Makefile

# ----------------------------------
#          Deployment
# ----------------------------------
update_heroku:
	git commit --allow-empty -m 'trigger heroku after updating forecast data'
	git push heroku master

# ----------------------------------
#      Training on GCP or locally
# ----------------------------------

JOB_NAME=electricity_price_predictor_$(shell date +'%Y%m%d_%H%M')
BUCKET_NAME=electricity_price_predictor
BUCKET_TRAINING_FOLDER=trainings
PACKAGE_NAME=electricity_price_predictor
FILENAME=sarimax
PYTHON_VERSION=3.7
RUNTIME_VERSION=2.3
REGION=europe-west4

train_on_gcp:
	gcloud ai-platform jobs submit training ${JOB_NAME} \
					--job-dir gs://${BUCKET_NAME}/${BUCKET_TRAINING_FOLDER} \
					--package-path ${PACKAGE_NAME} \
					--module-name ${PACKAGE_NAME}.${FILENAME}	\
					--python-version=${PYTHON_VERSION} \
					--runtime-version=${RUNTIME_VERSION} \
					--region ${REGION}

	python -m ${PACKAGE_NAME}.make_public
	explorer.exe "https://electricity-price-predictor.herokuapp.com/"

train_local:
	python -m ${PACKAGE_NAME}.${FILENAME}
	python -m ${PACKAGE_NAME}.make_public
	explorer.exe "https://electricity-price-predictor.herokuapp.com/"
# ----------------------------------
#          INSTALL & TEST
# ----------------------------------
install_requirements:
	@pip install -r requirements.txt

test:
	@coverage run -m pytest tests/*.py

clean:
	@rm -f */version.txt
	@rm -f .coverage
	@rm -fr */__pycache__ */*.pyc __pycache__
	@rm -fr build dist
	@rm -fr electricity_price_predictor-*.dist-info
	@rm -fr electricity_price_predictor.egg-info

install:
	@pip install . -U

all: clean install test


uninstall:
	@python setup.py install --record files.txt
	@cat files.txt | xargs rm -rf
	@rm -f files.txt

# ----------------------------------
#      UPLOAD PACKAGE TO PYPI
# ----------------------------------
build:
	@python setup.py sdist bdist_wheel

pypi_test:
	@twine upload -r testpypi dist/* -u lologibus2

pypi:
	@twine upload dist/* -u lologibus2