Merge pull request #12892 from nirusrin/patch-92

Update service-python-packages-support.md
MicrosoftDocs · Jan 24, 2025 · b2dd483 · b2dd483
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diff --git a/powerbi-docs/connect-data/service-python-packages-support.md b/powerbi-docs/connect-data/service-python-packages-support.md
@@ -8,7 +8,7 @@ ms.custom: ''
 ms.service: powerbi
 ms.subservice: pbi-data-sources
 ms.topic: conceptual
-ms.date: 01/13/2023
+ms.date: 01/17/2025
 LocalizationGroup: Connect to data
 ---
 # Learn which Python packages are supported in Power BI
@@ -17,27 +17,99 @@ You can use the powerful [Python programming language](https://www.python.org/)
 
 The following sections provide an alphabetical table of which Python packages are supported in Power BI.
 
-## Request support for a new Python package
-
-Supported Python packages for Power BI are found in the [following section](#python-packages-that-are-supported-in-power-bi). If you would like to request support of a Python package not found in that list, submit your request to [Power BI Ideas](https://ideas.powerbi.com).
-
 ## Requirements and limitations of Python packages
 
 There are a handful of requirements and limitations for Python packages:
 
-* Current Python runtime: Python 3.7.7.
 * Power BI, for the most part, supports Python packages with free and open-source software licenses such as GPL-2, GPL-3, MIT+, and so on.
 * Power BI supports packages published in PyPI. The service doesn't support private or custom Python packages. Users are encouraged to make their private packages available on PyPI prior to requesting the package be available in Power BI.
 * For Python visuals in Power BI Desktop, you can install any package, including custom Python packages.
 * For security and privacy reasons, Python packages that provide client-server queries over the web in the service, aren't supported. Networking is blocked for such attempts.
 * The approval process for including a new Python package has a tree of dependencies. Some dependencies required to be installed in the service can't be supported.
 
-## Python packages that are supported in Power BI
+### For reports in Premium/Fabric backed workspaces
+* Python runtime: Python 3.11
+
+## Python packages that are supported in the Power BI service (Premium/ Fabric backed workspaces)
+
+The following table shows which packages **are supported** in Power BI for reports in **Premium/Fabric backed workspaces**.
+[Download packages here] (https://pypi.org/) 
+
+| Package            | Version   |  
+|--------------------|-----------|
+| asttokens          | 2.4.1     | 
+| certifi            | 2024.8.30 |
+| comm               | 0.2.2     |
+| contourpy          | 1.3.0     |
+| cycler             | 0.12.1    |
+| debugpy            | 1.8.5     | 
+| decorator          | 5.1.1     |
+| exceptiongroup     | 1.2.2     |
+| executing          | 2.1.0     | 
+| fonttools          | 4.53.1    |
+| importlib_metadata | 8.4.0     |
+| ipykernel          | 6.29.4    |
+| ipython            | 8.27.0    | 
+| jedi               | 0.19.1    | 
+| joblib             | 1.4.2     |
+| jupyter_client     | 8.6.2     | 
+| jupyter_core       | 5.7.2     |  
+| kiwisolver         | 1.4.5     | 
+| matplotlib         | 3.8.4     |
+| matplotlib inline  | 0.1.7     | 
+| munkres            | 1.1.4     | 
+| nest_asyncio       | 1.6.0     |  
+| numpy              | 2.0.0     | 
+| packaging          | 24.1      |  
+| pandas             | 2.2.2     |  
+| parso              | 0.8.4     |  
+| patsy              | 0.5.6     |
+| pexpect            | 4.9.0     |  
+| pickleshare        | 0.7.5     |
+| pillow             | 10.4.0    |  
+| pip                | 24        |  
+| platformdirs       | 4.2.2     |  
+| ply                | 3.11      |  
+| prompt_toolkit     | 3.0.47    |  
+| psutil             | 6.0.0     |
+| ptyprocess         | 0.7.0     |
+| pure_eval          | 0.2.3     |  
+| Pygments           | 2.18.0    |  
+| pyparsing          | 3.1.2     |  
+| PyQt5              | 5.15.9    |  
+| PyQt5 sip          | 12.12.2   |  
+| python dateutil    | 2.9.0     |  
+| pytz               | 2024.1    |  
+| pyzmq              | 26.2.0    |
+| scikit learn       | 1.5.0     |
+| scipy              | 1.13.1    |  
+| seaborn            | 0.13.2    |  
+| setuptools         | 70.0.0    |  
+| sip                | 6.7.12    |  
+| six                | 1.16.0    |  
+| stack data         | 0.6.2     |  
+| statsmodels        | 0.14.2    |
+| threadpoolctl      | 3.5.0     |
+| toml               | 0.10.2    |  
+| tomli              | 2.0.1     |  
+| tornado            | 6.4.1     |
+| traitlets          | 5.14.3    |  
+| typing_extensions  | 4.12.2    |
+| tzdata             | 2024.1    |  
+| unicodedata2       | 15.1.0    |
+| wcwidth            | 0.2.13    | 
+| wheel              | 0.44.0    | 
+| xgboost            | 2.0.3     |
+| zipp               | 3.20.1    | 
+
 
-The following table shows which packages **are supported** in Power BI.
+### For non-Premium/Fabric backed workspaces/Sov. Clouds
+* Python runtime: Python 3.7.7
+
+The following table shows which packages **are supported** in Power BI reports in **non-Premium/Fabric backed workspaces**.
 
 |        Package        |   Version   |                                   Link                                   |
-|:----------------------|:------------|:-------------------------------------------------------------------------|
+|-----------------------|-------------|--------------------------------------------------------------------------|
 | `cycler` | 0.11.0 | [https://pypi.org/project/cycler](https://pypi.org/project/cycler) |
 | `joblib` | 1.1.0 | [https://pypi.org/project/joblib](https://pypi.org/project/joblib) |
 | `kiwisolver` | 1.4.4 | [https://pypi.org/project/kiwisolver](https://pypi.org/project/kiwisolver) |
@@ -60,6 +132,13 @@ The following table shows which packages **are supported** in Power BI.
 | `typing-extensions` | 4.3.0 | [https://pypi.org/project/typing-extensions](https://pypi.org/project/typing-extensions) |
 | `xgboost` | 1.6.1 | [https://pypi.org/project/xgboost](https://pypi.org/project/xgboost) |
 
+
+## Considerations and limitations
+
+- Py visuals aren't supported with Service Principal Profiles for App Owns Data.
+- Py visuals rendered from the Power BI service (for Premium/ F SKUs) will support payloads of < 30Mb.
+
+
 ## Related content
 
 For more information about Python in Power BI, take a look at the following articles:

diff --git a/...ocs/guidance/powerbi-implementation-planning-integration-with-other-services.md b/...ocs/guidance/powerbi-implementation-planning-integration-with-other-services.md
@@ -476,7 +476,7 @@ To refresh a published semantic model that uses Python or R integrated in Power
 
 You can integrate Python or R with Power BI reports in order to create custom visuals with Python libraries, like Seaborn or R packages like ggplot2. These visuals are fully customizable and support interactive features in Power BI like rendering a filtered result, cross-filtering, custom tooltips, drilldown, and drillthrough.
 
-Ensure that all your Python or R visuals use [Python libraries](../connect-data/service-python-packages-support.md#python-packages-that-are-supported-in-power-bi) and [R packages](../connect-data/service-r-packages-support.md#r-packages-that-are-supported-in-power-bi-(-premium-/-fabric-backed-workspaces-) that are supported in Fabric. If you use an unsupported library or package, the visual won't render in the Power BI service, even when the visual renders in your report in Power BI Desktop.
+Ensure that all your Python or R visuals use [Python libraries](../connect-data/service-python-packages-support.md#for-reports-in-premiumfabric-backed-workspaces) and [R packages](../connect-data/service-r-packages-support.md#r-packages-that-are-supported-in-power-bi-premiumfabric-backed-workspaces) that are supported in Fabric. If you use an unsupported library or package, the visual won't render in the Power BI service, even when the visual renders in your report in Power BI Desktop.
 
 While you can transform data and make calculations as part of a Python or R custom visual, it isn't recommended. Placing this logic in the Python or R visual can result in slower render durations, and greater difficulty to maintain the visual and achieve harmonization across visuals and reports in calculation logic.