# All required components, to create and fill a database,
# instantiate backend and frontend. 

MAKE_ROOT = $(shell pwd)

### Input data
# I received ssj500k in one .xml file,
# kres is composed of many .xml files
# I generated srl tags for kres in separate .json files
# (for each kres.xml file there is a kres.json file with srl tags)
SSJ_FILE = "$(MAKE_ROOT)/data/samples/ssj_example/ssj500k-sl.body.sample.xml"
KRES_FOLDER = "$(MAKE_ROOT)/data/samples/kres_example"
KRES_SRL_FOLDER = "$(MAKE_ROOT)/data/kres_srl"
OUTPUT = "db"
OUTDIR = "/home/voje/workdir/test_out"
DBADDR = "0.0.0.0:27017"  # don't use localhost

DB_ADM_USER = testadmin
DB_ADM_PASS = testadminpass
DB_USR_USER = testuser
DB_USR_PASS = testuserpass
export

.PHONY: python-env fill_database

all:
	echo "Select an argument"

# create database (run from host):
# !!! might need to run several times, so the containers come online
# Successful if you see the lines:
# Successfully added user: { "user" : "testuser", "roles" : [ "readWrite" ] }
# bye
database-service:
	cd dockerfiles/database; $(MAKE) build_run

database-users:
	cd dockerfiles/database; $(MAKE) create_users

# also useful, if we want to restart the db
database-clean:
	cd dockerfiles/database; $(MAKE) clean_stack

# create python-env container
python-env:
	cd dockerfiles/python-env; $(MAKE)

# inside the container, install our packages
python-env-install:
	pip3 install -e src/pkg/cjvt-corpusparser/.

# from inside python-env container:
data/samples:
	cd data; tar xzvf samples.tar.gz

# from inside python-env container:
fill_database: data/samples
	python3 src/pkg/cjvt-corpusparser/corpusparser/main.py --kres-folder $(KRES_FOLDER) \
		--ssj-file $(SSJ_FILE) --kres-srl-folder $(KRES_SRL_FOLDER) \
		--output $(OUTPUT) --outdir $(OUTDIR) --dbaddr $(DBADDR) \
		--dbuser $(DB_USR_USER) --dbpass $(DB_USR_PASS)