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Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-17 01:05 UTC

mistralai / client-python

Python client library for Mistral AI platform

PythonApache-2.0★ 756 Sterne⑂ 197 Forksseit Dez. 2023Auf GitHub ansehen ↗

mistralai/client-python erreicht einen Gesundheitsindex von 82 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (94/100) ab, am schwächsten bei Security (57/100). Zuletzt heute aktualisiert. 6 Mitwirkende tragen den Großteil der jüngsten Arbeit.

82
gesamt / 100
Gut

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.

82
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

Mistral AIOrganisation
8.794 Follower26 öffentliche Reposseit Mai 2023

Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPImistralai2.6.044.528.60898vor 10 Tagen

Metriken nach Kategorie

Vitalität

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

94Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 0 Tagen
25.6/36Commit-Rhythmus — 37/52 Wochen mit Commits
18/18Commit-Volumen — 192 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year192
human_commit_share
days_since_last_push0
active_weeks_last_year37

Release-Disziplin

100Exzellent
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 85 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 10 Tagen
27/27Release-Rhythmus — ein Release etwa alle 4,4 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count85
latest_release_tagv2.6.0
releases_from_tagsnein
days_since_latest_release10
mean_days_between_releases4,4
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.

Community & Verbreitung

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

79Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
46.7/60Stars — 756 Stars
19.1/25Forks — 197 Forks
8/15Watcher — 28 Watcher
Verwendete Eingangsdaten
forks197
stars756
watchers28
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (Apache-2.0)
18/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templatenein
Wie die Bewertung erfolgt
80/80Downloads pro Monat — 44.528.608 Downloads/Monat über pypi
0/20Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen
Verwendete Eingangsdaten
packagesmistralai
dependents
ecosystemspypi
total_downloads
monthly_downloads44.528.608
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Abhängige in der Registry. Die verbleibenden Gewichte wurden renormalisiert.

Nachhaltigkeit & Governance

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

86Exzellent · 24 % des Gesamtindex
Wie die Bewertung erfolgt
48.6/54Bus-Faktor — 6 Beitragende decken die Hälfte aller Commits ab
19.4/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 14 % der Commits
13.5/13.5Breite der Beitragenden — 57 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor6
contributors_sampled57
top_contributor_share0,14
Wie die Bewertung erfolgt
40.5/46.8Issue-Lösungsquote — 87 % der Issues geschlossen
25.1/38.3PR-Annahme — 286/436 entschiedene PRs gemergt
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Verwendete Eingangsdaten
merged_prs286
open_issues20
closed_issues130
issue_closed_ratio0,867
closed_unmerged_prs150
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 8.794 Follower von mistralai
16.8/25Kontohistorie — 26 öffentliche Repos, Kontoalter ca. 3 Jahre
Verwendete Eingangsdaten
followers8.794
owner_typeOrganization
is_verified
owner_loginmistralai
public_repos26
account_age_days1.171

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 10 Tagen
20/20Versionshistorie — 98 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesmistralai
ecosystemspypi
any_deprecatednein
min_days_since_publish10

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

86Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 8 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_configja
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
0/15Dokumentations-/Homepage-Site
10/10Repository-Beschreibung
0/10Topics
10/10Wiki
Verwendete Eingangsdaten
topics
has_wikija
homepage
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

57Mittel · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
6/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 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 5 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Lizenz — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
4.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
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 — keine Daten
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 57 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5,7
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): signed_releases. 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.

80Gut · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — AGENTS.md, CLAUDE.md, docs/models/agent.md
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_filesAGENTS.md, CLAUDE.md, docs/models/agent.md
agent_instruction_max_bytes5.980
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
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
11/11Statische Typprüfung — packages/azure/py.typed, packages/azure/src/mistralai/azure/client/py.typed, packages/gcp/py.typed, packages/gcp/src/mistralai/gcp/client/py.typed, py.typed, src/mistralai/client/py.typed, src/mistralai/extra/py.typed
10/10Reproduzierbare Umgebung — lockfile
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
9/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesuv.lock
has_dockerfilenein
typed_languagenein
bootstrap_filesMakefile
has_devcontainernein
has_linter_configja
typecheck_configspackages/azure/py.typed, packages/azure/src/mistralai/azure/client/py.typed, packages/gcp/py.typed, packages/gcp/src/mistralai/gcp/client/py.typed, py.typed, src/mistralai/client/py.typed, src/mistralai/extra/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 (packages/azure/py.typed, packages/azure/src/mistralai/azure/client/py.typed, packages/gcp/py.typed, packages/gcp/src/mistralai/gcp/client/py.typed, py.typed, src/mistralai/client/py.typed, src/mistralai/extra/py.typed)
54.4/55Handhabbare Dateigrößen — 13/1.243 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes335.431
source_files_sampled1.243
oversized_source_files13
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples
Verwendete Eingangsdaten
example_dirsexamples
has_mcp_signalnein
api_schema_files

Eckdaten

756GitHub-Sterne
57Mitwirkende
192Commits, letzte 12 Monate
0Tage seit letztem Push
85Releases
6Bus-Faktor
20offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 5.7 / 10
5.7Gesamtwert

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 · 2026-07-17 01:04 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 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 5 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
k. A.Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities57 existing vulnerabilities detected
Direkte Abhängigkeiten 8
RegistryPaketVersionsvorgabeManifest
PyPIeval-type-backport>=0.2.0pyproject.toml
PyPIhttpx>=0.28.1pyproject.toml
PyPIpydantic>=2.11.2pyproject.toml
PyPIpython-dateutil>=2.8.2pyproject.toml
PyPItyping-inspection>=0.4.0pyproject.toml
PyPIopentelemetry-api(>=1.33.1,<2.0.0)pyproject.toml
PyPIopentelemetry-semantic-conventions(>=0.60b1,<0.61)pyproject.toml
PyPIjsonpath-python>=1.0.6pyproject.toml
Alle Abhängigkeiten 136

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 10 direkte und 126 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIeval-type-backport0.3.1direkt
PyPIhttpx0.28.1direkt
PyPIjsonpath-python1.1.5direkt
PyPIopentelemetry-api1.39.1direkt
PyPIopentelemetry-semantic-conventions0.60b1direkt
PyPIpydantic2.11.7direkt
PyPIpydantic2.12.5direkt
PyPIpython-dateutil2.9.0.post0direkt
PyPItyping-inspection0.4.0direkt
PyPItyping-inspection0.4.2direkt
PyPIaioboto312.4.0indirekt
PyPIaiobotocore2.12.3indirekt
PyPIaiofiles25.1.0indirekt
PyPIaiohappyeyeballs2.6.1indirekt
PyPIaiohttp3.13.5indirekt
PyPIaioitertools0.13.0indirekt
PyPIaiosignal1.4.0indirekt
PyPIannotated-types0.7.0indirekt
PyPIanyio4.12.0indirekt
PyPIanyio4.4.0indirekt
PyPIastroid3.2.4indirekt
PyPIasync-timeout5.0.1indirekt
PyPIattrs25.4.0indirekt
PyPIauthlib1.6.6indirekt
PyPIazure-core1.39.0indirekt
PyPIazure-identity1.25.3indirekt
PyPIazure-storage-blob12.28.0indirekt
PyPIbackoff2.2.1indirekt
PyPIboto31.34.69indirekt
PyPIbotocore1.34.69indirekt
PyPIcachetools6.2.4indirekt
PyPIcertifi2024.7.4indirekt
PyPIcertifi2025.11.12indirekt
PyPIcffi2.0.0indirekt
PyPIchardet6.0.0.post1indirekt
PyPIcharset-normalizer3.4.4indirekt
PyPIclick8.3.1indirekt
PyPIcolorama0.4.6indirekt
PyPIcryptography46.0.3indirekt
PyPIdill0.3.8indirekt
PyPIdill0.4.0indirekt
PyPIexceptiongroup1.2.2indirekt
PyPIexceptiongroup1.3.1indirekt
PyPIfrozenlist1.8.0indirekt
PyPIgcloud-aio-auth5.4.4indirekt
PyPIgcloud-aio-storage9.6.4indirekt
PyPIgoogle-auth2.45.0indirekt
PyPIgoogleapis-common-protos1.75.0indirekt
PyPIgriffe1.15.0indirekt
PyPIh110.16.0indirekt
PyPIhatchlingindirekt
PyPIhttpcore1.0.9indirekt
PyPIhttpx-sse0.4.3indirekt
PyPIidna3.11indirekt
PyPIidna3.7indirekt
PyPIimportlib-metadata8.7.1indirekt
PyPIiniconfig2.0.0indirekt
PyPIiniconfig2.3.0indirekt
PyPIinvoke2.2.1indirekt
PyPIisodate0.7.2indirekt
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PyPIjmespath1.1.0indirekt
PyPIjsonschema4.25.1indirekt
PyPIjsonschema-specifications2025.9.1indirekt
PyPImccabe0.7.0indirekt
PyPImcp1.25.0indirekt
PyPImistralai2.7.0indirekt
PyPImistralai-azure2.1.0indirekt
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PyPImypy-extensions1.1.0indirekt
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PyPIopentelemetry-exporter-otlp-proto-common1.39.1indirekt
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PyPIopentelemetry-instrumentation0.60b1indirekt
PyPIopentelemetry-instrumentation-httpx0.60b1indirekt
PyPIopentelemetry-proto1.39.1indirekt
PyPIopentelemetry-sdk1.39.1indirekt
PyPIopentelemetry-util-http0.60b1indirekt
PyPIpackaging24.1indirekt
PyPIpackaging25.0indirekt
PyPIplatformdirs4.2.2indirekt
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PyPIpluggy1.5.0indirekt
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PyPIprotobuf6.33.6indirekt
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PyPIpycparser2.23indirekt
PyPIpydantic-core2.33.2indirekt
PyPIpydantic-core2.41.5indirekt
PyPIpydantic-settings2.12.0indirekt
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PyPIpylint3.2.3indirekt
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PyPIpytest-asyncio0.23.8indirekt
PyPIpython-dotenv1.2.1indirekt
PyPIpython-multipart0.0.21indirekt
PyPIpywin32311indirekt
PyPIpyyaml6.0.3indirekt
PyPIreferencing0.37.0indirekt
PyPIrequests2.32.5indirekt
PyPIrpds-py0.30.0indirekt
PyPIrsa4.9.1indirekt
PyPIruff0.11.13indirekt
PyPIs3transfer0.10.4indirekt
PyPIsix1.17.0indirekt
PyPIsniffio1.3.1indirekt
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PyPItomlkit0.13.0indirekt
PyPItomlkit0.13.3indirekt
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PyPItypes-pyyaml6.0.12.20250915indirekt
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PyPIurllib32.6.2indirekt
PyPIuvicorn0.40.0indirekt
PyPIwebsockets16.0indirekt
PyPIwrapt1.17.3indirekt
PyPIyarl1.23.0indirekt
PyPIzipp3.23.0indirekt
PyPIzstandard0.25.0indirekt
JSON-Rohbericht maschinenlesbar
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    "metrics_version": "1.13.0"
  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-17T01:05:13.409766Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/mistralai/client-python.svg",
  "full_name": "mistralai/client-python",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.

Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.11.0 — vollständige Methodik · Metriken-Wiki.

Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte StatistikenPyPI.