73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
#!/usr/bin/env python3
|
||
"""计算 L1/L2 用户流失率
|
||
口径（李承龙确认）：
|
||
- 分母：历史上有过学习行为（play_status=1）的用户（按 account_id 去重）
|
||
- 分子：分母中，最后一次学习距今超过 30 天的用户
|
||
- 区分 L1 和 L2 分别计算
|
||
"""
|
||
import os
|
||
import psycopg2
|
||
|
||
PG_HOST = "bj-postgres-16pob4sg.sql.tencentcdb.com"
|
||
PG_PORT = 28591
|
||
PG_USER = "ai_member"
|
||
PG_DB = "vala_bi"
|
||
PG_PASSWORD = os.environ.get("PG_ONLINE_PASSWORD", "")
|
||
|
||
conn = psycopg2.connect(
|
||
host=PG_HOST, port=PG_PORT, user=PG_USER,
|
||
password=PG_PASSWORD, dbname=PG_DB
|
||
)
|
||
cur = conn.cursor()
|
||
|
||
# L1 chapters: 333-581, L2 chapters: 55-331
|
||
level_ranges = {
|
||
"L1": (333, 581),
|
||
"L2": (55, 331),
|
||
}
|
||
|
||
shards = list(range(8))
|
||
|
||
for level, (ch_min, ch_max) in level_ranges.items():
|
||
# Build UNION ALL across all 8 shards
|
||
union_parts = []
|
||
for s in shards:
|
||
union_parts.append(f"""
|
||
SELECT c.account_id, MAX(r.created_at) as last_study
|
||
FROM bi_user_chapter_play_record_{s} r
|
||
JOIN bi_vala_app_character c ON r.user_id = c.id
|
||
WHERE r.play_status = 1
|
||
AND r.chapter_id BETWEEN {ch_min} AND {ch_max}
|
||
GROUP BY c.account_id
|
||
""")
|
||
|
||
union_sql = " UNION ALL ".join(union_parts)
|
||
|
||
# Aggregate across shards: take max last_study per account
|
||
sql = f"""
|
||
WITH all_records AS (
|
||
{union_sql}
|
||
),
|
||
user_last_study AS (
|
||
SELECT account_id, MAX(last_study) as last_study
|
||
FROM all_records
|
||
GROUP BY account_id
|
||
)
|
||
SELECT
|
||
COUNT(*) as total_users,
|
||
COUNT(*) FILTER (WHERE last_study < NOW() - INTERVAL '30 days') as churned_users,
|
||
ROUND(
|
||
100.0 * COUNT(*) FILTER (WHERE last_study < NOW() - INTERVAL '30 days') / COUNT(*),
|
||
1
|
||
) as churn_rate_pct
|
||
FROM user_last_study
|
||
"""
|
||
|
||
cur.execute(sql)
|
||
row = cur.fetchone()
|
||
total, churned, rate = row
|
||
print(f"{level}: 总用户={total}, 流失用户={churned}, 流失率={rate}%")
|
||
|
||
cur.close()
|
||
conn.close()
|