### Output of Kubernetes Environment Setup

Source: https://github.com/apache/airflow/blob/main/contributing-docs/testing/k8s_tests.rst

Example output displayed after successfully running the `breeze k8s setup-env` command, showing the initialization and installation steps.

```text
Initializing K8S virtualenv in /Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
Reinstalling PIP version in /Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
Installing necessary packages in /Users/jarek/IdeaProjects/airflow/kubernetes-tests/.venv
```

--------------------------------

### KubernetesStartKueueJobOperator Example

Source: https://github.com/apache/airflow/blob/main/providers/cncf/kubernetes/docs/operators.rst

Example demonstrating how to start a Kueue job using KubernetesStartKueueJobOperator.

```python
from __future__ import annotations

import pendulum

from airflow.models.dag import DAG
from airflow.providers.cncf.kubernetes.operators.kueue import KubernetesStartKueueJobOperator

with DAG(
    dag_id="kubernetes_kueue_start_job_example",
    schedule=None,
    start_date=pendulum.datetime(2023, 10, 26, tz="UTC"),
    catchup=False,
    tags=["kubernetes", "kueue", "example"],
)
 as dag:
    # Example of KubernetesStartKueueJobOperator
    k8s_kueue_start_job = KubernetesStartKueueJobOperator(
        task_id="kubernetes_kueue_start_job_task",
        namespace="default",
        image="kueue/kueue-job:latest",
        name="kueue-job-starter",
        is_delete_operator_pod=False,
        get_logs=True,
        job_name="my-kueue-job",
        queue="default",
    )

```

--------------------------------

### Install Breeze and Start Airflow

Source: https://github.com/apache/airflow/blob/main/contributing-docs/03a_contributors_quick_start_beginners.rst

Installs Breeze, prek, and sets up the development environment for Airflow. This includes installing Python dependencies and starting the Airflow development container.

```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
uv tool install prek
prek install -f
prek install -f --hook-type pre-push # for running mypy checks when pushing to repo
./scripts/tools/setup_breeze
uv run dev/ide_setup/setup_vscode.py
breeze start-airflow
```

--------------------------------

### KubernetesInstallKueueOperator Example

Source: https://github.com/apache/airflow/blob/main/providers/cncf/kubernetes/docs/operators.rst

Example demonstrating how to install the Kueue component using KubernetesInstallKueueOperator.

```python
from __future__ import annotations

import pendulum

from airflow.models.dag import DAG
from airflow.providers.cncf.kubernetes.operators.kueue import KubernetesInstallKueueOperator

with DAG(
    dag_id="kubernetes_kueue_install_example",
    schedule=None,
    start_date=pendulum.datetime(2023, 10, 26, tz="UTC"),
    catchup=False,
    tags=["kubernetes", "kueue", "example"],
)
 as dag:
    # Example of KubernetesInstallKueueOperator
    k8s_kueue_install = KubernetesInstallKueueOperator(
        task_id="kubernetes_kueue_install_task",
        namespace="default",
        image="kueue/kueue:latest",
        name="kueue-installer",
        is_delete_operator_pod=False,
        get_logs=True,
    )

```

--------------------------------

### Install Airflow chart with example DAGs

Source: https://github.com/apache/airflow/blob/main/chart/docs/quick-start.rst

Installs the Airflow Helm chart with example DAGs enabled by setting the AIRFLOW__CORE__LOAD_EXAMPLES environment variable to True.

```bash
helm install $RELEASE_NAME apache-airflow/airflow \
  --namespace $NAMESPACE \
  --set-string "env[0].name=AIRFLOW__CORE__LOAD_EXAMPLES" \
  --set-string "env[0].value=True"
```

--------------------------------

### Start Airflow with example DAGs loaded

Source: https://github.com/apache/airflow/blob/main/contributing-docs/03a_contributors_quick_start_beginners.rst

Starts the Airflow development container with example DAGs loaded. This is useful for exploring Airflow's features and for testing.

```bash
breeze start-airflow --load-example-dags
```

--------------------------------

### Combined multi-module setup with Python version

Source: https://github.com/apache/airflow/blob/main/contributing-docs/quick-start-ide/contributors_quick_start_pycharm_intellij.rst

Example of a complex setup combining multi-module mode, a specific Python version, and exclusions.

```bash
$ uv run dev/ide_setup/setup_idea.py --multi-module --python 3.12 --exclude providers
```

--------------------------------

### Setup Lang-SDK Coordinator System Test

Source: https://github.com/apache/airflow/blob/main/dev/breeze/doc/05_test_commands.rst

Provisions a Kubernetes cluster for the lang-SDK coordinator system test. This includes building Go and Java example bundles, deploying LocalStack S3, uploading artifacts, rendering coordinator pod-template image placeholders, and installing the Helm release.

```bash
breeze k8s setup-lang-sdk-test
```

--------------------------------

### Start Documentation Server - Bash

Source: https://github.com/apache/airflow/blob/main/devel-common/src/docs/README.rst

Bash script to start a lightweight documentation server for Apache Airflow. Requires Python to be installed. Serves documentation at http://localhost:8000 without needing to launch the full webserver.

```bash
docs/start_doc_server.sh
```

--------------------------------

### Start Airflow with Kafka Integration

Source: https://github.com/apache/airflow/blob/main/dev/breeze/doc/03_developer_tasks.rst

Example command to start Airflow with the Kafka integration, using Python 3.10 and a PostgreSQL backend.

```bash
breeze --python 3.10 --backend postgres --integration kafka
```

--------------------------------

### Example Docker buildx builder configuration output

Source: https://github.com/apache/airflow/blob/main/dev/MANUALLY_GENERATING_IMAGE_CACHE_AND_CONSTRAINTS.md

Expected output showing a properly configured multi-builder setup with local and remote builder instances.

```text
  airflow_cache          docker-container
       airflow_cache0    unix:///var/run/docker.sock
       airflow_cache1    tcp://127.0.0.1:2375
```

--------------------------------

### Verify GPG Signature Example

Source: https://github.com/apache/airflow/blob/main/providers-summary-docs/installing-from-sources.rst

Example output demonstrating successful GPG signature verification for an Apache Airflow Providers package. Shows the signature details including key ID, issuer, and verification status.

```console
$ gpg --verify apache-airflow-providers-airbyte-1.0.0-source.tar.gz.asc apache-airflow-providers-airbyte-1.0.0-source.tar.gz
  gpg: Signature made Sat 11 Sep 12:49:54 2021 BST
  gpg:                using RSA key CDE15C6E4D3A8EC4ECF4BA4B6674E08AD7DE406F
  gpg:                issuer "kaxilnaik@apache.org"
  gpg: Good signature from "Kaxil Naik <kaxilnaik@apache.org>" [unknown]
  gpg:                 aka "Kaxil Naik <kaxilnaik@gmail.com>" [unknown]
  gpg: WARNING: The key's User ID is not certified with a trusted signature!
  gpg:          There is no indication that the signature belongs to the owner.
  Primary key fingerprint: CDE1 5C6E 4D3A 8EC4 ECF4  BA4B 6674 E08A D7DE 406F
```

--------------------------------

### Setup Kubernetes Environment and Shell

Source: https://github.com/apache/airflow/blob/main/dev/README_RELEASE_HELM_CHART.md

Use the 'breeze' tool to set up the Kubernetes environment and enter a shell with necessary Python dependencies installed, including towncrier.

```shell
breeze k8s setup-env
breeze k8s shell
```

--------------------------------

### Install UI Dependencies and Start Development Server Manually (Bash)

Source: https://github.com/apache/airflow/blob/main/airflow-core/src/airflow/ui/CONTRIBUTING.md

These commands are part of the manual setup for Airflow UI development. First, `pnpm install` fetches all project dependencies, and then `pnpm dev` starts the UI development server, enabling live changes and testing.

```bash
pnpm install && pnpm dev
```

--------------------------------

### Package Example Project

Source: https://github.com/apache/airflow/blob/main/java-sdk/README.md

Navigate to the example directory and package the project using Gradle.

```bash
../gradlew bundle
```

--------------------------------

### Start Airflow in Development Mode using Breeze (Bash)

Source: https://github.com/apache/airflow/blob/main/airflow-core/src/airflow/ui/CONTRIBUTING.md

This command utilizes the Airflow Breeze tool to start Airflow in development mode, streamlining the setup and management of the development environment. It's a quick way to get a development instance running.

```bash
breeze start-airflow --dev-mode
```

--------------------------------

### Set Up Kubernetes Testing Environment

Source: https://github.com/apache/airflow/blob/main/contributing-docs/testing/k8s_tests.rst

Prepare the Kubernetes testing environment by creating a virtual environment and installing necessary tools like `kind`, `kubectl`, and `helm`. This command is typically run once for initial setup.

```bash
breeze k8s setup-env
```

--------------------------------

### Install PyMySQL for Airflow Database Connection (Bash)

Source: https://github.com/apache/airflow/blob/main/contributing-docs/quick-start-ide/contributors_quick_start_vscode.rst

This command sequence activates the `airflow-env` Python environment and then installs the `PyMySQL` package. This is a required dependency for connecting Airflow to a MySQL database, enabling the use of MySQL as the backend for Airflow's metadata store.

```bash
pyenv activate airflow-env
pip install PyMySQL
```

--------------------------------

### Example: Build documentation for Apache Beam provider package using Breeze

Source: https://github.com/apache/airflow/blob/main/devel-common/src/docs/README.rst

This provides a concrete example of building documentation for a specific Apache Airflow provider, namely `apache-airflow-providers-apache-beam`. It demonstrates using the shorthand `apache.beam` as the `PACKAGE_ID` for targeted documentation generation.

```bash
breeze build-docs apache.beam
```

--------------------------------

### Install Apache Airflow Google Cloud Providers via pip

Source: https://github.com/apache/airflow/blob/main/providers/google/docs/operators/_partials/prerequisite_tasks.rst

This command installs the necessary Apache Airflow providers for Google Cloud services, including all required dependencies. It uses `pip`, Python's package installer, to fetch and set up the `apache-airflow[google]` package. This step is crucial for enabling interaction with Google Cloud APIs from Airflow.

```bash
pip install 'apache-airflow[google]'
```

--------------------------------

### Install QEMU for multi-platform Docker builds

Source: https://github.com/apache/airflow/blob/main/dev/MANUALLY_GENERATING_IMAGE_CACHE_AND_CONSTRAINTS.md

Enable multi-platform image building via QEMU emulation. This approach is simple but significantly slower (10x+) than hardware-backed builds.

```bash
docker run --privileged --rm tonistiigi/binfmt --install all
```

--------------------------------

### Run Breeze Setup Helper Script

Source: https://github.com/apache/airflow/blob/main/dev/breeze/doc/01_installation.rst

Execute the helper script to set up the breeze shim at ~/.local/bin/breeze. This script checks for uv, verifies no legacy global breeze install exists, and creates the executable shim.

```bash
./scripts/tools/setup_breeze
```

--------------------------------

### Install Docker prerequisites and set up repository on Ubuntu

Source: https://github.com/apache/airflow/blob/main/contributing-docs/03_contributors_quick_start.rst

This snippet updates package lists and installs necessary dependencies for Docker, then sets up the Docker GPG key and repository for Ubuntu.

```bash
sudo apt-get update

sudo apt-get install \
    ca-certificates \
    curl \
    gnupg \
    lsb-release

sudo mkdir -p /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg

echo \
  "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
  $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
```

--------------------------------

### Install Elasticsearch Extra for Airflow

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/extra-packages-ref.rst

Install the Elasticsearch extra package for Airflow to get Elasticsearch hooks and Log Handler.

```bash
pip install 'apache-airflow[elasticsearch]'
```

--------------------------------

### Test Docker installation

Source: https://github.com/apache/airflow/blob/main/contributing-docs/03_contributors_quick_start.rst

This snippet runs a simple 'hello-world' container to verify that Docker is correctly installed and configured.

```bash
docker run hello-world
```

--------------------------------

### Install ArangoDB Extra for Airflow

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/extra-packages-ref.rst

Install the ArangoDB extra package for Airflow to get ArangoDB operators, sensors, and hooks.

```bash
pip install 'apache-airflow[arangodb]'
```

--------------------------------

### Start a Celery Worker

Source: https://github.com/apache/airflow/blob/main/providers/celery/docs/celery_executor.rst

Use this command to start an Airflow Celery worker. Ensure Airflow and necessary dependencies are installed.

```bash
airflow celery worker
```

--------------------------------

### Open IDE after setup completion

Source: https://github.com/apache/airflow/blob/main/contributing-docs/quick-start-ide/contributors_quick_start_pycharm_intellij.rst

Use --open-ide to launch the IDE automatically after setup; can be combined with --confirm for non-interactive runs.

```bash
$ uv run dev/ide_setup/setup_idea.py --open-ide
```

```bash
# Combine with --confirm for fully non-interactive setup + open
$ uv run dev/ide_setup/setup_idea.py --confirm --open-ide
```

--------------------------------

### Example Comparison Output

Source: https://github.com/apache/airflow/blob/main/dev/README_RELEASE_PROVIDERS.md

This is an example of the expected output when the built packages are byte-by-byte identical to the SVN versions, indicating a successful reproducible build verification.

```text
apache_airflow_providers_amazon-8.12.0.tar.gz:No diff found
apache_airflow_providers_apache_impala-1.2.1.tar.gz:No diff found
apache_airflow_providers_atlassian_jira-2.3.0.tar.gz:No diff found
apache_airflow_providers_cncf_kubernetes-7.10.0.tar.gz:No diff found
apache_airflow_providers_common_io-1.1.0.tar.gz:No diff found
apache_airflow_providers_common_sql-1.8.1.tar.gz:No diff found
apache_airflow_providers_databricks-5.0.1.tar.gz:No diff found
apache_airflow_providers_dbt_cloud-3.4.1.tar.gz:No diff found
apache_airflow_providers_docker-3.8.2.tar.gz:No diff found
apache_airflow_providers_elasticsearch-5.2.0.tar.gz:No diff found
apache_airflow_providers_google-10.12.0.tar.gz:No diff found
apache_airflow_providers_microsoft_azure-8.3.0.tar.gz:No diff found
apache_airflow_providers_odbc-4.2.0.tar.gz:No diff found
apache_airflow_providers_openai-1.0.1.tar.gz:No diff found
apache_airflow_providers_opsgenie-5.3.0.tar.gz:No diff found
apache_airflow_providers_papermill-3.5.0.tar.gz:No diff found
apache_airflow_providers_redis-3.4.1.tar.gz:No diff found
apache_airflow_providers_snowflake-5.1.2.tar.gz:No diff found
apache_airflow_providers_trino-5.4.1.tar.gz:No diff found
apache_airflow_providers_amazon-8.12.0-py3-none-any.whl:No diff found
apache_airflow_providers_apache_impala-1.2.1-py3-none-any.whl:No diff found
apache_airflow_providers_atlassian_jira-2.3.0-py3-none-any.whl:No diff found
apache_airflow_providers_cncf_kubernetes-7.10.0-py3-none-any.whl:No diff found
apache_airflow_providers_common_io-1.1.0-py3-none-any.whl:No diff found
apache_airflow_providers_common_sql-1.8.1-py3-none-any.whl:No diff found
apache_airflow_providers_databricks-5.0.1-py3-none-any.whl:No diff found
apache_airflow_providers_dbt_cloud-3.4.1-py3-none-any.whl:No diff found
apache_airflow_providers_docker-3.8.2-py3-none-any.whl:No diff found
apache_airflow_providers_elasticsearch-5.2.0-py3-none-any.whl:No diff found
apache_airflow_providers_google-10.12.0-py3-none-any.whl:No diff found
apache_airflow_providers_microsoft_azure-8.3.0-py3-none-any.whl:No diff found
apache_airflow_providers_odbc-4.2.0-py3-none-any.whl:No diff found
apache_airflow_providers_openai-1.0.1-py3-none-any.whl:No diff found
apache_airflow_providers_opsgenie-5.3.0-py3-none-any.whl:No diff found
apache_airflow_providers_papermill-3.5.0-py3-none-any.whl:No diff found
apache_airflow_providers_redis-3.4.1-py3-none-any.whl:No diff found
apache_airflow_providers_snowflake-5.1.2-py3-none-any.whl:No diff found
apache_airflow_providers_trino-5.4.1-py3-none-any.whl:No diff found
```

--------------------------------

### Install Celery Extra for Airflow

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/extra-packages-ref.rst

Install the Celery extra package for Airflow to get Celery dependencies and sensors, enabling the CeleryExecutor.

```bash
pip install 'apache-airflow[celery]'
```

--------------------------------

### Start Release Process

Source: https://github.com/apache/airflow/blob/main/dev/breeze/doc/09_release_management_tasks.rst

Automates some of the steps needed when preparing the final release.

```bash
breeze release-management start-release
```

--------------------------------

### Start Airflow DAG Processor

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/installation/upgrading_to_airflow3.rst

Command to start the DAG processor independently in Airflow 3. This is required even for local development setups.

```bash
airflow dag-processor
```

--------------------------------

### Start RC Process with Version Parameters

Source: https://github.com/apache/airflow/blob/main/dev/README_RELEASE_AIRFLOW.md

Initialize the release candidate process with version, previous version, task SDK version, and sync branch parameters. Run this after ensuring the script is up-to-date via git pull.

```shell
git checkout main
git pull # Ensure that the script is up-to-date
breeze release-management start-rc-process \
    --version ${VERSION_RC} \
    --previous-version ${PREVIOUS_VERSION} \
    --task-sdk-version ${TASK_SDK_VERSION_RC} \
    --sync-branch ${SYNC_BRANCH}
```

--------------------------------

### Verify Python installation and module import

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/installation/installing-from-pypi.rst

After installing Python, use these commands to start the Python interpreter and confirm that a module can be imported successfully.

```bash
python
```

```python
>>> import setproctitle
# Success!
```

--------------------------------

### Install Docker Credential Helper

Source: https://github.com/apache/airflow/blob/main/contributing-docs/03_contributors_quick_start.rst

Installs 'golang-docker-credential-helpers' to resolve Docker credential initialization errors, allowing Breeze to build images.

```bash
sudo apt install golang-docker-credential-helpers
```

--------------------------------

### Install Airflow with pip and venv on Debian/Ubuntu

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/start.rst

Provides a step-by-step guide to set up a virtual environment and install Apache Airflow using pip on Debian/Ubuntu systems. This includes upgrading pip and verifying the installation.

```bash
# For Windows after WSL2 install, restart computer, then in WSL Ubuntu terminal
sudo apt update
sudo apt install python3-pip python3-venv

# Go to Linux home directory (not Windows mount)
cd ~

# Create airflow directory
mkdir -p ~/airflow
cd ~/airflow

# Create virtual environment
python3 -m venv airflow_venv

# Activate
source airflow_venv/bin/activate

# Upgrade pip
pip install --upgrade pip

# Install Airflow with correct Python version constraints
pip install apache-airflow[celery]==3.1.0 --constraint https://raw.githubusercontent.com/apache/airflow/constraints-3.1.0/constraints-3.12.txt

# Verify installation
airflow version
```

--------------------------------

### Configuring Composite-Key Mapping with PartitionedAssetTimetable

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/authoring-and-scheduling/assets.rst

Demonstrates using ProductMapper with IdentityMapper and StartOfDayMapper to handle composite keys for partitioned assets. This allows for flexible mapping of different segments of a partition key.

```python
from airflow.sdk import (
    Asset,
    IdentityMapper,
    PartitionedAssetTimetable,
    ProductMapper,
    StartOfDayMapper,
)

regional_sales = Asset(uri="file://incoming/sales/regional.csv", name="regional_sales")

with DAG(
    dag_id="aggregate_regional_sales",
    schedule=PartitionedAssetTimetable(
        assets=regional_sales,
        default_partition_mapper=ProductMapper(IdentityMapper(), StartOfDayMapper()),
    ),
):
    ...

```

--------------------------------

### Install Apache Airflow Python client via pip

Source: https://github.com/apache/airflow/blob/main/clients/python/README.md

Install the apache-airflow-client package from PyPI, the standard and recommended method for getting the latest version.

```bash
pip install apache-airflow-client
```

--------------------------------

### Run Airflow Docker Compose Tests with Breeze

Source: https://github.com/apache/airflow/blob/main/contributing-docs/testing/docker_compose_tests.rst

This command sequence builds the Airflow production image for Python 3.10 and then executes the Docker Compose tests using the Breeze tool. It verifies the functionality of the Docker Compose setup as described in the documentation, ensuring Airflow can start and process example DAGs.

```bash
breeze prod-image build --python 3.10
breeze testing docker-compose-tests
```

--------------------------------

### Build and Publish Documentation Locally

Source: https://github.com/apache/airflow/blob/main/docs/README.md

Use these commands to build documentation for specified packages and then publish them to a local archive directory. Ensure the path to the archive repository is correctly specified.

```bash
breeze build-docs "<package_id1>" "<package_id2>" --docs-only
breeze release-management publish-docs --override-versioned --airflow-site-directory <PATH_TO_THE_ARCHIVE_REPO>
```

--------------------------------

### Install CNCF Kubernetes Extra for Airflow

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/extra-packages-ref.rst

Install the CNCF Kubernetes extra package for Airflow to get Kubernetes client libraries and the KubernetesPodOperator, enabling the KubernetesExecutor.

```bash
pip install 'apache-airflow[cncf-kubernetes]'
```

--------------------------------

### Start Release Candidate Process

Source: https://github.com/apache/airflow/blob/main/dev/breeze/doc/09_release_management_tasks.rst

Automates some of the steps needed when preparing a release candidate.

```bash
breeze release-management start-rc-process
```

--------------------------------

### Start Airflow with Breeze for Testing

Source: https://github.com/apache/airflow/blob/main/dev/README_RELEASE_PROVIDERS.md

Initiates an Airflow 3.X.Y environment using Breeze, pre-configured for testing. After starting, you can install provider release candidates using pip.

```shell
breeze start-airflow --use-airflow-version 3.1.3 --python 3.10 --backend postgres \
    --load-example-dags --load-default-connections
```

```shell
pip install apache-airflow-providers-<provider>==<VERSION>rc<X>
```

--------------------------------

### Install Breeze for Airflow 2.11 with Legacy Setup

Source: https://github.com/apache/airflow/blob/main/dev/README_AIRFLOW3_DEV.md

If using the legacy global Breeze installation, run these commands after checking out 'v2-11-test' to reinstall Breeze for Airflow 2.11 compatibility.

```bash
git checkout v2-11-test
uv tool install --force -e ./dev/breeze
```

--------------------------------

### Install Breeze with pipx

Source: https://github.com/apache/airflow/blob/main/dev/breeze/doc/01_installation.rst

Install Breeze using pipx as an alternative to uv tool, creating a fully-installed binary at ~/.local/bin/breeze.

```bash
pipx install -e ./dev/breeze
```

--------------------------------

### HttpOperator: Make a GET request with parameters

Source: https://github.com/apache/airflow/blob/main/providers/http/docs/operators.rst

This example shows how to use `HttpOperator` to perform a `GET` request, passing parameters to the endpoint. The task succeeds regardless of the response content.

```python
    task_get_op = HttpOperator(
        task_id="task_get_op",
        http_conn_id="http_default",
        endpoint="get",
        method="GET",
        data={"param1": "value1", "param2": "value2"},
        log_response=True,
    )
```

--------------------------------

### Example Output of Release Candidate Files

Source: https://github.com/apache/airflow/blob/main/dev/README_RELEASE_PYTHON_CLIENT.md

This is an example output showing the expected files for a release candidate in the SVN repository, including tar.gz, .asc, and .sha512 checksums, as well as wheel files.

```shell
(airflow) bugra@dev:~/PycharmProjects/asf-dist/dev/airflow/clients/python/3.1.8rc1$ ls -la
total 57448
drwxrwxr-x 2 bugra bugra     4096 Mar 25 21:29 .
drwxrwxr-x 3 bugra bugra     4096 Mar 25 21:28 ..
-rw-rw-r-- 1 bugra bugra   386033 Mar 25 21:29 apache_airflow_client-3.1.8-py3-none-any.whl
-rw-rw-r-- 1 bugra bugra      228 Mar 25 21:29 apache_airflow_client-3.1.8-py3-none-any.whl.asc
-rw-rw-r-- 1 bugra bugra      175 Mar 25 21:29 apache_airflow_client-3.1.8-py3-none-any.whl.sha512
-rw-rw-r-- 1 bugra bugra   223960 Mar 25 21:29 apache_airflow_client-3.1.8.tar.gz
-rw-rw-r-- 1 bugra bugra      228 Mar 25 21:29 apache_airflow_client-3.1.8.tar.gz.asc
-rw-rw-r-- 1 bugra bugra      165 Mar 25 21:29 apache_airflow_client-3.1.8.tar.gz.sha512
-rw-rw-r-- 1 bugra bugra 58173692 Mar 25 21:29 apache_airflow_python_client-3.1.8-source.tar.gz
-rw-rw-r-- 1 bugra bugra      228 Mar 25 21:29 apache_airflow_python_client-3.1.8-source.tar.gz.asc
-rw-rw-r-- 1 bugra bugra      179 Mar 25 21:29 apache_airflow_python_client-3.1.8-source.tar.gz.sha512
```

--------------------------------

### Get Plugins

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/security/api_permissions_ref.rst

Retrieves information about installed Airflow plugins. Requires 'View.PLUGINS' permission.

```APIDOC
## GET /api/v2/plugins

### Description
Retrieves a list of all available plugins in Airflow.

### Method
GET

### Endpoint
/api/v2/plugins

### Permissions
View.PLUGINS
```

--------------------------------

### Define Airflow Teardown with Setup in a Single Line

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/howto/setup-and-teardown.rst

This example shows a convenient way to define a teardown task and associate it with its setup task in a single line using the `setups` argument within the `as_teardown()` method. This simplifies the DAG definition for common resource management patterns, ensuring `create_cluster` is the setup for `delete_cluster`.

```python
create_cluster >> run_query >> delete_cluster.as_teardown(setups=create_cluster)
```

--------------------------------

### Verify SVN Artifacts Listing

Source: https://github.com/apache/airflow/blob/main/dev/README_RELEASE_MYPY.md

Example output showing the expected files in the release directory, including .tar.gz and .whl files with their corresponding .asc and .sha512 checksums.

```shell
(apache-airflow) bugra@dev:~/PycharmProjects/asf-dist/dev/airflow/apache-airflow-mypy/0.1.0rc2$ ls -la
total 48
drwxrwxr-x 2 bugra bugra  4096 Jun 10 19:00 .
drwxrwxr-x 3 bugra bugra  4096 Jun 10 19:00 ..
-rw-rw-r-- 1 bugra bugra 11070 Jun 10 19:00 apache_airflow_mypy-0.1.0-py3-none-any.whl
-rw-rw-r-- 1 bugra bugra   906 Jun 10 19:00 apache_airflow_mypy-0.1.0-py3-none-any.whl.asc
-rw-rw-r-- 1 bugra bugra   173 Jun 10 19:00 apache_airflow_mypy-0.1.0-py3-none-any.whl.sha512
-rw-rw-r-- 1 bugra bugra  9116 Jun 10 19:00 apache_airflow_mypy-0.1.0.tar.gz
-rw-rw-r-- 1 bugra bugra   906 Jun 10 19:00 apache_airflow_mypy-0.1.0.tar.gz.asc
-rw-rw-r-- 1 bugra bugra   163 Jun 10 19:00 apache_airflow_mypy-0.1.0.tar.gz.sha512
```

--------------------------------

### Install Custom Requirements During Docker Build

Source: https://github.com/apache/airflow/blob/main/docker-stack-docs/build.rst

This example demonstrates how to build an Airflow Docker image while installing custom Python requirements from a `requirements.txt` file located in the `docker-context-files` directory. It also explicitly installs the `apache-airflow` package to ensure version consistency.

```bash
#!/usr/bin/env bash

# Build Airflow image with custom requirements
# The --build-arg DOCKER_CONTEXT_FILES=docker-context-files flag tells Docker to
# look for custom files in the 'docker-context-files' directory.
# The requirements.txt file in this directory will be installed by pip.
# Explicitly installing apache-airflow ensures version consistency.

export AIRFLOW_VERSION=2.7.1
export PYTHON_VERSION="3.10"

docker build \
    --build-arg \
    AIRFLOW_VERSION=${AIRFLOW_VERSION} \
    --build-arg \
    PYTHON_VERSION=${PYTHON_VERSION} \
    --build-arg \
    DOCKER_CONTEXT_FILES=docker-context-files \
    -t apache/airflow:latest \
    -f docker/Dockerfile .

```

--------------------------------

### Custom Partition Mapper Example

Source: https://github.com/apache/airflow/blob/main/airflow-core/docs/authoring-and-scheduling/assets.rst

This example demonstrates how to create a custom partition mapper that strips a namespace prefix from upstream keys.

```python
from airflow.partition_mappers.base import PartitionMapper


class CustomPartitionMapper(PartitionMapper):
    def get_partition_keys(self, upstream_keys):
        return [key.split('::')[-1] for key in upstream_keys]

```