Pulire

A lightweight DataFrame validation library for Pandas.

Auto Formatting

poetry run black .

Testing

Run the following command for unit tests:

poetry run pytest tests

Schema

Pulire requires a Schema which describes all columns in a given DataFrame.

from pulire import Schema, Column, validators, formatters

Schema([
    Column("temp", "Float64", [
        validators.minimum(-80),
        validators.maximum(65),
        formatters.decimals(1)
    ])
])

Validate

Pulire automatically removes values which fail the validation. Let's use the meteostat library to get some data:

from datetime import datetime
from meteostat import Hourly

df = Hourly("10637", datetime(2018, 1, 1), datetime(2018, 1, 1, 23, 59)).fetch()

print(df)

Now, we can get a valid copy of our Meteostat DataFrame by running our schema's validate method:

df = myschema.validate(df)

Lazy Validations

try:
    schema.validate(df, lazy=True)
except ValueError as error:
    print(error.args[0])

Key dates

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  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for meteostat from gravatar.com meteostat

Credits

PyPI data
Data sourced directly from PyPI's database.

Author: Meteostat

Requires

Python <4.0, >=3.9

Classifiers

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