def test_parse_feature_after_parser_error():
parser = Parser()
with assert_raises(ParserError):
parser.parse(TokenScanner('# a comment\n' +
'Feature: Foo\n' +
' Scenario: Bar\n' +
' Given x\n' +
' ```\n' +
' unclosed docstring\n'))
feature = parser.parse(TokenScanner('Feature: Foo\n' +
' Scenario: Bar\n' +
' Given x\n'
' """\n'
' closed docstring\n'
' """\n'))
expected = [{
'name': u'Bar',
'keyword': u'Scenario',
'tags': [],
'steps': [{
'text': u'x',
'type': 'Step',
'location': {'column': 5, 'line': 3},
'keyword': u'Given ',
'argument': {
'content': u'closed docstring',
'type': 'DocString',
'contentType': u'',
'location': {'column': 7, 'line': 4}}}],
'location': {'column': 3, 'line': 2},
'type': 'Scenario'}]
assert_equals(expected, feature['scenarioDefinitions'])
def test_parse_feature_after_parser_error():
parser = Parser()
with assert_raises(ParserError):
parser.parse(TokenScanner('# a comment\n' +
'Feature: Foo\n' +
' Scenario: Bar\n' +
' Given x\n' +
' ```\n' +
' unclosed docstring\n'))
feature = parser.parse(TokenScanner('Feature: Foo\n' +
' Scenario: Bar\n' +
' Given x\n'
' """\n'
' closed docstring\n'
' """\n'))
expected = [{
'name': u'Bar',
'keyword': u'Scenario',
'tags': [],
'steps': [{
'text': u'x',
'type': 'Step',
'location': {'column': 5, 'line': 3},
'keyword': u'Given ',
'argument': {
'content': u'closed docstring',
'type': 'DocString',
'location': {'column': 7, 'line': 4}}}],
'location': {'column': 3, 'line': 2},
'type': 'Scenario'}]
assert_equals(expected, feature['scenarioDefinitions'])
def process_gherkin(gherkin_filename, basedir, output):
print(f"Processing gherkin: {gherkin_filename}")
if verbose:
print(f"Basedir: {basedir}")
print(f"Output: {output}")
with open(gherkin_filename, 'r') as f:
content = f.read()
parser = Parser()
feature = parser.parse(content)
global settings_lines, test_cases_lines, keywords_lines, seen_steps
settings_lines = []
test_cases_lines = []
keywords_lines = []
seen_steps = {}
process_feature(feature)
feature_base = os.path.dirname(gherkin_filename)
feature_sub = None
if feature_base.startswith(basedir):
feature_sub = feature_base[len(basedir) + 1:]
else:
feature_sub = feature_base
generate_robot_script(os.path.join(output, feature_sub), feature['name'])
def parse(cls, string=None, filename=None, language=None):
"""
Parse either a string or a file.
"""
parser = Parser()
# pylint:disable=redefined-variable-type
# https://bitbucket.org/logilab/pylint/issues/710
if language:
if language == 'pt-br':
language = 'pt'
token_matcher = LanguageTokenMatcher(language)
else:
token_matcher = TokenMatcher()
# pylint:enable=redefined-variable-type
if string:
token_scanner = TokenScanner(string=string)
else:
token_scanner = TokenScanner(filename=filename)
try:
return cls(
parser.parse(token_scanner, token_matcher=token_matcher),
filename=filename,
)
except ParserError as ex:
raise AloeSyntaxError(filename, str(ex))
def dump_gherkin(gherkin_filename):
with open(gherkin_filename, 'r') as f:
str = f.read()
parser = Parser()
feature = parser.parse(str)
print yaml.dump(feature)
def dump_gherkin(gherkin_filename):
with open(gherkin_filename, 'r') as f:
content = f.read()
parser = Parser()
feature = parser.parse(content)
print(yaml.dump(feature))
class Reader:
def __init__(self):
self.parser = Parser()
def strip_comments(self, step):
comment = step.find(GHERKIN_COMMENT)
if comment != -1:
return step[:comment].rstrip()
return step
def filter_definitions(self, defs):
f = lambda prev, curr: prev + list(
map(self.strip_comments, pluck(curr['steps'], 'text')))
return reduce(f, defs, [])
def read_steps(self, filename):
try:
feature = self.parser.parse(TokenScanner(filename))
defs = []
if GHERKIN_SCENARIOS in feature: defs += feature[GHERKIN_SCENARIOS]
if GHERKIN_BACKGROUND in feature:
defs.append(feature[GHERKIN_BACKGROUND])
steps = self.filter_definitions(defs)
cache.set(filename, steps)
except CompositeParserException as e:
steps = []
print(e)
return steps
def get_steps(self, filename):
if cache.has(filename):
return cache.get(filename)
return self.read_steps(filename)
def test_parse_multiple_features():
parser = Parser()
f1 = parser.parse(TokenScanner("Feature: 1"))
f2 = parser.parse(TokenScanner("Feature: 2"))
assert_equals("1", f1['name'])
assert_equals("2", f2['name'])
class Reader:
def __init__(self):
self.parser = Parser()
def strip_comments(self, step):
comment = step.find(GHERKIN_COMMENT)
if comment != -1:
return step[:comment].rstrip()
return step
def filter_definitions(self, defs):
f = lambda prev, curr: prev + list(map(self.strip_comments, pluck(curr['steps'], 'text')))
return reduce(f, defs, [])
def read_steps(self, filename):
try:
feature = self.parser.parse(TokenScanner(filename))
defs = []
if GHERKIN_SCENARIOS in feature: defs += feature[GHERKIN_SCENARIOS]
if GHERKIN_BACKGROUND in feature: defs.append(feature[GHERKIN_BACKGROUND])
steps = self.filter_definitions(defs)
cache.set(filename, steps)
except CompositeParserException as e:
steps = []
print(e)
return steps
def get_steps(self, filename):
if cache.has(filename):
return cache.get(filename)
return self.read_steps(filename)
def test_parse_multiple_features():
parser = Parser()
f1 = parser.parse(TokenScanner("Feature: 1"))
f2 = parser.parse(TokenScanner("Feature: 2"))
assert_equals("1", f1['name'])
assert_equals("2", f2['name'])
def gherkin_pieces_grouped_by_featurename(features_dir):
""" For a list of BDD feature files, discover the parts
that are tagged with FM feature names (features and scenarios) and group them by the FM feature names.
"""
gherkin_parser = Parser()
pieces_grouped_by_tag = {}
for feature_file in listdir(features_dir):
feature_file = open(path.join(features_dir, feature_file), "r")
feature_parsed = gherkin_parser.parse(feature_file.read())
for tag in feature_parsed['tags']:
tag_name = tag['name'][1:] # remove @
if tag_name not in pieces_grouped_by_tag:
pieces_grouped_by_tag[tag_name] = []
pieces_grouped_by_tag[tag_name].append(feature_parsed['name'])
for scenario in feature_parsed['scenarioDefinitions']:
for tag in scenario['tags']:
tag_name = tag['name'][1:] # remove @
if tag_name not in pieces_grouped_by_tag:
pieces_grouped_by_tag[tag_name] = []
pieces_grouped_by_tag[tag_name].append(scenario['name'])
return pieces_grouped_by_tag
def test_parser():
parser = Parser()
feature = parser.parse(TokenScanner("Feature: Foo"))
expected = {'comments': [],
'keyword': u'Feature',
'language': 'en',
'location': {'column': 1, 'line': 1},
'name': u'Foo',
'scenarioDefinitions': [],
'tags': [],
'type': 'Feature'}
assert_equals(expected, feature)
def test_parser():
parser = Parser()
feature = parser.parse(TokenScanner("Feature: Foo"))
expected = {'comments': [],
'keyword': u'Feature',
'language': 'en',
'location': {'column': 1, 'line': 1},
'name': u'Foo',
'scenarioDefinitions': [],
'tags': [],
'type': 'Feature'}
assert_equals(expected, feature)
def test_change_the_default_language():
parser = Parser()
matcher = TokenMatcher('no')
feature = parser.parse(TokenScanner("Egenskap: i18n support"), matcher)
expected = {'comments': [],
'keyword': u'Egenskap',
'language': 'no',
'location': {'column': 1, 'line': 1},
'name': u'i18n support',
'scenarioDefinitions': [],
'tags': [],
'type': 'Feature'}
assert_equals(expected, feature)
def test_change_the_default_language():
parser = Parser()
matcher = TokenMatcher('no')
feature = parser.parse(TokenScanner("Egenskap: i18n support"), matcher)
expected = {'comments': [],
'keyword': u'Egenskap',
'language': 'no',
'location': {'column': 1, 'line': 1},
'name': u'i18n support',
'scenarioDefinitions': [],
'tags': [],
'type': 'Feature'}
assert_equals(expected, feature)
def process_gherkin(gherkin_filename, basedir, output):
with open(gherkin_filename, 'r') as f:
content = f.read()
parser = Parser()
feature = parser.parse(content)
global settings_lines, test_cases_lines, keywords_lines, seen_steps
settings_lines = []
test_cases_lines = []
keywords_lines = []
seen_steps = set([])
process_feature(feature)
feature_base = os.path.dirname(gherkin_filename)
feature_sub = feature_base[len(basedir)+1:]
generate_robot_script(os.path.join(output, feature_sub), feature['name'])
def parse(cls, string=None, filename=None, language=None):
"""
Parse either a string or a file.
"""
parser = Parser()
if language:
if language == 'pt-br':
language = 'pt'
token_matcher = LanguageTokenMatcher(language)
else:
token_matcher = TokenMatcher()
if string:
token_scanner = TokenScanner(string=string)
else:
token_scanner = TokenScanner(filename=filename)
return cls(
parser.parse(token_scanner, token_matcher=token_matcher),
filename=filename,
)
arg_parser = argparse.ArgumentParser(description='Draw dot file from FeatureIDE model.xml')
arg_parser.add_argument('model_xml_file', help="Location of the model XML file")
arg_parser.add_argument('features_dir', help="Location of the feature files")
arg_parser.add_argument('reports_dir', help="Location of the test results files for products")
arg_parser.add_argument('output_dir', help="Location where the output file should be rendered")
arg_parser.add_argument('--output_filename', default="feature_model", help="Name to use for the output file")
arg_parser.add_argument('--productconfig', default="all", help="")
args = arg_parser.parse_args()
gherkin_parser = Parser()
tags = {}
for feature_file in listdir(args.features_dir):
feature_file = open(path.join(args.features_dir, feature_file), "r")
feature_parsed = gherkin_parser.parse(feature_file.read())
for tag in feature_parsed['tags']:
tag_name = tag['name'][1:] # remove @
if tag_name not in tags:
tags[tag_name] = []
tags[tag_name].append("F: " + feature_parsed['name'])
for scenario in feature_parsed['scenarioDefinitions']:
for tag in scenario['tags']:
tag_name = tag['name'][1:] # remove @
if tag_name not in tags:
tags[tag_name] = []
tags[tag_name].append("S: " + scenario['name'])
def parseFeature(feature, parent, graph, test_results, product_features):