for wordlistdata_id in cr.wordlistdata_ids_for_bibtex_key(source) for concept, counterpart in cr.concepts_with_counterparts_for_wordlistdata_id(wordlistdata_id) ) # print header print("wordlist_id"+"\t"+"language_book_name"+"\t"+"concept"+"\t"+"counterpart"+"\t"+"graphemic_parse"+"\t"+"ipa_parse"+"\t"+"orthographic_rules_parse") err_count = 0 errors = "" # print all the things! for wordlistdata_id, concept, counterpart in wordlist_iterator: # counterpart = unicodedata.normalize("NFD", counterpart) grapheme_parsed_counterpart_tuple = o.parse_string_to_graphemes_string(counterpart) phoneme_parsed_counterpart_tuple = o.parse_string_to_ipa_string(counterpart) if grapheme_parsed_counterpart_tuple[0] == False: report_unparsables(wordlistdata_id, concept, counterpart, grapheme_parsed_counterpart_tuple) continue if phoneme_parsed_counterpart_tuple[0] == False: report_unparsables(wordlistdata_id, concept, counterpart, phoneme_parsed_counterpart_tuple) continue grapheme_parse = grapheme_parsed_counterpart_tuple[1] phoneme_parse = phoneme_parsed_counterpart_tuple[1] rule_parsed_grapheme_parse = rules.parse_string(grapheme_parse) print(wordlistdata_id+"\t"+cr.get_language_bookname_for_wordlistdata_id(wordlistdata_id)+"\t"+concept+"\t"+counterpart+"\t"+grapheme_parse+"\t"+phoneme_parse+"\t"+rule_parsed_grapheme_parse)