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Web application for monitoring EM results

Project description

Web application for monitoring EM results

Launching the development server

conda create --name=emhub python=3.8
conda activate emhub

cd ~/work/development
git clone git@github.com:3dem/emhub.git
git clone git@github.com:3dem/emhub-testdata.git

cd emhub
pip install -e .

export FLASK_APP=emhub
export FLASK_ENV=development
export EMHUB_TESTDATA=~/work/development/emhub-testdata
export EMHUB_INSTANCE=~/work/development/emhub/instance

# Now launch the built-in Flask development server:
flask run

# or with gunicorn:
gunicorn -k gevent --workers=2 'emhub:create_app()' --bind 0.0.0.0:8080

To initialize the db:

python -m emhub.data

Running tests

python -m unittest emhub.tests

Publishing the package to PyPI

In order to make the emhub available to install with pip install emhub, we need to:

python install twine restructuredtext-lint
cd emhub

# It might be a good idea to check the README.rst before uploading:
rst-lint README.rst

python setup.py sdist
twine upload dist/emhub-0.0.1a3.tar.gz

Creating a Docker image

A Dockerfile has been include to create Docker images.

cd emhub
docker build . -t emhub
docker run --rm -p 8080:8080 --name=emhub -v $PWD/instance:/instance

Upgrading Database model with Alembic

If we modify the database models, then an update/migration is required.

# Do changes in the model (data_models.py)

alembic revision --autogenerate

# Review the generated script

alembic upgrade head  # or use first the --sql option to see the commands

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