Migration
Migration from youtube-transcript-api
Review request, response and error differences.
Open →Scority vs youtube-transcript-api
Compare Scority's hosted YouTube transcript API with the open-source youtube-transcript-api Python library for transcript workflows.
Direct answer
Use the library for local scripts; use Scority when you need a hosted API
The open-source youtube-transcript-api Python library can be a good fit for local scripts, experiments and teams that want to own the transcript fetching logic. Scority is a hosted API for teams that want API-key auth, normalized responses, quota controls and operational docs.
- Use the library when a Python-only local workflow is enough.
- Use Scority when multiple services or users need a shared HTTP API.
- Use Scority when you want server-side x-api-key auth instead of embedding library logic in each app.
- Neither path guarantees transcripts for every YouTube video.
Open source
Where youtube-transcript-api can fit better
A library can be simpler when you control the runtime and do not need a hosted service boundary.
- Hobby scripts and one-off research tasks.
- Local Python jobs where a direct dependency is easier than an external API.
- Teams comfortable maintaining retries, errors, quota controls and operational handling themselves.
- Projects where hosted API access is not wanted.
Hosted API
Where Scority can fit better
A hosted API is useful when transcript access becomes part of a product or shared workflow.
- Backend services in different languages can use the same HTTP contract.
- API keys, monthly quota and rate-limit headers are part of the platform boundary.
- OpenAPI and human docs describe the contract for developers.
- Quota controls, rate-limit headers and documentation are available through the API surface.
Migration
Migration considerations
Migrating is not a drop-in replacement. Treat it as moving from a Python library call to an HTTP API contract.
- Replace local function calls with GET /v1/youtube/transcript.
- Send x-api-key from server-side code.
- Map response fields: text, segments, source and language.
- Map errors such as transcript_not_available, rate_limited and upstream_transcript_failed.
- Plan quota and caching behavior before moving high-volume jobs.