Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 08:05 UTC

Arize-ai / client_python

A Python client to interact with Arize API

PythonApache-2.0★ 56 stars⑂ 22 forkssince Mar 2020View on GitHub ↗

Arize-ai/client_python holds a health index of 84 out of 100, placing it in the Excellent band. It scores highest on Vitality (91/100) and lowest on Security (55/100). It was last updated 3 days ago. 3 contributors account for most of its recent work.

84
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.

84
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 71 is calibrated to 84 on the published index scale (record calibration 2026-08-02).

Ownership

Arize AIOrganization
563 followers73 public repossince Jan 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIarize8.52.1652,7013623 days agoarizeevaluationsexplainabilityllmmonitoringobservabilitytracing

Metrics by category

Vitality

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

91Excellent · 21% of overall
How it's scored
36/36Push recency — last push 3 days ago
22.2/36Commit cadence — 32/52 weeks with commits
16.9/18Commit volume — 76 commits in the last year
10/10OpenSSF Scorecard: Maintained — 19 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year76
human_commit_share1
days_since_last_push3
active_weeks_last_year32

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 9 releases published
36/36Release recency — latest release 3 days ago
27/27Release cadence — a release every ~4.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count9
latest_release_tagv8.52.1
releases_from_tagsno
days_since_latest_release3
mean_days_between_releases4.2
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?

60Moderate · 17% of overall
How it's scored
28.2/60Stars — 56 stars
11/25Forks — 22 forks
6.4/15Watchers — 15 watchers
Inputs used
forks22
stars56
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
77.5/80Monthly downloads — 652,701 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesarize
dependents—
ecosystemspypi
total_downloads—
monthly_downloads652,701
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?

77Good · 23% of overall
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
14.7/22.5Commit distribution — top contributor authored 35% of commits
13.5/13.5Contributor breadth — 13 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor3
contributors_sampled13
top_contributor_share0.348
How it's scored
38.2/42Issue resolution — 91% of issues closed
23.6/30PR acceptance — 85/108 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs85
open_issues2
closed_issues20
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.909
closed_unmerged_prs23
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
19.8/25Owner reach — 563 followers of Arize-ai
25/25Track record — 73 public repos, account ~6 yr old
Inputs used
followers563
owner_typeOrganization
is_verifiedno
owner_loginArize-ai
public_repos73
account_age_days2,435

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 3 days ago
20/20Version history — 362 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesarize
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.black])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://docs.arize.com/arize
10/10Repository description
10/10Topics — 11 topics
10/10Wiki
Inputs used
topicsml-monitoring, model-monitoring, ai-monitoring, performance-monitoring, drift-monitoring, data-quality-monitoring, ml-observability, ai-observability, model-performance-management, model-explainability, ai-roi
has_wikiyes
homepage—
docs_sitehttps://docs.arize.com/arize
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

55Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
0/10Dangerous-Workflow — no data
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 19 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — no data
0/5SAST — no SAST tool detected
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — no data
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate4.4
Excluded from scoring (no data or not applicable): CI-Tests, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. 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_packages30
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:arize@8.52.1 runtime dependency closure — what installing the published package pulls in — 30 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.

59Moderate · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://arize.com/llms.txt)
0/40Legible commit history — 0 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://arize.com/llms.txt
legible_history_share0
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.black])
11/11Static type checking — src/arize/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/arize/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
27/45Type-checkable code — Python with type-check config (src/arize/py.typed)
53.9/55Manageable file sizes — 24/1,182 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes239,116
source_files_sampled1,182
oversized_source_files24
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, notebooks
Inputs used
example_dirsexamples, notebooks
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

56GitHub stars
13contributors
76commits, last 12 months
3days since last push
9releases
3bus factor
2open 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 ★ / 22 ⇿
0Stars
22Forks
6Releases

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.

048121620242232021-082024-022026-09
Major 0Minor 6Patch 0

Each point covers 5 days.

OpenSSF Scorecard 4.4 / 10
4.4aggregate

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 · 2026-09-14 08:05 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained19 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 17
RegistryPackageVersion constraintManifest
PyPInumpy>=2.0.0pyproject.toml
PyPIopeninference-semantic-conventions>=0.1.25, <1pyproject.toml
PyPIopentelemetry-exporter-otlp-proto-common>=1.38.0pyproject.toml
PyPIopentelemetry-exporter-otlp-proto-grpc>=1.38.0pyproject.toml
PyPIopentelemetry-sdk>=1.38.0pyproject.toml
PyPIopentelemetry-semantic-conventions>=0.43b0, <1pyproject.toml
PyPIpandas>=2.0.0, <3pyproject.toml
PyPIprotobuf>=4.21.0, <7pyproject.toml
PyPIpyarrow>=0.15.0pyproject.toml
PyPIpydantic>=2, <3pyproject.toml
PyPIpython-dateutil>=2.8.2, <3pyproject.toml
PyPIrequests>=2.0.0, <3pyproject.toml
PyPIrequests_futures>=1.0.0, <2pyproject.toml
PyPItqdm>4, <5pyproject.toml
PyPItyping-extensions>=4.7.1, <5pyproject.toml
PyPIurllib3>=2.1.0, <3pyproject.toml
PyPIwrapt>=1.0.0, <2.0.0pyproject.toml
All dependencies 41

Full resolved dependency set from the GitHub dependency graph: 17 direct and 24 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpy—direct
PyPIopeninference-semantic-conventions—direct
PyPIopentelemetry-exporter-otlp-proto-common—direct
PyPIopentelemetry-exporter-otlp-proto-grpc—direct
PyPIopentelemetry-sdk—direct
PyPIopentelemetry-semantic-conventions—direct
PyPIpandas—direct
PyPIprotobuf—direct
PyPIpyarrow—direct
PyPIpydantic—direct
PyPIpython-dateutil—direct
PyPIrequests—direct
PyPIrequests-futures—direct
PyPItqdm—direct
PyPItyping-extensions—direct
PyPIurllib3—direct
PyPIwrapt—direct
PyPIarize-otel—indirect
PyPIdatasets—indirect
PyPIhatchling—indirect
PyPIinterpret-community—indirect
PyPImypy1.19.1indirect
PyPImyst-parser—indirect
PyPIpandas-stubs—indirect
PyPIpillow—indirect
PyPIpydata-sphinx-theme—indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov6.0.0indirect
PyPIruff0.14.9indirect
PyPIsphinx—indirect
PyPIsphinx-autobuild—indirect
PyPIsphinx-copybutton—indirect
PyPIsphinx-design—indirect
PyPItaskipy—indirect
PyPItokenizers—indirect
PyPItorch—indirect
PyPItransformers—indirect
PyPItypes-python-dateutil—indirect
PyPItypes-requests—indirect
PyPItypes-tabulate—indirect
PyPItypes-tqdm—indirect
Dependency advisories 0

Installing pypi:arize@8.52.1 pulls in 30 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.