eyesoft-api-client 0.1.0

No project description provided

Eyesoft API Client

Python client for the Eyesoft API.

Installation

pip install eyesoft-api-client

Quick start

from eyesoft_api_client import Client

with Client(
    base_url="https://api.example.com",
    username="user",
    password="pass",
    client_id="client_id",
    client_secret="client_secret",
) as client:
    patients = client.list_patients()
    print(patients[0].id)

Authentication

The client authenticates with the API using OAuth2 (username/password + client credentials). Tokens are managed automatically by the HTTP session.

Parameter	Description
base_url	Root URL of the API (no trailing slash)
username	User account login
password	User account password
client_id	OAuth2 client ID
client_secret	OAuth2 client secret

Usage

Patients

# List all patients
patients = client.list_patients()

# Fetch a single patient by UUID
patient = client.get_patient("550e8400-e29b-41d4-a716-446655440000")

# Access patient fields directly as attributes
print(patient.id, patient.name)

Exercises

# List all exercises for a patient
exercises = patient.list_exercises()

# Fetch a single exercise for a patient
exercise = patient.get_exercise("550e8400-e29b-41d4-a716-446655440001")

# Fetch raw exercise data (parsed JSON)
data = exercise.get_data()

# Or fetch exercise data directly from the client
data = client.get_exercise_data("550e8400-e29b-41d4-a716-446655440001")

Resource objects

Patient and Exercise objects proxy attribute access to the underlying API response, so any field returned by the API is accessible directly:

patient = client.get_patient("550e8400-e29b-41d4-a716-446655440000")
patient.id        # any field in the JSON response
patient["name"]   # dict-style access also works

Lifecycle

Use the client as a context manager (recommended) to ensure the underlying HTTP session is closed:

with Client(...) as client:
    ...

Or manage it manually:

client = Client(...)
try:
    ...
finally:
    client.close()

Development

Publishing

This project uses python-semantic-release with Conventional Commits for automated versioning and publishing to PyPI via GitLab CI.

Releases are triggered automatically on every push to the default branch when the commit history contains releasable changes:

Commit prefix	Version bump
fix: ...	Patch (0.1.0 → 0.1.1)
feat: ...	Minor (0.1.0 → 0.2.0)
feat!: ... / BREAKING CHANGE:	Major (0.1.0 → 1.0.0)