Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-21 19:43 UTC

ArturSepp / OptimalPortfolios

Production multi-asset portfolio construction and rolling backtesting in Python

PythonMIT★ 98 stars⑂ 43 forkssince Jul 2023View on GitHub ↗

#backtesting #backtesting-trading-strategies #cvxpy #optimal-portfolio #portfolio-optimization #asset-allocation #covariance-estimation #factor-models #python #quantitative-finance

ArturSepp/OptimalPortfolios holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Vitality (93/100) and lowest on Community & Adoption (61/100). It was last updated today. 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 75 is calibrated to 89 on the published index scale (record calibration 2026-08-02).

Ownership

Artur SeppPersonal account

314 followers13 public repossince May 2018LGT Private Banking

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish	Tags
PyPI	optimalportfolios	7.22.1	1,910	123	4 days ago	portfolio-optimization quantitative-finance asset-allocation risk-budgeting backtesting covariance-estimation lasso-regularization cvxpy

Metrics by category

Vitality

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

93Exceptional · 21% of overall

Development activity

88Excellent

How it's scored

36/36	Push recency — last push 0 days ago
23.5/36	Commit cadence — 34/52 weeks with commits
18/18	Commit volume — 371 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	371
human_commit_share	1
days_since_last_push	0
active_weeks_last_year	34

Release discipline

100Exceptional

How it's scored

27/27	Ships releases — 30 releases published
36/36	Release recency — latest release 20 days ago
27/27	Release cadence — a release every ~4.2 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	30
latest_release_tag	v7.10.2
releases_from_tags	no
days_since_latest_release	20
mean_days_between_releases	4.2

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?

61Moderate · 17% of overall

Popularity & adoption

50Moderate

How it's scored

32.2/60	Stars — 98 stars
13.5/25	Forks — 43 forks
3.9/15	Watchers — 6 watchers

Inputs used

forks	43
stars	98
watchers	6
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

77Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (MIT)
18/18	CONTRIBUTING guide
0/13.5	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	no
readme_badge_services	github.com, readthedocs.org, shields.io
has_pull_request_template	yes

Ecosystem adoption (downloads)

55Moderate

How it's scored

43.8/80	Monthly downloads — 1,910 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	optimalportfolios
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	1,910
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?

62Moderate · 23% of overall

Maintainer resilience (bus factor)

26At Risk

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
1.8/22.5	Commit distribution — top contributor authored 92% of commits
5.4/13.5	Contributor breadth — 4 contributors
10/10	OpenSSF Scorecard: Contributors — project has 4 contributing companies or organizations

Inputs used

bus_factor	1
contributors_sampled	4
top_contributor_share	0.921

Issue & PR responsiveness

78Good

How it's scored

42/42	Issue resolution — 100% of issues closed
26/30	PR acceptance — 71/82 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 0/22 approved changesets -- score normalized to 0

Inputs used

merged_prs	71
open_issues	0
closed_issues	36
prs_merged_7d	3
prs_decided_7d	3
prs_merged_30d	33
prs_decided_30d	35
issue_closed_ratio	1
closed_unmerged_prs	11
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

60Moderate

How it's scored

10/30	Ownership backing — personal (user) account
0/20	Verified domain — not applicable to user accounts
18/25	Owner reach — 314 followers of ArturSepp
20.3/25	Track record — 13 public repos, account ~8 yr old

Inputs used

followers	314
owner_type	User
is_verified	—
owner_login	ArturSepp
public_repos	13
account_age_days	3,064

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 4 days ago
20/20	Version history — 123 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	optimalportfolios
ecosystems	pypi
any_deprecated	no
min_days_since_publish	4

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall

Engineering practices

84Excellent

How it's scored

24/24	CI workflows — 10 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 7 out of 7 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	no

Documentation

100Exceptional

How it's scored

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

Inputs used

topics	backtesting, backtesting-trading-strategies, cvxpy, optimal-portfolio, portfolio-optimization, asset-allocation, covariance-estimation, factor-models, python, quantitative-finance
has_wiki	yes
homepage	https://optimalportfolios.readthedocs.io
docs_site	https://optimalportfolios.readthedocs.io
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
2.2/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5	CI-Tests — 7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 0/22 approved changesets -- score normalized to 0
2.5/2.5	Contributors — project has 4 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
5/5	Packaging — packaging workflow detected
5/5	Pinned-Dependencies — all dependencies are pinned
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
7.5/7.5	Token-Permissions — GitHub workflow tokens follow principle of least privilege
6.8/7.5	Vulnerabilities — 1 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	17
scorecard_version	v5.5.0
checks_inconclusive	1
scorecard_aggregate	6.1

Excluded from scoring (no data or not applicable): 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	43
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:optimalportfolios@7.22.1 runtime dependency closure — what installing the published package pulls in — 43 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.

77Good · 4% of overall

Agent context & guidance

96Exceptional

How it's scored

45/45	Agent instructions — AGENTS.md, CLAUDE.md, papers/AGENTS.md
15/15	Machine-readable docs (llms.txt) — llms.txt served by the project website (https://optimalportfolios.readthedocs.io/llms.txt)
35.7/40	Legible commit history — 67 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	yes
llms_txt_url	https://optimalportfolios.readthedocs.io/llms.txt
legible_history_share	0.67
agent_instruction_files	AGENTS.md, CLAUDE.md, papers/AGENTS.md
agent_instruction_max_bytes	43,485

Verify loop (build / test / typecheck)

63Moderate

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
0/11	Static type checking
10/10	Reproducible environment — lockfile
10/10	Demonstrated agent practice — 41 of the last 100 commits agent-authored or agent-credited
0/8	Automated maintenance — no automated dependency updates observed
10/10	OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned

Inputs used

has_nix	no
has_tests	yes
lockfiles	uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0.41
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

55Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
54.7/55	Manageable file sizes — 2/369 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	83,761
source_files_sampled	369
oversized_source_files	2

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, notebooks

Inputs used

example_dirs	examples, notebooks
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

98GitHub stars

4contributors

371commits, last 12 months

0days since last push

30releases

1bus factor

0open 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

30Releases

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.

Major 1Minor 20Patch 9

Each point covers 3 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 · 2026-10-21 19:43 UTC

10	Binary-Artifacts	no binaries found in the repo
3	Branch-Protection	branch protection is not maximal on development and all release branches
10	CI-Tests	7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 0/22 approved changesets -- score normalized to 0
10	Contributors	project has 4 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
10	Packaging	packaging workflow detected
10	Pinned-Dependencies	all dependencies are pinned
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
10	Token-Permissions	GitHub workflow tokens follow principle of least privilege
9	Vulnerabilities	1 existing vulnerabilities detected

Direct dependencies 11

Registry	Package	Version constraint	Manifest
PyPI	numpy	`>=2.0`	pyproject.toml
PyPI	scipy	`>=1.12.0`	pyproject.toml
PyPI	pandas	`>=2.2.0`	pyproject.toml
PyPI	matplotlib	`>=3.8.0`	pyproject.toml
PyPI	Pillow	`>=13.0.0`	pyproject.toml
PyPI	seaborn	`>=0.13.0`	pyproject.toml
PyPI	openpyxl	`>=3.1.0`	pyproject.toml
PyPI	PyYAML	`>=6.0`	pyproject.toml
PyPI	cvxpy	`>=1.5.2`	pyproject.toml
PyPI	scs	`>=3.2.4.post3,!=3.3.0`	pyproject.toml
PyPI	qis	`>=5.38.1`	pyproject.toml

All dependencies 117

Full resolved dependency set from the GitHub dependency graph: 13 direct and 104 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	cvxpy	`1.9.2`	direct
PyPI	matplotlib	`3.11.1`	direct
PyPI	numpy	`2.4.6`	direct
PyPI	numpy	`2.5.2`	direct
PyPI	openpyxl	`3.1.5`	direct
PyPI	pandas	`3.0.5`	direct
PyPI	pillow	`13.0.0`	direct
PyPI	pyyaml	`6.0.3`	direct
PyPI	qis	`5.38.1`	direct
PyPI	scipy	`1.17.1`	direct
PyPI	scipy	`1.18.0`	direct
PyPI	scs	`3.2.11`	direct
PyPI	seaborn	`0.13.2`	direct
PyPI	accessible-pygments	`0.0.5`	indirect
PyPI	alabaster	`1.0.0`	indirect
PyPI	attrs	`26.1.0`	indirect
PyPI	babel	`2.18.0`	indirect
PyPI	beautifulsoup4	`4.15.0`	indirect
PyPI	boolean-py	`5.0`	indirect
PyPI	cachecontrol	`0.14.4`	indirect
PyPI	certifi	`2026.10.19`	indirect
PyPI	cffi	`2.1.1`	indirect
PyPI	charset-normalizer	`3.5.0`	indirect
PyPI	clarabel	`0.11.1`	indirect
PyPI	click	`8.4.2`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	contourpy	`1.3.3`	indirect
PyPI	coverage	`7.15.4`	indirect
PyPI	curl-cffi	`0.16.0`	indirect
PyPI	cycler	`0.12.1`	indirect
PyPI	cyclonedx-python-lib	`11.11.2`	indirect
PyPI	defusedxml	`0.7.1`	indirect
PyPI	deptry	`0.25.1`	indirect
PyPI	docutils	`0.22.4`	indirect
PyPI	et-xmlfile	`2.0.0`	indirect
PyPI	filelock	`3.32.2`	indirect
PyPI	fonttools	`4.63.0`	indirect
PyPI	furo	`2025.12.19`	indirect
PyPI	highspy	`1.15.1`	indirect
PyPI	html5lib	`1.1`	indirect
PyPI	idna	`3.18`	indirect
PyPI	imagesize	`2.0.0`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	interrogate	`1.7.0`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	joblib	`1.5.3`	indirect
PyPI	kiwisolver	`1.5.0`	indirect
PyPI	license-expression	`30.4.4`	indirect
PyPI	llvmlite	`0.49.0`	indirect
PyPI	lxml	`6.1.1`	indirect
PyPI	markdown	`3.10.3`	indirect
PyPI	markdown-it-py	`4.2.0`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	mdit-py-plugins	`0.6.1`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	mosek	`11.2.3`	indirect
PyPI	msgpack	`1.2.1`	indirect
PyPI	multitasking	`0.0.13`	indirect
PyPI	myst-parser	`5.1.0`	indirect
PyPI	numba	`0.67.0`	indirect
PyPI	optimalportfolios	`8.0.0rc2`	indirect
PyPI	osqp	`1.1.3`	indirect
PyPI	packageurl-python	`0.17.6`	indirect
PyPI	packaging	`26.3`	indirect
PyPI	patsy	`1.0.2`	indirect
PyPI	peewee	`4.3.0`	indirect
PyPI	pip	`26.2.1`	indirect
PyPI	pip-api	`0.0.34`	indirect
PyPI	pip-audit	`2.10.1`	indirect
PyPI	pip-requirements-parser	`32.0.1`	indirect
PyPI	platformdirs	`4.11.2`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	protobuf	`7.35.1`	indirect
PyPI	py	`1.11.0`	indirect
PyPI	py-serializable	`2.1.0`	indirect
PyPI	pybloqs	`1.4.3`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	pyparsing	`3.3.2`	indirect
PyPI	pytest	`9.1.1`	indirect
PyPI	pytest-cov	`7.1.0`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	pytz	`2026.3.post1`	indirect
PyPI	qdldl	`0.1.9.post1`	indirect
PyPI	quadprog	`0.1.13`	indirect
PyPI	requests	`2.34.2`	indirect
PyPI	requirements-parser	`0.13.1`	indirect
PyPI	rich	`15.0.0`	indirect
PyPI	roman-numerals	`4.1.0`	indirect
PyPI	ruff	`0.16.9`	indirect
PyPI	setuptools	`84.0.0`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	snowballstemmer	`3.1.1`	indirect
PyPI	sortedcontainers	`2.4.0`	indirect
PyPI	soupsieve	`2.9.2`	indirect
PyPI	sparsediffpy	`0.3.0`	indirect
PyPI	sphinx	`9.0.4`	indirect
PyPI	sphinx	`9.1.0`	indirect
PyPI	sphinx-basic-ng	`1.0.0b2`	indirect
PyPI	sphinxcontrib-applehelp	`2.0.0`	indirect
PyPI	sphinxcontrib-devhelp	`2.0.0`	indirect
PyPI	sphinxcontrib-htmlhelp	`2.1.0`	indirect
PyPI	sphinxcontrib-jsmath	`1.0.1`	indirect
PyPI	sphinxcontrib-mermaid	`2.1.1`	indirect
PyPI	sphinxcontrib-qthelp	`2.0.0`	indirect
PyPI	sphinxcontrib-serializinghtml	`2.0.0`	indirect
PyPI	statsmodels	`0.14.6`	indirect
PyPI	tabulate	`0.10.0`	indirect
PyPI	tomli	`2.4.1`	indirect
PyPI	tomli-w	`1.2.0`	indirect
PyPI	typing-extensions	`4.16.0`	indirect
PyPI	tzdata	`2026.3`	indirect
PyPI	urllib3	`2.8.0`	indirect
PyPI	uv	`0.12.23`	indirect
PyPI	webencodings	`0.5.1`	indirect
PyPI	websockets	`17.0.1`	indirect
PyPI	yfinance	`1.5.2`	indirect

Dependency advisories 0

Installing pypi:optimalportfolios@7.22.1 pulls in 43 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 v0.34.0 — 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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