google/pyglove holds a health index of 68 out of 100, placing it in the Moderate band. It scores highest on Community & Adoption (74/100) and lowest on AI Readiness (30/100). It was last updated 4 days ago. A single contributor accounts for most of its recent work.
68
overall / 100
Moderate
Software health index
Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.
68
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe problems (abandoned, single-maintainer, no hygiene)
Score profile
Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.
Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25
Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40
No advisories left outstanding — no advisory carries a publication date
Inputs used
source
osv
advisories
0
affected_packages
0
assessed_packages
2
unassessed_packages
0
affected_by_severity
none
direct_affected_packages
0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:pyglove@0.4.5 runtime dependency closure — what installing the published package pulls in — 2 packages. Reachability is not analyzed.
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.
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
More detail
Star and fork history 0 ★ / 39 ⇿
0Stars
39Forks
10Releases
When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.
Major 0Minor 3Patch 7
Each point covers 4 days.
OpenSSF Scorecard 5.9 / 10
5.9aggregate
Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-07-25 08:48 UTC
Full resolved dependency set from the GitHub dependency graph: 0 direct and 10 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
Registry
Package
Version
Relation
PyPI
absl-py
—
indirect
PyPI
autodocsumm
—
indirect
PyPI
docstring-parser
—
indirect
PyPI
fsspec
—
indirect
PyPI
furo
—
indirect
PyPI
jinja2
—
indirect
PyPI
myst-nb
—
indirect
PyPI
sphinx-autodoc-typehints
—
indirect
PyPI
sphinx-copybutton
—
indirect
PyPI
termcolor
—
indirect
Dependency advisories 0
Installing pypi:pyglove@0.4.5 pulls in 2 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.
No known advisories affect the assessed dependencies.
An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.
Raw JSON report machine-readable
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"body": "With this change, `Dict.get()`, `Dict.values()`, `Dict.items()` will evaluate element value if the element is `pg.Inferential`. This also aligns the semantics with `List.__getitem__()` `List.__getattr__` and `List.__iter__()`.\n\nExample:\n```\nclass A(pg.Object):\n pass\n\nd = pg.Dict(x=pg.Ref(A())\nassert\n[…]\n # Instead of `pg.Ref`\nassert isinstance(list(d.values())[0], A) # Instead of `pg.Ref`\nassert isinstance(list(d.items())[0][1], A) # Instead of `pg.Ref`\n```\nPiperOrigin-RevId: 821342698",
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"author_name": "Daiyi Peng",
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"committed_at": "2025-10-16T04:29:39Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "e7c8e81c40a225a8c4f0541acb3a9f936d769d9c",
"body": "* Counters are metrics that track the number of times an event occurs. It's\nmonotonically increasing over time.\n\n* Scalars are metrics that track a single value at a given time, for example,\navailable memory size. It does not accumulate over time like counters.\n\n* Distributions are metrics that track the distribution of a numerical value.\nFor example, the latency of an operation.\n\nPiperOrigin-RevId: 816976497",
"is_bot": false,
"headline": "Formalize monitoring metrics: Counter, Scalar and Distributions.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-10-09T03:14:09Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "4a1e8b45a3982a727f9abfbf87a2ef5882ccb055",
"body": "…duration`.\n\nPiperOrigin-RevId: 814384615",
"is_bot": false,
"headline": "[pg.monitoring] Handle empty error with `pg.monitoring.Scalar.record_…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-10-02T21:22:12Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "ef07d6af69fcbeb6b983a5a458375326c0344ead",
"body": "PiperOrigin-RevId: 814368980",
"is_bot": false,
"headline": "[pg.monitoring] Scalar.record_duration to optionally track error.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-10-02T20:45:17Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "46304868d813ddcce575163a58d9579844f340da",
"body": "PiperOrigin-RevId: 814064958",
"is_bot": false,
"headline": "Add `pg.monitoring.Scalar.record_duration()`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-10-02T05:02:07Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "e9edd54ca5d16218ec264e9636e86136d2e0afc4",
"body": "…() by providing an empty dict as a fallback.\n\nPiperOrigin-RevId: 813104024",
"is_bot": false,
"headline": "This change ensures that hyper_dict is not None before calling .items…",
"author_name": "PyGlove Authors",
"author_login": null,
"committed_at": "2025-09-30T06:11:34Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "5a187bafd52d2cc0843679f977633c2826a92991",
"body": "…ecution.\n\n```python\ncollection = pg.monitoring.metric_collection('/myapp')\nfoo = collection.get_counter('foo', 'description for foo')\nassert foo.increment() == 1\n\nbar = collection.get_scalar('bar', 'description for bar', parameters={'module': str})\nbar.record(10, module='module1')\nassert bar.distribution(module='module1').mean == 10.0\n```\nPiperOrigin-RevId: 811946930",
"is_bot": false,
"headline": "Introduce `pg.monitoring`: MetricCollection for monitoring program ex…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-09-26T21:01:11Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "a4c17fe82eeee8bb84fa4d37484a0c51292f4396",
"body": "This allows user to redirect loggers to custom IOs.\n\nPiperOrigin-RevId: 811115465",
"is_bot": false,
"headline": "Introduce `pg.logging.use_stream`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-09-25T01:18:17Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "c6819c42469f36e31eab2ff09d3f18c3dd33c8d1",
"body": "PiperOrigin-RevId: 805921677",
"is_bot": false,
"headline": "Extract `pg.match_error` from `pg.catch_errors`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-09-11T18:34:36Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "c080ff49620cd427c7230fa5e9bdd24cb9582e55",
"body": "PiperOrigin-RevId: 786880724",
"is_bot": false,
"headline": "`JsonConvertible.add_module_alias` to support multiple aliases",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-07-24T23:47:52Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "5f38cad20384fdcc6eb848284e82e6934e2f1aaa",
"body": "PiperOrigin-RevId: 783503779",
"is_bot": false,
"headline": "Merge pull request #372 from google:daiyip-patch-1",
"author_name": "pyglove authors",
"author_login": null,
"committed_at": "2025-07-15T22:58:38Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "0f4c7f73dd41c9c814b94f0c374db1a30efc65e5",
"body": null,
"is_bot": false,
"headline": "Bump PyGlove dev version to 0.5.0",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-07-15T19:11:10Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "d655ea0f60c22add8a43fe3024ce1801bdc27e78",
"body": "PiperOrigin-RevId: 782393896",
"is_bot": false,
"headline": "Python 3.13 Support.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-07-12T20:43:34Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "4809eb5314420d1969c7528b43ac80a304fa9c92",
"body": null,
"is_bot": false,
"headline": "Python 3.13 support",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-07-12T17:33:49Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "976ecbfb2800d7119ef835feec8c37a00ac05419",
"body": "…ues=True`.\n\n`np.ndarray == <number>` will return a `np.ndarray` which does not evaluate to a bool value. By putting `field.default_value` on the left, the `__eq__` method of `field.default_value` will take higher priority than `np.ndarray.__eq__`.\n\nPiperOrigin-RevId: 761832755",
"is_bot": false,
"headline": "Make `pg.to_json` compatible with `np.ndarray` with `hide_default_val…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-05-22T07:08:59Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "e55ea669df8dce6b2fdb1f92494da1ca080b7445",
"body": "PiperOrigin-RevId: 759654174",
"is_bot": false,
"headline": "Expose `pg.ErrorInfo`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-05-16T16:57:29Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "28c9b51d35d4390ae68e0487d6428e7754d32272",
"body": "Previous pg.utils.ErrorInfo is not HTML friendly. To fix this issue, we introduce\nsymbolic ErrorInfo class. Besides HTML support, it inherits all the benefits of PyGlove objects, e.g. automatic serialization support, flexible formatting, symbolic traversal etc.\n\nThis CL also fix pytype errors for python files under docs.\n\nPiperOrigin-RevId: 759385485",
"is_bot": false,
"headline": "Introduce symbolic ErrorInfo.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-05-16T01:23:40Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "f7390c120b0c173ee73c97c239c7668def226723",
"body": "```python\nclass Foo(metadata=abc.ABCMeta):\n @property\n @abc.abstractmethod\n def bar(self):\n pass\n\nclass Bar(pg.Object, Foo):\n # `bar` will introduce property `bar` that overrides the abstract `Foo.bar`.\n bar: int\n\nassert Bar(1).bar == 1\n```\n\nPiperOrigin-RevId: 759224544",
"is_bot": false,
"headline": "Allow symbolic attribute to override abstract properties.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-05-15T18:18:01Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "9018f2589b4ef861a02100bb03b67e07187e5509",
"body": "```python\nclass A(pg.Object):\n x: int\n y: str\n\n# Schema to JSON schema.\nA.__schema__.to_json_schema()\n\n# ValueSpec to JSON schema.\nA.__schema__['x'].value.to_json_schema()\n```\n\nPiperOrigin-RevId: 754047380",
"is_bot": false,
"headline": "Add PyGlove schema to JSON Schema conversion.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-05-02T17:16:06Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "d1f94c9120ce50db9180f618bfbaf44a6c72a86e",
"body": "To make composition of child HTML elements easier, we make\n1. Html.element to support nestable list of child elements.\n2. LabelGroup to support nestable list of Labels that contains None.\n3. TabControl to support nestable list of Tabs that contains None. `select` supports name and name list.\n\nPiperOrigin-RevId: 752953428",
"is_bot": false,
"headline": "Enhancement to PyGlove HTML controls.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-04-30T01:03:02Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "cb9964e8651f363a93273dde0d1a1769ddca9f58",
"body": "Allow passing `is_noneable` and `use_none_as_default` arguments. We also unset the default value for Union converted from annotation without default value.\n\nPiperOrigin-RevId: 752777826",
"is_bot": false,
"headline": "Enhancing `pg.typing.ValueSpec.noneable()`",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-04-29T16:59:07Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "4b9c25fb57b76a1669cec783dca343e77fb37f05",
"body": "PiperOrigin-RevId: 752414465",
"is_bot": false,
"headline": "Automated Code Change",
"author_name": "Hana Joo",
"author_login": "h-joo",
"committed_at": "2025-04-28T19:55:38Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "9c0086afd0220248732973ed485749f3a70fde46",
"body": "…pers.\n\nPiperOrigin-RevId: 751851424",
"is_bot": false,
"headline": "Add `pg.logging.register_frame_to_skip` to better support logger wrap…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-04-26T23:04:13Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "5f0aa14a8fa3e83d09cf605687f51150bea87dba",
"body": "Allow passing `is_noneable` and `use_none_as_default` arguments. We also unset the default value for Union converted from annotation without default value.\n\nPiperOrigin-RevId: 750812311",
"is_bot": false,
"headline": "Enhancing `pg.typing.ValueSpec.noneable()`",
"author_name": "Joe Richey",
"author_login": "josephlr",
"committed_at": "2025-04-24T02:31:01Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "9209f971c82736d5e569a933a4410dc8a4bbc121",
"body": "Allow passing `is_noneable` and `use_none_as_default` arguments. We also unset the default value for Union converted from annotation without default value.\n\nPiperOrigin-RevId: 750779137",
"is_bot": false,
"headline": "Enhancing `pg.typing.ValueSpec.noneable()`",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-04-24T00:24:21Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "29591ea564770b0080fb12aae15b6c4c60571fb9",
"body": "Also `pg.print` now supports variable positional arguments.\n\nPiperOrigin-RevId: 750352628",
"is_bot": false,
"headline": "`pg.format` to handle recursive structures.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-04-22T22:44:05Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "b3ad22583c65e630a5dfb8ff524789e91e19ced4",
"body": "This allows exceptions like SystemExit to be caught from bad code.\n\nPiperOrigin-RevId: 749911071",
"is_bot": false,
"headline": "Catch BaseException for pg.coding.evaluate.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-04-21T21:02:45Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "86aad872fc60c8c16ee64e8b8e414e0e6c68b3f2",
"body": "PiperOrigin-RevId: 740822511",
"is_bot": false,
"headline": "Internal change.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-03-26T17:37:04Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "fd75005974e56fd64e446633832afc949e7bef90",
"body": "PiperOrigin-RevId: 739010067",
"is_bot": false,
"headline": "Set the default file/sequence permissions to world readable.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-03-21T01:39:09Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "2e8981da77f89b8743659998b0a7336fa54d91f8",
"body": "… default.\n\nPiperOrigin-RevId: 736539531",
"is_bot": false,
"headline": "Set the default value of arg `exist_ok` for `pg.io.mkdirs` to True by…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-03-13T16:50:06Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "65c7e520cb8aa0ca5c8bf7d7f1cc9ab72123d5b2",
"body": "PiperOrigin-RevId: 723558958",
"is_bot": false,
"headline": "Improve annotation inference to be compatible with module reloading.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-02-05T18:17:58Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "97d6446a2dea91c67f5f39335e0509573ccb8cdd",
"body": "With this CL, PyGlove is compatible with `__future__.annotations`.\nFor example:\n\n```python\nfrom __future__ import annotations\n\nclass A(pg.Object):\n child: A | None\n```\n\nPiperOrigin-RevId: 723114026",
"is_bot": false,
"headline": "pg.typing to support `__future__.annotations`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-02-04T17:20:26Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "50d8a38b0328222c2570c95c93caf934b7354966",
"body": "Protocol is a special base class, which cannot be tested via `issubclass` and `isinstance` (without @typing.runtime_checkable). Before this change, PyGlove does not treat Protocol subclasses correctly for typing. This CL fixes this by:\n1) pg.typing.is_subclass(cls, protocol_cls) always returns True \n[…]\n\nclass Foo(Protocol):\n def __call__(self) -> int:\n ...\n\nclass A(pg.Object):\n foo: Foo\n\nclass Bar:\n def __call__(self) -> int:\n return 0\n\nA(Bar()) # Will work.\n```\n\nPiperOrigin-RevId: 722370929",
"is_bot": false,
"headline": "`pg.typing` to support Protocol subclassses.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-02-02T17:32:25Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "c8c5d1ca9e5a750ed828b07c0668bc56da30dd94",
"body": "… at the last expression.\n\nPiperOrigin-RevId: 721812914",
"is_bot": false,
"headline": "`pg.coding.evaluate`: Fix raise when attribute assignment takes place…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-31T18:09:20Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "ddeb5932ba0c26cdc58e76f99800726bf644f974",
"body": "PiperOrigin-RevId: 718981795",
"is_bot": false,
"headline": "Fix stuck multiprocessing sandbox on large STDOUT.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-23T21:00:47Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "d31a11938dabb9f518cf41986e9d3e469b6161f7",
"body": "PiperOrigin-RevId: 716236530",
"is_bot": false,
"headline": "cleanup of deprecated test methods",
"author_name": "PyGlove Authors",
"author_login": null,
"committed_at": "2025-01-16T15:59:01Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "063caf94dd80587954d9206126e382760ace7d34",
"body": "…narios.\n\n```\nclass A(pg.Object):\n x: str\n\n def foo(self):\n return 1\n\nclass B(A):\n pass\n\nclass C(pg.Object):\n x: Literal['a', 'b']\n\n def foo(self):\n return 2\n\nclass D(B, C):\n pass\n\n# D.foo will be C.foo.\n# Like-wise, D.x shall be Literal['a', 'b'] as B doesn't override A.x.\n# Before this CL D.x is str (B takes precedence of C in multi-inheritance order).\n```\n\nPiperOrigin-RevId: 716220803",
"is_bot": false,
"headline": "Fix symbolic attribute inheritance behavior for multi-inheritance sce…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-16T15:03:50Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "ba91fc783b079bc8fb783256a00d6c3bf0a7c670",
"body": "Contextual objects are objects whose attribute values could be manipulated by context manager `pg.contextual_override` and/or accessed from parent objects via `pg.contextual_attribute` placeholder.\n\nExample:\n\n```\nclass A(pg.ContextualObject):\n x: int\n y: Any = pg.contextual_attribute()\n\na = A(1)\nprint(a.x) # 1\nwith pg.contextual_override(x=2):\n print(a.x) # 2\nprint(a.x) #1\n\npg.Dict(y=3, a=a)\nprint(a.y) # 3. (Accessing parent's y)\n```\n\nPiperOrigin-RevId: 716013142",
"is_bot": false,
"headline": "Introduce `pg.ContextualObject`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-16T01:35:43Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "264cfa133d400aeb3b6df548f8df6b317d0565d8",
"body": "With this change, the following code is valid, and the reported elapsed time for the 'task' status will be aggregated accordingly.\n\n```\n with pg.timeit() as t:\n with pg.timeit('task'):\n time.sleep(1)\n time.sleep(1)\n with pg.timeit('task'):\n time.sleep(1)\n print(t.status()['task'].elapse)\n # Will print a number around 2.\n```\n\nPiperOrigin-RevId: 715540752",
"is_bot": false,
"headline": "`pg.time` now supports aggregating sub-timers with the same name.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-14T22:53:02Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "20cf7607bb2bdb1edc8c51a039d3461a09ca7c8e",
"body": "PiperOrigin-RevId: 715083241",
"is_bot": false,
"headline": "Expose `lf.coding.permission` and `lf.coding.maybe_sandbox_call`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-13T21:16:04Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "faca119a9c80361e8bbe4c0d91d23ddd4a3f8572",
"body": "PiperOrigin-RevId: 713385689",
"is_bot": false,
"headline": "Expose `pg.colored` and `pg.decolor` from the root module.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-08T20:52:21Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "23ca0c221051622a9f95d2c95e5988c8e2443473",
"body": "…ontrol.\n\nPiperOrigin-RevId: 713290439",
"is_bot": false,
"headline": "`pg.coding`: Add support for Python code evaluation with permission c…",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-08T15:52:22Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "1125d6dc869ac64820954bdc0bd98d81ca1b5f4b",
"body": "PiperOrigin-RevId: 713009923",
"is_bot": false,
"headline": "Add `pg.utils.text_color` submodule.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-07T20:50:46Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "f3f06ae0b764419843cbd2e49db7ca2db0eabac0",
"body": "Currently this sub-module has been expanded with utilities beyond dealing with objects. This rename allows better organization of code.\n\n`pg.object_utils` is kept as an alias to `pg.utils` for backward-compatibility.\n\nPiperOrigin-RevId: 712329689",
"is_bot": false,
"headline": "Rename `pg.object_utils` sub-module to `pg.utils`.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-01-06T00:00:48Z",
"body_truncated": false,
"is_coding_agent": false
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{
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"note": null,
"notes": [],
"value": 68,
"inputs": {
"has_ci": true,
"has_tests": true,
"has_editorconfig": false,
"has_linter_config": false,
"has_precommit_config": false
},
"components": [
{
"key": "ci_workflows",
"name": "CI workflows",
"detail": "4 workflow(s)",
"points": 24,
"status": "met",
"details": [
{
"code": "ci_workflows",
"params": {
"count": 4
}
}
],
"max_points": 24
},
{
"key": "tests_present",
"name": "Tests present",
"detail": null,
"points": 24,
"status": "met",
"details": [],
"max_points": 24
},
{
"key": "linter_config",
"name": "Linter config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 16
},
{
"key": "pre_commit_hooks",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 9.6
},
{
"key": "editorconfig",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 6.4
},
{
"key": "openssf_scorecard_ci_tests",
"name": "OpenSSF Scorecard: CI-Tests",
"detail": "20 out of 20 merged PRs checked by a CI test -- score normalized to 10",
"points": 20,
"status": "met",
"details": [],
"max_points": 20
}
]
},
{
"key": "documentation",
"band": "good",
"name": "Documentation",
"note": null,
"notes": [],
"value": 75,
"inputs": {
"topics": [
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"evolution",
"machine-learning",
"meta-learning",
"meta-programming",
"symbolic-programming",
"manipulation",
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"has_wiki": false,
"homepage": null,
"has_readme": true,
"has_docs_dir": true,
"has_description": true
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"components": [
{
"key": "readme",
"name": "README",
"detail": null,
"points": 30,
"status": "met",
"details": [],
"max_points": 30
},
{
"key": "documentation_directory",
"name": "Documentation directory",
"detail": null,
"points": 25,
"status": "met",
"details": [],
"max_points": 25
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{
"key": "documentation_homepage_site",
"name": "Documentation / homepage site",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "repository_description",
"name": "Repository description",
"detail": null,
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "topics",
"name": "Topics",
"detail": "8 topics",
"points": 10,
"status": "met",
"details": [
{
"code": "topics_count",
"params": {
"count": 8
}
}
],
"max_points": 10
},
{
"key": "wiki",
"name": "Wiki",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
}
],
"description": "Are baseline engineering and documentation practices in place?"
},
{
"key": "security",
"band": "moderate",
"name": "Security",
"value": 67,
"weight": 0.16,
"metrics": [
{
"key": "security_posture",
"band": "moderate",
"name": "Security posture",
"note": "Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"branch_protection",
"packaging",
"signed_releases"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 59,
"inputs": {
"source": "openssf_scorecard",
"checks_evaluated": 15,
"scorecard_version": "v5.5.0",
"checks_inconclusive": 3,
"scorecard_aggregate": 5.9
},
"components": [
{
"key": "binary_artifacts",
"name": "Binary-Artifacts",
"detail": "no binaries found in the repo",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "branch_protection",
"name": "Branch-Protection",
"detail": "internal 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",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "ci_tests",
"name": "CI-Tests",
"detail": "20 out of 20 merged PRs checked by a CI test -- score normalized to 10",
"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
},
{
"key": "cii_best_practices",
"name": "CII-Best-Practices",
"detail": "no effort to earn an OpenSSF best practices badge detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 2.5
},
{
"key": "code_review",
"name": "Code-Review",
"detail": "Found 9/30 approved changesets -- score normalized to 3",
"points": 2.2,
"status": "partial",
"details": [],
"max_points": 7.5
},
{
"key": "contributors",
"name": "Contributors",
"detail": "project has 1 contributing companies or organizations -- score normalized to 3",
"points": 0.8,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "dangerous_workflow",
"name": "Dangerous-Workflow",
"detail": "no dangerous workflow patterns detected",
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "dependency_update_tool",
"name": "Dependency-Update-Tool",
"detail": "no update tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
"detail": "11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9",
"points": 6.8,
"status": "partial",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
"name": "Packaging",
"detail": "packaging workflow not detected",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "sast",
"name": "SAST",
"detail": "SAST tool is run on all commits",
"points": 5,
"status": "met",
"details": [],
"max_points": 5
},
{
"key": "security_policy",
"name": "Security-Policy",
"detail": "security policy file detected",
"points": 5,
"status": "met",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "0 existing vulnerabilities detected",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
"band": "excellent",
"name": "Dependency advisories",
"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:pyglove@0.4.5 runtime dependency closure — what installing the published package pulls in — 2 packages. Reachability is not analyzed.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
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]
}
},
{
"code": "weights_renormalized",
"params": {}
},
{
"code": "advisories_scope_published",
"params": {
"package": "pypi:pyglove@0.4.5",
"assessed": 2
}
},
{
"code": "advisories_reachability",
"params": {}
}
],
"value": 100,
"inputs": {
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"advisories": 0,
"affected_packages": 0,
"assessed_packages": 2,
"unassessed_packages": 0,
"affected_by_severity": "none",
"direct_affected_packages": 0
},
"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
{
"code": "no_direct_advisories",
"params": {}
}
],
"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": [
{
"code": "no_indirect_advisories",
"params": {}
}
],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
"name": "No advisories left outstanding",
"detail": "no advisory carries a publication date",
"points": 0,
"status": "excluded",
"details": [
{
"code": "advisories_no_publication_date",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "malicious_dependencies",
"band": "excellent",
"name": "Malicious dependencies",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"source": "osv",
"meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
"packages": [],
"red_flag": false,
"assessed_packages": 2,
"malicious_packages": 0,
"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
},
"components": [
{
"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": 6
},
"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": 30,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 24,
"inputs": {
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"legible_history_share": 0.46,
"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",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "46 of 100 human commits state their intent (structured subject or explanatory body)",
"points": 24.5,
"status": "partial",
"details": [
{
"code": "legible_history",
"params": {
"legible": 46,
"sampled": 100
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "critical",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 22,
"inputs": {
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"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": 0,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
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"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no agent-authored commits among the last 100",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_authored_commits",
"params": {
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no automated dependency updates observed",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"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": 53,
"inputs": {
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"largest_source_bytes": 131170,
"source_files_sampled": 241,
"oversized_source_files": 8
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "8/241 source files over 60KB",
"points": 53.2,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 241,
"oversized": 8
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "at_risk",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"examples",
"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": "examples, notebooks",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "examples, 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": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
],
"report_type": "repository",
"generated_at": "2026-07-25T08:48:34.421399Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/g/google/pyglove.svg",
"full_name": "google/pyglove",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}
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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.
Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v1.13.0, schema v0.27.0 — full methodology · metrics wiki.
