def test_bootstrapSetsUpClassifierAsExpected(self):
ProgrammingBayesianClassifier.bootstrap(TestConfig)
self.assertEqual(
ZipFileStub.called,
[
'init-trainers.zip-r',
'namelist',
'read-foo.def',
'read-bar.def'
]
)
self.assertTrue(
ismethod(SimpleBayesStub.Tokenizer) or
isfunction(SimpleBayesStub.Tokenizer)
)
self.assertIsInstance(registry.get('PP_bayes'), SimpleBayesStub)
self.assertEqual(
SimpleBayesStub.Languages,
{
'foo': 'foo.def-text',
'bar': 'bar.def-text'
}
)
def test_classifierProducesExpectedResult(self):
ProgrammingBayesianClassifier.bootstrap(TestConfig)
classifier = ProgrammingBayesianClassifier()
result = classifier.classify('echo "Hello World";')
self.assertEqual('echo "Hello World";', SimpleBayesStub.data_string)
self.assertEqual('FooBar', result)
def test_classifierProducesExpectedResult(self):
ProgrammingBayesianClassifier.bootstrap(TestConfig)
classifier = ProgrammingBayesianClassifier()
result = classifier.classify('echo "Hello World";')
self.assertEqual('echo "Hello World";', SimpleBayesStub.data_string)
self.assertEqual('FooBar', result)
def test_bootstrapSetsUpClassifierAsExpected(self):
ProgrammingBayesianClassifier.bootstrap(TestConfig)
self.assertEqual(ZipFileStub.called, [
'init-trainers.zip-r', 'namelist', 'read-foo.def', 'read-bar.def'
])
self.assertTrue(
ismethod(SimpleBayesStub.Tokenizer)
or isfunction(SimpleBayesStub.Tokenizer))
self.assertIsInstance(registry.get('PP_bayes'), SimpleBayesStub)
self.assertEqual(SimpleBayesStub.Languages, {
'foo': 'foo.def-text',
'bar': 'bar.def-text'
})
def bootstrap(config):
"""Loads tokens from the yaml files on disk"""
all_keywords = []
language_keywords = {}
directory = os.path.dirname(os.path.abspath(__file__))
path = os.path.join(directory, "languages/*.yaml")
for file_path in glob.glob(path):
with open(file_path, 'r') as language_file:
language = yaml.load(language_file)
all_keywords.extend(language['keywords'])
language_keywords[language['id']] = language
registry.set('PP_all_keywords', set(all_keywords))
registry.set('PP_language_keywords', language_keywords)
ProgrammingBayesianClassifier.bootstrap(config)
def bootstrap(config):
"""
This method is statically called to bootstrap a parser
:param config: cahoots config
:type config: cahoots.config.BaseConfig
"""
all_keywords = []
language_keywords = {}
directory = os.path.dirname(os.path.abspath(__file__))
path = os.path.join(directory, "languages/*.yaml")
for file_path in glob.glob(path):
with open(file_path, "r") as language_file:
language = yaml.load(language_file)
all_keywords.extend(language["keywords"])
language_keywords[language["id"]] = language
registry.set("PP_all_keywords", set(all_keywords))
registry.set("PP_language_keywords", language_keywords)
ProgrammingBayesianClassifier.bootstrap(config)
def bootstrap(config):
"""
This method is statically called to bootstrap a parser
:param config: cahoots config
:type config: cahoots.config.BaseConfig
"""
all_keywords = []
language_keywords = {}
directory = os.path.dirname(os.path.abspath(__file__))
path = os.path.join(directory, "languages/*.yaml")
for file_path in glob.glob(path):
with open(file_path, 'r') as language_file:
language = yaml.load(language_file)
all_keywords.extend(language['keywords'])
language_keywords[language['id']] = language
registry.set('PP_all_keywords', set(all_keywords))
registry.set('PP_language_keywords', language_keywords)
ProgrammingBayesianClassifier.bootstrap(config)
