Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 22:28 UTC

mosaicml / streaming

A Data Streaming Library for Efficient Neural Network Training

PythonApache-2.0★ 1,555 stars⑂ 205 forkssince Jun 2022View on GitHub ↗
KindCommand-line toolhow this is determined

mosaicml/streaming holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Community & Adoption (85/100) and lowest on Vitality (41/100). It was last updated 84 days ago. 2 contributors account for most of its recent work.

78
overall / 100
Good

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.

78
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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

1,103 followers7 public repossince Nov 2020

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

Metrics by category

Vitality

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

41Weak · 21% of overall
How it's scored
18/36Push recency — last push 84 days ago
1.4/36Commit cadence — 2/52 weeks with commits
8.1/18Commit volume — 7 commits in the last year
0/10OpenSSF Scorecard: Maintained — 1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year7
human_commit_share0.42
days_since_last_push84
active_weeks_last_year2
How it's scored
27/27Ships releases — 31 releases published
7.2/36Release recency — latest release 429 days ago
19.8/27Release cadence — a release every ~51.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count31
latest_release_tagv0.13.0
releases_from_tagsno
days_since_latest_release429
mean_days_between_releases51.4
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?

85Excellent · 17% of overall
How it's scored
51.8/60Stars — 1,555 stars
19.2/25Forks — 205 forks
7.6/15Watchers — 24 watchers
Inputs used
forks205
stars1,555
watchers24
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges7
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, readthedocs.org, shields.io
has_pull_request_templateyes

Sustainability & Governance

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

70Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
15.3/22.5Commit distribution — top contributor authored 32% of commits
13.5/13.5Contributor breadth — 59 contributors
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled59
top_contributor_share0.32
How it's scored
27.4/42Issue resolution — 65% of issues closed
25.2/30PR acceptance — 611/726 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs611
open_issues77
closed_issues144
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.652
closed_unmerged_prs115
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
21.9/25Owner reach — 1,103 followers of mosaicml
18.2/25Track record — 7 public repos, account ~5 yr old
Inputs used
followers1,103
owner_typeOrganization
is_verifiedno
owner_loginmosaicml
public_repos7
account_age_days2,120

Engineering Quality

Are baseline engineering and documentation practices in place?

82Excellent · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.isort], [tool.yapf])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
2/20OpenSSF Scorecard: CI-Tests — 5 out of 30 merged PRs checked by a CI test -- score normalized to 1
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://streaming.docs.mosaicml.com
10/10Repository description
10/10Topics — 6 topics
0/10Wiki
Inputs used
topicsdataset, deep-learning, machine-learning, neural-network, pytorch, streaming
has_wikino
homepagehttps://streaming.docs.mosaicml.com
docs_sitehttps://streaming.docs.mosaicml.com
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

59Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0.2/2.5CI-Tests — 5 out of 30 merged PRs checked by a CI test -- score normalized to 1
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 6 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
0/7.5Maintained — 1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — no data
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
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.9
Excluded from scoring (no data or not applicable): Packaging, 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
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories58
affected_packages2
assessed_packages27
unassessed_packages37
affected_by_severitycritical 1, moderate 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 27 resolved dependencies against OSV. 37 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

72Good · 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://docs.databricks.com/llms.txt)
40/40Legible commit history — 40 of 42 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.databricks.com/llms.txt
legible_history_share0.952
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.isort], [tool.yapf])
11/11Static type checking — streaming/py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 58 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, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsstreaming/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.58
How it's scored
27/45Type-checkable code — Python with type-check config (streaming/py.typed)
54.7/55Manageable file sizes — 1/185 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes69,244
source_files_sampled185
oversized_source_files1
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, samples
Inputs used
example_dirsexamples, notebooks, samples
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

1,555GitHub stars
59contributors
7commits, last 12 months
84days since last push
31releases
2bus factor
77open 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 ★ / 205 ⇿
0Stars
205Forks
31Releases

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.

04080120160200199132022-092024-092026-08
Major 0Minor 12Patch 19

Each point covers 4 days.

OpenSSF Scorecard 4.9 / 10
4.9aggregate

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 · 2026-09-17 22:27 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
1CI-Tests5 out of 30 merged PRs checked by a CI test -- score normalized to 1
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 6 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not 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
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 64

Full resolved dependency set from the GitHub dependency graph: 0 direct and 64 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIalipcs-py—indirect
PyPIaltair—indirect
PyPIazure-identity—indirect
PyPIazure-storage-blob—indirect
PyPIazure-storage-file-datalake—indirect
PyPIboto3—indirect
PyPIbrotli—indirect
PyPIcatalogue—indirect
PyPIdatabricks-sdk0.79.0indirect
PyPIdatasets—indirect
PyPIdocformatter—indirect
PyPIdocutils0.17.1indirect
PyPIfastapi0.116.1indirect
PyPIfuro2022.9.29indirect
PyPIgitpython3.1.42indirect
PyPIgoogle-cloud-storage—indirect
PyPIhuggingface-hub—indirect
PyPIhumanize—indirect
PyPIjupyter1.1.1indirect
PyPImatplotlib—indirect
PyPImosaicml-cli—indirect
PyPImoto—indirect
PyPImyst-parser0.16.1indirect
PyPInbsphinx0.9.1indirect
PyPInumpy—indirect
PyPIoci—indirect
PyPIomegaconf—indirect
PyPIpandas—indirect
PyPIpandoc2.3indirect
PyPIparamiko—indirect
PyPIpre-commit—indirect
PyPIpyarrow—indirect
PyPIpydantic2.11.7indirect
PyPIpypandoc1.13indirect
PyPIpyspark—indirect
PyPIpytest8.4.1indirect
PyPIpytest-codeblocks0.17.0indirect
PyPIpytest-cov—indirect
PyPIpytest-split0.10.0indirect
PyPIpython-snappy—indirect
PyPIpyyaml—indirect
PyPIsetuptools—indirect
PyPIsortedcollections—indirect
PyPIsphinx4.4.0indirect
PyPIsphinx-argparse0.4.0indirect
PyPIsphinx-copybutton0.5.2indirect
PyPIsphinx-tabs3.4.5indirect
PyPIsphinxcontrib-applehelp1.0.0indirect
PyPIsphinxcontrib-devhelp1.0.0indirect
PyPIsphinxcontrib-htmlhelp2.0.0indirect
PyPIsphinxcontrib-katex0.9.6indirect
PyPIsphinxcontrib-qthelp1.0.0indirect
PyPIsphinxcontrib-serializinghtml1.1.5indirect
PyPIstreamlit—indirect
PyPItoml0.10.2indirect
PyPItorch—indirect
PyPItorchvision—indirect
PyPItqdm—indirect
PyPItransformers—indirect
PyPIuvicorn0.35.0indirect
PyPIwandb—indirect
PyPIxxhash—indirect
PyPIyamllint1.37.1indirect
PyPIzstd—indirect
Dependency advisories 2

This repository publishes no package the index resolves, so its own dependency graph was assessed — 27 packages, which also include development and test pins that never ship: 2 carry known advisories, of which 0 are direct. 37 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
gitpython3.1.42indirectcritical563.1.60
pytest8.4.1indirectmoderate29.0.3

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.