109 lines
3.9 KiB
Python
109 lines
3.9 KiB
Python
#!/usr/bin/env python3
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"""流失用户最后完课 Lesson 分布 — 拆成 U00 和 U01+ 各一张"""
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import os, psycopg2
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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import matplotlib.ticker as ticker
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import numpy as np
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PG_HOST = "bj-postgres-16pob4sg.sql.tencentcdb.com"
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PG_PORT = 28591
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PG_USER = "ai_member"
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PG_DB = "vala_bi"
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PG_PASSWORD = os.environ.get("PG_ONLINE_PASSWORD", "")
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conn = psycopg2.connect(host=PG_HOST, port=PG_PORT, user=PG_USER, password=PG_PASSWORD, dbname=PG_DB)
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cur = conn.cursor()
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level_ranges = {"L1": (333, 581), "L2": (55, 331)}
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shards = list(range(8))
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plt.rcParams['font.sans-serif'] = ['WenQuanYi Micro Hei', 'SimHei', 'Noto Sans CJK SC', 'DejaVu Sans']
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plt.rcParams['axes.unicode_minus'] = False
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for level, (ch_min, ch_max) in level_ranges.items():
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union_parts = []
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for s in shards:
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union_parts.append(f"""
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SELECT c.account_id, r.chapter_id, r.created_at
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FROM bi_user_chapter_play_record_{s} r
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JOIN bi_vala_app_character c ON r.user_id = c.id
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WHERE r.play_status = 1
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AND r.chapter_id BETWEEN {ch_min} AND {ch_max}
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""")
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union_sql = " UNION ALL ".join(union_parts)
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sql = f"""
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WITH all_records AS ({union_sql}),
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user_last AS (
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SELECT DISTINCT ON (account_id) account_id, chapter_id, created_at as last_study
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FROM all_records
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ORDER BY account_id, created_at DESC
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),
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churned AS (
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SELECT account_id, chapter_id FROM user_last
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WHERE last_study < NOW() - INTERVAL '30 days'
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)
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SELECT l.course_unit, l.course_lesson, COUNT(*) as cnt
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FROM churned c
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JOIN bi_level_unit_lesson l ON c.chapter_id = l.id
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GROUP BY l.course_unit, l.course_lesson
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ORDER BY l.course_unit, l.course_lesson
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"""
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cur.execute(sql)
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rows = cur.fetchall()
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data_map = {}
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for unit, lesson, cnt in rows:
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data_map[f"{unit}_{lesson}"] = cnt
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cur.execute(f"SELECT course_unit, course_lesson FROM bi_level_unit_lesson WHERE course_level='{level}' ORDER BY course_unit, course_lesson")
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all_lessons = cur.fetchall()
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# Split into U00 and U01+
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u00_lessons = [(u, l) for u, l in all_lessons if u == 'U00']
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u01p_lessons = [(u, l) for u, l in all_lessons if u != 'U00']
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for suffix, lessons in [("U00", u00_lessons), ("U01+", u01p_lessons)]:
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labels = [f"{u}_{l}" for u, l in lessons]
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values = [data_map.get(f"{u}_{l}", 0) for u, l in lessons]
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# Build unit tick positions
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x_ticks = []
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x_tick_labels = []
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prev_unit = None
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for i, (u, l) in enumerate(lessons):
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if u != prev_unit:
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x_ticks.append(i)
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x_tick_labels.append(u)
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prev_unit = u
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fig, ax = plt.subplots(figsize=(14 if suffix == "U00" else 18, 5))
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color = '#E74C3C' if level == 'L1' else '#3498DB'
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x = range(len(labels))
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ax.plot(x, values, color=color, linewidth=1.5, marker='o', markersize=3)
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# Add value labels on top of each point
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for xi, vi in zip(x, values):
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if vi > 0:
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ax.annotate(str(vi), (xi, vi), textcoords="offset points", xytext=(0, 5),
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fontsize=6, ha='center', color='#555')
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ax.set_xticks(x_ticks)
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ax.set_xticklabels(x_tick_labels, fontsize=9, rotation=0)
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ax.set_ylabel('流失人数', fontsize=11)
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ax.set_title(f'{level} 流失用户最后完课 Lesson 分布 — {suffix}', fontsize=14, fontweight='bold')
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ax.set_xlim(-0.5, len(labels) - 0.5)
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ax.grid(axis='y', alpha=0.3)
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ax.yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
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plt.tight_layout()
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out_path = f'/root/.openclaw/workspace/output/churn_lesson_{level}_{suffix}.png'
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plt.savefig(out_path, dpi=150)
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plt.close()
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print(f"Saved: {out_path}")
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cur.close()
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conn.close()
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print("Done.")
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