deezer-python-gql 0.5.1

Async typed Python client for Deezer's Pipe GraphQL API.

deezer-python-gql

Async typed Python client for Deezer's Pipe GraphQL API.

Built with ariadne-codegen — all client methods and response models are generated from the GraphQL schema and .graphql query files.

Installation

uv add deezer-python-gql

Quick Start

import asyncio

from deezer_python_gql import DeezerGQLClient

async def main():
    client = DeezerGQLClient(arl="YOUR_ARL_COOKIE")

    # Current user
    me = await client.get_me()
    print(me)

    # Track with media URLs, lyrics, and contributors
    track = await client.get_track(track_id="3135556")
    print(track.title, track.duration)

    # Album with paginated track list
    album = await client.get_album(album_id="302127")
    print(album.display_title, album.tracks_count)

    # Artist with top tracks and discography
    artist = await client.get_artist(artist_id="27")
    print(artist.name, artist.fans_count)

    # Playlist with tracks
    playlist = await client.get_playlist(playlist_id="53362031")
    print(playlist.title, playlist.estimated_tracks_count)

    # Unified search across all entity types
    results = await client.search(query="Daft Punk")
    print(len(results.tracks.edges), "tracks found")

asyncio.run(main())

Available Queries

Method	Description
get_me()	Current authenticated user
get_track(track_id)	Full track details — ISRC, media tokens, lyrics, contributors
get_album(album_id)	Album with cover, label, paginated tracks, fallback
get_artist(artist_id)	Artist with bio, top tracks, albums (ordered by release date)
get_playlist(playlist_id)	Playlist with owner, picture, paginated tracks
search(query, ...)	Unified search across tracks, albums, artists, playlists
get_flow()	User's default Flow with tracks
get_flow_configs(moods_first, genres_first)	Mood & genre flow config lists for discovery
get_flow_config_tracks(flow_config_id)	Tracks for a specific mood/genre flow config
get_made_for_me(first)	"Made For You" SmartTracklist & Flow items
get_smart_tracklist(smart_tracklist_id, first)	Smart tracklist with paginated tracks
get_charts(country_code, ...)	Country charts — tracks, albums, artists, playlists
get_recommendations(playlists_first, ...)	Personalized recommendations across categories
get_recently_played(first)	Recently played mixed content (albums, playlists, artists...)
get_favorite_artists(first, after)	Paginated favorite artists
get_favorite_albums(first, after)	Paginated favorite albums
get_favorite_tracks(first, after)	Paginated favorite tracks
get_favorite_playlists(first, after)	Paginated favorite playlists

All methods return fully-typed Pydantic models generated from the GraphQL schema.

Development

Requires Python 3.12+ and uv.

# Install all dependencies (including codegen tooling)
make setup

# Re-generate the typed client from schema + queries
make generate

# Run linters and type checks
make lint

# Run tests
make test

Adding a new query

1. Create a .graphql file in queries/.
2. Run make generate to produce the typed client method and response models.
3. Add tests in tests/.

Exploring the API

To run ad-hoc GraphQL queries against the live Pipe API during development:

1. Create a .env file (already gitignored) with your ARL cookie:

   echo 'DEEZER_ARL=your_arl_cookie_value' > .env
   

2. Run queries:

   # Run a .graphql file
   uv run python scripts/explore.py queries/get_me.graphql
   
   # Run an inline query
   uv run python scripts/explore.py -q '{ me { id } }'
   
   # With variables
   uv run python scripts/explore.py -q 'query($id: String!) { track(trackId: $id) { title } }' \
       -v '{"id": "3135556"}'
   
   # Via make
   make explore Q=queries/get_me.graphql
   

The script handles JWT auth automatically — no manual token management needed.

Authentication

The Pipe API uses short-lived JWTs obtained from an ARL cookie. The base client handles token acquisition and refresh automatically — you only need to supply a valid ARL value.

License

Apache-2.0