17 KiB
Plex Media Library Statistics Generator
A production-quality Python 3 command-line tool for scanning Plex-style media libraries and generating CSV statistics about storage size versus total video duration.
Purpose
This tool analyzes media libraries (TV shows, anime, and movies) without requiring Plex itself or the Plex API. It operates directly on the filesystem and generates CSV reports showing:
- Storage size (in bytes and GB)
- Total video duration (in seconds and hours)
- Storage efficiency (GB per hour of video)
The key innovation is incremental scanning with SQLite caching: after the first full scan, subsequent scans are fast because unchanged files are never re-probed with FFmpeg.
Features
- ✅ Supports TV shows, anime (treated as TV), and movies
- ✅ Automatic library type detection (override with
--type) - ✅ Persistent SQLite cache with change detection
- ✅ Fast incremental scans using file size + mtime signatures
- ✅ Comprehensive error handling (one bad file doesn't break the scan)
- ✅ Progress output during scanning and probing
- ✅ CSV output sorted alphabetically by series/movie
- ✅ Support for multiple libraries in a single database
- ✅ Per-video metadata stored for future feature expansion
Requirements
System
- Linux (though Windows/macOS paths would work with minor adjustments)
- Python 3.10+
- FFmpeg with
ffprobeinstalled
Python
Only Python standard library is used:
argparse(CLI argument parsing)pathlib(filesystem operations)sqlite3(caching)subprocess(invoking ffprobe)csv(output generation)
Installation
Ubuntu / Debian
# Install FFmpeg
sudo apt update
sudo apt install ffmpeg
# Clone or download the tool
cd /path/to/media-scrapper
# Make the script executable (optional)
chmod +x plex_stats.py
# Test that ffprobe works
ffprobe -version
CentOS / RHEL
sudo yum install ffmpeg
macOS (using Homebrew)
brew install ffmpeg
Quick Start
Scan a TV library
python3 plex_stats.py /plex/tv --type tv --csv-prefix tv
Output:
tv_seasons.csv— one row per seasontv_series.csv— one row per complete seriesplex_stats.db— SQLite cache
Scan an anime library
python3 plex_stats.py /plex/anime --type tv --csv-prefix anime
TV and anime use the same directory structure and CSV format.
Scan a movies library
python3 plex_stats.py /plex/movies --type movies --csv-prefix movies
Output:
movies_movies.csv— one row per movie folder
Re-scan (fast)
Run the same command again. Files that haven't changed will be cached and won't be re-probed:
python3 plex_stats.py /plex/tv --type tv --csv-prefix tv
Expected output:
Scanning /plex/tv...
Files discovered: 4,812
Cached/unchanged: 4,790
New: 17
Changed: 5
Removed: 3
Probing 22 files...
[1/22] Breaking Bad...
[2/22] Game of Thrones...
...
Scan complete.
TV shows: 163
Seasons: 691
Video files: 4,809
Total size: 6.82 TB
Total runtime: 3,921.4 hours
Unchanged: 4,790
New: 14
Changed: 5
Removed: 3
Errors: 0
CSV files written:
tv_seasons.csv
tv_series.csv
Database:
plex_stats.db
CLI Options
usage: plex_stats.py [-h] [--type {tv,movies}] [--db DB]
[--output-dir OUTPUT_DIR] [--csv-prefix CSV_PREFIX]
[--force] [--verbose]
library_root
positional arguments:
library_root Path to media library root (e.g. /plex/tv)
optional arguments:
-h, --help show help message
--type {tv,movies} Library type. If omitted, inferred from directory name.
--db DB Path to SQLite database (default: plex_stats.db)
--output-dir OUTPUT Directory for CSV files (default: current directory)
--csv-prefix PREFIX Prefix for CSV filenames (default: derived from root name)
--force Force ffprobe scan of all files (ignore cache)
--verbose Print verbose output
Usage Examples
Basic single-library scan
python3 plex_stats.py /plex/tv
Infers type as "tv", creates plex_stats.db in current directory, outputs tv_seasons.csv and tv_series.csv.
All three libraries with explicit prefixes
python3 plex_stats.py /plex/tv --type tv --csv-prefix tv
python3 plex_stats.py /plex/anime --type tv --csv-prefix anime
python3 plex_stats.py /plex/movies --type movies --csv-prefix movies
All use the same plex_stats.db, creating six CSV files:
tv_seasons.csv,tv_series.csvanime_seasons.csv,anime_series.csvmovies_movies.csv
Centralized database and output directory
python3 plex_stats.py /plex/tv \
--type tv \
--db /var/lib/plex-stats/plex_stats.db \
--output-dir /home/user/plex-reports \
--csv-prefix tv
Force complete re-scan (e.g., after fixing bad ffprobe issues)
python3 plex_stats.py /plex/tv --force
Every file is re-probed. Useful if you suspect cache corruption or want to update all durations.
Verbose output
python3 plex_stats.py /plex/tv --verbose
Directory Structure
TV / Anime
/plex/tv/
├── Breaking Bad/ <- Series name (first directory level)
│ ├── Season 01/ <- Season folder (second level)
│ │ ├── Breaking Bad - S01E01.mkv
│ │ ├── Breaking Bad - S01E02.mkv
│ │ └── ...
│ ├── Season 02/
│ │ └── ...
│ └── Specials/ <- Any season name is recognized
├── Game of Thrones/
│ ├── Season 01/
│ │ └── ...
│ └── Season 02/
│ └── ...
Season folder names are flexible:
Season 01,Season 1Season 00(for pilots/specials)Specials,SpecialS01,S1
The actual folder name found on disk is preserved in the CSV output.
Movies
/plex/movies/
├── Dune (2021)/ <- Movie name (first directory level)
│ └── Dune (2021).mkv
├── Interstellar (2014)/
│ ├── Interstellar (2014).mkv
│ └── Interstellar (2014) - Extras.mkv <- Multiple files per movie are aggregated
Recognized Video Extensions
The tool recognizes these file extensions (case-insensitive):
.mkv,.mp4,.m4v,.avi,.mov.ts,.m2ts,.webm.mpg,.mpeg,.wmv
Other files (subtitles, .srt, .sub, .idx, .nfo, images, metadata) are ignored.
CSV Output Format
TV Seasons (*_seasons.csv)
One row per season of a TV series:
Library,Series,Season,File_Count,Size_Bytes,Size_GB,Duration_Seconds,Duration_Hours,GB_Per_Hour
tv,Breaking Bad,Season 01,7,13786845020,12.84,20952,5.82,2.21
tv,Breaking Bad,Season 02,13,25887942819,24.11,38628,10.73,2.25
tv,Breaking Bad,Season 03,13,26943589405,25.10,38628,10.73,2.34
tv,Game of Thrones,Season 01,10,47129348901,43.91,41932,11.65,3.77
tv,Game of Thrones,Season 02,10,45219374812,42.13,41932,11.65,3.61
- Library: Always "tv" for TV/anime
- Series: Show name
- Season: Season folder name as found on disk
- File_Count: Number of video files in this season
- Size_Bytes: Total bytes (numeric, for calculation)
- Size_GB: Decimal gigabytes (1 GB = 1,000,000,000 bytes)
- Duration_Seconds: Total duration in seconds
- Duration_Hours: Total duration in hours
- GB_Per_Hour: Storage efficiency (size / duration)
TV Series (*_series.csv)
One row per complete series, summing all seasons:
Library,Series,Season_Count,File_Count,Size_Bytes,Size_GB,Duration_Seconds,Duration_Hours,GB_Per_Hour
tv,Breaking Bad,5,62,128608176245,119.88,191500,53.19,2.25
tv,Game of Thrones,8,80,434328947123,404.56,334656,92.96,4.35
- Season_Count: Number of seasons in the series
- Other fields aggregate across all seasons
Movies (*_movies.csv)
One row per movie:
Library,Movie,File_Count,Size_Bytes,Size_GB,Duration_Seconds,Duration_Hours,GB_Per_Hour
movies,Dune (2021),1,4829348901,4.50,10680,2.97,1.51
movies,Interstellar (2014),2,6234919234,5.81,14400,4.00,1.45
- Movie: Movie folder name
- File_Count: Number of video files under the movie folder (includes extras)
- Other fields aggregate all files
CSV Import to Google Sheets
All numeric columns remain numeric (not formatted as strings), so they import cleanly into Google Sheets:
- Open Google Sheets
- Click "File" > "Import" > "Upload"
- Select the CSV file
- Choose "Replace spreadsheet"
- Numeric columns are automatically detected
SQLite Cache Database
Schema
The tool automatically creates and maintains a SQLite database with this schema:
CREATE TABLE media_files (
id INTEGER PRIMARY KEY AUTOINCREMENT,
path TEXT UNIQUE NOT NULL,
library_root TEXT NOT NULL,
library_type TEXT NOT NULL,
show_movie TEXT NOT NULL,
season TEXT,
size_bytes INTEGER NOT NULL,
mtime_ns INTEGER NOT NULL,
duration_seconds REAL,
scan_timestamp REAL NOT NULL,
error_message TEXT
);
CREATE INDEX idx_library_root ON media_files(library_root);
CREATE INDEX idx_path ON media_files(path);
CREATE INDEX idx_show_movie ON media_files(show_movie);
CREATE INDEX idx_season ON media_files(season);
Per-Video Storage
Every video file is stored individually, not just aggregated season/movie totals. This enables future features like:
- Per-episode statistics
- Codec and resolution analysis
- Average file size per series
- Duplicate detection
- Video quality metrics
Change Detection & Incremental Scanning
How It Works
- File discovery: Walk the filesystem and list all video files.
- Stat check: For each file, read
stat()to get size and modification time. - Cache lookup: Check SQLite for this file's cached entry.
- Decision logic:
- If cached entry exists AND size and mtime match → Reuse cache (no ffprobe)
- If cached entry exists BUT size or mtime differs → Re-probe (file changed)
- If no cached entry → Probe (new file)
- If cached entry is in SQLite BUT file no longer exists → Delete from cache
Why Size + mtime?
- Size: Detects if video content changed
- mtime (modification time): Detects if metadata or the file was touched
- Together: Extremely fast check without hashing or reading file content
- Safe: Works reliably for normal media workflows (copying files, minor edits)
Limitations
If you manually edit file bytes without updating mtime (unusual), the cache will not detect it. This is acceptable for media libraries.
Handling Unchanged, New, and Changed Files
Unchanged
ffprobe not called → instant retrieval from cache
New
File doesn't exist in cache → ffprobe called → database entry created
Changed
File exists but size_bytes or mtime_ns differs → ffprobe called → database entry updated
Removed
Cached file path no longer exists → removed from database
Note: Only scanned library root is checked.
Other libraries' files are not affected.
Forced Rescans
Use --force to ignore the cache and re-probe every file:
python3 plex_stats.py /plex/tv --force
This is useful if:
- You suspect cache corruption
- FFmpeg was updated and you want fresh probes
- You want to update all durations to the latest ffprobe version
Forced rescans still respect the database schema and update all cached entries.
Error Handling
FFprobe Failures
If ffprobe fails on a specific file:
- A warning is printed to console
- The error is recorded in the database (
error_messagecolumn) - The scan continues with other files
- The file is eligible for retry on future scans
What's Not an Error
- Permission denied reading a file → warning, continue
- Corrupted video file → ffprobe fails, recorded, continue
- Network timeouts on NFS → handled, continue
Error Summary
At scan completion, total error count is displayed:
Errors: 5
To see details, query the database:
sqlite3 plex_stats.db "SELECT path, error_message FROM media_files WHERE error_message IS NOT NULL;"
Database Management
View cached files for a library
sqlite3 plex_stats.db "SELECT COUNT(*) FROM media_files WHERE library_root = '/plex/tv';"
Export all files for a series
sqlite3 plex_stats.db "SELECT path, size_bytes, duration_seconds FROM media_files WHERE show_movie = 'Breaking Bad';"
Clear all cache for one library
sqlite3 plex_stats.db "DELETE FROM media_files WHERE library_root = '/plex/tv';"
sqlite3 plex_stats.db "VACUUM;" # Reclaim disk space
Clear entire database
rm plex_stats.db
The tool will recreate it on the next run.
Performance Tips
- First scan is slow: Thousands of ffprobe calls can take 10–30 minutes for large libraries.
- Subsequent scans are fast: Usually under a minute if only a few files changed.
- Use
--forcesparingly: Only when you have a specific reason. - Database is small: Even for 10,000+ files, SQLite database is typically < 1 MB.
- CSV generation is instant: All heavy lifting is in the scanning phase.
Estimated Timeline
- 1,000 files: 3–10 minutes (first scan), 10–30 seconds (subsequent)
- 5,000 files: 15–50 minutes (first scan), 30–60 seconds (subsequent)
- 10,000 files: 30–90 minutes (first scan), 1–2 minutes (subsequent)
Varies based on filesystem speed, network latency (NFS/SMB), and average file size.
Multiple Libraries in One Database
All three examples below use the same plex_stats.db:
python3 plex_stats.py /plex/tv --type tv --csv-prefix tv
python3 plex_stats.py /plex/anime --type tv --csv-prefix anime
python3 plex_stats.py /plex/movies --type movies --csv-prefix movies
Database records are scoped by library_root, so:
- Scanning
/plex/tvonly touches records wherelibrary_root = '/plex/tv' - Deletion detection only removes files that belong to that library
- Each library can be scanned independently
This allows a single CSV output directory with files from multiple sources:
tv_seasons.csv (from /plex/tv)
tv_series.csv (from /plex/tv)
anime_seasons.csv (from /plex/anime)
anime_series.csv (from /plex/anime)
movies_movies.csv (from /plex/movies)
Troubleshooting
ffprobe not found
Error: ffprobe was not found.
Install FFmpeg, for example on Ubuntu/Debian:
sudo apt install ffmpeg
Solution: Install FFmpeg as shown in the error message.
Permission denied scanning directory
Warning: Could not access /plex/tv: Permission denied
Solution: Run with appropriate permissions:
sudo python3 plex_stats.py /plex/tv
Database locked
sqlite3.OperationalError: database is locked
Solution: Ensure only one instance of the tool is running. If multiple processes try to write simultaneously, wait for the first to finish.
CSV files not created
Check that the output directory exists and is writable:
python3 plex_stats.py /plex/tv --output-dir /tmp
Strange results in CSV
- Verify the directory structure matches TV or movie format
- Check for videos in unexpected locations
- Re-scan with
--forceto regenerate all probes
Extending the Tool
The database stores per-video metadata, so future enhancements are straightforward:
Adding codec analysis
# Expand ffprobe query to include codec
ffprobe ... -show_entries stream=codec_name
# Add columns: video_codec, audio_codec
# Aggregate in CSV generation
Adding resolution tracking
# Query video stream height
ffprobe ... -show_entries stream=height
# Add columns: resolution, resolution_count
Per-episode breakdown
# Parse episode numbers from filenames
# Create *_episodes.csv with per-episode stats
All of this is possible without redesigning the cache because per-video data is preserved.
License
MIT License. Use freely.
Support
For issues or feature requests, consult the source code and modify as needed. The tool is designed to be maintainable and extensible.
Example complete workflow:
#!/bin/bash
# Install FFmpeg (first time only)
sudo apt install ffmpeg
# Create output directory
mkdir -p ~/plex-reports
# Scan TV library
python3 plex_stats.py /plex/tv \
--type tv \
--db ~/plex-stats.db \
--output-dir ~/plex-reports \
--csv-prefix tv
# Scan anime library
python3 plex_stats.py /plex/anime \
--type tv \
--db ~/plex-stats.db \
--output-dir ~/plex-reports \
--csv-prefix anime
# Scan movies library
python3 plex_stats.py /plex/movies \
--type movies \
--db ~/plex-stats.db \
--output-dir ~/plex-reports \
--csv-prefix movies
# View results
ls -lh ~/plex-reports/*.csv
# Import into Google Sheets:
# - Open Google Sheets
# - File > Import
# - Upload ~/plex-reports/tv_seasons.csv