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Project description
BonsaiT: an interface for BONSAI classifications
BonsaiT is a Python package for the standardization of classifications in Life-Cycle Assessment (LCA). It leverages NLP to aligns external classification systems with the BONSAI framework, ensuring data consistency across LCA datasets.
Key components include the Encoder
, which converts text to vectors via language models like Sentence Transformers and Hugging Face's BERT, and the BonsaiTransformer
, which identifies the BONSAI class most similar to a given source class through vector analysis and cosine similarity.
BonsaiT can be used to:
- Identify the BONSAI class most similar to a given source class.
- Translate classifications between different systems.
- Harmonize LCA data from different sources.
Installation
To get started with BonsaiT, install it via pip:
pip install bonsait
Quick start
Here is how to quickly implement BonsaiT in your project:
from bonsait import BonsaiTransformer
source_class = "electricity from coal"
# Set up the BonsaiTransformer
class_transformer = BonsaiTransformer()
# Perform the transformation to find the BONSAI equivalent
transformed_class = class_transformer.transform(source_class=source_class)
print(f"The source classification <{source_class}> is transformed into BONSAI classification: <{transformed_class}>")
License
BonsaiT is released under the MIT License
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