Python Enhancement Proposal is referred to as PEP. In essence, it is a design document that offers the Python community information or suggests a new feature for the Python language. Consider a PEP as an official means for Python developers to convey ideas that potentially influence Python’s development, document choices, and propose improvements.
Why Do PEPs Matter?
PEPs are the backbone of how Python evolves. Every time a new feature is added to the language—or even when someone proposes changing or removing a feature—it typically starts with a PEP.
They serve multiple purposes:
- Propose new features (like f-strings or async/await).
- Explain design decisions behind features.
- Set coding standards (like the famous PEP 8).
- Facilitate community discussion before making changes.
A Real-World Example: PEP 8
One of the most well-known PEPs is PEP 8, which outlines the style guide for writing Python code. It covers things like how to name variables, when to use spaces vs. tabs, and how to format your code to keep it readable and consistent.
PEP 8 isn’t about changing the language—it’s about making sure the code we write is clean, professional, and easy to understand.
Who Writes PEPs?
Anyone in the Python community can write a PEP, but the process is detailed and collaborative. Once written, a PEP is submitted and goes through discussions, feedback, and revisions. Eventually, it may be accepted, rejected, or deferred.
The final decision often comes down to the Python Steering Council—a group of core developers who oversee the language’s direction.
Types of PEPs
There are a few categories of PEPs:
- Standards Track PEPs: Propose new features or implementations.
- Informational PEPs: Share guidelines or best practices.
- Process PEPs: Propose changes to how Python is developed or managed.
How to Read a PEP
Each PEP has a specific format, including:
- An abstract (summary of the proposal)
- Motivation (why the change is needed)
- Specification (details of the proposal)
- Backward compatibility (how it affects existing code)
- Reference implementation (if applicable)
You can find all current and historical PEPs on the official Python PEP index.