Introduction
The Python automation package allows you to invoke and execute a Python script
wherever necessary within the automation process flow. This functionality is
provided by the RunPythonScript component in the Robility , which is part of the
Python Automation package.
Moreover, it simplifies the management of Python scripts by centralizing them
within RobilityDesigner. As a result, users can efficiently harness the power of
Python automation to optimize their tasks and achieve greater productivity.
Pre-requisites
- Ensure that your Python script is indented correctly to avoid indentation
during runtime. - When passing a variable name as the value for an argument, the names
must match. - For example, if the argument name is 'Sample,' the variable name should
also be 'Sample.’ - Failure to match the names will result in a mismatch error being thrown.
- The Python functionality in Robility requires the "Python.exe" file to execute
the process, and this file will be automatically installed when you install the
feature. - Refer the attached sample Python file to view how to parse arguments in
the script.
Benefits
1. Customization: You can create custom Python scripts to handle specific
tasks or scenarios that might be challenging with native Robility activities, giving
you more control and flexibility.
2. Integration: Python can easily integrate with external APIs, databases, and
web services, enabling you to connect your workflows to a broader array of systems
and data sources.
3. Machine Learning: You can incorporate machine learning models and algorithms
to make data-driven decisions and predictions within your workflow.
4. Performance: Python is known for its performance, making it suitable for handling
large datasets and computationally intensive tasks.
Use Cases
1. Data Manipulation and Analysis: Python can be used to clean, transform, and
analyze data before or after processing it. This is particularly useful for tasks
involving Excel spreadsheets, CSV files, or databases.
2. Image and Video Processing: You can employ Python libraries such as OpenCV
to work with images and videos within the workflows. This is valuable for tasks like
image recognition, object detection, or video processing.
3. Machine Learning Integration: Integrate machine learning models trained in
Python into your automation bot to automate decision-making processes, such as
fraud detection or recommendation systems.
4. Database Interaction: Python can connect to various databases (SQL, NoSQL) to
perform data extraction, transformation, and loading tasks as part of your workflows.
5. Automating Script Execution: Execute Python scripts at specific points in your
automation to perform specialized calculations or tasks.
To see the available activities in Python Automation, click the link below.