Python Decimal: Precision Starts at the Input
Use Python Decimal with exact input conversion, explicit precision and rounding, bounded validation, quantization tests, and stable data boundaries.
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Use Python Decimal with exact input conversion, explicit precision and rounding, bounded validation, quantization tests, and stable data boundaries.
Use Python ZoneInfo with aware timestamps, IANA zones, ambiguous-time policies, timezone-data dependencies, calendar intent, and daylight-saving tests.
Use asyncio TaskGroup with scoped task ownership, exception-group handling, cooperative cleanup, bounded concurrency, and tested partial-failure behavior.
Use Git stash with explicit tracked and untracked scope, descriptive entries, inspected changes, conflict handling, and verified restoration before cleanup.
Use Git clean with dry-run previews, explicit path scope, ignored-file awareness, protected local data, and separate clean-build verification workflows.
Use PostgreSQL savepoints with explicit partial-failure rules, rollback boundaries, correct release behavior, driver checks, and external side-effect limits.
Plan PostgreSQL materialized views with a clear freshness contract, compatible refresh mode, unique-index requirements, safe scheduling, and result validation.
Use PostgreSQL Serializable with whole-transaction retries, fresh decisions, bounded attempts, protected external effects, and realistic concurrent tests.
Plan Kubernetes resource quotas with namespace budgets, LimitRange defaults, rollout headroom, object limits, admission checks, and capacity-aware monitoring.
Design Kubernetes init containers with repeatable setup, narrow mounts and credentials, bounded dependency waits, resource planning, and failed-start tests.