def parse(self, limit=None):
        """
        Override Source.parse()
        Args:
            :param limit (int, optional) limit the number of rows processed
        Returns:
            :return None
        """
        if limit is not None:
            LOG.info("Only parsing first %d rows", limit)

        sgd_file = '/'.join((self.rawdir, self.files['sgd_phenotype']['file']))
        columns = [
            'Feature Name', 'Feature Type', 'Gene Name', 'SGDID', 'Reference',
            'Experiment Type', 'Mutant Type', 'Allele', 'Strain Background',
            'Phenotype', 'Chemical', 'Condition', 'Details', 'Reporter']
        sgd_df = pd.read_csv(sgd_file, sep='\t', names=columns)
        records = sgd_df.to_dict(orient='records')
        for index, assoc in enumerate(records):
            if isinstance(assoc['Gene Name'], str):
                if limit is not None and index > limit:
                    break
                self.make_association(assoc)

        return
def parse ( self , limit = None ) : if limit is not None : LOG . info ( "Only parsing first %d rows" , limit ) sgd_file = '/' . join ( ( self . rawdir , self . files [ 'sgd_phenotype' ] [ 'file' ] ) ) columns = [ 'Feature Name' , 'Feature Type' , 'Gene Name' , 'SGDID' , 'Reference' , 'Experiment Type' , 'Mutant Type' , 'Allele' , 'Strain Background' , 'Phenotype' , 'Chemical' , 'Condition' , 'Details' , 'Reporter' ] sgd_df = pd . read_csv ( sgd_file , sep = '\t' , names = columns ) records = sgd_df . to_dict ( orient = 'records' ) for index , assoc in enumerate ( records ) : if isinstance ( assoc [ 'Gene Name' ] , str ) : if limit is not None and index > limit : break self . make_association ( assoc ) return
Override Source.parse()
        Args:
            :param limit (int, optional) limit the number of rows processed
        Returns:
            :return None