Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-22 18:15 UTC

evangelosmeklis / peepdb

CLI tool and python library to inspect databases fast.

PythonGPL-3.0★ 491 stars⑂ 20 forkssince Aug 2024View on GitHub ↗

KindCommand-line toolhow this is determined

#database-management #python3 #sql #cli #python #open-source #backend-as-a-service #database-as-a-service #developer-tools #nosql #serverless #daatabase

evangelosmeklis/peepdb holds a health index of 27 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (69/100) and lowest on Vitality (25/100). It was last updated 505 days ago. A single contributor accounts for most of its recent work.

overall / 100

At Risk

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.

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)

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 47 is calibrated to 45 on the published index scale (record calibration 2026-08-02).

Ownership

Evangelos MeklisPersonal account

40 followers18 public repossince Nov 2019Nokia

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
PyPI	peepdbpoints to another repo — not scored	0.1.4	30	3	754 days ago

Metrics by category

Vitality

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

25At Risk · 21% of overall

Development activity

1Critical

Abandonment alert

Work has arrived and nobody has attended to it

no human commit in 505 daysautomated commits excludedpull requests left unansweredissues left unansweredreleases stalledOpenSSF Scorecard reports it unmaintainedOverall rating: At Risk ceiling

Silence alone is never the finding — a small, finished library may need no commits for years. This alert requires both: no human commit for a long time, and obligations the project is visibly not discharging. Automated commits do not count as maintenance.

How abandonment is assessed

How it's scored

0/36	Push recency — last push 505 days ago
0/36	Commit cadence — 0/52 weeks with commits
0/18	Commit volume — 0 commits in the last year
0/10	OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0

Inputs used

commits_last_year	0
human_commit_share	1
days_since_last_push	505
active_weeks_last_year	0

Release discipline

60Moderate

How it's scored

27/27	Ships releases — 4 releases published
0/36	Release recency — latest release 754 days ago
27/27	Release cadence — a release every ~7 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	4
latest_release_tag	v0.1.4
releases_from_tags	no
days_since_latest_release	754
mean_days_between_releases	7

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?

64Moderate · 17% of overall

Popularity & adoption

59Moderate

How it's scored

43.6/60	Stars — 491 stars
10.7/25	Forks — 20 forks
5/15	Watchers — 9 watchers

Inputs used

forks	20
stars	491
watchers	9
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

70Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (GPL-3.0)
18/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
0/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	0
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	—
has_pull_request_template	no

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

49Weak · 23% of overall

Maintainer resilience (bus factor)

28At Risk

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
3.2/22.5	Commit distribution — top contributor authored 86% of commits
9.5/13.5	Contributor breadth — 7 contributors
6/10	OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6

Inputs used

bus_factor	1
contributors_sampled	7
top_contributor_share	0.857

Issue & PR responsiveness

70Good

How it's scored

31/42	Issue resolution — 74% of issues closed
25.2/30	PR acceptance — 26/31 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
4.5/15	OpenSSF Scorecard: Code-Review — Found 10/29 approved changesets -- score normalized to 3

Inputs used

merged_prs	26
open_issues	10
closed_issues	28
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	0.737
closed_unmerged_prs	5
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

54Moderate

How it's scored

10/30	Ownership backing — personal (user) account
0/20	Verified domain — not applicable to user accounts
11.6/25	Owner reach — 40 followers of evangelosmeklis
21.3/25	Track record — 18 public repos, account ~6 yr old

Inputs used

followers	40
owner_type	User
is_verified	—
owner_login	evangelosmeklis
public_repos	18
account_age_days	2,541

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

69Good · 19% of overall

Engineering practices

48Weak

How it's scored

24/24	CI workflows — 2 workflow(s)
24/24	Tests present
0/16	Linter config
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
0/20	OpenSSF Scorecard: CI-Tests — 0 out of 18 merged PRs checked by a CI test -- score normalized to 0

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	no
has_precommit_config	no

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://docs.peepdb.dev/
10/10	Repository description
10/10	Topics — 12 topics
10/10	Wiki

Inputs used

topics	database-management, python3, sql, cli, python, open-source, backend-as-a-service, database-as-a-service, developer-tools, nosql, serverless, daatabase
has_wiki	yes
homepage	https://docs.peepdb.dev/
docs_site	https://docs.peepdb.dev/
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?

33At Risk · 16% of overall

Security posture

26At Risk

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0.8/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
0/2.5	CI-Tests — 0 out of 18 merged PRs checked by a CI test -- score normalized to 0
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
2.2/7.5	Code-Review — Found 10/29 approved changesets -- score normalized to 3
1.5/2.5	Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
0/7.5	Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 62 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	2.6

Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

63Moderate

How it's scored

6.2/35	Direct dependencies free of known advisories — 2 affected: mariadb 1.1.14 (critical 9.8), pymongo 4.9.1 (high 8.4)
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
32.1/40	No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 131 days ago

Inputs used

source	osv
advisories	9
affected_packages	2
assessed_packages	20
unassessed_packages	0
affected_by_severity	critical 1, high 1
direct_affected_packages	2

Matched the pypi:peepdb@0.1.4 runtime dependency closure — what installing the published package pulls in — 20 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.

31At Risk · 4% of overall

Agent context & guidance

18Critical

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
18/40	Legible commit history — 26 of 77 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.338
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

32At Risk

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
0/11	Lint / format config
0/11	Static type checking
10/10	Reproducible environment — lockfile
0/10	Demonstrated agent practice — no agent-authored commits among the last 77
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	Gemfile.lock
has_dockerfile	no
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	no
typecheck_configs	—
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

55Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
55/55	Manageable file sizes — 0/24 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	7,565
source_files_sampled	24
oversized_source_files	0

Key facts

491GitHub stars

7contributors

0commits, last 12 months

505days since last push

4releases

1bus factor

10open issues

PyPI, RubyGemspackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
pypi package 'peepdb' points at a different repository (https://github.com/PeepDB-dev/peepdb); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 20 ⇿

0Stars

20Forks

2Releases

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.

Major 0Minor 0Patch 2

Each point covers 2 days.

OpenSSF Scorecard 2.6 / 10

2.6aggregate

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 · 2026-10-22 18:15 UTC

10	Binary-Artifacts	no binaries found in the repo
1	Branch-Protection	branch protection is not maximal on development and all release branches
0	CI-Tests	0 out of 18 merged PRs checked by a CI test -- score normalized to 0
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
3	Code-Review	Found 10/29 approved changesets -- score normalized to 3
6	Contributors	project has 2 contributing companies or organizations -- score normalized to 6
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
0	Maintained	0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	62 existing vulnerabilities detected

All dependencies 107

Full resolved dependency set from the GitHub dependency graph: 0 direct and 107 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	async-timeout	`4.0.3`	indirect
PyPI	backports-tarfile	`1.2.0`	indirect
PyPI	cachecontrol	`0.14.0`	indirect
PyPI	cachetools	`—`	indirect
PyPI	cachetools	`5.5.0`	indirect
PyPI	certifi	`2024.8.30`	indirect
PyPI	cffi	`1.17.1`	indirect
PyPI	charset-normalizer	`3.3.2`	indirect
PyPI	click	`—`	indirect
PyPI	click	`8.1.7`	indirect
PyPI	coverage	`7.6.1`	indirect
PyPI	cryptography	`—`	indirect
PyPI	cryptography	`43.0.0`	indirect
PyPI	dnspython	`2.6.1`	indirect
PyPI	exceptiongroup	`1.2.2`	indirect
PyPI	firebase-admin	`6.5.0`	indirect
PyPI	google-api-core	`2.20.0`	indirect
PyPI	google-api-python-client	`2.147.0`	indirect
PyPI	google-auth	`2.35.0`	indirect
PyPI	google-auth-httplib2	`0.2.0`	indirect
PyPI	google-cloud-core	`2.4.1`	indirect
PyPI	google-cloud-firestore	`2.19.0`	indirect
PyPI	google-cloud-storage	`2.18.2`	indirect
PyPI	google-crc32c	`1.6.0`	indirect
PyPI	google-resumable-media	`2.7.2`	indirect
PyPI	googleapis-common-protos	`1.65.0`	indirect
PyPI	grpcio	`1.66.2`	indirect
PyPI	grpcio-status	`1.66.2`	indirect
PyPI	httplib2	`0.22.0`	indirect
PyPI	idna	`3.10`	indirect
PyPI	importlib-metadata	`8.5.0`	indirect
PyPI	iniconfig	`2.0.0`	indirect
PyPI	jaraco-classes	`3.4.0`	indirect
PyPI	jaraco-context	`6.0.1`	indirect
PyPI	jaraco-functools	`4.1.0`	indirect
PyPI	keyring	`—`	indirect
PyPI	keyring	`25.4.1`	indirect
PyPI	mariadb	`—`	indirect
PyPI	mariadb	`1.1.10`	indirect
PyPI	more-itertools	`10.5.0`	indirect
PyPI	msgpack	`1.1.0`	indirect
PyPI	mysql-connector-python	`—`	indirect
PyPI	mysql-connector-python	`9.0.0`	indirect
PyPI	oracledb	`2.5.1`	indirect
PyPI	packaging	`24.1`	indirect
PyPI	pluggy	`1.5.0`	indirect
PyPI	proto-plus	`1.24.0`	indirect
PyPI	protobuf	`5.28.2`	indirect
PyPI	psycopg2-binary	`—`	indirect
PyPI	psycopg2-binary	`2.9.9`	indirect
PyPI	pyasn1	`0.6.1`	indirect
PyPI	pyasn1-modules	`0.4.1`	indirect
PyPI	pycparser	`2.22`	indirect
PyPI	pyjwt	`2.9.0`	indirect
PyPI	pymongo	`4.9.1`	indirect
PyPI	pymysql	`—`	indirect
PyPI	pymysql	`1.1.1`	indirect
PyPI	pyodbc	`5.2.0`	indirect
PyPI	pyparsing	`3.1.4`	indirect
PyPI	pytest	`8.3.2`	indirect
PyPI	pytest-cov	`5.0.0`	indirect
PyPI	redis	`5.2.0`	indirect
PyPI	requests	`2.32.3`	indirect
PyPI	rsa	`4.9`	indirect
PyPI	tabulate	`—`	indirect
PyPI	tabulate	`0.8.9`	indirect
PyPI	tomli	`2.0.1`	indirect
PyPI	uritemplate	`4.1.1`	indirect
PyPI	urllib3	`2.2.3`	indirect
PyPI	zipp	`3.20.2`	indirect
RubyGems	addressable	`2.8.7`	indirect
RubyGems	bigdecimal	`3.1.8`	indirect
RubyGems	colorator	`1.1.0`	indirect
RubyGems	concurrent-ruby	`1.3.4`	indirect
RubyGems	em-websocket	`0.5.3`	indirect
RubyGems	eventmachine	`1.2.7`	indirect
RubyGems	ffi	`1.17.0`	indirect
RubyGems	ffi	`1.17.0-x86_64-linux-gnu`	indirect
RubyGems	forwardable-extended	`2.6.0`	indirect
RubyGems	google-protobuf	`4.27.3`	indirect
RubyGems	http_parser.rb	`0.8.0`	indirect
RubyGems	i18n	`1.14.5`	indirect
RubyGems	jekyll	`4.3.3`	indirect
RubyGems	jekyll-include-cache	`0.2.1`	indirect
RubyGems	jekyll-sass-converter	`3.0.0`	indirect
RubyGems	jekyll-seo-tag	`2.8.0`	indirect
RubyGems	jekyll-watch	`2.2.1`	indirect
RubyGems	just-the-docs	`0.9.0`	indirect
RubyGems	kramdown	`2.4.0`	indirect
RubyGems	kramdown-parser-gfm	`1.1.0`	indirect
RubyGems	liquid	`4.0.4`	indirect
RubyGems	listen	`3.9.0`	indirect
RubyGems	mercenary	`0.4.0`	indirect
RubyGems	pathutil	`0.16.2`	indirect
RubyGems	public_suffix	`6.0.1`	indirect
RubyGems	rake	`13.2.1`	indirect
RubyGems	rb-fsevent	`0.11.2`	indirect
RubyGems	rb-inotify	`0.11.1`	indirect
RubyGems	rexml	`3.3.5`	indirect
RubyGems	rouge	`4.3.0`	indirect
RubyGems	safe_yaml	`1.0.5`	indirect
RubyGems	sass-embedded	`1.77.8`	indirect
RubyGems	sass-embedded	`1.77.8-x86_64-linux-gnu`	indirect
RubyGems	strscan	`3.1.0`	indirect
RubyGems	terminal-table	`3.0.2`	indirect
RubyGems	unicode-display_width	`2.5.0`	indirect
RubyGems	webrick	`1.8.1`	indirect

Dependency advisories 2

Installing pypi:peepdb@0.1.4 pulls in 20 packages, direct and transitive: 2 carry known advisories, of which 2 are direct dependencies.

Package	Version	Relation	Severity	Advisories	Fixed in
mariadb	`1.1.14`	direct	critical	1	—
pymongo	`4.9.1`	direct	high	8	`4.18.2`

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.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

Related records