49 lines
1.2 KiB
Python
49 lines
1.2 KiB
Python
from surprise import Dataset, SVD
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import numpy as np
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import pandas as pd
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import sqlite3
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from lightfm import LightFM
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from lightfm.datasets import fetch_movielens
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c = sqlite3.connect("./prisma/dev.db")
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df = pd.read_sql_query(
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"""
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SELECT
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s1.user_id as user_id,
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s1.beatmap_id as before_beatmap_id,
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s2.beatmap_id as after_beatmap_id,
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ms_between
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FROM Transition as t
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JOIN Score as s1 ON s1.id = t.before_id
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JOIN Score as s2 ON s2.id = t.after_id
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""",
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c,
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)
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print(df)
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# Beatmaps with most data:
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"""
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SELECT
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beatmapset_id, artist, title, COUNT(*) as count
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FROM Score
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JOIN BeatmapSet ON Score.beatmapset_id = BeatmapSet.id
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GROUP BY beatmapset_id
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ORDER BY count DESC;
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"""
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# Given a specific beatmap, what maps do they go on to
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"""
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SELECT
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bs1.artist, bs1.title, b1.difficulty, bs2.artist, bs2.title, b2.difficulty, COUNT(*) as count
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FROM Transition
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JOIN Score as s1 ON s1.id = Transition.before_id
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JOIN Score as s2 ON s2.id = Transition.after_id
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JOIN Beatmap as b1 on s1.beatmap_id = b1.id
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JOIN BeatmapSet as bs1 on s1.beatmapset_id = bs1.id
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JOIN Beatmap as b2 on s2.beatmap_id = b2.id
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JOIN BeatmapSet as bs2 on s2.beatmapset_id = bs2.id
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WHERE s1.beatmapset_id = 320118
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GROUP BY s2.beatmap_id
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ORDER BY count DESC;
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"""
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