- name
- asyncio
- description
- asyncio patterns, concurrency pitfalls, and backpressure. Use when writing async Python services.
Asyncio
Structured guidance for async Python with asyncio: confirm triggers, propose the stages below, and adapt if the user wants a lighter pass.
When to Offer This Workflow
Trigger conditions:
- User mentions asyncio, async python, or closely related work
- They want a structured workflow rather than ad-hoc tips
- They are preparing a review, rollout, or stakeholder communication
Initial offer: Explain the four stages briefly and ask whether to follow this workflow or work freeform. If they decline, continue in their preferred style.
Workflow Stages
Stage 1: Clarify context & goals
Anchor on event loop and tasks. Ask what success looks like, constraints, and what must not break. Capture unknowns early.
Stage 2: Design or plan the approach
Translate goals into a concrete plan around cancellation and timeouts. Compare alternatives and explicit trade-offs; avoid implicit assumptions.
Stage 3: Implement, validate, and harden
Execute with verification loops tied to backpressure and queues. Prefer small steps, measurable checks, and rollback points where risk is high.
Stage 4: Operate, communicate, and iterate
Close the loop with debugging concurrency: monitoring, documentation, stakeholder updates, and lessons learned for the next cycle.
Checklist Before Completion
- Goals and constraints are explicit for asyncio work
- Risks and trade-offs are stated, not hand-waved
- Verification steps match the change’s impact (tests, canary, peer review)
- Operational follow-through is covered (monitoring, docs, owners)
Tips for Effective Guidance
- Be procedural: stage-by-stage, with clear exit criteria
- Ask for missing context (environment, scale, deadlines) before prescribing
- Prefer checklists and concrete examples over generic platitudes
- If the user declines the workflow, switch to freeform help without lecturing
Handling Deviations
- If the user wants to skip a stage: confirm and continue with what they need.
- If context is missing: ask targeted questions before strong recommendations.
- Prefer concrete examples, trade-offs, and verification steps over generic advice.
Quality Bar
- Each recommendation should be actionable (what to do next).
- Call out failure modes relevant to asyncio concurrency (security, scale, UX, or ops).
- Keep tone direct and respectful of the user’s time.