Introduction
When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.
Python Packages
When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,
- revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
- microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
- Anaconda 4.2 – Anaconda is an opensource Python package
Get all installed Python Packages
The below T-SQL Statements lists all installed Python Packages.
EXECUTE sp_execute_external_script
@language = N'Python',
@script = N'
import pkg_resources
import pandas
OutputDataSet = pandas.DataFrame(sorted([(i.key, i.version) for i in pkg_resources.working_set]))'
WITH result sets((Package NVARCHAR(128), Version NVARCHAR(128)));
From the above statement, pkg_resources contains the information about the Python packages and we are looping it get details of each packages. i.key in the for loop holds the information about the Package name and i.version holds the information about the version. And the T-SQL Statement results as,

At this time of writing this article, the T-SQL Statement results 164 rows of Package information. In this T-SQL Statement we are not able to see the version of these packages. To get version details, we have to use import sys.
Version of Python
To get the Python package version, we have to import the sys. The below T-SQL statement shows how to get the version of Python,
EXECUTE sp_execute_external_script
@language = N'Python',
@script = N'
import sys
print(sys.version)
'
The sys.version results the Python version.

Conclusion
In this article, we have discussed about the default Python packages installed while setting up the Machine Learning Services in SQL Server installing. We can also install more packages, which we will discuss in our upcoming articles. I hope you all found this article much useful. Please share your feedback in the comment section.
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