公开记录
软件健康报告模式 0.27.0 · 指标 1.13.0 · 2026-07-25 12:19 UTC

equinor / fmu-tools

fmu-tools is a library containing tools for pre- and post-processing in a Fast Model Update (FMU) context

Python · OpenEdge ABLLGPL-3.0★ 13 星标⑂ 20 复刻始于 2020年3月在 GitHub 上查看 ↗

equinor/fmu-tools 的健康指数为 100 分中的 80 分,处于「良好」区间。 其得分最高的类别是Vitality(94/100),最低的是AI Readiness(46/100)。 最近一次更新在今天。 近期的大部分工作由 3 位贡献者完成。

80
总分 / 100
良好

软件健康指数

指标归入加权类别,统一采用 1–100 量表。总体分先取类别加权平均;当公开证据触发高风险司法辖区政策时,评级会按政策调整,并设置 49(有风险)的上限。AI 就绪度不计入总体分。

80
优秀85-100堪称典范;基本满足所有检验标准
良好70-84健康;仅有轻微不足
中等50-69可接受,但存在明显不足;建议进行审查
存在风险30-49存在重大薄弱环节;采用时应保持审慎
危急1-29问题严重(项目被弃置、仅有单一维护者、缺乏基本工程规范)
活力社区与采用可持续性与治理工程质量安全AI 就绪度

评分画像

每条轴代表一个类别。形状比平均值更重要——健康的对象会填满整个图形,而“一峰一谷”式画像意味着某一维度的优势正掩盖另一维度的风险。

所有权

Equinor组织
1,757 关注者751 个公开仓库始于 2010年12月

该仓库由组织支持——共同承担、可问责的托管责任,可延续于任何单一维护者之后。

软件包生态系统

注册表软件包版本月下载量版本数最近发布标签
PyPIfmu-tools1.32.1-3923 天前energysubsurfacereservoirscientificengineering

按类别列示的指标

活力

项目是否仍有生命——是否仍在编写代码,是否仍在发布版本?

94优秀 · 占总体的 22%
评分方式
36/36推送新近度 — 最近一次推送于 0 天前
26.3/36提交节奏 — 52 周中有 38 周有提交
18/18提交量 — 最近一年 118 次提交
10/10OpenSSF Scorecard:Maintained — 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
所用输入
commits_last_year118
human_commit_share0.69
days_since_last_push0
active_weeks_last_year38

发布纪律

100优秀
评分方式
27/27有发布版本 — 已发布 52 个发布版本
36/36发布时效 — 最近一次发布版本于 23 天前
27/27发布节奏 — 约每 29.4 天发布一次
0/10OpenSSF Scorecard:Signed-Releases — 无数据
所用输入
releases_count52
latest_release_tag1.32.1
releases_from_tags
days_since_latest_release23
mean_days_between_releases29.4
已排除计分(无数据或不适用):OpenSSF Scorecard:Signed-Releases。 其余权重已重新归一化。

社区与采用

项目是否拥有用户、下载量与关注度,并具备欢迎贡献者参与的配置?

55中等 · 占总体的 18%

流行度与采用

35存在风险
评分方式
17.5/60星标 — 13 个星标
10.7/25复刻 — 20 个复刻
6.5/15关注者 — 16 位关注者
所用输入
forks20
stars13
watchers16
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

社区健康

77良好
评分方式
22.5/22.5README
22.5/22.5许可证 — 可识别的许可证(LGPL-3.0)
18/18CONTRIBUTING 指南
0/13.5行为准则
0/7.2议题模板
6.3/6.3PR 模板
所用输入
has_readme
has_license
has_contributing
has_issue_template
has_code_of_conduct
has_pull_request_template

可持续性与治理

项目能否在其成员之外延续——巴士系数、响应能力、由谁支持,以及软件包的维护状况?

83良好 · 占总体的 24%
评分方式
36/54巴士系数 — 3 位贡献者贡献了半数提交
17.6/22.5提交分布 — 头号贡献者编写了 22% 的提交
13.5/13.5贡献者广度 — 19 位贡献者
6/10OpenSSF Scorecard:Contributors — project has 2 contributing companies or organizations -- score normalized to 6
所用输入
bus_factor3
contributors_sampled19
top_contributor_share0.216
评分方式
40/46.8议题解决 — 86% 的议题已关闭
33.3/38.3PR 接受 — 已裁定的 PR 中 280/322 已合并
15/15OpenSSF Scorecard:Code-Review — all changesets reviewed
所用输入
merged_prs280
open_issues22
closed_issues130
issue_closed_ratio0.855
closed_unmerged_prs42
评分方式
30/30所有权背书 — 组织持有
0/20已验证域名
23.3/25所有者影响力 — equinor 有 1,757 位关注者
25/25既往记录 — 751 个公开仓库,账户约 15 年
所用输入
followers1,757
owner_typeOrganization
is_verified
owner_loginequinor
public_repos751
account_age_days5,699
评分方式
25/25已发布且可解析 — pypi 上有 1 个软件包
35/35发布时效 — 最近一次发布于 23 天前
20/20版本历史 — 39 个已发布版本
20/20未被弃用 — 活跃,未被弃用或撤回
所用输入
packagesfmu-tools
ecosystemspypi
any_deprecated
min_days_since_publish23

工程质量

基础的工程与文档实践是否到位?

77良好 · 占总体的 20%

工程实践

68中等
评分方式
24/24CI 工作流 — 4 个工作流
24/24存在测试
0/16Linter 配置
0/9.6Pre-commit 钩子
0/6.4.editorconfig
20/20OpenSSF Scorecard:CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
所用输入
has_ci
has_tests
has_editorconfig
has_linter_config
has_precommit_config

文档

90优秀
评分方式
30/30README
25/25文档目录
15/15文档 / 主页站点 — https://equinor.github.io/fmu-tools/
10/10仓库描述
0/10主题标签
10/10Wiki
所用输入
topics
has_wiki
homepagehttps://equinor.github.io/fmu-tools/
has_readme
has_docs_dir
has_description

安全

可见的安全与供应链实践是否稳固,且不存在未解决的高风险司法辖区暴露?

89优秀 · 占总体的 16%

安全态势

86优秀
评分方式
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — 无数据
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
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5许可证 — license file detected
7.5/7.5Maintained — 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — 无数据
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
所用输入
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate8.6
已排除计分(无数据或不适用):branch_protection, signed_releases。 其余权重已重新归一化。
评分方式
35/35直接依赖不含已知公告 — 没有直接依赖携带已知公告
25/25间接依赖不含已知公告 — 没有间接依赖携带已知公告
0/40没有长期未处理的公告 — 没有公告带有发布日期
所用输入
sourceosv
advisories0
affected_packages0
assessed_packages50
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
已排除计分(无数据或不适用):没有长期未处理的公告。 其余权重已重新归一化。 比对的是 pypi:fmu-tools@1.32.1 的运行时依赖闭包——安装已发布的软件包时真正被拉取进来的内容——共 50 个软件包。 未对可达性进行分析。

AI 就绪度

该仓库在多大程度上具备与 AI 编码代理协同开发与维护的条件?这是一枚独立的实验性徽章——权重为 0.0,因此单独呈现,不影响总体健康评分。

46存在风险 · 占总体的 0%
评分方式
0/45代理指令 — 没有 CLAUDE.md / AGENTS.md / 编辑器规则
0/15机器可读文档(llms.txt)
17/40可读的提交历史 — 69 次人类提交中有 22 次说明了意图(结构化标题或解释性正文)
所用输入
has_llms_txt
legible_history_share0.319
agent_instruction_files
agent_instruction_max_bytes
评分方式
0/18一条命令的引导启动
22/22自动化测试
0/11Lint / 格式化配置
11/11静态类型检查 — mypy.ini
10/10可复现环境 — lockfile
0/10已体现的代理实践 — 最近 100 次提交中没有代理编写的提交
8/8自动化维护 — 最近 100 次提交中有 31 次为自动依赖更新
4/10OpenSSF Scorecard:Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
所用输入
has_nix
has_tests
lockfilesuv.lock
has_dockerfile
typed_language
bootstrap_files
has_devcontainer
has_linter_config
typecheck_configsmypy.ini
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.31
评分方式
27/45可类型检查的代码 — Python,已配置类型检查(mypy.ini)
54.3/55可控的文件大小 — 采样的 84 个源文件中有 1 个超过 60KB
所用输入
primary_languagePython
largest_source_bytes74,386
source_files_sampled84
oversized_source_files1

关键数据

13GitHub 星标
19贡献者
118最近 12 个月提交数
0距最近推送天数
52发布版本数
3巴士系数(bus factor)
22开放议题
PyPI软件包生态系统数

数据采集警告

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

更多细节

Star 与 Fork 历史 0 ★ / 20 ⇿
0Star
20Fork
46发布

每颗 star 和每个 fork 的添加时间,来自 GitHub 并按天汇总。累计增长位于其构成来源——每日新增——的正上方,二者可相互对照:稳定的自然增长与短暂的突增形态截然不同。当这一差别可被衡量时,它会作为增长真实性予以报告。

0481216202022020-062023-062026-06
主版本 0次版本 30修订 14

每个点涵盖 6 天。

OpenSSF Scorecard 8.6 / 10
8.6综合

来自开源项目 OpenSSF Scorecard 的独立、工具无关的安全评估。每项检查奖励的是安全实践本身,而非特定供应商的工具。Scorecard 无法判定的检查项标记为 不适用,并从安全评分中剔除(绝不按零分计)。Scorecard v5.5.0 · 2026-07-25 12:19 UTC

10Binary-Artifactsno binaries found in the repo
不适用Branch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
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
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
不适用Signed-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
直接依赖 10
注册表软件包版本约束清单文件
PyPIdisjoint-setpyproject.toml
PyPIjsonschema>=3.2.0pyproject.toml
PyPInumpy>=1.23.5pyproject.toml
PyPIopenpyxl>=2.6pyproject.toml
PyPIpandas>=0.21pyproject.toml
PyPIpydanticpyproject.toml
PyPIpyyaml>=5.3pyproject.toml
PyPIscipy>=1.2pyproject.toml
PyPIxlrd>=1.2pyproject.toml
PyPIxtgeo>=4.23.0pyproject.toml
全部依赖 103

来自 GitHub 依赖图的完整解析依赖集合:12 个直接依赖与 91 个间接(传递)软件包。仓库提交锁文件时,传递闭包才是完整的。

注册表软件包版本关系
PyPIdisjoint-set0.9.0直接
PyPIjsonschema4.26.0直接
PyPInumpy2.4.6直接
PyPInumpy2.5.0直接
PyPIopenpyxl3.1.5直接
PyPIpandas3.0.3直接
PyPIpydantic2.13.4直接
PyPIpyyaml6.0.3直接
PyPIscipy1.17.1直接
PyPIscipy1.18.0直接
PyPIxlrd2.0.2直接
PyPIxtgeo4.24.5直接
PyPIalabaster1.0.0间接
PyPIannotated-doc0.0.4间接
PyPIannotated-types0.7.0间接
PyPIast-serialize0.5.0间接
PyPIattrs26.1.0间接
PyPIautoapi2.0.1间接
PyPIbabel2.18.0间接
PyPIcertifi2026.6.17间接
PyPIcharset-normalizer3.4.7间接
PyPIcolorama0.4.6间接
PyPIcontourpy1.3.3间接
PyPIcoverage7.14.3间接
PyPIcycler0.12.1间接
PyPIdeprecation2.1.0间接
PyPIdocutils0.21.2间接
PyPIemcee3.1.6间接
PyPIet-xmlfile2.0.0间接
PyPIexecnet2.1.2间接
PyPIfonttools4.63.0间接
PyPIgstools1.7.0间接
PyPIgstools-cython1.2.0间接
PyPIh5py3.16.0间接
PyPIhankel1.2.2间接
PyPIhdf5plugin6.0.0间接
PyPIidna3.18间接
PyPIimagesize2.0.0间接
PyPIiniconfig2.3.0间接
PyPIjinja23.1.6间接
PyPIjoblib1.5.3间接
PyPIjsonschema-specifications2025.9.1间接
PyPIkiwisolver1.5.0间接
PyPIlibrt0.11.0间接
PyPImarkdown-it-py4.2.0间接
PyPImarkupsafe3.0.3间接
PyPImatplotlib3.11.0间接
PyPImdit-py-plugins0.6.1间接
PyPImdurl0.1.2间接
PyPImeshio5.3.5间接
PyPImpmath1.4.1间接
PyPImypy2.1.0间接
PyPImypy-extensions1.1.0间接
PyPImyst-parser5.1.0间接
PyPIpackaging26.2间接
PyPIpathspec1.1.1间接
PyPIpillow12.3.0间接
PyPIpluggy1.6.0间接
PyPIpyarrow24.0.0间接
PyPIpydantic-core2.46.4间接
PyPIpyevtk1.7.0间接
PyPIpygments2.20.0间接
PyPIpyparsing3.3.2间接
PyPIpytest9.1.1间接
PyPIpytest-cov7.1.0间接
PyPIpytest-mock3.15.1间接
PyPIpytest-runner6.0.1间接
PyPIpytest-snapshot0.9.0间接
PyPIpytest-xdist3.8.0间接
PyPIpython-dateutil2.9.0.post0间接
PyPIreferencing0.37.0间接
PyPIrequests2.34.2间接
PyPIresfo5.0.1间接
PyPIrich15.0.0间接
PyPIroffio1.1.1间接
PyPIrpds-py2026.5.1间接
PyPIrstcheck6.2.5间接
PyPIrstcheck-core1.3.0间接
PyPIruff0.15.20间接
PyPIsegyio1.9.14间接
PyPIshapely2.1.2间接
PyPIshellingham1.5.4间接
PyPIsix1.17.0间接
PyPIsnowballstemmer3.1.1间接
PyPIsphinx8.1.3间接
PyPIsphinx-argparse0.6.0间接
PyPIsphinx-autodoc-typehints2.3.0间接
PyPIsphinx-rtd-theme3.1.0间接
PyPIsphinxcontrib-applehelp2.0.0间接
PyPIsphinxcontrib-devhelp2.0.0间接
PyPIsphinxcontrib-htmlhelp2.1.0间接
PyPIsphinxcontrib-jquery4.1间接
PyPIsphinxcontrib-jsmath1.0.1间接
PyPIsphinxcontrib-qthelp2.0.0间接
PyPIsphinxcontrib-serializinghtml2.0.0间接
PyPItomli2.4.1间接
PyPItyper0.26.7间接
PyPItypes-pyyaml6.0.12.20260518间接
PyPItyping-extensions4.15.0间接
PyPItyping-inspection0.4.2间接
PyPItzdata2026.2间接
PyPIurllib32.7.0间接
PyPIxtgeoviz0.3.1间接
依赖安全公告 0

安装 pypi:fmu-tools@1.32.1 会引入 50 个包(直接与传递):其中 0 个存在已知公告,0 个为直接依赖。

没有已知公告影响已评估的依赖。

公告表示依赖图中记录的版本落入某条公告的受影响范围。可达性未经分析,且依赖图包含开发与测试的版本固定——某项发现可能只涉及工具链而非交付的软件。

原始 JSON 报告 机器可读
{
  "data": {
    "repo": {
      "topics": [],
      "is_fork": false,
      "size_kb": 58074,
      "has_wiki": true,
      "homepage": "https://equinor.github.io/fmu-tools/",
      "languages": {
        "Shell": 946,
        "Python": 717622,
        "OpenEdge ABL": 368221
      },
      "pushed_at": "2026-07-25T00:24:46Z",
      "created_at": "2020-03-05T13:37:29Z",
      "owner_type": "Organization",
      "updated_at": "2026-07-23T08:49:17Z",
      "description": "fmu-tools is a library containing tools for pre- and post-processing in a Fast Model Update (FMU) context",
      "is_archived": false,
      "is_disabled": false,
      "license_spdx": "LGPL-3.0",
      "default_branch": "main",
      "license_spdx_raw": "LGPL-3.0",
      "primary_language": "Python",
      "significant_languages": [
        "Python",
        "OpenEdge ABL"
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    },
    "owner": {
      "blog": "https://equinor.com/",
      "name": "Equinor",
      "type": "Organization",
      "login": "equinor",
      "company": null,
      "location": "Norway",
      "followers": 1757,
      "avatar_url": "https://avatars.githubusercontent.com/u/525862?v=4",
      "created_at": "2010-12-16T14:09:24Z",
      "is_verified": null,
      "public_repos": 751,
      "account_age_days": 5699
    },
    "license": {
      "state": "standard",
      "spdx_id": "LGPL-3.0",
      "raw_spdx": "LGPL-3.0",
      "file_present": true,
      "scorecard_found": true,
      "profile_has_license": true
    },
    "activity": {
      "releases": [
        {
          "tag": "1.32.1",
          "kind": "patch",
          "published_at": "2026-07-02T07:18:48Z"
        },
        {
          "tag": "1.32.0",
          "kind": "minor",
          "published_at": "2026-06-30T06:52:08Z"
        },
        {
          "tag": "1.31.0",
          "kind": "minor",
          "published_at": "2026-06-03T10:13:49Z"
        },
        {
          "tag": "1.30.0",
          "kind": "minor",
          "published_at": "2026-04-28T15:26:16Z"
        },
        {
          "tag": "1.29.0",
          "kind": "minor",
          "published_at": "2026-04-07T10:23:02Z"
        },
        {
          "tag": "1.28.0",
          "kind": "minor",
          "published_at": "2026-03-12T09:58:03Z"
        },
        {
          "tag": "1.27.0",
          "kind": "minor",
          "published_at": "2026-03-03T07:24:43Z"
        },
        {
          "tag": "1.26.0",
          "kind": "minor",
          "published_at": "2026-01-07T10:19:01Z"
        },
        {
          "tag": "1.25.1",
          "kind": "patch",
          "published_at": "2025-11-11T11:29:10Z"
        },
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                "key": "owner_reach",
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        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
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  ],
  "report_type": "repository",
  "generated_at": "2026-07-25T12:19:44.077797Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/e/equinor/fmu-tools.svg",
  "full_name": "equinor/fmu-tools",
  "license_state": "standard",
  "license_spdx": "LGPL-3.0"
}

评分是信号,而非担保。 评分反映的是 GitHub 上公开可见的实践——不是代码审计,也不是安全保证。

缺失数据将被剔除并重新归一化权重,绝不按零分计。方法论已版本化并公开:指标 v1.13.0、模式 v0.27.0—— 完整方法论 · 指标知识库.

单项结果在整体记录中的位置: 汇总统计PyPI.