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data | 1 year ago | |
dip_src | 1 year ago | |
dockerfiles | 1 year ago | |
old_api_examples | 1 year ago | |
src | 1 year ago | |
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Dockerfile-backend-flask | 1 year ago | |
Makefile | 1 year ago | |
README.md | 1 year ago | |
env.default | 1 year ago | |
nginx.conf | 1 year ago | |
production.yaml | 1 year ago |
Required submodules:
https://gitea.cjvt.si/kristjan/cjvt-corpusparser.git
$ git submodule init
$ git submodule update
Copy env.default
to env.local
(gitignored).
Modify database credentials in env.local
.
The file is used by make
.
Set db admin, user, pass, etc in 'Makefile'.
Spin up the database service and create users:
Make sure you create a folder for the data on host machine (see mongodb-stack.yml
volumes
.
$ mkdir -p ${HOME}/mongo_container/data/ # default one
# $ make database-clean # opt, removes docker services, not data
$ make database-service
$ make database-users # only first time; user data persists too
Populate the database with data form files:
Set path to files in Makefile
.
# spin up a container with python env
$ make python-env
# install our packages
$ make python-env-install
# run the code
# beforehand, set the data files in Makefile
# instead of mounting directories into the container, you can
# create a link inside ./data, that points to the desired location
# I've separated the processes for better memory management
$ make fill-database-ssj
$ make fill-database-kres
# You can detach from the running process using Ctrl-p + Ctrl-q
# this is a long operation
# if running on a remote server, use nohup:
$ nohup $(make fill-database > fill-database.log) &
If all goes well, we should be able to inspect the database, filled with corpora, on 0.0.0.0:8087
.
Relies heavily on the database. Set that up first.
# spin up container
$ make python-env
# install our packages
$ make python-env-install
# needs to be ran once to modify a new database
$ make backend-prepare-db
# if you have the file prepared (sskj_senses.json), you can
# fill the database with some senses
$ make sskj-senses
# with debugger
$ make backend-dev
# production
$ make backend-prod
API endpoints:
Relies on Flask backend.
Before running make
, you might need to set the correct api address.
Check ./src/frontend_vue/config/config_prod.json
.
bash
# $ make frontend-dev # development
$ make frontend-prod
App available on: http://0.0.0.0:8080
.
Prerequisite: machine with free ports 80 and 8084.
Either build the database from scratch (lenghty process) using above instructions or just migrate the database from the faculty server (recommended).
Build container my-mongo:
# run once and destroy containers
$ make database-service
Set database connection details in /src/backend_flask/db_config.py
.
Change 'valuser' and 'valuserpass' to the database user.
mongodb://valuser:valuserpass@my_mongo/valdb
In the above line, replace valuser
with the username and valuserpass
with the password that was used to create the database tables (the values were set in the root Makefile).
You can also set the number of workers in /src/backend_flask/entrypoint.sh
.
In line with gunicorn -t 4 -b 127.0.0.1:8084 app:app
, edit the -t
parameter.
Rule of thumb is 2x number of available CPU cores.
Build the backend container:
# From git root
$ make build-backend-flask
Set the server address (where backend will be runnig) in src/frontend_vue/config/config_prod.json
.
Build the /dist
folder that contains the static app (we will be using Nginx to serve it).
# From git root
$ make build-frontend-prod
All set, now run the stack.
Stack configuration in production.yaml
.
# From git root
$ make deploy-prod-stack
There's a 15GB mongo dump containing the fully processed kres and ssj data.
We can use that file to deploy our aplication.
With this database, we will need a minimum of 8GB ram to serve the app.
If the server is struggling, frontend will throw "Network errors".
Check 0.0.0.0:8081
and remove (or backup) the current example database valdb
.
Run the stack with mongo port mapped:
(uncomment the lines in production.yaml
)
ports:
- 27017:27017
Run a separate my-mongo container with the mounted data:
$ mongo run -it --net host -v <local_dump_path>/dumps my-mongo /bin/bash
Inside the container (edit the uesrname, password):
$ mongorestore /dumps/valdb --db valdb --uri=mongodb://valuser:valuserpass@0.0.0.0:27017
After uploading, restart the stack with 27017
commented out.