async-python-patterns

Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.

5 stars

Best use case

async-python-patterns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.

Teams using async-python-patterns should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/async-python-patterns/SKILL.md --create-dirs "https://raw.githubusercontent.com/FrancoStino/opencode-skills-collection/main/bundled-skills/async-python-patterns/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/async-python-patterns/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How async-python-patterns Compares

Feature / Agentasync-python-patternsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Async Python Patterns

Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.

## Use this skill when

- Building async web APIs (FastAPI, aiohttp, Sanic)
- Implementing concurrent I/O operations (database, file, network)
- Creating web scrapers with concurrent requests
- Developing real-time applications (WebSocket servers, chat systems)
- Processing multiple independent tasks simultaneously
- Building microservices with async communication
- Optimizing I/O-bound workloads
- Implementing async background tasks and queues

## Do not use this skill when

- The workload is CPU-bound with minimal I/O.
- A simple synchronous script is sufficient.
- The runtime environment cannot support asyncio/event loop usage.

## Instructions

- Clarify workload characteristics (I/O vs CPU), targets, and runtime constraints.
- Pick concurrency patterns (tasks, gather, queues, pools) with cancellation rules.
- Add timeouts, backpressure, and structured error handling.
- Include testing and debugging guidance for async code paths.
- If detailed examples are required, open `resources/implementation-playbook.md`.

Refer to `resources/implementation-playbook.md` for detailed patterns and examples.

## Resources

- `resources/implementation-playbook.md` for detailed patterns and examples.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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