import spark

from src.Helper_Function.sigma_dq_generate_dq_report import sigma_dq_generate_dq_report


def sigma_dq_check_isBoolean(target_column,target_table,Execution_Type='',meta={}):
    column = target_column
    dq_rule = 'isBoolean'

    boolean_values = ['True','False',0,1]

    if(Execution_Type == 'Incremental'):
      StrSQl = "select "+target_column+",case when "+target_column+" in ("+','.join("'"+str(x)+"'" for x in boolean_values)+") then 'PASS' else 'FAIL' end as            DQ_Status from  "+target_table+ " WHERE "+target_table+"."+"dqAction = 'NA'" 
    else:
      StrSQl = "select "+target_column+",case when "+target_column+" in ("+','.join("'"+str(x)+"'" for x in boolean_values)+") then 'PASS' else 'FAIL' end as            DQ_Status from  "+target_table+ "  "

    
    dq_apply_column_data = spark.sql(StrSQl)
    
    dq_report = sigma_dq_generate_dq_report(dq_apply_column_data,column,dq_rule)
  
    return dq_report
