python

python is a cursor rule for coding agents from PatrickJS/awesome-cursorrules. It costs 734 tokens per session, scanned A, original, CC0-1.0.

Python best practices and patterns for modern software development with Flask and SQLite.

Cursor rule

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 rules/patrickjs/awesome-cursorrules/python
Clone the repo
git clone --depth 1 https://github.com/PatrickJS/awesome-cursorrules

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for python

README.md
[![agentmods](https://agentmods.dev/badge/rules/patrickjs/awesome-cursorrules/python.svg)](https://agentmods.dev/rules/patrickjs/awesome-cursorrules/python)
Your own site
<a href="https://agentmods.dev/rules/patrickjs/awesome-cursorrules/python"><img src="https://agentmods.dev/badge/rules/patrickjs/awesome-cursorrules/python.svg" alt="Measured on agentmods" height="20"></a>
Per session 734 This file is loaded in full into every session.
When invoked 734 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00734 $0.00734
Opus 5 $0.00367 $0.00367
Sonnet 5 $0.00147 $0.00147
Haiku 4.5 $0.00073 $0.00073

Measured today against content hash 385f0a1700f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python 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 today.

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.

rules/python.mdc · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Best Practices

Project Structure

  • Use src-layout with src/your_package_name/
  • Place tests in tests/ directory parallel to src/
  • Keep configuration in config/ or as environment variables
  • Store requirements in requirements.txt or pyproject.toml
  • Place static files in static/ directory
  • Use templates/ for Jinja2 templates

Code Style

  • Follow Black code formatting
  • Use isort for import sorting
  • Follow PEP 8 naming conventions:
    • snake_case for functions and variables
    • PascalCase for classes
    • UPPER_CASE for constants
  • Maximum line length of 88 characters (Black default)
  • Use absolute imports over relative imports

Type Hints

  • Use type hints for all function parameters and returns
  • Import types from typing module
  • Use Optional[Type] instead of Type | None
  • Use TypeVar for generic types
  • Define custom types in types.py
  • Use Protocol for duck typing

Flask Structure

  • Use Flask factory pattern
  • Organize routes using Blueprints
  • Use Flask-SQLAlchemy for database
  • Implement proper error handlers
  • Use Flask-Login for authentication
  • Structure views with proper separation of concerns

Database

  • Use SQLAlchemy ORM
  • Implement database migrations with Alembic
  • Use proper connection pooling
  • Define models in separate modules
  • Implement proper relationships
  • Use proper indexing strategies

Authentication

  • Use Flask-Login for session management
  • Implement Google OAuth using Flask-OAuth
  • Hash passwords with bcrypt
  • Use proper session security
  • Implement CSRF protection
  • Use proper role-based access control

API Design

  • Use Flask-RESTful for REST APIs
  • Implement proper request validation
  • Use proper HTTP status codes
  • Handle errors consistently
  • Use proper response formats
  • Implement proper rate limiting

Testing

  • Use pytest for testing
  • Write tests for all routes
  • Use pytest-cov for coverage
  • Implement proper fixtures
  • Use proper mocking with pytest-mock
  • Test all error scenarios

Read the full file on GitHub · 121 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. today First seen · 121 lines · 734 tokens per session scan A 385f0a1700f8

Subscribe to this mod's changes

python is a cursor rule published in the GitHub repository PatrickJS/awesome-cursorrules (40,717 stars, last pushed 3mo ago), licensed CC0-1.0. It adds 734 tokens to every session, about $0.0037 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 2026-09-03.