Software health reportschema 0.30.0 · metrics 2.10.0 · 2026-08-04 18:12 UTC

Textualize / rich

Rich is a Python library for rich text and beautiful formatting in the terminal.

PythonMIT★ 57,002 stars⑂ 2,280 forkssince Nov 2019View on GitHub ↗

KindLibraryCommand-line toolhow this is determined

#python #python3 #python-library #terminal #terminal-color #markdown #tables #syntax-highlighting #ansi-colors #progress-bar-python #progress-bar #traceback #rich #tracebacks-rich #emoji #tui

Textualize/rich holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Community & Adoption (97/100) and lowest on Vitality (64/100). It was last updated 42 days ago. A single contributor accounts for most of its recent work.

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.

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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).

Ownership

TextualizeOrganization

2,363 followers33 public repossince Oct 2021

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

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	rich	15.0.0	592,951,204	207	114 days ago

Metrics by category

Vitality

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

64Moderate · 21% of overall

Development activity

52Moderate

How it's scored

18/36	Push recency — last push 42 days ago
11.8/36	Commit cadence — 17/52 weeks with commits
18/18	Commit volume — 177 commits in the last year
4/10	OpenSSF Scorecard: Maintained — 2 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 4

Inputs used

commits_last_year	177
human_commit_share	0.98
days_since_last_push	42
active_weeks_last_year	17

Release discipline

82Excellent

How it's scored

27/27	Ships releases — 100 releases published
27/36	Release recency — latest release 114 days ago
19.8/27	Release cadence — a release every ~58.4 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	100
latest_release_tag	v15.0.0
releases_from_tags	no
days_since_latest_release	114
mean_days_between_releases	58.4

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?

97Exceptional · 17% of overall

Popularity & adoption

100Exceptional

How it's scored

60/60	Stars — 57,002 stars
25/25	Forks — 2,280 forks
15/15	Watchers — 526 watchers

Inputs used

forks	2,280
stars	57,002
watchers	526
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

92Excellent

How it's scored

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

Inputs used

has_readme	yes
has_license	yes
readme_badges	5
has_contributing	yes
has_issue_template	no
has_code_of_conduct	yes
readme_badge_services	badge.fury.io, shields.io
has_pull_request_template	yes

Ecosystem adoption (downloads)

100Exceptional

How it's scored

80/80	Monthly downloads — 592,951,204 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	rich
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	592,951,204
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?

69Good · 23% of overall

Maintainer resilience (bus factor)

38Weak

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
5.4/22.5	Commit distribution — top contributor authored 76% of commits
13.5/13.5	Contributor breadth — 99 contributors
10/10	OpenSSF Scorecard: Contributors — project has 51 contributing companies or organizations

Inputs used

bus_factor	1
contributors_sampled	99
top_contributor_share	0.758

Issue & PR responsiveness

56Moderate

How it's scored

35.6/42	Issue resolution — 85% of issues closed
19/30	PR acceptance — 869/1,369 decided PRs merged
0/13	Newcomer PR acceptance — 0/1 first-time contributors' PRs merged in 30d
1.5/15	OpenSSF Scorecard: Code-Review — Found 1/10 approved changesets -- score normalized to 1

Inputs used

merged_prs	869
open_issues	232
closed_issues	1,286
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	1
issue_closed_ratio	0.847
closed_unmerged_prs	500
first_time_authors_30d	1
first_time_prs_merged_30d	0
first_time_prs_decided_30d	1

Ownership & stewardship

94Exceptional

How it's scored

30/30	Ownership backing — organization-owned
0/20	Verified domain — verified-domain status not read for this organization
24.3/25	Owner reach — 2,363 followers of Textualize
20.7/25	Track record — 33 public repos, account ~4 yr old

Inputs used

followers	2,363
owner_type	Organization
is_verified	—
owner_login	Textualize
public_repos	33
account_age_days	1,740

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

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 114 days ago
20/20	Version history — 207 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	rich
ecosystems	pypi
any_deprecated	no
min_days_since_publish	114

Engineering Quality

Are baseline engineering and documentation practices in place?

94Exceptional · 19% of overall

Engineering practices

90Excellent

How it's scored

24/24	CI workflows — 6 workflow(s)
24/24	Tests present
16/16	Linter config — tox.ini
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
16/20	OpenSSF Scorecard: CI-Tests — 6 out of 7 merged PRs checked by a CI test -- score normalized to 8

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://rich.readthedocs.io/en/latest/
10/10	Repository description
10/10	Topics — 16 topics
10/10	Wiki

Inputs used

topics	python, python3, python-library, terminal, terminal-color, markdown, tables, syntax-highlighting, ansi-colors, progress-bar-python, progress-bar, traceback, rich, tracebacks-rich, emoji, tui
has_wiki	yes
homepage	https://rich.readthedocs.io/en/latest/
docs_site	https://rich.readthedocs.io/en/latest/
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?

69Good · 16% of overall

Security posture

61Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2/2.5	CI-Tests — 6 out of 7 merged PRs checked by a CI test -- score normalized to 8
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0.8/7.5	Code-Review — Found 1/10 approved changesets -- score normalized to 1
2.5/2.5	Contributors — project has 51 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
5/5	Fuzzing — project is fuzzed
2.5/2.5	License — license file detected
3/7.5	Maintained — 2 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 4
0/5	Packaging — no data
1/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
4.5/5	SAST — SAST tool detected but not run on all commits
5/5	Security-Policy — security policy file detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0.8/7.5	Vulnerabilities — 9 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	6.1

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

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	3
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:rich@15.0.0 runtime dependency closure — what installing the published package pulls in — 3 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

Agent context & guidance

14Critical

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
14.1/40	Legible commit history — 26 of 98 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.265
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

85Excellent

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 — rich/py.typed
10/10	Reproducible environment — lockfile
6/10	Demonstrated agent practice — 3 of the last 100 commits agent-authored or agent-credited
5/8	Automated maintenance — dependency automation configured, none observed in the sampled commits
2/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2

Inputs used

has_nix	no
has_tests	yes
lockfiles	poetry.lock
has_dockerfile	no
typed_language	no
bootstrap_files	Makefile, docs/Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	rich/py.typed
agent_commit_share	0.03
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

81Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (rich/py.typed)
54.2/55	Manageable file sizes — 3/213 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	140,235
source_files_sampled	213
oversized_source_files	3

Machine-readable interfaces

100Exceptional

How it's scored

0/40	API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20	MCP server — not applicable to this kind of software
40/40	Runnable examples — examples

Inputs used

example_dirs	examples
has_mcp_signal	no
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

57,002GitHub stars

99contributors

177commits, last 12 months

42days since last push

100releases

1bus factor

232open 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 ★ / 2,280 ⇿

0Stars

2,280Forks

34Releases

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.

Major 2Minor 12Patch 20

Each point covers 4 days.

OpenSSF Scorecard 6.1 / 10

6.1aggregate

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 · 2026-08-04 18:11 UTC

10	Binary-Artifacts	no binaries found in the repo
n/a	Branch-Protection	internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
8	CI-Tests	6 out of 7 merged PRs checked by a CI test -- score normalized to 8
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
1	Code-Review	Found 1/10 approved changesets -- score normalized to 1
10	Contributors	project has 51 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
10	Fuzzing	project is fuzzed
10	License	license file detected
4	Maintained	2 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 4
n/a	Packaging	packaging workflow not detected
2	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 2
9	SAST	SAST tool detected but not run on all commits
10	Security-Policy	security policy file detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
1	Vulnerabilities	9 existing vulnerabilities detected

Direct dependencies 3

Registry	Package	Version constraint	Manifest
PyPI	pygments	`^2.13.0`	pyproject.toml
PyPI	ipywidgets	`>=7.5.1,<9`	pyproject.toml
PyPI	markdown-it-py	`>=2.2.0`	pyproject.toml

All dependencies 53

Full resolved dependency set from the GitHub dependency graph: 3 direct and 50 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	ipywidgets	`8.1.7`	direct
PyPI	markdown-it-py	`3.0.0`	direct
PyPI	pygments	`2.19.2`	direct
PyPI	alabaster	`1.0.0`	indirect
PyPI	appnope	`0.1.4`	indirect
PyPI	asttokens	`3.0.0`	indirect
PyPI	attrs	`21.4.0`	indirect
PyPI	backcall	`0.2.0`	indirect
PyPI	black	`22.12.0`	indirect
PyPI	cfgv	`3.4.0`	indirect
PyPI	click	`8.1.8`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	comm	`0.2.3`	indirect
PyPI	coverage	`7.6.1`	indirect
PyPI	decorator	`5.2.1`	indirect
PyPI	distlib	`0.4.0`	indirect
PyPI	exceptiongroup	`1.3.0`	indirect
PyPI	executing	`2.2.1`	indirect
PyPI	filelock	`3.16.1`	indirect
PyPI	identify	`2.6.1`	indirect
PyPI	iniconfig	`2.1.0`	indirect
PyPI	ipython	`8.12.3`	indirect
PyPI	jedi	`0.19.2`	indirect
PyPI	jupyterlab-widgets	`3.0.15`	indirect
PyPI	matplotlib-inline	`0.1.7`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	mypy	`1.14.1`	indirect
PyPI	mypy-extensions	`1.1.0`	indirect
PyPI	nodeenv	`1.9.1`	indirect
PyPI	packaging	`25.0`	indirect
PyPI	parso	`0.8.5`	indirect
PyPI	pathspec	`0.12.1`	indirect
PyPI	pexpect	`4.9.0`	indirect
PyPI	pickleshare	`0.7.5`	indirect
PyPI	platformdirs	`4.3.6`	indirect
PyPI	pluggy	`1.5.0`	indirect
PyPI	pre-commit	`2.21.0`	indirect
PyPI	prompt-toolkit	`3.0.52`	indirect
PyPI	ptyprocess	`0.7.0`	indirect
PyPI	pure-eval	`0.2.3`	indirect
PyPI	pytest	`7.4.4`	indirect
PyPI	pytest-cov	`3.0.0`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	sphinx	`8.2.3`	indirect
PyPI	sphinx-copybutton	`0.5.2`	indirect
PyPI	sphinx-rtd-theme	`3.0.2`	indirect
PyPI	stack-data	`0.6.3`	indirect
PyPI	tomli	`2.3.0`	indirect
PyPI	traitlets	`5.14.3`	indirect
PyPI	typing-extensions	`4.13.2`	indirect
PyPI	virtualenv	`20.34.0`	indirect
PyPI	wcwidth	`0.2.14`	indirect
PyPI	widgetsnbextension	`4.0.14`	indirect

Dependency advisories 0

Installing pypi:rich@15.0.0 pulls in 3 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.

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 v0.30.0 — 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

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