Jupyter notebook and web UI for modelling visualising DNA concentration over time.
While developing the workflow, we are using a Jupyter notebook. Assuming you have your Python sci dev environment set up (Python 3.5 was used during development), you can start it from the root of the git repository with:
jupyter notebook --notebook-dir=./notebook
And see it in your browser at http://127.0.0.1:8888/.
If you just want to view the contents, you can see it here without installing anything.
Assuming a Python sci/dev environment, which would on e.g. OS X be more or less:
-
install OS X command line tools (or Xcode)
-
install Homebrew
-
install some binary dependencies
brew install python3 gcc freetype -
install some Python global dependencies
pip install virtualenvwrapper
Get ready:
mkvirtualenv -p /usr/bin/python3 TruePCR
pip install -r requirements/dev.txt
npm install
bower install
grunt build
See if any migrations are necessary:
./manage.py migrate
Link up your front+backend:
util/bootstrap.sh
Then in one tab spin up the frontend workflow:
grunt serve
And in another the backend workflow:
./manage.py runserver_plus
Everything the same, except:
pip install -r requirements/prod.txt
util/boostrap.sh prod
Or use the prod brunch:
grunt publish
cd prod
git checkout prod
./manage.py runserver
To deploy to Heroku, from the repo root run:
grunt publish
(cd prod; git push heroku prod:master)