Last.fm + deariary: the soundtrack of your days

#integration #guide #lastfm

You played Nujabes on repeat while working through the morning. Around lunch you switched to silence. In the afternoon, halfway through a long pull request review, you put on Tycho and stayed there until six. After dinner you listened to an album your friend had recommended weeks ago, the one you kept meaning to try, and got through the whole thing on the couch before bed.

Last.fm scrobbled all of it. Thirty-seven tracks, four artists, five albums, timestamps down to the minute. What it did not record is that the Nujabes stretch was the most focused two hours you had all week, that the silence at lunch meant you were stuck on something, or that the album on the couch turned out to be exactly the kind of thing you needed after a long day.

We announced Last.fm as an integration previously. This post is the technical companion: exactly what deariary pulls from Last.fm, how it handles the data, and what your diary looks like when your listening history becomes entries.

How the connection works

Last.fm uses web authentication for authorization. When you connect Last.fm in deariary, you are redirected to Last.fm’s own authorization page to grant deariary permission to read your scrobble data.

deariary stores a session key for your account. Last.fm session keys do not expire, so authorization is a one-time step. The key grants read-only access: deariary cannot scrobble tracks, edit your library, or modify your Last.fm account in any way. You can revoke access at any time by disconnecting Last.fm from your deariary settings, or by removing deariary from your Last.fm application settings.

What deariary collects from Last.fm

Each morning, deariary fetches your previous day’s scrobbles from the Last.fm API. The Last.fm changelog post covers the basics. Here is the full picture of what each part yields:

Scrobbled tracks

Every track you played during the collection period, with:

Track name: the title as reported by your player
Artist name: the primary artist credited on the track
Album name: when the scrobbler or Last.fm’s database provides it (tracks without an album are grouped under “(single)”)
Scrobble timestamp: converted to your configured timezone so entries read in local time
Loved flag: whether you marked the track as a favorite on Last.fm

Tracks are grouped by artist and album, not listed one by one. A two-hour stretch of the same album reads as a single listening session, not fourteen disconnected lines.

Top artists

deariary computes the three artists you listened to most during the period, ranked by play count. Each top artist surfaces as a highlight card on your diary entry with:

Artist name
Play count for that day
Album cover art from the most-played album by that artist
Link to the artist’s Last.fm page

Play counts and totals

At the end of collection, deariary computes:

Total tracks scrobbled for the day
Unique tracks (distinct artist-track combinations) and unique artists
Per-artist play counts, used for ranking and for the LLM’s sense of proportion

What deariary does NOT collect

No personal tags. Your Last.fm library tags (artist tags, album tags, track tags) are not accessed.
No social data. Your friends, shoutbox messages, and listening activity of other users stay private.
No recommendations. Last.fm’s recommendation engine and similar-artist data are not used.
No full listening history backfill. Only scrobbles within the collection period (usually the previous day). Your years of listening history on Last.fm are not copied to deariary.
No write access. deariary cannot scrobble tracks, love or unlove songs, edit tags, or modify your Last.fm profile.
No real-time listening. deariary reads completed scrobbles from the previous day, not what you are listening to right now.

Revoking access is immediate: disconnect Last.fm from your settings page and the stored session key is discarded.

Music as a memory trigger

Listening history behaves differently from most integrations because music is one of the strongest involuntary memory cues. The phenomenon is well documented: hearing a song you associate with a specific period can bring back the setting, the people, and even the emotional state of that time, often more vividly than a photograph.

Scrobble data captures this implicitly. You do not need to annotate your listening. The artist, the album, the time of day, and the duration of the session already contain the signal. Six months from now, reading that you played the same album for two hours straight on a Tuesday afternoon carries the weight of whatever that Tuesday afternoon was, because you will remember why you chose that album, even if you could not articulate it at the time.

From scrobbles to a readable day

Here is what the transformation looks like. Say you had a Wednesday with a focused morning, a quiet lunch, and an evening discovery:

Last.fm’s data looks something like:

09:12  Nujabes – Luv(sic) Part 3          (Modal Soul)
09:17  Nujabes – Reflection Eternal        (Modal Soul)  ♥
09:22  Nujabes – Music Is Mine             (Modal Soul)
  ... 8 more Nujabes tracks ...
11:45  Nujabes – Feather                   (Modal Soul)  ♥
14:30  Tycho – A Walk                      (Dive)
14:35  Tycho – Hours                       (Dive)
  ... 6 more Tycho tracks ...
15:52  Tycho – Daydream                    (Dive)
20:15  Khruangbin – Maria También          (Mordechai)
20:19  Khruangbin – Time (You and I)       (Mordechai)
  ... 8 more Khruangbin tracks ...
21:12  Khruangbin – Shida                  (Mordechai)

The ♥ marks are loved tracks you favorited on Last.fm.

deariary hands this to the LLM alongside any other integration data for that day. The result reads like:

Wednesday had a Nujabes morning: eleven tracks from Modal Soul between nine and noon, the kind of loop that means deep focus or autopilot, and from the rest of the day it looks like focus. The afternoon shifted to Tycho’s Dive for a quieter stretch. In the evening you put on Khruangbin’s Mordechai and listened through the whole album on the couch.

Thirty-plus scrobbles became a day with three movements. The artist repetition told the LLM these were sustained listening sessions, not shuffle. The timestamps gave it the rhythm of the day: morning, afternoon, evening. The album names gave it specificity. “Modal Soul between nine and noon” is a morning someone will recognize when they re-read it.

What the LLM does with Last.fm data

The Last.fm fetcher provides context hints to the LLM: scrobbles represent background activity (the user was doing something else while listening), repeated plays of the same artist indicate a sustained session, and the top-artist ranking reflects the sonic weight of the day. Tracks marked as loved are flagged as songs the user explicitly favorited, so the LLM knows to mention them. On sparse days with fewer than five scrobbles, the hints tell the LLM to keep the mention brief rather than stretching thin data into a full paragraph.

On a day where you scrobbled forty tracks and had no calendar events, the music carries the entry. On a day packed with meetings and Slack threads where you squeezed in an hour of music during lunch, the listening gets a brief mention and the workday carries the entry. The LLM weighs all the data and lets the dominant signal lead.

Music also provides texture that other integrations cannot. A calendar event says “worked from home.” Forty Nujabes scrobbles during that same window say something about the mood and focus of the work. The LLM uses timestamps to correlate music with other activities when possible, shading the narrative so a lo-fi morning reads differently from a silence morning, even when the calendar shows the same block of unstructured time.

Last.fm alone vs. with other integrations

A Last.fm-only diary captures what you listened to and when. For someone who listens throughout the day, that is already a surprisingly complete picture of how a day felt.

Add other integrations and the listening gains context:

Last.fm only:

You listened to 37 tracks today. The morning was Nujabes on repeat, the afternoon was Tycho, and the evening was Khruangbin’s Mordechai from start to finish.

Last.fm + Google Calendar + Slack:

You played Nujabes through the morning while working on the API migration, eleven tracks from Modal Soul that carried you from standup to lunch. The afternoon was quieter: Tycho’s Dive in the background while you reviewed Kenji’s PR and left comments in the engineering channel. After dinner you put on Khruangbin’s Mordechai, the album your friend had recommended in Slack last week, and listened through the whole thing.

The first version is a listening log. The second is a day with a soundtrack. The calendar explains what you were doing while the music played. The Slack message connects the evening album to a recommendation. Together they reconstruct not just the listening, but the living.

On the Free plan you can connect one integration, which is enough to try Last.fm on its own. Upgrading to Basic (up to 5 integrations) lets you layer your listening history with your calendar, messages, and check-ins. See pricing on deariary.com for details.

Scrobblers and the universal pipe

Last.fm does not care which player you use. If you listen on Spotify, Apple Music, YouTube Music, Tidal, foobar2000, or anything else with a scrobbler, the plays reach Last.fm and then reach deariary. The music player is a source; Last.fm is the pipe; deariary is the diary.

This means your listening history is already unified. You do not need to connect Spotify and Apple Music separately. If they both scrobble to Last.fm, your entire listening day is already in one place, and deariary reads from that one place.

For desktop and local players, third-party scrobblers like Web Scrobbler (browser extension) and Last.fm’s own desktop app handle the connection. If you are already scrobbling, there is nothing to set up on the music side.

When you do not listen

Some days there are no scrobbles at all. You worked in silence, spent the day outside, or listened to podcasts that your scrobbler does not track.

On those days, deariary has no Last.fm data to include. Your other integrations carry the day instead: the calendar shows where you were, Todoist shows what you finished, GitHub shows what you built. The diary entry is still there, just without the musical thread.

Over time, the days you listen and the days you do not form their own pattern. A week of heavy scrobbling followed by three days of silence might mark the shift from solo work to collaboration, or from energy to exhaustion. The diary captures both without commentary.

Getting started

The setup takes about a minute:

Go to app.deariary.com
Open Settings and find the Integrations section
Click Last.fm and authorize through Last.fm’s login page

No API tokens to copy, no webhook URLs to configure. The session key is granted through Last.fm’s web auth flow and never expires. Your first batch of scrobbles arrives the next morning, timestamped in your configured timezone.

Last.fm is available on every paid plan and on the Free plan. On the Free plan, Last.fm counts as your one active integration.

What surprised us

We have been using Last.fm with our own diaries since the day it shipped. A few patterns emerged that we did not expect.

Album listens are more interesting than shuffle. A diary entry that says “you listened to Modal Soul from start to finish” carries a different weight than “you played 14 tracks across 9 artists.” The album listen implies a choice, a mood, a commitment to one sound for an hour. Shuffle implies background noise. Both are valid, but the album listens are the ones we re-read. If you want richer diary entries from Last.fm, listening to albums helps.

Silence is part of the story. The days with no scrobbles turned out to be just as revealing as the days with fifty. A sudden gap in an otherwise music-heavy week stands out in the diary. You notice it, and you remember why. The silence was the meeting marathon, the outdoor day, the afternoon you spent reading instead. Last.fm does not record silence, but the absence of data is its own signal.

The three-artist highlight card is the right default. We experimented with showing five, then one, then settled on three. One artist does not capture a day with multiple moods. Five feels like a list. Three is enough to show the arc of a day (morning, afternoon, evening) without turning the highlight into a chart.

Your Last.fm already records every song you play. deariary turns those scrobbles into a diary that preserves not just the tracks, but the days they belonged to. The albums become moods, the sessions become rhythm, and the listening becomes the soundtrack of a life you can read back.

Connect Last.fm to deariary