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)
