Readme for LOFAR pipeline REST Api

This is an experiment to see if we can make the LOFAR data more accessible. This is a django REST api using the django rest_framework.

Get it working

Download this repo
Create a venv in which you want to do your things (using python3) or use conda
Install django (e.g. pip install django)
Install the rest_framework (e.g. pip install djangorestframework)
Install all the pipelines (as of 27JUN18 this is: https://github.com/EOSC-LOFAR/LGPPP_LOFAR_pipeline)
Navigate to the folder containing the manage.py
Start your local host: python manage.py runserver
You can now send http requests to the localhost:8000. For example in your browser: localhost:8000/sessions/

Install

Requirements:

git
pipenv, https://docs.pipenv.org/

Run the following commands to install

git clone https://github.com/EOSC-LOFAR/lofar_workflow_api.git
cd lofar_workflow_api
pipenv install
pipenv shell
cd lofar_workflow_api/

Run

Start web service with following command:

python manage.py runserver

Goto http://localhost:8000/sessions

Follow an example

Check out the jupyter notebook: example_for_lofar_pilot_REST_api.ipynb.

Current models in the api

Session: a session that will run a pipeline on an observation
pipelineschemas: this gives you a list with implemented pipelines and configuration schemas.
A post of a session using the request package could look like this:

	data = {
			"email": "pipo@popo.com",
			"description": "Add your description to figure out later what this is.",
			"pipeline" : "LGPPP_LOFAR_pipeline",
			"config": "{\"avg_freq_step\": 1, \"avg_time_step\": 1, \"do_demix\": 1, \"demix_freq_step\": 1, \"demix_time_step\": 1, \"demix_sources\": 1, \"select_NL\": 1,\"parset\": 1}",
			"observation": "an observation code",
			}
	response = s.post('http://localhost:8000/sessions/', data=data)

You can do a get to pipelineschemas to get a json with pipelines and their schemas like this:

	response = s.get('http://localhost:8000/pipelineschemas/')
	response_data = response.json()
	pp.pprint(response_data)

Adding your own pipeline

Please follow the intructions at the pipeline template python package: https://github.com/EOSC-LOFAR/LOFAR_pipeline_template