Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-12 12:57 UTC

fredrike / pydaikin

PythonGPL-3.0★ 29 stars⑂ 34 forkssince Feb 2024View on GitHub ↗

fredrike/pydaikin 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 Community & Adoption (63/100). It was last updated 4 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

Fredrik ErlandssonPersonal account
63 followers97 public repossince Mar 2011Consid

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIpydaikin2.19.157,034948 days ago

Metrics by category

Vitality

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

82Excellent · 21% of overall
How it's scored
36/36Push recency — last push 4 days ago
7.6/36Commit cadence — 11/52 weeks with commits
17.1/18Commit volume — 80 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year80
human_commit_share0.67
days_since_last_push4
active_weeks_last_year11

Release discipline

98Exceptional
How it's scored
27/27Ships releases — 22 releases published
36/36Release recency — latest release 8 days ago
27/27Release cadence — a release every ~37 days
8/10OpenSSF Scorecard: Signed-Releases — 5 out of the last 5 releases have a total of 5 signed artifacts.
Inputs used
releases_count22
latest_release_tagv2.19.1
releases_from_tagsno
days_since_latest_release8
mean_days_between_releases37

Community & Adoption

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

63Moderate · 17% of overall
How it's scored
23.5/60Stars — 29 stars
12.7/25Forks — 34 forks
3.3/15Watchers — 5 watchers
Inputs used
forks34
stars29
watchers5
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonbelow_threshold
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (GPL-3.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges8
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateyes
How it's scored
63.4/80Monthly downloads — 57,034 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespydaikin
dependents—
ecosystemspypi
total_downloads—
monthly_downloads57,034
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?

66Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
9/22.5Commit distribution — top contributor authored 60% of commits
13.5/13.5Contributor breadth — 35 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled35
top_contributor_share0.599
How it's scored
33.4/42Issue resolution — 80% of issues closed
26.5/30PR acceptance — 91/103 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-Review — Found 4/19 approved changesets -- score normalized to 2
Inputs used
merged_prs91
open_issues9
closed_issues35
prs_merged_7d0
prs_decided_7d0
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.795
closed_unmerged_prs12
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
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
13/25Owner reach — 63 followers of fredrike
25/25Track record — 97 public repos, account ~15 yr old
Inputs used
followers63
owner_typeUser
is_verified—
owner_loginfredrike
public_repos97
account_age_days5,657
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 8 days ago
20/20Version history — 94 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespydaikin
ecosystemspypi
any_deprecatedno
min_days_since_publish8

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 25 out of 25 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
0/10Repository description
10/10Topics — 3 topics
10/10Wiki
Inputs used
topicsdaikin, hacktoberfest, python3
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

66Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 25 out of 25 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
1.5/7.5Code-Review — Found 4/19 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
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
6/7.5Signed-Releases — 5 out of the last 5 releases have a total of 5 signed artifacts.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities — 1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate5.7

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages12
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:pydaikin@2.19.1 runtime dependency closure — what installing the published package pulls in — 12 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
How it's scored
45/45Agent instructions — AGENTS.md
0/15Machine-readable docs (llms.txt)
29.5/40Legible commit history — 37 of 67 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.552
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes2,376
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
0/10Reproducible environment
4/10Demonstrated agent practice — 2 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 20 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.02
toolchain_manifests—
dependency_bot_commit_share0.2
How it's scored
0/45Type-checkable code — Python without a type-check config
53.3/55Manageable file sizes — 1/32 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes67,716
source_files_sampled32
oversized_source_files1

Key facts

29GitHub stars
35contributors
80commits, last 12 months
4days since last push
22releases
1bus factor
9open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Star history carried forward from 2026-07-15: GitHub restricted the stargazers API to repository admins, so it can no longer be collected. The repository has 29 stars today.

More detail

Star and fork history 26 ★ / 34 ⇿
26Stars
34Forks
21Releases

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.

Star history is shown as collected on 2026-07-15. GitHub restricted the stargazers API to repository administrators in July 2026, so this series can no longer be extended; the current star total above remains live.

0132538263422024-022025-052026-08
Major 0Minor 7Patch 13

Each point covers 3 days.

OpenSSF Scorecard 5.7 / 10
5.7aggregate

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 · 2026-09-12 12:57 UTC

10Binary-Artifactsno binaries found in the repo
1Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests25 out of 25 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 4/19 approved changesets -- score normalized to 2
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow 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
8Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIpsutil—pyproject.toml
PyPIaiohttp—pyproject.toml
PyPIurllib3—pyproject.toml
PyPItenacity—pyproject.toml
All dependencies 10

Full resolved dependency set from the GitHub dependency graph: 4 direct and 6 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiohttp—direct
PyPIpsutil—direct
PyPItenacity—direct
PyPIurllib3—direct
PyPIaresponses3.0.0indirect
PyPIfreezegun1.5.1indirect
PyPIpytest8.3.2indirect
PyPIpytest-asyncio0.24.0indirect
PyPIpytest-cov5.0.0indirect
PyPIsetuptools—indirect
Dependency advisories 0

Installing pypi:pydaikin@2.19.1 pulls in 12 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 statistics — PyPI.