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cni/deployments/kubernetes/Dockerfile.install-cni
ARG BASE_DISTRIBUTION=debug # Version is the base image version from the TLD Makefile ARG BASE_VERSION=latest ARG ISTIO_BASE_REGISTRY=gcr.io/istio-release # The following section is used as base image if BASE_DISTRIBUTION=debug FROM ${ISTIO_BASE_REGISTRY}/base:${BASE_VERSION} AS debug # The following section is used as base image if BASE_DISTRIBUTION=distroless
Registered: Wed Nov 06 22:53:10 UTC 2024 - Last Modified: Wed Jun 26 22:17:14 UTC 2024 - 1002 bytes - Viewed (0) -
docs/de/docs/tutorial/body-nested-models.md
/// ## Bodys aus reinen Listen Wenn Sie möchten, dass das äußerste Element des JSON-Bodys ein JSON-`array` (eine Python-`list`e) ist, können Sie den Typ im Funktionsparameter deklarieren, mit der gleichen Syntax wie in Pydantic-Modellen: ```Python images: List[Image] ``` oder in Python 3.9 und darüber: ```Python
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 10.3K bytes - Viewed (0) -
docs/en/docs/deployment/docker.md
## What is a Container Image A **container** is run from a **container image**. A container image is a **static** version of all the files, environment variables, and the default command/program that should be present in a container. **Static** here means that the container **image** is not running, it's not being executed, it's only the packaged files and metadata.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Wed Sep 18 16:09:57 UTC 2024 - 28.5K bytes - Viewed (0) -
docs/de/docs/deployment/docker.md
## Offizielles Docker-Image mit Gunicorn – Uvicorn Es gibt ein offizielles Docker-Image, in dem Gunicorn mit Uvicorn-Workern ausgeführt wird, wie in einem vorherigen Kapitel beschrieben: [Serverworker – Gunicorn mit Uvicorn](server-workers.md){.internal-link target=_blank}.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Mon Aug 12 21:47:53 UTC 2024 - 39K bytes - Viewed (0) -
docs/en/overrides/main.html
<img class="sponsor-image" src="/img/sponsors/platform-sh-banner.png" /> </a> </div> <div class="item"> <a title="Deploy FastAPI on AWS with a few clicks" style="display: block; position: relative;" href="https://www.porter.run" target="_blank"> <span class="sponsor-badge">sponsor</span> <img class="sponsor-image" src="/img/sponsors/porter-banner.png" /> </a> </div>
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tests/compose.yml
services: mysql: image: 'mysql/mysql-server:latest' ports: - "127.0.0.1:9910:3306" environment: - MYSQL_DATABASE=gorm - MYSQL_USER=gorm - MYSQL_PASSWORD=gorm - MYSQL_RANDOM_ROOT_PASSWORD="yes" postgres: image: 'postgres:latest' ports: - "127.0.0.1:9920:5432" environment: - TZ=Asia/Shanghai - POSTGRES_DB=gorm - POSTGRES_USER=gorm
Registered: Sun Nov 03 09:35:10 UTC 2024 - Last Modified: Mon Sep 30 03:21:19 UTC 2024 - 798 bytes - Viewed (0) -
docs/en/docs/tutorial/body-nested-models.md
/// ## Bodies of pure lists If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models: ```Python images: List[Image] ``` or in Python 3.9 and above: ```Python images: list[Image] ``` as in:
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 9.4K bytes - Viewed (0) -
requirements-docs.txt
mkdocs-material==9.5.18 mdx-include >=1.4.1,<2.0.0 mkdocs-redirects>=1.2.1,<1.3.0 typer == 0.12.5 pyyaml >=5.3.1,<7.0.0 # For Material for MkDocs, Chinese search jieba==0.42.1 # For image processing by Material for MkDocs pillow==11.0.0 # For image processing by Material for MkDocs cairosvg==2.7.1 mkdocstrings[python]==0.26.1 griffe-typingdoc==0.2.7 # For griffe, it formats with black black==24.3.0 mkdocs-macros-plugin==1.0.5
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.github/workflows/iam-integrations.yaml
Registered: Sun Nov 03 19:28:11 UTC 2024 - Last Modified: Tue Sep 17 16:45:46 UTC 2024 - 5.3K bytes - Viewed (0) -
docs/ru/docs/tutorial/body-nested-models.md
/// ## Тела с чистыми списками элементов Если верхний уровень значения тела JSON-объекта представляет собой JSON `array` (в Python - `list`), вы можете объявить тип в параметре функции, так же, как в моделях Pydantic: ```Python images: List[Image] ``` в Python 3.9 и выше: ```Python images: list[Image] ``` например так:
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