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Extract, Transform, and Load PowerShell Scripts in Python

The CData Python Connector for PowerShell enables you to create ETL applications and pipelines for PowerShell scripts in Python with petl.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for PowerShell and the petl framework, you can build PowerShell-connected applications and pipelines for extracting, transforming, and loading PowerShell scripts. This article shows how to connect to PowerShell with the CData Python Connector and use petl and pandas to extract, transform, and load PowerShell scripts.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live PowerShell scripts in Python. When you issue complex SQL queries from PowerShell, the driver pushes supported SQL operations, like filters and aggregations, directly to PowerShell and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to PowerShell Scripts

Connecting to PowerShell scripts looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

The ScriptLocation, under the Data section, must be set to a valid script location.

After installing the CData PowerShell Connector, follow the procedure below to install the other required modules and start accessing PowerShell through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for PowerShell Scripts in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.powershell as mod

You can now connect with a connection string. Use the connect function for the CData PowerShell Connector to create a connection for working with PowerShell scripts.

cnxn = mod.connect("ScriptLocation='%Public%\Documents\CData PowerShell Scripts';ExecuteQuery=True;")

Create a SQL Statement to Query PowerShell

Use SQL to create a statement for querying PowerShell. In this article, we read data from the Process entity.

sql = "SELECT ProcessName, CPU FROM Process WHERE ProcessName = 'RemoteConnectorService'"

Extract, Transform, and Load the PowerShell Scripts

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the PowerShell scripts. In this example, we extract PowerShell scripts, sort the data by the CPU column, and load the data into a CSV file.

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'CPU')

etl.tocsv(table2,'process_data.csv')

With the CData Python Connector for PowerShell, you can work with PowerShell scripts just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the PowerShell Python Connector to start building Python apps and scripts with connectivity to PowerShell scripts. Reach out to our Support Team if you have any questions.



Full Source Code

import petl as etl
import pandas as pd
import cdata.powershell as mod

cnxn = mod.connect("ScriptLocation='%Public%\Documents\CData PowerShell Scripts';ExecuteQuery=True;")

sql = "SELECT ProcessName, CPU FROM Process WHERE ProcessName = 'RemoteConnectorService'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'CPU')

etl.tocsv(table2,'process_data.csv')