vitest-dev/vitest

Next generation testing framework powered by Vite.

Hotness score

Reliability score

16,862

Stars

over 4 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: 14
40% Hot this week: 29
20% Breakout: 25
Stars gained: 1d: 3
Stars gained: 7d: 26
Stars gained: 14d: 16862
Stars gained: 30d: 125
Stars gained: 90d: 16862

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: 84
30% Closure: 78
20% Shipping: 90
10% Liveness: 100
10% Support burden: 61

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 headline84

Activity on 88 of 90 tracked days in the last 90 and 28 of 30 in the last 30.

Activity pulse

Closure30% of headline78

Merged 274 of 442 PRs opened and closed 148 of 162 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 headline90

26 releases in the last 180 days, 14 in the last 90 and 3 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 headline61

328 open issues against 16,862 stars — about 19 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 quality86

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

Risk score20

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

Stays active (30d)84%

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

Stays active (90d)92%

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)11%

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

Javascript Vite

Weekly total

Full metrics details

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

179 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.

179 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.

179 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.

179 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.

179 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.

146 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.

174 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

Project Overview

Vitest is a Vite-powered testing framework built for fast feedback in modern JavaScript and TypeScript repos.

Install and run npx vitest; verify Node and Vite prerequisites before rollout.

Key Challenges Addressed

It addresses transform drift and slow loops by reusing Vite internals and strong watch-mode behavior.

You can run unit and component tests with snapshot, mock, coverage, and type-level testing support.

Getting Started

Install and run npx vitest; verify Node and Vite prerequisites before rollout.

Your team should confirm environment prerequisites and CI runtime alignment before scaling usage.

Features and Use Cases

You can run unit and component tests with snapshot, mock, coverage, and type-level testing support.

It aligns naturally with Vite-based monorepos and reduces dependency sprawl through built-in integrations.

Ecosystem and Dependencies

It aligns naturally with Vite-based monorepos and reduces dependency sprawl through built-in integrations.

Execution uses Vite transformation plus worker-based parallelism for scalable local and CI runs.

Architectural Overview

Execution uses Vite transformation plus worker-based parallelism for scalable local and CI runs.

Pros are speed and modern ergonomics; cons are migration effort from older runner-specific internals.

Pros and Cons

Pros are speed and modern ergonomics; cons are migration effort from older runner-specific internals.

Your team gets clear strengths and clear operational constraints, so fit depends on your testing scope.

Comparison and Alternatives

Measured 90-day trends for this project and its alternatives.

Weekly star gains

Vitest Ts Jest Cypress Playwright

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.

Vitest

151 observed daily rows. Missing days are not fabricated.

Date	Value

Ts Jest

180 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

157 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

180 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Vitest Cypress Playwright

Full metrics details

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

Vitest

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

179 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

68 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

177 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Vitest Cypress Playwright

Full metrics details

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

Vitest

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

179 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

68 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

177 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Vitest Cypress Playwright

Full metrics details

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

Vitest

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

179 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

68 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

177 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Vitest Cypress Playwright

Full metrics details

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

Vitest

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

179 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

68 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

177 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Vitest Cypress Playwright

Full metrics details

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

Vitest

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

179 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

68 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

177 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly average

Vitest Ts Jest Cypress Playwright

Full metrics details

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

Vitest

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Ts Jest

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly average

Vitest Ts Jest Cypress Playwright

Full metrics details

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

Vitest

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Ts Jest

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly total

Vitest Ts Jest Cypress Playwright

Full metrics details

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

Vitest

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Ts Jest

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Cypress

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Playwright

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

180 observed daily rows. Missing days are not fabricated.

Date	Value

Weekly average

Vitest Ts Jest Cypress Playwright

Full metrics details

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

Vitest

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

180 observed daily rows. Missing days are not fabricated.

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

Ts Jest

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

180 observed daily rows. Missing days are not fabricated.

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

Cypress

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

180 observed daily rows. Missing days are not fabricated.

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

Playwright

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

180 observed daily rows. Missing days are not fabricated.

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

Vitest Ts Jest Cypress Playwright

Full metrics details

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

Vitest

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

180 observed daily rows. Missing days are not fabricated.

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

Ts Jest

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

180 observed daily rows. Missing days are not fabricated.

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

Cypress

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

180 observed daily rows. Missing days are not fabricated.

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

Playwright

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

180 observed daily rows. Missing days are not fabricated.

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

Alternatives in evaluations are ts-jest, Cypress, and Playwright.

Project	Repo	Adoption confidence (~6mo)	PRs merged (~6mo)	Star growth (~6mo)
Vitest	https://github.com/vitest-dev/vitest	{{BAR10_ADOPTION_CONFIDENCE_365D:vitest-dev/vitest}} {{ADOPTION_CONFIDENCE_365D:vitest-dev/vitest}}	{{BAR10_PRS_MERGED_365D:vitest-dev/vitest}} {{PRS_MERGED_365D:vitest-dev/vitest}}	{{BAR10_STAR_GROWTH_365D:vitest-dev/vitest}} {{STAR_GROWTH_365D:vitest-dev/vitest}}
ts-jest	https://github.com/kulshekhar/ts-jest	{{BAR10_ADOPTION_CONFIDENCE_365D:kulshekhar/ts-jest}} {{ADOPTION_CONFIDENCE_365D:kulshekhar/ts-jest}}	{{BAR10_PRS_MERGED_365D:kulshekhar/ts-jest}} {{PRS_MERGED_365D:kulshekhar/ts-jest}}	{{BAR10_STAR_GROWTH_365D:kulshekhar/ts-jest}} {{STAR_GROWTH_365D:kulshekhar/ts-jest}}
Cypress	https://github.com/cypress-io/cypress	{{BAR10_ADOPTION_CONFIDENCE_365D:cypress-io/cypress}} {{ADOPTION_CONFIDENCE_365D:cypress-io/cypress}}	{{BAR10_PRS_MERGED_365D:cypress-io/cypress}} {{PRS_MERGED_365D:cypress-io/cypress}}	{{BAR10_STAR_GROWTH_365D:cypress-io/cypress}} {{STAR_GROWTH_365D:cypress-io/cypress}}
Playwright	https://github.com/microsoft/playwright	{{BAR10_ADOPTION_CONFIDENCE_365D:microsoft/playwright}} {{ADOPTION_CONFIDENCE_365D:microsoft/playwright}}	{{BAR10_PRS_MERGED_365D:microsoft/playwright}} {{PRS_MERGED_365D:microsoft/playwright}}	{{BAR10_STAR_GROWTH_365D:microsoft/playwright}} {{STAR_GROWTH_365D:microsoft/playwright}}

Best overall alternative: ts-jest. It offers stronger default breadth for most teams.

Conclusion

Vitest is ideal for Vite-native teams that prioritize fast local loops. Keep repository, docs, and guide.

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vitest-dev/vitest

Hotness and reliability

Hotness score

Hotness formula

Reliability score

Reliability formula

What drives the reliability score

Explore related topics

Project metrics

Issues opened

Issues closed

Pull requests opened

Pull requests closed

Pull requests merged

Issue close ratio (daily)

Pull request close ratio (daily)

Releases

Project Overview

Key Challenges Addressed

Getting Started

Features and Use Cases

Ecosystem and Dependencies

Architectural Overview

Pros and Cons

Comparison and Alternatives

GitHub stars

Vitest

Ts Jest

Cypress

Playwright

Issues opened

Vitest

Cypress

Playwright

Issues closed

Vitest

Cypress

Playwright

Pull requests opened

Vitest

Cypress

Playwright

Pull requests closed

Vitest

Cypress

Playwright

Pull requests merged

Vitest

Cypress

Playwright

Open/closed pull request ratio

Vitest

Ts Jest

Cypress

Playwright

Open/closed issues ratio

Vitest

Ts Jest

Cypress

Playwright

Releases

Vitest

Ts Jest

Cypress

Playwright

Hotness score

Vitest

Ts Jest

Cypress

Playwright

Reliability score

Vitest

Ts Jest

Cypress

Playwright

Conclusion

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