A Python package for efficient storage, manipulation, and analysis of mining block models using Parquet files.
Project description
parq-blockmodel
Overview
A Python package for efficient storage, manipulation, and analysis of mining block models using Parquet files. parq-blockmodel provides tools for reading, writing, indexing, and transforming large-scale block model datasets, leveraging the performance of Apache Arrow and Parquet for scalable geoscience data workflows.
Installation
Install the base package from PyPI:
pip install parq-blockmodel
Install the optional schema validation support when you want to validate block model attributes with Pandera schemas or load schema definitions from YAML:
pip install "parq-blockmodel[schema]"
Schema validation
ParquetBlockModel accepts an optional schema= argument on its main
constructors. You can pass either a Pandera DataFrameSchema object or a path
to a YAML schema file, then validate the resulting model in chunks:
from pathlib import Path
from parq_blockmodel import ParquetBlockModel
pbm = ParquetBlockModel.from_parquet(
Path("path/to/blockmodel.parquet"),
schema=Path("schemas/blockmodel.schema.yaml"),
)
pbm.validate()
pbm.validate(sample_chunks=1) # quick spot-check for large models
See the installation guide and user guide for more detail.
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