大模型数据工程：架构、算法及项目实战
C-Rank Grade: B (Solid) - 51/100
External PR Merge Rate: 84%
Response Time: 6d
First Timer Success: 73%
datascale-ai/data_engineering_book has a recorded first-timer success rate of 73.3%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in datascale-ai/data_engineering_book respond to incoming external pull requests in approximately 138.7 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
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 51.5 places datascale-ai/data_engineering_book in the B tier.
The external contributor pull request merge rate for datascale-ai/data_engineering_book is 84.1%, based on public PR activity from non-core contributors.
datascale-ai/data_engineering_book does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/datascale-ai/data_engineering_book?utm_source=github&utm_medium=badge)
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 17:00 UTC (17:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 15:00 to 19:00 UTC (15:00 - 19:00 UTC local).
Limited recent maintainer review activity recorded for this repository. Prediction based on heuristic baseline.
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No cached good first issues currently tracked for datascale-ai/data_engineering_book.
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When evaluating whether to contribute to datascale-ai/data_engineering_book, 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 datascale-ai/data_engineering_book acknowledge new external contributions in approximately 5 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 84.1% were successfully merged into the primary branch.
datascale-ai/data_engineering_book has a recorded first-timer success rate of 73.3%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~5 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
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 51.5 places datascale-ai/data_engineering_book in the Solid tier.
The external pull request merge rate is 84.1%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
datascale-ai/data_engineering_book does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for datascale-ai/data_engineering_book 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.