Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 14:43 UTC

sinaptik-ai / pandas-ai

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

PythonCustom license★ 23,799 stars⑂ 2,339 forkssince Apr 2023View on GitHub ↗
KindCommand-line toolLibraryhow this is determined
#llm#pandas#ai#data-analysis#data-science#gpt-4#csv#data#sql#database#datalake#data-visualization#text-to-sql

sinaptik-ai/pandas-ai holds a health index of 75 out of 100, placing it in the Good band. It scores highest on Engineering Quality (92/100) and lowest on Security (36/100). It was last updated 324 days ago. A single contributor accounts for most of its recent work.

75
overall / 100
Good

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

75
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 65 is calibrated to 75 on the published index scale (record calibration 2026-08-02).

Ownership

PandasAIOrganization
314 followers6 public repossince Dec 2023

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIpandasai3.0.0244,374225345 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

45Weak · 21% of overall

Development activity

23At Risk
How it's scored
3.6/36Push recency — last push 324 days ago
3.5/36Commit cadence — 5/52 weeks with commits
15.9/18Commit volume — 58 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year58
human_commit_share1
days_since_last_push324
active_weeks_last_year5

Release discipline

78Good
How it's scored
27/27Ships releases — 100 releases published
16.2/36Release recency — latest release 345 days ago
27/27Release cadence — a release every ~25 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv3.0.0
releases_from_tagsno
days_since_latest_release345
mean_days_between_releases25
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

86Excellent · 17% of overall

Popularity & adoption

97Exceptional
How it's scored
60/60Stars — 23,799 stars
25/25Forks — 2,339 forks
12.4/15Watchers — 169 watchers
Inputs used
forks2,339
stars23,799
watchers169
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

71Good
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

90Excellent
How it's scored
71.8/80Monthly downloads — 244,374 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespandasai
dependents—
ecosystemspypi
total_downloads—
monthly_downloads244,374
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

64Moderate · 23% of overall

Maintainer resilience (bus factor)

43Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
10.8/22.5Commit distribution — top contributor authored 52% of commits
13.5/13.5Contributor breadth — 97 contributors
10/10OpenSSF Scorecard: Contributors — project has 8 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled97
top_contributor_share0.521

Issue & PR responsiveness

70Good
How it's scored
41.7/42Issue resolution — 99% of issues closed
23.7/30PR acceptance — 564/714 decided PRs merged
0/13Newcomer PR acceptance — 0/1 first-time contributors' PRs merged in 30d
4.5/15OpenSSF Scorecard: Code-Review — Found 4/13 approved changesets -- score normalized to 3
Inputs used
merged_prs564
open_issues6
closed_issues928
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d1
issue_closed_ratio0.994
closed_unmerged_prs150
first_time_authors_30d1
first_time_prs_merged_30d0
first_time_prs_decided_30d1

Ownership & stewardship

60Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
18/25Owner reach — 314 followers of sinaptik-ai
11.6/25Track record — 6 public repos, account ~2 yr old
Inputs used
followers314
owner_typeOrganization
is_verifiedno
owner_loginsinaptik-ai
public_repos6
account_age_days1,002

Package maintenance

91Excellent
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
26/35Publish recency — latest publish 345 days ago
20/20Version history — 225 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespandasai
ecosystemspypi
any_deprecatedno
min_days_since_publish345

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall

Engineering practices

86Excellent
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
12/20OpenSSF Scorecard: CI-Tests — 6 out of 9 merged PRs checked by a CI test -- score normalized to 6
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pandas-ai.com
10/10Repository description
10/10Topics — 13 topics
10/10Wiki
Inputs used
topicsllm, pandas, ai, data-analysis, data-science, gpt-4, csv, data, sql, database, datalake, data-visualization, text-to-sql
has_wikiyes
homepagehttps://pandas-ai.com
docs_sitehttps://pandas-ai.com
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

36Weak · 16% of overall

Security posture

30At Risk
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
1.5/2.5CI-Tests — 6 out of 9 merged PRs checked by a CI test -- score normalized to 6
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-Review — Found 4/13 approved changesets -- score normalized to 3
2.5/2.5Contributors — project has 8 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 189 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3.1
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

62Moderate
How it's scored
8.1/35Direct dependencies free of known advisories — 2 affected: pillow 10.4.0 (critical 9.1), pyarrow 18.1.0 (high 7.0)
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
28.5/40No advisories left outstanding — 2 advisory-carrying package(s) unaddressed past 90 days; oldest published 218 days ago
Inputs used
sourceosv
advisories36
affected_packages2
assessed_packages36
unassessed_packages0
affected_by_severitycritical 1, high 1
direct_affected_packages2
Matched the pypi:pandasai@3.0.0 runtime dependency closure — what installing the published package pulls in — 36 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

65Good · 4% of overall

Agent context & guidance

45Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.pandas-ai.com/llms.txt)
30.4/40Legible commit history — 57 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.pandas-ai.com/llms.txt
legible_history_share0.57
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

71Good
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 9 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.09
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/191 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes23,307
source_files_sampled191
oversized_source_files0

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

23,799GitHub stars
97contributors
58commits, last 12 months
324days since last push
100releases
1bus factor
6open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'pandasai' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • pypi download figures for pandasai carried forward from the previous scan (stats endpoint unavailable this scan)

More detail

Star and fork history 0 ★ / 2,339 ⇿
0Stars
2,339Forks
12Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

1,2001,4001,6001,8002,0002,2002,4002,339482025-022025-112026-09
Major 1Minor 0Patch 1

Each point covers 2 days.

OpenSSF Scorecard 3.1 / 10
3.1aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-17 14:42 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
6CI-Tests6 out of 9 merged PRs checked by a CI test -- score normalized to 6
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 4/13 approved changesets -- score normalized to 3
10Contributorsproject has 8 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities189 existing vulnerabilities detected
Direct dependencies 16
RegistryPackageVersion constraintManifest
PyPIpython-dotenv^1.0.0pyproject.toml
PyPIpandas^2.0.3pyproject.toml
PyPIscipy1.10.1pyproject.toml
PyPIastor^0.8.1pyproject.toml
PyPImatplotlib<3.8,>=3.7.1pyproject.toml
PyPIpydantic^2.6.4pyproject.toml
PyPIduckdb^1.0.0pyproject.toml
PyPIpillow^10.1.0pyproject.toml
PyPIrequests^2.31.0pyproject.toml
PyPIjinja2^3.1.3pyproject.toml
PyPInumpy^1.17pyproject.toml
PyPIopenpyxl^3.1.5pyproject.toml
PyPIseaborn^0.12.2pyproject.toml
PyPIsqlglot^25.0.3pyproject.toml
PyPIpyarrow>=14.0.1,<19.0.0pyproject.toml
PyPIpyyaml^6.0.2pyproject.toml
All dependencies 272

Full resolved dependency set from the GitHub dependency graph: 20 direct and 252 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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PyPIscikit-learn1.3.2indirect
PyPIscikit-learn1.6.1indirect
PyPIsemver3.0.2indirect
PyPIsentence-transformers2.7.0indirect
PyPIsetuptools70.0.0indirect
PyPIsetuptools75.8.0indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIsniffio1.3.1indirect
PyPIsnowflake-connector-python3.12.4indirect
PyPIsnowflake-sqlalchemy1.7.3indirect
PyPIsortedcontainers2.4.0indirect
PyPIsoupsieve2.6indirect
PyPIsourcery1.33.0indirect
PyPIsqlalchemy2.0.37indirect
PyPIsqlalchemy-bigquery1.12.0indirect
PyPIsqlglotrs0.3.0indirect
PyPIstarlette0.41.3indirect
PyPIsympy1.12.1indirect
PyPIsympy1.13.1indirect
PyPIsympy1.13.3indirect
PyPItenacity9.0.0indirect
PyPIthreadpoolctl3.5.0indirect
PyPIthrift0.20.0indirect
PyPItiktoken0.7.0indirect
PyPItokenizers0.20.3indirect
PyPItokenizers0.21.0indirect
PyPItomli2.2.1indirect
PyPItomlkit0.13.2indirect
PyPItorch2.4.1indirect
PyPItorch2.5.1indirect
PyPItqdm4.67.1indirect
PyPItransformers4.46.3indirect
PyPItransformers4.48.1indirect
PyPItriton3.0.0indirect
PyPItriton3.1.0indirect
PyPItyper0.15.1indirect
PyPItyping-extensions4.12.2indirect
PyPItzdata2024.2indirect
PyPItzdata2025.1indirect
PyPIujson5.10.0indirect
PyPIurllib31.26.20indirect
PyPIurllib32.2.3indirect
PyPIurllib32.3.0indirect
PyPIuvicorn0.34.0indirect
PyPIuvloop0.21.0indirect
PyPIvirtualenv20.29.1indirect
PyPIwatchfiles1.0.4indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.8.0indirect
PyPIwebsockets14.2indirect
PyPIwrapt1.17.2indirect
PyPIyarl1.15.2indirect
PyPIyfinance0.2.52indirect
PyPIzipp3.20.2indirect
PyPIzipp3.21.0indirect
Dependency advisories 2

Installing pypi:pandasai@3.0.0 pulls in 36 packages, direct and transitive: 2 carry known advisories, of which 2 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
pillow10.4.0directcritical3412.3.0
pyarrow18.1.0directhigh223.0.1

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.