PythonOT/POT - Open Source PR Review Scorecard

POT : Python Optimal Transport

C-Rank Grade: A (Welcoming) - 61/100

External PR Merge Rate: 64%

Response Time: -

First Timer Success: 100%

Frequently Asked Questions

Is PythonOT/POT welcoming to first-time open-source contributors?

PythonOT/POT has a recorded first-timer success rate of 100.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in PythonOT/POT respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 61.3 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 61.3 places PythonOT/POT in the A tier.

What is the external contributor pull request merge rate for PythonOT/POT?

The external contributor pull request merge rate for PythonOT/POT is 63.6%, based on public PR activity from non-core contributors.

Are there Good First Issues available in PythonOT/POT?

PythonOT/POT does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.5/10
Patience Score
8.2/10
Nitpick Rate
20%

Collaborative maintainer environment in PythonOT/POT. Reviews community pull requests with focus on project quality.

What Contributors Actually Say

Discussions in PythonOT/POT focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.

Hidden Friction Signals

Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.

Unwritten Rules

  • •1) Keep PR scope strictly aligned with the linked issue.
  • •2) Ensure local linters pass before opening a review.
  • •3) Maintain full test coverage for modified logic.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
-
No reviewer activity recorded

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
63.6%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
100.0%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
11 core
Highly collaborative maintainer core
Diagnostic Health HUD
63.6%
Merge Gauge
100.0%
1st-Timer
Community Vibe55/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for PythonOT/POT
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/PythonOT/POT)](https://getmerged.abhishekco.de/PythonOT/POT?utm_source=github&utm_medium=badge)

Active Good First Issues (1)

View on GitHub

Describe the bug NumpyBackend.seed() only accepts an int (or None). Passing an already-instantiated np.random.RandomState raises a TypeError, because RandomState.seed() itself doesn't accept another RandomState as input: TypeError: Cannot cast scalar from dtype('O') to dtype('int64') according to the rule 'safe' As a result, every caller that wants to support passing an existing RandomState has to special-case it manually instead of relying on the shared nx.seed(seed) / nx.randn(...) abstraction. TorchBackend and TensorflowBackend already handle this correctly -- both adopt an externally-passed generator (torch.Generator, tf.random.Generator) directly. NumpyBackend is the outlier. Code sample import numpy as np from ot.backend import NumpyBackend nx = NumpyBackend() rng = np.random.RandomState(42) nx.seed(rng) # raises TypeError Expected behavior nx.seed(rng) should adopt rng as the backend's own generator (same pattern as TorchBackend/TensorflowBackend), so later nx.rand

📅 Opened Sep 7, 2026💬 1 comment
Quality: 50/100Contribute
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Contributor Compatibility & Review Speed Analysis for PythonOT/POT

When evaluating whether to contribute to PythonOT/POT, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of PythonOT/POT acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 63.6% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to PythonOT/POT

01

Is PythonOT/POT welcoming to first-time open-source contributors?

PythonOT/POT has a recorded first-timer success rate of 100.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 61.3 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 61.3 places PythonOT/POT in the Welcoming tier.

04

What is the external contributor pull request merge rate for PythonOT/POT?

The external pull request merge rate is 63.6%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in PythonOT/POT?

PythonOT/POT does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for PythonOT/POT are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.