Statsfm

stats.fm CLI

Comprehensive Python CLI for querying stats.fm API (Spotify listening analytics).

Requirements: Python 3.6+ (stdlib only, no pip installs needed)

Script location: scripts/statsfm.py in this skill's directory. Examples use ./statsfm.py assuming you're in the scripts folder.

Prerequisites

Stats.fm account (optional)

• A stats.fm account is only needed for personal listening data (history, top tracks, now playing, etc.)
• Without an account, you can still use public features: album tracklists, artist discographies, search, and global charts
• Don't have one? Visit stats.fm and sign up with Spotify or Apple Music (AM untested, Plus status unknown)
• Already have one? Copy your username from your profile

Setup

No account needed for public commands: search, album, artist-albums, charts-top-tracks, charts-top-artists, charts-top-albums.

For personal stats (profile, top-artists, top-tracks, recent, np, etc.), pass your username with --user USERNAME / -u USERNAME. These commands exit with code 1 if no user is provided.

Quick Start

# View your profile
./statsfm.py profile

# Top tracks this month
./statsfm.py top-tracks --limit 10

# Track stats for 2025
./statsfm.py track-stats 188745898 --start 2025 --end 2026

All Commands

User Profile

• profile - Show user profile and stats.fm membership info

Top Lists

• top-tracks - Your most played tracks
• top-artists - Your most played artists
• top-albums - Your most played albums
• top-genres - Your top music genres

Current Activity

• now-playing (aliases: now, np) - Currently playing track
• recent - Recently played tracks

Detailed Stats

• artist-stats <artist_id> - Detailed stats for specific artist (with monthly breakdown)
• track-stats <track_id> - Detailed stats for specific track (with monthly breakdown)
• album-stats <album_id> - Detailed stats for specific album (with monthly breakdown)
• stream-stats - Overall streaming statistics

Lookups

• album <album_id> - Album info and full tracklist (release date, label, genres, tracks with duration and [E] tags)
• artist-albums <artist_id> - All albums/singles by artist, grouped by type (Albums, Singles & EPs, Compilations), newest first. Deduped by ID, 15 per section by default, shows "(N more)" overflow.
  • --type album|single|all (default: all)
  • --limit N - Items per section

Drill-Down

• top-tracks-from-artist <artist_id> - Top tracks from specific artist
• top-tracks-from-album <album_id> - Top tracks from specific album
• top-albums-from-artist <artist_id> - Top albums from specific artist

Global Charts

• charts-top-tracks - Global top tracks chart
• charts-top-artists - Global top artists chart
• charts-top-albums - Global top albums chart

Search

• search <query> - Search for artists, tracks, or albums

Common Flags

Date Ranges

All stats commands support both predefined ranges and custom dates:

Predefined ranges:

• --range today - Today only
• --range weeks - Last 4 weeks (default)
• --range months - Last 6 months
• --range lifetime - All time

Custom date ranges:

• --start YYYY - Start year (e.g., --start 2025)
• --start YYYY-MM - Start month (e.g., --start 2025-07)
• --start YYYY-MM-DD - Start date (e.g., --start 2025-07-15)
• --end YYYY[-MM[-DD]] - End date (same formats)

Examples:

# All of 2025
./statsfm.py top-artists --start 2025 --end 2026

# Just July 2025
./statsfm.py top-tracks --start 2025-07 --end 2025-08

# Q1 2025
./statsfm.py artist-stats 39118 --start 2025-01-01 --end 2025-03-31

Other Flags

• --limit N / -l N - Limit results (default: 15)
• --user USERNAME / -u USERNAME - Specify the stats.fm username to query
• --no-album - Hide album names in track listings (albums show by default)

Usage Examples

# Search for an artist, then drill down
./statsfm.py search "madison beer" --type artist
./statsfm.py artist-stats 39118 --start 2025
./statsfm.py top-tracks-from-artist 39118 --limit 20

# Weekly breakdown of a track
./statsfm.py track-stats 188745898 --start 2025 --end 2026 --granularity weekly

# Custom date range
./statsfm.py top-artists --start 2025-06 --end 2025-09

# Album tracklist and discography
./statsfm.py album 1365235
./statsfm.py artist-albums 39118 --type album

# Global charts
./statsfm.py charts-top-tracks --limit 20

Output Features

Automatic Monthly Breakdowns

Stats commands (artist-stats, track-stats, album-stats) automatically show:

• Total plays and listening time
• Monthly breakdown with plays and time per month
• Works for both predefined ranges and custom date ranges

Example output:

Total: 505 plays  (29h 53m)

Monthly breakdown:
  2025-02:   67 plays  (3h 52m)
  2025-03:  106 plays  (6h 21m)
  2025-04:   40 plays  (2h 24m)
  ...

Display Information

• Track listings: Show position, track name, artist, album (by default), play count, time
• Album listings: Show position, album name, artist, play count, time
• Artist listings: Show position, artist name, play count, time, genres
• Charts: Show global rankings with stream counts
• Recent streams: Show timestamp, track, artist, album (by default)

Plus vs Free Users

Stats.fm Plus required for:

• Stream counts in top lists
• Listening time (play duration)
• Detailed statistics

Free users get:

• Rankings/positions
• Track/artist/album names
• Currently playing
• Search functionality
• Monthly breakdowns (via per-day stats endpoint)

The script handles both gracefully, showing [Plus required] for missing data.

API Information

Base URL: https://api.stats.fm/api/v1

Authentication: None needed for public profiles

Response format: JSON with item (single) or items (list) wrapper

Rate limiting: Be reasonable with requests. Avoid more than ~10 calls in rapid succession during deep dives.

Error Handling

All errors print to stderr and exit with code 1.

Finding IDs

Use search to find artist/track/album IDs:

# Find artist
./statsfm.py search "sabrina carpenter" --type artist
# Returns: [22369] Sabrina Carpenter [pop]

# Find track
./statsfm.py search "espresso" --type track
# Returns: [188745898] Espresso by Sabrina Carpenter

# Find album
./statsfm.py search "short n sweet" --type album
# Returns: [56735245] Short n' Sweet by Sabrina Carpenter

Then use the ID numbers in other commands.

Tips

1. Use custom dates for analysis: --start 2025 --end 2026 to see full year stats
2. Chain discoveries: Search → Get ID → Detailed stats → Drill down
3. Compare periods: Run same command with different date ranges
4. Export data: Pipe output to file for records: ./statsfm.py top-tracks --start 2025 > 2025_top_tracks.txt
5. Albums show by default: Match the stats.fm UI behavior (album art is prominent)
6. Monthly breakdowns: All stats commands show month-by-month progression automatically

For AI Agents

Setup

Check your memory for a stored stats.fm username. If you don't have one, ask. Every command that touches user data needs --user USERNAME.

What This Tool Is For

This gives you direct access to someone's music listening history. That's personal. The value isn't in dumping tables of data — it's in showing someone something about themselves they didn't already know.

When someone asks about their music, they're not asking for a database query. They want to understand their own taste, revisit a memory, or discover a pattern. Your job is to connect the data to something meaningful.

How to Think About It

Someone mentions an artist: They have a relationship with that artist. Find out what it looks like — how long they've been listening, what era they discovered them, which tracks stuck. search → artist-stats tells the story. top-tracks-from-artist shows what resonated. artist-albums gives context on the discography. Don't just list all three — read the first result and decide what's interesting before going deeper.

Someone asks about their taste: They want a mirror, not a spreadsheet. top-artists and top-genres across different time ranges reveal how their taste is shifting. Compare --range weeks to --range months to --range lifetime — the differences are the story. A lifetime #1 that's not in the top 20 this month is more interesting than the current #1.

Someone mentions an album: They want to know about it or remember it. album gives the tracklist and metadata. If they also have listening data, album-stats shows when and how much they played it. Monthly breakdowns reveal whether it was a one-week obsession or a slow burn.

Someone asks what they're listening to: now-playing is the literal answer. But recent with the last 10-15 tracks shows the session's mood. If there's a pattern (same artist, same genre), name it.

Date Ranges

When the user says a time period, translate it:

• "This year" → --start 2025 --end 2026
• "Last summer" → --start 2025-06 --end 2025-09
• "When did I start listening to X" → artist-stats <id> with --range lifetime — the monthly breakdown shows the first month

Reading the Data

The numbers tell stories. Look for these:

• A month with 200+ plays — that artist owned their life for a while. Say so.
• First appearance in monthly breakdown — that's when they discovered the artist. Context: was an album released that month?
• Sudden drop after months of plays — something changed. New obsession displaced it, or they moved on.
• Old tracks in recent plays — nostalgia trip or rediscovery. Worth noting.
• One track with 5x the plays of the next — that's their song. The one they put on repeat.

Don't just report numbers. "You played 847 tracks" means nothing. "You listened to Madison Beer for 30 hours in March — that's almost an hour a day" means something.

Command Reference

Edge Cases

• Free users: Play counts are not available for top tracks — rankings and breakdowns still work, lead with those
• Empty results: Try --range lifetime as fallback. Could also be a private profile.
• Search duplicates: Use the first result
• Apple Music: Untested, may have gaps

References

• Github Repo: statsfm/statsfm-cli
• API Endpoints: references/api.md
• Official JS Client: statsfm/statsfm.js