Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-18 23:53 UTC

rotmanfinhub / deep-macrofin

Deep neural network for solving continuous time economic models

PythonMIT★ 13 stars⑂ 10 forkssince May 2024View on GitHub ↗
KindLibraryhow this is determined

rotmanfinhub/deep-macrofin holds a health index of 54 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (67/100) and lowest on Community & Adoption (35/100). It was last updated 31 days ago. A single contributor accounts for most of its recent work.

54
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.

54
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 53 is calibrated to 54 on the published index scale (record calibration 2026-08-02).

Ownership

Rotman FinHubOrganization
28 followers8 public repossince Oct 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdeep_macrofin0.5.3661675 days ago

Metrics by category

Vitality

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

58Moderate · 21% of overall

Development activity

35Weak
How it's scored
18/36Push recency — last push 31 days ago
4.8/36Commit cadence — 7/52 weeks with commits
11.5/18Commit volume — 18 commits in the last year
1/10OpenSSF Scorecard: Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
Inputs used
commits_last_year18
human_commit_share1
days_since_last_push31
active_weeks_last_year7

Release discipline

92Excellent
How it's scored
27/27Ships releases — 17 releases published
36/36Release recency — latest release 75 days ago
19.8/27Release cadence — a release every ~73.1 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count17
latest_release_tagv0.5.3
releases_from_tagsno
days_since_latest_release75
mean_days_between_releases73.1
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?

35Weak · 17% of overall

Popularity & adoption

26At Risk
How it's scored
17.5/60Stars — 13 stars
8/25Forks — 10 forks
0/15Watchers — 1 watchers
Inputs used
forks10
stars13
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
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_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, github.com, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

30At Risk
How it's scored
24.3/80Monthly downloads — 66 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdeep_macrofin
dependents—
ecosystemspypi
total_downloads—
monthly_downloads66
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?

58Moderate · 23% of overall

Maintainer resilience (bus factor)

13Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1.1/22.5Commit distribution — top contributor authored 95% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.952

Issue & PR responsiveness

79Good
How it's scored
39.4/42Issue resolution — 94% of issues closed
29.4/30PR acceptance — 50/51 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/23 approved changesets -- score normalized to 0
Inputs used
merged_prs50
open_issues1
closed_issues15
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.938
closed_unmerged_prs1
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

57Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
10.5/25Owner reach — 28 followers of rotmanfinhub
16.9/25Track record — 8 public repos, account ~4 yr old
Inputs used
followers28
owner_typeOrganization
is_verifiedno
owner_loginrotmanfinhub
public_repos8
account_age_days1,815

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 75 days ago
20/20Version history — 16 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdeep_macrofin
ecosystemspypi
any_deprecatedno
min_days_since_publish75

Engineering Quality

Are baseline engineering and documentation practices in place?

67Good · 19% of overall

Engineering practices

58Moderate
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
10/20OpenSSF Scorecard: CI-Tests — 13 out of 22 merged PRs checked by a CI test -- score normalized to 5
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://rotmanfinhub.github.io/deep-macrofin/
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttps://rotmanfinhub.github.io/deep-macrofin/
docs_sitehttps://rotmanfinhub.github.io/deep-macrofin/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

44Weak · 16% of overall

Security posture

30At Risk
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
1.2/2.5CI-Tests — 13 out of 22 merged PRs checked by a CI test -- score normalized to 5
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/23 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0.8/7.5Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
5/5Packaging — packaging workflow detected
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
0/7.5Vulnerabilities — 127 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate3
Excluded from scoring (no data or not applicable): 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
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_packages48
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:deep_macrofin@0.5.3 runtime dependency closure — what installing the published package pulls in — 48 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.

45Weak · 4% of overall

Agent context & guidance

29At Risk
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
29.4/40Legible commit history — 48 of 87 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.552
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

32At Risk
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 87
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

54Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
53.5/55Manageable file sizes — 2/71 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes109,873
source_files_sampled71
oversized_source_files2

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

13GitHub stars
2contributors
18commits, last 12 months
31days since last push
17releases
1bus factor
1open 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 ★ / 10 ⇿
0Stars
10Forks
11Releases

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.

02468101012024-082025-082026-07
Major 0Minor 3Patch 8

Each point covers 2 days.

OpenSSF Scorecard 3.0 / 10
3.0aggregate

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 · 2026-10-18 23:53 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
5CI-Tests13 out of 22 merged PRs checked by a CI test -- score normalized to 5
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/23 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
1Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
10Packagingpackaging workflow 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
0Vulnerabilities127 existing vulnerabilities detected
Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPInumpy>=2.0pyproject.toml
PyPIpandas>=2.2.2pyproject.toml
PyPItorch>=2.3.0pyproject.toml
PyPIsympy>=1.12pyproject.toml
PyPItqdm>=4.66.4pyproject.toml
PyPImatplotlib>=3.9.0pyproject.toml
PyPIscikit-learn>=1.3.2pyproject.toml
All dependencies 186

Full resolved dependency set from the GitHub dependency graph: 18 direct and 168 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPImatplotlib3.10.8direct
PyPInumpy—direct
PyPInumpy2.2.6direct
PyPInumpy2.4.2direct
PyPIpandas—direct
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PyPIpandas3.0.1direct
PyPIscikit-learn—direct
PyPIscikit-learn1.7.2direct
PyPIscikit-learn1.8.0direct
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PyPIsympy1.14.0direct
PyPItorch—direct
PyPItorch2.10.0direct
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PyPItqdm—direct
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PyPIbackrefs6.2indirect
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PyPIcuda-pathfinder1.3.4indirect
PyPIcycler0.12.1indirect
PyPIdebugpy1.8.20indirect
PyPIdecorator5.2.1indirect
PyPIdeep-macrofin0.5.0indirect
PyPIdefusedxml0.7.1indirect
PyPIexceptiongroup1.3.1indirect
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PyPIurllib32.6.3indirect
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PyPIwebsocket-client1.9.0indirect
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Dependency advisories 0

Installing pypi:deep_macrofin@0.5.3 pulls in 48 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.