Self-hosted personal YouTube management app. FastAPI + SQLite backend, React + Vite + Tailwind frontend. Dockerfiles and compose included for Portainer deployment. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
145 lines
4.8 KiB
Python
145 lines
4.8 KiB
Python
from fastapi import APIRouter, Depends
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from sqlalchemy.orm import Session
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from sqlalchemy import text
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from ..auth_utils import get_current_user
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from ..database import get_db
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from ..models import User
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router = APIRouter()
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@router.get("")
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def get_stats(
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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uid = current_user.id
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totals = db.execute(
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text("""
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SELECT
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COUNT(*) AS total_watched,
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SUM(uv.watch_progress_seconds) AS total_watch_seconds
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FROM user_videos uv
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WHERE uv.user_id = :uid AND uv.watched = 1
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"""),
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{"uid": uid},
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).mappings().first()
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top_channels = db.execute(
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text("""
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SELECT c.id, c.name,
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COUNT(*) AS watch_count,
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SUM(uv.watch_progress_seconds) AS watch_seconds
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FROM user_videos uv
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JOIN videos v ON uv.video_id = v.id
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JOIN channels c ON v.channel_id = c.id
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WHERE uv.user_id = :uid AND uv.watched = 1
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GROUP BY c.id, c.name
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ORDER BY watch_seconds DESC
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LIMIT 10
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"""),
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{"uid": uid},
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).mappings().all()
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daily = db.execute(
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text("""
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SELECT date(uv.last_watched_at) AS date,
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COUNT(*) AS count,
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SUM(uv.watch_progress_seconds) AS seconds
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FROM user_videos uv
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WHERE uv.user_id = :uid
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AND uv.watched = 1
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AND uv.last_watched_at >= datetime('now', '-30 days')
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GROUP BY date(uv.last_watched_at)
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ORDER BY date ASC
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"""),
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{"uid": uid},
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).mappings().all()
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this_week = db.execute(
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text("""
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SELECT COUNT(*) AS count, SUM(uv.watch_progress_seconds) AS seconds
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FROM user_videos uv
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WHERE uv.user_id = :uid AND uv.watched = 1
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AND uv.last_watched_at >= datetime('now', '-7 days')
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"""),
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{"uid": uid},
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).mappings().first()
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this_month = db.execute(
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text("""
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SELECT COUNT(*) AS count, SUM(uv.watch_progress_seconds) AS seconds
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FROM user_videos uv
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WHERE uv.user_id = :uid AND uv.watched = 1
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AND uv.last_watched_at >= datetime('now', '-30 days')
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"""),
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{"uid": uid},
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).mappings().first()
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avg_completion = db.execute(
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text("""
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SELECT AVG(uv.completion_percent) AS avg_pct,
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COUNT(CASE WHEN uv.completion_percent >= 90 THEN 1 END) AS finished_count,
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COUNT(CASE WHEN uv.completion_percent < 20 AND uv.completion_percent IS NOT NULL THEN 1 END) AS bailed_count,
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SUM(uv.rewatch_count) AS total_rewatches,
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COUNT(CASE WHEN uv.rewatch_count > 0 THEN 1 END) AS rewatched_videos
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FROM user_videos uv
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WHERE uv.user_id = :uid AND uv.watched = 1
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"""),
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{"uid": uid},
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).mappings().first()
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top_categories = db.execute(
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text("""
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SELECT v.category, COUNT(*) AS watch_count,
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AVG(uv.completion_percent) AS avg_completion
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FROM user_videos uv
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JOIN videos v ON uv.video_id = v.id
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WHERE uv.user_id = :uid AND uv.watched = 1 AND v.category IS NOT NULL
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GROUP BY v.category
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ORDER BY watch_count DESC
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LIMIT 8
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"""),
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{"uid": uid},
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).mappings().all()
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taste_profile = db.execute(
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text("""
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SELECT tag, score FROM user_tag_affinity
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WHERE user_id = :uid AND score > 0
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ORDER BY score DESC
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LIMIT 20
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"""),
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{"uid": uid},
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).mappings().all()
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liked_count = db.execute(
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text("SELECT COUNT(*) AS n FROM user_videos WHERE user_id = :uid AND liked = 1"),
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{"uid": uid},
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).mappings().first()
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return {
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"total_watched": totals["total_watched"] or 0,
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"total_watch_seconds": totals["total_watch_seconds"] or 0,
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"top_channels": [dict(r) for r in top_channels],
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"daily": [dict(r) for r in daily],
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"this_week": {
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"count": this_week["count"] or 0,
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"seconds": this_week["seconds"] or 0,
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},
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"this_month": {
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"count": this_month["count"] or 0,
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"seconds": this_month["seconds"] or 0,
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},
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"avg_completion_percent": round(avg_completion["avg_pct"] or 0, 1),
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"finished_count": avg_completion["finished_count"] or 0,
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"bailed_count": avg_completion["bailed_count"] or 0,
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"total_rewatches": avg_completion["total_rewatches"] or 0,
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"rewatched_videos": avg_completion["rewatched_videos"] or 0,
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"total_liked": liked_count["n"] or 0,
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"top_categories": [dict(r) for r in top_categories],
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"taste_profile": [dict(r) for r in taste_profile],
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}
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