python-ffmpeg
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.
What this skill does
# Python FFmpeg Skill Use this skill for Python-driven FFmpeg work: encoding, filtering, audio processing, metadata probing, streaming, thumbnails, PyAV frame access, subprocess integration, and production troubleshooting. ## When to Use This Skill Use when the user asks for tasks covered by the frontmatter triggers, especially implementation guidance, debugging, architecture choices, production hardening, or performance-sensitive decisions in this domain. Start from this orchestrator, then load the focused reference file that matches the requested detail level. ## Core Workflow 1. Choose the integration layer first: ffmpeg-python for readable filter graphs, subprocess for full CLI parity, PyAV for frame-level access, and moviepy only for simple edits. 2. Probe inputs before processing so codec, duration, resolution, FPS, audio streams, and metadata are known. 3. Preserve audio explicitly whenever a video filter is applied; filtered video streams do not automatically carry audio. 4. Select the output codec and acceleration path based on compatibility, compression, and deployment hardware. 5. Use overwrite/error-handling patterns consistently: `overwrite_output()` with ffmpeg-python or `-y` with subprocess, plus captured stderr for diagnostics. 6. For large media, stream frames or use temp files instead of reading all stdout or frames into memory. ## Key Gotchas - Video filters commonly drop audio unless the audio stream is passed to `ffmpeg.output(...)` or copied explicitly. - Subprocess pipes can deadlock if stdout/stderr are not drained or frame reads are not sized correctly. - Windows paths are safest as `Path(...).as_posix()` or as subprocess argument-list entries, not hand-quoted command strings. - CRF values are codec-specific: H.265 CRF 28 is roughly comparable to H.264 CRF 23. - Hardware encoders trade compression efficiency for speed; validate availability before choosing NVENC, QSV, AMF, or VAAPI. ## Reference Map - [references/ffmpeg-complete-recipes.md](references/ffmpeg-complete-recipes.md) - Full original recipe guide covering encoding, hardware acceleration, audio/audio filters, video filters, trimming, concatenation, streaming, probing, thumbnails, PyAV, subprocess patterns, common transformations, errors, and performance tips. - [references/ffmpeg-advanced-patterns.md](references/ffmpeg-advanced-patterns.md) - Additional advanced FFmpeg patterns already maintained for this skill. ## Response Guidance - Preserve the user's existing framework, library, and tooling choices unless there is a clear compatibility or performance reason to suggest an alternative. - Give copy-pasteable code only for the exact task at hand; otherwise point to the relevant reference section. - Call out tradeoffs, failure modes, and verification steps for production workflows. - Prefer accessible, maintainable, measurable solutions over clever micro-optimizations.
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