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A wrapper for the drchrono API

Project description

drchrono-wrapper

Requirements

  • checkout the requirements.txt file
  • min. python version: 3.10 because of switch statement utilization that is only available starting with python 3.10

API token requirement

  • please visit for more information on how to generate: https://app.drchrono.com/api-docs/#section/Authorization
  • first load in the package and set the API token:
    • from drchrono.drc import drc
    • load in API token from .env:
      • drc_client = drc(api_key=os.getenv('DRCHRONO_API_TOKEN'))
    • type in API token manually (not recommended):
      • drc_client = drc(api_key=123321asddsa321123)

Endpoints currently covered:

  • Fake data generation:

    • Admin:
      • Users
      • Doctors
    • Clinical:
      • Patients
      • Appointments
  • Real data pulls:

    • Admin:
      • Users
      • Doctors
    • Clinical:
      • Patients
      • Appointments
      • Medications
      • Documents

Basic examples:

Getting real data:

  • Get all patients:
    • patient_all = drc_client.patients().patientlist
    • If you want additional metadata, like custom demographics, add on verbose_true=True
      • patient_all = drc_client.patients().patientlist(verbose_true=True)
  • Get a single patient:
    • patient_single = drc_client.patients().patient_single(patient_id='200110461')
  • Get a list of all doctors:
    • doctor_list = drc_client.doctors().doctorlist
  • Get a list of all appointments (requires a specific start date):
    • appointments = drc_client.appointments().appointment_list(appointment_startdate='2019-01-01')
  • Pushing a existing pdf into a patient record as a document:
    • Load the file: files = {'document': open('src/new_test_myfile.pdf', 'rb')}
    • Send the data over: drc_client.documents().create_document(date='2017-01-01', description='testdocumentnov21_ANOTHER ONE' doctor=os.getenv('DRCHRONO_DOCTOR_ID'), patient=os.getenv('DRCHRONO_PATIENT_ID'), metatags='["fake-pdf", "document"]', document=files)

Generating fake dataset:

  • Fake dataset with linked patients and appointments; fake users and doctors;
    • f_users, f_doctors, f_patients, f_appointments = drc.faker().generate(20, 40, 150, 500)

Package admin:

  • Note to self, to create new version:
    • update setup.py version number
    • re-run python setup.py sdist to create new distribution
    • upload to pypi with twine upload dist/*

Project details


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