zeolite 0.1.3

A library to process raw data into a structured format

⚗️ Zeolite

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Zeolite is a Python library that uses a simple configuration approach to define a table/schema structure. Raw data can normalised, cleaned, and validated against the schema in a performant and standardised way.

The final datasets are guaranteed to be in the correct format and can be easily exported to a variety of formats. In addition, Zeolite captures errors and warnings during the processing of the data, which can be used to improve the quality of the data.

Example

import zeolite as z

individual_schema = z.schema("individual").columns(
    z.str_col("id")
    .clean(to="id", prefix="ORG_X::")
    .validations(
        z.check_is_value_empty(warning="any", error=0.1, reject=0.01, treat_empty_strings_as_null=True),
        z.check_is_value_duplicated(check_on_cleaned=True, reject="any"),
    ),
    
    z.str_col("birthdate")
    .clean(to="date")
    .validations(z.check_is_value_invalid_date(reject="all")),
    
    z.str_col("gender").clean(
        to="enum",
        sanitize="lowercase",
        enum_map={
            "m": "Male", "male": "Male",
            "f": "Female", "female": "Female",  
            "d":"Gender Diverse", "diverse": "Gender Diverse"
        },
    ),
    
    z.str_col("is_active").clean(
        to="boolean", 
        true_values={"yes", "active"}, false_values={"no", "inactive"}
    ),
    
    z.str_col("ethnicity").clean(to="sanitised_string"),
    z.str_col("ethnicity_2").clean(to="sanitised_string"),
    z.derived_col(
        "is_maori",
        function=(
            z.ref("ethnicity").clean().col.eq("maori")
            | z.ref("ethnicity_2").clean().col.eq("maori")
        ),
        data_type="boolean",
    ),
)