Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.23.0 · Metriken 1.13.0 · 2026-07-21 20:22 UTC
lmfit / asteval
minimalistic evaluator of python expression using ast module
lmfit/asteval erreicht einen Gesundheitsindex von 67 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (81/100) ab, am schwächsten bei AI Readiness (34/100). Zuletzt vor 40 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
67
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.
67
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
lmfitOrganisation
34 Follower5 öffentliche Reposseit Dez. 2013
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 | Tags |
|---|---|---|---|---|---|---|
| PyPI | asteval | 1.0.9 | - | 42 | vor 40 Tagen | astexpression-evaluationeval |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
68
Entwicklungsaktivität
52Mittel
Wie die Bewertung erfolgt
| 18/36 | Push-Aktualität — letzter Push vor 40 Tagen |
| 8.3/36 | Commit-Rhythmus — 12/52 Wochen mit Commits |
| 15.3/18 | Commit-Volumen — 49 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 49 |
| human_commit_share | 1 |
| days_since_last_push | 40 |
| active_weeks_last_year | 12 |
Release-Disziplin
92Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 36 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 40 Tagen |
| 19.8/27 | Release-Rhythmus — ein Release etwa alle 78,9 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 36 |
| latest_release_tag | 1.0.9 |
| releases_from_tags | nein |
| days_since_latest_release | 40 |
| mean_days_between_releases | 78,9 |
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?
54
Popularität & Verbreitung
58Mittel
Wie die Bewertung erfolgt
| 37.9/60 | Stars — 219 Stars |
| 14.2/25 | Forks — 51 Forks |
| 5.8/15 | Watcher — 12 Watcher |
Verwendete Eingangsdaten
| forks | 51 |
| stars | 219 |
| watchers | 12 |
| 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 (MIT) |
| 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 |
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
65
Maintainer-Resilienz (Bus-Faktor)
35Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 2.5/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 89 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 26 Beitragende |
| 10/10 | OpenSSF Scorecard: Contributors — project has 9 contributing companies or organizations |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 26 |
| top_contributor_share | 0,888 |
Wie die Bewertung erfolgt
| 46.8/46.8 | Issue-Lösungsquote — 100 % der Issues geschlossen |
| 30.4/38.3 | PR-Annahme — 58/73 entschiedene PRs gemergt |
| 1.5/15 | OpenSSF Scorecard: Code-Review — Found 1/10 approved changesets -- score normalized to 1 |
Verwendete Eingangsdaten
| merged_prs | 58 |
| open_issues | 0 |
| closed_issues | 79 |
| issue_closed_ratio | 1 |
| closed_unmerged_prs | 15 |
Eigentümerschaft & Trägerschaft
59Mittel
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 11.1/25 | Reichweite des Inhabers — 34 Follower von lmfit |
| 17.7/25 | Kontohistorie — 5 öffentliche Repos, Kontoalter ca. 12 Jahre |
Verwendete Eingangsdaten
| followers | 34 |
| owner_type | Organization |
| is_verified | — |
| owner_login | lmfit |
| public_repos | 5 |
| account_age_days | 4.601 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 40 Tagen |
| 20/20 | Versionshistorie — 42 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | asteval |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 40 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
81
Engineering-Praktiken
68Mittel
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 4 Workflow(s) |
| 24/24 | Tests vorhanden |
| 0/16 | Linter-Konfiguration |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 5 out of 5 merged PRs checked by a CI test -- score normalized to 10 |
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://lmfit.github.io/asteval |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 3 Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | python, ast, eval |
| has_wiki | ja |
| homepage | https://lmfit.github.io/asteval |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
65
Sicherheitslage
65Mittel
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 |
| 2.5/2.5 | CI-Tests — 5 out of 5 merged PRs checked by a CI test -- score normalized to 10 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0.8/7.5 | Code-Review — Found 1/10 approved changesets -- score normalized to 1 |
| 2.5/2.5 | Contributors — project has 9 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 |
| 7.5/7.5 | Maintained — 16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — keine Daten |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 4.5/5 | SAST — SAST tool is not run on all commits -- score normalized to 9 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — keine Daten |
| 7.5/7.5 | Token-Permissions — GitHub workflow tokens follow principle of least privilege |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 6,5 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): packaging, 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.
34
AI-Agentenkontext & Leitlinien
8Kritisch
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 8.5/40 | Lesbare Commit-Historie — 16 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text) |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | 0,16 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
AI-Verify-Loop (Build / Test / Typprüfung)
45Gefährdet
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — doc/Makefile |
| 22/22 | Automatisierte Tests |
| 0/11 | Lint-/Format-Konfiguration |
| 0/11 | Statische Typprüfung |
| 0/10 | Reproduzierbare Umgebung |
| 0/10 | Belegte Agentenpraxis — keine von Agenten verfassten Commits unter den letzten 100 |
| 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 | nein |
| typed_language | nein |
| bootstrap_files | doc/Makefile |
| has_devcontainer | nein |
| has_linter_config | nein |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
AI-Code-Lesbarkeit für Modelle
55Mittel
Wie die Bewertung erfolgt
| 0/45 | Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration |
| 55/55 | Handhabbare Dateigrößen — 0/6 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 58.300 |
| source_files_sampled | 6 |
| oversized_source_files | 0 |
Eckdaten
219GitHub-Sterne
26Mitwirkende
49Commits, letzte 12 Monate
40Tage seit letztem Push
36Releases
1Bus-Faktor
0offene Issues
PyPIPaket-Ökosysteme
Weitere Details
Stern- und Fork-Verlauf 219 ★ / 51 ⇿
219Sterne
51Forks
36Releases
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.
Major 1Minor 0Patch 34
Jeder Punkt umfasst 13 Tage.
OpenSSF Scorecard 6.5 / 10
6.5Gesamtwert
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 |
| 10 | CI-Tests | 5 out of 5 merged PRs checked by a CI test -- score normalized to 10 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 1 | Code-Review | Found 1/10 approved changesets -- score normalized to 1 |
| 10 | Contributors | project has 9 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 |
| 10 | Maintained | 16 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| k. A. | Packaging | packaging workflow not detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 9 | SAST | SAST tool is not run on all commits -- score normalized to 9 |
| 0 | Security-Policy | security policy file not detected |
| k. A. | Signed-Releases | no releases found |
| 10 | Token-Permissions | GitHub workflow tokens follow principle of least privilege |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Alle Abhängigkeiten 0
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 0 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|
Abhängigkeits-Advisories nicht bewertet
Der Advisory-Abgleich konnte für diesen Bericht nicht ausgeführt werden: No resolved dependencies to assess
JSON-Rohbericht maschinenlesbar
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{
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],
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{
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}
]
},
{
"key": "ai_code_legibility",
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"components": [
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],
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},
{
"key": "manageable_file_sizes",
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],
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]
}
],
"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": "2026-07-21T20:22:10.329960Z",
"schema_version": "0.23.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/l/lmfit/asteval.svg",
"full_name": "lmfit/asteval",
"license_state": "standard",
"license_spdx": "MIT"
}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 v0.23.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.