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A modular project with a core library and multiple adapters

Project description

pypeh

pypeh is a lightweight ETL and data-ops toolkit for Personal Exposure and Health (PEH) data.

It helps you:

  • work with PEH-model resources in Python
  • load/transform/validate PEH study data
  • support FAIR data workflows (findable, accessible, interoperable, reusable)

The toolkit is built to interact with the PEH model from PARC:

Install

Core package:

uv pip install pypeh

With dataframe adapter extras (Polars-based workflows):

uv pip install "pypeh[dataframe-adapter]"

Basic Usage

from pypeh import Session

# Start a session
session = Session()
# Load PEH model resources (e.g. YAML configs) into cache
session.load_persisted_cache(source="config")
# Load tabular data as a DatasetSeries using a DataImportConfig from cache
data_import_config = session.cache.get("<data_import_config_id>", "DataImportConfig")
dataset_series = session.load_tabular_dataset_series(
    source="my_data.xlsx",
    data_import_config=data_import_config,
)

From there you can use adapters for:

  • validation
  • enrichment (derived variables)
  • aggregation
  • export/persistence

Run Tests

make test-core
make test-dataframe
make test-rocrate

Documentation

Build the static documentation site with MkDocs:

make docs

Preview it locally:

make docs-serve

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