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INSTALL.md

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Installation procedure

It is advised to used the Docker images jaesivsm/jarr-server and jaesivsm/jarr-worker. However, the jaesivsm/jarr-front is build with the address of the production server as API URL. You'll then to rebuild it.

You can take inspiration in Dockerfiles/prod-example.yml which will provide you a working instance of JARR.

Prerquisite

To run JARR you'll need at least Docker installed.

You'll also need pipenv even if there are undocumented ways around that.

Running the code

# first clone the repository
git clone https://github.com/jaesivsm/JARR.git

# then copy Dockerfiles/prod-example.yml and edit it to your liking
# for the documentation here, we'll say that you use the example one

# first get inside the cloned repo
cd JARR

# ensure you have the proper packages installed
pipenv sync --dev

# Build base image for server and workers
make build-base

# bring up env
# /!\ You'll want to edit the example proposed below :
#  * have your own configurations file in a directory of you're own
#  * specify a proper directory for postgres to store your data in
make start-env COMPOSE_FILE=Dockerfiles/prod-example.yml

# create database inside the running postgres
# /!\ this command is for test purpose and create db and user without password
# you'll want to change that in production
make db-bootstrap-user COMPOSE_FILE=Dockerfiles/prod-example.yml
make db-bootstrap-tables COMPOSE_FILE=Dockerfiles/prod-example.yml

# create JARR tables
# /!\ this step will fail if you leave the default value for Database address,
# you'll want to replace it with "postgresql" in the jarr.json configuration file
make init-env-docker COMPOSE_FILE=Dockerfiles/prod-example.yml

Once finished, you may access jarr on http://localhost:8501/ and login with admin:admin.

Maintenance

Some tasks will require you to run commands on either the server or the worker :

Starting the scheduler

To start the scheduler that'll run all background processing, run :

docker-compose --file Dockerfiles/prod-example.yml exec jarr-worker pipenv run python3

Then in the python terminal

from jarr.crawler.main import scheduler
scheduler.apply_async()

Executing Schema and Data migration

docker-compose --file Dockerfiles/prod-example.yml exec jarr-worker flask db upgrade