SHARE is creating a free, open dataset of research (meta)data.

http://share-research.readthedocs.io/en/latest/index.html

https://osf.io/sdxvj/

It is useful to set up a virtual environment to ensure python3 is your designated version of python and make the python requirements specific to this project.

mkvirtualenv share -p `which python3.5`
workon share

Once in the share virtual environment, install the necessary requirements.

pip install -r requirements.txt

docker-compose assumes Docker is installed and running. docker-compose up -d web creates and starts containers for elasticsearch, rabbitmq, and postgres. Finally, ./up.sh ensures everything has been installed properly.

docker-compose up -d web
./up.sh

---------------- or ----------------

pg
createuser share
psql
    CREATE DATABASE share;
python manage.py makemigrations
python manage.py maketriggermigrations
python manage.py makeprovidermigrations
python manage.py migrate
python manage.py createsuperuser

Run the API server

python manage.py runserver

Run Celery

python manage.py celery worker -l DEBUG

This is particularly applicable to running ember-share, an interface for SHARE.

Harvest data from providers, for example

./manage.py harvest com.nature --async
./manage.py harvest io.osf --async

Pass data to elasticsearch with runbot. Rerunning this command will get the most recently harvested data. This can take a minute or two to finish.

./manage.py runbot elasticsearch

cd docs/
pip install -r requirements.txt
make watch