SMART FHIR Client

This is fhirclient, a flexible Python client for FHIR servers supporting the SMART on FHIR protocol.

Client versioning is not identical to FHIR versioning. The main branch is usually on the latest version of the client, as shown below, and possibly on their bugfix releases. The develop branch should be on recent freezes, and the feature/latest-ci branch is periodically updated to the latest FHIR continuous integration builds.

Installation

pip install fhirclient

Documentation

Technical documentation is available at docs.smarthealthit.org/client-py/.

Client Use

To connect to a SMART on FHIR server (or any open FHIR server), you can use the FHIRClient class. It will initialize and handle a FHIRServer instance, your actual handle to the FHIR server you'd like to access.

Read Data from Server

To read a given patient from an open FHIR server, you can use:

from fhirclient import client
from fhirclient.models.patient import Patient

settings = {
    'app_id': 'my_web_app',
    'api_base': 'https://r4.smarthealthit.org'
}
smart = client.FHIRClient(settings=settings)

patient = Patient.read('2cda5aad-e409-4070-9a15-e1c35c46ed5a', smart.server)
print(patient.birthDate.isostring)
# '1992-07-03'
print(smart.human_name(patient.name[0]))
# 'Mr. steve Smith'

If this is a protected server, you will first have to send your user to the authorization endpoint to log in. Just call smart.authorize_url to obtain the correct URL. You can use smart.prepare(), which will return False if the server is protected and you need to authorize. The smart.ready property has the same purpose. However, it will not retrieve the server's CapabilityStatement resource and hence is only fit as a quick check whether the server instance is ready.

from fhirclient import client

settings = {
    'app_id': 'my_web_app',
    'api_base': 'https://r4.smarthealthit.org'
}
smart = client.FHIRClient(settings=settings)

smart.ready
# prints `False`
smart.prepare()
# prints `True` after fetching CapabilityStatement
smart.ready
# prints `True`
smart.prepare()
# prints `True` immediately
smart.authorize_url
# is `None`

You can work with the FHIRServer class directly without using FHIRClient. But this is not recommended:

from fhirclient import server
from fhirclient.models.patient import Patient

smart = server.FHIRServer(None, 'https://r4.smarthealthit.org')
patient = Patient.read('2cda5aad-e409-4070-9a15-e1c35c46ed5a', smart)
print(patient.name[0].given)
# ['steve']

Search Records on Server

You can also search for resources matching a particular set of criteria:

from fhirclient import client
from fhirclient.models.encounter import Encounter
from fhirclient.models.procedure import Procedure

settings = {
    'app_id': 'my_web_app',
    'api_base': 'https://r4.smarthealthit.org'
}
smart = client.FHIRClient(settings=settings)

search = Encounter.where(struct={'subject': '2cda5aad-e409-4070-9a15-e1c35c46ed5a', 'status': 'finished'})
print({res.type[0].text for res in search.perform_resources_iter(smart.server)})
# {'Encounter for symptom', 'Encounter for check up (procedure)'}

# to include the resources referred to by the encounter via `subject` in the results
search = search.include('subject')
print({res.resource_type for res in search.perform_resources_iter(smart.server)})
# {'Encounter', 'Patient'}

# to include the Procedure resources which refer to the encounter via `encounter`
search = search.include('encounter', Procedure, reverse=True)
print({res.resource_type for res in search.perform_resources_iter(smart.server)})
# {'Encounter', 'Patient', 'Procedure'}

# to get the raw Bundles instead of resources only, you can use:
bundles = search.perform_iter(smart.server)
print({entry.resource.resource_type for bundle in bundles for entry in bundle.entry})
# {'Encounter', 'Patient', 'Procedure'}

Data Model Use

The client contains data model classes, built using fhir-parser, that handle (de)serialization and allow you to work with FHIR data in a Pythonic way. From version 1.0.5, the validity of the data model is enforced to a certain extent.

Initialize Data Model

from fhirclient.models.patient import Patient
from fhirclient.models.humanname import HumanName

patient = Patient({'id': 'patient-1'})
print(patient.id)
# patient-1

name = HumanName()
name.given = ['Peter']
name.family = 'Parker'
patient.name = [name]
print(patient.as_json())
# {'id': 'patient-1', 'name': [{'family': 'Parker', 'given': ['Peter']}], 'resourceType': 'Patient'}

name.given = 'Peter'
print(patient.as_json())
# throws FHIRValidationError:
# {root}:
#   name.0:
#     given:
#       Expecting property "given" on <class 'fhirclient.models.humanname.HumanName'> to be list, but is <class 'str'>

Initialize from JSON

import json
from fhirclient.models.patient import Patient

pjs = json.loads('{"name": [{"given": ["Peter"]}], "resourceType": "Patient"}')
patient = Patient(pjs)
print(patient.name[0].given)
# ['Peter']

Flask App

Take a look at flask_app.py to see how you can use the client in a simple (Flask) app.

This demo requires a server that is capable of SMART OAuth logins for patients, so make sure you have such a server ready first.

This app will start a web server, listen on localhost:8000, and prompt you to log in to our sandbox server and select a patient. It then retrieves the selected patient's demographics and med prescriptions and lists them on a simple HTML page.

The Flask demo app has separate requirements. Clone the client-py repository, then create a virtual environment (not compulsory but recommended) and install the needed packages as shown:

git clone https://github.com/smart-on-fhir/client-py.git
cd client-py/demos/flask
python3 -m venv env
. env/bin/activate
pip install -r requirements.txt
# Edit flask_app.py and put your own server's URL as api_base.
./flask_app.py

See Also

• cumulus-fhir-support: similar network client, with more authentication options and built-in retries, but no FHIR classes
• fhir.resources: similar FHIR classes, but has no network client
• fhirpy: similar FHIR classes and network client, with async options, but has no OAuth support
• smart-fetch: is a CLI command instead of a Python library, but supports bulk export and REST requests