Python Client

dalux-build is a lightweight Python client for the Dalux Build REST API. Requires Python 3.10+ and requests ≥ 2.28.

pip install dalux-build

from dalux_build import create_client

dalux = create_client(
    base_url="https://<your-company>.dalux.com/api",
    api_key="YOUR_API_KEY",
)

projects = dalux.projects.list_projects()
tasks = dalux.tasks.get_project_tasks(project_id="my-project-id")

The returned DaluxClient exposes one attribute per API resource group (projects, tasks, files, forms, …) — 16 in total, see API Reference for the full list, or python/README.md#api-reference for every method and path.

Note: The Python client recently refactored pagination methods to make pagination the default behavior with cleaner names (e.g., get_files() instead of get_all_files()). See the Migration Guide for details. Old method names are still supported with deprecation warnings for backward compatibility.

Client-level defaults

Most methods take project_id (and file_area_id) as keyword-only args. Set defaults once if you mostly work against one project:

dalux = create_client(
    base_url="https://<your-company>.dalux.com/api",
    api_key="YOUR_API_KEY",
    project_id="my-project-id",       # or env var DALUX_PROJECT_ID
    file_area_id="my-file-area-id",   # or env var DALUX_FILE_AREA_ID
)

dalux.tasks.get_project_tasks()                          # uses the default
dalux.tasks.get_project_tasks(project_id="other-project") # explicit wins

full_response and to_dataframe

List methods default to returning a plain list[...]. Pass full_response=True for the full response model (.metadata, .links), or to_dataframe=True to flatten items directly into a pandas DataFrame (nested fields become ::-separated columns, e.g. owner::userId):

df = dalux.tasks.get_project_tasks(project_id="p1", to_dataframe=True)
df.columns  # Index(['taskId', 'title', 'type::typeId', ...])

pandas is required only if you use to_dataframe=True (pip install pandas).

Embedded webhook server

dalux.webhook_server runs the same polling scheduler and management API as the standalone webhook server, embedded directly in a Python process — no separate deployment:

from cryptography.fernet import Fernet

dalux.webhook_server.start(
    management_token="local-admin-token",
    master_key=Fernet.generate_key().decode(),
    state_db_path="monitor.sqlite3",
)
job_id = dalux.webhook_server.register_change_job(
    project_id="p1", file_area_id="fa1", cron="*/15 * * * *",
    scope="fileIds", file_ids=["f1"], initial_run="baseline",
    callback_url="https://n8n.example/webhook/dalux",
)

Full details: python/docs/webhook_server.md.

Error handling

All methods raise requests.HTTPError on 4xx/5xx:

import requests
try:
    dalux.projects.get_project(project_id="unknown-id")
except requests.HTTPError as exc:
    print(exc.response.status_code, exc.response.json())

Full reference

See python/README.md for: every API namespace with method/HTTP/path tables, individual API-class instantiation, and testing instructions.