Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-20 07:34 UTC

scrapy / cssselect

CSS Selectors for Python

PythonCustom license★ 310 stars⑂ 70 forkssince Apr 2012View on GitHub ↗

scrapy/cssselect holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (100/100) and lowest on AI Readiness (49/100). It was last updated 3 days ago. 3 contributors account for most of its recent work.

92
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.

92
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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

Scrapy projectOrganization
844 followers33 public repossince Apr 2011

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIcssselect1.5.019,233,9292154 days ago

Metrics by category

Vitality

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

66Good · 21% of overall
How it's scored
36/36Push recency — last push 3 days ago
6.9/36Commit cadence — 10/52 weeks with commits
14.3/18Commit volume — 38 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year38
human_commit_share0.98
days_since_last_push3
active_weeks_last_year10
How it's scored
16.2/27Ships releases — 13 version tags (no GitHub releases)
36/36Release recency — latest release 54 days ago
5.4/27Release cadence — a release every ~410.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count13
latest_release_tagv1.5.0
releases_from_tagsyes
days_since_latest_release54
mean_days_between_releases410.4
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?

66Good · 17% of overall
How it's scored
40.4/60Stars — 310 stars
15.3/25Forks — 70 forks
7.1/15Watchers — 20 watchers
Inputs used
forks70
stars310
watchers20
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — license file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads — 19,233,929 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagescssselect
dependents—
ecosystemspypi
total_downloads—
monthly_downloads19,233,929
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?

82Excellent · 23% of overall
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
16.3/22.5Commit distribution — top contributor authored 28% of commits
13.5/13.5Contributor breadth — 29 contributors
10/10OpenSSF Scorecard: Contributors — project has 49 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled29
top_contributor_share0.275
How it's scored
35.9/42Issue resolution — 86% of issues closed
26.6/30PR acceptance — 108/122 decided PRs merged
8.7/13Newcomer PR acceptance — 2/3 first-time contributors' PRs merged in 30d
12/15OpenSSF Scorecard: Code-Review — Found 14/16 approved changesets -- score normalized to 8
Inputs used
merged_prs108
open_issues9
closed_issues53
prs_merged_7d2
prs_decided_7d2
prs_merged_30d5
prs_decided_30d6
issue_closed_ratio0.855
closed_unmerged_prs14
first_time_authors_30d2
first_time_prs_merged_30d2
first_time_prs_decided_30d3
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
21/25Owner reach — 844 followers of scrapy
23.2/25Track record — 33 public repos, account ~15 yr old
Inputs used
followers844
owner_typeOrganization
is_verifiedno
owner_loginscrapy
public_repos33
account_age_days5,635

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 54 days ago
20/20Version history — 21 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagescssselect
ecosystemspypi
any_deprecatedno
min_days_since_publish54

Engineering Quality

Are baseline engineering and documentation practices in place?

100Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.pylint]), tox.ini
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 17 out of 17 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://cssselect.readthedocs.io/
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicscss, python, selectors, hacktoberfest
has_wikiyes
homepagehttps://cssselect.readthedocs.io/
docs_sitehttps://cssselect.readthedocs.io/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

80Excellent · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 17 out of 17 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5Code-Review — Found 14/16 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 49 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
5/5Fuzzing — project is fuzzed
2.2/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
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
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate7.5
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages2
unassessed_packages1
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 2 resolved dependencies against OSV. 1 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

49Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
26.7/40Legible commit history — 49 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.5
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.pylint]), tox.ini
11/11Static type checking — cssselect/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 2 of the last 100 commits are automated dependency updates
4/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configscssselect/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.02
How it's scored
27/45Type-checkable code — Python with type-check config (cssselect/py.typed)
47.1/55Manageable file sizes — 1/7 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes93,485
source_files_sampled7
oversized_source_files1

Key facts

310GitHub stars
29contributors
38commits, last 12 months
3days since last push
13releases
3bus factor
9open issues
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 ★ / 70 ⇿
0Stars
70Forks
13Releases

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.

01325385063757022012-042019-062026-09
Major 1Minor 5Patch 7

Each point covers 14 days.

OpenSSF Scorecard 7.5 / 10
7.5aggregate

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 · 2026-09-20 07:33 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests17 out of 17 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 14/16 approved changesets -- score normalized to 8
10Contributorsproject has 49 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
10Fuzzingproject is fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 3

Full resolved dependency set from the GitHub dependency graph: 0 direct and 3 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIhatchling—indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-rtd-theme3.1.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 2 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 1 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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 statistics — PyPI.