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#Instructions

##Running on Docker's containers

You will need to use docker-compose, that can be installed following this documentation Docker Installation

git clone  git@github.com:gustavoalmeida/fullstack-coding-challenge.git
cd ./fullstack-coding-challenge
docker-compose up

##Running on localhost

For this project you need to have a little knowledge of Redis and Mongo. Because both servers will have to stay running before to run this app

To run on localhost you will need Python 2.7+, Virtualenv, Redis, MongoDB

To start the project, first you need to ensure that the redis server and the mongoDb is running.

We created a autorun that will to configure your unbabel api credentials, install requirements of environment and start Flask App, Celery Beat and Flower Monitor This will configure also your Unbabel Sandbox credentials in ~/.unbabel file

So clone the project repository and run run_app.sh file

git clone git@github.com:gustavoalmeida/fullstack-coding-challenge.git
cd ./fullstack-coding-challenge
source run_app.sh

##Celery

We use Celery to work with our asynchronous task queue/job. It's very easy to use. And do the job very well.

####To run celery

git clone git@github.com:gustavoalmeida/fullstack-coding-challenge.git
cd ./fullstack-coding-challenge
source run_celery.sh

##Flower Monitor

Flower is a very nice monitor for to see what is happening with celery workers.

####To run flower

git clone git@github.com:gustavoalmeida/fullstack-coding-challenge.git
cd ./fullstack-coding-challenge
source run_celery.sh

To access Flower Monitor, put your prowser on http://127.0.0.1:5555/

Testing

Run the tests by using this code Make sure that you have configured your Unbabel credentials at ~/.unbabel. If you have not done that, please first use run_app.sh before this.

git clone git@github.com:gustavoalmeida/fullstack-coding-challenge.git
cd ./fullstack-coding-challenge/hackernews/hackernewsclone
virtualenv .venv
source ./venv/bin/activate
pip install -r requirements.txt
pytest

To Do

  1. Put translations in separate collection
  2. Improve performance for comments and translations
  3. Show nested comments