REPOGEO REPORT · LITE

graphistry/pygraphistry

Default branch master · commit f08c4588 · scanned 6/28/2026, 2:11:47 PM

GitHub: 2,523 stars · 231 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

28 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface graphistry/pygraphistry, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Reposition the README H1 to explicitly state pygraphistry's core differentiator as a Python library

Why:

CURRENT

# PyGraphistry: Leverage the power of graphs & GPUs to visualize, analyze, and scale your data

COPY-PASTE FIX

# PyGraphistry: The Python Library for GPU-Accelerated Interactive Graph Visualization & Analytics

mediumabout#2
Add the missing homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
https://pygraphistry.readthedocs.io/en/latest/
```

lowreadme#3

Refine the first paragraph of the README to emphasize pygraphistry's standalone library capabilities

Why:

CURRENT

PyGraphistry is an open source Python library for data scientists and developers to leverage the power of graph visualization, analytics, AI, including with native GPU acceleration:

COPY-PASTE FIX

PyGraphistry is the open-source Python library for data scientists and developers to perform GPU-accelerated, interactive graph visualization and analytics directly within Python environments. It enables high-performance exploration of complex graph data at scale, and seamlessly integrates with the Graphistry platform for advanced features.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface graphistry/pygraphistry

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Graphistry

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Graphistry · recommended 2×
Datashader · recommended 2×
HoloViews · recommended 2×
NetworkX · recommended 2×
Plotly · recommended 2×

CATEGORY QUERY
How can I visualize large datasets as graphs using Python with GPU acceleration?
you: not recommended
AI recommended (in order):
1. Graphistry
2. cuGraph
3. Datashader
4. HoloViews
5. Panel
6. PyVista
7. NetworkX
8. Plotly
9. Dash
10. CuPy
11. Dask-GPU
12. Altair
AI recommended 12 alternatives but never named graphistry/pygraphistry. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are good Python libraries for interactive graph exploration of large datasets?
you: not recommended
AI recommended (in order):
1. Dash
2. Cytoscape.js
3. Pyvis
4. vis.js
5. Graphistry
6. NetworkX
7. Plotly
8. HoloViews
9. hvPlot
10. Bokeh
11. Datashader
12. Gleam
13. Graph-tool
AI recommended 13 alternatives but never named graphistry/pygraphistry. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of graphistry/pygraphistry?
pass
AI did not name graphistry/pygraphistry — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts graphistry/pygraphistry in production, what risks or prerequisites should they evaluate first?
pass
AI named graphistry/pygraphistry explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo graphistry/pygraphistry solve, and who is the primary audience?
pass
AI named graphistry/pygraphistry explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of graphistry/pygraphistry. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/graphistry/pygraphistry.svg)](https://repogeo.com/en/r/graphistry/pygraphistry)

HTML

<a href="https://repogeo.com/en/r/graphistry/pygraphistry"><img src="https://repogeo.com/badge/graphistry/pygraphistry.svg" alt="RepoGEO" /></a>

Pro

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graphistry/pygraphistry — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite