User_Guide_Python.md

Using Python

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Examples below follow the same pattern as those using curl. The requests library is recommended. Use Python shell to run the commands below, Jupyter Notebook or create and execute a .py file.

Data Discovery

Import following two libraries, define the endpoints - authentication is not needed for metadata discovery on local docker deployment

import requests
import json
import os

FDS_ENDPOINT="https://localhost:8443/federated-data-sharing/1.1.0"

In development, insecure SSL connections warnings can safely be ignored. Change verify=False to True as required.

Make a call to the /dataset/list endpoint, then print the result dictionary:

r = requests.get(f'{FDS_ENDPOINT}/datasets', verify=False)
dataset_list = r.json()
print(json.dumps(dataset_list, indent=4, sort_keys=True))

Choose 1st dataset for further exploration:

dataset_1 = dataset_list['datasets'][0]['id']

Request first dataset catalogue by making a get call to /catalogue endpoint:

r = requests.get(f'{FDS_ENDPOINT}/datasets/{dataset_1}/catalogue', verify=False)
catalogue = r.json()
print(json.dumps(catalogue, indent=4, sort_keys=True))

Request first dataset dictionary by making a get call to /dictionary endpoint:

r = requests.get(f'{FDS_ENDPOINT}/datasets/{dataset_1}/dictionaries', verify=False)
dictionaries = r.json()
print(json.dumps(dictionaries, indent=4, sort_keys=True))

Data Selection

Set the payload (Assuming you are in the top level folder of this project):

file = open('./src/examples/example-query.graphql', 'r')
query = file.read()

Verify if the request is valid:

headers = {'Content-type': 'plain/text', 'Accept': 'application/json' }
r = requests.post(f'{FDS_ENDPOINT}/selection/validate', data = query, headers=headers, verify=False)
valid = r.json() == 'True'

The response should be the simple JSON token "True" or "False".

Then if the request is valid, the selection can be made:

headers = {'Content-type': 'plain/text', 'Accept': 'application/json' }
r = requests.post(f'{FDS_ENDPOINT}/selection/select', data = query, headers=headers, verify=False)
data = r.json()

Tasks using federated computation

TODO - pending updating the task API

Next steps

• Back to the main page
• Look at some Worked examples