Is running, using - for example - result of id -u command, which allows to use the dynamic host On the other hand, the environment variables below can be set when the container TheĪIRFLOW_UID build arg defaults to 50000 when the image is built, so it is Run docker compose build to build the image, or add -build flag to docker compose up orĭocker compose run commands to build the image automatically as needed.Įnvironment variables supported by Docker Compose ¶ĭo not confuse the variable names here with the build arguments set when image is built. Place requirements.txt file in the same directory. That conflicts with the version of apache-airflow that you are using.
#AIRFLOW WITH PYTHON UPGRADE#
This way you can be sure that pip will not try to downgrade or upgrade apacheĪirflow while installing other requirements, which might happen in case you try to add a dependency
#AIRFLOW WITH PYTHON INSTALL#
It is the best practice to install apache-airflow in the same version as the one that comes from the The relevant part of the docker-compose file of yours should look similar
Specifically when you want to add your own requirement file,Ĭomment out the image. You can - following the previous chapter, automatically build and use your custom image when you Will start much slower - each additional dependency will further delay your containers start up time).Īlso it is completely unnecessary, because docker compose has the development workflow built-in. Starting the original airflow image, but this has a number of side effects (for example your containers For development, you might be tempted to add it dynamically when you are Usual case for custom images, is when you want to add a set of requirements to it - usually stored in Special case - adding dependencies via requirements.txt file ¶ If you need to install a new Python library or system library, you can build your image. This file uses the latest Airflow image ( apache/airflow). plugins - you can put your custom plugins here. config - you can add custom log parser or add airflow_local_settings.py to configure cluster policy. logs - contains logs from task execution and scheduler. dags - you can put your DAG files here. Some directories in the container are mounted, which means that their contents are synchronized between your computer and the container. For more information, see Architecture Overview. It is available at All these services allow you to run Airflow with CeleryExecutor. docker compose up flower.įlower - The flower app for monitoring the environment. docker compose -profile flower up, or by explicitly specifying it on the command line e.g. Optionally, you can enable flower by adding -profile flower option, e.g. Redis - The redis - broker that forwards messages from scheduler to worker. Īirflow-worker - The worker that executes the tasks given by the scheduler.Īirflow-triggerer - The triggerer runs an event loop for deferrable tasks.Īirflow-init - The initialization service.Task instances once their dependencies are complete.Īirflow-webserver - The webserver is available at
This file contains several service definitions:Īirflow-scheduler - The scheduler monitors all tasks and DAGs, then triggers the
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