PyHiveLMS 1.1.1

Python bindings for Hive

PyHive — a minimal Hive API client for Python

PyHive (package: PyHiveLMS) is a small, synchronous Python client for the Hive API. It provides:

• A simple HiveClient you use as a context manager to handle authentication and the HTTP session.
• Generator-based list endpoints for memory-efficient iteration of large result sets.

Supported Hive Versions

• 5.1.2
• 6.2.0

Install

Install from PyPI. It's recommended to use a virtual environment.

Using pip (PyPI):

pip install PyHiveLMS

Quickstart — connect and list resources

The primary entry point is HiveClient. It accepts your Hive username, password and the base URL for your Hive instance. Use it as a context manager to ensure the underlying HTTP session is closed cleanly.

Example — list programs and print name/ID:

from pyhive import HiveClient

USERNAME = "Mentor123"
PASSWORD = "Password1"
HIVE_URL = "https://hive.org"

with HiveClient(USERNAME, PASSWORD, HIVE_URL) as client:
	for program in client.get_programs():
		print(program.id, program.name)

Example — fetch a program, its subjects and modules:

from pyhive import HiveClient

with HiveClient(USERNAME, PASSWORD, HIVE_URL) as client:
	program = client.get_program(42)
	print("Program:", program.name)

	# list subjects for the same program
	subjects = list(client.get_subjects(parent_program__id__in=[program.id]))
	for subject in subjects:
		print(" -", subject.id, subject.name)

	# modules for the first subject
	if subjects:
		for module in client.get_modules(parent_subject=subjects[0]):
			print("   *", module.id, module.name)

Example — find exercises in a module and read their form fields:

with HiveClient(USERNAME, PASSWORD, HIVE_URL) as client:
	# you can pass ids or model objects to filter helpers
	module = client.get_module(123)
	for exercise in client.get_exercises(parent_module=module):
		print(exercise.id, exercise.name)
		for field in client.get_exercise_fields(exercise):
			print("     field:", field.id, field.label)

Example — list assignments for a user and read responses:

with HiveClient(USERNAME, PASSWORD, HIVE_URL) as client:
	assignments = client.get_assignments(user__id__in=[55])
	for a in assignments:
		print("Assignment:", a.id, a.exercise_name)
		for resp in client.get_assignment_responses(a):
			print("  response:", resp.id, resp.submitted_by)

Filtering and convenience

• List endpoints (get_programs, get_subjects, get_modules, get_exercises, get_assignments, get_users, etc.) accept filter keyword arguments that are forwarded to the API. Use id__in, parent_program__id__in, queue__id, and the other documented kwargs to restrict results.
• Many methods accept either an integer id or a model instance. For example client.get_exercise_fields(exercise_id_or_model) accepts either.

Error handling

Network and HTTP errors are surfaced from the underlying httpx client. Typical patterns:

from httpx import HTTPError

try:
	with HiveClient(USERNAME, PASSWORD, HIVE_URL) as client:
		programs = list(client.get_programs())
except HTTPError as exc:
	print("Network/HTTP error:", exc)

Model parsing errors will raise normal Python exceptions — wrap calls where you need robust failure handling.

Common methods (short reference)

• HiveClient(username, password, hive_url, **kwargs) — construct and authenticate client
• get_programs(...)
• get_program(program_id)
• get_subjects(...)
• get_modules(...)
• get_exercises(...)
• get_exercise(exercise_id)
• get_exercise_fields(exercise)
• get_assignments(...)
• get_assignment(assignment_id)
• get_assignment_responses(assignment)
• get_users(...)
• get_classes(...)

Return values are typed model objects from src/types or generators of those objects.

Try it locally / Run tests

Install dev dependencies and run tests with pytest:

pip install -e .
pytest -q

Troubleshooting

• Authentication errors: verify username/password and the hive_url base. The client authenticates at construction.
• SSL verification: pass verify=False to the client constructor for self-signed servers (not recommended for production).

Contributing & development

• Tests live under tests/ and show common usage patterns. Use them as examples.
• The typed models are in src/types and the HiveClient convenience layer is in pyhive/client.py.

If you plan to make changes, please add tests for new behavior and keep changes small and focused.