 2.0}
>>> Range('A4:B5').options(dict, transpose=True).value
{'a': 1.0, 'b': 2.0}

transpose option: This works in both directions and finally allows us to e.g. write a list in column orientation to Excel (GH11):
```
Range('A1').options(transpose=True).value = [1, 2, 3]
```

dates option: This allows us to read Excel date-formatted cells in specific formats:

>>> import datetime as dt
>>> Range('A1').value
datetime.datetime(2015, 1, 13, 0, 0)
>>> Range('A1').options(dates=dt.date).value
datetime.date(2015, 1, 13)

empty option: This allows us to override the default behavior for empty cells:

>>> Range('A1:B1').value
[None, None]
>>> Range('A1:B1').options(empty='NA')
['NA', 'NA']

numbers option: This transforms all numbers into the indicated type.

>>> xw.Range('A1').value = 1
>>> type(xw.Range('A1').value)  # Excel stores all numbers interally as floats
float
>>> type(xw.Range('A1').options(numbers=int).value)
int

expand option: This works the same as the Range properties table, vertical and horizontal but is only evaluated when getting the values of a Range:

>>> import xlwings as xw
>>> wb = xw.Workbook()
>>> xw.Range('A1').value = [[1,2], [3,4]]
>>> rng1 = xw.Range('A1').table
>>> rng2 = xw.Range('A1').options(expand='table')
>>> rng1.value
[[1.0, 2.0], [3.0, 4.0]]
>>> rng2.value
[[1.0, 2.0], [3.0, 4.0]]
>>> xw.Range('A3').value = [5, 6]
>>> rng1.value
[[1.0, 2.0], [3.0, 4.0]]
>>> rng2.value
[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]

All these options work the same with decorators for UDFs, e.g. for transpose:

@xw.arg('x', transpose=True)
@xw.ret(transpose=True)
def myfunction(x):
    # x will be returned unchanged as transposed both when reading and writing
    return x

Note: These options (dates, empty, numbers) currently apply to the whole Range and can’t be selectively applied to e.g. only certain columns.

UDF debug server

The new UDF debug server allows you to easily debug UDFs: just set UDF_DEBUG_SERVER = True in the VBA Settings, at the top of the xlwings VBA module (make sure to update it to the latest version!). Then add the following lines to your Python source file and run it:
```
if __name__ == '__main__':
    xw.serve()
```
When you recalculate the Sheet, the code will stop at breakpoints or print any statements that you may have. For details, see: Debugging.
pyc files: The creation of pyc files has been disabled when using RunPython, leaving your directory in an uncluttered state when having the Python source file next to the Excel workbook (GH326).

API changes¶

UDF decorator changes (it is assumed that xlwings is imported as xw and numpy as np):

New Old

@xw.func @xw.xlfunc

@xw.arg @xw.xlarg

@xw.ret @xw.xlret

@xw.sub @xw.xlsub

Pay attention to the following subtle change:

New Old

@xw.arg("x", np.array) @xw.xlarg("x", "nparray")

Samples of how the new options method replaces the old Range keyword arguments:

New	Old
`Range('A1:A2').options(ndim=2)`	`Range('A1:A2', atleast_2d=True)`
`Range('A1:B2').options(np.array)`	`Range('A1:B2', asarray=True)`
`Range('A1').options(index=False, header=False).value = df`	`Range('A1', index=False, header=False).value = df`

Upon writing, Pandas Series are now shown by default with their name and index name, if they exist. This can be changed using the same options as for DataFrames (GH276):

import pandas as pd

# unchanged behaviour
Range('A1').value = pd.Series([1,2,3])

# Changed behaviour: This will print a header row in Excel
s = pd.Series([1,2,3], name='myseries', index=pd.Index([0,1,2], name='myindex'))
Range('A1').value = s

# Control this behaviour like so (as with DataFrames):
Range('A1').options(header=False, index=True).value = s

NumPy scalar values

Previously, NumPy scalar values were returned as np.atleast_1d. To keep the same behaviour, this now has to be set explicitly using ndim=1. Otherwise they’re returned as numpy scalar values.

New Old

Range('A1').options(np.array, ndim=1).value Range('A1', asarray=True).value

Bug Fixes¶

A few bugfixes were made: GH352, GH359.

v0.6.4 (January 6, 2016) ******************–

API changes¶

None

Enhancements¶

Quickstart: It’s now easier than ever to start a new xlwings project, simply use the command line client (GH306):

xlwings quickstart myproject will produce a folder with the following files, ready to be used (see Command Line Client (CLI)):
```
myproject
  |--myproject.xlsm
  |--myproject.py
```
New documentation about how to use xlwings with other languages like R and Julia, see r_and_julia.

Bug Fixes¶

[Win]: Importing UDFs with the add-in was throwing an error if the filename was including characters like spaces or dashes (GH331). To fix this, close Excel completely and run xlwings addin update.
[Win]: Workbook.caller() is now also accessible within functions that are decorated with @xlfunc. Previously, it was only available with functions that used the @xlsub decorator (GH316).
Writing a Pandas DataFrame failed in case the index was named the same as a column (GH334).

v0.6.3 (December 18, 2015) ******************—-

Bug Fixes¶

[Mac]: This fixes a bug introduced in v0.6.2: When using RunPython from VBA, errors were not shown in a pop-up window (GH330).

v0.6.2 (December 15, 2015) ******************—-

API changes¶

LOG_FILE: So far, the log file has been placed next to the Excel file per default (VBA settings). This has been changed as it was causing issues for files on SharePoint/OneDrive and Mac Excel 2016: The place where LOG_FILE = "" refers to depends on the OS and the Excel version.

Enhancements¶

[Mac]: This version adds support for the VBA module on Mac Excel 2016 (i.e. the RunPython command) and is now feature equivalent with Mac Excel 2011 (GH206).

Bug Fixes¶

[Win]: On certain systems, the xlwings dlls weren’t found (GH323).

v0.6.1 (December 4, 2015) ******************—

Bug Fixes¶

[Python 3]: The command line client has been fixed (GH319).
[Mac]: It now works correctly with psutil>=3.0.0 (GH315).

v0.6.0 (November 30, 2015)¶

API changes¶

None

Enhancements¶

User Defined Functions (UDFs) - currently Windows only

The ExcelPython project has been fully merged into xlwings. This means that on Windows, UDF’s are now supported via decorator syntax. A simple example:
```
from xlwings import xlfunc

@xlfunc
def double_sum(x, y):
    """Returns twice the sum of the two arguments"""
    return 2 * (x + y)
```
For array formulas with or without NumPy, see the docs: User Defined Functions (UDFs)
Command Line Client

The new xlwings command line client makes it easy to work with the xlwings template and the developer add-in (the add-in is currently Windows-only). E.g. to create a new Excel spreadsheet from the template, run:
```
xlwings template open
```
For all commands, see the docs: Command Line Client (CLI)
Other enhancements:
- New method: xlwings.Sheet.delete()
- New method: xlwings.Range.top()
- New method: xlwings.Range.left()

v0.5.0 (November 10, 2015)¶

API changes¶

None

Enhancements¶

This version adds support for Matplotlib! Matplotlib figures can be shown in Excel as pictures in just 2 lines of code:

Get a matplotlib figure object:

via PyPlot interface:

import matplotlib.pyplot as plt
fig = plt.figure()
plt.plot([1, 2, 3, 4, 5])

via object oriented interface:

from matplotlib.figure import Figure
fig = Figure(figsize=(8, 6))
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 4, 5])

via Pandas:

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
ax = df.plot(kind='bar')
fig = ax.get_figure()

Show it in Excel as picture:
```
plot = Plot(fig)
plot.show('Plot1')
```

See the full API: xlwings.Plot(). There’s also a new example available both on GitHub and as download on the homepage.

Other enhancements:

New xlwings.Shape() class
New xlwings.Picture() class
The PYTHONPATH in the VBA settings now accepts multiple directories, separated by ; (GH258)
An explicit exception is raised when Range is called with 0-based indices (GH106)

Bug Fixes¶

Sheet.add was not always acting on the correct workbook (GH287)
Iteration over a Range only worked the first time (GH272)
[Win]: Sometimes, an error was raised when Excel was not running (GH269)
[Win]: Non-default Python interpreters (as specified in the VBA settings under PYTHON_WIN) were not found if the path contained a space (GH257)

v0.4.1 (September 27, 2015)¶

API changes¶

None

Enhancements¶

This release makes it easier than ever to connect to Excel from Python! In addition to the existing ways, you can now connect to the active Workbook (on Windows across all instances) and if the Workbook is already open, it’s good enough to refer to it by name (instead of having to use the full path). Accordingly, this is how you make a connection to… (GH30 and GH226):

a new workbook: wb = Workbook()
the active workbook [New!]: wb = Workbook.active()
an unsaved workbook: wb = Workbook('Book1')
a saved (open) workbook by name (incl. xlsx etc.) [New!]: wb = Workbook('MyWorkbook.xlsx')
a saved (open or closed) workbook by path: wb = Workbook(r'C:\\path\\to\\file.xlsx')

Also, there are some new docs:

Bug Fixes¶

The Excel template was updated to the latest VBA code (GH234).
Connections to files that are saved on OneDrive/SharePoint are now working correctly (GH215).
Various issues with timezone-aware objects were fixed (GH195).
[Mac]: A certain range of integers were not written to Excel (GH227).

v0.4.0 (September 13, 2015)¶

API changes¶

None

Enhancements¶

The most important update with this release was made on Windows: The methodology used to make a connection to Workbooks has been completely replaced. This finally allows xlwings to reliably connect to multiple instances of Excel even if the Workbooks are opened from untrusted locations (network drives or files downloaded from the internet). This gets rid of the dreaded Filename is already open... error message that was sometimes shown in this context. It also allows the VBA hooks (RunPython) to work correctly if the very same file is opened in various instances of Excel.

Note that you will need to update the VBA module and that apart from pywin32 there is now a new dependency for the Windows version: comtypes. It should be installed automatically though when installing/upgrading xlwings with pip.

Other updates:

Added support to manipulate named Ranges (GH92):

>>> wb = Workbook()
>>> Range('A1').name = 'Name1'
>>> Range('A1').name
>>> 'Name1'
>>> del wb.names['Name1']

New Range properties (GH81):

Range now also accepts Sheet objects, the following 3 ways are hence all valid (GH92):

r = Range(1, 'A1')
r = Range('Sheet1', 'A1')
sheet1 = Sheet(1)
r = Range(sheet1, 'A1')

[Win]: Error pop-ups show now the full error message that can also be copied with Ctrl-C (GH221).

Bug Fixes¶

The VBA module was not accepting lower case drive letters (GH205).
Fixed an error when adding a new Sheet that was already existing (GH211).

v0.3.6 (July 14, 2015)¶

API changes¶

Application as attribute of a Workbook has been removed (wb is a Workbook object):

Correct Syntax (as before)	Removed
`Application(wkb=wb)`	`wb.application`

Enhancements¶

Excel 2016 for Mac Support (GH170)

Excel 2016 for Mac is finally supported (Python side). The VBA hooks (RunPython) are currently not yet supported. In more details:

This release allows Excel 2011 and Excel 2016 to be installed in parallel.
Workbook() will open the default Excel installation (usually Excel 2016).
The new keyword argument app_target allows to connect to a different Excel installation, e.g.:
```
Workbook(app_target='/Applications/Microsoft Office 2011/Microsoft Excel')
```
Note that app_target is only available on Mac. On Windows, if you want to change the version of Excel that xlwings talks to, go to Control Panel > Programs and Features and Repair the Office version that you want as default.
The RunPython calls in VBA are not yet available through Excel 2016 but Excel 2011 doesn’t get confused anymore if Excel 2016 is installed on the same system - make sure to update your VBA module!

Other enhancements

New method: xlwings.Application.calculate() (GH207)

Bug Fixes¶

[Win]: When using the OPTIMIZED_CONNECTION on Windows, Excel left an orphaned process running after closing (GH193).

Various improvements regarding unicode file path handling, including:

[Mac]: Excel 2011 for Mac now supports unicode characters in the filename when called via VBA’s RunPython (but not in the path - this is a limitation of Excel 2011 that will be resolved in Excel 2016) (GH154).
[Win]: Excel on Windows now handles unicode file paths correctly with untrusted documents. (GH154).

v0.3.5 (April 26, 2015)¶

API changes¶

Sheet.autofit() and Range.autofit(): The integer argument for the axis has been removed (GH186). Use string arguments rows or r for autofitting rows and columns or c for autofitting columns (as before).

Enhancements¶

New methods:

Example:

>>> rng = Range('A1').table
>>> rng.row, rng.column
(1, 1)
>>> rng.last_cell.row, rng.last_cell.column
(4, 5)

Bug Fixes¶

The unicode bug on Windows/Python3 has been fixed (GH161)

v0.3.4 (March 9, 2015)¶

Bug Fixes¶

The installation error on Windows has been fixed (GH160)

v0.3.3 (March 8, 2015)¶

API changes¶

None

Enhancements¶

New class Application with quit method and properties screen_updating und calculation (GH101, GH158, GH159). It can be conveniently accessed from within a Workbook (on Windows, Application is instance dependent). A few examples:

>>> from xlwings import Workbook, Calculation
>>> wb = Workbook()
>>> wb.application.screen_updating = False
>>> wb.application.calculation = Calculation.xlCalculationManual
>>> wb.application.quit()

New headless mode: The Excel application can be hidden either during Workbook instantiation or through the application object:
```
>>> wb = Workbook(app_visible=False)
>>> wb.application.visible
False
>>> wb.application.visible = True
```
Newly included Excel template which includes the xlwings VBA module and boilerplate code. This is currently accessible from an interactive interpreter session only:
```
>>> from xlwings import Workbook
>>> Workbook.open_template()
```

Bug Fixes¶

[Win]: datetime.date objects were causing an error (GH44).
Depending on how it was instantiated, Workbook was sometimes missing the fullname attribute (GH76).
Range.hyperlink was failing if the hyperlink had been set as formula (GH132).
A bug introduced in v0.3.0 caused frozen versions (eg. with cx_Freeze) to fail (GH133).
[Mac]: Sometimes, xlwings was causing an error when quitting the Python interpreter (GH136).

v0.3.2 (January 17, 2015)¶

API changes¶

None

Enhancements¶

None

Bug Fixes¶

The xlwings.Workbook.save() method has been fixed to show the expected behavior (GH138): Previously, calling save() without a path argument would always create a new file in the current working directory. This is now only happening if the file hasn’t been previously saved.

v0.3.1 (January 16, 2015)¶

API changes¶

None

Enhancements¶

New method xlwings.Workbook.save() (GH110).

New method xlwings.Workbook.set_mock_caller() (GH129). This makes calling files from both Excel and Python much easier:

import os
from xlwings import Workbook, Range

def my_macro():
    wb = Workbook.caller()
    Range('A1').value = 1

if __name__ == '__main__':
    # To run from Python, not needed when called from Excel.
    # Expects the Excel file next to this source file, adjust accordingly.
    path = os.path.abspath(os.path.join(os.path.dirname(__file__), 'myfile.xlsm'))
    Workbook.set_mock_caller(path)
    my_macro()

The simulation example on the homepage works now also on Mac.

Bug Fixes¶

[Win]: A long-standing bug that caused the Excel file to close and reopen under certain circumstances has been fixed (GH10): Depending on your security settings (Trust Center) and in connection with files downloaded from the internet or possibly in connection with some add-ins, Excel was either closing the file and reopening it or giving a “file already open” warning. This has now been fixed which means that the examples downloaded from the homepage should work right away after downloading and unzipping.

v0.3.0 (November 26, 2014)¶

API changes¶

To reference the calling Workbook when running code from VBA, you now have to use Workbook.caller(). This means that wb = Workbook() is now consistently creating a new Workbook, whether the code is called interactively or from VBA.

New Old

Workbook.caller() Workbook()

Enhancements¶

This version adds two exciting but still experimental features from ExcelPython (Windows only!):

Optimized connection: Set the OPTIMIZED_CONNECTION = True in the VBA settings. This will use a COM server that will keep the connection to Python alive between different calls and is therefore much more efficient. However, changes in the Python code are not being picked up until the pythonw.exe process is restarted by killing it manually in the Windows Task Manager. The suggested workflow is hence to set OPTIMIZED_CONNECTION = False for development and only set it to True for production - keep in mind though that this feature is still experimental!
User Defined Functions (UDFs): Using ExcelPython’s wrapper syntax in VBA, you can expose Python functions as UDFs, see User Defined Functions (UDFs) for details.

Note: ExcelPython’s developer add-in that autogenerates the VBA wrapper code by simply using Python decorators isn’t available through xlwings yet.

Further enhancements include:

New method xlwings.Range.resize() (GH90).
New method xlwings.Range.offset() (GH89).
New property xlwings.Range.shape (GH109).
New property xlwings.Range.size (GH109).
New property xlwings.Range.hyperlink and new method xlwings.Range.add_hyperlink() (GH104).
New property xlwings.Range.color (GH97).
The len built-in function can now be used on Range (GH109):
```
>>> len(Range('A1:B5'))
5
```

The Range object is now iterable (GH108):

for cell in Range('A1:B2'):
    if cell.value < 2:
        cell.color = (255, 0, 0)

[Mac]: The VBA module finds now automatically the default Python installation as per PATH variable on .bash_profile when PYTHON_MAC = "" (the default in the VBA settings) (GH95).
The VBA error pop-up can now be muted by setting SHOW_LOG = False in the VBA settings. To be used with care, but it can be useful on Mac, as the pop-up window is currently showing printed log messages even if no error occurred(GH94).

Bug Fixes¶

[Mac]: Environment variables from .bash_profile are now available when called from VBA, e.g. by using: os.environ['USERNAME'] (GH95)

v0.2.3 (October 17, 2014)¶

API changes¶

None

Enhancements¶

New method Sheet.add() (GH71):

>>> Sheet.add()  # Place at end with default name
>>> Sheet.add('NewSheet', before='Sheet1')  # Include name and position
>>> new_sheet = Sheet.add(after=3)
>>> new_sheet.index
4

New method Sheet.count():
```
>>> Sheet.count()
3
```

autofit() works now also on Sheet objects, not only on Range objects (GH66):

>>> Sheet(1).autofit()  # autofit columns and rows
>>> Sheet('Sheet1').autofit('c')  # autofit columns

New property number_format for Range objects (GH60):

>>> Range('A1').number_format
'General'
>>> Range('A1:C3').number_format = '0.00%'
>>> Range('A1:C3').number_format
'0.00%'

Works also with the Range properties table, vertical, horizontal:

>>> Range('A1').value = [1,2,3,4,5]
>>> Range('A1').table.number_format = '0.00%'

New method get_address for Range objects (GH7):

>>> Range((1,1)).get_address()
'$A$1'
>>> Range((1,1)).get_address(False, False)
'A1'
>>> Range('Sheet1', (1,1), (3,3)).get_address(True, False, include_sheetname=True)
'Sheet1!A$1:C$3'
>>> Range('Sheet1', (1,1), (3,3)).get_address(True, False, external=True)
'[Workbook1]Sheet1!A$1:C$3'

New method Sheet.all() returning a list with all Sheet objects:

>>> Sheet.all()
[<Sheet 'Sheet1' of Workbook 'Book1'>, <Sheet 'Sheet2' of Workbook 'Book1'>]
>>> [i.name.lower() for i in Sheet.all()]
['sheet1', 'sheet2']
>>> [i.autofit() for i in Sheet.all()]

Bug Fixes¶

xlwings works now also with NumPy < 1.7.0. Before, doing something like Range('A1').value = 'Foo' was causing a NotImplementedError: Not implemented for this type error when NumPy < 1.7.0 was installed (GH73).
[Win]: The VBA module caused an error on the 64bit version of Excel (GH72).
[Mac]: The error pop-up wasn’t shown on Python 3 (GH85).
[Mac]: Autofitting bigger Ranges, e.g. Range('A:D').autofit() was causing a time out (GH74).
[Mac]: Sometimes, calling xlwings from Python was causing Excel to show old errors as pop-up alert (GH70).

v0.2.2 (September 23, 2014)¶

API changes¶

The Workbook qualification changed: It now has to be specified as keyword argument. Assume we have instantiated two Workbooks like so: wb1 = Workbook() and wb2 = Workbook(). Sheet, Range and Chart classes will default to wb2 as it was instantiated last. To target wb1, use the new wkb keyword argument:

New Old

Range('A1', wkb=wb1).value wb1.range('A1').value

Chart('Chart1', wkb=wb1) wb1.chart('Chart1')

Alternatively, simply set the current Workbook before using the Sheet, Range or Chart classes:
```
wb1.set_current()
Range('A1').value
```

Through the introduction of the Sheet class (see Enhancements), a few methods moved from the Workbook to the Sheet class. Assume the current Workbook is: wb = Workbook():

New	Old
`Sheet('Sheet1').activate()`	`wb.activate('Sheet1')`
`Sheet('Sheet1').clear()`	`wb.clear('Sheet1')`
`Sheet('Sheet1').clear_contents()`	`wb.clear_contents('Sheet1')`
`Sheet.active().clear_contents()`	`wb.clear_contents()`

The syntax to add a new Chart has been slightly changed (it is a class method now):

New Old

Chart.add() Chart().add()

Enhancements¶

[Mac]: Python errors are now also shown in a Message Box. This makes the Mac version feature equivalent with the Windows version (GH57):
New Sheet class: The new class handles everything directly related to a Sheet. See the Python API section about Sheet for details (GH62). A few examples:
```
>>> Sheet(1).name
'Sheet1'
>>> Sheet('Sheet1').clear_contents()
>>> Sheet.active()
<Sheet 'Sheet1' of Workbook 'Book1'>
```

The Range class has a new method autofit() that autofits the width/height of either columns, rows or both (GH33).

Arguments:

axis : string or integer, default None
    - To autofit rows, use one of the following: 'rows' or 'r'
    - To autofit columns, use one of the following: 'columns' or 'c'
    - To autofit rows and columns, provide no arguments

Examples:

# Autofit column A
Range('A:A').autofit()
# Autofit row 1
Range('1:1').autofit()
# Autofit columns and rows, taking into account Range('A1:E4')
Range('A1:E4').autofit()
# AutoFit rows, taking into account Range('A1:E4')
Range('A1:E4').autofit('rows')

The Workbook class has the following additional methods: current() and set_current(). They determine the default Workbook for Sheet, Range or Chart. On Windows, in case there are various Excel instances, when creating new or opening existing Workbooks, they are being created in the same instance as the current Workbook.
```
>>> wb1 = Workbook()
>>> wb2 = Workbook()
>>> Workbook.current()
<Workbook 'Book2'>
>>> wb1.set_current()
>>> Workbook.current()
<Workbook 'Book1'>
```
If a Sheet, Range or Chart object is instantiated without an existing Workbook object, a user-friendly error message is raised (GH58).
New docs about Debugging and Data Structures Tutorial.

Bug Fixes¶

The atleast_2d keyword had no effect on Ranges consisting of a single cell and was raising an error when used in combination with the asarray keyword. Both have been fixed (GH53):
```
>>> Range('A1').value = 1
>>> Range('A1', atleast_2d=True).value
[[1.0]]
>>> Range('A1', atleast_2d=True, asarray=True).value
array([[1.]])
```
[Mac]: After creating two new unsaved Workbooks with Workbook(), any Sheet, Range or Chart object would always just access the latest one, even if the Workbook had been specified (GH63).
[Mac]: When xlwings was imported without ever instantiating a Workbook object, Excel would start upon quitting the Python interpreter (GH51).
[Mac]: When installing xlwings, it now requires psutil to be at least version 2.0.0 (GH48).

v0.2.1 (August 7, 2014)¶

API changes¶

None

Enhancements¶

All VBA user settings have been reorganized into a section at the top of the VBA xlwings module:

PYTHON_WIN = ""
PYTHON_MAC = GetMacDir("Home") & "/anaconda/bin"
PYTHON_FROZEN = ThisWorkbook.Path & "\build\exe.win32-2.7"
PYTHONPATH = ThisWorkbook.Path
LOG_FILE = ThisWorkbook.Path & "\xlwings_log.txt"

Calling Python from within Excel VBA is now also supported on Mac, i.e. Python functions can be called like this: RunPython("import bar; bar.foo()"). Running frozen executables (RunFrozenPython) isn’t available yet on Mac though.

Note that there is a slight difference in the way that this functionality behaves on Windows and Mac:

Windows: After calling the Macro (e.g. by pressing a button), Excel waits until Python is done. In case there’s an error in the Python code, a pop-up message is being shown with the traceback.
Mac: After calling the Macro, the call returns instantly but Excel’s Status Bar turns into “Running…” during the duration of the Python call. Python errors are currently not shown as a pop-up, but need to be checked in the log file. I.e. if the Status Bar returns to its default (“Ready”) but nothing has happened, check out the log file for the Python traceback.

Bug Fixes¶

None

Special thanks go to Georgi Petrov for helping with this release.

v0.2.0 (July 29, 2014)¶

API changes¶

None

Enhancements¶

Cross-platform: xlwings is now additionally supporting Microsoft Excel for Mac. The only functionality that is not yet available is the possibility to call the Python code from within Excel via VBA macros.
The clear and clear_contents methods of the Workbook object now default to the active sheet (GH5):
```
wb = Workbook()
wb.clear_contents()  # Clears contents of the entire active sheet
```

Bug Fixes¶

DataFrames with MultiHeaders were sometimes getting truncated (GH41).

v0.1.1 (June 27, 2014)¶

API Changes¶

If asarray=True, NumPy arrays are now always at least 1d arrays, even in the case of a single cell (GH14):
```
>>> Range('A1', asarray=True).value
array([34.])
```

Similar to NumPy’s logic, 1d Ranges in Excel, i.e. rows or columns, are now being read in as flat lists or 1d arrays. If you want the same behavior as before, you can use the atleast_2d keyword (GH13).

Note

The table property is also delivering a 1d array/list, if the table Range is really a column or row.

>>> Range('A1').vertical.value
[1.0, 2.0, 3.0, 4.0]
>>> Range('A1', atleast_2d=True).vertical.value
[[1.0], [2.0], [3.0], [4.0]]
>>> Range('C1').horizontal.value
[1.0, 2.0, 3.0, 4.0]
>>> Range('C1', atleast_2d=True).horizontal.value
[[1.0, 2.0, 3.0, 4.0]]
>>> Range('A1', asarray=True).table.value
array([ 1.,  2.,  3.,  4.])
>>> Range('A1', asarray=True, atleast_2d=True).table.value
array([[ 1.],
       [ 2.],
       [ 3.],
       [ 4.]])

The single file approach has been dropped. xlwings is now a traditional Python package.

Enhancements¶

xlwings is now officially suppported on Python 2.6-2.7 and 3.1-3.4

Support for Pandas Series has been added (GH24):

>>> import numpy as np
>>> import pandas as pd
>>> from xlwings import Workbook, Range
>>> wb = Workbook()
>>> s = pd.Series([1.1, 3.3, 5., np.nan, 6., 8.])
>>> s
0    1.1
1    3.3
2    5.0
3    NaN
4    6.0
5    8.0
dtype: float64
>>> Range('A1').value = s
>>> Range('D1', index=False).value = s

Excel constants have been added under their original Excel name, but categorized under their enum (GH18), e.g.:

# Extra long version
import xlwings as xl
xl.constants.ChartType.xlArea

# Long version
from xlwings import constants
constants.ChartType.xlArea

# Short version
from xlwings import ChartType
ChartType.xlArea

Slightly enhanced Chart support to control the ChartType (GH1):

>>> from xlwings import Workbook, Range, Chart, ChartType
>>> wb = Workbook()
>>> Range('A1').value = [['one', 'two'],[10, 20]]
>>> my_chart = Chart().add(chart_type=ChartType.xlLine,
                           name='My Chart',
                           source_data=Range('A1').table)

alternatively, the properties can also be set like this:

>>> my_chart = Chart().add()  # Existing Charts: my_chart = Chart('My Chart')
>>> my_chart.name = 'My Chart'
>>> my_chart.chart_type = ChartType.xlLine
>>> my_chart.set_source_data(Range('A1').table)

pytz is no longer a dependency as datetime object are now being read in from Excel as time-zone naive (Excel doesn’t know timezones). Before, datetime objects got the UTC timezone attached.
The Workbook class has the following additional methods: close()
The Range class has the following additional methods: is_cell(), is_column(), is_row(), is_table()

Bug Fixes¶

Writing None or np.nan to Excel works now (GH16 & GH15).
The import error on Python 3 has been fixed (GH26).
Python 3 now handles Pandas DataFrames with MultiIndex headers correctly (GH39).
Sometimes, a Pandas DataFrame was not handling nan correctly in Excel or numbers were being truncated (GH31) & (GH35).
Installation is now putting all files in the correct place (GH20).

v0.1.0 (March 19, 2014)¶

Initial release of xlwings.

License¶

xlwings (Open Source) is licensed under an open-source BSD 3-clause license. xlwings includes all files in the xlwings package except the pro folder, i.e. the xlwings.pro subpackage.
xlwings PRO, i.e. everything in the xlwings.pro subpackage, is licensed under a commercial license and must be used with a valid license key and a paid subscription as advertised on https://www.xlwings.org/pricing.

Both licenses as well as the licenses of the open source dependencies follow below.

xlwings Open Source License¶

xlwings is distributed under a BSD 3-clause license.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

xlwings PRO End User License Agreement¶

Last updated: June 4, 2021

This End User License Agreement together with the Order Form (the “Agreement”) is between Zoomer Analytics GmbH, a Zurich/Switzerland corporation (“Zoomer Analytics”), and the Customer signing this Agreement (“Customer”). This Agreement shall be effective as of the Subscription Term Start Date as defined in the applicable Order Form (the “Effective Date”).

Please read this Agreement carefully before using the Software. The parties agree to be bound by the following terms and conditions in connection with the subscription to and use of Zoomer Analytics Software as defined herein. If the Customer does not accept the terms of this Agreement, then the Customer must not Access, install or use the Software.

DEFINITIONS

1.  Access or Accessing shall mean accessing, installing, using, or viewing the Software or any other proprietary information owned by Zoomer Analytics.
2.  Content Updates means content used by the Software which is updated from time to time.
3.  Documentation means the documentation for the Software generally supplied by Zoomer Analytics to assist its customers in their use of the Software, including developer guides, manuals, and the functionality specifications.
4.  End-User means any person or entity to which Licensee provides a Licensee Product with no right to distribute the Software.
5.  Licensee means any person or entity to whom the License is granted under these Terms.
6.  Licensee Product means any proprietary software product owned or otherwise controlled by Licensee, in which the Software has been incorporated, and which Licensee may use for its internal purposes or make available to End-Users.
7.  Order Form means Zoomer Analytics’ order form or other ordering document signed or referenced by Customer or its authorized reseller which identifies the specific Software ordered, the Product Limitations, and the price agreed upon by the parties.
8.  Product Limitations means the capacity indicated on the Order Form, including number of Licensees.
9.  Software shall mean the xlwings PRO software licensed to Licensee under these Terms. Unless otherwise noted, the Software and Documentation are referred to collectively herein as “Software”.
10. Subscription Term means the period in which Licensee is authorized to utilize the Software. The Subscription Term shall be listed on the applicable Order Form and shall commence on the Effective Date.

LICENSE

2.1.  Developer License. Under the Developer License Zoomer Analytics grants to Licensee a non-exclusive, non-transferrable, non-sublicensable otherwise than to the Developer, irrevocable subject to compliance with the terms hereof, right to use, test, examine, reproduce, modify, create works based upon (“Derivative Works”), and distribute or otherwise make available, the Software and Derivative Works. The Developer License is a per-seat license meaning that where Licensee enables two or more of its Developers to make use of the rights granted hereby it should purchase the Developer License for each one of them.
2.2.  Evaluation License. If Customer’s license is for a trial or evaluation only, then the Subscription Term shall be thirty days, or the trial or evaluation term specified on the Order Form. Customer may not utilize the same software for more than one trial or evaluation term in any twelve-month period, unless otherwise agreed to by Zoomer Analytics. Zoomer Analytics may revoke Customer’s evaluation or trial license at any time and for any reason. Sections 4 (Limited Warranty) and 8.1 (Indemnification) shall not be applicable to any evaluation or trial license.
2.3.  Use by Affiliates. Subject to the Product Limitations, Customer may make the Software available to its Affiliates under these terms, provided that Customer is liable for any breach of this Agreement by any of its Affiliates. “Affiliate(s)” means any entity now existing that is directly or indirectly controlled by Customer. For purposes of this definition “control” means the direct possession of a majority of the outstanding voting securities of an entity.
2.4.  Delivery and Copies. Delivery shall be deemed to have been made upon Zoomer Analytics providing instructions to download or activate the Software, as applicable. Notwithstanding anything to the contrary herein, Customer may make a reasonable number of copies of the Software for the sole purpose of backing-up and archiving the Software. Each copy of the Software is subject to this Agreement and must contain the same titles, trademarks, and copyright notices as the original.
2.5.  Restrictions. Except for the Developer License granted to the Customer in Section 2.1, Zoomer Analytics does not grant to the Customer any other licenses to Software or any other proprietary information owned by Zoomer Analytics. Notwithstanding any other provision of this Agreement, the Customer shall not:
(a)   Use Software in any manner to provide service bureau, time-sharing or other computer services to third parties.
(b)   Use Software, or allow the transfer, transmission, export, or re-export of Software or portion thereof in violation of any export control laws or regulations administered by any government agency.
(c)   Remove, modify or obscure any copyright, trademark, legal notices, or other proprietary notations in Software.
(d)   Distribute Software or its modifications as part of any application that can be described as a software competitive with the Software.
(e)   Allow Access to, disclose, transfer, or distribute the Software to any party other than to a Licensee or End-User.
(f)   Rent, sublicense, lease, or sell the Software, or make any attempt to do so.
(g)   Use the Software to perform any illegal, dishonest, or fraudulent act, to damage or injure a third party, or to infringe the intellectual property or privacy rights of any person or entity.
(h)   Use the Software in any manner that could be detrimental to Zoomer Analytics.

The Customer represents and warrants to Zoomer Analytics that the Customer will comply at all times with the terms of this Agreement and all applicable laws and regulations in using the Software. If the Licensee or any End-Users uses the Software in an unlawful manner, for unlawful purposes or in any way that does not comply with this Agreement or all applicable laws and regulations, then the Software License may be revoked by Zoomer Analytics and, in such event, the Licensee and its End-Users will immediately cease any use of the Software.
6.  Ownership of Software. Zoomer Analytics retains all right, title, and interest in and to the Documentation, Software, Content Updates and in all copies, modifications and derivative works thereto including, without limitation, all rights to patent, copyright, trade secret, trademark, and other proprietary or intellectual property rights.
7.  Customer Systems. Customer represents and warrants that it has the appropriate authorizations from the owner of the hardware and other involved systems on which it deploys the Software.
8.  Open Source. The open source libraries in the Software are included in compliance with pertaining licenses and subject to any such disclaimers and limitations on liability as set forth in the open source library licenses. Zoomer Analytics expressly rejects and disclaims any and all liability for their content, consequences, or fitness for Licensee’s purposes. The full list of open source libraries included in the Software can be found at https://docs.xlwings.org/en/stable/license.html#open-source-licenses.

   FEES AND PAYMENT TERMS

Customer agrees to pay the fees, charges, and other amounts in accordance with the Order Form from the date of invoice. All fees are nonrefundable, unless otherwise stated herein. If Customer is purchasing the Software through a Zoomer Analytics authorized reseller, then the fees shall be as set forth between Customer and reseller and the applicable fees shall be paid directly to the reseller. Customer shall be responsible for all taxes levied on any transaction under this Agreement, including, without limitation, all federal, state, and local sales taxes, levies and assessments, and local withholding taxes in Customer’s jurisdiction, if any, excluding, however, any taxes based on Zoomer Analytics’ income. In the event Customer is required to withhold taxes from its payment or withholding taxes are subsequently required to be paid to a local taxing jurisdiction, Customer is obligated to pay such tax, and Zoomer Analytics as applicable, will receive the full payment, net of any such taxes, as agreed in the applicable Order Form and Customer shall provide to Zoomer Analytics written evidence that such withholding tax payment was made. Note that for Swiss-based Customers, VAT will be added to the total amount of fees and included in the invoice.



   LIMITED WARRANTY

1.  Software Warranty. Zoomer Analytics warrants that during the Subscription Term the Software will conform, in all material respects, with the applicable Documentation. Zoomer Analytics makes no warranty regarding third party features or services. For a breach of the above warranty, Zoomer Analytics will, at no additional cost to Customer, use commercially reasonable efforts to provide remedial services necessary to enable the Software to conform to the warranty. If Zoomer Analytics is unable to restore such functionality, Customer shall be entitled to terminate the applicable Order Form and receive a pro rata refund of the fees paid. Customer will provide Zoomer Analytics with a reasonable opportunity to remedy any breach and reasonable assistance in remedying any defects. The remedies set out in this subsection are Customer’s sole remedies for breach of the above warranty.
2.  Disclaimer. ZOOMER ANALYTICS DOES NOT REPRESENT THAT THE SOFTWARE WILL BE UNINTERRUPTED, ERROR-FREE, OR WILL MEET CUSTOMER’S REQUIREMENTS. EXCEPT FOR THE WARRANTY ABOVE, ZOOMER ANALYTICS MAKES NO OTHER WARRANTIES OR REPRESENTATIONS, EXPRESS OR IMPLIED, INCLUDING, WITHOUT LIMITATION, THOSE OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.

   LIMITATION OF LIABILITY

1.  Limitation on Indirect Liability. NEITHER PARTY WILL BE LIABLE UNDER THIS AGREEMENT FOR LOST REVENUES OR INDIRECT, SPECIAL, INCIDENTAL, CONSEQUENTIAL, EXEMPLARY, OR PUNITIVE DAMAGES, EVEN IF THE PARTY KNEW OR SHOULD HAVE KNOWN THAT SUCH DAMAGES WERE POSSIBLE.
2.  Limitation on Amount of Liability. NEITHER PARTY MAY BE HELD LIABLE UNDER THIS AGREEMENT FOR MORE THAN THE AMOUNT PAID OR PAYABLE BY CUSTOMER TO ZOOMER ANALYTICS HEREUNDER DURING THE TWELVE MONTHS PRIOR TO THE EVENT GIVING RISE TO LIABILITY.
3.  Exceptions to Limitations. The limitations of liability in Section 5.2 apply to the fullest extent permitted by applicable law, except that there is no limitation on loss, claims, or damages directly arising out of violations of: (i) a party’s intellectual property rights by the other party; (ii) use of the Software in excess of the Product Limitations; or (iii) a party’s indemnification obligations.


   CONFIDENTIALITY

1.  Confidential Information. During the term of this Agreement, each party will regard any information provided to it by the other party and designated in writing as proprietary or confidential as confidential (“Confidential Information”). Confidential Information shall also include information which a reasonable person familiar with the disclosing party’s business and the industry in which it operates would know is of a confidential or proprietary nature. A party will not disclose the other party’s Confidential Information to any third party without the prior written consent of the other party, nor make use of any of the other party’s Confidential Information except in its performance under this Agreement. Each party accepts responsibility for the actions of its agents or employees and shall protect the other party’s Confidential Information in the same manner as it protects its own Confidential Information of a similar nature, but in no event with less than reasonable care. The parties expressly agree that the terms and pricing of this Agreement are Confidential Information. A receiving party shall promptly notify the disclosing party upon becoming aware of a breach or threatened breach hereunder and shall cooperate with any reasonable request of the disclosing party in enforcing its rights.
2.  Exclusions. Information will not be deemed Confidential Information if such information: (i) is known prior to receipt from the disclosing party, without any obligation of confidentiality; (ii) becomes known to the receiving party directly or indirectly from a source other than one having an obligation of confidentiality to the disclosing party; (iii) becomes publicly known or otherwise publicly available, except through a breach of this Agreement; or (iv) is independently developed by the receiving party without use of the disclosing party’s Confidential Information. The receiving party may disclose Confidential Information pursuant to the requirements of applicable law, stock exchange rule, legal process or government regulation, provided that, unless prohibited from doing so by law enforcement or court order, the receiving party gives the disclosing party reasonable prior written notice, and such disclosure is otherwise limited to the required disclosure.

   TERM & TERMINATION

The Subscription Term will not automatically renew. Instead, Zoomer Analytics will reach out approximately 30 days before the end of the Subscription Term to see if Customer wants to renew. In case of a renewal, a new Agreement will be extended to the Customer.

This Agreement or an Order Form may be terminated: (i) by either party if the other party is adjudicated as bankrupt, or if a petition in bankruptcy is filed against the other party and such petition is not discharged within sixty days of such filing; or (ii) by either party if the other party materially breaches this Agreement or the Order Form and fails to cure such breach to such party’s reasonable satisfaction within thirty days following receipt of written notice thereof. Customer’s license to use the Software shall also terminate upon the expiration of the applicable Subscription Term. Upon any termination of this Agreement or an Order Form by Zoomer Analytics, all applicable licenses are revoked and Customer shall immediately cease use of the applicable Software. Termination of this Agreement or a license granted hereunder shall not relieve Customer of its obligation to pay all fees that have accrued, have been paid, or have become payable by Customer hereunder. All provisions of this Agreement which by their nature are intended to survive the termination of this Agreement shall survive such termination.

   INDEMNIFICATION

1.  By Zoomer Analytics. Zoomer Analytics will indemnify, defend, and hold harmless Customer from and against all liabilities, damages, and costs (including settlement costs and reasonable attorneys’ fees) arising out of a third-party claim that the Software infringes or misappropriates any intellectual property right of such third party. Notwithstanding the foregoing, in no event shall Zoomer Analytics have any obligations or liability under this Section arising from: (i) use of any Software in a manner not anticipated by this Agreement or in combination with materials not furnished by Zoomer Analytics; or (ii) any content, information or data provided by Customer or other third parties. If the Software is or is likely to become subject to a claim of infringement or misappropriation, then Zoomer Analytics will, at its sole option and expense, either: (i) obtain for the Customer the right to continue using the Software; (ii) replace or modify the Software to be non-infringing and substantially equivalent to the infringing Software; or (iii) if options (i) and (ii) above cannot be accomplished despite the reasonable efforts of Zoomer Analytics, then Zoomer Analytics may terminate Customer’s rights to use the infringing Software and will refund pro-rata any prepaid fees for the infringing portion of the Software. THE RIGHTS GRANTED TO CUSTOMER UNDER THIS SECTION 8.1 SHALL BE CUSTOMER’S SOLE AND EXCLUSIVE REMEDY FOR ANY ALLEGED INFRINGEMENT BY THE SOFTWARE OF ANY PATENT, COPYRIGHT, OR OTHER PROPRIETARY RIGHT.
2.  By Customer. Customer will indemnify, defend, and hold harmless Zoomer Analytics from and against all liabilities, damages, and costs (including settlement costs and reasonable attorneys’ fees) arising out of a third party claim regarding Customer’s: (i) use of the Software in violation of applicable law; or (ii) breach of the representation and warranty made in Section 2.7 of this Agreement.

   TECHNICAL SUPPORT

1.  Support and Maintenance Services. The support and maintenance shall be set forth on the applicable Order Form.

  GENERAL PROVISIONS

1. Miscellaneous. (a) This Agreement shall be construed in accordance with and governed for all purposes by the laws of Zurich/Switzerland for all questions and controversies arising out of this Agreement and waives all objections to venue and personal jurisdiction in these forums for such disputes; (b) this Agreement, along with the accompanying Order Form(s) constitute the entire agreement and understanding of the parties hereto with respect to the subject matter hereof and supersedes all prior agreements and undertakings, both written and oral; (c) this Agreement and each Order Form may not be modified except by a writing signed by each of the parties; (d) in case any one or more of the provisions contained in this Agreement shall for any reason be held to be invalid, illegal, or unenforceable in any respect, such invalidity, illegality, or unenforceability shall not affect any other provisions of this Agreement, but rather this Agreement shall be construed as if such invalid, illegal, or other unenforceable provision had never been contained herein; (e) Customer shall not assign its rights or obligations hereunder without Zoomer Analytics’ advance written consent; (f) subject to the foregoing subsection (e), this Agreement shall be binding upon and shall inure to the benefit of the parties hereto and their successors and permitted assigns; (g) no waiver of any right or remedy hereunder with respect to any occurrence or event on one occasion shall be deemed a waiver of such right or remedy with respect to such occurrence or event on any other occasion; (h) nothing in this Agreement, express or implied, is intended to or shall confer upon any other person any right, benefit, or remedy of any nature whatsoever under or by reason of this Agreement, including but not limited to any of Customer’s own clients, customers, or employees; (i) the headings to the sections of this Agreement are for ease of reference only and shall not affect the interpretation or construction of this Agreement; and (j) in the event of a conflict between the terms of this Agreement and the terms of an Order Form, the terms in the Order Form shall take precedence.
2. Data Privacy. Customer represents and warrants that Customer has obtained all necessary rights to permit Zoomer Analytics to process Customer Data from and about Customer.
3. Relationship of the Parties. Zoomer Analytics and Customer are independent contractors, and nothing in this Agreement shall be construed as making them partners or creating the relationships of principal and agent between them, for any purpose whatsoever. Neither party shall make any contracts, warranties or representations or assume or create any obligations, express or implied, in the other party’s name or on its behalf.
4. Force Majeure. Neither party will be liable for inadequate performance to the extent caused by a condition (for example, natural disaster, act of war or terrorism, riot, labor condition, or internet disturbance) that was beyond the party’s reasonable control.
5. No Reliance. Customer represents that it has not relied on the availability of any future version of the Software or any future product or service in executing this Agreement or purchasing any Software hereunder.
6. Publicity. Customer acknowledges that Zoomer Analytics may use Customer’s name and logo for the purpose of identifying Customer as a customer of Zoomer Analytics products and/or services. Zoomer Analytics will cease using the customer’s name and logo upon written request.

Open Source Licenses¶

xlwings is built on top of a few open source dependencies. Their licenses are listed here:

pywin32 (Windows only)¶

com subpackage

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither names of Greg Stein, Mark Hammond nor the name of contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ‘’AS IS’’ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

win32 subpackage

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither name of Mark Hammond nor the name of contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ‘’AS IS’’ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Pythonwin subpackage

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither name of Mark Hammond nor the name of contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ‘’AS IS’’ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

psutil (macOS only)¶

BSD 3-Clause License

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither the name of the psutil authors nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Appscript (macOS only)¶

Appscript is released into the public domain, except for the following code:

portions of ae.c, which are Copyright (C) the original authors:

Original code taken from _AEmodule.c, _CFmodule.c, _Launchmodule.c

Copyright (C) 2001-2008 Python Software Foundation.

License: https://docs.python.org/3/license.html.
SendThreadSafe.h/SendThreadSafe.m, which are modified versions of Apple

code (https://developer.apple.com/library/archive/samplecode/AESendThreadSafe):

Written by: DTS

Copyright: Copyright (c) 2007 Apple Inc. All Rights Reserved.

Disclaimer: IMPORTANT: This Apple software is supplied to you by Apple Inc.

(“Apple”) in consideration of your agreement to the following terms, and your use, installation, modification or redistribution of this Apple software constitutes acceptance of these terms. If you do not agree with these terms, please do not use, install, modify or redistribute this Apple software. In consideration of your agreement to abide by the following terms, and subject to these terms, Apple grants you a personal, non-exclusive license, under Apple’s copyrights in this original Apple software (the “Apple Software”), to use, reproduce, modify and redistribute the Apple Software, with or without modifications, in source and/or binary forms; provided that if you redistribute the Apple Software in its entirety and without modifications, you must retain this notice and the following text and disclaimers in all such redistributions of the Apple Software. Neither the name, trademarks, service marks or logos of Apple Inc. may be used to endorse or promote products derived from the Apple Software without specific prior written permission from Apple. Except as expressly stated in this notice, no other rights or licenses, express or implied, are granted by Apple herein, including but not limited to any patent rights that may be infringed by your derivative works or by other works in which the Apple Software may be incorporated. The Apple Software is provided by Apple on an “AS IS” basis.

APPLE MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE APPLE SOFTWARE OR ITS USE AND OPERATION ALONE OR IN COMBINATION WITH YOUR PRODUCTS. IN NO EVENT SHALL APPLE BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) ARISING IN ANY WAY OUT OF THE USE, REPRODUCTION, MODIFICATION AND/OR DISTRIBUTION OF THE APPLE SOFTWARE, HOWEVER CAUSED AND WHETHER UNDER THEORY OF CONTRACT, TORT (INCLUDING NEGLIGENCE), STRICT LIABILITY OR OTHERWISE, EVEN IF APPLE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

cryptography¶

This software is made available under the terms of either of the licenses found in LICENSE.APACHE or LICENSE.BSD. Contributions to cryptography are made under the terms of both these licenses.

The code used in the OpenSSL locking callback and OS random engine is derived from CPython, and is licensed under the terms of the PSF License Agreement.

Mistune¶

BSD 3-Clause License

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither the name of the creator nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

VBA-Dictionary¶

The MIT License (MIT)

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Python API¶

Top-level functions¶

xlwings.view(obj, sheet=None, table=True, chunksize=5000)¶

Opens a new workbook and displays an object on its first sheet by default. If you provide a sheet object, it will clear the sheet before displaying the object on the existing sheet.

Note

Only use this in an interactive context like e.g. a Jupyter notebook! Don’t use this in a script as it depends on the active book.

Parameters:

obj (any type with built-in converter) – the object to display, e.g. numbers, strings, lists, numpy arrays, pandas dataframes
sheet (Sheet, default None) – Sheet object. If none provided, the first sheet of a new workbook is used.
table (bool, default True) – If your object is a pandas DataFrame, by default it is formatted as an Excel Table
chunksize (int, default 5000) – Chunks the loading of big arrays.

Examples

>>> import xlwings as xw
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame(np.random.rand(10, 4), columns=['a', 'b', 'c', 'd'])
>>> xw.view(df)

Object model¶

Apps¶

class xlwings.main.Apps(impl)¶

A collection of all app objects:

>>> import xlwings as xw
>>> xw.apps
Apps([<Excel App 1668>, <Excel App 1644>])

active¶: Returns the active app.

New in version 0.9.0.

add()¶: Creates a new App. The new App becomes the active one. Returns an App object.

count¶: Returns the number of apps.

New in version 0.9.0.

keys()¶: Provides the PIDs of the Excel instances that act as keys in the Apps collection.

New in version 0.13.0.

App¶

class xlwings.App(visible=None, spec=None, add_book=True, impl=None)¶

An app corresponds to an Excel instance. New Excel instances can be fired up like so:

>>> import xlwings as xw
>>> app1 = xw.App()
>>> app2 = xw.App()

An app object is a member of the apps collection:

>>> xw.apps
Apps([<Excel App 1668>, <Excel App 1644>])
>>> xw.apps[1668]  # get the available PIDs via xw.apps.keys()
<Excel App 1668>
>>> xw.apps.active
<Excel App 1668>

Parameters:

visible (bool, default None) – Returns or sets a boolean value that determines whether the app is visible. The default leaves the state unchanged or sets visible=True if the object doesn’t exist yet.
spec (str, default None) –
Mac-only, use the full path to the Excel application, e.g. /Applications/Microsoft Office 2011/Microsoft Excel or /Applications/Microsoft Excel

On Windows, if you want to change the version of Excel that xlwings talks to, go to Control Panel > Programs and Features and Repair the Office version that you want as default.

Note

On Mac, while xlwings allows you to run multiple instances of Excel, it’s a feature that is not officially supported by Excel for Mac: Unlike on Windows, Excel will not ask you to open a read-only version of a file if it is already open in another instance. This means that you need to watch out yourself so that the same file is not being overwritten from different instances.

activate(steal_focus=False)¶

Activates the Excel app.

Parameters:	steal_focus (bool, default False) – If True, make frontmost application and hand over focus from Python to Excel.

New in version 0.9.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

books¶: A collection of all Book objects that are currently open.

New in version 0.9.0.

calculate()¶: Calculates all open books.

New in version 0.3.6.

calculation¶

Returns or sets a calculation value that represents the calculation mode. Modes: 'manual', 'automatic', 'semiautomatic'

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> wb.app.calculation = 'manual'

Changed in version 0.9.0.

display_alerts¶: The default value is True. Set this property to False to suppress prompts and alert messages while code is running; when a message requires a response, Excel chooses the default response.

New in version 0.9.0.

hwnd¶: Returns the Window handle (Windows-only).

New in version 0.9.0.

kill()¶: Forces the Excel app to quit by killing its process.

New in version 0.9.0.

macro(name)¶

Runs a Sub or Function in Excel VBA that are not part of a specific workbook but e.g. are part of an add-in.

Parameters:	name (Name of Sub or Function with or without module name, e.g. `'Module1.MyMacro'` or `'MyMacro'`) –

Examples

This VBA function:

Function MySum(x, y)
    MySum = x + y
End Function

can be accessed like this:

>>> import xlwings as xw
>>> app = xw.App()
>>> my_sum = app.macro('MySum')
>>> my_sum(1, 2)
3

Books¶

class xlwings.main.Books(impl)¶

A collection of all book objects:

>>> import xlwings as xw
>>> xw.books  # active app
Books([<Book [Book1]>, <Book [Book2]>])
>>> xw.apps[10559].books  # specific app, get the PIDs via xw.apps.keys()
Books([<Book [Book1]>, <Book [Book2]>])

New in version 0.9.0.

active¶: Returns the active Book.

add()¶: Creates a new Book. The new Book becomes the active Book. Returns a Book object.

open(fullname, update_links=None, read_only=None, format=None, password=None, write_res_password=None, ignore_read_only_recommended=None, origin=None, delimiter=None, editable=None, notify=None, converter=None, add_to_mru=None, local=None, corrupt_load=None)¶

Opens a Book if it is not open yet and returns it. If it is already open, it doesn’t raise an exception but simply returns the Book object.

Parameters:	fullname (str or path-like object) – filename or fully qualified filename, e.g. `r'C:\path\to\file.xlsx'` or `'file.xlsm'`. Without a full path, it looks for the file in the current working directory. Parameters (Other) – see: `xlwings.Book()`
Returns:	Book
Return type:	Book that has been opened.

Book¶

class xlwings.Book(fullname=None, update_links=None, read_only=None, format=None, password=None, write_res_password=None, ignore_read_only_recommended=None, origin=None, delimiter=None, editable=None, notify=None, converter=None, add_to_mru=None, local=None, corrupt_load=None, impl=None)¶

A book object is a member of the books collection:

>>> import xlwings as xw
>>> xw.books[0]
<Book [Book1]>

The easiest way to connect to a book is offered by xw.Book: it looks for the book in all app instances and returns an error, should the same book be open in multiple instances. To connect to a book in the active app instance, use xw.books and to refer to a specific app, use:

>>> app = xw.App()  # or something like xw.apps[10559] for existing apps, get the PIDs via xw.apps.keys()
>>> app.books['Book1']

	xw.Book	xw.books
New book	`xw.Book()`	`xw.books.add()`
Unsaved book	`xw.Book('Book1')`	`xw.books['Book1']`
Book by (full)name	`xw.Book(r'C:/path/to/file.xlsx')`	`xw.books.open(r'C:/path/to/file.xlsx')`

Parameters:

fullname (str or path-like object, default None) – Full path or name (incl. xlsx, xlsm etc.) of existing workbook or name of an unsaved workbook. Without a full path, it looks for the file in the current working directory.
update_links (bool, default None) – If this argument is omitted, the user is prompted to specify how links will be updated
read_only (bool, default False) – True to open workbook in read-only mode
format (str) – If opening a text file, this specifies the delimiter character
password (str) – Password to open a protected workbook
write_res_password (str) – Password to write to a write-reserved workbook
ignore_read_only_recommended (bool, default False) – Set to True to mute the read-only recommended message
origin (int) – For text files only. Specifies where it originated. Use XlPlatform constants.
delimiter (str) – If format argument is 6, this specifies the delimiter.
editable (bool, default False) – This option is only for legacy Microsoft Excel 4.0 addins.
notify (bool, default False) – Notify the user when a file becomes available If the file cannot be opened in read/write mode.
converter (int) – The index of the first file converter to try when opening the file.
add_to_mru (bool, default False) – Add this workbook to the list of recently added workbooks.
local (bool, default False) – If True, saves files against the language of Excel, otherwise against the language of VBA. Not supported on macOS.
corrupt_load (int, default xlNormalLoad) – Can be one of xlNormalLoad, xlRepairFile or xlExtractData. Not supported on macOS.

activate(steal_focus=False)¶

Activates the book.

Parameters:	steal_focus (bool, default False) – If True, make frontmost window and hand over focus from Python to Excel.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

app¶: Returns an app object that represents the creator of the book.

New in version 0.9.0.

classmethod caller()¶

References the calling book when the Python function is called from Excel via RunPython. Pack it into the function being called from Excel, e.g.:

import xlwings as xw

 def my_macro():
    wb = xw.Book.caller()
    wb.sheets[0].range('A1').value = 1

To be able to easily invoke such code from Python for debugging, use xw.Book.set_mock_caller().

New in version 0.3.0.

close()¶: Closes the book without saving it.

New in version 0.1.1.

fullname¶: Returns the name of the object, including its path on disk, as a string. Read-only String.

macro(name)¶

Runs a Sub or Function in Excel VBA.

Parameters:	name (Name of Sub or Function with or without module name, e.g. `'Module1.MyMacro'` or `'MyMacro'`) –

Examples

This VBA function:

Function MySum(x, y)
    MySum = x + y
End Function

can be accessed like this:

>>> import xlwings as xw
>>> wb = xw.books.active
>>> my_sum = wb.macro('MySum')
>>> my_sum(1, 2)
3

Sheets¶

class xlwings.main.Sheets(impl)¶

A collection of all sheet objects:

>>> import xlwings as xw
>>> xw.sheets  # active book
Sheets([<Sheet [Book1]Sheet1>, <Sheet [Book1]Sheet2>])
>>> xw.Book('Book1').sheets  # specific book
Sheets([<Sheet [Book1]Sheet1>, <Sheet [Book1]Sheet2>])

New in version 0.9.0.

active¶: Returns the active Sheet.

add(name=None, before=None, after=None)¶

Creates a new Sheet and makes it the active sheet.

Parameters:	name (str, default None) – Name of the new sheet. If None, will default to Excel’s default name. before (Sheet, default None) – An object that specifies the sheet before which the new sheet is added. after (Sheet, default None) – An object that specifies the sheet after which the new sheet is added.

Sheet¶

class xlwings.Sheet(sheet=None, impl=None)¶

A sheet object is a member of the sheets collection:

>>> import xlwings as xw
>>> wb = xw.Book()
>>> wb.sheets[0]
<Sheet [Book1]Sheet1>
>>> wb.sheets['Sheet1']
<Sheet [Book1]Sheet1>
>>> wb.sheets.add()
<Sheet [Book1]Sheet2>

Changed in version 0.9.0.

activate()¶: Activates the Sheet and returns it.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

autofit(axis=None)¶

Autofits the width of either columns, rows or both on a whole Sheet.

Parameters:	axis (string, default None) – To autofit rows, use one of the following: `rows` or `r` To autofit columns, use one of the following: `columns` or `c` To autofit rows and columns, provide no arguments

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> wb.sheets['Sheet1'].autofit('c')
>>> wb.sheets['Sheet1'].autofit('r')
>>> wb.sheets['Sheet1'].autofit()

New in version 0.2.3.

book¶: Returns the Book of the specified Sheet. Read-only.

cells¶: Returns a Range object that represents all the cells on the Sheet (not just the cells that are currently in use).

New in version 0.9.0.

charts¶: See Charts

New in version 0.9.0.

clear()¶: Clears the content and formatting of the whole sheet.

clear_contents()¶: Clears the content of the whole sheet but leaves the formatting.

copy(before=None, after=None, name=None)¶

Copy a sheet to the current or a new Book. By default, it places the copied sheet after all existing sheets in the current Book. Returns the copied sheet.

New in version 0.22.0.

Parameters:	before (sheet object, default None) – The sheet object before which you want to place the sheet after (sheet object, default None) – The sheet object after which you want to place the sheet, by default it is placed after all existing sheets name (str, default None) – The sheet name of the copy
Returns:	Sheet object – The copied sheet
Return type:	Sheet

Examples

# Create two books and add a value to the first sheet of the first book
first_book = xw.Book()
second_book = xw.Book()
first_book.sheets[0]['A1'].value = 'some value'

# Copy to same Book with the default location and name
first_book.sheets[0].copy()

# Copy to same Book with custom sheet name
first_book.sheets[0].copy(name='copied')

# Copy to second Book requires to use before or after
first_book.sheets[0].copy(after=second_book.sheets[0])

delete()¶: Deletes the Sheet.

index¶: Returns the index of the Sheet (1-based as in Excel).

name¶: Gets or sets the name of the Sheet.

names¶: Returns a names collection that represents all the sheet-specific names (names defined with the “SheetName!” prefix).

New in version 0.9.0.

pictures¶: See Pictures

New in version 0.9.0.

range(cell1, cell2=None)¶: Returns a Range object from the active sheet of the active book, see Range().

New in version 0.9.0.

render_template(**data)¶

This method requires xlwings PRO.

Replaces all Jinja variables (e.g {{ myvar }}) in the sheet with the keyword argument that has the same name. Following variable types are supported:

strings, numbers, lists, simple dicts, NumPy arrays, Pandas DataFrames, PIL Image objects that have a filename and Matplotlib figures.

New in version 0.22.0.

Parameters:	data (kwargs) – All key/value pairs that are used in the template.
Returns:	sheet
Return type:	xlwings Sheet

Examples

>>> import xlwings as xw
>>> book = xw.Book()
>>> book.sheets[0]['A1:A2'].value = '{{ myvar }}'
>>> book.sheets[0].render_template(myvar='test')

select()¶: Selects the Sheet. Select only works on the active book.

New in version 0.9.0.

shapes¶: See Shapes

New in version 0.9.0.

tables¶: See Tables

New in version 0.21.0.

to_pdf(path=None)¶

Exports the sheet to a PDF file.

Parameters:	path (str or path-like object, default None) – Path to the PDF file, defaults to the name of the sheet in the same directory of the workbook. For unsaved workbooks, it defaults to the current working directory instead.

Examples

>>> wb = xw.Book()
>>> sheet = wb.sheets[0]
>>> sheet['A1'].value = 'PDF'
>>> sheet.to_pdf()

Range¶

class xlwings.Range(cell1=None, cell2=None, **options)¶

Returns a Range object that represents a cell or a range of cells.

Parameters:

cell1 (str or tuple or Range) – Name of the range in the upper-left corner in A1 notation or as index-tuple or as name or as xw.Range object. It can also specify a range using the range operator (a colon), .e.g. ‘A1:B2’
cell2 (str or tuple or Range, default None) – Name of the range in the lower-right corner in A1 notation or as index-tuple or as name or as xw.Range object.

Examples

Active Sheet:

import xlwings as xw
xw.Range('A1')
xw.Range('A1:C3')
xw.Range((1,1))
xw.Range((1,1), (3,3))
xw.Range('NamedRange')
xw.Range(xw.Range('A1'), xw.Range('B2'))

Specific Sheet:

xw.books['MyBook.xlsx'].sheets[0].range('A1')

add_hyperlink(address, text_to_display=None, screen_tip=None)¶

Adds a hyperlink to the specified Range (single Cell)

Parameters:

address (str) – The address of the hyperlink.
text_to_display (str, default None) – The text to be displayed for the hyperlink. Defaults to the hyperlink address.
screen_tip (str, default None) – The screen tip to be displayed when the mouse pointer is paused over the hyperlink. Default is set to ‘<address> - Click once to follow. Click and hold to select this cell.’

New in version 0.3.0.

address¶: Returns a string value that represents the range reference. Use get_address() to be able to provide paramaters.

New in version 0.9.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

autofit()¶

Autofits the width and height of all cells in the range.

To autofit only the width of the columns use xw.Range('A1:B2').columns.autofit()
To autofit only the height of the rows use xw.Range('A1:B2').rows.autofit()

Changed in version 0.9.0.

clear()¶: Clears the content and the formatting of a Range.

clear_contents()¶: Clears the content of a Range but leaves the formatting.

color¶

Gets and sets the background color of the specified Range.

To set the color, either use an RGB tuple (0, 0, 0) or a color constant. To remove the background, set the color to None, see Examples.

Returns:	RGB
Return type:	tuple

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> xw.Range('A1').color = (255,255,255)
>>> xw.Range('A2').color
(255, 255, 255)
>>> xw.Range('A2').color = None
>>> xw.Range('A2').color is None
True

New in version 0.3.0.

column¶

Returns the number of the first column in the in the specified range. Read-only.

Returns:
Return type:	Integer

New in version 0.3.5.

column_width¶

Gets or sets the width, in characters, of a Range. One unit of column width is equal to the width of one character in the Normal style. For proportional fonts, the width of the character 0 (zero) is used.

If all columns in the Range have the same width, returns the width. If columns in the Range have different widths, returns None.

column_width must be in the range: 0 <= column_width <= 255

Note: If the Range is outside the used range of the Worksheet, and columns in the Range have different widths, returns the width of the first column.

Returns:
Return type:	float

New in version 0.4.0.

columns¶: Returns a RangeColumns object that represents the columns in the specified range.

New in version 0.9.0.

copy(destination=None)¶

Copy a range to a destination range or clipboard.

Parameters:	destination (xlwings.Range) – xlwings Range to which the specified range will be copied. If omitted, the range is copied to the Clipboard.
Returns:
Return type:	None

count¶: Returns the number of cells.

current_region¶

This property returns a Range object representing a range bounded by (but not including) any combination of blank rows and blank columns or the edges of the worksheet. It corresponds to Ctrl-* on Windows and Shift-Ctrl-Space on Mac.

Returns:
Return type:	Range object

delete(shift=None)¶

Deletes a cell or range of cells.

Parameters:	shift (str, default None) – Use `left` or `up`. If omitted, Excel decides based on the shape of the range.
Returns:
Return type:	None

end(direction)¶

Returns a Range object that represents the cell at the end of the region that contains the source range. Equivalent to pressing Ctrl+Up, Ctrl+down, Ctrl+left, or Ctrl+right.

Parameters:	direction (One of 'up', 'down', 'right', 'left') –

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> xw.Range('A1:B2').value = 1
>>> xw.Range('A1').end('down')
<Range [Book1]Sheet1!$A$2>
>>> xw.Range('B2').end('right')
<Range [Book1]Sheet1!$B$2>

New in version 0.9.0.

expand(mode='table')¶

Expands the range according to the mode provided. Ignores empty top-left cells (unlike Range.end()).

Parameters:	mode (str, default 'table') – One of `'table'` (=down and right), `'down'`, `'right'`.
Returns:
Return type:	Range

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> xw.Range('A1').value = [[None, 1], [2, 3]]
>>> xw.Range('A1').expand().address
$A$1:$B$2
>>> xw.Range('A1').expand('right').address
$A$1:$B$1

New in version 0.9.0.

formula¶: Gets or sets the formula for the given Range.

formula2¶: Gets or sets the formula2 for the given Range.

formula_array¶: Gets or sets an array formula for the given Range.

New in version 0.7.1.

get_address(row_absolute=True, column_absolute=True, include_sheetname=False, external=False)¶

Returns the address of the range in the specified format. address can be used instead if none of the defaults need to be changed.

Parameters:	row_absolute (bool, default True) – Set to True to return the row part of the reference as an absolute reference. column_absolute (bool, default True) – Set to True to return the column part of the reference as an absolute reference. include_sheetname (bool, default False) – Set to True to include the Sheet name in the address. Ignored if external=True. external (bool, default False) – Set to True to return an external reference with workbook and worksheet name.
Returns:
Return type:	str

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> xw.Range((1,1)).get_address()
'$A$1'
>>> xw.Range((1,1)).get_address(False, False)
'A1'
>>> xw.Range((1,1), (3,3)).get_address(True, False, True)
'Sheet1!A$1:C$3'
>>> xw.Range((1,1), (3,3)).get_address(True, False, external=True)
'[Book1]Sheet1!A$1:C$3'

New in version 0.2.3.

has_array¶: Are we part of an Array formula?

height¶

Returns the height, in points, of a Range. Read-only.

Returns:
Return type:	float

New in version 0.4.0.

hyperlink¶

Returns the hyperlink address of the specified Range (single Cell only)

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> xw.Range('A1').value
'www.xlwings.org'
>>> xw.Range('A1').hyperlink
'http://www.xlwings.org'

New in version 0.3.0.

insert(shift=None, copy_origin='format_from_left_or_above')¶

Insert a cell or range of cells into the sheet.

Parameters:	shift (str, default None) – Use `right` or `down`. If omitted, Excel decides based on the shape of the range. copy_origin (str, default format_from_left_or_above) – Use `format_from_left_or_above` or `format_from_right_or_below`. Note that this is not supported on macOS.
Returns:
Return type:	None

last_cell¶

Returns the bottom right cell of the specified range. Read-only.

Returns:
Return type:	Range

Example

>>> import xlwings as xw
>>> wb = xw.Book()
>>> rng = xw.Range('A1:E4')
>>> rng.last_cell.row, rng.last_cell.column
(4, 5)

New in version 0.3.5.

left¶

Returns the distance, in points, from the left edge of column A to the left edge of the range. Read-only.

Returns:
Return type:	float

New in version 0.6.0.

merge(across=False)¶

Creates a merged cell from the specified Range object.

Parameters:	across (bool, default False) – True to merge cells in each row of the specified Range as separate merged cells.

merge_area¶: Returns a Range object that represents the merged Range containing the specified cell. If the specified cell isn’t in a merged range, this property returns the specified cell.

merge_cells¶: Returns True if the Range contains merged cells, otherwise False

name¶: Sets or gets the name of a Range.

New in version 0.4.0.

number_format¶

Gets and sets the number_format of a Range.

Examples

>>> import xlwings as xw
>>> wb = xw.Book()
>>> xw.Range('A1').number_format
'General'
>>> xw.Range('A1:C3').number_format = '0.00%'
>>> xw.Range('A1:C3').number_format
'0.00%'

New in version 0.2.3.

offset(row_offset=0, column_offset=0)¶

Returns a Range object that represents a Range that’s offset from the specified range.

Returns:	Range object
Return type:	Range

New in version 0.3.0.

options(convert=None, **options)¶

Allows you to set a converter and their options. Converters define how Excel Ranges and their values are being converted both during reading and writing operations. If no explicit converter is specified, the base converter is being applied, see Converters and Options.

Keyword Arguments:
Parameters:	convert (object, default None) – A converter, e.g. `dict`, `np.array`, `pd.DataFrame`, `pd.Series`, defaults to default converter
	ndim (int, default None) – number of dimensions numbers (type, default None) – type of numbers, e.g. `int` dates (type, default None) – e.g. `datetime.date` defaults to `datetime.datetime` empty (object, default None) – transformation of empty cells transpose (Boolean, default False) – transpose values expand (str, default None) – One of `'table'`, `'down'`, `'right'` chunksize (int) – Use a chunksize, e.g. `10000` to prevent timeout or memory issues when reading or writing large amounts of data. Works with all formats, including DataFrames, NumPy arrays, and list of lists. => For converter-specific options, see Converters and Options.
Returns:
Return type:	Range object

New in version 0.7.0.

paste(paste=None, operation=None, skip_blanks=False, transpose=False)¶

Pastes a range from the clipboard into the specified range.

Parameters:	paste (str, default None) – One of `all_merging_conditional_formats`, `all`, `all_except_borders`, `all_using_source_theme`, `column_widths`, `comments`, `formats`, `formulas`, `formulas_and_number_formats`, `validation`, `values`, `values_and_number_formats`. operation (str, default None) – One of “add”, “divide”, “multiply”, “subtract”. skip_blanks (bool, default False) – Set to `True` to skip over blank cells transpose (bool, default False) – Set to `True` to transpose rows and columns.
Returns:
Return type:	None

raw_value¶: Gets and sets the values directly as delivered from/accepted by the engine that is being used (pywin32 or appscript) without going through any of xlwings’ data cleaning/converting. This can be helpful if speed is an issue but naturally will be engine specific, i.e. might remove the cross-platform compatibility.

resize(row_size=None, column_size=None)¶

Resizes the specified Range

Parameters:	row_size (int > 0) – The number of rows in the new range (if None, the number of rows in the range is unchanged). column_size (int > 0) – The number of columns in the new range (if None, the number of columns in the range is unchanged).
Returns:	Range object
Return type:	Range

New in version 0.3.0.

row¶

Returns the number of the first row in the specified range. Read-only.

Returns:
Return type:	Integer

New in version 0.3.5.

row_height¶

Gets or sets the height, in points, of a Range. If all rows in the Range have the same height, returns the height. If rows in the Range have different heights, returns None.

row_height must be in the range: 0 <= row_height <= 409.5

Note: If the Range is outside the used range of the Worksheet, and rows in the Range have different heights, returns the height of the first row.

Returns:
Return type:	float

New in version 0.4.0.

rows¶: Returns a RangeRows object that represents the rows in the specified range.

New in version 0.9.0.

select()¶: Selects the range. Select only works on the active book.

New in version 0.9.0.

shape¶: Tuple of Range dimensions.

New in version 0.3.0.

sheet¶: Returns the Sheet object to which the Range belongs.

New in version 0.9.0.

size¶: Number of elements in the Range.

New in version 0.3.0.

table¶: Returns a Table object if the range is part of one, otherwise None.

New in version 0.21.0.

top¶

Returns the distance, in points, from the top edge of row 1 to the top edge of the range. Read-only.

Returns:
Return type:	float

New in version 0.6.0.

unmerge()¶: Separates a merged area into individual cells.

value¶

Gets and sets the values for the given Range. See see xlwings.Range.options() about how to set options, e.g. to transform it into a DataFrame or how to set a chunksize.

Returns:	object
Return type:	returned object depends on the converter being used, see `xlwings.Range.options()`

width¶

Returns the width, in points, of a Range. Read-only.

Returns:
Return type:	float

New in version 0.4.0.

wrap_text¶: Returns True if the wrap_text property is enabled and False if it’s disabled. If not all cells have the same value in a range, on Windows it returns None and on macOS False.

New in version 0.23.2.

RangeRows¶

class xlwings.RangeRows(rng)¶

Represents the rows of a range. Do not construct this class directly, use Range.rows instead.

Example

import xlwings as xw

rng = xw.Range('A1:C4')

assert len(rng.rows) == 4  # or rng.rows.count

rng.rows[0].value = 'a'

assert rng.rows[2] == xw.Range('A3:C3')
assert rng.rows(2) == xw.Range('A2:C2')

for r in rng.rows:
    print(r.address)

autofit()¶: Autofits the height of the rows.

count¶: Returns the number of rows.

New in version 0.9.0.

RangeColumns¶

class xlwings.RangeColumns(rng)¶

Represents the columns of a range. Do not construct this class directly, use Range.columns instead.

Example

import xlwings as xw

rng = xw.Range('A1:C4')

assert len(rng.columns) == 3  # or rng.columns.count

rng.columns[0].value = 'a'

assert rng.columns[2] == xw.Range('C1:C4')
assert rng.columns(2) == xw.Range('B1:B4')

for c in rng.columns:
    print(c.address)

autofit()¶: Autofits the width of the columns.

count¶: Returns the number of columns.

New in version 0.9.0.

Shapes¶

class xlwings.main.Shapes(impl)¶

A collection of all shape objects on the specified sheet:

>>> import xlwings as xw
>>> xw.books['Book1'].sheets[0].shapes
Shapes([<Shape 'Oval 1' in <Sheet [Book1]Sheet1>>, <Shape 'Rectangle 1' in <Sheet [Book1]Sheet1>>])

New in version 0.9.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

count¶: Returns the number of objects in the collection.

Shape¶

class xlwings.Shape(*args, **options)¶

The shape object is a member of the shapes collection:

>>> import xlwings as xw
>>> sht = xw.books['Book1'].sheets[0]
>>> sht.shapes[0]  # or sht.shapes['ShapeName']
<Shape 'Rectangle 1' in <Sheet [Book1]Sheet1>>

Changed in version 0.9.0.

activate()¶: Activates the shape.

New in version 0.5.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.19.2.

delete()¶: Deletes the shape.

New in version 0.5.0.

height¶: Returns or sets the number of points that represent the height of the shape.

New in version 0.5.0.

left¶: Returns or sets the number of points that represent the horizontal position of the shape.

New in version 0.5.0.

name¶: Returns or sets the name of the shape.

New in version 0.5.0.

parent¶: Returns the parent of the shape.

New in version 0.9.0.

scale_height(factor, relative_to_original_size=False, scale='scale_from_top_left')¶

factor : float: For example 1.5 to scale it up to 150%
relative_to_original_size : bool, optional: If False, it scales relative to current height (default). For True must be a picture or OLE object.
scale : str, optional: One of scale_from_top_left (default), scale_from_bottom_right, scale_from_middle

New in version 0.19.2.

scale_width(factor, relative_to_original_size=False, scale='scale_from_top_left')¶

factor : float: For example 1.5 to scale it up to 150%
relative_to_original_size : bool, optional: If False, it scales relative to current width (default). For True must be a picture or OLE object.
scale : str, optional: One of scale_from_top_left (default), scale_from_bottom_right, scale_from_middle

New in version 0.19.2.

text¶: Returns or sets the text of a shape.

New in version 0.21.4.

top¶: Returns or sets the number of points that represent the vertical position of the shape.

New in version 0.5.0.

type¶: Returns the type of the shape.

New in version 0.9.0.

width¶: Returns or sets the number of points that represent the width of the shape.

New in version 0.5.0.

Charts¶

class xlwings.main.Charts(impl)¶

A collection of all chart objects on the specified sheet:

>>> import xlwings as xw
>>> xw.books['Book1'].sheets[0].charts
Charts([<Chart 'Chart 1' in <Sheet [Book1]Sheet1>>, <Chart 'Chart 1' in <Sheet [Book1]Sheet1>>])

New in version 0.9.0.

add(left=0, top=0, width=355, height=211)¶

Creates a new chart on the specified sheet.

Parameters:	left (float, default 0) – left position in points top (float, default 0) – top position in points width (float, default 355) – width in points height (float, default 211) – height in points
Returns:
Return type:	Chart

Examples

>>> import xlwings as xw
>>> sht = xw.Book().sheets[0]
>>> sht.range('A1').value = [['Foo1', 'Foo2'], [1, 2]]
>>> chart = sht.charts.add()
>>> chart.set_source_data(sht.range('A1').expand())
>>> chart.chart_type = 'line'
>>> chart.name
'Chart1'

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

count¶: Returns the number of objects in the collection.

Chart¶

class xlwings.Chart(name_or_index=None, impl=None)¶

The chart object is a member of the charts collection:

>>> import xlwings as xw
>>> sht = xw.books['Book1'].sheets[0]
>>> sht.charts[0]  # or sht.charts['ChartName']
<Chart 'Chart 1' in <Sheet [Book1]Sheet1>>

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

chart_type¶

Returns and sets the chart type of the chart. The following chart types are available:

3d_area, 3d_area_stacked, 3d_area_stacked_100, 3d_bar_clustered, 3d_bar_stacked, 3d_bar_stacked_100, 3d_column, 3d_column_clustered, 3d_column_stacked, 3d_column_stacked_100, 3d_line, 3d_pie, 3d_pie_exploded, area, area_stacked, area_stacked_100, bar_clustered, bar_of_pie, bar_stacked, bar_stacked_100, bubble, bubble_3d_effect, column_clustered, column_stacked, column_stacked_100, combination, cone_bar_clustered, cone_bar_stacked, cone_bar_stacked_100, cone_col, cone_col_clustered, cone_col_stacked, cone_col_stacked_100, cylinder_bar_clustered, cylinder_bar_stacked, cylinder_bar_stacked_100, cylinder_col, cylinder_col_clustered, cylinder_col_stacked, cylinder_col_stacked_100, doughnut, doughnut_exploded, line, line_markers, line_markers_stacked, line_markers_stacked_100, line_stacked, line_stacked_100, pie, pie_exploded, pie_of_pie, pyramid_bar_clustered, pyramid_bar_stacked, pyramid_bar_stacked_100, pyramid_col, pyramid_col_clustered, pyramid_col_stacked, pyramid_col_stacked_100, radar, radar_filled, radar_markers, stock_hlc, stock_ohlc, stock_vhlc, stock_vohlc, surface, surface_top_view, surface_top_view_wireframe, surface_wireframe, xy_scatter, xy_scatter_lines, xy_scatter_lines_no_markers, xy_scatter_smooth, xy_scatter_smooth_no_markers

New in version 0.1.1.

delete()¶: Deletes the chart.

height¶: Returns or sets the number of points that represent the height of the chart.

left¶: Returns or sets the number of points that represent the horizontal position of the chart.

name¶: Returns or sets the name of the chart.

parent¶: Returns the parent of the chart.

New in version 0.9.0.

set_source_data(source)¶

Sets the source data range for the chart.

Parameters:	source (Range) – Range object, e.g. `xw.books['Book1'].sheets[0].range('A1')`

top¶: Returns or sets the number of points that represent the vertical position of the chart.

width¶: Returns or sets the number of points that represent the width of the chart.

Pictures¶

class xlwings.main.Pictures(impl)¶

A collection of all picture objects on the specified sheet:

>>> import xlwings as xw
>>> xw.books['Book1'].sheets[0].pictures
Pictures([<Picture 'Picture 1' in <Sheet [Book1]Sheet1>>, <Picture 'Picture 2' in <Sheet [Book1]Sheet1>>])

New in version 0.9.0.

add(image, link_to_file=False, save_with_document=True, left=0, top=0, width=None, height=None, name=None, update=False, scale=1)¶

Adds a picture to the specified sheet.

Parameters:	image (str or path-like object or matplotlib.figure.Figure) – Either a filepath or a Matplotlib figure object. left (float, default 0) – Left position in points. top (float, default 0) – Top position in points. width (float, default None) – Width in points. If PIL/Pillow is installed, it defaults to the width of the picture. Otherwise it defaults to 100 points. height (float, default None) – Height in points. If PIL/Pillow is installed, it defaults to the height of the picture. Otherwise it defaults to 100 points. name (str, default None) – Excel picture name. Defaults to Excel standard name if not provided, e.g. ‘Picture 1’. update (bool, default False) – Replace an existing picture with the same name. Requires `name` to be set.
Returns:
Return type:	Picture

Examples

Picture

>>> import xlwings as xw
>>> sht = xw.Book().sheets[0]
>>> sht.pictures.add(r'C:\path\to\file.jpg')
<Picture 'Picture 1' in <Sheet [Book1]Sheet1>>

Matplotlib

>>> import matplotlib.pyplot as plt
>>> fig = plt.figure()
>>> plt.plot([1, 2, 3, 4, 5])
>>> sht.pictures.add(fig, name='MyPlot', update=True)
<Picture 'MyPlot' in <Sheet [Book1]Sheet1>>

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

count¶: Returns the number of objects in the collection.

Picture¶

class xlwings.Picture(impl=None)¶

The picture object is a member of the pictures collection:

>>> import xlwings as xw
>>> sht = xw.books['Book1'].sheets[0]
>>> sht.pictures[0]  # or sht.charts['PictureName']
<Picture 'Picture 1' in <Sheet [Book1]Sheet1>>

Changed in version 0.9.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

delete()¶: Deletes the picture.

New in version 0.5.0.

height¶: Returns or sets the number of points that represent the height of the picture.

New in version 0.5.0.

left¶: Returns or sets the number of points that represent the horizontal position of the picture.

New in version 0.5.0.

name¶: Returns or sets the name of the picture.

New in version 0.5.0.

parent¶: Returns the parent of the picture.

New in version 0.9.0.

top¶: Returns or sets the number of points that represent the vertical position of the picture.

New in version 0.5.0.

update(image)¶

Replaces an existing picture with a new one, taking over the attributes of the existing picture.

Parameters:	image (str or path-like object or matplotlib.figure.Figure) – Either a filepath or a Matplotlib figure object.

New in version 0.5.0.

width¶: Returns or sets the number of points that represent the width of the picture.

New in version 0.5.0.

Names¶

class xlwings.main.Names(impl)¶

A collection of all name objects in the workbook:

>>> import xlwings as xw
>>> sht = xw.books['Book1'].sheets[0]
>>> sht.names
[<Name 'MyName': =Sheet1!$A$3>]

New in version 0.9.0.

add(name, refers_to)¶

Defines a new name for a range of cells.

Parameters:	name (str) – Specifies the text to use as the name. Names cannot include spaces and cannot be formatted as cell references. refers_to (str) – Describes what the name refers to, in English, using A1-style notation.
Returns:
Return type:	Name

New in version 0.9.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

count¶: Returns the number of objects in the collection.

Name¶

class xlwings.Name(impl)¶

The name object is a member of the names collection:

>>> import xlwings as xw
>>> sht = xw.books['Book1'].sheets[0]
>>> sht.names[0]  # or sht.names['MyName']
<Name 'MyName': =Sheet1!$A$3>

New in version 0.9.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.9.0.

delete()¶: Deletes the name.

New in version 0.9.0.

name¶: Returns or sets the name of the name object.

New in version 0.9.0.

refers_to¶: Returns or sets the formula that the name is defined to refer to, in A1-style notation, beginning with an equal sign.

New in version 0.9.0.

refers_to_range¶: Returns the Range object referred to by a Name object.

New in version 0.9.0.

Tables¶

class xlwings.main.Tables(impl)¶

A collection of all table objects on the specified sheet:

>>> import xlwings as xw
>>> xw.books['Book1'].sheets[0].tables
Tables([<Table 'Table1' in <Sheet [Book11]Sheet1>>, <Table 'Table2' in <Sheet [Book11]Sheet1>>])

New in version 0.21.0.

add(source=None, name=None, source_type=None, link_source=None, has_headers=True, destination=None, table_style_name='TableStyleMedium2')¶

Creates a Table to the specified sheet.

Parameters:	source (xlwings range, default None) – An xlwings range object, representing the data source. name (str, default None) – The name of the Table. By default, it uses the autogenerated name that is assigned by Excel. source_type (str, default None) – This currently defaults to `xlSrcRange`, i.e. expects an xlwings range object. No other options are allowed at the moment. link_source (bool, default None) – Currently not implemented as this is only in case `source_type` is `xlSrcExternal`. has_headers (bool or str, default True) – Indicates whether the data being imported has column labels. Defaults to `True`. Possible values: `True`, `FAlse`, `'guess'` destination (xlwings range, default None) – Currently not implemented as this is used in case `source_type` is `xlSrcExternal`. table_style_name (str, default 'TableStyleMedium2') – Possible strings: `'TableStyleLightN''` (where N is 1-21), `'TableStyleMediumN'` (where N is 1-28), `'TableStyleDarkN'` (where N is 1-11)
Returns:
Return type:	Table

Examples

>>> import xlwings as xw
>>> sheet = xw.Book().sheets[0]
>>> sheet['A1'].value = [['a', 'b'], [1, 2]]
>>> table = sheet.tables.add(source=sheet['A1'].expand(), name='MyTable')
>>> table
<Table 'MyTable' in <Sheet [Book1]Sheet1>>

Table¶

class xlwings.main.Table(*args, **options)¶

The table object is a member of the tables collection:

>>> import xlwings as xw
>>> sht = xw.books['Book1'].sheets[0]
>>> sht.tables[0]  # or sht.tables['TableName']
<Table 'Table 1' in <Sheet [Book1]Sheet1>>

New in version 0.21.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

data_body_range¶: Returns an xlwings range object that represents the range of values, excluding the header row

display_name¶: Returns or sets the display name for the specified Table object

header_row_range¶: Returns an xlwings range object that represents the range of the header row

insert_row_range¶: Returns an xlwings range object representing the row where data is going to be inserted. This is only available for empty tables, otherwise it’ll return None

name¶: Returns or sets the name of the Table.

parent¶: Returns the parent of the table.

range¶: Returns an xlwings range object of the table.

show_autofilter¶: Turn the autofilter on or off by setting it to True or False (read/write boolean)

show_headers¶: Show or hide the header (read/write)

show_table_style_column_stripes¶: Returns or sets if the Column Stripes table style is used for (read/write boolean)

show_table_style_first_column¶: Returns or sets if the first column is formatted (read/write boolean)

show_table_style_last_column¶: Returns or sets if the last column is displayed (read/write boolean)

show_table_style_row_stripes¶: Returns or sets if the Row Stripes table style is used (read/write boolean)

show_totals¶: Gets or sets a boolean to show/hide the Total row.

table_style¶: Gets or sets the table style. See Tables.add for possible values.

totals_row_range¶: Returns an xlwings range object representing the Total row

update(data)¶

This method requires xlwings PRO

Updates the Excel table with the provided data. Currently restricted to DataFrames.

Changed in version 0.21.3.

Parameters:	data (pandas DataFrame) – Currently restricted to pandas DataFrames. If you want to hide the index, set the first column as the index, e.g. `df.set_index('column_name')`.
Returns:
Return type:	Table

Examples

import pandas as pd
import xlwings as xw

sheet = xw.Book('Book1.xlsx').sheets[0]
table_name = 'mytable'

# Sample DataFrame
nrows, ncols = 3, 3
df = pd.DataFrame(data=nrows * [ncols * ['test']],
                  columns=['col ' + str(i) for i in range(ncols)])

# Hide the index, then insert a new table if it doesn't exist yet,
# otherwise update the existing one
df = df.set_index('col 0')
if table_name in [table.name for table in sheet.tables]:
    sheet.tables[table_name].update(df)
else:
    mytable = sheet.tables.add(source=sheet['A1'], name=table_name).update(df)

Font¶

class xlwings.main.Font(impl)¶

The font object can be accessed as an attribute of the range or shape object.

mysheet['A1'].font
mysheet.shapes[0].font

New in version 0.23.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.23.0.

bold¶

Returns or sets the bold property (boolean).

>>> sheet['A1'].font.bold = True
>>> sheet['A1'].font.bold
True

New in version 0.23.0.

color¶

Returns or sets the color property (tuple).

>>> sheet['A1'].font.color = (255, 0, 0) # RGB tuple
>>> sheet['A1'].font.color
(255, 0, 0)

New in version 0.23.0.

italic¶

Returns or sets the italic property (boolean).

>>> sheet['A1'].font.italic = True
>>> sheet['A1'].font.italic
True

New in version 0.23.0.

name¶

Returns or sets the name of the font (str).

>>> sheet['A1'].font.name = 'Calibri'
>>> sheet['A1'].font.name
Calibri

New in version 0.23.0.

size¶

Returns or sets the size (float).

>>> sheet['A1'].font.size = 13
>>> sheet['A1'].font.size
13

New in version 0.23.0.

Characters¶

class xlwings.main.Characters(impl)¶

The characters object can be accessed as an attribute of the range or shape object.

mysheet['A1'].characters
mysheet.shapes[0].characters

Note

On macOS, characters are currently not supported due to bugs/lack of support in AppleScript.

New in version 0.23.0.

api¶: Returns the native object (pywin32 or appscript obj) of the engine being used.

New in version 0.23.0.

font¶

Returns or sets the text property of a characters object.

>>> sheet['A1'].characters[1:3].font.bold = True
>>> sheet['A1'].characters[1:3].font.bold
True

New in version 0.23.0.

text¶

Returns or sets the text property of a characters object.

>>> sheet['A1'].value = 'Python'
>>> sheet['A1'].characters[:3].text
Pyt

New in version 0.23.0.

Markdown¶

class xlwings.pro.Markdown(text, style=<MarkdownStyle> h1.font: .bold: True h1.blank_lines_after: 1 paragraph.blank_lines_after: 1 unordered_list.bullet_character: • unordered_list.blank_lines_after: 1 strong.bold: True emphasis.italic: True)¶

Markdown objects can be assigned to a single cell or shape via myrange.value or myshape.text. They accept a string in Markdown format which will cause the text in the cell to be formatted accordingly. They can also be used in mysheet.render_template().

Note

On macOS, formatting is currently not supported, but things like bullet points will still work.

Parameters:	text (str) – The text in Markdown syntax style (MarkdownStyle object, optional) – The MarkdownStyle object defines how the text will be formatted.

Examples

>>> mysheet['A1'].value = Markdown("A text with *emphasis* and **strong** style.")
>>> myshape.text = Markdown("A text with *emphasis* and **strong** style.")

New in version 0.23.0.

MarkdownStyle¶

class xlwings.pro.MarkdownStyle¶

MarkdownStyle defines how Markdown objects are being rendered in Excel cells or shapes. Start by instantiating a MarkdownStyle object. Printing it will show you the current (default) style:

>>> style = MarkdownStyle()
>>> style
<MarkdownStyle>
h1.font: .bold: True
h1.blank_lines_after: 1
paragraph.blank_lines_after: 1
unordered_list.bullet_character: •
unordered_list.blank_lines_after: 1
strong.bold: True
emphasis.italic: True

You can override the defaults, e.g., to make **strong** text red instead of bold, do this:

>>> style.strong.bold = False
>>> style.strong.color = (255, 0, 0)
>>> style.strong
strong.color: (255, 0, 0)

New in version 0.23.0.

UDF decorators¶

xlwings.func(category="xlwings", volatile=False, call_in_wizard=True)¶

Functions decorated with xlwings.func will be imported as Function to Excel when running “Import Python UDFs”.

category : int or str, default “xlwings”: 1-14 represent built-in categories, for user-defined categories use strings

New in version 0.10.3.
volatile : bool, default False: Marks a user-defined function as volatile. A volatile function must be recalculated whenever calculation occurs in any cells on the worksheet. A nonvolatile function is recalculated only when the input variables change. This method has no effect if it’s not inside a user-defined function used to calculate a worksheet cell.

New in version 0.10.3.
call_in_wizard : bool, default True: Set to False to suppress the function call in the function wizard.

New in version 0.10.3.

xlwings.sub()¶: Functions decorated with xlwings.sub will be imported as Sub (i.e. macro) to Excel when running “Import Python UDFs”.

xlwings.arg(arg, convert=None, **options)¶

Apply converters and options to arguments, see also Range.options().

Examples:

Convert x into a 2-dimensional numpy array:

import xlwings as xw
import numpy as np

@xw.func
@xw.arg('x', np.array, ndim=2)
def add_one(x):
    return x + 1

xlwings.ret(convert=None, **options)¶

Apply converters and options to return values, see also Range.options().

Examples

Suppress the index and header of a returned DataFrame:

import pandas as pd

@xw.func
@xw.ret(index=False, header=False)
def get_dataframe(n, m):
    return pd.DataFrame(np.arange(n * m).reshape((n, m)))

Dynamic array:

Note

If your version of Excel supports the new native dynamic arrays, then you don’t have to do anything special, and you shouldn’t use the expand decorator! To check if your version of Excel supports it, see if you have the =UNIQUE() formula available. Native dynamic arrays were introduced in Office 365 Insider Fast at the end of September 2018.

expand='table' turns the UDF into a dynamic array. Currently you must not use volatile functions as arguments of a dynamic array, e.g. you cannot use =TODAY() as part of a dynamic array. Also note that a dynamic array needs an empty row and column at the bottom and to the right and will overwrite existing data without warning.

Unlike standard Excel arrays, dynamic arrays are being used from a single cell like a standard function and auto-expand depending on the dimensions of the returned array:

import xlwings as xw
import numpy as np

@xw.func
@xw.ret(expand='table')
def dynamic_array(n, m):
    return np.arange(n * m).reshape((n, m))

New in version 0.10.0.

Reports¶

xlwings.pro.reports.create_report(template, output, book_settings=None, app=None, **data)¶

This function requires xlwings PRO.

This is a convenience wrapper around mysheet.render_template

Writes the values of all key word arguments to the output file according to the template and the variables contained in there (Jinja variable syntax). Following variable types are supported:

strings, numbers, lists, simple dicts, NumPy arrays, Pandas DataFrames, PIL Image objects that have a filename and Matplotlib figures.

Parameters:	template (str) – Path to your Excel template, e.g. `r'C:\Path\to\my_template.xlsx'` output (str) – Path to your Report, e.g. `r'C:\Path\to\my_report.xlsx'` book_settings (dict, default None) – A dictionary of `xlwings.Book` parameters, for details see: `xlwings.Book`. For example: `book_settings={'update_links': False}`. app (xlwings App, default None) – By passing in an xlwings App instance, you can control where your report runs and configure things like `visible=False`. For details see `xlwings.App`. By default, it creates the report in the currently active instance of Excel. data (kwargs) – All key/value pairs that are used in the template.
Returns:	wb
Return type:	xlwings Book

Examples

In my_template.xlsx, put the following Jinja variables in two cells: {{ title }} and {{ df }}

>>> from xlwings.pro.reports import create_report
>>> import pandas as pd
>>> df = pd.DataFrame(data=[[1,2],[3,4]])
>>> wb = create_report('my_template.xlsx', 'my_report.xlsx', title='MyTitle', df=df)

With many template variables it may be useful to collect the data first:

>>> data = dict(title='MyTitle', df=df)
>>> wb = create_report('my_template.xlsx', 'my_report.xlsx', **data)

If you need to handle external links or a password, use it like so:

>>> wb = create_report('my_template.xlsx', 'my_report.xlsx',
                       book_settings={'update_links': True, 'password': 'mypassword'},
                       **data)

You can control the Excel instance by passing in an xlwings App instance. For example, to run the report in a separate and hidden instance of Excel, do the following:

>>> import xlwings as xw
>>> from xlwings.pro.reports import create_report
>>> app = xw.App(visible=False)  # Separate and hidden Excel instance
>>> wb = create_report('my_template.xlsx', 'my_report.xlsx', app=app, **data)
>>> app.quit()  # Close the wb and quit the Excel instance

REST API¶

New in version 0.13.0.

Quickstart¶

xlwings offers an easy way to expose an Excel workbook via REST API both on Windows and macOS. This can be useful when you have a workbook running on a single computer and want to access it from another computer. Or you can build a Linux based web app that can interact with a legacy Excel application while you are in the progress of migrating the Excel functionality into your web app (if you need help with that, give us a shout).

You can run the REST API server from a command prompt or terminal as follows (this requires Flask>=1.0, so make sure to pip install Flask):

xlwings restapi run

Then perform a GET request e.g. via PowerShell on Windows or Terminal on Mac (while having an unsaved “Book1” open). Note that you need to run the server and the GET request from two separate terminals (or you can use something more convenient like Postman or Insomnia for testing the API):

$ curl "http://127.0.0.1:5000/book/book1/sheets/0/range/A1:B2"
{
  "address": "$A$1:$B$2",
  "color": null,
  "column": 1,
  "column_width": 10.0,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "1",
      "2"
    ],
    [
      "3",
      "4"
    ]
  ],
  "formula_array": null,
  "height": 32.0,
  "last_cell": "$B$2",
  "left": 0.0,
  "name": null,
  "number_format": "General",
  "row": 1,
  "row_height": 16.0,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 0.0,
  "value": [
    [
      1.0,
      2.0
    ],
    [
      3.0,
      4.0
    ]
  ],
  "width": 130.0
}

In the command prompt where your server is running, press Ctrl-C to shut it down again.

The xlwings REST API is a thin wrapper around the Python API which makes it very easy if you have worked previously with xlwings. It also means that the REST API does require the Excel application to be up and running which makes it a great choice if the data in your Excel workbook is constantly changing as the REST API will always deliver the current state of the workbook without the need of saving it first.

Note

Currently, we only provide the GET methods to read the workbook. If you are also interested in the POST methods to edit the workbook, let us know via GitHub issues. Some other things will also need improvement, most notably exception handling.

Run the server¶

xlwings restapi run will run a Flask development server on http://127.0.0.1:5000. You can provide --host and --port as command line args and it also respects the Flask environment variables like FLASK_ENV=development.

If you want to have more control, you can run the server directly with Flask, see the Flask docs for more details:

set FLASK_APP=xlwings.rest.api
flask run

If you are on Mac, use export FLASK_APP=xlwings.rest.api instead of set FLASK_APP=xlwings.rest.api.

For production, you can use any WSGI HTTP Server like gunicorn (on Mac) or waitress (on Mac/Windows) to serve the API. For example, with gunicorn you would do: gunicorn xlwings.rest.api:api. Or with waitress (adjust the host accordingly if you want to make the api accessible from outside of localhost):

from xlwings.rest.api import api
from waitress import serve
serve(wsgiapp, host='127.0.0.1', port=5000)

Indexing¶

While the Python API offers Python’s 0-based indexing (e.g. xw.books[0]) as well as Excel’s 1-based indexing (e.g. xw.books(1)), the REST API only offers 0-based indexing, e.g. /books/0.

Range Options¶

The REST API accepts Range options as query parameters, see xlwings.Range.options() e.g.

/book/book1/sheets/0/range/A1?expand=table&transpose=true

Remember that options only affect the value property.

Endpoint overview¶

Endpoint	Corresponds to	Short Description
/book	Book	Finds your workbook across all open instances of Excel and will open it if it can’t find it
/books	Books	Books collection of the active Excel instance
/apps	Apps	This allows you to specify the Excel instance you want to work with

Endpoint details¶

/book¶

GET /book/<fullname_or_name>¶

Example response:

{
  "app": 1104,
  "fullname": "C:\\Users\\felix\\DEV\\xlwings\\scripts\\Book1.xlsx",
  "name": "Book1.xlsx",
  "names": [
    "Sheet1!myname1",
    "myname2"
  ],
  "selection": "Sheet2!$A$1",
  "sheets": [
    "Sheet1",
    "Sheet2"
  ]
}

GET /book/<fullname_or_name>/names¶

Example response:

{
  "names": [
    {
      "name": "Sheet1!myname1",
      "refers_to": "=Sheet1!$B$2:$C$3"
    },
    {
      "name": "myname2",
      "refers_to": "=Sheet1!$A$1"
    }
  ]
}

GET /book/<fullname_or_name>/names/<name>¶

Example response:

{
  "name": "myname2",
  "refers_to": "=Sheet1!$A$1"
}

GET /book/<fullname_or_name>/names/<name>/range¶

Example response:

{
  "address": "$A$1",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 1,
  "current_region": "$A$1:$B$2",
  "formula": "=1+1.1",
  "formula_array": "=1+1,1",
  "height": 14.25,
  "last_cell": "$A$1",
  "left": 0.0,
  "name": "myname2",
  "number_format": "General",
  "row": 1,
  "row_height": 14.3,
  "shape": [
    1,
    1
  ],
  "size": 1,
  "top": 0.0,
  "value": 2.1,
  "width": 51.0
}

GET /book/<fullname_or_name>/sheets¶

Example response:

{
  "sheets": [
    {
      "charts": [
        "Chart 1"
      ],
      "name": "Sheet1",
      "names": [
        "Sheet1!myname1"
      ],
      "pictures": [
        "Picture 3"
      ],
      "shapes": [
        "Chart 1",
        "Picture 3"
      ],
      "used_range": "$A$1:$B$2"
    },
    {
      "charts": [],
      "name": "Sheet2",
      "names": [],
      "pictures": [],
      "shapes": [],
      "used_range": "$A$1"
    }
  ]
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>¶

Example response:

{
  "charts": [
    "Chart 1"
  ],
  "name": "Sheet1",
  "names": [
    "Sheet1!myname1"
  ],
  "pictures": [
    "Picture 3"
  ],
  "shapes": [
    "Chart 1",
    "Picture 3"
  ],
  "used_range": "$A$1:$B$2"
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/charts¶

Example response:

{
  "charts": [
    {
      "chart_type": "line",
      "height": 211.0,
      "left": 0.0,
      "name": "Chart 1",
      "top": 0.0,
      "width": 355.0
    }
  ]
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/charts/<chart_name_or_ix>¶

Example response:

{
  "chart_type": "line",
  "height": 211.0,
  "left": 0.0,
  "name": "Chart 1",
  "top": 0.0,
  "width": 355.0
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/names¶

Example response:

{
  "names": [
    {
      "name": "Sheet1!myname1",
      "refers_to": "=Sheet1!$B$2:$C$3"
    }
  ]
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/names/<sheet_scope_name>¶

Example response:

{
  "name": "Sheet1!myname1",
  "refers_to": "=Sheet1!$B$2:$C$3"
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/names/<sheet_scope_name>/range¶

Example response:

{
  "address": "$B$2:$C$3",
  "color": null,
  "column": 2,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "",
      ""
    ],
    [
      "",
      ""
    ]
  ],
  "formula_array": "",
  "height": 28.5,
  "last_cell": "$C$3",
  "left": 51.0,
  "name": "Sheet1!myname1",
  "number_format": "General",
  "row": 2,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 14.25,
  "value": [
    [
      null,
      null
    ],
    [
      null,
      null
    ]
  ],
  "width": 102.0
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/pictures¶

Example response:

{
  "pictures": [
    {
      "height": 100.0,
      "left": 0.0,
      "name": "Picture 3",
      "top": 0.0,
      "width": 100.0
    }
  ]
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/pictures/<picture_name_or_ix>¶

Example response:

{
  "height": 100.0,
  "left": 0.0,
  "name": "Picture 3",
  "top": 0.0,
  "width": 100.0
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/range¶

Example response:

{
  "address": "$A$1:$B$2",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "=1+1.1",
      "a string"
    ],
    [
      "43395.0064583333",
      ""
    ]
  ],
  "formula_array": null,
  "height": 28.5,
  "last_cell": "$B$2",
  "left": 0.0,
  "name": null,
  "number_format": null,
  "row": 1,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 0.0,
  "value": [
    [
      2.1,
      "a string"
    ],
    [
      "Mon, 22 Oct 2018 00:09:18 GMT",
      null
    ]
  ],
  "width": 102.0
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/range/<address>¶

Example response:

{
  "address": "$A$1:$B$2",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "=1+1.1",
      "a string"
    ],
    [
      "43395.0064583333",
      ""
    ]
  ],
  "formula_array": null,
  "height": 28.5,
  "last_cell": "$B$2",
  "left": 0.0,
  "name": null,
  "number_format": null,
  "row": 1,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 0.0,
  "value": [
    [
      2.1,
      "a string"
    ],
    [
      "Mon, 22 Oct 2018 00:09:18 GMT",
      null
    ]
  ],
  "width": 102.0
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/shapes¶

Example response:

{
  "shapes": [
    {
      "height": 211.0,
      "left": 0.0,
      "name": "Chart 1",
      "top": 0.0,
      "type": "chart",
      "width": 355.0
    },
    {
      "height": 100.0,
      "left": 0.0,
      "name": "Picture 3",
      "top": 0.0,
      "type": "picture",
      "width": 100.0
    }
  ]
}

GET /book/<fullname_or_name>/sheets/<sheet_name_or_ix>/shapes/<shape_name_or_ix>¶

Example response:

{
  "height": 211.0,
  "left": 0.0,
  "name": "Chart 1",
  "top": 0.0,
  "type": "chart",
  "width": 355.0
}

/books¶

GET /books¶

Example response:

{
  "books": [
    {
      "app": 1104,
      "fullname": "Book1",
      "name": "Book1",
      "names": [],
      "selection": "Sheet2!$A$1",
      "sheets": [
        "Sheet1"
      ]
    },
    {
      "app": 1104,
      "fullname": "C:\\Users\\felix\\DEV\\xlwings\\scripts\\Book1.xlsx",
      "name": "Book1.xlsx",
      "names": [
        "Sheet1!myname1",
        "myname2"
      ],
      "selection": "Sheet2!$A$1",
      "sheets": [
        "Sheet1",
        "Sheet2"
      ]
    },
    {
      "app": 1104,
      "fullname": "Book4",
      "name": "Book4",
      "names": [],
      "selection": "Sheet2!$A$1",
      "sheets": [
        "Sheet1"
      ]
    }
  ]
}

GET /books/<book_name_or_ix>¶

Example response:

{
  "app": 1104,
  "fullname": "C:\\Users\\felix\\DEV\\xlwings\\scripts\\Book1.xlsx",
  "name": "Book1.xlsx",
  "names": [
    "Sheet1!myname1",
    "myname2"
  ],
  "selection": "Sheet2!$A$1",
  "sheets": [
    "Sheet1",
    "Sheet2"
  ]
}

GET /books/<book_name_or_ix>/names¶

Example response:

{
  "names": [
    {
      "name": "Sheet1!myname1",
      "refers_to": "=Sheet1!$B$2:$C$3"
    },
    {
      "name": "myname2",
      "refers_to": "=Sheet1!$A$1"
    }
  ]
}

GET /books/<book_name_or_ix>/names/<name>¶

Example response:

{
  "name": "myname2",
  "refers_to": "=Sheet1!$A$1"
}

GET /books/<book_name_or_ix>/names/<name>/range¶

Example response:

{
  "address": "$A$1",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 1,
  "current_region": "$A$1:$B$2",
  "formula": "=1+1.1",
  "formula_array": "=1+1,1",
  "height": 14.25,
  "last_cell": "$A$1",
  "left": 0.0,
  "name": "myname2",
  "number_format": "General",
  "row": 1,
  "row_height": 14.3,
  "shape": [
    1,
    1
  ],
  "size": 1,
  "top": 0.0,
  "value": 2.1,
  "width": 51.0
}

GET /books/<book_name_or_ix>/sheets¶

Example response:

{
  "sheets": [
    {
      "charts": [
        "Chart 1"
      ],
      "name": "Sheet1",
      "names": [
        "Sheet1!myname1"
      ],
      "pictures": [
        "Picture 3"
      ],
      "shapes": [
        "Chart 1",
        "Picture 3"
      ],
      "used_range": "$A$1:$B$2"
    },
    {
      "charts": [],
      "name": "Sheet2",
      "names": [],
      "pictures": [],
      "shapes": [],
      "used_range": "$A$1"
    }
  ]
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>¶

Example response:

{
  "charts": [
    "Chart 1"
  ],
  "name": "Sheet1",
  "names": [
    "Sheet1!myname1"
  ],
  "pictures": [
    "Picture 3"
  ],
  "shapes": [
    "Chart 1",
    "Picture 3"
  ],
  "used_range": "$A$1:$B$2"
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/charts¶

Example response:

{
  "charts": [
    {
      "chart_type": "line",
      "height": 211.0,
      "left": 0.0,
      "name": "Chart 1",
      "top": 0.0,
      "width": 355.0
    }
  ]
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/charts/<chart_name_or_ix>¶

Example response:

{
  "chart_type": "line",
  "height": 211.0,
  "left": 0.0,
  "name": "Chart 1",
  "top": 0.0,
  "width": 355.0
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/names¶

Example response:

{
  "names": [
    {
      "name": "Sheet1!myname1",
      "refers_to": "=Sheet1!$B$2:$C$3"
    }
  ]
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/names/<sheet_scope_name>¶

Example response:

{
  "name": "Sheet1!myname1",
  "refers_to": "=Sheet1!$B$2:$C$3"
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/names/<sheet_scope_name>/range¶

Example response:

{
  "address": "$B$2:$C$3",
  "color": null,
  "column": 2,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "",
      ""
    ],
    [
      "",
      ""
    ]
  ],
  "formula_array": "",
  "height": 28.5,
  "last_cell": "$C$3",
  "left": 51.0,
  "name": "Sheet1!myname1",
  "number_format": "General",
  "row": 2,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 14.25,
  "value": [
    [
      null,
      null
    ],
    [
      null,
      null
    ]
  ],
  "width": 102.0
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/pictures¶

Example response:

{
  "pictures": [
    {
      "height": 100.0,
      "left": 0.0,
      "name": "Picture 3",
      "top": 0.0,
      "width": 100.0
    }
  ]
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/pictures/<picture_name_or_ix>¶

Example response:

{
  "height": 100.0,
  "left": 0.0,
  "name": "Picture 3",
  "top": 0.0,
  "width": 100.0
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/range¶

Example response:

{
  "address": "$A$1:$B$2",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "=1+1.1",
      "a string"
    ],
    [
      "43395.0064583333",
      ""
    ]
  ],
  "formula_array": null,
  "height": 28.5,
  "last_cell": "$B$2",
  "left": 0.0,
  "name": null,
  "number_format": null,
  "row": 1,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 0.0,
  "value": [
    [
      2.1,
      "a string"
    ],
    [
      "Mon, 22 Oct 2018 00:09:18 GMT",
      null
    ]
  ],
  "width": 102.0
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/range/<address>¶

Example response:

{
  "address": "$A$1:$B$2",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "=1+1.1",
      "a string"
    ],
    [
      "43395.0064583333",
      ""
    ]
  ],
  "formula_array": null,
  "height": 28.5,
  "last_cell": "$B$2",
  "left": 0.0,
  "name": null,
  "number_format": null,
  "row": 1,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 0.0,
  "value": [
    [
      2.1,
      "a string"
    ],
    [
      "Mon, 22 Oct 2018 00:09:18 GMT",
      null
    ]
  ],
  "width": 102.0
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/shapes¶

Example response:

{
  "shapes": [
    {
      "height": 211.0,
      "left": 0.0,
      "name": "Chart 1",
      "top": 0.0,
      "type": "chart",
      "width": 355.0
    },
    {
      "height": 100.0,
      "left": 0.0,
      "name": "Picture 3",
      "top": 0.0,
      "type": "picture",
      "width": 100.0
    }
  ]
}

GET /books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/shapes/<shape_name_or_ix>¶

Example response:

{
  "height": 211.0,
  "left": 0.0,
  "name": "Chart 1",
  "top": 0.0,
  "type": "chart",
  "width": 355.0
}

/apps¶

GET /apps¶

Example response:

{
  "apps": [
    {
      "books": [
        "Book1",
        "C:\\Users\\felix\\DEV\\xlwings\\scripts\\Book1.xlsx",
        "Book4"
      ],
      "calculation": "automatic",
      "display_alerts": true,
      "pid": 1104,
      "screen_updating": true,
      "selection": "[Book1.xlsx]Sheet2!$A$1",
      "version": "16.0",
      "visible": true
    },
    {
      "books": [
        "Book2",
        "Book5"
      ],
      "calculation": "automatic",
      "display_alerts": true,
      "pid": 7920,
      "screen_updating": true,
      "selection": "[Book5]Sheet2!$A$1",
      "version": "16.0",
      "visible": true
    }
  ]
}

GET /apps/<pid>¶

Example response:

{
  "books": [
    "Book1",
    "C:\\Users\\felix\\DEV\\xlwings\\scripts\\Book1.xlsx",
    "Book4"
  ],
  "calculation": "automatic",
  "display_alerts": true,
  "pid": 1104,
  "screen_updating": true,
  "selection": "[Book1.xlsx]Sheet2!$A$1",
  "version": "16.0",
  "visible": true
}

GET /apps/<pid>/books¶

Example response:

{
  "books": [
    {
      "app": 1104,
      "fullname": "Book1",
      "name": "Book1",
      "names": [],
      "selection": "Sheet2!$A$1",
      "sheets": [
        "Sheet1"
      ]
    },
    {
      "app": 1104,
      "fullname": "C:\\Users\\felix\\DEV\\xlwings\\scripts\\Book1.xlsx",
      "name": "Book1.xlsx",
      "names": [
        "Sheet1!myname1",
        "myname2"
      ],
      "selection": "Sheet2!$A$1",
      "sheets": [
        "Sheet1",
        "Sheet2"
      ]
    },
    {
      "app": 1104,
      "fullname": "Book4",
      "name": "Book4",
      "names": [],
      "selection": "Sheet2!$A$1",
      "sheets": [
        "Sheet1"
      ]
    }
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>¶

Example response:

{
  "app": 1104,
  "fullname": "C:\\Users\\felix\\DEV\\xlwings\\scripts\\Book1.xlsx",
  "name": "Book1.xlsx",
  "names": [
    "Sheet1!myname1",
    "myname2"
  ],
  "selection": "Sheet2!$A$1",
  "sheets": [
    "Sheet1",
    "Sheet2"
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>/names¶

Example response:

{
  "names": [
    {
      "name": "Sheet1!myname1",
      "refers_to": "=Sheet1!$B$2:$C$3"
    },
    {
      "name": "myname2",
      "refers_to": "=Sheet1!$A$1"
    }
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>/names/<name>¶

Example response:

{
  "name": "myname2",
  "refers_to": "=Sheet1!$A$1"
}

GET /apps/<pid>/books/<book_name_or_ix>/names/<name>/range¶

Example response:

{
  "address": "$A$1",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 1,
  "current_region": "$A$1:$B$2",
  "formula": "=1+1.1",
  "formula_array": "=1+1,1",
  "height": 14.25,
  "last_cell": "$A$1",
  "left": 0.0,
  "name": "myname2",
  "number_format": "General",
  "row": 1,
  "row_height": 14.3,
  "shape": [
    1,
    1
  ],
  "size": 1,
  "top": 0.0,
  "value": 2.1,
  "width": 51.0
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets¶

Example response:

{
  "sheets": [
    {
      "charts": [
        "Chart 1"
      ],
      "name": "Sheet1",
      "names": [
        "Sheet1!myname1"
      ],
      "pictures": [
        "Picture 3"
      ],
      "shapes": [
        "Chart 1",
        "Picture 3"
      ],
      "used_range": "$A$1:$B$2"
    },
    {
      "charts": [],
      "name": "Sheet2",
      "names": [],
      "pictures": [],
      "shapes": [],
      "used_range": "$A$1"
    }
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>¶

Example response:

{
  "charts": [
    "Chart 1"
  ],
  "name": "Sheet1",
  "names": [
    "Sheet1!myname1"
  ],
  "pictures": [
    "Picture 3"
  ],
  "shapes": [
    "Chart 1",
    "Picture 3"
  ],
  "used_range": "$A$1:$B$2"
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/charts¶

Example response:

{
  "charts": [
    {
      "chart_type": "line",
      "height": 211.0,
      "left": 0.0,
      "name": "Chart 1",
      "top": 0.0,
      "width": 355.0
    }
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/charts/<chart_name_or_ix>¶

Example response:

{
  "chart_type": "line",
  "height": 211.0,
  "left": 0.0,
  "name": "Chart 1",
  "top": 0.0,
  "width": 355.0
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/names¶

Example response:

{
  "names": [
    {
      "name": "Sheet1!myname1",
      "refers_to": "=Sheet1!$B$2:$C$3"
    }
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/names/<sheet_scope_name>¶

Example response:

{
  "name": "Sheet1!myname1",
  "refers_to": "=Sheet1!$B$2:$C$3"
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/names/<sheet_scope_name>/range¶

Example response:

{
  "address": "$B$2:$C$3",
  "color": null,
  "column": 2,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "",
      ""
    ],
    [
      "",
      ""
    ]
  ],
  "formula_array": "",
  "height": 28.5,
  "last_cell": "$C$3",
  "left": 51.0,
  "name": "Sheet1!myname1",
  "number_format": "General",
  "row": 2,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 14.25,
  "value": [
    [
      null,
      null
    ],
    [
      null,
      null
    ]
  ],
  "width": 102.0
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/pictures¶

Example response:

{
  "pictures": [
    {
      "height": 100.0,
      "left": 0.0,
      "name": "Picture 3",
      "top": 0.0,
      "width": 100.0
    }
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/pictures/<picture_name_or_ix>¶

Example response:

{
  "height": 100.0,
  "left": 0.0,
  "name": "Picture 3",
  "top": 0.0,
  "width": 100.0
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/range¶

Example response:

{
  "address": "$A$1:$B$2",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "=1+1.1",
      "a string"
    ],
    [
      "43395.0064583333",
      ""
    ]
  ],
  "formula_array": null,
  "height": 28.5,
  "last_cell": "$B$2",
  "left": 0.0,
  "name": null,
  "number_format": null,
  "row": 1,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 0.0,
  "value": [
    [
      2.1,
      "a string"
    ],
    [
      "Mon, 22 Oct 2018 00:09:18 GMT",
      null
    ]
  ],
  "width": 102.0
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/range/<address>¶

Example response:

{
  "address": "$A$1:$B$2",
  "color": null,
  "column": 1,
  "column_width": 8.47,
  "count": 4,
  "current_region": "$A$1:$B$2",
  "formula": [
    [
      "=1+1.1",
      "a string"
    ],
    [
      "43395.0064583333",
      ""
    ]
  ],
  "formula_array": null,
  "height": 28.5,
  "last_cell": "$B$2",
  "left": 0.0,
  "name": null,
  "number_format": null,
  "row": 1,
  "row_height": 14.3,
  "shape": [
    2,
    2
  ],
  "size": 4,
  "top": 0.0,
  "value": [
    [
      2.1,
      "a string"
    ],
    [
      "Mon, 22 Oct 2018 00:09:18 GMT",
      null
    ]
  ],
  "width": 102.0
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/shapes¶

Example response:

{
  "shapes": [
    {
      "height": 211.0,
      "left": 0.0,
      "name": "Chart 1",
      "top": 0.0,
      "type": "chart",
      "width": 355.0
    },
    {
      "height": 100.0,
      "left": 0.0,
      "name": "Picture 3",
      "top": 0.0,
      "type": "picture",
      "width": 100.0
    }
  ]
}

GET /apps/<pid>/books/<book_name_or_ix>/sheets/<sheet_name_or_ix>/shapes/<shape_name_or_ix>¶

Example response:

{
  "height": 211.0,
  "left": 0.0,
  "name": "Chart 1",
  "top": 0.0,
  "type": "chart",
  "width": 355.0
}

New	Old
`@xw.func`	`@xw.xlfunc`
`@xw.arg`	`@xw.xlarg`
`@xw.ret`	`@xw.xlret`
`@xw.sub`	`@xw.xlsub`

New	Old
`Range('A1', wkb=wb1).value`	`wb1.range('A1').value`
`Chart('Chart1', wkb=wb1)`	`wb1.chart('Chart1')`