This is fhirclient, a flexible Python client for FHIR servers supporting the SMART on FHIR protocol. The client is compatible with Python 2.7.10 and Python 3.
Client versioning is not identical to FHIR versioning.
The master
branch is usually on the latest version of the client as shown below, possibly on bugfix releases thereof.
See the develop
branch for models that are closer to the latest FHIR continuous integration builds.
Version | FHIR | |
---|---|---|
1.0.3 | 1.0.2 |
(DSTU 2) |
1.0 | 1.0.1 |
(DSTU 2) |
0.5 | 0.5.0.5149 |
(DSTU 2 Ballot, May 2015) |
0.0.4 | 0.0.82.2943 |
(DSTU 1) |
0.0.3 | 0.0.82.2943 |
(DSTU 1) |
0.0.2 | 0.0.82.2943 |
(DSTU 1) |
pip install fhirclient
Technical documentation is available at docs.smarthealthit.org/client-py/.
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.
To read a given patient from an open FHIR server, you can use:
from fhirclient import client
settings = {
'app_id': 'my_web_app',
'api_base': 'https://fhir-open-api-dstu2.smarthealthit.org'
}
smart = client.FHIRClient(settings=settings)
import fhirclient.models.patient as p
patient = p.Patient.read('hca-pat-1', smart.server)
patient.birthDate.isostring
# '1963-06-12'
smart.human_name(patient.name[0])
# 'Christy Ebert'
If this is a protected server, you will first have to send your user to the authorize 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, it will however not retrieve the server's Conformance statement and hence is only useful as a quick check whether the server instance is ready.
smart = client.FHIRClient(settings=settings)
smart.ready
# prints `False`
smart.prepare()
# prints `True` after fetching Conformance
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:
smart = server.FHIRServer(None, 'https://fhir-open-api-dstu2.smarthealthit.org')
import fhirclient.models.patient as p
patient = p.Patient.read('hca-pat-1', smart)
patient.name[0].given
# ['Christy']
You can also search for resources matching a particular set of criteria:
smart = client.FHIRClient(settings=settings)
import fhirclient.models.procedure as p
search = p.Procedure.where(struct={'subject': 'hca-pat-1', 'status': 'completed'})
procedures = search.perform_resources(smart.server)
for procedure in procedures:
procedure.as_json()
# {'status': u'completed', 'code': {'text': u'Lumpectomy w/ SN', ...
# to get the raw Bundle instead of resources only, you can use:
bundle = search.perform(smart.server)
The client contains data model classes, built using fhir-parser, that handle (de)serialization and allow to work with FHIR data in a Pythonic way. Starting with version 1.0.5, data model validity are enforced to a certain degree.
import fhirclient.models.patient as p
import fhirclient.models.humanname as hn
patient = p.Patient({'id': 'patient-1'})
patient.id
# prints `patient-1`
name = hn.HumanName()
name.given = ['Peter']
name.family = ['Parker']
patient.name = [name]
patient.as_json()
# prints patient's JSON representation, now with id and name
name.given = 'Peter'
patient.as_json()
# throws FHIRValidationError:
# {root}:
# name:
# given:
# Expecting property "given" on <class 'fhirclient.models.humanname.HumanName'> to be list, but is <class 'str'>
import json
import fhirclient.models.patient as p
with open('path/to/patient.json', 'r') as h:
pjs = json.load(h)
patient = p.Patient(pjs)
patient.name[0].given
# prints patient's given name array in the first `name` property
Take a look at flask_app.py
to see how you can use the client in a simple (Flask) app.
This app starts a webserver, listening on localhost:8000, and prompts you to login to our sandbox server and select a patient.
It then goes on to retrieve the selected patient's demographics and med prescriptions and lists them in a simple HTML page.
The Flask demo app has separate requirements. Clone the client-py repository, then best create a virtual environment and install the needed packages like so:
git clone https://github.com/smart-on-fhir/client-py.git
cd client-py
virtualenv -p python3 env
. env/bin/activate
pip install -r requirements_flask_app.txt
python flask_app.py
pip install -r requirements.txt
python setup.py sdist
python setup.py bdist_wheel
bumpversion patch
bumpversion minor
bumpversion major
Docs are generated with Doxygen and doxypypy.
You can install doxypypy via pip: pip install doxypypy
.
Then you can just run Doxygen, configuration is stored in the Doxyfile
.
Running Doxygen will put the generated documentation into docs
, the HTML files into docs/html
.
Those files make up the content of the gh-pages
branch.
I usually perform a second checkout of the gh-pages branch and copy the html files over, with:
doxygen
rsync -a docs/html/ ../client-py-web/
Using setuptools (Note: Alternatively, you can use twine https://pypi.python.org/pypi/twine/):
copy server.smarthealthit.org:/home/fhir/.pypirc to ~/.pypirc
python setup.py sdist
python setup.py bdist_wheel
python setup.py sdist upload -r pypi
python setup.py bdist_wheel upload -r pypi