Uyanide/lrx-cli
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: lrclib-search fetcher now do multiple request to cover more cases

Browse Source 
refactor: abstract selection logic & test dafür
This commit is contained in:
Uyanide
2026-04-02 04:00:24 +02:00
parent 5a44f2ba34
commit 9aaf4d8aed
8 changed files with 280 additions and 178 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.claude/resume
-1
View File
@@ -1 +0,0 @@
claude --resume 48d54aac-a89b-48c3-8a76-23e9eb73722d
lrx_cli/fetchers/cache_search.py
+11 -8
View File
@@ -15,6 +15,7 @@ from loguru import logger
from .base import BaseFetcher
from .selection import SearchCandidate, select_best
from ..models import TrackMeta, LyricResult, CacheStatus
from ..cache import CacheEngine
from ..lrc import LRCData
@@ -64,15 +65,17 @@ class CacheSearchFetcher(BaseFetcher):
return None
# Pick best: prefer synced, then first available
best = None
for m in matches:
if m.get("status") == CacheStatus.SUCCESS_SYNCED.value:
best = m
break
if best is None:
best = m
candidates = [
SearchCandidate(
item=m,
is_synced=m.get("status") == CacheStatus.SUCCESS_SYNCED.value,
)
for m in matches
if m.get("lyrics")
]
best = select_best(candidates, track.length)
if not best or not best.get("lyrics"):
if not best:
return None
status = CacheStatus(best["status"])
lrx_cli/fetchers/lrclib_search.py
+76 -74
View File
@@ -15,6 +15,7 @@ from loguru import logger
from urllib.parse import urlencode
from .base import BaseFetcher
from .selection import SearchCandidate, select_best
from ..models import TrackMeta, LyricResult, CacheStatus
from ..lrc import LRCData
from ..config import (
@@ -22,7 +23,6 @@ from ..config import (
TTL_UNSYNCED,
TTL_NOT_FOUND,
TTL_NETWORK_ERROR,
DURATION_TOLERANCE_MS,
LRCLIB_SEARCH_URL,
UA_LRX,
)
@@ -36,6 +36,34 @@ class LrclibSearchFetcher(BaseFetcher):
def is_available(self, track: TrackMeta) -> bool:
return bool(track.title)
def _build_queries(self, track: TrackMeta) -> list[dict[str, str]]:
"""Build up to 4 query param sets, from most specific to least.
1. title + artist + album (if all present)
2. title + artist (if artist present)
3. title + album (if album present)
4. title only
"""
assert track.title is not None
title = track.title
queries: list[dict[str, str]] = []
if track.artist and track.album:
queries.append(
{
"track_name": title,
"artist_name": track.artist,
"album_name": track.album,
}
)
if track.artist:
queries.append({"track_name": title, "artist_name": track.artist})
if track.album:
queries.append({"track_name": title, "album_name": track.album})
queries.append({"track_name": title})
return queries
def fetch(
self, track: TrackMeta, bypass_cache: bool = False
) -> Optional[LyricResult]:
@@ -44,40 +72,68 @@ class LrclibSearchFetcher(BaseFetcher):
logger.debug("LRCLIB-search: skipped — no title")
return None
params: dict[str, str] = {"track_name": track.title}
if track.artist:
params["artist_name"] = track.artist
if track.album:
params["album_name"] = track.album
url = f"{LRCLIB_SEARCH_URL}?{urlencode(params)}"
queries = self._build_queries(track)
logger.info(f"LRCLIB-search: searching for {track.display_name()}")
seen_ids: set[int] = set()
candidates: list[dict] = []
had_error = False
try:
with httpx.Client(timeout=HTTP_TIMEOUT) as client:
resp = client.get(url, headers={"User-Agent": UA_LRX})
for params in queries:
url = f"{LRCLIB_SEARCH_URL}?{urlencode(params)}"
logger.debug(f"LRCLIB-search: query {params}")
resp = client.get(url, headers={"User-Agent": UA_LRX})
if resp.status_code != 200:
logger.error(f"LRCLIB-search: API returned {resp.status_code}")
return LyricResult(
status=CacheStatus.NETWORK_ERROR, ttl=TTL_NETWORK_ERROR
)
if resp.status_code != 200:
logger.error(f"LRCLIB-search: API returned {resp.status_code}")
had_error = True
continue
data = resp.json()
data = resp.json()
if not isinstance(data, list):
continue
if not isinstance(data, list) or len(data) == 0:
for item in data:
if not isinstance(item, dict):
continue
item_id = item.get("id")
if item_id is not None and item_id in seen_ids:
continue
if item_id is not None:
seen_ids.add(item_id)
candidates.append(item)
if not candidates:
if had_error:
return LyricResult(
status=CacheStatus.NETWORK_ERROR, ttl=TTL_NETWORK_ERROR
)
logger.debug(f"LRCLIB-search: no results for {track.display_name()}")
return LyricResult(status=CacheStatus.NOT_FOUND, ttl=TTL_NOT_FOUND)
logger.debug(f"LRCLIB-search: got {len(data)} candidates")
logger.debug(
f"LRCLIB-search: got {len(candidates)} unique candidates "
f"from {len(queries)} queries"
)
# Select best match by duration
best = self._select_best(data, track)
mapped = [
SearchCandidate(
item=item,
duration_ms=item["duration"] * 1000
if isinstance(item.get("duration"), (int, float))
else None,
is_synced=isinstance(item.get("syncedLyrics"), str)
and bool(item["syncedLyrics"].strip()),
)
for item in candidates
]
best = select_best(mapped, track.length)
if best is None:
logger.debug("LRCLIB-search: no valid candidate found")
return LyricResult(status=CacheStatus.NOT_FOUND, ttl=TTL_NOT_FOUND)
# Extract lyrics
synced = best.get("syncedLyrics")
unsynced = best.get("plainLyrics")
@@ -108,57 +164,3 @@ class LrclibSearchFetcher(BaseFetcher):
except Exception as e:
logger.error(f"LRCLIB-search: unexpected error: {e}")
return None
@staticmethod
def _select_best(candidates: list[dict], track: TrackMeta) -> Optional[dict]:
"""Pick the best candidate, preferring synced lyrics and closest duration."""
if track.length is not None:
track_s = track.length / 1000.0
best: Optional[dict] = None
best_diff = float("inf")
for item in candidates:
if not isinstance(item, dict):
continue
duration = item.get("duration")
if not isinstance(duration, (int, float)):
continue
diff = abs(duration - track_s) * 1000 # compare in ms
if diff > DURATION_TOLERANCE_MS:
continue
# Prefer synced over unsynced at similar duration
has_synced = (
isinstance(item.get("syncedLyrics"), str)
and item["syncedLyrics"].strip()
)
best_synced = (
best is not None
and isinstance(best.get("syncedLyrics"), str)
and best["syncedLyrics"].strip()
)
if diff < best_diff or (
diff == best_diff and has_synced and not best_synced
):
best_diff = diff
best = item
if best is not None:
logger.debug(
f"LRCLIB-search: selected id={best.get('id')} (diff={best_diff:.0f}ms)"
)
return best
logger.debug(
f"LRCLIB-search: no candidate within {DURATION_TOLERANCE_MS}ms"
)
return None
# No duration — pick first with synced lyrics, or just first
for item in candidates:
if (
isinstance(item, dict)
and isinstance(item.get("syncedLyrics"), str)
and item["syncedLyrics"].strip()
):
return item
return candidates[0] if isinstance(candidates[0], dict) else None
lrx_cli/fetchers/netease.py
+16 -45
View File
@@ -17,13 +17,13 @@ import httpx
from loguru import logger
from .base import BaseFetcher
from .selection import SearchCandidate, select_best
from ..models import TrackMeta, LyricResult, CacheStatus
from ..lrc import LRCData
from ..config import (
HTTP_TIMEOUT,
TTL_NOT_FOUND,
TTL_NETWORK_ERROR,
DURATION_TOLERANCE_MS,
NETEASE_SEARCH_URL,
NETEASE_LYRIC_URL,
UA_BROWSER,
@@ -84,52 +84,23 @@ class NeteaseFetcher(BaseFetcher):
logger.debug(f"Netease: search returned {len(songs)} candidates")
# Duration-based best-match selection
if track.length is not None:
track_ms = track.length
best_id: Optional[int] = None
best_diff = float("inf")
for song in songs:
if not isinstance(song, dict):
continue
sid = song.get("id")
name = song.get("name", "?")
duration = song.get("dt") # milliseconds
if not isinstance(duration, int):
logger.debug(
f" candidate {sid} '{name}': no duration, skipped"
)
continue
diff = abs(duration - track_ms)
logger.debug(
f" candidate {sid} '{name}': "
f"duration={duration}ms, diff={diff}ms"
)
if diff < best_diff:
best_diff = diff
best_id = sid
if best_id is not None and best_diff <= DURATION_TOLERANCE_MS:
logger.debug(f"Netease: selected id={best_id} (diff={best_diff}ms)")
return best_id
logger.debug(
f"Netease: no candidate within {DURATION_TOLERANCE_MS}ms "
f"(best diff={best_diff}ms)"
candidates = [
SearchCandidate(
item=song.get("id"),
duration_ms=float(song["dt"])
if isinstance(song.get("dt"), int)
else None,
)
return None
for song in songs
if isinstance(song, dict) and song.get("id") is not None
]
best_id = select_best(candidates, track.length)
if best_id is not None:
logger.debug(f"Netease: selected id={best_id}")
return best_id
# No duration info — take the first result
first = songs[0]
if not isinstance(first, dict) or "id" not in first:
logger.error("Netease: first search result has no 'id'")
return None
logger.debug(
f"Netease: no duration available, using first result "
f"id={first['id']} '{first.get('name', '?')}'"
)
return first["id"]
logger.debug("Netease: no suitable candidate found")
return None
except Exception as e:
logger.error(f"Netease: search failed: {e}")
lrx_cli/fetchers/qqmusic.py
+16 -49
View File
@@ -16,13 +16,13 @@ import httpx
from loguru import logger
from .base import BaseFetcher
from .selection import SearchCandidate, select_best
from ..models import TrackMeta, LyricResult, CacheStatus
from ..lrc import LRCData
from ..config import (
HTTP_TIMEOUT,
TTL_NOT_FOUND,
TTL_NETWORK_ERROR,
DURATION_TOLERANCE_MS,
QQ_MUSIC_API_URL,
)
@@ -63,56 +63,23 @@ class QQMusicFetcher(BaseFetcher):
logger.debug(f"QQMusic: search returned {len(songs)} candidates")
# Duration-based best-match selection
if track.length is not None:
track_ms = track.length
best_mid: Optional[str] = None
best_diff = float("inf")
for song in songs:
if not isinstance(song, dict):
continue
mid = song.get("mid")
name = song.get("name", "?")
# interval is in seconds
interval = song.get("interval")
if not isinstance(interval, int):
logger.debug(
f" candidate {mid} '{name}': no duration, skipped"
)
continue
duration_ms = interval * 1000
diff = abs(duration_ms - track_ms)
logger.debug(
f" candidate {mid} '{name}': "
f"duration={duration_ms}ms, diff={diff}ms"
)
if diff < best_diff:
best_diff = diff
best_mid = mid
if best_mid is not None and best_diff <= DURATION_TOLERANCE_MS:
logger.debug(
f"QQMusic: selected mid={best_mid} (diff={best_diff}ms)"
)
return best_mid
logger.debug(
f"QQMusic: no candidate within {DURATION_TOLERANCE_MS}ms "
f"(best diff={best_diff}ms)"
candidates = [
SearchCandidate(
item=song.get("mid"),
duration_ms=float(song["interval"]) * 1000
if isinstance(song.get("interval"), int)
else None,
)
return None
for song in songs
if isinstance(song, dict) and song.get("mid") is not None
]
best_mid = select_best(candidates, track.length)
if best_mid is not None:
logger.debug(f"QQMusic: selected mid={best_mid}")
return best_mid
# No duration info — take the first result
first = songs[0]
if not isinstance(first, dict) or "mid" not in first:
logger.error("QQMusic: first search result has no 'mid'")
return None
logger.debug(
f"QQMusic: no duration available, using first result "
f"mid={first['mid']} '{first.get('name', '?')}'"
)
return first["mid"]
logger.debug("QQMusic: no suitable candidate found")
return None
except Exception as e:
logger.error(f"QQMusic: search failed: {e}")
lrx_cli/fetchers/selection.py
+68
View File
@@ -0,0 +1,68 @@
"""
Shared candidate-selection logic for search-based fetchers.
Each fetcher maps its API-specific results to SearchCandidate, then calls
select_best() which handles duration filtering and synced preference uniformly.
"""
from dataclasses import dataclass
from typing import Generic, Optional, TypeVar
from ..config import DURATION_TOLERANCE_MS
T = TypeVar("T")
@dataclass
class SearchCandidate(Generic[T]):
"""A normalized search result for best-match selection.
Attributes:
item: The original API-specific object (dict, ID, etc.)
duration_ms: Track duration in milliseconds, or None if unknown.
is_synced: Whether this candidate is known to have synced lyrics.
"""
item: T
duration_ms: Optional[float] = None
is_synced: bool = False
def select_best(
candidates: list[SearchCandidate[T]],
track_length_ms: Optional[int] = None,
tolerance_ms: float = DURATION_TOLERANCE_MS,
) -> Optional[T]:
"""Pick the best candidate by duration proximity and sync preference.
When track_length_ms is available:
- Filter by tolerance_ms
- Pick closest duration, prefer synced at equal distance
When track_length_ms is unavailable:
- Pick first synced candidate, or first overall
"""
if track_length_ms is not None:
best: Optional[SearchCandidate[T]] = None
best_diff = float("inf")
for c in candidates:
if c.duration_ms is None:
continue
diff = abs(c.duration_ms - track_length_ms)
if diff > tolerance_ms:
continue
if diff < best_diff or (
diff == best_diff
and c.is_synced
and (best is None or not best.is_synced)
):
best_diff = diff
best = c
return best.item if best is not None else None
# No duration — prefer synced, fallback to first
for c in candidates:
if c.is_synced:
return c.item
return candidates[0].item if candidates else None
tests/test_selection.py
+92
View File
@@ -0,0 +1,92 @@
from __future__ import annotations
from lrx_cli.fetchers.selection import SearchCandidate, select_best
def test_picks_closest_duration_within_tolerance() -> None:
candidates = [
SearchCandidate(item="far", duration_ms=10000.0),
SearchCandidate(item="close", duration_ms=5100.0),
SearchCandidate(item="exact", duration_ms=5000.0),
]
assert select_best(candidates, track_length_ms=5000) == "exact"
def test_filters_out_candidates_beyond_tolerance() -> None:
candidates = [
SearchCandidate(item="too_far", duration_ms=100000.0),
]
assert select_best(candidates, track_length_ms=5000, tolerance_ms=2000) is None
def test_prefers_synced_at_equal_duration() -> None:
candidates = [
SearchCandidate(item="unsynced", duration_ms=5000.0, is_synced=False),
SearchCandidate(item="synced", duration_ms=5000.0, is_synced=True),
]
assert select_best(candidates, track_length_ms=5000) == "synced"
def test_closer_duration_wins_over_synced() -> None:
candidates = [
SearchCandidate(item="synced_far", duration_ms=6000.0, is_synced=True),
SearchCandidate(item="unsynced_close", duration_ms=5001.0, is_synced=False),
]
assert select_best(candidates, track_length_ms=5000) == "unsynced_close"
def test_skips_candidates_without_duration_when_track_length_given() -> None:
candidates = [
SearchCandidate(item="no_dur", duration_ms=None),
SearchCandidate(item="has_dur", duration_ms=5000.0),
]
assert select_best(candidates, track_length_ms=5000) == "has_dur"
def test_returns_none_when_all_lack_duration_and_track_length_given() -> None:
candidates = [
SearchCandidate(item="a", duration_ms=None),
SearchCandidate(item="b", duration_ms=None),
]
assert select_best(candidates, track_length_ms=5000) is None
def test_prefers_synced_when_no_track_length() -> None:
candidates = [
SearchCandidate(item="unsynced", is_synced=False),
SearchCandidate(item="synced", is_synced=True),
]
assert select_best(candidates, track_length_ms=None) == "synced"
def test_falls_back_to_first_when_none_synced() -> None:
candidates = [
SearchCandidate(item="first"),
SearchCandidate(item="second"),
]
assert select_best(candidates, track_length_ms=None) == "first"
def test_empty_candidates_returns_none() -> None:
assert select_best([], track_length_ms=5000) is None
assert select_best([], track_length_ms=None) is None
def test_single_candidate_within_tolerance() -> None:
candidates = [SearchCandidate(item="only", duration_ms=5000.0)]
assert select_best(candidates, track_length_ms=5000) == "only"
def test_single_candidate_beyond_tolerance() -> None:
candidates = [SearchCandidate(item="only", duration_ms=99999.0)]
assert select_best(candidates, track_length_ms=5000, tolerance_ms=1000) is None
def test_generic_type_preserved() -> None:
"""select_best returns the same type as SearchCandidate.item."""
int_candidates = [SearchCandidate(item=42, duration_ms=5000.0)]
assert select_best(int_candidates, track_length_ms=5000) == 42
dict_candidates = [SearchCandidate(item={"id": 1}, duration_ms=5000.0)]
result = select_best(dict_candidates, track_length_ms=5000)
assert result == {"id": 1}
uv.lock
Generated
+1 -1
View File
@@ -153,7 +153,7 @@ wheels = [
[[package]]
name = "lrx-cli"
version = "0.2.0"
version = "0.2.1"
source = { editable = "." }
dependencies = [
{ name = "cyclopts" },