apache/datasketches-rust - Open Source PR Review Scorecard

A software library of stochastic streaming algorithms, a.k.a. sketches.

C-Rank Grade: S (Elite) - 71/100

External PR Merge Rate: 74%

Response Time: 6h

First Timer Success: 80%

Frequently Asked Questions

Is apache/datasketches-rust welcoming to first-time open-source contributors?

apache/datasketches-rust has a recorded first-timer success rate of 80.0%. Repositories ranked S 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 apache/datasketches-rust respond to incoming external pull requests in approximately 6.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 71.5 C-Rank™ score (S 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 71.5 places apache/datasketches-rust in the S tier.

What is the external contributor pull request merge rate for apache/datasketches-rust?

The external contributor pull request merge rate for apache/datasketches-rust is 74.1%, based on public PR activity from non-core contributors.

Are there Good First Issues available in apache/datasketches-rust?

apache/datasketches-rust currently has 3 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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apache/datasketches-rustS•Elite127
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apache/datasketches-rust

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InactiveS•Elite(71/100)Rust

A software library of stochastic streaming algorithms, a.k.a. sketches.

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AI Maintainer Review Guidelines

Review Persona

Welcoming Community Builder

Warmth Score
8.6/10
Patience Score
8.6/10
Nitpick Rate
35%

Highly welcoming maintainers in apache/datasketches-rust. 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
6 hours
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
74.1%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
80.0%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
19 core
Highly collaborative maintainer core
Diagnostic Health HUD
74.1%
Merge Gauge
80.0%
1st-Timer
Community Vibe79/100

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Active Good First Issues (5)

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Context BloomFilter::invert() flips every bit in the backing array. #194 raised the resulting contract questions and #202 documented the altered guarantees, but left the API-shape decision open: after inversion the type signature is unchanged and still permits every update operation. The semantics after inversion are worth pinning down precisely. Let B be the bit array before inversion and S(x) the k hash positions of an item x: contains(x) == true after inversion means every position of S(x) was 0 in B, so x was definitely not inserted before the inversion. This direction is certain; it has no error probability. contains(x) == false means at least one position of S(x) was 1 in B. All inserted items land here, but so does any absent item with at least one colliding position — with probability roughly 1 - (1 - load_factor)^k, which is close to 1 for typical configurations. So false carries little information. Inversion is therefore not the exact logical complement of the pre-inversio

📅 Opened Sep 2, 2026💬 4 comments
Quality: 100/100Contribute

Aggregation pipelines often own multiple partial TDigestMut states. Repeated borrowed merge calls recompress intermediate results, so consuming an iterator of digests should combine them with one compression pass while retaining the existing borrowed API. PR #261 explored FromIterator<TDigestMut>. A first implementation collected sorted slices into a BinaryHeap and then collected all centroids again, which added allocations and obscured the data flow. The revised approach lazily k-way merges fully compressed sorted buffers directly into compression; inputs with unsorted update tails are materialized and stably sorted once because sorting every tail separately was slower. A focused PR should cover empty and single inputs, mixed k values, stable tie ordering, compressed and uncompressed inputs, allocation-aware benchmarks, and the clone tradeoff between borrowed merge and consuming collection.

📅 Opened Sep 2, 2026💬 1 comment
Quality: 90/100Contribute

Repeated quantile calls scan the same centroid sequence independently. T-Digest should expose batch queries on TDigest and TDigestMut so ranks in nondecreasing order share one traversal while arbitrary input order is preserved. PR #261 explored this with a small cursor over the centroid sequence: sorted ranks use it directly, while unsorted ranks sort indices and scatter answers back into caller order. A focused PR should carry over the API, validation, tests, benchmark, and changelog entry without the merge changes from #261.

📅 Opened Sep 2, 2026💬 1 comment
Quality: 90/100Contribute

Context The Rust implementations currently use different error models for distribution queries: T-Digest returns Option when querying an empty sketch and panics for invalid ranks, NaN rank inputs, or invalid split points. KLL and REQ return Result, but currently classify an empty sketch as InvalidArgument alongside malformed query arguments. Deserializers separately report malformed serialized state as InvalidData. An empty sketch is a valid object state: it can be created, serialized, merged, and updated. However, quantile, rank, CDF, and PMF values are undefined until the sketch has observed data. That condition is distinct from an invalid query argument and from corrupted serialized data. The C++ and Java implementations preserve this distinction with exception categories: DataSketches C++ T-Digest and KLL throw std::runtime_error for queries on empty sketches and std::invalid_argument for invalid query parameters. DataSketches Java T-Digest throws SketchesStateException for quer

📅 Opened Sep 2, 2026💬 3 comments
Quality: 90/100Contribute

Description REQ deserialization currently accepts compactor states that cannot be produced by a valid sketch. Those states can later panic in safe public APIs or violate documented return-value contracts. Two concrete examples on current main: A single-level image with num_sections = 0 deserializes successfully. A subsequent ReqSketch::merge panics at 1u64 << (self.num_sections - 1) because the subtraction underflows. A single-level image whose level-0 compactor declares lg_weight = 63 and contains one item deserializes successfully. Its inclusive rank for that item is approximately 9.22e18, even though ReqSketch::rank promises a result in [0.0, 1.0]. Relevant code: Compactor::deserialize validates only broad section_size_raw and lg_weight bounds ensure_enough_sections assumes num_sections is nonzero ReqSketch::deserialize accepts the reconstructed compactors without validating cross-field invariants Expected fix Validate wire-controlled compactor state before constructing a ReqSke

📅 Opened Aug 25, 2026💬 0 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for apache/datasketches-rust

When evaluating whether to contribute to apache/datasketches-rust, 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 apache/datasketches-rust acknowledge new external contributions in approximately 6 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 74.1% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to apache/datasketches-rust

01

Is apache/datasketches-rust welcoming to first-time open-source contributors?

apache/datasketches-rust has a recorded first-timer success rate of 80.0%. Repositories ranked Elite 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 ~6 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 71.5 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 71.5 places apache/datasketches-rust in the Elite tier.

04

What is the external contributor pull request merge rate for apache/datasketches-rust?

The external pull request merge rate is 74.1%. 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 apache/datasketches-rust?

Yes, apache/datasketches-rust currently has 3 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 apache/datasketches-rust 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.