ytcap 0.1.4

Extract YouTube metadata and subtitles into JSON and JSONL outputs.

ytcap

ytcap is a Python CLI project for extracting video metadata and subtitle files from YouTube video, batch, and playlist sources, then turning them into reusable JSON and JSONL outputs.

It is designed for workflows where you have YouTube video URLs, video IDs, or playlists and want structured metadata plus subtitles for search, indexing, dataset preparation, education, or analysis.

Project Status

The current public release is:

0.1.4

Release pages:

• PyPI: https://pypi.org/project/ytcap/
• GitHub Releases: https://github.com/ozkozturk/ytcap/releases

Release automation uses GitHub Actions with PyPI and TestPyPI Trusted Publishing. See RELEASE.md for the maintainer release process.

ytcap is still pre-1.0, so CLI details and JSON/JSONL schemas may change in future 0.x releases. User-facing changes are tracked in CHANGELOG.md.

The current release includes:

• Importable Python package scaffold.
• Package version exposed as ytcap.__version__.
• Basic CLI entry point with ytcap --help and ytcap --version.
• CLI command structure for inspect, video, and export.
• batch command to process multiple video URLs or IDs from a text file, with run manifest logging, --resume and --skip-existing support.
• yt-dlp adapter support for inspect metadata extraction.
• Normalized video metadata mapping and inspect JSON summary output.
• Tested subtitle source selection for manual, auto, and any normalized tracks.
• Controlled subtitle format validation for srt and vtt.
• Standard output directory layout creation for video --out.
• video command metadata JSON writing and selected SRT/VTT subtitle file download.
• SRT/VTT cue parsing, cue-level JSONL writer helpers, and basic sentence-level segmentation helpers.
• export command conversion of existing SRT/VTT files to enriched cue-level or sentence-level JSONL.
• playlist command to process videos inside a YouTube playlist with --limit, --start, and --end range controls, run manifest logging, --resume, --skip-existing, and --dry-run.
• Safe validation for dynamic output filename parts to prevent path traversal from user input or extractor metadata.
• English manual subtitle variant matching for --lang en, including en-* tracks such as en-GB.
• GitHub Actions release automation with Trusted Publishing.

Core Decisions

Decision	Target
Language	Python
Minimum Python version	Python 3.11+
CLI approach	Standard library first: argparse
Test approach	Standard library first: unittest
YouTube Data API	Not used
Metadata and subtitle extraction	yt-dlp>=2026.06.09 is the core extractor dependency
Video/audio downloads	Out of scope for the MVP
Output format	JSON for metadata, JSONL for segment and sentence output
Distribution target	PyPI and pipx install ytcap
Additional dependencies	Require justification and approval before being added

Current Capabilities and Roadmap

The current release can:

• Accept a single YouTube video URL or video ID.
• Save normalized video metadata as JSON.
• Find subtitles for a requested language.
• Prefer manual subtitles when available, with optional fallback to automatic subtitles.
• Save subtitles as SRT or VTT.
• Convert subtitles to cue-level or sentence-level JSONL.
• Report videos with missing or failed subtitle extraction.
• Process a text batch file of video URLs or IDs.
• Process a YouTube playlist with range and limit controls.

Later releases may add:

• A dedicated retry command for failed records.
• A stable 1.0 CLI and JSON/JSONL schema.

Non-Goals

ytcap intentionally does not:

• Use the official YouTube Data API.
• Manage API keys or OAuth flows.
• Download video or audio files as an MVP goal.
• Redistribute YouTube content or bypass access restrictions.
• Start with advanced NLP sentence segmentation libraries; simple, testable heuristics come first.

CLI Examples

These commands show the current user experience. The inspect command uses yt-dlp for metadata and subtitle availability summaries. The video command extracts metadata through yt-dlp, writes normalized metadata JSON, selects a matching subtitle track, and saves the selected SRT/VTT subtitle file. SRT/VTT cue parsers, cue-level JSONL writer helpers, and basic punctuation-based sentence segmentation helpers are wired into the export command for existing subtitle files.

Inspect One Video

ytcap inspect --url "https://www.youtube.com/watch?v=VIDEO_ID"

This answers:

• Is the video reachable?
• Can metadata be extracted?
• Which subtitle languages are available?
• Are subtitles manual, automatic, or both?

Extract Metadata and Subtitles

ytcap video --url "https://www.youtube.com/watch?v=VIDEO_ID" --lang en --source any --format srt --out ./data

Part	Meaning
ytcap	CLI application
video	Single-video processing command
--url	Video URL
--lang en	Request English subtitles
--source any	Try manual subtitles first, then automatic subtitles
--format srt	Save subtitles as SRT
--out ./data	Write outputs under ./data

Implemented source selection behavior uses language and format matches: manual selects only manual subtitles, auto selects only automatic subtitles, and any tries manual first before falling back to automatic subtitles. For --lang en, manual English variants reported by YouTube as en-*, such as en-GB or en-eEY6OEpapP, are accepted while output file names still use the requested en language component. Implemented subtitle format validation currently accepts srt and vtt; other values return an UNSUPPORTED_FORMAT error before extraction work starts. When run without --dry-run, video writes normalized metadata to videos/{video_id}.info.json and the selected subtitle file to subtitles/{video_id}.{lang}.{source}.{format} under the output directory. If the requested subtitle cannot be selected or downloaded, the command returns a controlled error without leaving a new partial metadata file behind.

List Available Subtitles

ytcap inspect --url "https://www.youtube.com/watch?v=VIDEO_ID" --list-subs

Convert Existing Subtitles to JSONL

ytcap export --input ./data/subtitles/VIDEO_ID.en.manual.srt --segments cue --category education --out ./data/normalized

ytcap export --input ./data/subtitles --segments sentence --out ./data/normalized

The export command reads existing .srt and .vtt files and writes enriched JSONL records to {video_id}.{lang}.{segments}.jsonl under the output directory. It infers video_id, language, and source from names such as VIDEO_ID.en.manual.srt; when the source is missing, JSONL records use "source":"unknown". --video-id and --lang may override metadata for a single file input.

Export expects the matching normalized metadata file at videos/{video_id}.info.json in the standard output layout. Each JSONL record keeps the display text, adds a search-friendly normalized_text, and copies compact video, channel, available manual subtitle language, and downloaded subtitle language metadata from that file. English subtitle languages (en and en-*) are excluded from the subtitle language arrays. When --category is provided, JSONL records include dataset_category with that value and category_source:"user"; otherwise those fields are null and "none".

Dynamic filename parts such as video ID, language, source, format, segment type, and run ID are validated before paths are built. Empty values, path separators, control characters, absolute paths, . and .. are rejected.

Process a Batch File

ytcap batch --input videos.txt --lang en --source any --format srt --resume --skip-existing --out ./data

This command parses the input file and processes each URL/ID. It creates a run manifest under runs/{run_id}.manifest.json keeping track of execution statistics, output files, and errors. Failed attempts are appended to failed/failed.jsonl. --resume skips entries completed in the latest manifest and retries previous failures, while --skip-existing skips videos whose metadata and subtitle files already exist for the requested language, source, and format. --dry-run reports the batch plan without writing files or creating output directories.

Batch Input File Format

The --input file for the batch command is a plain text file containing one YouTube video URL or video ID per line.

• Empty lines and lines containing only whitespace are ignored.
• Lines starting with # (with optional leading whitespace) are ignored as comment lines.
• Inline comments starting with # are supported, and the comment text plus any preceding whitespace are ignored.

Example input file:

# This is a comment line
dQw4w9WgXcQ                  # Rick Astley - Never Gonna Give You Up
https://youtu.be/jNQXAC9IVRw # Another video URL

Process a Playlist

ytcap playlist --url "https://www.youtube.com/playlist?list=PLAYLIST_ID" --start 1 --limit 50 --lang en --source any --format srt --out ./data

The playlist command uses yt-dlp flat playlist extraction to collect video entries without the official YouTube Data API, then processes each video with the same metadata and subtitle flow as video. --start is 1-based, --end is inclusive, and --limit caps the selected range. --resume continues only from a matching playlist run manifest, while --skip-existing skips videos only when matching metadata and subtitle files already exist.

Output Layout

data/
  videos/
    VIDEO_ID.info.json
  subtitles/
    VIDEO_ID.en.manual.srt
  normalized/
    VIDEO_ID.en.cue.jsonl
  runs/
    RUN_ID.manifest.json
  failed/
    failed.jsonl

Example cue-level JSONL line:

{"schema_version":"0.1","type":"cue","video_id":"VIDEO_ID","language":"en","source":"manual","start":1.0,"end":3.5,"text":"Example subtitle text.","normalized_text":"example subtitle text","cue_index":1,"channel_id":"channel123","channel_name":"Example Channel","channel_url":"https://www.youtube.com/channel/channel123","video_title":"Example Video","video_url":"https://www.youtube.com/watch?v=VIDEO_ID","video_webpage_url":"https://www.youtube.com/watch?v=VIDEO_ID","video_duration_seconds":320,"video_upload_date":"20260101","available_manual_subtitles":["tr"],"downloaded_subtitles":["tr"],"dataset_category":"education","category_source":"user"}

Sentence-level segmentation uses a simple standard-library heuristic that splits on ., ?, and !. Timing is marked with a strategy such as cue_exact, cue_merge, heuristic, or unknown because sentence boundaries can fall inside or across subtitle cues.

Documentation

File	Purpose
USAGE.md	Usage boundaries, limitations, and responsible use notes
CLI_REFERENCE.md	Commands, flags, behavior, and error codes
OUTPUT_FORMAT.md	Target JSON and JSONL output formats
RELEASE.md	Packaging, Trusted Publishing, and release process
CONTRIBUTING.md	Contributor expectations
SECURITY.md	Security policy and sensitive data rules

Development Install

For local development, use Python 3.11 or newer:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install -e .

This installs yt-dlp>=2026.06.09 as the runtime extractor dependency. Unit tests use fixtures and mocks instead of making real YouTube or network calls.

Smoke-test the current CLI:

ytcap --help
ytcap --version

Installation

Recommended installation from PyPI:

pipx install ytcap

Alternative:

python -m pip install ytcap

Expected usage:

ytcap --help

ytcap video --url "https://www.youtube.com/watch?v=VIDEO_ID" --lang en --source any

License

This project is released under the MIT License. See LICENSE.md for details.