Add instruction to use local machine as development

docs/contributing.rst

@@ -16,56 +16,61 @@ To contribute to the cosmos project:
 #. Link your issue to the pull request
 #. Once developments are complete on your feature branch, request a review and it will be merged once approved.
 
+Setup local development on host machine
+---------------------------------------
 
-Using Hatch for local development
----------------------------------
+This guide will setup astronomer development on host machine, first clone the ``astronomer-cosmos`` repo and enter the repo directory:
 
-We currently use `hatch <https://github.com/pypa/hatch>`_ for building and distributing ``astronomer-cosmos``.
+.. code-block:: bash
 
-The tool can also be used for local development. The `pyproject.toml <https://github.com/astronomer/astronomer-cosmos/blob/main/pyproject.toml>`_ file currently defines a matrix of supported versions of Python and Airflow for which a user can run the tests against.
+    git clone https://github.com/astronomer/astronomer-cosmos.git
+    cd astronomer-cosmos/
 
-For instance, to run the tests using Python 3.10 and Apache Airflow 2.5, use the following:
+Then install ``airflow`` and ``astronomer-cosmos`` using python-venv:
 
 .. code-block:: bash
 
-    hatch run tests.py3.10-2.5:test-cov
+    python3 -venv m env && source env/bin/activate
+    pip3 install apache-airflow
+    pip3 install -e .[dbt-postgres,dbt-databricks]
 
-It is also possible to run the tests using all the matrix combinations, by using:
+Set airflow home to the ``dev/`` directory and disabled loading example DAGs:
 
 .. code-block:: bash
 
-    hatch run tests:test-cov
+    export AIRFLOW_HOME=$(pwd)/dev/
+    export AIRFLOW__CORE__LOAD_EXAMPLES=false
 
-The integration tests rely on Postgres. It is possible to host Postgres by using Docker, for example:
+Then, initialize the database and create a new user, the command below will create a new user admin with password admin:
+
+    By default airflow will use sqlite as database, you can overwrite this by set variable ``AIRFLOW__DATABASE__SQL_ALCHEMY_CONN`` to the sql connection string.
 
 .. code-block:: bash
 
-    docker run --name postgres -p 5432:5432 -p 5433:5433 -e POSTGRES_PASSWORD=postgres postgres
+    airflow db init
 
-To run the integration tests for the first time, use:
+    airflow users create \
+        --email [email protected] --firstname admin \
+        --lastname admin --password admin \
+        --role Admin --username admin
 
-.. code-block:: bash
+Run the following airflow component on the separate terminal
 
-    export AIRFLOW_HOME=`pwd`
-    export AIRFLOW_CONN_AIRFLOW_DB=postgres://postgres:[email protected]:5432/postgres
-    hatch run tests.py3.8-2.5:test-integration-setup
-    hatch run tests.py3.8-2.5:test-integration
+.. code-block:: bash
 
-If testing for the same Airflow and Python version, next runs of the integration tests can be:
+    airflow webserver
+    airflow scheduler
+    airflow triggerer
 
-.. code-block:: bash
+Once the airflow is up, you can access the Airflow UI at ``http://localhost:8080``.
 
-    hatch run tests.py3.8-2.5:test-integration
+    Note: whenever you want to start the development server, you need to activate the ``virtualenv`` and set the ``environment variables``
 
 Using Docker Compose for local development
-------------------------------------------
+--------------------------------------------
 
 It is also possible to just build the development environment using docker compose
 
-
-Local Sandbox
-+++++++++++++
-
 To launch a local sandbox with docker compose, first clone the ``astronomer-cosmos`` repo and enter the repo directory:
 
 .. code-block:: bash
@@ -88,9 +93,48 @@ Then, run the docker compose command:
 
 Once the sandbox is up, you can access the Airflow UI at ``http://localhost:8080``.
 
+Testing application with hatch
+------------------------------
+
+We currently use `hatch <https://github.com/pypa/hatch>`_ for building and distributing ``astronomer-cosmos``.
+
+The tool can also be used for local development. The `pyproject.toml <https://github.com/astronomer/astronomer-cosmos/blob/main/pyproject.toml>`_ file currently defines a matrix of supported versions of Python and Airflow for which a user can run the tests against.
+
+For instance, to run the tests using Python 3.10 and Apache Airflow 2.5, use the following:
+
+.. code-block:: bash
+
+    hatch run tests.py3.10-2.5:test-cov
+
+It is also possible to run the tests using all the matrix combinations, by using:
+
+.. code-block:: bash
+
+    hatch run tests:test-cov
+
+The integration tests rely on Postgres. It is possible to host Postgres by using Docker, for example:
+
+.. code-block:: bash
+
+    docker run --name postgres -p 5432:5432 -p 5433:5433 -e POSTGRES_PASSWORD=postgres postgres
+
+To run the integration tests for the first time, use:
+
+.. code-block:: bash
+
+    export AIRFLOW_HOME=`pwd`
+    export AIRFLOW_CONN_AIRFLOW_DB=postgres://postgres:[email protected]:5432/postgres
+    hatch run tests.py3.8-2.5:test-integration-setup
+    hatch run tests.py3.8-2.5:test-integration
+
+If testing for the same Airflow and Python version, next runs of the integration tests can be:
+
+.. code-block:: bash
+
+    hatch run tests.py3.8-2.5:test-integration
 
 Pre-Commit
-++++++++++
+----------
 
 We use pre-commit to run a number of checks on the code before committing. To install pre-commit, run: