Python Master

Modern Python patterns for Modal.com serverless platform. PROACTIVELY activate for: (1) Modal function deployment, (2) Type-safe Modal with Pydantic, (3) Async patterns in Modal, (4) GPU workloads (ML inference, training), (5) FastAPI web endpoints on Modal, (6) Scheduled tasks and cron jobs, (7) Modal Volumes and storage, (8) Testing Modal functions with pytest, (9) Modal classes and lifecycle methods, (10) Parallel processing with map/starmap. Provides: Type hints patterns, Pydantic integration, async/await patterns, pytest testing, FastAPI integration, scheduled tasks, Volume usage, cost optimization, and production-ready examples following Python 3.11+ best practices.

Expert guide to FFmpeg from Python for video/audio processing, encoding, streaming, and media manipulation. PROACTIVELY activate for: (1) Python+FFmpeg via ffmpeg-python, PyAV, subprocess, moviepy; (2) encoding (H.264, H.265/HEVC, VP9/WebM, AV1); (3) hardware acceleration (NVIDIA NVENC, Intel QSV, AMD AMF, VAAPI); (4) audio extraction, conversion, filter chains; (5) video filters (scale, crop, rotate, text/image overlays, color); (6) trim/concat workflows; (7) HLS, DASH, RTMP streaming; (8) metadata probing (ffprobe, ffmpeg.probe); (9) thumbnails (single + sprite sheets); (10) frame-accurate PyAV; (11) bug debugging (audio loss after filters, subprocess deadlocks, Windows paths, -y prompts); (12) GIF, speed change, picture-in-picture, blur/quality detection. Provides: library selection, install steps, copy-pasteable encoding recipes, hardware-accel flag reference, error handling, subprocess best practices, performance tuning for production Python+FFmpeg pipelines.

Complete OpenCV computer vision system for Python. PROACTIVELY activate for: (1) Image loading with cv2.imread (BGR format gotcha), (2) Video capture with cv2.VideoCapture, (3) Color space conversion (BGR to RGB, HSV, grayscale), (4) Image filtering (GaussianBlur, medianBlur, bilateralFilter), (5) Edge detection (Canny), (6) Contour detection with cv2.findContours, (7) Image resizing with interpolation methods, (8) Template matching, (9) Feature detection (SIFT, ORB, AKAZE), (10) Drawing functions (rectangle, circle, text), (11) Video writing with cv2.VideoWriter, (12) Morphological operations, (13) Deep learning with cv2.dnn module, (14) GPU acceleration with cv2.cuda, (15) Coordinate system (x,y vs row,col) gotchas. Provides: Image processing patterns, video capture/writing, memory management, performance optimization, Jupyter notebook workarounds. Ensures correct BGR handling and memory-safe OpenCV usage.

Complete Python Cloudflare deployment system. PROACTIVELY activate for: (1) Python Workers with Pyodide, (2) FastAPI on Workers, (3) Cloudflare Containers for heavy compute, (4) Service bindings (RPC), (5) Environment variables in Workers, (6) Cold start optimization, (7) Workflows for durable execution, (8) GPU containers for AI. Provides: Worker code patterns, wrangler config, Dockerfile templates, FastAPI integration. Ensures edge deployment with proper architecture choices.

Expert guide to end-to-end Python video pipelines combining FFmpeg, OpenCV, PyAV, ffmpegcv, Decord, VidGear, and Modal.com for scalable GPU-accelerated workflows. PROACTIVELY activate for: (1) FFmpeg+OpenCV in same pipeline (decode, process, re-encode); (2) color-format mismatches (BGR vs RGB across OpenCV, PIL, PyAV, FFmpeg); (3) frame dim ordering (HWC vs CHW) between OpenCV and ML frameworks; (4) audio stream loss in filter chains; (5) memory mgmt for long/large videos (streaming vs in-memory); (6) choosing ffmpegcv/Decord/VidGear/PyAV for performance; (7) GPU decode/encode on Modal.com; (8) parallel + chunk-based processing on Modal; (9) transcoding pipelines on serverless; (10) HLS generation on Modal; (11) upload -> process -> transcode -> HLS workflows; (12) batch sizing for GPU memory, pixel formats, large-video streaming. Provides: library selection matrix, integration recipes, Modal.com deployment examples, GPU pipeline tuning, production-ready workflow examples.

Complete Python 3.13+ fundamentals system. PROACTIVELY activate for: (1) Python 3.13 free-threading (no-GIL), (2) JIT compiler usage, (3) Pattern matching syntax, (4) Walrus operator, (5) F-string features 3.12+, (6) Type parameter syntax 3.12+, (7) Exception groups, (8) Dataclasses and enums, (9) Context managers. Provides: Modern syntax, performance features, best practices, naming conventions. Ensures correct Python 3.13+ patterns with optimal performance.

Complete Python package management system. PROACTIVELY activate for: (1) uv package manager (10-100x faster), (2) pyproject.toml configuration, (3) Virtual environment setup, (4) Dependency management with uv.lock, (5) Ruff linting and formatting, (6) src layout project structure, (7) Publishing to PyPI, (8) pip and requirements.txt. Provides: uv commands, pyproject.toml templates, ruff config, pre-commit setup. Ensures modern Python project setup with fast tooling.