def parse_configuration(node, base_config=None):
""" Parse input config to configuration information """
test_config = base_config
if not test_config:
test_config = TestConfig()
node = lowercase_keys(flatten_dictionaries(node)) # Make it usable
for key, value in node.items():
if key == u'timeout':
test_config.timeout = int(value)
elif key == u'print_bodies':
test_config.print_bodies = safe_to_bool(value)
elif key == u'retries':
test_config.retries = int(value)
elif key == u'variable_binds':
if not test_config.variable_binds:
test_config.variable_binds = dict()
test_config.variable_binds.update(flatten_dictionaries(value))
elif key == u'generators':
flat = flatten_dictionaries(value)
gen_map = dict()
for generator_name, generator_config in flat.items():
gen = parse_generator(generator_config)
gen_map[str(generator_name)] = gen
test_config.generators = gen_map
return test_config
def parse_configuration(node, base_config=None):
""" Parse input config to configuration information """
test_config = base_config
if not test_config:
test_config = TestConfig()
node = lowercase_keys(flatten_dictionaries(node)) # Make it usable
for key, value in node.items():
if key == u'timeout':
test_config.timeout = int(value)
elif key == u'print_bodies':
test_config.print_bodies = safe_to_bool(value)
elif key == u'retries':
test_config.retries = int(value)
elif key == u'variable_binds':
if not test_config.variable_binds:
test_config.variable_binds = dict()
test_config.variable_binds.update(flatten_dictionaries(value))
elif key == u'generators':
flat = flatten_dictionaries(value)
gen_map = dict()
for generator_name, generator_config in flat.items():
gen = parse_generator(generator_config)
gen_map[str(generator_name)] = gen
test_config.generators = gen_map
return test_config
def parse(config):
""" Create a validator that does an extract from body and applies a comparator,
Then does comparison vs expected value
Syntax sample:
{ jsonpath_mini: 'node.child',
operator: 'eq',
expected: 'myValue'
}
"""
output = ComparatorValidator()
config = parsing.lowercase_keys(parsing.flatten_dictionaries(config))
output.config = config
# Extract functions are called by using defined extractor names
output.extractor = _get_extractor(config)
if output.extractor is None:
raise ValueError(
"Extract function for comparison is not valid or not found!")
if 'comparator' not in config: # Equals comparator if unspecified
output.comparator_name = 'eq'
else:
output.comparator_name = config['comparator'].lower()
output.comparator = COMPARATORS[output.comparator_name]
if not output.comparator:
raise ValueError("Invalid comparator given!")
try:
expected = config['expected']
except KeyError:
raise ValueError(
"No expected value found in comparator validator config, one must be!"
)
# Expected value can be another extractor query, or a single value, or
# a templated value
if isinstance(expected, basestring) or isinstance(
expected, (int, long, float, complex)):
output.expected = expected
elif isinstance(expected, dict):
expected = parsing.lowercase_keys(expected)
template = expected.get('template')
if template: # Templated string
if not isinstance(template, basestring):
raise ValueError(
"Can't template a comparator-validator unless template value is a string"
)
output.isTemplateExpected = True
output.expected = template
else: # Extractor to compare against
output.expected = _get_extractor(expected)
if not output.expected:
raise ValueError(
"Can't supply a non-template, non-extract dictionary to comparator-validator"
)
return output
def parse(config):
""" Create a validator that does an extract from body and applies a comparator,
Then does comparison vs expected value
Syntax sample:
{ jsonpath_mini: 'node.child',
operator: 'eq',
expected: 'myValue'
}
"""
output = ComparatorValidator()
config = parsing.lowercase_keys(parsing.flatten_dictionaries(config))
output.config = config
# Extract functions are called by using defined extractor names
output.extractor = _get_extractor(config)
if output.extractor is None:
raise ValueErrors(
"Extract function for comparison is not valid or not found!")
if 'comparator' not in config: # Equals comparator if unspecified
output.comparator_name = 'eq'
else:
output.comparator_name = config['comparator'].lower()
output.comparator = COMPARATORS[output.comparator_name]
if not output.comparator:
raise ValueError("Invalid comparator given!")
try:
expected = config['expected']
except KeyError:
raise ValueError(
"No expected value found in comparator validator config, one must be!")
# Expected value can be another extractor query, or a single value, or
# a templated value
if isinstance(expected, basestring) or isinstance(expected, (int, long, float, complex)):
output.expected = expected
elif isinstance(expected, dict):
expected = parsing.lowercase_keys(expected)
template = expected.get('template')
if template: # Templated string
if not isinstance(template, basestring):
raise ValueError(
"Can't template a comparator-validator unless template value is a string")
output.isTemplateExpected = True
output.expected = template
else: # Extractor to compare against
output.expected = _get_extractor(expected)
if not output.expected:
raise ValueError(
"Can't supply a non-template, non-extract dictionary to comparator-validator")
return output
def test_flatten(self):
""" Test flattening of lists of dictionaries to single dictionaries """
# Test happy path: list of single-item dictionaries in
array = [{"url": "/cheese"}, {"method": "POST"}]
expected = {"url": "/cheese", "method": "POST"}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
# Test dictionary input
array = {"url": "/cheese", "method": "POST"}
expected = {"url": "/cheese", "method": "POST"}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertTrue(len(set(output.items()) ^ set(expected.items())) == 0)
# Test empty list input
array = []
expected = {}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
# Test empty dictionary input
array = {}
expected = {}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
# Test mixed-size input dictionaries
array = [{"url": "/cheese"}, {"method": "POST", "foo": "bar"}]
expected = {"url": "/cheese", "method": "POST", "foo": "bar"}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
def test_flatten(self):
""" Test flattening of lists of dictionaries to single dictionaries """
# Test happy path: list of single-item dictionaries in
array = [{"url": "/cheese"}, {"method": "POST"}]
expected = {"url": "/cheese", "method": "POST"}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
# Test dictionary input
array = {"url": "/cheese", "method": "POST"}
expected = {"url": "/cheese", "method": "POST"}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertTrue(len(set(output.items()) ^ set(expected.items())) == 0)
# Test empty list input
array = []
expected = {}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
# Test empty dictionary input
array = {}
expected = {}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
# Test mixed-size input dictionaries
array = [{"url": "/cheese"}, {"method": "POST", "foo": "bar"}]
expected = {"url": "/cheese", "method": "POST", "foo": "bar"}
output = flatten_dictionaries(array)
self.assertTrue(isinstance(output, dict))
# Test that expected output matches actual
self.assertFalse(len(set(output.items()) ^ set(expected.items())))
def parse(config):
output = ExtractTestValidator()
config = parsing.lowercase_keys(parsing.flatten_dictionaries(config))
output.config = config
extractor = _get_extractor(config)
output.extractor = extractor
test_name = config['test']
output.test_name = test_name
test_fn = VALIDATOR_TESTS[test_name]
output.test_fn = test_fn
return output
def parse(config):
output = ExtractTestValidator()
config = parsing.lowercase_keys(parsing.flatten_dictionaries(config))
output.config = config
extractor = _get_extractor(config)
output.extractor = extractor
test_name = config['test']
output.test_name = test_name
test_fn = VALIDATOR_TESTS[test_name]
output.test_fn = test_fn
return output
def parse_generator(configuration):
""" Parses a configuration built from yaml and returns a generator
Configuration should be a map
"""
configuration = lowercase_keys(flatten_dictionaries(configuration))
gen_type = str(configuration.get(u'type')).lower()
if gen_type not in GENERATOR_TYPES:
raise ValueError(
'Generator type given {0} is not valid '.format(gen_type))
# Do the easy parsing, delegate more complex logic to parsing functions
if gen_type == u'env_variable':
return factory_env_variable(configuration[u'variable_name'])()
elif gen_type == u'env_string':
return factory_env_string(configuration[u'string'])()
elif gen_type == u'number_sequence':
start = configuration.get('start')
increment = configuration.get('increment')
if not start:
start = 1
else:
start = int(start)
if not increment:
increment = 1
else:
increment = int(increment)
return factory_generate_ids(start, increment)()
elif gen_type == u'random_int':
return generator_random_int32()
elif gen_type == u'random_text':
return parse_random_text_generator(configuration)
elif gen_type in GENERATOR_TYPES:
return GENERATOR_PARSING[gen_type](configuration)
else:
raise Exception("Unknown generator type: {0}".format('gen_type'))
def parse_generator(configuration):
""" Parses a configuration built from yaml and returns a generator
Configuration should be a map
"""
configuration = lowercase_keys(flatten_dictionaries(configuration))
gen_type = str(configuration.get(u'type')).lower()
if gen_type not in GENERATOR_TYPES:
raise ValueError(
'Generator type given {0} is not valid '.format(gen_type))
# Do the easy parsing, delegate more complex logic to parsing functions
if gen_type == u'env_variable':
return factory_env_variable(configuration[u'variable_name'])()
elif gen_type == u'env_string':
return factory_env_string(configuration[u'string'])()
elif gen_type == u'number_sequence':
start = configuration.get('start')
increment = configuration.get('increment')
if not start:
start = 1
else:
start = int(start)
if not increment:
increment = 1
else:
increment = int(increment)
return factory_generate_ids(start, increment)()
elif gen_type == u'random_int':
return generator_random_int32()
elif gen_type == u'random_text':
return parse_random_text_generator(configuration)
elif gen_type in GENERATOR_TYPES:
return GENERATOR_PARSING[gen_type](configuration)
else:
raise Exception("Unknown generator type: {0}".format('gen_type'))
