mirror of
https://github.com/simon987/music-graph-scripts.git
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103 lines
3.1 KiB
Python
103 lines
3.1 KiB
Python
import csv
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import json
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import sqlite3
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from collections import defaultdict
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import sys
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artists = set()
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def disambiguate(lfm_artist, artist_release_count, name, mbid):
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existing_mbid = lfm_artist.get(name, None)
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if existing_mbid and mbid != existing_mbid:
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if artist_release_count[existing_mbid] < artist_release_count[mbid]:
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lfm_artist[name] = mbid
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# print("Replacing %s (%s) with %s (%d) for %s" %
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# (existing_mbid, artist_release_count[existing_mbid],
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# mbid, artist_release_count[mbid],
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# name))
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else:
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lfm_artist[name] = mbid
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def patch(lastfm_data):
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artist_listeners = dict()
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lastfm_artist_to_mbid = dict()
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artist_release_count = defaultdict(int)
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related = list()
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with open("repo/artist_release.csv") as f:
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for line in f:
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cols = line.split(',')
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artist_release_count[cols[0]] += 1
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with sqlite3.connect(lastfm_data) as conn:
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cur = conn.cursor()
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cur.execute("SELECT data FROM lastfmdata", )
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data = list(cur.fetchall())
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# A lastfm artist name can refer to multiple MBIDs
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# For RELATED_TO purposes, we assume that the MBID referring
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# to the artist with the most official releases is the one
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for row in data:
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meta = json.loads(row[0])
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disambiguate(lastfm_artist_to_mbid, artist_release_count, meta["name"], meta["artist"])
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for similar in [s for s in meta["similar"] if s["mbid"] is not None]:
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disambiguate(lastfm_artist_to_mbid, artist_release_count, similar["name"], similar["mbid"])
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# Get related links & listener counts
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for row in data:
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meta = json.loads(row[0])
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artist_listeners[lastfm_artist_to_mbid[meta["name"]]] = \
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(meta["listeners"], meta["playcount"])
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for similar in [s for s in meta["similar"] if s["mbid"] is not None]:
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related.append((
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lastfm_artist_to_mbid[similar["name"]],
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lastfm_artist_to_mbid[meta["name"]],
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similar["match"]
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))
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with open("repo/lastfm_artist.csv", "w") as out:
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writer = csv.writer(out)
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writer.writerow([
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"id:ID(Artist)", "name", "sortname", "year:short", "comment", ":LABEL", "listeners:int", "playcount:int"
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])
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with open("repo/artist.csv") as f:
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reader = csv.reader(f)
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reader.__next__() # Skip header
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for row in reader:
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writer.writerow([
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row[0],
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row[1],
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row[2],
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row[3],
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row[4],
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row[5],
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artist_listeners.get(row[0], (0, 0))[0],
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artist_listeners.get(row[0], (0, 0))[1],
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])
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artists.add(row[0])
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with open("repo/lastfm_artist_artist.csv", "w") as out:
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out.write(",".join((
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":START_ID(Artist)", ":END_ID(Artist)", "weight:float"
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)) + "\n")
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for x in related:
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if x[0] in artists and x[1] in artists:
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out.write(",".join(x) + "\n")
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patch(sys.argv[1])
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