QuantEcon/QuantEcon.py - Open Source PR Review Scorecard

A community based Python library for quantitative economics

C-Rank Grade: A (Welcoming) - 57/100

External PR Merge Rate: 63%

Response Time: <1h

First Timer Success: 33%

Frequently Asked Questions

Is QuantEcon/QuantEcon.py welcoming to first-time open-source contributors?

QuantEcon/QuantEcon.py has a recorded first-timer success rate of 33.3%. 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 QuantEcon/QuantEcon.py respond to incoming external pull requests in approximately 0.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 56.7 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 56.7 places QuantEcon/QuantEcon.py in the A tier.

What is the external contributor pull request merge rate for QuantEcon/QuantEcon.py?

The external contributor pull request merge rate for QuantEcon/QuantEcon.py is 62.5%, based on public PR activity from non-core contributors.

Are there Good First Issues available in QuantEcon/QuantEcon.py?

QuantEcon/QuantEcon.py currently has 7 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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QuantEcon/QuantEcon.py

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AWelcoming(57/100)Python

A community based Python library for quantitative economics

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AI Maintainer Review Guidelines

Review Persona

Welcoming Community Builder

Warmth Score
8.7/10
Patience Score
8.6/10
Nitpick Rate
40%

Highly welcoming maintainers in QuantEcon/QuantEcon.py. Prompt code reviews with positive guidance for new contributors.

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
<1 hour
⚡ Fast reviewer response

Average Response Latency

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

Merge Efficiency
62.5%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
33.3%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
15 core
Highly collaborative maintainer core
Diagnostic Health HUD
62.5%
Merge Gauge
33.3%
1st-Timer
Community Vibe65/100

Embed C-Rank Badge

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

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

Active Good First Issues (7)

View on GitHub

This repository currently has 7 open good first issue tickets available for newcomers.

View all good first issues directly on GitHub

Looking for more Python beginner tasks?Explore Python GFI

Contributor Community Vibe Feedback

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Contributor Compatibility & Review Speed Analysis for QuantEcon/QuantEcon.py

When evaluating whether to contribute to QuantEcon/QuantEcon.py, 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 QuantEcon/QuantEcon.py acknowledge new external contributions in approximately <1 hour. Out of all submitted pull requests from non-core authors in the last 180-day window, 62.5% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to QuantEcon/QuantEcon.py

01

Is QuantEcon/QuantEcon.py welcoming to first-time open-source contributors?

QuantEcon/QuantEcon.py has a recorded first-timer success rate of 33.3%. 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 ~<1 hour. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 56.7 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 56.7 places QuantEcon/QuantEcon.py in the Welcoming tier.

04

What is the external contributor pull request merge rate for QuantEcon/QuantEcon.py?

The external pull request merge rate is 62.5%. 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 QuantEcon/QuantEcon.py?

Yes, QuantEcon/QuantEcon.py currently has 7 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for QuantEcon/QuantEcon.py 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.