gxkent 0.1.0

An awesome package for GXKent.

GXKent

A simple library that allows Great Expectations to run easily in python notebook and CLI environments

Idea

Kent was the city featured in the Charles Dickens classic, and is therefore the sensible name for a container of expectations The central issue that Kent resolves is to ensure that pandas dataframes are available and populated with data in both of our data contexts: CLI and Notebooks

Usage

Kent = GXKent() Kent.is_print_on_success = False

sql_text = SELECT count(DISTINCT a.npi) AS new_npi_cnt FROM default_npi_setting_count.{table_name} a WHERE a.npi NOT IN ( SELECT DISTINCT b.npi FROM default_npi_setting_count.persetting_2021_12 b );

gxDF = Kent.gx_df_from_sql(sql_text)

Kent.capture_expectation( expectation_name='Between year comparision {this_year} {that_year}', expectation_result=gxDF.expect_column_max_to_be_between('new_npi_cnt',112671,253511) )

Kent.capture_expectation( expectation_name='Between year comparision {this_year} {that_year}', expectation_result=gxDF.expect_column_min_to_be_between('new_npi_cnt',11671,23511) )

Kent.capture_expectation( expectation_name='Between year comparision {this_year} {that_year}', expectation_result=gxDF.expect_column_avg_to_be_between('new_npi_cnt',50000,60000) )

Authors

Fred Trotter and Jose Cortina