Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-07 04:08 UTC

ScrapeGraphAI / scrapegraph-py

Official Python SDK for the ScrapeGraph AI API. Smart scraping, search, crawling, markdownify, agentic browser automation, scheduled jobs, and structured data extraction

Jupyter NotebookMIT★ 86 stars⑂ 16 forkssince Oct 2024View on GitHub ↗

ScrapeGraphAI/scrapegraph-py holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on AI Readiness (83/100) and lowest on Security (54/100). It was last updated 37 days ago. 2 contributors account for most of its recent work.

83
overall / 100
Excellent

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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

ScrapeGraphAIOrganization
594 followers30 public repossince May 2024

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIscrapegraph-py2.3.1212,8618337 days agoaiapiscrapingsdkweb-scraping

Metrics by category

Vitality

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

78Good · 21% of overall
How it's scored
18/36Push recencylast push 37 days ago
18.7/36Commit cadence27/52 weeks with commits
18/18Commit volume202 commits in the last year
8/10OpenSSF Scorecard: Maintained9 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 8
Inputs used
commits_last_year202
human_commit_share0.81
days_since_last_push37
active_weeks_last_year27

Release discipline

100Exceptional
How it's scored
27/27Ships releases82 releases published
36/36Release recencylatest release 37 days ago
27/27Release cadencea release every ~20.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count82
latest_release_tagv2.3.2
releases_from_tagsno
days_since_latest_release37
mean_days_between_releases20.7
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?

63Moderate · 17% of overall
How it's scored
31.3/60Stars86 stars
9.8/25Forks16 forks
0/15Watchers1 watchers
Inputs used
forks16
stars86
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, shields.io
has_pull_request_templateno
How it's scored
71/80Monthly downloads212,861 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesscrapegraph-py
dependents
ecosystemspypi
total_downloads
monthly_downloads212,861
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?

73Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
11.8/22.5Commit distributiontop contributor authored 48% of commits
13.5/13.5Contributor breadth11 contributors
10/10OpenSSF Scorecard: Contributorsproject has 6 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled11
top_contributor_share0.477
How it's scored
37.8/42Issue resolution90% of issues closed
25.4/30PR acceptance78/92 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 6/23 approved changesets -- score normalized to 2
Inputs used
merged_prs78
open_issues1
closed_issues9
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.9
closed_unmerged_prs14
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
19.9/25Owner reach594 followers of ScrapeGraphAI
15.4/25Track record30 public repos, account ~2 yr old
Inputs used
followers594
owner_typeOrganization
is_verifiedno
owner_loginScrapeGraphAI
public_repos30
account_age_days831

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 37 days ago
20/20Version history83 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesscrapegraph-py
ecosystemspypi
any_deprecatedno
min_days_since_publish37

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall
How it's scored
24/24CI workflows5 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://scrapegraphai.com
10/10Repository description
10/10Topics11 topics
0/10Wiki
Inputs used
topicsapi, sdk-js, sdk-nodejs, sdk-python, scrapegraph, scraping, web-crawler, web-scraping, json-schema, python, web-scraping-python
has_wikino
homepagehttps://scrapegraphai.com
docs_sitehttps://scrapegraphai.com
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

54Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
2.5/2.5CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 6/23 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 6 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
6/7.5Maintained9 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 8
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.2
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages11
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:scrapegraph-py@2.3.1 runtime dependency closure — what installing the published package pulls in — 11 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.

83Excellent · 4% of overall
How it's scored
45/45Agent instructionsCLAUDE.md
15/15Machine-readable docs (llms.txt)llms.txt served by the project website (https://scrapegraphai.com/llms.txt)
40/40Legible commit history78 of 81 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://scrapegraphai.com/llms.txt
legible_history_share0.963
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes3,491
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
11/11Static type checkingsrc/scrapegraph_py/py.typed
10/10Reproducible environmentlockfile
10/10Demonstrated agent practice55 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configssrc/scrapegraph_py/py.typed
agent_commit_share0.55
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable codeJupyter Notebook with type-check config (src/scrapegraph_py/py.typed)
55/55Manageable file sizes0/42 source files over 60KB
Inputs used
primary_languageJupyter Notebook
largest_source_bytes18,956
source_files_sampled42
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplescookbook, examples, notebooks
Inputs used
example_dirscookbook, examples, 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

86GitHub stars
11contributors
202commits, last 12 months
37days since last push
82releases
2bus factor
1open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 16 ⇿
0Stars
16Forks
57Releases

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.

04812161612025-012025-092026-06
Major 2Minor 39Patch 12

Each point covers 2 days.

OpenSSF Scorecard 4.2 / 10
4.2aggregate

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 · 2026-09-07 04:08 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 6/23 approved changesets -- score normalized to 2
10Contributorsproject has 6 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
8Maintained9 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 8
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
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPIhttpx>=0.27.0pyproject.toml
PyPIpydantic>=2.0.0pyproject.toml
All dependencies 26

Full resolved dependency set from the GitHub dependency graph: 2 direct and 24 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIhttpx0.28.1direct
PyPIpydantic2.13.0direct
npm@semantic-release/changelog^6.0.0indirect
npm@semantic-release/git^10.0.0indirect
npm@semantic-release/github^9.2.6indirect
npmsemantic-release^23.0.0indirect
npmsemantic-release-pypi^3.0.0indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.13.0indirect
PyPIcertifi2026.2.25indirect
PyPIcolorama0.4.6indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIidna3.11indirect
PyPIiniconfig2.3.0indirect
PyPIpackaging26.0indirect
PyPIpluggy1.6.0indirect
PyPIpydantic-core2.46.0indirect
PyPIpygments2.20.0indirect
PyPIpytest9.0.3indirect
PyPIpytest-asyncio1.3.0indirect
PyPIpython-dotenv1.2.2indirect
PyPIruff0.15.10indirect
PyPIscrapegraph-py2.1.1indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
Dependency advisories 0

Installing pypi:scrapegraph-py@2.3.1 pulls in 11 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

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 statisticsPyPI.