Публічний реєстрВідмінний
Звіт про здоров'я програмного забезпеченнясхема 0.27.0 · метрики 2.3.1 · 2026-08-01 12:48 UTC
vstorm-co / subagents-pydantic-ai
Subagent Delegation framework for Pydantic AI, enabling nested subagents that can spawn their own specialists on-the-fly, with smart sync/async/auto mode selection, runtime agent creation, and clean multi-agent architecture. Adds specialization, parallel execution, and task cancellation.
vstorm-co/subagents-pydantic-ai має індекс здоров’я 88 зі 100, що відповідає смузі «Відмінний». Найвищий показник — Engineering Quality (96/100), найнижчий — Security (53/100). Останнє оновлення — сьогодні. Більшість нещодавньої роботи виконує один учасник.
88
загалом / 100Індекс здоров'я програмного забезпечення
Метрики згруповано у зважені категорії на шкалі 1–100. Загальна оцінка починається як їхнє зважене середнє, відкаліброване за розподілом публічного реєстру, тож діапазони мають перцентильний зміст; коли публічні дані активують Політику юрисдикцій високого ризику, рейтинг коригується й отримує верхню межу 34 («У зоні ризику»).
88
Винятковий93-100Верхній щабель реєстру (≈ топ-5%); відповідає практично всім перевіреним критеріям
Відмінний80-92Сильний за всіма напрямами; незначні прогалини
Добрий65-79Здоровий; прогалини обмежені та керовані
Помірний50-64Прийнятний, але з помітними прогалинами; рекомендовано перевірку
Слабкий35-49Суттєві недоліки в кількох сферах
У зоні ризику20-34Суттєві слабкі місця; впровадження потребує обережності
Критичний1-19Серйозні проблеми (покинутий, єдиний мейнтейнер, без базової гігієни)
Профіль оцінок
Кожна вісь — окрема категорія. Форма важить більше, ніж середнє: здоровий об'єкт заповнює всю фігуру, тоді як профіль із піками та провалами означає, що сила в одному вимірі маскує ризик в іншому.
Зважений загальний бал 74 калібровано до 88 за шкалою опублікованого індексу (калібрування реєстру 2026-08-02).
Власність
VstormОрганізація
146 підписників34 публічні репозиторіїз бер. 2021 р.
За цим репозиторієм стоїть організація — спільна, підзвітна опіка, здатна пережити будь-якого окремого мейнтейнера.
Пакетні екосистеми
| Реєстр | Пакет | Версія | Завантажень / міс | Версії | Остання публікація | Теги |
|---|---|---|---|---|---|---|
| PyPI | subagents-pydantic-ai | 0.2.13 | 229 008 | 24 | 0 днів тому | agentsaimulti-agentpydanticpydantic-aisubagentstask-delegationtoolset |
Метрики за категоріями
Життєздатність
Чи живий проєкт — чи пишеться код і чи виходять релізи?
86
Активність розробки
77Добрий
Як обчислюється оцінка
| 36/36 | Свіжість push — останній push 0 дн. тому |
| 13.2/36 | Ритм комітів — 19/52 тижнів із комітами |
| 18/18 | Обсяг комітів — 135 комітів за останній рік |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10 |
Використані вхідні дані
| commits_last_year | 135 |
| human_commit_share | 0,94 |
| days_since_last_push | 0 |
| active_weeks_last_year | 19 |
Дисципліна релізів
100Винятковий
Як обчислюється оцінка
| 27/27 | Випускає релізи — опубліковано 24 релізів |
| 36/36 | Свіжість релізів — останній реліз 0 дн. тому |
| 27/27 | Ритм релізів — реліз кожні ~7,7 дн. |
| 0/10 | OpenSSF Scorecard: Signed-Releases — немає даних |
Використані вхідні дані
| releases_count | 24 |
| latest_release_tag | 0.2.13 |
| releases_from_tags | ні |
| days_since_latest_release | 0 |
| mean_days_between_releases | 7,7 |
Виключено з оцінювання (немає даних або не застосовно): OpenSSF Scorecard: Signed-Releases. Залишкові ваги перенормовано.
Спільнота та впровадження
Чи має проєкт користувачів, завантаження, увагу та влаштовані умови для контриб’юторів?
65
Популярність і впровадження
39Слабкий
Як обчислюється оцінка
| 28.4/60 | Зірки — 57 зірок |
| 10.3/25 | Форки — 18 форків |
| 0/15 | Спостерігачі — 2 спостерігачів |
Використані вхідні дані
| forks | 18 |
| stars | 57 |
| watchers | 2 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Здоров'я спільноти
77Добрий
Як обчислюється оцінка
| 22.5/22.5 | README |
| 22.5/22.5 | Ліцензія — визнана ліцензія (MIT) |
| 18/18 | Настанови CONTRIBUTING |
| 0/13.5 | Кодекс поведінки |
| 0/7.2 | Шаблон issue |
| 6.3/6.3 | Шаблон PR |
Використані вхідні дані
| has_readme | так |
| has_license | так |
| readme_badges | — |
| has_contributing | так |
| has_issue_template | ні |
| has_code_of_conduct | ні |
| readme_badge_services | — |
| has_pull_request_template | так |
Впровадження в екосистемі (завантаження)
89Відмінний
Як обчислюється оцінка
| 71.5/80 | Щомісячні завантаження — 229 008 завантажень/місяць у pypi |
| 0/20 | Залежні пакети в реєстрі — ця екосистема цього не повідомляє |
Використані вхідні дані
| packages | subagents-pydantic-ai |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 229 008 |
Виключено з оцінювання (немає даних або не застосовно): Залежні пакети в реєстрі. Залишкові ваги перенормовано.
Сталість та врядування
Чи переживе проєкт своїх людей — бас-фактор, реактивність, хто за ним стоїть і як супроводжуються пакети?
64
Стійкість мейнтейнерів (бас-фактор)
29У зоні ризику
Як обчислюється оцінка
| 9/54 | Бас-фактор — на 1 контриб’ютор(ів) припадає половина всіх комітів |
| 3.2/22.5 | Розподіл комітів — головний контриб’ютор — автор 86% комітів |
| 6.8/13.5 | Широта контриб’юторів — 5 контриб’юторів |
| 10/10 | OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations |
Використані вхідні дані
| bus_factor | 1 |
| contributors_sampled | 5 |
| top_contributor_share | 0,86 |
Реактивність на issue та PR
75Добрий
Як обчислюється оцінка
| 38.5/42 | Вирішення issue — закрито 92% issue |
| 23.9/30 | Прийняття PR — злито 39/49 вирішених PR |
| 0/13 | Newcomer PR acceptance — за 30 дн. не вирішено жодного PR від новачка |
| 3/15 | OpenSSF Scorecard: Code-Review — Found 2/7 approved changesets -- score normalized to 2 |
Використані вхідні дані
| merged_prs | 39 |
| open_issues | 1 |
| closed_issues | 11 |
| prs_merged_7d | — |
| prs_decided_7d | — |
| prs_merged_30d | — |
| prs_decided_30d | — |
| issue_closed_ratio | 0,917 |
| closed_unmerged_prs | 10 |
| first_time_authors_30d | — |
| first_time_prs_merged_30d | — |
| first_time_prs_decided_30d | — |
Виключено з оцінювання (немає даних або не застосовно): newcomer_pr_acceptance. Залишкові ваги перенормовано.
Власність та опіка
68Добрий
Як обчислюється оцінка
| 30/30 | Підтримка власника — у власності організації |
| 0/20 | Верифікований домен |
| 15.6/25 | Охоплення власника — 146 підписників у vstorm-co |
| 22/25 | Послужний список — 34 публічних репозиторіїв, вік облікового запису ~5 р. |
Використані вхідні дані
| followers | 146 |
| owner_type | Organization |
| is_verified | — |
| owner_login | vstorm-co |
| public_repos | 34 |
| account_age_days | 1 968 |
Супровід пакетів
100Винятковий
Як обчислюється оцінка
| 25/25 | Опубліковано й доступно — 1 пакет(ів) у pypi |
| 35/35 | Свіжість публікацій — остання публікація 0 дн. тому |
| 20/20 | Історія версій — 24 опублікованих версій |
| 20/20 | Не застарілий — активний, не deprecated і не yanked |
Використані вхідні дані
| packages | subagents-pydantic-ai |
| ecosystems | pypi |
| any_deprecated | ні |
| min_days_since_publish | 0 |
Інженерна якість
Чи наявні базові інженерні практики та документація?
96
Інженерні практики
94Винятковий
Як обчислюється оцінка
| 24/24 | Процеси CI — 3 процес(ів) CI |
| 24/24 | Наявні тести |
| 16/16 | Конфігурація лінтера |
| 9.6/9.6 | Pre-commit-хуки |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 9 out of 9 merged PRs checked by a CI test -- score normalized to 10 |
Використані вхідні дані
| has_ci | так |
| has_tests | так |
| has_editorconfig | ні |
| has_linter_config | так |
| has_precommit_config | так |
Документація
100Винятковий
Як обчислюється оцінка
| 30/30 | README |
| 25/25 | Каталог документації |
| 15/15 | Сайт документації / домашня сторінка — https://vstorm-co.github.io/subagents-pydantic-ai/ |
| 10/10 | Опис репозиторію |
| 10/10 | Теми — 17 тем |
| 10/10 | Wiki |
Використані вхідні дані
| topics | ai-agent-framework, aiagentsframework, anthropic, artificial-intelligence, chatgpt, claude-code, framework, genai, llm, mcp, open-source, openai, pydantic, pydantic-ai, python, subagents, vstorm |
| has_wiki | так |
| homepage | https://vstorm-co.github.io/subagents-pydantic-ai/ |
| has_readme | так |
| has_docs_dir | так |
| has_description | так |
Безпека
Чи міцні видимі практики безпеки й ланцюга постачання, без непослабленої пов’язаності з юрисдикціями високого ризику?
53
Стан безпеки
53Помірний
Як обчислюється оцінка
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — немає даних |
| 2.5/2.5 | CI-Tests — 9 out of 9 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 |
| 1.5/7.5 | Code-Review — Found 2/7 approved changesets -- score normalized to 2 |
| 2.5/2.5 | Contributors — project has 5 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 | Ліцензія — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — немає даних |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 1.5/7.5 | Vulnerabilities — 8 existing vulnerabilities detected |
Використані вхідні дані
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 5,3 |
Виключено з оцінювання (немає даних або не застосовно): branch_protection, signed_releases. Залишкові ваги перенормовано.
Готовність до ШІ
Наскільки репозиторій оснащений для розробки та супроводу за участі ШІ-агентів? Має свідомо малу вагу (4%): агентний інструментарій — реальний сигнал супроводу, але репозиторій без нього все одно може отримати 100/100.
80
Контекст і настанови для агентів
85Відмінний
Як обчислюється оцінка
| 45/45 | Інструкції для агентів — AGENTS.md |
| 0/15 | Машиночитана документація (llms.txt) |
| 40/40 | Читабельна історія комітів — намір зазначено у 73 з 94 людських комітів (структурований заголовок або пояснювальний текст) |
Використані вхідні дані
| has_llms_txt | ні |
| legible_history_share | 0,777 |
| agent_instruction_files | AGENTS.md |
| agent_instruction_max_bytes | 7 166 |
Як обчислюється оцінка
| 18/18 | Розгортання однією командою — Makefile |
| 22/22 | Автоматизовані тести |
| 11/11 | Конфігурація лінтера / форматера |
| 11/11 | Статична перевірка типів — src/subagents_pydantic_ai/py.typed |
| 10/10 | Відтворюване середовище — lockfile |
| 10/10 | Підтверджена практика роботи з агентами — 15 з останніх 100 комітів створено агентом або з його зазначенням |
| 8/8 | Автоматизоване супроводження — 6 з останніх 100 комітів — автоматичні оновлення залежностей |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Використані вхідні дані
| has_nix | ні |
| has_tests | так |
| lockfiles | uv.lock |
| has_dockerfile | ні |
| typed_language | ні |
| bootstrap_files | Makefile |
| has_devcontainer | ні |
| has_linter_config | так |
| typecheck_configs | src/subagents_pydantic_ai/py.typed |
| agent_commit_share | 0,15 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0,06 |
Читабельність коду для моделей
80Відмінний
Як обчислюється оцінка
| 27/45 | Типізований код — Python з конфігурацією перевірки типів (src/subagents_pydantic_ai/py.typed) |
| 53.3/55 | Керовані розміри файлів — 1/32 файлів вихідного коду понад 60 КБ |
Використані вхідні дані
| primary_language | Python |
| largest_source_bytes | 167 980 |
| source_files_sampled | 32 |
| oversized_source_files | 1 |
Машиночитні інтерфейси
40Слабкий
Як обчислюється оцінка
| 0/40 | Схема API (OpenAPI/GraphQL/proto) |
| 0/20 | Сервер MCP |
| 40/40 | Придатні до запуску приклади — examples |
Використані вхідні дані
| example_dirs | examples |
| has_mcp_signal | ні |
| api_schema_files | — |
Ключові факти
57зірок GitHub
5контриб'юторів
135комітів за останні 12 місяців
0днів від останнього пушу
24релізів
1бас-фактор
1відкритих issue
PyPIпакетних екосистем
Попередження щодо збору даних
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
- deps.dev does not index pypi:subagents-pydantic-ai@0.2.13; advisories assessed against the repository dependency graph instead
Докладніше
Історія зірок і форків 0 ★ / 18 ⇿
0Зірки
18Форки
17Релізи
Коли додано кожну зірку й форк — зібрано з GitHub і згруповано за днями. Кумулятивне зростання розміщено просто над денними додаваннями, з яких воно складається, тож їх видно одне проти одного: рівномірне органічне накопичення виглядає зовсім інакше, ніж різкий короткочасний сплеск. Там, де цю різницю можна виміряти, її подано як автентичність росту.
Мажорні 0Мінорні 2Патчі 15
OpenSSF Scorecard 5.3 / 10
5.3сукупно
Незалежна, не прив'язана до інструментів оцінка безпеки від відкритого проєкту OpenSSF Scorecard. Кожна перевірка винагороджує практику безпеки, а не інструмент конкретного постачальника. Перевірки, які Scorecard не зміг визначити, позначено н/д і виключено з оцінки безпеки (вони ніколи не зараховуються як нуль).
| 10 | Binary-Artifacts | no binaries found in the repo |
| н/д | Branch-Protection | 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 |
| 10 | CI-Tests | 9 out of 9 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 |
| 2 | Code-Review | Found 2/7 approved changesets -- score normalized to 2 |
| 10 | Contributors | project has 5 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 | 30 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| н/д | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 2 | Vulnerabilities | 8 existing vulnerabilities detected |
Прямі залежності 2
| Реєстр | Пакет | Обмеження версії | Маніфест |
|---|---|---|---|
| PyPI | pydantic | >=2.0 | pyproject.toml |
| PyPI | pydantic-ai-slim | >=2.0.0 | pyproject.toml |
Усі залежності не зібрано
Не вдалося зібрати розв'язаний набір залежностей для цього звіту: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
Звіт у форматі JSON машиночитний
{
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"repo": {
"topics": [
"ai-agent-framework",
"aiagentsframework",
"anthropic",
"artificial-intelligence",
"chatgpt",
"claude-code",
"framework",
"genai",
"llm",
"mcp",
"open-source",
"openai",
"pydantic",
"pydantic-ai",
"python",
"subagents",
"vstorm"
],
"is_fork": false,
"size_kb": 2136,
"has_wiki": true,
"homepage": "https://vstorm-co.github.io/subagents-pydantic-ai/",
"languages": {
"Python": 565583,
"Makefile": 3577
},
"pushed_at": "2026-08-01T12:42:38Z",
"created_at": "2026-01-19T22:49:07Z",
"owner_type": "Organization",
"updated_at": "2026-08-01T12:42:40Z",
"description": "Subagent Delegation framework for Pydantic AI, enabling nested subagents that can spawn their own specialists on-the-fly, with smart sync/async/auto mode selection, runtime agent creation, and clean multi-agent architecture. Adds specialization, parallel execution, and task cancellation.",
"is_archived": false,
"is_disabled": false,
"license_spdx": "MIT",
"default_branch": "main",
"license_spdx_raw": "MIT",
"primary_language": "Python",
"significant_languages": [
"Python"
]
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{
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"notes": [],
"value": 77,
"inputs": {
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"has_license": true,
"readme_badges": null,
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{
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{
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{
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{
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{
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"notes": [
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{
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{
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{
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]
},
{
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"inputs": {
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{
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{
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{
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{
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{
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{
"key": "vulnerabilities",
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},
{
"key": "ai_readiness",
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{
"key": "ai_agent_context",
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},
{
"key": "ai_interfaces",
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"inputs": {
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{
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{
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{
"key": "runnable_examples",
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"status": "met",
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}
],
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}
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}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
}
],
"classification": {
"labels": [
"library",
"framework"
],
"scores": {
"library": 6,
"framework": 4
},
"primary": "library",
"evidence": [
{
"tier": "distribution",
"label": "library",
"source": "registry:pypi",
"weight": 6
},
{
"tier": "description",
"label": "framework",
"source": "description:framework",
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{
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},
"metrics_version": "2.3.1"
},
"warnings": [
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"GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository",
"deps.dev does not index pypi:subagents-pydantic-ai@0.2.13; advisories assessed against the repository dependency graph instead"
],
"report_type": "repository",
"generated_at": "2026-08-01T12:48:04.101577Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/v/vstorm-co/subagents-pydantic-ai.svg",
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"license_state": "standard",
"license_spdx": "MIT"
}Оцінки — це сигнали, а не гарантії. Вони відображають публічно видимі практики на GitHub — це не аудит коду й не гарантія безпеки.
Відсутні дані виключаються, а ваги перенормовуються — нуль за відсутність ніколи не ставиться. Методологія версіонована й відкрита: метрики v2.3.1, схема v0.27.0 — повна методологія · вікі метрик.
Як окремий результат виглядає на тлі всього реєстру: сукупна статистика — PyPI.