Merge pull request #182 from cagov/writing_building_footprints_to_s3 #67

	name: docs
	on:
	push:
	branches:
	- main
	permissions:
	contents: write

	env:
	DBT_PROFILES_DIR: ci
	PRIVATE_KEY: ${{ SECRETS.SNOWFLAKE_PRIVATE_KEY }}
	SNOWFLAKE_PRIVATE_KEY_PATH: /tmp/private_key.p8
	SNOWFLAKE_USER: GITHUB_ACTIONS_SVC_USER_DEV

	jobs:
	deploy:
	runs-on: ubuntu-latest
	steps:
	- uses: actions/checkout@v3
	- uses: actions/setup-python@v4
	with:
	python-version: "3.10"
	- uses: snok/install-poetry@v1
	with:
	virtualenvs-create: false
	- id: auth
	name: Authenticate to Google Cloud
	uses: google-github-actions/auth@v1
	with:
	# The credentials here can read metadata, data, and create jobs (execute
	# queries), which allows it to compile the dbt project and generate docs.
	credentials_json: ${{ secrets.GOOGLE_CREDENTIALS }}
	export_environment_variables: true
	- uses: actions/cache@v2
	with:
	key: ${{ github.ref }}
	path: .cache
	- name: Install dependencies
	run: \|
	poetry install
	# TODO: once we are on dbt-snowflake 1.5, no need to pipe to a file, we can
	# just use $SNOWFLAKE_PRIVATE_KEY
	- name: Set up private key
	run: echo "$PRIVATE_KEY" > $SNOWFLAKE_PRIVATE_KEY_PATH
	- name: Build dbt docs
	run: \|
	# Generate snowflake dbt docs
	dbt deps --project-dir=transform
	dbt docs generate --project-dir=transform
	cp -r transform/target docs/dbt_docs_snowflake
	# Generate bigquery dbt docs
	dbt deps --project-dir=transform-bigquery
	dbt docs generate --project-dir=transform-bigquery
	cp -r transform-bigquery/target docs/dbt_docs_bigquery
	- name: Deploy 🚀
	run: mkdocs gh-deploy --force

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