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Software-GesundheitsberichtSchema 0.12.0 · Metriken 1.13.0 · 2026-07-18 13:36 UTC

lanpa / tensorboardX

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

PythonMIT★ 7.989 Sterne⑂ 852 Forksseit Juni 2017Auf GitHub ansehen ↗

lanpa/tensorboardX erreicht einen Gesundheitsindex von 64 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (84/100) ab, am schwächsten bei Security (34/100). Zuletzt vor 3 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

64
gesamt / 100
Mittel

Software-Gesundheitsindex

Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.

64
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
VitalitätCommunity &VerbreitungNachhaltigkeit &GovernanceEngineering-QualitätSicherheitAI Readiness

Bewertungsprofil

Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.

Eigentümerschaft

Tzu-Wei HuangPersönliches Konto
311 Follower30 öffentliche Reposseit Juli 2012

Dieses Repository gehört einem persönlichen Konto. Ein Projekt mit nur einem Eigentümer trägt ein höheres Kontinuitätsrisiko als ein organisationsgetragenes.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPItensorboardX2.6.5-26vor 105 Tagen

Metriken nach Kategorie

Vitalität

Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?

56Mittel · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 3 Tagen
1.4/36Commit-Rhythmus — 2/52 Wochen mit Commits
10.6/18Commit-Volumen — 14 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Verwendete Eingangsdaten
commits_last_year14
human_commit_share
days_since_last_push3
active_weeks_last_year2
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 17 Releases veröffentlicht
27/36Release-Aktualität — letztes Release vor 104 Tagen
12.6/27Release-Rhythmus — ein Release etwa alle 274 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count17
latest_release_tagv2.6.5
releases_from_tagsnein
days_since_latest_release104
mean_days_between_releases274

Community & Verbreitung

Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?

77Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
60/60Stars — 7.989 Stars
24.4/25Forks — 852 Forks
10.6/15Watcher — 82 Watcher
Verwendete Eingangsdaten
forks852
stars7.989
watchers82
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (MIT)
0/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingnein
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templateja

Nachhaltigkeit & Governance

Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?

66Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
5.7/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 75 % der Commits
13.5/13.5Breite der Beitragenden — 78 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor1
contributors_sampled78
top_contributor_share0,747
Wie die Bewertung erfolgt
38.9/46.8Issue-Lösungsquote — 83 % der Issues geschlossen
33.7/38.3PR-Annahme — 271/308 entschiedene PRs gemergt
1.5/15OpenSSF Scorecard: Code-Review — Found 3/27 approved changesets -- score normalized to 1
Verwendete Eingangsdaten
merged_prs271
open_issues77
closed_issues381
issue_closed_ratio0,832
closed_unmerged_prs37
Wie die Bewertung erfolgt
10/30Organisatorische Trägerschaft — persönliches (Nutzer-)Konto
0/20Verifizierte Domain — für Nutzerkonten nicht anwendbar
17.9/25Reichweite des Inhabers — 311 Follower von lanpa
22.9/25Kontohistorie — 30 öffentliche Repos, Kontoalter ca. 14 Jahre
Verwendete Eingangsdaten
followers311
owner_typeUser
is_verified
owner_loginlanpa
public_repos30
account_age_days5.112
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 105 Tagen
20/20Versionshistorie — 26 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagestensorboardX
ecosystemspypi
any_deprecatednein
min_days_since_publish105

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

84Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 3 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — .flake8
0/9.6Pre-Commit-Hooks
0/6.4.editorconfig
10/20OpenSSF Scorecard: CI-Tests — 14 out of 26 merged PRs checked by a CI test -- score normalized to 5
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_confignein

Dokumentation

100Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://tensorboardx.readthedocs.io/en/latest/tensorboard.html
10/10Repository-Beschreibung
10/10Topics — 5 Topics
10/10Wiki
Verwendete Eingangsdaten
topicspytorch, tensorboard, machine-learning, visualization, numpy
has_wikija
homepagehttps://tensorboardx.readthedocs.io/en/latest/tensorboard.html
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?

34Gefährdet · 16 % des Gesamtindex

Sicherheitslage

34Gefährdet
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
1.2/2.5CI-Tests — 14 out of 26 merged PRs checked by a CI test -- score normalized to 5
0/2.5CII-Best-Practices — keine Daten
0.8/7.5Code-Review — Found 3/27 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 5 contributing companies or organizations
0/10Dangerous-Workflow — dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Lizenz — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packaging — packaging workflow detected
0.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
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 — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate3,4
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): cii_best_practices. Die verbleibenden Gewichte wurden renormalisiert.

AI Readiness

Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.

55Mittel · 0 % des Gesamtindex
Wie die Bewertung erfolgt
0/45Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — Makefile, docs/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — .flake8
11/11Statische Typprüfung — tensorboardX/py.typed
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_filesMakefile, docs/Makefile
has_devcontainernein
has_linter_configja
typecheck_configstensorboardX/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis, Automatisierte Wartung. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (tensorboardX/py.typed)
55/55Handhabbare Dateigrößen — 0/84 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes52.965
source_files_sampled84
oversized_source_files0
Wie die Bewertung erfolgt
40/40API-Schema (OpenAPI/GraphQL/proto) — tensorboardX/proto/api.proto, tensorboardX/proto/attr_value.proto, tensorboardX/proto/event.proto, tensorboardX/proto/graph.proto, tensorboardX/proto/layout.proto, tensorboardX/proto/node_def.proto, tensorboardX/proto/plugin_hparams.proto, tensorboardX/proto/plugin_mesh.proto, tensorboardX/proto/plugin_pr_curve.proto, tensorboardX/proto/plugin_text.proto, tensorboardX/proto/resource_handle.proto, tensorboardX/proto/summary.proto, tensorboardX/proto/tensor.proto, tensorboardX/proto/tensor_shape.proto, tensorboardX/proto/types.proto, tensorboardX/proto/versions.proto
0/20MCP-Server
40/40Lauffähige Beispiele — examples
Verwendete Eingangsdaten
example_dirsexamples
has_mcp_signalnein
api_schema_filestensorboardX/proto/api.proto, tensorboardX/proto/attr_value.proto, tensorboardX/proto/event.proto, tensorboardX/proto/graph.proto, tensorboardX/proto/layout.proto, tensorboardX/proto/node_def.proto, tensorboardX/proto/plugin_hparams.proto, tensorboardX/proto/plugin_mesh.proto, tensorboardX/proto/plugin_pr_curve.proto, tensorboardX/proto/plugin_text.proto, tensorboardX/proto/resource_handle.proto, tensorboardX/proto/summary.proto, tensorboardX/proto/tensor.proto, tensorboardX/proto/tensor_shape.proto, tensorboardX/proto/types.proto, tensorboardX/proto/versions.proto

Eckdaten

7.989GitHub-Sterne
78Mitwirkende
14Commits, letzte 12 Monate
3Tage seit letztem Push
17Releases
1Bus-Faktor
77offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 3.4 / 10
3.4Gesamtwert

Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).Scorecard v5.5.0 · 2026-07-18 13:35 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
5CI-Tests14 out of 26 merged PRs checked by a CI test -- score normalized to 5
k. A.CII-Best-Practicesinternal error: error during json parsing: error during json.Unmarshal: invalid character '<' looking for beginning of value
1Code-ReviewFound 3/27 approved changesets -- score normalized to 1
10Contributorsproject has 5 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direkte Abhängigkeiten 3
RegistryPaketVersionsvorgabeManifest
PyPInumpypyproject.toml
PyPIpackagingpyproject.toml
PyPIprotobuf>=3.20pyproject.toml
Alle Abhängigkeiten 18

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 4 direkte und 14 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPInumpydirekt
PyPIpackagingdirekt
PyPIprotobufdirekt
PyPIprotobuf5.29.6direkt
PyPIboto3indirekt
PyPIflake8indirekt
PyPIimageioindirekt
PyPImatplotlibindirekt
PyPImotoindirekt
PyPImoviepyindirekt
PyPIonnxindirekt
PyPIpytestindirekt
PyPIpytest-covindirekt
PyPIsoundfileindirekt
PyPIsphinx-rtd-themeindirekt
PyPItensorboardindirekt
PyPItorchindirekt
PyPItorchvisionindirekt
JSON-Rohbericht maschinenlesbar
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