google/pyglove erreicht einen Gesundheitsindex von 68 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Community & Adoption (74/100) ab, am schwächsten bei AI Readiness (30/100). Zuletzt vor 4 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
68
gesamt / 100
Mittel
Software-Gesundheitsindex
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
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.
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Release-Aktualität — letztes Release vor 374 Tagen
19.8/27
Release-Rhythmus — ein Release etwa alle 112,1 Tage
0/10
OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count
10
latest_release_tag
v0.4.5
releases_from_tags
nein
days_since_latest_release
374
mean_days_between_releases
112,1
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, packaging, signed_releases. Die verbleibenden Gewichte wurden renormalisiert.
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
2
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:pyglove@0.4.5 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 2 Paketen. Erreichbarkeit wird nicht analysiert.
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.
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Weitere Details
Stern- und Fork-Verlauf 0 ★ / 39 ⇿
0Sterne
39Forks
10Releases
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 0Minor 3Patch 7
Jeder Punkt umfasst 4 Tage.
OpenSSF Scorecard 5.9 / 10
5.9Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).Scorecard v5.5.0 · 2026-07-25 08:48 UTC
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 10 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
Registry
Paket
Version
Beziehung
PyPI
absl-py
—
indirekt
PyPI
autodocsumm
—
indirekt
PyPI
docstring-parser
—
indirekt
PyPI
fsspec
—
indirekt
PyPI
furo
—
indirekt
PyPI
jinja2
—
indirekt
PyPI
myst-nb
—
indirekt
PyPI
sphinx-autodoc-typehints
—
indirekt
PyPI
sphinx-copybutton
—
indirekt
PyPI
termcolor
—
indirekt
Abhängigkeits-Advisories 0
Die Installation von pypi:pyglove@0.4.5 zieht 2 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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"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: 821712306",
"is_bot": false,
"headline": "`pg.Dict`: Evaluate inferential value for standard dict operations.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-10-20T17:45:58Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "7802e4f1d93693718637894daf097e615fd6d3d9",
"body": "PiperOrigin-RevId: 821361894",
"is_bot": false,
"headline": "No public description",
"author_name": "PyGlove Authors",
"author_login": null,
"committed_at": "2025-10-19T18:20:58Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "650ad917ddc08a43b7247eb821903fd2ef65e3c3",
"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",
"is_bot": false,
"headline": "`pg.Dict`: Evaluate inferential value for standard dict operations.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-10-19T16:33:23Z",
"body_truncated": true,
"is_coding_agent": false
},
{
"oid": "ea13a507bbfbdf70c6beb0e2a1900df8145d7365",
"body": "PiperOrigin-RevId: 820474675",
"is_bot": false,
"headline": "`with_contextual_override` to support coroutines.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"committed_at": "2025-10-17T01:43:10Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "779e9b1cf2fa8a779693d51cc12d62fe8a51c22c",
"body": "- `pg.ValueSpec.to_json_schema()` to support default value.\n- Introduce `pg.ValueSpec.from_json_schema()` / `pg.Schema.from_json_schema()` to allow creation of ValueSpec from JSON schema.\n\nPiperOrigin-RevId: 820048200",
"is_bot": false,
"headline": "`pg.typing`: Enhancements to JSON schema conversion.",
"author_name": "Daiyi Peng",
"author_login": "daiyip",
"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
},
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Verwandte Einträge
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