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How to use given_keywords method in Gherkin-python

Best Python code snippet using gherkin-python

gherkin_template_processor.py

Source:gherkin_template_processor.py

1import json2print("Make sure script is run using python3")3def generate_keyword_body(keywords):4    first_keyword = keywords[0].replace("'", "\\'")5    body = "\n\t("6    body += "'" +  keywords[0].replace("'", "\\'") + "'"7    8    if len(body) > 1:9        for keyword in range(1,len(keywords)): 10            body += "\n\t\t| '{k}'".format(k=keywords[keyword].replace("'", "\\'"))11    body += "\n\t) "12    return body13 14language_data = json.load(open('languages/gherkin-languages.json'))15template = """lexer grammar GherkinLexer;16fragment LANGUAGE_KEYWORD : WS* '#' WS* 'language' WS* ':' WS*;17LANGUAGE_HEADER : LANGUAGE_KEYWORD 'en' LINE_END -> mode(DEFAULT_MODE) ;18"""19for language in language_data.keys():20    l = language_data[language]21    ul = language.upper().replace("-", "_")22    template += "\n" + ul + "_LANGUAGE_HEADER : LANGUAGE_KEYWORD '" + language + "' LINE_END -> mode(" + ul + "), type(LANGUAGE_HEADER) ;"23template += "\n//////////////////////////////////////////////////////////////////////////"24template += '''25FEATURE_KEYWORD : ('Feature'26	| 'Business Need'27	| 'Ability') ':' -> channel(HIDDEN) ;28SCENARIO_KEYWORD : ('Scenario' | 'Example') ':' -> channel(HIDDEN) ;29SCENARIO_OUTLINE_KEYWORD : 'Scenario Outline:' -> channel(HIDDEN);30BACKGROUND_KEYWORD : 'Background:' ;31EXAMPLES_KEYWORD : 'Examples:' | 'Scenarios:';32RULE_KEYWORD : 'Rule:' ;33STARTING_STEP_KEYWORD : GIVEN_KEYWORD34	| WHEN_KEYWORD35	| THEN_KEYWORD36	| WILD_KEYWORD37	;38ALTERNATIVE_STEP_KEYWORD : AND_KEYWORD39	| BUT_KEYWORD40	| GIVEN_KEYWORD41	;42GIVEN_KEYWORD : 'Given ' ;43WHEN_KEYWORD : 'When ' ;44THEN_KEYWORD : 'Then ' ;45WILD_KEYWORD : '* ' ;46AND_KEYWORD : 'And ';47BUT_KEYWORD : 'But ';48fragment CAPTURE_DATA : '<' ~[>\\t\\r\\n ]'>' ;49fragment DOCSTRING_DOUBLE_QUOTES : WS* '"""' (CAPTURE_DATA | ~'"' | '"' ~'"')*?  '"""' LINE_END ;50fragment DOCSTRING_BACKTICKS : WS* '```' (~'`' | CAPTURE_DATA | '`' ~'`').*? '```' LINE_END;51fragment TAG : '@'~[ \\r\\n\\t@]+ ;52fragment ESCAPE_SEQUENCE : '\\\\' [\\\\|\\n]* ;53fragment CELL_CHARACTER54	:	CAPTURE_DATA55	| ~[\\r\\n|\\\\]56	|	ESCAPE_SEQUENCE57	;58fragment CELL_DATA : WS* CELL_CHARACTER* '|';59DOCSTRING : DOCSTRING_DOUBLE_QUOTES | DOCSTRING_BACKTICKS ;60TAGS : WS* TAG (WS* TAG)* (COMMENT? | LINE_END);61FEATURE_TITLE : WS* FEATURE_KEYWORD ~[\\r\\n]* LINE_END ;62BACKGROUND_TITLE : WS* BACKGROUND_KEYWORD ~[\\r\\n]* COMMENT? LINE_END ;63EXAMPLES_TITLE : WS* EXAMPLES_KEYWORD ~[\\r\\n]* COMMENT? LINE_END ;64SCENARIO_TITLE : WS* SCENARIO_KEYWORD ~[\\r\\n]* LINE_END ;65SCENARIO_OUTLINE_TITLE : WS* SCENARIO_OUTLINE_KEYWORD (CAPTURE_DATA | ~[\\r\\n])* LINE_END ;66RULE_TITLE : WS* RULE_KEYWORD ~[\\r\\n]* LINE_END ;67GIVEN_STEP : WS* GIVEN_KEYWORD ~[ @\\r\\n|] ~[\\r\\n]* LINE_END;68WHEN_STEP : WS* WHEN_KEYWORD ~[ @\\r\\n|] ~[\\r\\n]* LINE_END;69THEN_STEP : WS* THEN_KEYWORD ~[ @\\r\\n|] ~[\\r\\n]* LINE_END;70AND_STEP : WS* AND_KEYWORD ~[ @\\r\\n|] ~[\\r\\n]* LINE_END;71BUT_STEP : WS* BUT_KEYWORD ~[ @\\r\\n|] ~[\\r\\n]* LINE_END;72WILD_STEP : WS* WILD_KEYWORD ~[ @\\r\\n|] ~[\\r\\n]* LINE_END;73DATA_ROW : WS* '|' CELL_DATA+ LINE_END ;74INVALID_LANGUAGE_HEADER : LANGUAGE_KEYWORD ~[\\r\\n]* LINE_END ;75COMMENT : WS* '#' ~[\\r\\n]* LINE_END -> channel(HIDDEN) ;76LINE_END : WS* (NEWLINE+ | EOF) -> skip;77NEWLINE : [\\r\\n] -> skip ;78WS : [ \\t] -> skip;79LONG_DESCRIPTION : WS* ~[ @\\r\\n|] ~[\\r\\n]* LINE_END ;80///////////////////////////////////////////////////81'''82for language in language_data.keys():83    print(language)84    ul = language.upper().replace('-', '_')85    ld = language_data[language]86    template += "\n//" + ld["name"]87    template += "\n//" + ld["native"]88    template += "\nmode " + ul + ";"89    # Feature90    template += "\n\t" + ul + "_FEATURE : ( "91    template += generate_keyword_body(ld["feature"]) + "':'"92    template += "\n\t\t) -> type(FEATURE_KEYWORD) ;"93    # Background94    template += """95    {lc}_BACKGROUND : (96    """.format(lc=ul)97    template += generate_keyword_body(ld["background"]) + "':'"98    template += "\n\t\t) -> type(BACKGROUND_KEYWORD);"99    # Scenario100    template += "\n\t" + ul + "_SCENARIO : (\n"101    template += generate_keyword_body(ld["scenario"]) + "':'"102    template += "\n\t) -> type(SCENARIO_KEYWORD);\n"103    # Scenario Outline104    template += "\n\t" + ul + "_SCENARIO_OUTLINE : (\n"105    template += generate_keyword_body(ld["scenarioOutline"])106    template += "\n\t) -> type(SCENARIO_OUTLINE_KEYWORD);\n"107    # Examples108    template += "\n\t" + ul + "_EXAMPLES : (\n"109    template += generate_keyword_body(ld["examples"]) + "':'"110    template += "  ) -> type(EXAMPLES_KEYWORD) ;\n"111    # Rule112    template += "\n\t" + ul + "_RULE : (\n"113    template += generate_keyword_body(ld["rule"]) + "':'"114    template += "  ) -> type(RULE_KEYWORD) ;\n"115    # Given116    template += "\n\t" + ul + "_GIVEN : (\n"117    given_keywords = ld["given"]118    if "* " in given_keywords: given_keywords.remove("* ")119    template += generate_keyword_body(given_keywords)120    template += "  ) -> type(GIVEN_KEYWORD) ;\n"121    # When122    template += "\n\t" + ul + "_WHEN : (\n"123    when_keywords = ld["when"]124    if "* " in when_keywords: when_keywords.remove("* ")125    template += generate_keyword_body(when_keywords)126    template += "  ) -> type(WHEN_KEYWORD) ;\n"127    # Then128    template += "\n\t" + ul + "_THEN : (\n"129    then_keywords = ld["then"]130    if "* " in then_keywords: then_keywords.remove("* ")131    template += generate_keyword_body(then_keywords)132    template += "  ) -> type(THEN_KEYWORD) ;\n"133    # And134    template += "\n\t" + ul + "_AND : (\n"135    and_keywords = ld["and"]136    if "* " in and_keywords: and_keywords.remove("* ")137    template += generate_keyword_body(and_keywords)138    template += "  ) -> type(AND_KEYWORD) ;\n"139    # But140    template += "\n\t" + ul + "_BUT : (\n"141    but_keywords = ld["but"]142    if "* " in but_keywords: but_keywords.remove("* ")143    template += generate_keyword_body(but_keywords)144    template += "  ) -> type(BUT_KEYWORD) ;\n"145    # Starting step146    template += "\n\t" + ul + """_STARTING_STEP_KEYWORD : (\n147                {lc}_GIVEN148		| {lc}_WHEN149		| {lc}_THEN150		| WILD_KEYWORD151		) -> type(STARTING_STEP_KEYWORD);152    """.format(lc=ul)153    template += "\n\t" + ul + """_ALTERNATIVE_STEP_KEYWORD : (\n154                {lc}_AND155		| {lc}_BUT156		) -> type(ALTERNATIVE_STEP_KEYWORD);157    """.format(lc=ul)158    template += """159    {language_code}_FEATURE_TITLE : WS* {language_code}_FEATURE ~[\\r\\n]* WS* LINE_END -> type(FEATURE_TITLE) ;160    {language_code}_BACKGROUND_TITLE : WS* {language_code}_BACKGROUND ~[\\r\\n]* COMMENT? LINE_END -> type(BACKGROUND_TITLE) ;161    {language_code}_EXAMPLES_TITLE : WS* {language_code}_EXAMPLES ~[\\r\\n]* COMMENT? LINE_END -> type(EXAMPLES_TITLE);162    {language_code}_SCENARIO_TITLE : WS* {language_code}_SCENARIO ~[\\r\\n]* LINE_END -> type(SCENARIO_TITLE);163    {language_code}_SCENARIO_OUTLINE_TITLE : WS* {language_code}_SCENARIO_OUTLINE ~[\\r\\n]* LINE_END -> type(SCENARIO_OUTLINE_TITLE) ;164    {language_code}_RULE_TITLE : WS* {language_code}_RULE ~[\\r\\n]* LINE_END -> type(RULE_TITLE);165        {language_code}_GIVEN_STEP : WS* {language_code}_GIVEN ~[ @\\r\\n|] ~[\\r\\n]* LINE_END -> type(GIVEN_STEP);166	{language_code}_WHEN_STEP : WS* {language_code}_WHEN ~[ @\\r\\n|] ~[\\r\\n]* LINE_END -> type(WHEN_STEP);167	{language_code}_THEN_STEP : WS* {language_code}_THEN ~[ @\\r\\n|] ~[\\r\\n]* LINE_END -> type(THEN_STEP);168	{language_code}_AND_STEP : WS* {language_code}_AND ~[ @\\r\\n|] ~[\\r\\n]* LINE_END -> type(AND_STEP);169	{language_code}_BUT_STEP : WS* {language_code}_BUT ~[ @\\r\\n|] ~[\\r\\n]* LINE_END -> type(BUT_STEP);170""".format(language_code = ul)171    f = open("GherkinLexer.g4", "w")172    f.write(template)173    f.close()174print("GherkinLexer.g4 regenerated")...

day4.py

Source:day4.py

1# advent of code2# day43import re4keywords = ['byr', 'ecl', 'eyr', 'hcl', 'hgt', 'iyr',  'pid']5keywords.sort()6valid_passport_count_a = 0 7valid_passport_count_b = 08with open("../input/day4.txt","r") as file:9    entries = file.readlines()10    # first puzzle11    given_keywords = []12    for i in range(0, len(entries)):13        e = entries[i]14        if e == '\n' or i == len(entries) - 1:15            given_keywords.sort() # for debugging16            if len(given_keywords) == len(keywords):17                valid_passport_count_a += 118            # reset19            given_keywords = []20            21        else:22            items = e.split(' ')23            for i in items:24                key, value = i.split(':')25                if key != 'cid':26                    given_keywords.append(key)27    # second puzzle28    given_keywords = []29    debug_given_items=[]30    for i in range(0, len(entries)):31        e = entries[i]32        if e != '\n':33            items = e.split(' ')34            for item in items:35                key, value = item.split(':')36                37                # whether the key's value is valid or not38                valid_value = False 39                40                value = value.rstrip('\r\n') # remove windows end of line41                    42                if key == 'byr' :43                        valid_value =  1920 <= int(value) <= 200244                elif (key == 'ecl'):45                    valid_value = value in  ['amb', 'blu', 'brn', 'gry', 'grn' ,'hzl' ,'oth']46                elif key == 'iyr':47                        valid_value =  2010 <= int(value) <= 202048                elif key == 'eyr':49                        valid_value = 2020 <= int(value) <= 203050                elif key == 'hgt':51                    if 'cm' in value:52                            valid_value = 150 <= int(value.split('cm')[0]) <= 19353                    elif 'in' in value:54                        valid_value = 59 <= int(value.split('in')[0]) <= 7655                elif key == 'hcl' :56                    valid_value = re.search("^#[0-9a-f]{6}", value)57                elif key == 'pid' :58                    valid_value = re.search("^[0-9]{9}$", value)             59                    60                if valid_value:61                    given_keywords.append(key)62                    debug_given_items.append(key+":"+value) # for debugging63                    64                        65        if (i < len(entries) - 1 and entries[i+1] == '\n') or i ==len(entries) -1:66            given_keywords.sort() # for debugging67            if len(given_keywords) == len(keywords):68                valid_passport_count_b += 169                # for debugging70                debug_given_items.sort()71                #print("b) " + str(valid_passport_count_b)+":"+str(debug_given_items))72                73            # reset74            given_keywords = []75            debug_given_items=[]76                               77                    78print("a) valid passports ", valid_passport_count_a+1)79print("b) valid passports ",valid_passport_count_b)          80    ...

db_reader.py

Source:db_reader.py

1import os2import json3import django4os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'xmemo.settings')5django.setup()6from random import randrange7from cs.models import Question8from xmemo_bot_lib.match_funcs import *9class QuestionJson:10    def __init__(self, model_obj):11        self.model_obj = model_obj12        self.heading = self.model_obj.question13        self.child_list = json.loads(model_obj.answer)14        self.child_html = self.get_child_html()15    def get_child_html(self):16        html = ""17        for each_child in self.child_list:18            html += AnswerJson(each_child).get_html()19        return html20    def get_html(self):21        html = f"""\22<span class="question_group">23    <div class="question">24        <p>{self.heading}</p>25        <div></div>26    </div>27    {self.child_html}28    <div class="major-line-break"></div>29</span>"""30        return html31class AnswerJson:32    def __init__(self, struct):33        self.struct = struct34    def get_html(self):35        html = f"""\36<p class="main-text">37    By ~ <bold>{self.struct["author"]}</bold><br>38    Published on ~ <bold>{self.struct["publish_date"]}</bold><br><br>39    <bold>Answer:</bold><br><br><br><br>40</p>41<pre class="code-block"><code class="lang-python">{self.struct["answer"]}</code></pre>42<p class="main-text">Is this answer correct?</p>43<div id="{self.struct["unique_id"]}" class="validity-check">44    <span class="right inline-btn" onclick="update_correct_val(this)">Correct</span>45    <span class="wrong inline-btn" onclick="update_incorrect_val(this)">Incorrect</span>46</div>47<p id="{self.struct["unique_id"]}correct_indicator" class="main-text" style="color: green;">48    {self.struct["correct_val"]} found this answer to be correct.49</p>50<p id="{self.struct["unique_id"]}wrong_indicator" class="main-text" style="color: red;">51    {self.struct["wrong_val"]} found this answer to be incorrect.52</p>53<div class="minor-line-break"></div>"""54        return html55def get_html_by_date(given_date):56    date = given_date.lower()57    html = ""58    question_list = Question.objects.filter(date=date)59    if len(question_list) > 0:60        for each_question in Question.objects.filter(date=date):61            html += QuestionJson(each_question).get_html()62    else:63        return f'<p class="main-text" style="margin-bottom: 85vh;"><bold>{date}</bold>' \64               ' no record for given date exists.Please try again. </p>'65    return html66def get_html_by_key(given_keywords):67    keywords = given_keywords.lower()68    html = ""69    similar_questions = [model for model in Question.objects.all() if are_similar(keywords, model.question)]70    if len(similar_questions) > 0:71        for each_question in similar_questions:72            html += QuestionJson(each_question).get_html()73        return html74    else:75        return f'\76<p class="main-text" style="margin-bottom: 85vh;"><bold>"{given_keywords}"</bold> ' \...

compute_constraint_metrics.py

Source:compute_constraint_metrics.py

1import os2import pandas as pd3import ast4import spacy5from collections import Counter6from sklearn.metrics import f1_score7from sklearn.preprocessing import MultiLabelBinarizer8nlp = spacy.load("en_core_web_lg")9# csvë¡ ì ì¥í´ì stringì´ ë list ëëë¦¬ê¸°10def to_list(x):11    return ast.literal_eval(x)12def pos(slogan):13    pos = []14    doc = nlp(slogan)15    for token in doc:16        if str(token) in ['<', '>']:17            continue18        if str(token) in ['name', 'loc']:19            pos.append("PROPN")20        elif str(token) == 'year':21            pos.append("NUM")22        else:23            tag = token.pos_24            if str(tag) == 'SPACE':25                continue26            pos.append(tag)27    return pos28filenames = ['/home/yeoun/BART/PREDS/SynSemBart_lowered_preds.csv', '/home/yeoun/BART/PREDS/originalBart_preds.csv']29# df = pd.DataFrame()30for i, filename in enumerate(filenames):31	if i == 0:32		df = pd.read_csv(filename)33		df = df[['slogan', 'given_keywords', 'predicted_slogan']]34		df = df.rename(columns={'predicted_slogan':filename})35	else:36		temp = pd.read_csv(filename)37		temp = temp.rename(columns={'predicted_slogan':filename})38		df = pd.concat([df, temp[filename]], axis=1)39df.to_csv('multi_merged_preds.csv', index=False, encoding='utf-8')40N = df.shape[0]41df.given_keywords = df.given_keywords.apply(lambda x: to_list(x))42keywords = df.given_keywords.tolist()43slogans = df.slogan.tolist()44pos_tags = [["ADJ", "ADP", "ADV", "AUX", "CCONJ", "DET", "INTJ", "NOUN", "NUM", "PART", "PRON", "PROPN", "PUNCT", "SCONJ", "SYM", "VERB", "X"]]45multi = MultiLabelBinarizer()46multi.fit(pos_tags)47for column in filenames:48	preds = df[column].tolist()49	keyword_rates = []50	pos_f1 = []51	# keyword order score ì¶ê°52	# keyword53	for keyword, pred, slogan in zip(keywords, preds, slogans):54		doc = nlp(pred.lower())55		tokens = []56		for token in doc:57			tokens.append(str(token))58		total = len(keyword)59		count = 060		for k in keyword:61			if k in tokens:62				count += 163		if count / total > 1:64			print(keyword, slogan)65		keyword_rates.append(count / total)66		slogan_pos = [pos(slogan)]67		pred_pos = [pos(pred)]68		A_new = multi.transform(slogan_pos)69		B_new = multi.transform(pred_pos)70		pos_f1.append(f1_score(A_new,B_new,average='samples'))71	print(column, ' í¤ìë í¬í¨ ë¹ì¨: ', sum(keyword_rates) / N)...

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