Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-20 06:13 UTC

tensorcircuit / tensorcircuit-ng

Next-gen AI-native tensor-network-based quantum software framework

PythonApache-2.0★ 92 stars⑂ 25 forkssince Aug 2024View on GitHub ↗
KindLibraryhow this is determined
#jax#machine-learning#nisq#open-quantum-systems#pytorch#quantum-algorithm#quantum-circuit#quantum-computing#quantum-dynamics#quantum-hardware#quantum-noise#tensor-network#tensorflow#quantum-machine-learning#automatic-differentiation#gpu#quantum-simulation#distributed-training#ai-agent#quantum-error-correction

tensorcircuit/tensorcircuit-ng holds a health index of 77 out of 100, placing it in the Good band. It scores highest on Vitality (91/100) and lowest on Security (21/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

77
overall / 100
Good

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.

77
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 66 is calibrated to 77 on the published index scale (record calibration 2026-08-02).

Ownership

TensorCircuitOrganization
16 followers4 public repossince Dec 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPItensorcircuit-ng1.10.07811617 days ago

Metrics by category

Vitality

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

91Excellent · 21% of overall

Development activity

90Excellent
How it's scored
36/36Push recency — last push 2 days ago
27/36Commit cadence — 39/52 weeks with commits
18/18Commit volume — 647 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year647
human_commit_share1
days_since_last_push2
active_weeks_last_year39

Release discipline

92Excellent
How it's scored
27/27Ships releases — 14 releases published
36/36Release recency — latest release 17 days ago
19.8/27Release cadence — a release every ~64.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count14
latest_release_tagv1.10.0
releases_from_tagsno
days_since_latest_release17
mean_days_between_releases64.9

Community & Adoption

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

59Moderate · 17% of overall

Popularity & adoption

43Weak
How it's scored
31.8/60Stars — 92 stars
11.5/25Forks — 25 forks
0/15Watchers — 1 watchers
Inputs used
forks25
stars92
watchers1
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 (Apache-2.0)
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_servicesshields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

48Weak
How it's scored
38.6/80Monthly downloads — 781 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagestensorcircuit-ng
dependents—
ecosystemspypi
total_downloads—
monthly_downloads781
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)

33At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
7.1/22.5Commit distribution — top contributor authored 69% of commits
13.5/13.5Contributor breadth — 36 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor1
contributors_sampled36
top_contributor_share0.686

Issue & PR responsiveness

77Good
How it's scored
29.6/42Issue resolution — 70% of issues closed
25.9/30PR acceptance — 106/123 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_prs106
open_issues8
closed_issues19
prs_merged_7d4
prs_decided_7d4
prs_merged_30d26
prs_decided_30d28
issue_closed_ratio0.704
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

50Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
8.8/25Owner reach — 16 followers of tensorcircuit
10.7/25Track record — 4 public repos, account ~2 yr old
Inputs used
followers16
owner_typeOrganization
is_verifiedno
owner_logintensorcircuit
public_repos4
account_age_days1,028

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 17 days ago
20/20Version history — 16 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagestensorcircuit-ng
ecosystemspypi
any_deprecatedno
min_days_since_publish17

Engineering Quality

Are baseline engineering and documentation practices in place?

88Excellent · 19% of overall

Engineering practices

80Excellent
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — .pylintrc
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

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://tensorcircuit-ng.readthedocs.io/en/latest/platform/index.html
10/10Repository description
10/10Topics — 20 topics
10/10Wiki
Inputs used
topicsjax, machine-learning, nisq, open-quantum-systems, pytorch, quantum-algorithm, quantum-circuit, quantum-computing, quantum-dynamics, quantum-hardware, quantum-noise, tensor-network, tensorflow, quantum-machine-learning, automatic-differentiation, gpu, quantum-simulation, distributed-training, ai-agent, quantum-error-correction
has_wikiyes
homepagehttps://tensorcircuit-ng.readthedocs.io/en/latest/platform/index.html
docs_sitehttps://tensorcircuit-ng.readthedocs.io/en/latest/platform/index.html
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

21At Risk · 16% of overall

Security posture

1Critical
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—
manifestsbenchmarks/requirements.txt, pyproject.toml, requirements/requirements-2411.txt, requirements/requirements-dev.txt, requirements/requirements-docker-v2.txt, requirements/requirements-docker.txt, requirements/requirements-extra.txt, requirements/requirements-rtd.txt, requirements/requirements-types.txt, requirements/requirements.txt, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. 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_packages9
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:tensorcircuit-ng@1.10.0 runtime dependency closure — what installing the published package pulls in — 9 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.

73Good · 4% of overall

Agent context & guidance

62Moderate
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
16.5/40Legible commit history — 31 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.31
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes6,930

Verify loop (build / test / typecheck)

79Good
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — .pylintrc
0/11Static type checking
10/10Reproducible environment — devcontainer, Dockerfile
10/10Demonstrated agent practice — 8 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_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontaineryes
has_linter_configyes
typecheck_configs—
agent_commit_share0.08
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
53.7/55Manageable file sizes — 10/425 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes123,426
source_files_sampled425
oversized_source_files10

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

92GitHub stars
36contributors
647commits, last 12 months
2days since last push
14releases
1bus factor
8open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 25 ⇿
0Stars
25Forks
12Releases

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.

05101520252522024-122025-112026-09
Major 0Minor 9Patch 3

Each point covers 2 days.

Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPInumpy—pyproject.toml
PyPIscipy—pyproject.toml
PyPItensornetwork-ng—pyproject.toml
PyPInetworkx—pyproject.toml
PyPIsympy—pyproject.toml
All dependencies 316

Full resolved dependency set from the GitHub dependency graph: 13 direct and 303 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInetworkx—direct
PyPInetworkx3.4.2direct
PyPInumpy—direct
PyPInumpy1.23.5direct
PyPInumpy1.26.4direct
PyPIscipy—direct
PyPIscipy1.10.1direct
PyPIscipy1.14.1direct
PyPIsympy—direct
PyPIsympy1.12direct
PyPIsympy1.13.1direct
PyPItensornetwork-ng—direct
PyPItensornetwork-ng0.5.0direct
PyPIabsl-py2.1.0indirect
PyPIalabaster1.0.0indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.6.2.post1indirect
PyPIastroid3.3.5indirect
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PyPIastunparse1.6.3indirect
PyPIattrs24.2.0indirect
PyPIbabel2.16.0indirect
PyPIbaytune—indirect
PyPIbeautifulsoup44.12.3indirect
PyPIblack—indirect
PyPIblack23.3.0indirect
PyPIblack24.10.0indirect
PyPIbleach6.2.0indirect
PyPIbuild—indirect
PyPIcachetools5.5.0indirect
PyPIcertifi2024.8.30indirect
PyPIcffi1.17.1indirect
PyPIcharset-normalizer3.4.0indirect
PyPIchex0.1.87indirect
PyPIcirq—indirect
PyPIcirq1.1.0indirect
PyPIcirq1.4.1indirect
PyPIcirq-aqt1.4.1indirect
PyPIcirq-core1.4.1indirect
PyPIcirq-google1.4.1indirect
PyPIcirq-ionq1.4.1indirect
PyPIcirq-pasqal1.4.1indirect
PyPIcirq-rigetti1.4.1indirect
PyPIcirq-web1.4.1indirect
PyPIclick8.1.7indirect
PyPIcontourpy1.3.1indirect
PyPIcotengra—indirect
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PyPIquimb1.11.1indirect
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PyPIscikit-learn—indirect
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PyPIsphinxcontrib-htmlhelp2.1.0indirect
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PyPIstim—indirect
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PyPItensorflow2.11indirect
PyPItensorflow2.18.0indirect
PyPItensorflow2.20indirect
PyPItensorflow2.4.1indirect
PyPItensorflow2.7indirect
PyPItensorflow-io-gcs-filesystem0.37.1indirect
PyPItensorflow-quantum0.5.1indirect
PyPItensornetwork—indirect
PyPItensornetwork0.4.5indirect
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PyPItokenize-rt6.1.0indirect
PyPItomli2.2.1indirect
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PyPItorch—indirect
PyPItorch2.5.1indirect
PyPItorchvision—indirect
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PyPItqdm4.67.1indirect
PyPItraitlets5.14.3indirect
PyPItypes-deprecated1.2.15.20241117indirect
PyPItypes-docutils—indirect
PyPItypes-docutils0.21.0.20241128indirect
PyPItypes-protobuf—indirect
PyPItypes-protobuf5.28.3.20241030indirect
PyPItypes-pytz—indirect
PyPItypes-pytz2024.2.0.20241003indirect
PyPItypes-requests—indirect
PyPItypes-requests2.32.0.20241016indirect
PyPItypes-setuptools—indirect
PyPItypes-setuptools75.6.0.20241126indirect
PyPItypes-toml—indirect
PyPItypes-toml0.10.8.20240310indirect
PyPItypes-typed-ast—indirect
PyPItypes-typed-ast1.5.8.7indirect
PyPItypes-urllib3—indirect
PyPItypes-urllib31.26.25.14indirect
PyPItyping-extensions4.12.2indirect
PyPItzdata2024.2indirect
PyPIurllib31.26.15indirect
PyPIurllib32.2.3indirect
PyPIwcwidth0.2.13indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.8.0indirect
PyPIwerkzeug3.1.3indirect
PyPIwrapt1.17.0indirect
Dependency advisories 0

Installing pypi:tensorcircuit-ng@1.10.0 pulls in 9 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.

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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.