Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.17.0 · Metriken 1.13.0 · 2026-07-21 03:28 UTC
geopandas / contextily
Context geo-tiles in Python
geopandas/contextily erreicht einen Gesundheitsindex von 68 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Sustainability & Governance (74/100) ab, am schwächsten bei AI Readiness (39/100). Zuletzt vor 10 Tagen aktualisiert. 2 Mitwirkende tragen den Großteil der jüngsten Arbeit.
68
gesamt / 100Software-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.
68
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)
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
GeoPandasOrganisation
368 Follower14 öffentliche Reposseit Juli 2014
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht |
|---|---|---|---|---|---|
| PyPI | contextily | 1.7.1 | 641.407 | 20 | vor 10 Tagen |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
62
Entwicklungsaktivität
52Mittel
Wie die Bewertung erfolgt
| 28.8/36 | Push-Aktualität — letzter Push vor 10 Tagen |
| 8.3/36 | Commit-Rhythmus — 12/52 Wochen mit Commits |
| 11.7/18 | Commit-Volumen — 19 Commits im letzten Jahr |
| 3/10 | OpenSSF Scorecard: Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3 |
Verwendete Eingangsdaten
| commits_last_year | 19 |
| human_commit_share | — |
| days_since_last_push | 10 |
| active_weeks_last_year | 12 |
Release-Disziplin
76Gut
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 17 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 10 Tagen |
| 12.6/27 | Release-Rhythmus — ein Release etwa alle 138,9 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases. |
Verwendete Eingangsdaten
| releases_count | 17 |
| latest_release_tag | v1.7.1 |
| releases_from_tags | nein |
| days_since_latest_release | 10 |
| mean_days_between_releases | 138,9 |
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
69
Popularität & Verbreitung
68Mittel
Wie die Bewertung erfolgt
| 44.9/60 | Stars — 589 Stars |
| 16.3/25 | Forks — 91 Forks |
| 6.5/15 | Watcher — 16 Watcher |
Verwendete Eingangsdaten
| forks | 91 |
| stars | 589 |
| watchers | 16 |
| growth_state | organic |
| growth_factor_pct | 100 |
Community-Gesundheit
50Mittel
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (BSD-3-Clause) |
| 0/18 | CONTRIBUTING-Leitfaden |
| 0/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 0/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | nein |
| has_issue_template | nein |
| has_code_of_conduct | nein |
| has_pull_request_template | nein |
Ökosystem-Verbreitung (Downloads)
97Exzellent
Wie die Bewertung erfolgt
| 77.4/80 | Downloads pro Monat — 641.407 Downloads/Monat über pypi |
| 0/20 | Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen |
Verwendete Eingangsdaten
| packages | contextily |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 641.407 |
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?
74
Wie die Bewertung erfolgt
| 25.2/54 | Bus-Faktor — 2 Beitragende decken die Hälfte aller Commits ab |
| 12.5/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 45 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 32 Beitragende |
| 10/10 | OpenSSF Scorecard: Contributors — project has 55 contributing companies or organizations |
Verwendete Eingangsdaten
| bus_factor | 2 |
| contributors_sampled | 32 |
| top_contributor_share | 0,446 |
Wie die Bewertung erfolgt
| 34.1/46.8 | Issue-Lösungsquote — 73 % der Issues geschlossen |
| 34/38.3 | PR-Annahme — 128/144 entschiedene PRs gemergt |
| 6/15 | OpenSSF Scorecard: Code-Review — Found 10/21 approved changesets -- score normalized to 4 |
Verwendete Eingangsdaten
| merged_prs | 128 |
| open_issues | 36 |
| closed_issues | 97 |
| issue_closed_ratio | 0,729 |
| closed_unmerged_prs | 16 |
Eigentümerschaft & Trägerschaft
69Mittel
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 18.5/25 | Reichweite des Inhabers — 368 Follower von geopandas |
| 20.6/25 | Kontohistorie — 14 öffentliche Repos, Kontoalter ca. 12 Jahre |
Verwendete Eingangsdaten
| followers | 368 |
| owner_type | Organization |
| is_verified | — |
| owner_login | geopandas |
| public_repos | 14 |
| account_age_days | 4.393 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 10 Tagen |
| 20/20 | Versionshistorie — 20 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | contextily |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 10 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
74
Engineering-Praktiken
56Mittel
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 2 Workflow(s) |
| 24/24 | Tests vorhanden |
| 0/16 | Linter-Konfiguration |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 8/20 | OpenSSF Scorecard: CI-Tests — 12 out of 29 merged PRs checked by a CI test -- score normalized to 4 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | nein |
| has_precommit_config | nein |
Dokumentation
100Exzellent
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://contextily.readthedocs.io/en/latest/ |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 12 Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | tiles, stamen, openstreetmap, python, tile, mapping, webtiles, geography, cartography, matplotlib, osm, stamen-maps |
| has_wiki | ja |
| homepage | https://contextily.readthedocs.io/en/latest/ |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
57
Sicherheitslage
46Gefährdet
Wie die Bewertung erfolgt
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — branch protection not enabled on development/release branches |
| 1/2.5 | CI-Tests — 12 out of 29 merged PRs checked by a CI test -- score normalized to 4 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 3/7.5 | Code-Review — Found 10/21 approved changesets -- score normalized to 4 |
| 2.5/2.5 | Contributors — project has 55 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Lizenz — license file detected |
| 2.2/7.5 | Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — Project has not signed or included provenance with any releases. |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 18 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 0 |
| scorecard_aggregate | 4,6 |
Abhängigkeits-Advisories
100Exzellent
Wie die Bewertung erfolgt
| 35/35 | Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory |
| 25/25 | Indirekte Abhängigkeiten ohne bekannte Advisories — keine indirekte Abhängigkeit trägt ein bekanntes Advisory |
| 0/40 | Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum |
Verwendete Eingangsdaten
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 26 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. Abgeglichen wurde die Laufzeit-Abhängigkeitshülle von pypi:contextily@1.7.1 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 26 Paketen. Erreichbarkeit wird nicht analysiert.
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.
39
AI-Agentenkontext & Leitlinien
1Kritisch
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 0/40 | Lesbare Commit-Historie — keine Daten |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| 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
| 18/18 | Bootstrap mit einem Befehl — docs/Makefile |
| 22/22 | Automatisierte Tests |
| 0/11 | Lint-/Format-Konfiguration |
| 0/11 | Statische Typprüfung |
| 10/10 | Reproduzierbare Umgebung — Dockerfile |
| 0/10 | Belegte Agentenpraxis — keine Daten |
| 5/8 | Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | ja |
| typed_language | nein |
| bootstrap_files | docs/Makefile |
| has_devcontainer | nein |
| has_linter_config | nein |
| typecheck_configs | — |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis. Die verbleibenden Gewichte wurden renormalisiert.
AI-Code-Lesbarkeit für Modelle
55Mittel
Wie die Bewertung erfolgt
| 0/45 | Typprüfbarer Code — Jupyter Notebook ohne Typprüfungs-Konfiguration |
| 55/55 | Handhabbare Dateigrößen — 0/9 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Jupyter Notebook |
| largest_source_bytes | 37.297 |
| source_files_sampled | 9 |
| oversized_source_files | 0 |
Maschinenlesbare AI-Schnittstellen
40Gefährdet
Wie die Bewertung erfolgt
| 0/40 | API-Schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP-Server |
| 40/40 | Lauffähige Beispiele — notebooks |
Verwendete Eingangsdaten
| example_dirs | notebooks |
| has_mcp_signal | nein |
| api_schema_files | — |
Eckdaten
589GitHub-Sterne
32Mitwirkende
19Commits, letzte 12 Monate
10Tage seit letztem Push
17Releases
2Bus-Faktor
36offene Issues
PyPIPaket-Ökosysteme
Weitere Details
Stern- und Fork-Verlauf 589 ★ / 0 ⇿
589Sterne
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Es wird nur die jüngste Historie angezeigt — dieses Repository überschreitet das Erfassungsfenster, sodass die früheste Historie nicht erfasst wird.
Jeder Punkt umfasst 9 Tage.
OpenSSF Scorecard 4.6 / 10
4.6Gesamtwert
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 0 | Branch-Protection | branch protection not enabled on development/release branches |
| 4 | CI-Tests | 12 out of 29 merged PRs checked by a CI test -- score normalized to 4 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 4 | Code-Review | Found 10/21 approved changesets -- score normalized to 4 |
| 10 | Contributors | project has 55 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 3 | Maintained | 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| 0 | Signed-Releases | Project has not signed or included provenance with any releases. |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Direkte Abhängigkeiten 8
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | geopy | — | pyproject.toml |
| PyPI | matplotlib | — | pyproject.toml |
| PyPI | mercantile | — | pyproject.toml |
| PyPI | pillow | — | pyproject.toml |
| PyPI | rasterio | — | pyproject.toml |
| PyPI | requests | — | pyproject.toml |
| PyPI | joblib | — | pyproject.toml |
| PyPI | xyzservices | — | pyproject.toml |
Alle Abhängigkeiten 2
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 2 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | setuptools | — | indirekt |
| PyPI | setuptools-scm | — | indirekt |
Abhängigkeits-Advisories 0
Die Installation von pypi:contextily@1.7.1 zieht 26 Pakete nach sich, direkt und transitiv: 0 tragen bekannte Advisories, davon 0 direkte Abhängigkeiten.
Keine bekannten Advisories betreffen die bewerteten Abhängigkeiten.
Ein Advisory bedeutet, dass die im Abhängigkeitsgraphen erfasste Version in den betroffenen Bereich eines Advisories fällt. Erreichbarkeit wird nicht analysiert, und der Graph enthält Entwicklungs- und Test-Pins — ein Fund kann das Werkzeug betreffen und nicht die ausgelieferte Software.
JSON-Rohbericht maschinenlesbar
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{
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}
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"points": 16.3,
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"code": "forks",
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}
],
"max_points": 25
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},
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"count": 641407,
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}
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{
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{
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}
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}
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{
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}
]
},
{
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"issue_closed_ratio": 0.729,
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}
],
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{
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"details": [
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}
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{
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]
},
{
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"components": [
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{
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{
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{
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{
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{
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{
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}
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],
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},
{
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{
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{
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},
{
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"inputs": {
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}
],
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{
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{
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{
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},
{
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},
{
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},
{
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},
{
"key": "license",
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},
{
"key": "maintained",
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{
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{
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{
"key": "sast",
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"points": 0,
"status": "missed",
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},
{
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"status": "missed",
"details": [],
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},
{
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"points": 0,
"status": "missed",
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"max_points": 7.5
},
{
"key": "token_permissions",
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"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "0 existing vulnerabilities detected",
"points": 7.5,
"status": "met",
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"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
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"notes": [
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{
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{
"code": "advisories_scope_published",
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},
{
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"inputs": {
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"direct_affected_packages": 0
},
"components": [
{
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"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
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}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
"name": "Indirect dependencies free of known advisories",
"detail": "no indirect dependency carries a known advisory",
"points": 25,
"status": "met",
"details": [
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],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
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"points": 0,
"status": "excluded",
"details": [
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],
"max_points": 40
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]
},
{
"key": "malicious_dependencies",
"band": "excellent",
"name": "Malicious dependencies",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"source": "osv",
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"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
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},
"components": [
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"key": "no_dependency_reported_as_a_malicious_package",
"name": "No dependency reported as a malicious package",
"detail": "no dependency is reported as a malicious package",
"points": 100,
"status": "met",
"details": [
{
"code": "no_malicious_dependencies",
"params": {}
}
],
"max_points": 100
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "excellent",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 33
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 39,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"legible_commit_history"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 1,
"inputs": {
"has_llms_txt": false,
"legible_history_share": null,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "moderate",
"name": "Verify loop (build / test / typecheck)",
"note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"demonstrated_agent_practice"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 61,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": true,
"typed_language": false,
"bootstrap_files": [
"docs/Makefile"
],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": null,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "docs/Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "docs/Makefile"
}
}
],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": "Dockerfile",
"points": 10,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "Dockerfile"
}
}
],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "dependency automation configured, none observed in the sampled commits",
"points": 5,
"status": "partial",
"details": [
{
"code": "dependency_bot_config_only",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 55,
"inputs": {
"primary_language": "Jupyter Notebook",
"largest_source_bytes": 37297,
"source_files_sampled": 9,
"oversized_source_files": 0
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Jupyter Notebook without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Jupyter Notebook"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "0/9 source files over 60KB",
"points": 55,
"status": "met",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 9,
"oversized": 0
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "at_risk",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"notebooks"
],
"has_mcp_signal": false,
"api_schema_files": []
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 40
},
{
"key": "mcp_server",
"name": "MCP server",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": "notebooks",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "notebooks"
}
}
],
"max_points": 40
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [],
"report_type": "repository",
"generated_at": "2026-07-21T03:28:49.387302Z",
"schema_version": "0.17.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/g/geopandas/contextily.svg",
"full_name": "geopandas/contextily",
"license_state": "standard",
"license_spdx": "BSD-3-Clause"
}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 v0.17.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.