joke2k / faker
Faker is a Python package that generates fake data for you.
joke2k/faker holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Community & Adoption (92/100) and lowest on AI Readiness (62/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.
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.
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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).
Ownership
This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.
Package ecosystems
| Registry | Package | Version | Downloads / mo | Versions | Last publish | Tags |
|---|---|---|---|---|---|---|
| PyPI | Faker | 40.39.0 | - | 506 | 2 days ago | fakerfixturesdatatestmockgenerator |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
Development activity
How it's scored
| 36/36 | Push recency — last push 1 days ago |
| 22.2/36 | Commit cadence — 32/52 weeks with commits |
| 18/18 | Commit volume — 279 commits in the last year |
| 0/10 | OpenSSF Scorecard: Maintained — no data |
Inputs used
| commits_last_year | 279 |
| human_commit_share | 0.96 |
| days_since_last_push | 1 |
| active_weeks_last_year | 32 |
Release discipline
How it's scored
| 27/27 | Ships releases — 100 releases published |
| 36/36 | Release recency — latest release 2 days ago |
| 27/27 | Release cadence — a release every ~6.2 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 100 |
| latest_release_tag | v40.39.0 |
| releases_from_tags | no |
| days_since_latest_release | 2 |
| mean_days_between_releases | 6.2 |
Community & Adoption
Does the project have users, downloads, attention, and a welcoming setup for contributors?
Popularity & adoption
How it's scored
| 60/60 | Stars — 19,402 stars |
| 25/25 | Forks — 2,115 forks |
| 13/15 | Watchers — 222 watchers |
Inputs used
| forks | 2,115 |
| stars | 19,402 |
| watchers | 222 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
How it's scored
| 22.5/22.5 | README |
| 22.5/22.5 | License — recognized license (MIT) |
| 18/18 | CONTRIBUTING guide |
| 0/13.5 | Code of conduct |
| 7.2/7.2 | Issue template |
| 6.3/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| readme_badges | 0 |
| has_contributing | yes |
| has_issue_template | yes |
| has_code_of_conduct | no |
| readme_badge_services | — |
| has_pull_request_template | yes |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
Maintainer resilience (bus factor)
How it's scored
| 9/54 | Bus factor — 1 contributor(s) cover half of all commits |
| 7.4/22.5 | Commit distribution — top contributor authored 67% of commits |
| 13.5/13.5 | Contributor breadth — 99 contributors |
| 0/10 | OpenSSF Scorecard: Contributors — no data |
Inputs used
| bus_factor | 1 |
| contributors_sampled | 99 |
| top_contributor_share | 0.671 |
Issue & PR responsiveness
How it's scored
| 41.5/42 | Issue resolution — 99% of issues closed |
| 25/30 | PR acceptance — 1,315/1,578 decided PRs merged |
| 5.2/13 | Newcomer PR acceptance — 4/10 first-time contributors' PRs merged in 30d |
| 0/15 | OpenSSF Scorecard: Code-Review — no data |
Inputs used
| merged_prs | 1,315 |
| open_issues | 10 |
| closed_issues | 836 |
| prs_merged_7d | 3 |
| prs_decided_7d | 3 |
| prs_merged_30d | 6 |
| prs_decided_30d | 13 |
| issue_closed_ratio | 0.988 |
| closed_unmerged_prs | 263 |
| first_time_authors_30d | 6 |
| first_time_prs_merged_30d | 4 |
| first_time_prs_decided_30d | 10 |
Ownership & stewardship
How it's scored
| 10/30 | Ownership backing — personal (user) account |
| 0/20 | Verified domain — not applicable to user accounts |
| 19.8/25 | Owner reach — 565 followers of joke2k |
| 23.8/25 | Track record — 41 public repos, account ~16 yr old |
Inputs used
| followers | 565 |
| owner_type | User |
| is_verified | — |
| owner_login | joke2k |
| public_repos | 41 |
| account_age_days | 5,882 |
Package maintenance
How it's scored
| 25/25 | Published & resolvable — 1 package(s) on pypi |
| 35/35 | Publish recency — latest publish 2 days ago |
| 20/20 | Version history — 506 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | Faker |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 2 |
Engineering Quality
Are baseline engineering and documentation practices in place?
Engineering practices
How it's scored
| 24/24 | CI workflows — 3 workflow(s) |
| 24/24 | Tests present |
| 16/16 | Linter config — tox.ini |
| 0/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — no data |
Inputs used
| has_ci | yes |
| has_tests | yes |
| has_editorconfig | no |
| has_linter_config | yes |
| has_precommit_config | no |
Documentation
How it's scored
| 30/30 | README |
| 25/25 | Documentation directory |
| 15/15 | Documentation / homepage site — https://faker.readthedocs.io |
| 10/10 | Repository description |
| 10/10 | Topics — 9 topics |
| 10/10 | Wiki |
Inputs used
| topics | python, fake, testing, dataset, fake-data, test-data, test-data-generator, faker, faker-generator |
| has_wiki | yes |
| homepage | https://faker.readthedocs.io |
| docs_site | https://faker.readthedocs.io |
| has_readme | yes |
| has_docs_dir | yes |
| has_description | yes |
Security
Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?
Security posture
How it's scored
| 30/30 | Security policy (SECURITY.md) |
| 25/25 | Dependabot config |
| 0/25 | Dependency lockfiles |
| 0/20 | CodeQL workflow |
Inputs used
| source | file_signals |
| lockfiles | — |
| manifests | setup.cfg, setup.py |
| has_codeql_workflow | no |
| has_security_policy | yes |
| has_dependabot_config | yes |
Dependency advisories
How it's scored
| 35/35 | Direct dependencies free of known advisories — no direct dependency carries a known advisory |
| 0/25 | Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope |
| 0/40 | No advisories left outstanding — no advisory carries a publication date |
Inputs used
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 4 |
| unassessed_packages | 22 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
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.
Agent context & guidance
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 18.3/40 | Legible commit history — 33 of 96 human commits state their intent (structured subject or explanatory body) |
Inputs used
| has_llms_txt | no |
| llms_txt_url | — |
| legible_history_share | 0.344 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Verify loop (build / test / typecheck)
How it's scored
| 18/18 | One-command bootstrap — Makefile, docs/Makefile |
| 22/22 | Automated tests |
| 11/11 | Lint / format config — tox.ini |
| 11/11 | Static type checking — faker/py.typed, mypy.ini |
| 0/10 | Reproducible environment |
| 10/10 | Demonstrated agent practice — 32 of the last 100 commits agent-authored or agent-credited |
| 8/8 | Automated maintenance — 4 of the last 100 commits are automated dependency updates |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — no data |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | Makefile, docs/Makefile |
| has_devcontainer | no |
| has_linter_config | yes |
| typecheck_configs | faker/py.typed, mypy.ini |
| agent_commit_share | 0.32 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0.04 |
Code legibility for models
How it's scored
| 27/45 | Type-checkable code — Python with type-check config (faker/py.typed, mypy.ini) |
| 53/55 | Manageable file sizes — 30/814 source files over 60KB |
Inputs used
| primary_language | Python |
| largest_source_bytes | 769,957 |
| source_files_sampled | 814 |
| oversized_source_files | 30 |
Key facts
Data collection warnings
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- pypi download statistics for 'Faker' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
- OpenSSF Scorecard timed out after 240s; skipping Scorecard checks
More detail
Star and fork history 0 ★ / 2,115 ⇿
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.
Each point covers 6 days.
All dependencies 26
Full resolved dependency set from the GitHub dependency graph: 0 direct and 26 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | black | — | indirect |
| PyPI | check-manifest | — | indirect |
| PyPI | coverage | — | indirect |
| PyPI | doc8 | — | indirect |
| PyPI | email-validator | 1.0.3 | indirect |
| PyPI | flake8 | — | indirect |
| PyPI | flake8-comprehensions | — | indirect |
| PyPI | freezegun | — | indirect |
| PyPI | isort | — | indirect |
| PyPI | mock | 2.0.0 | indirect |
| PyPI | mypy | — | indirect |
| PyPI | mypy-extensions | — | indirect |
| PyPI | packaging | — | indirect |
| PyPI | pillow | — | indirect |
| PyPI | pytest | — | indirect |
| PyPI | python-dateutil | — | indirect |
| PyPI | python-stdnum | — | indirect |
| PyPI | setuptools | — | indirect |
| PyPI | six | — | indirect |
| PyPI | text-unidecode | 1.2 | indirect |
| PyPI | tox | — | indirect |
| PyPI | twine | — | indirect |
| PyPI | tzdata | — | indirect |
| PyPI | ukpostcodeparser | 1.1.2 | indirect |
| PyPI | validators | — | indirect |
| PyPI | wheel | — | indirect |
Dependency advisories 0
This repository publishes no package the index resolves, so its own dependency graph was assessed — 4 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 22 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.
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.