FlaPy
An open-source tool for mining flaky tests at scale
At a glance
- Editor scoreNot yet scored
- PricingFree plan
- Best forResearchers localizing flaky faults in test suites
- Free planYes
- Paid fromNone
- Flaky test detectionYes
- Facts checked26 Sep 2026
Where it wins
- Reruns test suites and analyzes repeated runs for infrastructure flakiness
- Traces calls and uses line coverage to calculate suspiciousness scores
- Runs locally in Docker or on a SLURM cluster
Where it doesn't
- Requires users to provide project and test selections through CSV input
- Is self-run rather than a hosted CI analysis service
- Does not provide fix suggestions or test quarantine
Our verdict on FlaPy
FlaPy is an open-source research tool for developers and researchers investigating flaky tests across specified projects. It accepts project details and test selections through CSV input, then reruns suites to identify inconsistent behavior. Its focus is fault localization through repeated execution and analysis, rather than serving as a hosted CI analysis service. Researchers who can run and interpret this workflow may find its coverage and call-tracing features useful; teams seeking automated remediation or a managed CI workflow should look elsewhere.
FlaPy supports local execution in Docker containers and jobs on a SLURM cluster. It aggregates and parses results across repeated project runs, and analyzes those runs to detect infrastructure flakiness. During test execution, it can trace function and method calls, collect line coverage, and calculate suspiciousness scores for flaky fault localization. This makes it a better fit for research and investigation workflows that need evidence about likely faulty code than for teams looking primarily for test quarantine or suggested fixes.
The software is distributed as source code under the GNU Lesser General Public License, and its pricing model is open source with a free plan. It is self-hosted and supports Linux. FlaPy’s scope is deliberately centered on analyzing reruns: it does not offer AI features, fix suggestions, or test quarantine. Choose it when you want to study flaky behavior with local or cluster-based runs and can manage the execution yourself. For a hosted service or a workflow centered on integrations and automation, FlaPy is not the right choice.
FlaPy pricing
FlaPy fact sheet
| Free plan | Yes |
|---|---|
| Paid from | None |
| Flaky test detection | Yes |
| Failure root-cause analysis | Yes |
| AI fix suggestions | No |
| Test quarantine | No |
| CI integrations | Not verified |
| Failure history | Not verified |
| Deployment | Self-hosted |
| Platforms | Linux |
| Built for | Solo, Small business, Mid-market (editorial estimate) |
| Pricing | Free plan |
| Website | github.com |
| Facts checked | 26 Sep 2026 |
Alternatives to FlaPy
- Datadog Test OptimizationA broad CI test toolkit for finding, managing, and investigating flaky tests.5.0
- MergifyCombines flaky-test analysis and quarantine with merge queues and CI workflows.7.0
- JenkinsFlexible self-managed CI infrastructure, but not a dedicated flaky-test analysis tool.—
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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
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