lca-algebraic-dev 1.1.1985003.dev0

This library provides a layer above brightway2 for defining parametric models and running super fast LCA for monte carlo analysis.

Introduction

This library is a layer above brightway2 designed for the definition of parametric inventories with fast computation of LCA impacts, suitable for monte-carlo / global sensitivity analysis

It integrates the magic of Sympy in order to write parametric formulas as regular Python expressions.

lca-algebraic provides a set of helper functions for :

• compact & human readable definition of activities :
  • search background (tech and biosphere) activities
  • create new foreground activities with parametrized amounts
  • parametrize / update existing background activities (extending the class Activity)
• Definition of parameters
• Fast computation of LCAs
• Computation of monte carlo method and global sensitivity analysis (Sobol indices)

Installation

We don't provide conda package anymore.

This packages is available via pip /pypi

1) Setup separate environement

First create a python environment, with Python [>=3.9] :

With Conda (or mamba)

conda env create -n lca python==3.10
conda activate lca

With virtual env

python3.10 -m venv .venv
source .venv/bin/activate

2) Install lca_algebraic

pip install lca_algebraic

Licence & Copyright

This library has been developed by OIE - MinesParistech, for the project INCER-ACV, lead by ADEME.

It is distributed under the BSD License

Mailing list

Please register to this dedicated mailing list to discuss the evolutions of this library and be informed of future releases :

[e-mail]

Documentation

Full documentation and example notebooks are hosted on readthedocs