Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-15 01:38 UTC

qiboteam / qibocal

Quantum calibration, characterization and validation module for Qibo.

PythonApache-2.0★ 42 stars⑂ 12 forkssince Jul 2022View on GitHub ↗
KindCommand-line toolLibraryhow this is determined
#calibration#qcvv#quantum-computing#quantum-control

qiboteam/qibocal holds a health index of 90 out of 100, placing it in the Excellent band. It scores highest on Vitality (97/100) and lowest on Community & Adoption (44/100). It was last updated today. 2 contributors account for most of its recent work.

90
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.

90
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 76 is calibrated to 90 on the published index scale (record calibration 2026-08-02).

Ownership

qiboteamOrganization
97 followers43 public repossince Jan 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIqibocal0.2.63372131 days ago

Metrics by category

Vitality

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

97Exceptional · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recency — last push 0 days ago
36/36Commit cadence — 52/52 weeks with commits
18/18Commit volume — 1,092 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,092
human_commit_share0.95
days_since_last_push0
active_weeks_last_year52

Release discipline

92Excellent
How it's scored
27/27Ships releases — 20 releases published
36/36Release recency — latest release 31 days ago
19.8/27Release cadence — a release every ~76.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count20
latest_release_tagv0.2.6
releases_from_tagsno
days_since_latest_release31
mean_days_between_releases76.2
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?

44Weak · 17% of overall

Popularity & adoption

40Weak
How it's scored
26.2/60Stars — 42 stars
8.7/25Forks — 12 forks
5/15Watchers — 9 watchers
Inputs used
forks12
stars42
watchers9
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 (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

42Weak
How it's scored
33.7/80Monthly downloads — 337 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesqibocal
dependents—
ecosystemspypi
total_downloads—
monthly_downloads337
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?

73Good · 23% of overall

Maintainer resilience (bus factor)

64Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
15/22.5Commit distribution — top contributor authored 33% of commits
13.5/13.5Contributor breadth — 31 contributors
10/10OpenSSF Scorecard: Contributors — project has 12 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled31
top_contributor_share0.333

Issue & PR responsiveness

68Good
How it's scored
27/42Issue resolution — 64% of issues closed
25.5/30PR acceptance — 809/951 decided PRs merged
0/13Newcomer PR acceptance — 0/1 first-time contributors' PRs merged in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs809
open_issues245
closed_issues443
prs_merged_7d1
prs_decided_7d1
prs_merged_30d16
prs_decided_30d18
issue_closed_ratio0.644
closed_unmerged_prs142
first_time_authors_30d1
first_time_prs_merged_30d0
first_time_prs_decided_30d1

Ownership & stewardship

68Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
14.3/25Owner reach — 97 followers of qiboteam
24/25Track record — 43 public repos, account ~6 yr old
Inputs used
followers97
owner_typeOrganization
is_verifiedno
owner_loginqiboteam
public_repos43
account_age_days2,428

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 31 days ago
20/20Version history — 21 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesqibocal
ecosystemspypi
any_deprecatedno
min_days_since_publish31

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
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
20/20OpenSSF Scorecard: CI-Tests — 5 out of 5 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://qibo.science
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicscalibration, qcvv, quantum-computing, quantum-control
has_wikiyes
homepagehttps://qibo.science
docs_sitehttps://qibo.science
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

71Good · 16% of overall

Security posture

64Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 5 out of 5 merged PRs checked by a CI test -- score normalized to 10
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 12 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
7.5/7.5Maintained — 30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10
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_aggregate6.4
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
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:qibocal@0.2.6 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.

49Weak · 4% of overall

Agent context & guidance

24At Risk
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
24.1/40Legible commit history — 43 of 95 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.453
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

65Good
How it's scored
18/18One-command bootstrap — doc/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Nix, lockfile
4/10Demonstrated agent practice — 2 of the last 100 commits agent-authored or agent-credited
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_nixyes
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesdoc/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.02
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/192 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes42,493
source_files_sampled192
oversized_source_files0

Key facts

42GitHub stars
31contributors
1,092commits, last 12 months
0days since last push
20releases
2bus factor
245open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'qibocal' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • pypi download figures for qibocal carried forward from the previous scan (stats endpoint unavailable this scan)

More detail

Star and fork history 0 ★ / 12 ⇿
0Stars
12Forks
20Releases

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.

0246810121212022-112024-102026-09
Major 0Minor 2Patch 18

Each point covers 4 days.

OpenSSF Scorecard 6.4 / 10
6.4aggregate

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 · 2026-09-15 01:38 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests5 out of 5 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 12 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 24 issue activity found in the last 90 days -- score normalized to 10
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
Direct dependencies 12
RegistryPackageVersion constraintManifest
PyPIqibolab>=0.2.16,<0.3.0pyproject.toml
PyPIqibo>=0.3.1,<0.4.0pyproject.toml
PyPInumpy>=2.0.0,<3.0.0pyproject.toml
PyPIscipy>=1.10.1,<2.0.0pyproject.toml
PyPIscikit-learn>=1.3.0,<2.0.0pyproject.toml
PyPIpandas>=3.0.0,<4.0.0pyproject.toml
PyPIpydantic>=2.8.0,<3.0.0pyproject.toml
PyPIclick>=8.1.3,<9.0.0pyproject.toml
PyPIjinja2>=3.1.2,<4.0.0pyproject.toml
PyPIplotly>=7.0.0,<8.0.0pyproject.toml
PyPIskops>=0.14.0,<0.15.0pyproject.toml
PyPIpyyaml>=6.0.0,<7.0.0pyproject.toml
All dependencies 193

Full resolved dependency set from the GitHub dependency graph: 23 direct and 170 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIclick8.4.1direct
PyPIclick8.5.0direct
PyPIjinja23.1.6direct
PyPInumpy2.2.6direct
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PyPIpandas2.3.3direct
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PyPIpydantic2.13.4direct
PyPIpydantic2.13.5direct
PyPIpyyaml6.0.3direct
PyPIqibo0.3.3direct
PyPIqibo0.3.4direct
PyPIqibolab0.2.16direct
PyPIscikit-learn1.7.2direct
PyPIscikit-learn1.9.0direct
PyPIscipy1.15.3direct
PyPIscipy1.17.1direct
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PyPIannotated-types0.7.0indirect
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PyPIfonttools4.64.0indirect
PyPIfuro2023.9.10indirect
PyPIfuro2025.12.19indirect
PyPIgreenlet3.5.2indirect
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PyPIh110.16.0indirect
PyPIhtml5lib1.1indirect
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PyPInarwhals2.25.0indirect
PyPInetworkx3.4.2indirect
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PyPIopenqasm31.0.1indirect
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PyPIpackaging26.2indirect
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PyPIpybtex-docutils1.0.3indirect
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PyPIpydantic-core2.46.5indirect
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PyPIpygments2.21.0indirect
PyPIpymdown-extensions11.0.1indirect
PyPIpymdown-extensions11.0.2indirect
PyPIpyparsing3.3.2indirect
PyPIpytest9.1.1indirect
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PyPIpytest-cov7.1.0indirect
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PyPIpytest-mock3.15.1indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-multipart0.0.32indirect
PyPIpytz2026.2indirect
PyPIpyzmq27.1.0indirect
PyPIpyzmq27.2.0indirect
PyPIqibocal0.2.7indirect
PyPIrecommonmark0.7.1indirect
PyPIrequests2.34.2indirect
PyPIroman-numerals4.1.0indirect
PyPIruff0.16.0indirect
PyPIruff0.16.6indirect
PyPIsetuptools83.0.0indirect
PyPIsix1.17.0indirect
PyPIsnowballstemmer3.1.1indirect
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PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
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PyPIsqlalchemy2.0.52indirect
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PyPItraitlets5.16.1indirect
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PyPItyping-inspection0.4.4indirect
PyPItzdata2026.2indirect
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PyPIurllib32.7.0indirect
PyPIuvicorn0.49.0indirect
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PyPIwebencodings0.6.1indirect
PyPIwebsockets16.0indirect
PyPIwebsockets17.1indirect
Dependency advisories 0

Installing pypi:qibocal@0.2.6 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

Feedback

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Related records

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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.