Skip to main content

Python library to build parametric LCA models from a configuration file.

Project description

🚀 LCA-Modeller

image image License: GPL v3

LCA-Modeller offers a streamlined interface to facilitate the creation of parametric LCA models with prospective capabilities. It builds on the open-source libraries lca-algebraic and premise, so having a basic understanding of these tools is recommended.

The core functionality of LCA-Modeller revolves around reading a user-provided configuration file that defines the LCA model. From this configuration file, LCA-Modeller generates a parametric LCA model with lca-algebraic, which can then be evaluated for any parameter values using lca-algebraic's built-in functions.
If prospective scenarios are provided, premise is used to adapt the EcoInvent database to future conditions. The parametric LCA model then interpolates the prospective databases to enable the evaluation for any year specified by the user.

Additional features include the definition of custom impact assessment methods and the ability to modify existing activities in the EcoInvent database by adding or updating flows.

📦 Installation

To install LCA-Modeller, setup a separate conda environment:

conda create -n lca_modeller python==3.10
conda activate lca_modeller

And pip install the package:

pip install lca-modeller

A tutorial notebook is provided in the notebooks directory to help you get started with LCA-Modeller.

✈️ Applications

LCA-Modeller is currently being used in the following projects:

  • AeroMAPS : Multidisciplinary Assessment of Prospective Scenarios for air transport.
  • FAST-UAV: Future Aircraft Sizing Tool - Unmanned Aerial Vehicles
  • FAST-OAD: Future Aircraft Sizing Tool - Overall Aircraft Design

🤝 Questions and contributions

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lca_modeller-0.1.3b0.tar.gz (41.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lca_modeller-0.1.3b0-py3-none-any.whl (47.8 kB view details)

Uploaded Python 3

File details

Details for the file lca_modeller-0.1.3b0.tar.gz.

File metadata

  • Download URL: lca_modeller-0.1.3b0.tar.gz
  • Upload date:
  • Size: 41.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.19 Linux/6.11.0-1018-azure

File hashes

Hashes for lca_modeller-0.1.3b0.tar.gz
Algorithm Hash digest
SHA256 e65f60e76f3e9ed6010a14b29689f40116db760f70d65cdd31c94024c5d123f3
MD5 455931889ca8fde04ca34c62edbb202e
BLAKE2b-256 e0fd4d1d68b82656dee9eff20435afb800ac0e1e89462d704186907535b350fe

See more details on using hashes here.

File details

Details for the file lca_modeller-0.1.3b0-py3-none-any.whl.

File metadata

  • Download URL: lca_modeller-0.1.3b0-py3-none-any.whl
  • Upload date:
  • Size: 47.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.19 Linux/6.11.0-1018-azure

File hashes

Hashes for lca_modeller-0.1.3b0-py3-none-any.whl
Algorithm Hash digest
SHA256 862495640a07072e140750ae5406f711e57391170aa0aba6ef36766eb803a149
MD5 d55bda6cc3b44c80aa52a3ca8f0983a1
BLAKE2b-256 cd464d1c748cf34ce20ca8a74d1633d4840dfff3e53ac987aca9749936b85e5b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page