Files
deb-python-ddt/ddt.py
Bulkan Evcimen 563dc177a3 when JSON data file is missing visibly fail
* creates a fake test function that raises ValueError
2013-02-27 11:23:00 +11:00

119 lines
3.8 KiB
Python

import inspect
import json
import os
from functools import wraps
__version__ = '0.4.0'
# this value cannot conflict with any real python attribute
DATA_ATTR = '%values'
# store the path to JSON file
FILE_ATTR = '%file_path'
def data(*values):
"""
Method decorator to add to your test methods.
Should be added to methods of instances of ``unittest.TestCase``.
"""
def wrapper(func):
setattr(func, DATA_ATTR, values)
return func
return wrapper
def file_data(value):
"""
Method decorator to add to your test methods.
Should be added to methods of instances of ``unittest.TestCase``.
``value`` should be a path relative to the directory of the file
containing the decorated ``unittest.TestCase``. The file
should contain JSON encoded data, that can either be a list or a
dict.
In case of a list, each value in the list will correspond to one
test case, and the value will be concatenated to the test method
name.
In case of a dict, keys will be used as suffixes to the name of the
test case, and values will be fed as test data.
"""
def wrapper(func):
setattr(func, FILE_ATTR, value)
return func
return wrapper
def ddt(cls):
"""
Class decorator for subclasses of ``unittest.TestCase``.
Apply this decorator to the test case class, and then
decorate test methods with ``@data``.
For each method decorated with ``@data``, this will effectively create as
many methods as data items are passed as parameters to ``@data``.
The names of the test methods follow the pattern ``test_func_name
+ "_" + str(data)``. If ``data.__name__`` exists, it is used
instead for the test method name.
For each method decorated with ``@file_data('test_data.json')``, the
decorator will try to load the test_data.json file located relative
to the python file containing the method that is decorated. It will,
for each ``test_name`` key create as many methods in the list of values
from the ``data`` key.
The names of these test methods follow the pattern of
``test_name`` + str(data)``
"""
def feed_data(func, *args, **kwargs):
"""
This internal method decorator feeds the test data item to the test.
"""
@wraps(func)
def wrapper(self):
return func(self, *args, **kwargs)
return wrapper
def process_file_data(name, func, file_attr):
"""
Process the parameter in the `file_data` decorator.
"""
cls_path = os.path.abspath(inspect.getsourcefile(cls))
data_file_path = os.path.join(os.path.dirname(cls_path), file_attr)
def _raise_ve(*args):
raise ValueError("%s does not exist" % file_attr)
if os.path.exists(data_file_path) is False:
test_name = "{0}_{1}".format(name, "error")
setattr(cls, test_name, feed_data(_raise_ve, None))
else:
data = json.loads(open(data_file_path).read())
for elem in data:
if isinstance(data, dict):
key, value = elem, data[elem]
test_name = "{0}_{1}".format(name, key)
elif isinstance(data, list):
value = elem
test_name = "{0}_{1}".format(name, value)
setattr(cls, test_name, feed_data(func, value))
for name, func in list(cls.__dict__.items()):
if hasattr(func, DATA_ATTR):
for v in getattr(func, DATA_ATTR):
test_name = getattr(v, "__name__", "{0}_{1}".format(name, v))
setattr(cls, test_name, feed_data(func, v))
delattr(cls, name)
elif hasattr(func, FILE_ATTR):
file_attr = getattr(func, FILE_ATTR)
process_file_data(name, func, file_attr)
delattr(cls, name)
return cls