Instalasi Eval AI di Ubuntu 17.10

Instalasi Eval AI di Ubuntu 17.10

Artikel ini adalah adaptasi dari prosedur instalasi di


apt-get install openssh-server
apt-get install net-tools

Instalasi software dependencies:

apt-get install python2.7
apt-get install git
apt-get install postgresql

# Success. You can now start the database server using:
# /usr/lib/postgresql/9.6/bin/pg_ctl -D /var/lib/postgresql/9.6/main -l logfile start

apt-get install rabbitmq-server
apt-get install virtualenv
apt-get install python-psycopg2 (thanks to
apt-get install libpq-dev
apt-get install python-dev
apt-get install build-essential

# clone the EvalAI code

git clone evalai

# Create a python virtual environment and install python dependencies.

cd evalai
virtualenv venv
source venv/bin/activate # run this command everytime before working on project
pip install -r requirements/dev.txt

Proses sampai tahap ini berhasil, selanjutnya masih perlu diujicoba:

cp settings/ settings/

Use your postgres username and password for fields USER and PASSWORD in file.

Create an empty postgres database and run database migration.

sudo -i -u (username)
createdb evalai
python migrate –

Seed the database with some fake data to work with.

python seed –

This command also creates a superuser(admin), a host user and a participant user with following credentials.

SUPERUSER- username: admin password: password
HOST USER- username: host password: password
PARTICIPANT USER- username: participant password: password

That’s it. Now you can run development server at (for serving backend)

python runserver –

Open a new terminal window with node(6.9.2) and ruby(gem) installed on your machine and type

npm install

Install bower(1.8.0) globally by running:

npm install -g bower

Now install the bower dependencies by running:

bower install

If you running npm install behind a proxy server, use

npm config set proxy http://proxy:port

Now to connect to dev server at (for serving frontend)

gulp dev:runserver

That’s it, Open web browser and hit the url

(Optional) If you want to see the whole game into play, then start the RabbitMQ worker in a new terminal window using the following command that consumes the submissions done for every challenge:

python scripts/workers/


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