Local Development

Use python version 3.10 for development.

pyenv is the recommended method to install and manage python versions.

Python Setup

python -m venv venv/
source venv/bin/activate
python -m pip install pip-tools
python -m pip install -e ".[testing]"
pre-commit install

Developing in PyCharm

Run/Debug Configurations

1. Select Module name: from the drop list for the first field and enter analysis.cli

2. In the Parameters: field enter run-analysis --date=2022-11-15 ./config_files (any date can be specified)

3. In the Environment variables: field enter

   PYTHONUNBUFFERED=1;SLACK_BOT_TOKEN=<slackbot_token>;GOOGLE_APPLICATION_CREDENTIALS=<service account file>;DEV_REPORT_SLACK_CHANNEL=overwatch-mvp
   

   Contact gleonard@mozilla.com for SLACK_BOT_TOKEN

Updating Dependencies

DO NOT UPDATE requirements.txt or requirements.in manually!

1. If you have not set up your local environment run the steps described above.

2. Activate your local environment in not already activated.

source venv/bin/activate

3. Make required changes to pyproject.toml

4. Generate a new version of requirements.in and requirements.txt and apply updated requirements.txt to venv.

make update_deps

Testing

To run pytest:

make local_test

Pytest is configured to also run black and flake8. Formatting failures are treated as test failures.

Docker

Setting Image Version

When building the docker image set the following environment variable to indicate the version

IMAGE_VERSION=<version>

If IMAGE_VERSION is not set the default value is <username>-dev (e.g. gleonard-dev) is used

Building the Docker Image

To build a docker image run:

make image

To update environment, run pytest and build a new image run:

make build

Running Locally

After building the docker image, use the following command to launch the container. make run is configured to publish reports to the development #overwatch-mvp Slack channel instead of the production Slack channel #overwatch-reports

make run RUN_DATE=<YYYY-MM-DD> CREDENTIAL_VOLUME_MOUNT=<location of service account file> DESTINATION_CREDENTIAL_FILENAME=<service_account_filename>.json SLACK_BOT_TOKEN=<slackbot_token>

To run the docker image with access to a shell prompt use (generally for debugging purposes):

make shell

To stop the docker container:

make stop

Running via Airflow

Testing Overwatch with Airflow can be accomplished by running Airflow locally. Follow the steps outlined in https://mana.mozilla.org/wiki/pages/viewpage.action?spaceKey=SRE&title=WTMO+Developer+Guide to set up Airflow

1. The Container Registry in the automated-analysis-dev project has been enabled (https://console.cloud.google.com/gcr/images/automated-analysis-dev?project=automated-analysis-dev). This is where development images are pushed and pulled. To push a development docker image use (see IMAGE_VERSION notes above).

make dev_push

2. Launch airflow and create gke (see https://mana.mozilla.org/wiki/pages/viewpage.action?spaceKey=SRE&title=WTMO+Developer+Guide)

3. Create the following Variables in Airflow:

   • overwatch_slack_token and set the value to the Slack token (contact gleonard@mozilla.com for access).
   • overwatch_image_version and set to the value of IMAGE_VERSION or <username>-dev if IMAGE_VERSION is not set

4. Update your local copy of overwatch.py DAG in telemetry-airflow with the following changes:

   1. image repository - replace moz-fx-data-airflow-prod-88e0 with automated-analysis-dev
   2. report slack channel - add "DEV_REPORT_SLACK_CHANNEL" "overwatch-mvp" to env_vars dict for GKEPodOperator
   3. add GCP dev GKE cluster settings to GKEPodOperator (replacing with your username:
      1. gcp_conn_id="google_cloud_gke_sandbox",
      2. project_id="moz-fx-data-gke-sandbox",
      3. cluster_name="-gke-sandbox",
      4. location="us-west1",

   What it Does