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Local Virtual Environment (virtualenv)

Use the local virtualenv development option in the combination with the Breeze development environment. This option helps you benefit from the infrastructure provided by your IDE (for example, IntelliJ PyCharm/IntelliJ Idea) and work in the environment where all necessary dependencies and tests are available and set up within Docker images.

But you can also use the local virtualenv as a standalone development option if you develop Airflow functionality that does not incur large external dependencies and CI test coverage.

These are examples of the development options available with the local virtualenv in your IDE:

  • local debugging;
  • Airflow source view;
  • autocompletion;
  • documentation support;
  • unit tests.

This document describes minimum requirements and insructions for using a standalone version of the local virtualenv.

Prerequisites

Required Software Packages

Use system-level package managers like yum, apt-get for Linux, or Homebrew for macOS to install required software packages:

  • Python (2.7, 3.5 or 3.6)
  • MySQL
  • libxml

Refer to the Dockerfile for a comprehensive list of required packages.

Extra Packages

You can also install extra packages (like [gcp], etc) via pip install -e [EXTRA1,EXTRA2 ...]. However, some of them may have additional install and setup requirements for your local system.

For example, if you have a trouble installing the mysql client on macOS and get an error as follows:

ld: library not found for -lssl

you should set LIBRARY_PATH before running pip install:

export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/opt/openssl/lib/

You are STRONGLY encouraged to also install and use pre-commit hooks for your local virtualenv development environment. Pre-commit hooks can speed up your development cycle a lot.

The full list of extras is available in setup.py.

Creating a Local virtualenv

To use your IDE for Airflow development and testing, you need to configure a virtual environment. Ideally you should set up virtualenv for all Python versions that Airflow supports (2.7, 3.5, 3.6).

To create and initialize the local virtualenv:

  1. Create an environment with one of the two options:

    • Option 1: consider using one of the following utilities to create virtual environments and easily switch between them with the workon command:

    mkvirtualenv <ENV_NAME> --python=python<VERSION>

    • Option 2: create a local virtualenv with Conda
    conda create -n airflow python=3.6
conda activate airflow

  2. Install Python PIP requirements:

    pip install -U -e ".[devel,<OTHER EXTRAS>]" # for example: pip install -U -e ".[devel,gcp,postgres]"

Note: when you first initialize database (the next step), you may encounter some problems. This is because airflow by default will try to load in example dags where some of them requires dependencies gcp and postgres. You can solve the problem by:

  • installing the extras i.e. [devel,gcp,postgres] or
  • disable the example dags with environment variable: export AIRFLOW__CORE__LOAD_EXAMPLES=False or
  • simply ignore the error messages and proceed

In addition to above, you may also encounter problems during database migration. This is a known issue and please see the progress here: AIRFLOW-6265

  1. Create the Airflow sqlite database:

    # if necessary, start with a clean AIRFLOW_HOME, e.g.
# rm -rf ~/airflow
airflow db init

  2. Select the virtualenv you created as the project's default virtualenv in your IDE.

Note that if you have the Breeze development environment installed, the breeze script can automate initializing the created virtualenv (steps 2 and 3). Simply enter the Breeze environment by using workon and, once you are in it, run:

./breeze --initialize-local-virtualenv

Running Tests

Running tests is described in TESTING.rst.

While most of the tests are typical unit tests that do not require external components, there are a number of Integration tests. You can technically use local virtualenv to run those tests, but it requires to set up a number of external components (databases/queues/kubernetes and the like). So, it is much easier to use the Breeze development environment for Integration tests.

Note: Soon we will separate the integration and system tests out via pytest so that you can clearly know which tests are unit tests and can be run in the local virtualenv and which should be run using Breeze.

Connecting to database

When analyzing the situation, it is helpful to be able to directly query the database. You can do it using the built-in Airflow command:

airflow db shell