Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 13:45 UTC

nephila / giturlparse

Parse & rewrite git urls (supports GitHub, Bitbucket, Assembla ...)

PythonApache-2.0★ 101 stars⑂ 30 forkssince Dec 2014View on GitHub ↗

nephila/giturlparse holds a health index of 87 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (86/100) and lowest on AI Readiness (43/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

87
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.

87
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 73 is calibrated to 87 on the published index scale (record calibration 2026-08-02).

Ownership

NephilaOrganization · verified domain
96 followers117 public repossince Feb 2011

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIgiturlparse0.15.021,392,614972 days agogiturlparse

Metrics by category

Vitality

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

77Good · 21% of overall
How it's scored
36/36Push recencylast push 2 days ago
15.9/36Commit cadence23/52 weeks with commits
13.9/18Commit volume34 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year34
human_commit_share0.35
days_since_last_push2
active_weeks_last_year23
How it's scored
27/27Ships releases9 releases published
36/36Release recencylatest release 72 days ago
12.6/27Release cadencea release every ~348.6 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count9
latest_release_tag0.15.0
releases_from_tagsno
days_since_latest_release72
mean_days_between_releases348.6

Community & Adoption

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

71Good · 17% of overall
How it's scored
32.4/60Stars101 stars
12.2/25Forks30 forks
2.7/15Watchers4 watchers
Inputs used
forks30
stars101
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes
How it's scored
80/80Monthly downloads21,392,614 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesgiturlparse
dependents
ecosystemspypi
total_downloads
monthly_downloads21,392,614
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
9/54Bus factor1 contributor(s) cover half of all commits
11.1/22.5Commit distributiontop contributor authored 51% of commits
13.5/13.5Contributor breadth15 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor1
contributors_sampled15
top_contributor_share0.507
How it's scored
30/42Issue resolution71% of issues closed
25.6/30PR acceptance94/110 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs94
open_issues12
closed_issues30
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.714
closed_unmerged_prs16
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
20/20Verified domain
14.3/25Owner reach96 followers of nephila
25/25Track record117 public repos, account ~15 yr old
Inputs used
followers96
owner_typeOrganization
is_verifiedyes
owner_loginnephila
public_repos117
account_age_days5,665

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 72 days ago
20/20Version history9 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesgiturlparse
ecosystemspypi
any_deprecatedno
min_days_since_publish72

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows5 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff], [tool.black], [tool.isort]), tox.ini
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://pypi.python.org/pypi/giturlparse
10/10Repository description
10/10Topics1 topics
0/10Wiki
Inputs used
topicshacktoberfest
has_wikino
homepagehttps://pypi.python.org/pypi/giturlparse
docs_sitehttps://pypi.python.org/pypi/giturlparse
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

60Moderate · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
20/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestspyproject.toml, requirements-test.txt, requirements.txt, setup.cfg, setup.py
has_codeql_workflowyes
has_security_policyno
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

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.

43Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
32/40Legible commit history21 of 35 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.6
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff], [tool.black], [tool.isort]), tox.ini
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance1 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.01
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/15 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes29,142
source_files_sampled15
oversized_source_files0

Key facts

101GitHub stars
15contributors
34commits, last 12 months
2days since last push
9releases
1bus factor
12open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • No resolved dependencies carried a version and a supported ecosystem
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 30 ⇿
0Stars
30Forks
8Releases

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.

0510152025302922016-052021-062026-06
Major 0Minor 5Patch 3

Each point covers 10 days.

All dependencies 5

Full resolved dependency set from the GitHub dependency graph: 0 direct and 5 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcoverageindirect
PyPIcoverallsindirect
PyPImockindirect
PyPIsetuptoolsindirect
PyPItoxindirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

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.