aeondave/python-patterns
programming/python-patterns/SKILL.md
Pythonic patterns and best practices for writing readable, robust Python: typing, error handling, data modeling, iteration, resource management, project layout, and tooling. Use when writing or reviewing Python code and APIs.
$ install --global
skillsauthnpx skillsauth add aeondave/malskill python-patternsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
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9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
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OWASP Dep-Check
50%
Last scanned: Mar 31, 2026, 9:57 PM61.6s8 files scanned
SKILL.md
- name:
- python-patterns
- description:
- Pythonic patterns and best practices for writing readable, robust Python: typing, error handling, data modeling, iteration, resource management, project layout, and tooling. Use when writing or reviewing Python code and APIs.
- license:
- MIT
- compatibility:
- Python 3.11+ (guidance baseline). Optional tools: ruff, mypy, pytest.
- author:
- AeonDave
- version:
- 1.1
Python Patterns
This skill is for day-to-day Python code quality: readability, correctness, maintainability.
If you are doing asyncio-heavy work, prefer python-async-patterns for structured concurrency, cancellation, and backpressure.
When to activate
- Writing/refactoring Python modules, libraries, services
- Reviewing PRs for idioms, clarity, and footguns
- Introducing typing or improving error handling
- Designing lightweight data models and APIs
Core principles (high signal)
- Readability beats cleverness.
- Be explicit at boundaries (I/O, parsing, network). Keep inner code simple.
- Prefer small, typed functions with clear names.
- Use context managers for resource safety.
- Raise specific exceptions and preserve causes (
raise ... from e).
Quick review checklist
- No mutable default arguments;
Nonesentinel used is None/is not None(not== None)- Specific
exceptclauses; no bareexcept: - Types: public functions/classes have annotations; complex types use aliases
- Files/paths use
pathlib.Pathwhere appropriate - Iteration uses comprehensions/generators only when simple
Resources
Load on demand:
references/typing.md— modern typing (3.11), aliases, Protocol, genericsreferences/errors.md— exception hygiene, custom errors, chaining, boundariesreferences/data-models.md— dataclasses, NamedTuple, immutability, validationreferences/iteration.md— comprehensions vs loops, generators, itertoolsreferences/resources.md— context managers, cleanup, temp filesreferences/performance.md— simple perf rules (avoid premature optimization)references/layout-tooling.md— project layout, ruff/mypy/pytest notes
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