virtualenv -p /usr/bin/python2.7 venv
source venv/bin/activate`
pip install -r requirements.txt
python -m nltk.downloader all
cp example.config.ini config.ini
apt-get install -y libpq-dev
apt-get install python-tk
python server/manage.py migrate
python server/start_server.py
docker build -t git_better .
docker run -d -p 8000:8000 git_better
To predict repository labels based on your own training data or based on pre-trained models, follow the instructions of our main script:
python app/main.py --help
As an example, to classify the input data from the challenge repository using our pre-trained models, run
python app/main.py -i data/example-input.txt
To visualize the data with the TensorBoard Embedding Projector, run python app/embedding_visualization.py
and start tensorboard with tensorboard --logdir log/
. Tensorboard will display the port on which the server listens, open localhost:[port]
with your browser (standard port is 6006).
To test whether the app works correctly, simply run python -m unittest discover
docker build -t git_better .
docker tag git_better registry.heroku.com/git-better/web
docker push registry.heroku.com/git-better/web
heroku open