Public record
Software health reportschema 0.27.0 · metrics 2.5.0 · 2026-08-02 15:12 UTC

fireblocks / py-sdk

PythonMIT★ 9 stars⑂ 7 forkssince Jun 2023View on GitHub ↗

fireblocks/py-sdk holds a health index of 63 out of 100, placing it in the Moderate band. It scores highest on Vitality (84/100) and lowest on Security (10/100). It was last updated today. 2 contributors account for most of its recent work.

63
overall / 100
Moderate

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.

63
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 59 is calibrated to 63 on the published index scale (record calibration 2026-08-02).

Ownership

FireblocksOrganization
224 followers71 public repossince Jul 2018

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIfireblocks25.0.0307,531460 days agofireblockssdkfireblocks-api

Metrics by category

Vitality

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

84Excellent · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
13.8/36Commit cadence — 20/52 weeks with commits
16/18Commit volume — 59 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year59
human_commit_share0.89
days_since_last_push0
active_weeks_last_year20

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 44 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~11.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count44
latest_release_tagv25.0.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases11.6

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

49Weak · 17% of overall
How it's scored
14.6/60Stars — 9 stars
6.5/25Forks — 7 forks
0/15Watchers — 2 watchers
Inputs used
forks7
stars9
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
73.2/80Monthly downloads — 307,531 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesfireblocks
dependents
ecosystemspypi
total_downloads
monthly_downloads307,531
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?

66Good · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
11.8/22.5Commit distribution — top contributor authored 48% of commits
9.5/13.5Contributor breadth — 7 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor2
contributors_sampled7
top_contributor_share0.477
How it's scored
21/42Issue resolution — 50% of issues closed
14.5/30PR acceptance — 70/145 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs70
open_issues3
closed_issues3
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.5
closed_unmerged_prs75
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
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
16.9/25Owner reach — 224 followers of fireblocks
25/25Track record — 71 public repos, account ~8 yr old
Inputs used
followers224
owner_typeOrganization
is_verified
owner_loginfireblocks
public_repos71
account_age_days2,948

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 46 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesfireblocks
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

74Good · 19% of overall
How it's scored
24/24CI workflows — 7 workflow(s)
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

10Critical · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestspyproject.toml, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.
How it's scored
10.2/35Direct dependencies free of known advisories — 3 affected: cryptography 43.0.3 (high 7.5), pyjwt 2.9.0 (high 7.5), urllib3 2.2.3 (high 7.5)
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
25.6/40No advisories left outstanding — 3 advisory-carrying package(s) unaddressed past 90 days; oldest published 536 days ago
Inputs used
sourceosv
advisories38
affected_packages5
assessed_packages44
unassessed_packages14
affected_by_severityhigh 3, moderate 2
direct_affected_packages3
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 44 resolved dependencies against OSV. 14 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.

49Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
33/40Legible commit history — 55 of 89 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
legible_history_share0.618
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — tox.ini
11/11Static type checking — fireblocks/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_files
has_devcontainerno
has_linter_configyes
typecheck_configsfireblocks/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
27/45Type-checkable code — Python with type-check config (fireblocks/py.typed)
54.7/55Manageable file sizes — 15/2,506 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes241,029
source_files_sampled2,506
oversized_source_files15

Key facts

9GitHub stars
7contributors
59commits, last 12 months
0days since last push
44releases
2bus factor
3open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:fireblocks@25.0.0; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

More detail

Star and fork history 0 ★ / 7 ⇿
0Stars
7Forks
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.

1234567712024-062025-052026-04
Major 15Minor 10Patch 6

Each point covers 2 days.

Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPIurllib3>= 2.1.0, < 3.0.0pyproject.toml
PyPIpython-dateutil>= 2.8.2pyproject.toml
PyPIpydantic>= 2pyproject.toml
PyPItyping-extensions>= 4.7.1pyproject.toml
PyPIPyJWT>= 2.3.0pyproject.toml
PyPIcryptography>= 2.7pyproject.toml
All dependencies 58

Full resolved dependency set from the GitHub dependency graph: 12 direct and 46 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcryptographydirect
PyPIcryptography43.0.3direct
PyPIpydanticdirect
PyPIpydantic2.10.6direct
PyPIpyjwtdirect
PyPIpyjwt2.9.0direct
PyPIpython-dateutildirect
PyPIpython-dateutil2.9.0.post0direct
PyPItyping-extensionsdirect
PyPItyping-extensions4.13.2direct
PyPIurllib3direct
PyPIurllib32.2.3direct
PyPIannotated-types0.7.0indirect
PyPIast-serialize0.6.0indirect
PyPIcachetools5.5.2indirect
PyPIcffi1.17.1indirect
PyPIchardet5.2.0indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.6.1indirect
PyPIdistlib0.4.3indirect
PyPIexceptiongroup1.3.1indirect
PyPIfilelock3.16.1indirect
PyPIflake8indirect
PyPIflake85.0.4indirect
PyPIiniconfig2.1.0indirect
PyPIlibrt0.13.0indirect
PyPIlibrt0.7.4indirect
PyPImccabe0.7.0indirect
PyPImypyindirect
PyPImypy1.14.1indirect
PyPImypy-extensions1.1.0indirect
PyPIpackaging26.2indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.3.6indirect
PyPIpluggy1.5.0indirect
PyPIpycodestyle2.9.1indirect
PyPIpycparser2.23indirect
PyPIpydantic-core2.27.2indirect
PyPIpyflakes2.5.0indirect
PyPIpygments2.20.0indirect
PyPIpyproject-api1.8.0indirect
PyPIpytestindirect
PyPIpytest8.3.5indirect
PyPIpytest-covindirect
PyPIpytest-cov5.0.0indirect
PyPIpytest-mockindirect
PyPIpytest-mock3.14.1indirect
PyPIpython-discovery1.5.1indirect
PyPIsetuptoolsindirect
PyPIsix1.17.0indirect
PyPItomli2.4.1indirect
PyPItomli-w1.2.0indirect
PyPItoxindirect
PyPItox4.25.0indirect
PyPItypes-python-dateutilindirect
PyPItypes-python-dateutil2.9.0.20241206indirect
PyPItyping-inspection0.4.2indirect
PyPIvirtualenv21.4.3indirect
Dependency advisories 5

This repository publishes no package the index resolves, so its own dependency graph was assessed — 44 packages, which also include development and test pins that never ship: 5 carry known advisories, of which 3 are direct. 14 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
cryptography43.0.3directhigh748.0.1
pyjwt2.9.0directhigh132.13.0
urllib32.2.3directhigh122.7.0
filelock3.16.1indirectmoderate43.20.3
pytest8.3.5indirectmoderate29.0.3

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

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 v2.5.0, schema v0.27.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.