Python Coding Conventions

A set of guidelines for writing Python code, covering naming, type hints, documentation, formatting, error handling, and maintainability.

In plain words
What is it for?
Use it when writing Python functions, algorithms, dependencies, comments, docstrings, and exception handling.
Why use it?
It gives coding work a consistent style and makes Python code easier to read, review, and maintain.

Instructions file for GitHub Copilot

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/timothywarner-org/context-engineering/python-coding-conventions
Clone the repo
git clone --depth 1 https://github.com/timothywarner-org/context-engineering

Made for: GitHub Copilot.

Per session 426 This file is loaded in full into every session.
When invoked 426 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00426 $0.00426
Opus 5 $0.00213 $0.00213
Sonnet 5 $0.00085 $0.00085
Haiku 4.5 $0.00043 $0.00043

Measured 2d ago against content hash 055c4dcad2a9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Python Coding Conventions scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.github/instructions/Python Coding Conventions.instructions.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Coding Conventions

Python Instructions

  • Write clear and concise comments for each function.
  • Ensure functions have descriptive names and include type hints.
  • Provide docstrings following PEP 257 conventions.
  • Use the typing module for type annotations (e.g., List[str], Dict[str, int]).
  • Break down complex functions into smaller, more manageable functions.

General Instructions

  • Always prioritize readability and clarity.
  • For algorithm-related code, include explanations of the approach used.
  • Write code with good maintainability practices, including comments on why certain design decisions were made.
  • Handle edge cases and write clear exception handling.
  • For libraries or external dependencies, mention their usage and purpose in comments.
  • Use consistent naming conventions and follow language-specific best practices.
  • Write concise, efficient, and idiomatic code that is also easily understandable.

Code Style and Formatting

  • Follow the PEP 8 style guide for Python.
  • Maintain proper indentation (use 4 spaces for each level of indentation).
  • Ensure lines do not exceed 79 characters.
  • Place function and class docstrings immediately after the def or class keyword.
  • Use blank lines to separate functions, classes, and code blocks where appropriate.

Edge Cases and Testing

  • Always include test cases for critical paths of the application.
  • Account for common edge cases like empty inputs, invalid data types, and large datasets.
  • Include comments for edge cases and the expected behavior in those cases.
  • Write unit tests for functions and document them with docstrings explaining the test cases.

Example of Proper Documentation

def calculate_area(radius: float) -> float:
    """
    Calculate the area of a circle given the radius.

    Parameters:
    radius (float): The radius of the circle.

    Returns:
    float: The area of the circle, calculated as π * radius^2.
    """
    import math
    return math.pi * radius ** 2

Read the full file on GitHub · 57 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 57 lines · 426 tokens per session scan A 055c4dcad2a9

Subscribe to this mod's changes

Python Coding Conventions is an instructions file published in the GitHub repository timothywarner-org/context-engineering (27 stars, last pushed 2mo ago), licensed MIT. It adds 426 tokens to every session, about $0.0021 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.