Design and implement Python AI applications with provider-neutral LLM clients, local models, structured outputs, RAG, embeddings, reranking, tool calling, agents, streaming, evaluation, observability, and GPU inference. Use when building or reviewing…
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Design and debug Python asyncio systems with structured concurrency, TaskGroup, gather, cancellation, timeouts, bounded concurrency, queues, backpressure, streaming, graceful shutdown, blocking-call isolation, and async testing. Use for concurrent I/O,…
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Build and review robust Python command-line applications with argparse, Typer, Click, Rich, or Textual. Use for commands, subcommands, options, config precedence, environment variables, stdin/stdout/stderr contracts, exit codes, JSON output, progress, shell…
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Build and review reliable Python data workflows with pandas 3, Polars, NumPy, Arrow, DuckDB, CSV, Parquet, and ETL patterns. Use for DataFrame transformations, schema design, null handling, joins, aggregations, time series, lazy or streaming execution,…
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Build and review cross-platform Python desktop applications with tkinter, ttk, CustomTkinter, PySide6, or PyQt6. Use for windows, widgets, layouts, dialogs, system tray, background jobs, event loops, model-view separation, accessibility, high-DPI behavior,…
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Modernize Python projects and choose version-appropriate language features. Use for Python 3.12, 3.13, or 3.14 upgrades, PEP 695 generics, typing improvements, deferred annotations, template strings, free-threaded CPython, experimental JIT evaluation,…
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Build and review authorized Python networking software across TCP, UDP, TLS, HTTP clients, WebSocket, DNS, SSH, proxies, and custom protocols. Use for socket or asyncio streams, message framing, connection limits, timeouts, retries, backpressure, graceful…
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Package, build, lock, install, and publish Python applications or libraries with pyproject.toml, PEP 517/518/621 metadata, uv, pip, build backends, src layouts, wheel, sdist, dependency groups, entry points, CI matrices, TestPyPI, Trusted Publishing, and…
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