Async Python Latency Benchmarking
Benchmark p50/p95/p99 with 1000+ samples per scenario. Use py-spy for sampling profiling without code changes. Histograms over averages — averages hide the tail. Profile representative traffic at steady state.
instructor — Structured LLM Outputs
instructor wraps the Anthropic and OpenAI clients to enforce Pydantic schema validation on every LLM response, with automatic retry on validation failure.
Polars + DuckDB
The two workhorses of Python data processing for AI engineers. Polars is a DataFrame library (pandas replacement) built on Apache Arrow — lazy evaluation, parallel by default, no GIL.
PyPI Distribution and Packaging
PyPI Trusted Publishers (OIDC) eliminates long-lived API tokens from CI — GitHub proves to PyPI it's running your workflow. Pytest plugins register via entry_points in pyproject.toml. No passwords stored, tokens expire automatically.
Python Async Programming
Python async/await is cooperative multitasking on a single thread — critical for LLM API calls, streaming, and any I/O-bound AI workload where waiting for a model response shouldn't block other work.
Python Ecosystem for AI Engineers
Production AI Python stack — uv for packaging (10-100x faster than pip), AsyncAnthropic + httpx for async I/O, Pydantic v2 for validation, respx for mock testing, polars for dataset work.
SQLAlchemy 2.0
Python's standard ORM and SQL toolkit. Version 2.0 (2023) introduced fully type-annotated models via `Mapped[T]` + `mapped_column()`, a unified `select()` API, and first-class async support.