Setting up your Dev Environment

Prerequisites

In order to contribute to Great Expectations, you will need the following:

• A GitHub account—this is sufficient if you only want to contribute to the documentation.

• If you want to contribute code, you will also need a working version of Git on your computer. Please refer to the Git setup instructions for your environment.

• We also recommend going through the SSH key setup process on GitHub for easier authentication.

Fork and clone the repository

1. Fork the Great Expectations repo

• Go to the Great Expectations repo on GitHub.

• Click the Fork button in the top right. This will make a copy of the repo in your own GitHub account.

• GitHub will take you to your forked version of the repository.

2. Clone your fork

• Click the green Clone button and choose the SSH or HTTPS URL depending on your setup.

• Copy the URL and run git clone <url> in your local terminal.

• This will clone the develop branch of the great_expectations repo. Please use develop (not main!) as the starting point for your work.

• Atlassian has a nice tutorial for developing on a fork.

3. Add the upstream remote

• On your local machine, cd into the great_expectations repo you cloned in the previous step.

• Run: git remote add upstream git@github.com:great-expectations/great_expectations.git

• This sets up a remote called upstream to track changes to the main branch.

4. Create a feature branch to start working on your changes.

• Example: git checkout -b feature/my-feature-name

• We do not currently follow a strict naming convention for branches. Please pick something clear and self-explanatory, so that it will be easy for others to get the gist of your work.

Install Python dependencies

5. Create a new virtual environment

• Make a new virtual environment (e.g. using virtualenv or conda), name it “great_expectations_dev” or similar.

• Ex virtualenv: python3 -m venv <path_to_environments_folder\>/great_expectations_dev and then <source path_to_environments_folder\>/great_expectations_dev/bin/activate

• Ex conda: conda create --name great_expectations_dev and then conda activate great_expectations_dev

This is not required, but highly recommended.

6. Install dependencies from requirements-dev.txt

• pip install -r requirements-dev.txt -c constraints-dev.txt

• MacOS users will be able to pip / pip3 install requirements-dev.txt using the above command from within conda, yet Windows users utilizing a conda environment will need to individually install all files within requirements-dev.txt

• This will ensure that sure you have the right libraries installed in your Python environment.

  • Note that you can also substitute requirements-dev-test.txt to only install requirements required for testing all backends, and requirements-dev-spark.txt or requirements-dev-sqlalchemy.txt if you would like to add support for Spark or SQLAlchemy tests, respectively. For some database backends, such as MSSQL additional driver installation may required in your environment; see below for more information.

  • Installing Microsoft ODBC driver for MacOS

  • Installing Microsoft ODBC driver for Linux

7. Install great_expectations from your cloned repo

• pip install -e .

  *-e will install Great Expectations in “editable” mode. This is not required, but is often very convenient as a developer.

(Optional) Configure resources for testing and documentation

Depending on which features of Great Expectations you want to work on, you may want to configure different backends for local testing, such as PostgreSQL and Spark. Also, there are a couple of extra steps if you want to build documentation locally.

If you want to develop against local PostgreSQL:

• To simplify setup, the repository includes a docker-compose file that can stand up a local PostgreSQL container. To use it, you’ll need to have Docker installed.

• Navigate to assets/docker/postgresql in your great_expectations repo and run docker-compose up -d

• Within the same directory, you can run docker-compose ps to verify that the container is running. You should see something like:

      Name                       Command              State           Ports———————————————————————————————————————————postgresql_travis_db_1   docker-entrypoint.sh postgres   Up      0.0.0.0:5432->5432/tcp

• Once you’re done testing, you can shut down your postgesql container by running docker-compose down from the same directory.

• Caution: If another service is using port 5432, Docker may start the container but silently fail to set up the port. In that case, you will probably see errors like this:

  psycopg2.OperationalError: could not connect to server: Connection refused    Is the server running on host "localhost" (::1) and accepting    TCP/IP connections on port 5432?could not connect to server: Connection refused    Is the server running on host "localhost" (127.0.0.1) and accepting    TCP/IP connections on port 5432?

• Or this…

  sqlalchemy.exc.OperationalError: (psycopg2.OperationalError) FATAL:  database "test_ci" does not exist(Background on this error at: http://sqlalche.me/e/e3q8)

If you want to develop against local mysql:

• To simplify setup, the repository includes a docker-compose file that can stand up a local mysqldb container. To use it, you’ll need to have Docker installed.

• Navigate to assets/docker/mysql in your great_expectations repo and run docker-compose up -d

• Within the same directory, you can run docker-compose ps to verify that the container is running. You should see something like:

        Name                   Command             State                 Ports------------------------------------------------------------------------------------------mysql_mysql_db_1   docker-entrypoint.sh mysqld   Up      0.0.0.0:3306->3306/tcp, 33060/tcp

• Once you’re done testing, you can shut down your mysql container by running docker-compose down from the same directory.

• Caution: If another service is using port 3306, Docker may start the container but silently fail to set up the port.

If you want to develop against local Spark:

• In most cases, pip install requirements-dev.txt should set up pyspark for you.

• If you don’t have Java installed, you will probably need to install it and set your PATH or JAVA_HOME environment variables appropriately.

• You can find official installation instructions for Spark here.

If you want to build documentation locally:

• pip install -r docs/requirements.txt

• To build documentation, the command is cd docs; make html

• Documentation will be generated in docs/build/html/ with the index.html as the index page.

• Note: we use autoapi to generate API reference docs, but it’s not compatible with pandas 1.1.0. You’ll need to have pandas 1.0.5 (or a previous version) installed in order to successfully build docs.

Run tests to confirm that everything is working

• You can run all tests by running pytest in the great_expectations directory root. Please see Testing for testing options and details.

Start coding!

At this point, you have everything you need to start coding!