apache/superset

Apache Superset is a Data Visualization and Data Exploration Platform

Hotness score

Reliability score

73,897

Stars

about 11 years

Age

Published reviews

Questions

Weekly average

Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

180 observed daily rows. Missing days are not fabricated.

Hotness formula

40% Hot today + 40% Hot this week + 20% Breakout.

40% Hot today: 28
40% Hot this week: 40
20% Breakout: 1
Stars gained: 1d: 14
Stars gained: 7d: 93
Stars gained: 14d: 241
Stars gained: 30d: 565
Stars gained: 90d: 1637

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))

Date	Stars	Stars 1d	Stars 7d	Stars 14d	Stars 30d	Stars 90d	Same-day multiplier	Weekly multiplier	Fortnight multiplier	Hot today	Hot week	Breakout	Stored score

Weekly average

Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

180 observed daily rows. Missing days are not fabricated.

Reliability formula

30% Continuity + 30% Closure + 20% Shipping + 10% Liveness + 10% Support burden.

30% Continuity: 91
30% Closure: 91
20% Shipping: 100
10% Liveness: 100
10% Support burden: 93

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
Support burden = 100 − 2 × open issues per 1,000 stars
Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

Date	Issues opened	Issues closed	PRs opened	PRs merged	Releases	Stars	Open issues	Pushed days ago	Continuity	Closure	Shipping	Liveness	Support burden	License	Observed days	Missing days	Needs healing	Stored score

Continuity30% of headline91

Activity on 87 of 90 tracked days in the last 90 and 27 of 30 in the last 30.

Activity pulse

Closure30% of headline91

Merged 1,811 of 2,162 PRs opened and closed 575 of 207 issues opened over the last 90 tracked days — PR flow carries 55% of this component, issue flow 45%.

PRs merged (90d)PRs opened (90d)Issues closed (90d)Issues opened (90d)

Shipping20% of headline100

21 releases in the last 180 days, 16 in the last 90 and 10 in the last 30 — a steady cadence scores highest.

Releases

Liveness10% of headline100

Last push 0 days ago — freshness decays as pushes age (roughly halves every 83 days without a push).

Repository

Support burden10% of headline93

268 open issues against 73,897 stars — about 4 open issues per 1,000 stars. Lighter backlogs score higher.

Open issues Stargazers

Adoption confidence100

Modeled — how confidently teams are adopting this repo. Stargazers

Maintenance quality95

Modeled from PR/issue responsiveness and upkeep signals. Activity pulse

Risk score6

Modeled — lower is better; adoption and continuity risk. Repository

Stays active (30d)98%

Modeled chance the repo stays active over 30 days. Activity pulse

Stays active (90d)97%

Modeled chance the repo stays active over 90 days. Activity pulse

Release rhythm (180d)100

Regularity of releases over the last 180 days. Releases

Maintainer bus risk (90d)3%

Modeled — lower is better; concentration of commits in few maintainers. Contributors graph

Semantic Layer

Weekly star gains

Full metrics details

GitHub GraphQL current stargazer cohort, reconstructed from starredAt events and totalCount retrieved in one stable pagination walk. GitHub does not expose historical unstar events, so this is not an exact ledger of past star counts.

180 observed daily rows. Missing days are not fabricated.

Date	Value

Cumulative total

Full metrics details

Running total of the GitHub GraphQL stargazer count over time (not weekly deltas), reconstructed from starredAt events and totalCount in one stable pagination walk. GitHub does not expose historical unstar events, so this is not an exact ledger of past star counts.

180 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Full metrics details

GitHub API observation. Historical values render only when the source provides a real observation for that day.

175 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Full metrics details

GitHub Search issue totals queried for exact UTC days; rolling values are sums of proven daily counts.

175 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Full metrics details

GitHub API observation. Historical values render only when the source provides a real observation for that day.

175 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Full metrics details

GitHub Search pull-request totals queried for exact UTC days; rolling values are sums of proven daily counts.

175 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Full metrics details

GitHub API observation. Historical values render only when the source provides a real observation for that day.

175 observed daily rows. Missing days are not fabricated.

Date	Value

Daily ratio — a gap means nothing was opened that day

How this works: each day's value is issues closed that day ÷ issues opened that day. Days when nothing was opened render as gaps — never a rolling average or a made-up zero. Values above 1 mean the project closed more issues than arrived that day.

Full metrics details

GitHub Search issue totals queried for exact UTC days; rolling values are sums of proven daily counts.

147 observed daily rows. Missing days are not fabricated.

Per-day formula: issues closed that day ÷ issues opened that day; blank when nothing was opened (a gap, not a zero).

Date	Issues opened	Issues closed	Stored score

Daily ratio — a gap means nothing was opened that day

How this works: each day's value is pull requests closed that day ÷ pull requests opened that day. Days when nothing was opened render as gaps — never a rolling average or a made-up zero. Values above 1 mean the project closed more pull requests than arrived that day.

Full metrics details

GitHub Search pull-request totals queried for exact UTC days; rolling values are sums of proven daily counts.

175 observed daily rows. Missing days are not fabricated.

Per-day formula: pull requests closed that day ÷ pull requests opened that day; blank when nothing was opened (a gap, not a zero).

Date	PRs opened	PRs closed	Stored score

Weekly total

Full metrics details

GitHub release published_at events bucketed by UTC day; drafts are excluded.

180 observed daily rows. Missing days are not fabricated.

Date	Value

About Superset

Open-source data exploration and dashboard platform with SQL editor, charts, and role-based security; React front end plus pluggable back end for analytics teams.

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apache/superset

Hotness and reliability

Hotness score

Hotness formula

Reliability score

Reliability formula

What drives the reliability score

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Project metrics

Weekly star gains

Cumulative stars

Issues opened

Issues closed

Pull requests opened

Pull requests closed

Pull requests merged

Issue close ratio (daily)

Pull request close ratio (daily)

Releases

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