Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-11 09:45 UTC

mbk-dev / okama

Investment portfolio and stocks analyzing tools for Python with free historical data

PythonMIT★ 273 stars⑂ 43 forkssince Mar 2020View on GitHub ↗
KindLibraryhow this is determined
#finance#investments#mathematics#python#optimization#portfolio-optimization#quantitative-finance#historical-data#portfolio#financial-data#cfa#time-series#markowitz#modern-portfolio-theory

mbk-dev/okama holds a health index of 16 out of 100, placing it in the Critical band. It scores highest on Engineering Quality (95/100) and lowest on Security (28/100). It was last updated 10 days ago. A single contributor accounts for most of its recent work.

16
overall / 100
Critical

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.

16
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 68 is calibrated to 80 on the published index scale (record calibration 2026-08-02). High-Risk Jurisdiction Policy applies a 20% multiplier to weighted overall health and gives it an At Risk ceiling of 34.

Ownership

MBK DevelopmentOrganization
29 followers13 public repossince Sep 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIokama3.0.09935310 days agofinanceinvestmentsefficient-frontierpythonoptimization

Metrics by category

Vitality

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

89Excellent · 21% of overall

Development activity

82Excellent
How it's scored
28.8/36Push recency — last push 10 days ago
24.9/36Commit cadence — 36/52 weeks with commits
18/18Commit volume — 339 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year339
human_commit_share1
days_since_last_push10
active_weeks_last_year36

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 54 releases published
36/36Release recency — latest release 10 days ago
27/27Release cadence — a release every ~10.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count54
latest_release_tagv3.0.0
releases_from_tagsno
days_since_latest_release10
mean_days_between_releases10.6
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?

65Good · 17% of overall

Popularity & adoption

58Moderate
How it's scored
39.5/60Stars — 273 stars
13.5/25Forks — 43 forks
5/15Watchers — 9 watchers
Inputs used
forks43
stars273
watchers9
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescoveralls.io, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

50Moderate
How it's scored
40/80Monthly downloads — 993 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesokama
dependents—
ecosystemspypi
total_downloads—
monthly_downloads993
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?

56Moderate · 23% of overall

Maintainer resilience (bus factor)

21At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1/22.5Commit distribution — top contributor authored 96% of commits
8.1/13.5Contributor breadth — 6 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.955

Issue & PR responsiveness

58Moderate
How it's scored
36.1/42Issue resolution — 86% of issues closed
14.1/30PR acceptance — 15/32 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_prs15
open_issues11
closed_issues67
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.859
closed_unmerged_prs17
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.

Ownership & stewardship

61Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
10.6/25Owner reach — 29 followers of mbk-dev
20.3/25Track record — 13 public repos, account ~5 yr old
Inputs used
followers29
owner_typeOrganization
is_verifiedno
owner_loginmbk-dev
public_repos13
account_age_days2,175

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 10 days ago
20/20Version history — 53 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesokama
ecosystemspypi
any_deprecatedno
min_days_since_publish10

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-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_configyes
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://okama.io/
10/10Repository description
10/10Topics — 14 topics
10/10Wiki
Inputs used
topicsfinance, investments, mathematics, python, optimization, portfolio-optimization, quantitative-finance, historical-data, portfolio, financial-data, cfa, time-series, markowitz, modern-portfolio-theory
has_wikiyes
homepagehttps://okama.io/
docs_sitehttps://okama.io/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

28At Risk · 16% of overall

Security posture

10Critical
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
0/2.5CI-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
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 30 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_aggregate4.9
high_risk_jurisdiction_cap34
high_risk_jurisdiction_multiplier20
security_posture_after_multiplier10
security_posture_before_jurisdiction49
Excluded from scoring (no data or not applicable): CI-Tests, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized. High-Risk Jurisdiction Policy applies a 20% multiplier and gives Security posture an At risk ceiling of 34.

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:okama@3.0.0 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.

76Good · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 93 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.93
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes10,303

Verify loop (build / test / typecheck)

68Good
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
0/10Reproducible environment
10/10Demonstrated agent practice — 70 of the last 100 commits agent-authored or agent-credited
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_configs—
agent_commit_share0.7
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.

Code legibility for models

53Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
52.7/55Manageable file sizes — 3/72 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes72,118
source_files_sampled72
oversized_source_files3

Machine-readable interfaces

100Exceptional
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

273GitHub stars
6contributors
339commits, last 12 months
10days since last push
54releases
1bus factor
11open 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 ★ / 43 ⇿
0Stars
43Forks
35Releases

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.

010203040504332020-122023-092026-06
Major 2Minor 7Patch 17

Each point covers 5 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 · 2026-09-11 09:45 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/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
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 30 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 10
RegistryPackageVersion constraintManifest
PyPIpandas>=2.0.0pyproject.toml
PyPIpyarrow>=13.0.0pyproject.toml
PyPIscipy*pyproject.toml
PyPImatplotlib>=3.5.1pyproject.toml
PyPIrequests*pyproject.toml
PyPIjoblib*pyproject.toml
PyPIpandas-stubs*pyproject.toml
PyPIarch>=7.2.0pyproject.toml
PyPIstatsmodels>=0.14.5pyproject.toml
PyPIidna>=3.15pyproject.toml
All dependencies 190

Full resolved dependency set from the GitHub dependency graph: 20 direct and 170 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIarch8.0.0direct
PyPIidna—direct
PyPIidna3.19direct
PyPIjoblib—direct
PyPIjoblib1.6.0direct
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PyPImatplotlib3.11.1direct
PyPIpandas—direct
PyPIpandas3.0.5direct
PyPIpandas-stubs—direct
PyPIpandas-stubs3.0.5.260730direct
PyPIpyarrow—direct
PyPIpyarrow25.0.1direct
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PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
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PyPIurllib32.7.0indirect
PyPIvirtualenv21.7.7indirect
PyPIwcwidth0.8.3indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.6.1indirect
PyPIwebsocket-client1.9.1indirect
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PyPIwrapt2.4.0indirect
PyPIzmq0.0.0indirect
Dependency advisories 0

Installing pypi:okama@3.0.0 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

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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.