Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-21 00:04 UTC

dbfixtures / pytest-postgresql

This is a pytest plugin, that enables you to test your code that relies on a running PostgreSQL Database. It allows you to specify fixtures for PostgreSQL process and client.

PythonLGPL-3.0★ 532 stars⑂ 55 forkssince Sep 2016View on GitHub ↗
KindPluginLibraryhow this is determined

dbfixtures/pytest-postgresql holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Sustainability & Governance (64/100). It was last updated today. A single contributor accounts 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

4 followers9 public repossince Feb 2025

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpytest-postgresql9.1.13,914,5844916 days agofixturepostgresqlpytesttests

Metrics by category

Vitality

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

92Excellent · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recency — last push 0 days ago
36/36Commit cadence — 52/52 weeks with commits
18/18Commit volume — 495 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year495
human_commit_share0.24
days_since_last_push0
active_weeks_last_year52
How it's scored
16.2/27Ships releases — 49 version tags (no GitHub releases)
36/36Release recency — latest release 16 days ago
19.8/27Release cadence — a release every ~84.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count49
latest_release_tagv9.1.1
releases_from_tagsyes
days_since_latest_release16
mean_days_between_releases84.5
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?

75Good · 17% of overall
How it's scored
44.2/60Stars — 532 stars
14.4/25Forks — 55 forks
4.3/15Watchers — 7 watchers
Inputs used
forks55
stars532
watchers7
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (LGPL-3.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads — 3,914,584 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespytest-postgresql
dependents—
ecosystemspypi
total_downloads—
monthly_downloads3,914,584
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?

64Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
11/22.5Commit distribution — top contributor authored 51% of commits
13.5/13.5Contributor breadth — 42 contributors
10/10OpenSSF Scorecard: Contributors — project has 15 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled42
top_contributor_share0.512
How it's scored
39.4/42Issue resolution — 94% of issues closed
28.8/30PR acceptance — 1,232/1,285 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/2 approved changesets -- score normalized to 0
Inputs used
merged_prs1,232
open_issues12
closed_issues180
prs_merged_7d2
prs_decided_7d2
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio0.938
closed_unmerged_prs53
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 backing — organization-owned
0/20Verified domain
5/25Owner reach — 4 followers of dbfixtures
10.6/25Track record — 9 public repos, account ~1 yr old
Inputs used
followers4
owner_typeOrganization
is_verifiedno
owner_logindbfixtures
public_repos9
account_age_days608

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 16 days ago
20/20Version history — 49 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespytest-postgresql
ecosystemspypi
any_deprecatedno
min_days_since_publish16

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows — 12 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 — 15 out of 15 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

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://pypi.python.org/pypi/pytest-postgresql/
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicspython, pytest-plugin, postgresql, pytest
has_wikiyes
homepagehttps://pypi.python.org/pypi/pytest-postgresql/
docs_sitehttps://pypi.python.org/pypi/pytest-postgresql/
has_readmeyes
has_docs_diryes
has_descriptionyes

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
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 15 out of 15 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
0/7.5Code-Review — Found 0/2 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 15 contributing companies or organizations
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 24 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
3/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
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
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities — 1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.8
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
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_packages9
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:pytest-postgresql@9.1.1 runtime dependency closure — what installing the published package pulls in — 9 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.

66Good · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 18 of 24 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.75
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])
11/11Static type checking — pytest_postgresql/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 31 of the last 100 commits are automated dependency updates
6/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configspytest_postgresql/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.31
How it's scored
27/45Type-checkable code — Python with type-check config (pytest_postgresql/py.typed)
55/55Manageable file sizes — 0/43 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes41,959
source_files_sampled43
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
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

532GitHub stars
42contributors
495commits, last 12 months
0days since last push
49releases
1bus factor
12open 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 ★ / 55 ⇿
0Stars
55Forks
46Releases

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.

01020304050605522016-122021-112026-09
Major 8Minor 15Patch 23

Each point covers 9 days.

OpenSSF Scorecard 5.8 / 10
5.8aggregate

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 · 2026-10-21 00:04 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests15 out of 15 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/2 approved changesets -- score normalized to 0
10Contributorsproject has 15 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
6Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 6
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 5
RegistryPackageVersion constraintManifest
PyPImirakuru>=2.6.0pyproject.toml
PyPIpackaging—pyproject.toml
PyPIport-for>=0.7.3pyproject.toml
PyPIpsycopg>=3.0.0pyproject.toml
PyPIpytest>=8.4pyproject.toml
All dependencies 43

Full resolved dependency set from the GitHub dependency graph: 10 direct and 33 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImirakuru2.6.0direct
PyPImirakuru3.0.4direct
PyPIpackaging23.2direct
PyPIpackaging26.3direct
PyPIport-for0.7.3direct
PyPIport-for1.1.1direct
PyPIpsycopg3.0.0direct
PyPIpsycopg3.3.6direct
PyPIpytest9.0.3direct
PyPIpytest9.1.1direct
PyPIaiofiles23.2.1indirect
PyPIaiofiles25.1.0indirect
PyPIast-serialize0.12.1indirect
PyPIcli-ui0.19.0indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.16.2indirect
PyPIdocopt0.6.2indirect
PyPIexecnet2.1.2indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIlibrt0.16.0indirect
PyPImarkupsafe3.0.3indirect
PyPImock5.2.0indirect
PyPImypy2.4.0indirect
PyPImypy-extensions1.1.0indirect
PyPIpathspec1.1.1indirect
PyPIpluggy1.6.0indirect
PyPIpsutil7.2.2indirect
PyPIpsycopg-binary3.3.6indirect
PyPIpygments2.20.0indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpytest-postgresql9.1.1indirect
PyPIpytest-xdist3.8.0indirect
PyPIschema0.7.8indirect
PyPItabulate0.9.0indirect
PyPItbump6.11.0indirect
PyPItomlkit0.11.8indirect
PyPItowncrier26.9.0indirect
PyPItypes-aiofiles25.1.0.20260518indirect
PyPItyping-extensions4.16.0indirect
PyPItzdata2026.3indirect
PyPIunidecode1.4.0indirect
Dependency advisories 0

Installing pypi:pytest-postgresql@9.1.1 pulls in 9 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.