TIDAS Python SDK

中文文档

Type-safe Python SDK for working with ILCD/TIDAS life-cycle assessment (LCA) data. It provides generated Pydantic models plus higher-level helpers so you can read, manipulate, validate and export ILCD-compatible datasets from Python.

Installation

From PyPI

pip install tidas-sdk

From source (this repository)

cd sdks/python
uv sync --group dev

Quick Start

Run the end-to-end sample to see the core features in action:

uv run python examples/usage.py

Minimal usage example:

from tidas_sdk import create_process

process = create_process({})
process.process_data_set.process_information.data_set_information.name.base_name.set_text(
    "Sample Process", lang="en"
)

print(process.to_json())

Basic Usage

Creating entities

from tidas_sdk import create_process, create_flow, create_source

process = create_process({})
flow = create_flow({})
source = create_source({})

You can also build entities directly from ILCD‑style JSON:

from pathlib import Path
from tidas_sdk import create_process_from_json

process = create_process_from_json(Path("process.json"))

Or start from ILCD XML when you already have the canonical .xml datasets:

from pathlib import Path
from tidas_sdk import create_process_from_xml, TidasProcess

process = create_process_from_xml(Path("process.xml"))
# or, if you prefer to work with the class directly
process = TidasProcess.from_xml(Path("process.xml"))

Working with multilingual fields

name_list = process.process_data_set.process_information.data_set_information.name.base_name
name_list.set_text("Sample Process", lang="en")
name_list.set_text("示例工艺", lang="zh")
print(name_list.get_text("en"))

Validation and export

is_valid = process.validate()          # Pydantic (and optional JSON Schema) validation
json_payload = process.to_json()       # ILCD‑compatible dict
xml_payload = process.to_xml()         # ILCD XML string

Main Features

• JSON ➜ Object: create_process() and other factory helpers build rich entity objects from complete or partial ILCD JSON.
• Object ➜ JSON: to_json() returns ILCD-compatible dictionaries suitable for storage or downstream tooling.
• Multilingual fields: MultiLangList with set_text() / get_text() simplifies @xml:lang / #text handling.
• Strong typing: generated Pydantic models expose full type hints for IDE autocompletion and static checking.
• On-demand validation: validate() runs Pydantic and optional JSON Schema validation when your dataset is ready.
• XML export: to_xml() converts entities into ILCD XML for interoperability with other LCA systems.

See examples/usage.py for a step‑by‑step walkthrough of these features.

Development Workflow (for contributors)

# Install / update dependencies
uv sync --group dev

# Linting & formatting
uv run ruff check src
uv run ruff format src

# Type checking
uv run mypy src

# Tests
uv run pytest

Project Layout

• src/tidas_sdk: Core implementation and generated models
• examples/usage.py: Feature walkthrough used in this README
• scripts/: Utility scripts for code generation and maintenance

For questions or contributions, open an issue or pull request at https://github.com/tiangong-lca/tidas-sdk.