# Gradle runtimes

Gradle is made up of the following processes that work together to "run the build":

- Gradle daemon. This is the process that actually runs the build. It hosts build logic and coordinates the lifecycle of the build. It is a long-running daemon process.
- CLI client. This is the `gradle` or `gradlew` command, and is responsible for locating, starting and interacting with the Gradle daemon, potentially downloading the Gradle distribution. 

name: PyLint
on:
  pull_request:
    paths:
      - '**.py'

permissions:
  contents: read

jobs:
  build:
    name: PyLint
    runs-on: ubuntu-latest
    steps:
    - name: Checkout code
      uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
    - name: Get file changes
      id: get_file_changes

Stellen wir uns vor, Sie verfügen über einige **Modelle für maschinelles Lernen**, die Sie zur Bearbeitung von Requests verwenden möchten. 🤖

Die gleichen Modelle werden von den Requests gemeinsam genutzt, es handelt sich also nicht um ein Modell pro Request, pro Benutzer, oder ähnliches.

As indicated, each of those components require a Java runtime to run.

The recommended way of invoking Gradle is to use the Gradle Wrapper.
The Wrapper then downloads the Gradle distribution (if necessary), starts the Launcher and runs the build, spawning and connecting to other processes such as the Daemon as required.

./mvnw --projects '!guava-testlib,!guava-tests,!guava-bom,!guava-gwt' initialize -P print-java-11-home
export JAVA_HOME=$(<target/java_11_home)

# Gradle Wrapper overwrites some files when it runs.
# To avoid modifying the Git client, we copy everything we need to another directory.
# That provides general hygiene, including avoiding release errors:
#
# Preparing to update Javadoc and JDiff for the release...

on:
  schedule:
    - cron: '42 2 * * 1' # Every monday 2:42am UTC
  workflow_dispatch:

permissions:
  contents: write
  id-token: write
  pull-requests: write

jobs:
  update-test-buckets:
    runs-on: ubuntu-latest

    if: github.repository == 'gradle/gradle'

    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
      - name: configure aws credentials

    /**
     * Context object containing crawler state and configuration.
     */
    protected CrawlerContext crawlerContext;

    /**
     * Flag indicating whether the crawler runs in background mode.
     */
    protected boolean background = false;

    /**
     * Flag indicating whether crawler threads run as daemon threads.
     */
    protected boolean daemon = false;

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[8:9] *}

Diese deklariert einen optionalen Query-Parameter `q` vom Typ `str` und gibt ihn dann einfach zurück.

Das ist recht einfach (nicht sehr nützlich), hilft uns aber dabei, uns auf die Funktionsweise der Unterabhängigkeiten zu konzentrieren.

## Zweite Abhängigkeit, „Dependable“ und „Dependant“ { #second-dependency-dependable-and-dependant }

This provider might be charging you per request, and calling it might take some extra time than if you had a fixed mock user for tests.

You probably want to test the external provider once, but not necessarily call it for every test that runs.

In this case, you can override the dependency that calls that provider, and use a custom dependency that returns a mock user, only for your tests.

All replication failures are picked up by the scanner which runs at a one minute frequency, each time scanning up to a sixteenth of the namespace. Object versions marked `PENDING` or `FAILED` are re-queued for replication.