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Rachael Grey
Rachael Grey

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7 Best Practices Used in Python for Automation

Given its scalability, speed, availability across platforms, and 24/7 support, Python is a favorite programming language for developers regarding intelligent automation and hyper-automation. These are only the conversation's starting points; in the following blog, we'll go into more detail.

Let's talk about why Python is preferred by every product owner, including you, to accomplish scalable and creative automation, as you have already read in the introduction about Python's popularity for automation projects.

No matter which automation project using Python you would be working on, it is vulnerable to bugs and errors. But with the best practices listed here, the chances of errors or bugs would be null.

When automating manual tasks, using Python code, scripts, and modules, you must consider the following 7 tips.

1. Leverage Version Control

Use version control systems like Git to monitor the changes made to code and help in collaborating. Moreover, you can even leverage version control to try it through several other ways and revert to the original version.

2. Make a Habit of Writing Clear & Concise Code

Write an easy-to-understand, read, and maintainable code with relevant names, systematic formatting, and additional comments, if complex code is required.

3. Leverage Exceptional Handling

With the help of exceptional handling, youh can manage all the errors without any hassle while maintaining your code. Make sure you use try/except blocks to catch and handle exceptions and also notify exceptions if highlighted.

4. Make a Habit of Testing Codes

Testing would sort out the errors that would create trouble in the later stages of either development or deployment. For this purpose, you can even use the pytest (a Python testing framework) for writing and running automated tests.

5. Leverage Logging

With the help of logging, you can keep a check on your written code. You can leverage Python’s built-in logging module to record crucial events and messages in your code.

6. Leverage Virtual Environments

Leveraging virtual environments would abandon Python environments. Besides, it even manages dependencies for other projects. You can leverage tools like conda or virtualenv to create your own environment.

7. Make a Habit of Documenting a Code

You must make sure that you document your code to use and understand. For this, you can use docstrings, modules, classes, and functions, and write README files, explaining the use of code.


Python scripts, modules, and libraries are potential programming languages that effectively perform automation tasks. The talk of the town is Python's prowess in carrying out functions for diverse specialties, and being simple and easy to comprehend has become a cherry on the cake for Python developers to exploit the language and conduct automation chores.

Utilizing Python for automation tasks has many advantages, and our developers are knowledgeable in the most recent upgrades. If you plan to build an automation project, connect with the best python developers. The decision is on you, but the discussion would simplify and benefit you.

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