glpi-python-client is a typed Python client for GLPI ITSM APIs.
The goal is to let GLPI integrations work with domain objects instead of raw JSON payloads. The package exposes Pydantic models for tickets, users, followups, documents, locations, and related records, while converting GLPI HTML content into Markdown for Python-side workflows and rendering Markdown back to HTML for outgoing payloads.
It currently focuses on ticket-centric workflows and exposes matching sync and async high-level clients.
pip install glpi-python-clientFor local development:
python -m pip install -e .[dev]
python -m pytestCreate a client with your GLPI API URL and at least one complete auth pair:
client_idandclient_secretusernameandpassword- both pairs together
from glpi_python_client import GlpiClient, GlpiTicket
with GlpiClient(
glpi_api_url="https://glpi.example.com/api.php",
client_id="oauth-client-id",
client_secret="oauth-client-secret",
username="api-user",
password="api-password",
) as glpi:
ticket_id = glpi.create_ticket(
GlpiTicket(
name="Printer issue",
content="The printer is not reachable from the office network.",
urgency=3,
impact=3,
)
)
ticket = glpi.get_ticket_record(ticket_id)
print(ticket.id)
print(ticket.content)Async code uses the same model layer and nearly the same API surface:
from glpi_python_client import AsyncGlpiClient
async with AsyncGlpiClient(
glpi_api_url="https://glpi.example.com/api.php",
client_id="oauth-client-id",
client_secret="oauth-client-secret",
) as glpi:
tickets = await glpi.search_ticket_records(query='status.id=in=(1,2)')If your application already provides GLPI_ environment variables,
GlpiClient.from_env() and AsyncGlpiClient.from_env() are also available.
To build the Sphinx documentation locally:
python -m pip install -e .[docs]
python -m sphinx -b html docs docs/_build/html