Language

Language is an helpful application to learn English, Japanese and Chinese

Requirements

Development requirements

Python
Docker
Docker Toolbox (if under Windows or Mac OSX)
Postgres client (psql)

Install Python requirements with pip

If you want your IDE to be able to perform autocompletion with the library used by the Language python application, you should install the depedencies.

Note that anyway, the Docker container will run it for you, and as the application folder is mounted into the container, the installation of dependencies will be written on the host.

If you want to manually install the depedencies, run the following command:

pip install -r docker/application/requirements.txt

The Application

The application itself is running with Python and based on Django framework.

The Client

The client is an SPA application, served with Nginx and based on Angular framework.

The databases

There are two databases systems used by Language application:

Elasticsearch (used to perform full-text search, store the multi-language data)
PostgreSQL (used for user credentials, etc.)

PostgreSQL database

Connection via a shell

In order to connect to the PostgreSQL database, a postrgres client is required. For development purposes, such a client has been set up into the application container.

To connect the docker container, se the corresponsing section, under "Docker".

Once you established a shell between host and the app's docker container, you will be able to connect the PostgreSQL client this way:

psql -hpostgres -Upostgres

Then, the prompt will ask you for the password, which, in development environnement has been set to toto (yes, I have a very fertile imagination, I know that).

As a reminder, to connect a specific database use \c db_name, to list databases use \l, to quit the shell use \q

Setup the database with Django

First, ensure that the dabase named language exists

Once connected to the application container, executing the following command will synchronize the Django models with the database:

python manage.py migrate

Docker

Language runs under Docker micro containers.

There are different containers, with different usages:

A container for Elasticsearch with persistency on host
A container for PostgreSQL, currently without persistency
A container for the python API (the application itself)
A container for the client (SPA served with Nginx)

Note for users under Mac OSX

As Docker is only available on Linux distributions, users under Mac OSX have to install Docker Toolbox.

Enable Elasticsearch persistency under Mac OSX

To enable the persistency under Mac OSX, run the following commands:

cd elasticsearch
mkdir data && chown 775 data
mkdir logs && chown 775 logs

Now, the data written into Elasticsearch via the Docker container will be in fact written on your HDD, under elasticsearch/data folder. That allows you to turn off the container without suffering a loss of data.

Runing the containers

Language runs under Docker micro containers.

Run from the docker folder with:

docker-compose up

4 containers:

application
client
db (elasticsearch)
db (postgresql)

Connect to a running container via a remote shell

Connect to the python application container

If you want to connect to the python application container, use the shell.sh in the rood directory of the project:

./shell.sh

If you get an error while runing this script, you can either:

Run it with sh shell.sh
Apply chmod u+x shell.sh on it
Use the "classical" way to connect a container using docker exec

Connect to an other container

In order to connect a running container, first, you need to get its ID:

docker ps

Once you spotted the corresponding container in the prompted table, copy its ID. Then, connect to it via:

docker exec -it [CONTAINER_ID_GOES_HERE] /bin/bash

quentinfayet / python-language