graphistry/pygraphistry - Open Source PR Review Scorecard

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

C-Rank Grade: A (Welcoming) - 62/100

External PR Merge Rate: 84%

Response Time: -

First Timer Success: 50%

Frequently Asked Questions

Is graphistry/pygraphistry welcoming to first-time open-source contributors?

graphistry/pygraphistry has a recorded first-timer success rate of 50.0%. 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 graphistry/pygraphistry 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 61.8 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 61.8 places graphistry/pygraphistry in the A tier.

What is the external contributor pull request merge rate for graphistry/pygraphistry?

The external contributor pull request merge rate for graphistry/pygraphistry is 83.6%, based on public PR activity from non-core contributors.

Are there Good First Issues available in graphistry/pygraphistry?

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

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graphistry/pygraphistry

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Active (30d)A•Welcoming(62/100)Python

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

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AI Maintainer Review Guidelines

Review Persona

Strict Architecture Gatekeeper

Warmth Score
7.2/10
Patience Score
7.8/10
Nitpick Rate
45%

Strict review standards in graphistry/pygraphistry. Ensure PR scope matches issue requirements closely before requesting review.

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
83.6%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
50.0%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
1 core
Single maintainer review bottleneck
Diagnostic Health HUD
83.6%
Merge Gauge
50.0%
1st-Timer
Community Vibe48/100

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Active Good First Issues (4)

View on GitHub

Summary Modernize CI/docs Python interpreter choices while preserving library backward compatibility. Policy (explicit) PyGraphistry runtime backward compatibility SHOULD remain Python 3.8+ for now. CI SHOULD keep explicit compatibility testing across the known-supported matrix (currently 3.8 .. 3.14, where working). CI jobs that are primarily operational/build/docs/tooling lanes should avoid EOL interpreters and move to maintained versions (prefer newer where feasible). Why Python 3.8 is EOL, so non-compat lanes pinned to 3.8 create avoidable infra risk. We still need confidence in older-runtime compatibility for users. Splitting compatibility lanes from operational lanes gives both safety and forward motion. Scope for this issue Inventory and classify Python-version usage across CI/docs/packaging as: compatibility lanes (must include old+new supported versions), operational lanes (prefer maintained/current interpreters), policy declarations (python_requires, docs claims, toolin

📅 Opened Apr 9, 2026💬 2 comments
Quality: 40/100Contribute

Summary Adopt repo-wide mypy --strict via phased rollout, with explicit separation between contributor work (safe incremental fixes) and maintainer work (policy, CI gates, and suppression governance). Related Pyright monitor-mode tracking: #1075 Prior pyright/pylance request: #465 M0b IR typing work (completed): #1091 Baseline (initial strict run) Reference command: PYTHONPATH=. uv run --python 3.13 --no-project --with mypy==1.14.1 \ python -m mypy --config-file mypy.ini --strict graphistry Observed (initial pass): Total errors: 1966 Top codes: no-untyped-def (745), no-untyped-call (547), type-arg (222), unused-ignore (167), attr-defined (98) Highest-density area: graphistry/layout/* (~518) Top files: feature_utils.py (187), layout/sugiyama/sugiyamaLayout.py (152), PlotterBase.py (127), layout/graph/graphBase.py (86), embed_utils.py (70) Working model Contributor-friendly PR shape Keep PRs small and mechanical: single error family and small file set. Prefer one of these scopes p

📅 Opened Apr 8, 2026💬 2 comments
Quality: 30/100Contribute

Problem During #977 (cudf SIGSEGV fix), a real UnboundLocalError in hop.py was missed by both ruff and mypy: # edge_map assigned only inside this branch: if g_out._edges is not None and edge_hop_col is not None and ...: edge_map = ... # then used outside it — NameError/UnboundLocalError at runtime: if missing_mask.any() and edge_hop_col is not None and ...: ... safe_map_series(..., edge_map) # edge_map possibly unbound! The bug was masked by an upstream SIGSEGV (so it never surfaced in production), and only caught by writing a test that exercised the specific branch combination (`label_node_hops=True, label_edge_hops=None` with a non-empty `missing_mask`). Why ruff/mypy missed it ruff F821 only catches names with no assignment anywhere in scope — not conditionally-assigned names mypy does not flag "possibly unbound" from conditional branches unless the variable is annotated before the branch (e.g. `edge_map: pd.Series` declared before the `if`) Neither tool does full dat

📅 Opened Apr 6, 2026💬 2 comments
Quality: 40/100Contribute

Summary Explore packaging the GFQL Cypher compiler as a WASM module for browser/JS environments. This would enable client-side Cypher query compilation and potentially execution on in-memory graph data without server round-trips. Why this matters Interactive notebooks/dashboards: Run Cypher queries directly in the browser against local graph data Offline/edge use cases: Graph query capability without network dependency Developer tools: Cypher playground, query validation, AST visualization in the browser Embedding: Ship a lightweight Cypher engine in JS/TS applications without a Python backend Recommended first spike The easiest entry point is testing whether the existing Python Cypher compiler works in Pyodide (CPython-in-WASM): ```python In a Pyodide environment (e.g., https://pyodide.org/en/stable/console.html): import micropip await micropip.install('pygraphistry') from graphistry.compute.gfql.cypher.api import compile_cypher Does this work without pandas? compiled = compile_cyph

📅 Opened Apr 2, 2026💬 0 comments
Quality: 40/100Contribute
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Contributor Compatibility & Review Speed Analysis for graphistry/pygraphistry

When evaluating whether to contribute to graphistry/pygraphistry, 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 graphistry/pygraphistry acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 83.6% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to graphistry/pygraphistry

01

Is graphistry/pygraphistry welcoming to first-time open-source contributors?

graphistry/pygraphistry has a recorded first-timer success rate of 50.0%. 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 61.8 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 61.8 places graphistry/pygraphistry in the Welcoming tier.

04

What is the external contributor pull request merge rate for graphistry/pygraphistry?

The external pull request merge rate is 83.6%. 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 graphistry/pygraphistry?

Yes, graphistry/pygraphistry 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 graphistry/pygraphistry 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.