fa5962b Oct 10, 2015
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PyRestTest provides hooks for extending built-in components with your own Python code.

What Can An Extension Do?

  • In general: use more advanced dependencies while not making them required for installation
  • Generators: generate data for templating URL/request body/tests/etc
  • Extractors: get data from HTTP response body/headers and use it in future tests
  • Validators: write custom tests using headers & response bodies
  • Test Functions: for the ExtractTest validator, validate a single condition
  • Comparator function:s for the ComparatorValidator, compare expected and actual values

Extensions are specified for loadin at runtime with the --import_extensions argument:

python pyresttest/ extension_use_test.yaml --import_extensions 'sample_extension'

Extensions are python module names, separated by semicolons:

python pyresttest/ fancypants_test.yaml --import_extensions 'fancy_validator;form_data_generator'

What does an extension look like?

import pyresttest.validators as validators

# Define a simple generator that doubles with each value
def parse_generator_doubling(config):

    start = 1
    if 'start' in config:
        start = int(config['start'])

    # We cannot simply use start as the variable, because of scoping limitations
    def generator():
        val = start
            yield val
            val = val*2
    return generator()

GENERATORS = {'doubling': parse_generator_doubling}

If this is imported when executing the test, you can now use this generator in tests.

Full Example

See the sample extension.
It shows an extension for all extensible functions.

What Doe An Extension Need To Work?

  1. Function(s) to run
  2. Registry Entries: these are special ALLCAPS variables binding extension names

Functions (different for each type)

Test Functions

These are the simplest, one-argument functions that return True or False

def test(x):
    return x in [1, 2, 3]

Comparator Functions

Compare two values and return True/False

def compare(a, b):
    return a > b


These are standard python generators. There is ONE twist, they should be infinite (for benchmark use).

The function takes one argument, config, which is a string or dictionary of arguments for creating the generator.

def factory_choice_generator(values):
    """ Return a generator that picks values from a list randomly """

    def choice_generator():
        my_list = list(values)
        rand = random.Random()
            yield random.choice(my_list)
    return choice_generator

def parse_choice_generator(config):
    """ Parse choice generator """
    vals = config['values']
    if not vals:
        raise ValueError('Values for choice sequence must exist')
    if not isinstance(vals,list):
        raise ValueError('Values must be a list of entries')
    return factory_choice_generator(vals)()

The function for the registry would be parse_choice_generator

Extractors (Now things get a bit more complex)

These need to be objects, and should extend pyresttest.AbstractExtractor The 'parse' function below will be registered in the registry.


class HeaderExtractor(AbstractExtractor):
    """ Extractor that pulls out a named header """
    extractor_type = 'header'  # Printable name for the type
    is_header_extractor = True  # Use headers in extraction
    is_body_extractor = False  # Uses body in extraction

    def extract_internal(self, query=None, args=None, body=None, headers=None):
        """ The real logic, extract a value, using a templated query string and args
            The query is an attribute stored in the parent, and templating is used
            return headers[query]
        except Exception:
            return None

    def parse(cls, config, extractor_base=None):
        base = HeaderExtractor()
        # Base parser automatically handles templating logic
        # And reads the query
        return cls.configure_base(config, base)


Validators should extend AbstractValidator. The parse function below will be registered in the registry VALIDATORS.

class ExtractTestValidator(AbstractValidator):
    """ Does extract and test from request body """
    name = 'ExtractTestValidator'
    extractor = None
    test_fn = None
    test_name = None
    config = None

    def parse(config):
        """ Config is a dict """
        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 validate(self, body=None, headers=None, context=None):
            extracted = self.extractor.extract(body=body, headers=headers, context=context)
        except Exception as e:
            return Failure(message="Exception thrown while running extraction from body", details=e, validator=self)

        tested = self.test_fn(extracted)
        if tested:
            return True
            failure = Failure(details=self.config, validator=self)
            failure.message = "Extract and test validator failed on test: {0}({1})".format(self.test_name, extracted)
            return failure


The extension loader will look for special registry variables in the module and attempt to load them.

Registries are dictionarys of {registered_name: function}. Registry names are ALWAYS case-insensitive, since they are keywords for the YAML syntax.

These are:

  • VALIDATOR_TESTS - function is just thetest function
  • COMPARATORS - function is just the comparison function
  • GENERATORS - function is a parse function to get a generator
  • EXTRACTORS - function is a parse function returning an AbstractExtractor implementation
  • VALIDATORS - function is a parse function returning an AbstractValidator implementation

Each one maps to the same registry in pyresttest.validators.

Use Case Suggestions

  • Need to generate complex, formatted data?
    • Write a generator extension, or multiple generators may be used together to create a complex result
  • Want to test whether API results fit a business rule?
    • Write a validator extension, your logic can be as complex as you like
  • Want to apply a business rule to the output and use the result?
    • Write an extractor extension
    • You can do testing with the result via the validators ExtractTest and ComparatorValidator
    • By declaring the extractor with the test, it can be used in future tests
  • Want to test with complex matching logic between two parts of a response?
    • Write a Comparator to do the comparison, use extractors for pulling out the components
  • Want to run external logic after a test?
  • Want to interact with an external system (a DB, for example) before tests?
    • Write a custom generator function returning data
  • Want to confirm results were written to a database?
    • Write a custom validator or extractor that speaks to the database
    • An extractor can return a value from the DB for comparison
    • A validator can do the database fetch and return a failure if it was not right