Spotify Global & Regional Charts Monitor

Scrape Spotify's Top 50 daily charts across 49 countries, the Top Songs weekly charts across 14, and the global weekly track, album and artist charts — and, because Spotify's chart playlists publish only today's order, find out what actually moved.

Built for label analysts, radio programmers, music journalists and digital marketers who need chart history rather than a single snapshot: schedule it and every run reports climbers, fallers, new entries and drop-outs per territory.

No Spotify account, no API key, no browser.

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What you get

Per CHART_ENTRY row:

Field	Notes
rank, previousRank, rankChange, entryStatus	MOVED_UP / MOVED_DOWN / NO_CHANGE / NEW_ENTRY
trackName, artistName, artistNames, albumName	The charting recording and everyone credited
playcount	Lifetime streams — not in Spotify's official API
chartName, country, recurrence, chartLastUpdated	Which chart, and when Spotify last recalculated it
trackUrl, artistUrl, albumUrl, coverArt	Links and artwork

Plus a CHART_EXIT row for every track that was on the chart last run and is not now, and one CHART_SUMMARY per chart — entry count, followers, how many are new, how many climbed or fell, and the biggest climber.

From the public charts service you additionally get album and artist charts, with Spotify's own peakRank, appearancesOnChart (weeks on chart) and consecutiveAppearances.

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Quick start

{
  "countries": ["GLOBAL", "US", "GB", "ID", "BR"],
  "recurrence": "daily",
  "includeGlobalWeeklyCharts": true,
  "trackRankMovement": true,
  "exportFormats": ["csv"]
}

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Two very different chart surfaces

Country charts come from Spotify's editorial chart playlists. They cover around fifty territories and both cadences — but they are just ordered track lists. Spotify tells you there are "3 new entries" and never which three.

The public charts service needs no credential whatsoever, and returns real chart records: previousRank, peakRank, entryStatus, weeks on chart, for tracks and albums and artists. Its limitation is coverage: global weekly only. Per-country and historical charts there sit behind a login.

This actor reads both, and fills the gap in the first with its own memory.

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How movement tracking works

Each run writes the order it saw into a named key-value store (trackingStoreName) and compares the next run against it.

• The first run is the baseline — entries are marked

  entryStatus: "BASELINE"
  , deliberately not NEW_ENTRY, because a real 50-track turnover should not look identical to a first run.
• Matching is on trackUri, so a re-release under a different id counts as a new entry — which is also how Spotify treats it.
• Use a named store, not the run's own: a run-scoped store is deleted with its run and every run would report BASELINE.

Daily charts recalculate once a day, so scheduling more often than daily produces NO_CHANGE rows. Weekly charts update Thursdays.

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Cost

One request per country chart, one for the whole public charts service, plus one to pick up an anonymous token. Ten countries plus the global charts is twelve requests.

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Limits worth knowing

• Viral 50 no longer exists. Spotify retired it. Its old ids still answer HTTP 200 with an empty body, so the actor recognises them by name and says so in the error row rather than reporting an empty chart.
• Weekly charts cover far fewer countries than daily ones — 14 against 49. Asking for an unavailable country stops the run with the full list instead of silently returning nothing.
• Chart playlists are invisible to search. Spotify excludes them from every search surface, so they can only be reached by id. The catalogue in src/catalog.py was verified entry by entry; anything outside it can be passed as a playlistUrls entry.
• peakRank and weeks-on-chart are only published on the public service, and even there Spotify leaves them unset on many entries. Unset arrives as 0, which is normalised to null so it cannot read as "peaked at 0".

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Output

Every run writes to the Apify dataset. Set exportFormats to also drop a ready-made spotify-charts.csv, .xlsx, .json or .ndjson into the run's key-value store.

See CRAWLING_METHOD.md for how the data is obtained.