Testing Class Material

extra_slides/mocking/code.py

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+
+>>> from smtplib import SMTP
+>>> mock_smtp = Mock(spec=SMTP)
+
+>>> isinstance(mock_smtp, SMTP)
+True
+
+>>> mock_smtp.<TAB>
+                    mock_smtp.assert_any_call         mock_smtp.attach_mock             mock_smtp.call_args                
+                    mock_smtp.assert_called_once_with mock_smtp.auth                    mock_smtp.call_args_list           
+                    mock_smtp.assert_called_with      mock_smtp.auth_cram_md5           mock_smtp.call_count              >
+                    mock_smtp.assert_has_calls        mock_smtp.auth_login              mock_smtp.called                   
+                    mock_smtp.assert_not_called       mock_smtp.auth_plain              mock_smtp.close                    
+
+>>> mock_smtp.bogus
+---------------------------------------------------------------------------
+AttributeError                            Traceback (most recent call last)
+<ipython-input-17-4856e93b6e10> in <module>()
+----> 1 mock_smtp.bogus
+
+/Users/pberkes/miniconda3/envs/gnode/lib/python3.5/unittest/mock.py in __getattr__(self, name)
+    576         elif self._mock_methods is not None:
+    577             if name not in self._mock_methods or name in _all_magics:
+--> 578                 raise AttributeError("Mock object has no attribute %r" % name)
+    579         elif _is_magic(name):
+    580             raise AttributeError(name)
+
+AttributeError: Mock object has no attribute 'bogus'
+
+

extra_slides/mocking/demo_Mock.py

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+##### Mock basic
+m = Mock()
+m.x = 3
+m.x
+m.f(1,2,3)
+m.whatever(3, key=2)
+m
+m.f
+m.g
+
+##### special attributes and assert methods
+mock=Mock()
+mock.f(2,3)
+mock.f('a')
+
+mock.f.called
+mock.add.called
+mock.f.called
+mock.f.call_args
+mock.f.call_count
+mock.f.call_args_list
+mock.f.assert_called_with('a')
+mock.f.assert_called_once_with('a')
+mock.f.assert_called_with(2, 3)
+mock.f.assert_any_call(2, 3)
+mock.f.assert_has_calls(['a', (2,3)])
+
+#### return_value and side_effect
+mock.g.return_value = 7
+mock.g(32)
+mock.g('r')
+
+# useful to simulate file errors or server errors
+mock.g.side_effect = Exception('Noooo')  
+mock.g(2)
+mock.g.side_effect = lambda x: x.append(2)
+a=[1]
+mock.g(a)
+a
+
+mock.g.side_effect = [1, 4, 5]
+mock.g()
+mock.g()
+mock.g()
+mock.g()
+
+#####
+mock = Mock()
+mock.f(3,4)
+mock.g('a')
+mock.f.a()
+mock.method_calls
+
+result = m.h(32)
+result(1)
+m.mock_calls
+
+##### spec
+from chaco.api import Plot
+m2 = Mock(spec=Plot)
+isinstance(m2, Plot)
+m2.add
+m2.add(12,'asdfasd')
+m2.aaa

extra_slides/mocking/report.py

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+report_template = """
+Report
+======
+
+The experiment was a {judgment}!
+Let's do this again, with a bigger budget.
+"""
+
+
+def send_report(result, smtp):
+    if result > 0.5:
+        judgment = 'big success'
+    else:
+        judgment = 'total failure'
+    report = report_template.format(judgment=judgment)
+    smtp.send_message(
+        report,
+        from_addr='pony@magicpony.com',
+        to_addrs=['ferenc@magicpony.com'],
+    )
+
+
+from unittest.mock import Mock
+
+def test_send_report_success():
+    smtp = Mock()
+
+    send_report(0.6, smtp)
+    assert smtp.send_message.call_count == 1
+    pos_args, kw_args = smtp.send_message.call_args
+    message = pos_args[0]
+    assert 'success' in message
+
+    smtp.reset_mock()
+
+    send_report(0.4, smtp)
+    assert smtp.send_message.call_count == 1
+    args, kwargs = smtp.send_message.call_args
+    message = args[0]
+    assert 'failure' in message
+

extra_slides/mocking/telescope/telescope_driver.py

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+
+def connect(address):
+    import time
+    time.sleep(5)
+    return '1'
+
+def get_angle(address):
+    return 0.0
+
+def set_angle(address, angle):
+    if angle < 0 or angle > 1.40:
+        raise IOError('Telescope jammed -- please call technical support')
+    return True

extra_slides/mocking/telescope/telescope_model.py

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+import telescope_driver
+
+
+class TelescopeModel(object):
+
+    # Minimum safe elevation angle (see handbook).
+    MIN_ANGLE = 0.0
+
+    # Maximum safe elevation angle (see handbook).
+    MAX_ANGLE = 80.0
+
+    def __init__(self, address):
+        self.address = address
+        # Connect to telescope
+        self.connection = telescope_driver.connect(address)
+        # Get initial state of telescope.
+        self.current_angle = telescope_driver.get_angle(self.connection)
+
+    def set_elevation_angle(self, angle):
+        """ Set the elevation angle of the telescope (in rad).
+
+        If the angle is outside the range allowed by the manufacturer,
+        raise a ValueError.
+        """
+
+        if angle < self.MIN_ANGLE or angle > self.MAX_ANGLE:
+            raise ValueError('Unsafe elevation angle: {}'.format(angle))
+
+        telescope_driver.set_angle(self.connection, angle)
+        self.current_angle = angle

extra_slides/mocking/telescope/test_telescope_model.py

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+import numpy as np
+from py.test import raises
+
+from telescope_model import TelescopeModel
+
+
+def test_unsafe_elevation_angle():
+    telescope = TelescopeModel(address='10.2.1.1')
+    elevation_angle = np.pi / 2.0
+
+    with raises(ValueError):
+        telescope.set_elevation_angle(elevation_angle)

extra_slides/mocking/telescope/test_telescope_model_with_mock.py

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+from unittest import mock
+
+import numpy as np
+from py.test import raises
+
+from telescope_model import TelescopeModel
+
+
+def test_unsafe_elevation_angle():
+    with mock.patch('telescope_model.telescope_driver'):
+        telescope = TelescopeModel(address='10.2.1.1')
+        elevation_angle = np.pi / 2.0
+        with raises(ValueError):
+            telescope.set_elevation_angle(elevation_angle)
+
+
+def test_model_initialization():
+    connection_id = 'bogus_connection'
+    initial_angle = 1.23
+
+    with mock.patch('telescope_model.telescope_driver') as driver:
+        driver.connect.return_value = connection_id
+        driver.get_angle.return_value = initial_angle
+
+        telescope = TelescopeModel(address='10.2.1.1')
+        assert telescope.connection == connection_id
+        assert driver.connect.call_count == 1
+        assert telescope.current_angle == initial_angle
+    

extra_slides/packaging/noiser_project_final/noiser/main.py

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+import os.path
+
+import matplotlib.pyplot as plt
+from scipy.ndimage import imread
+from pkg_resources import resource_filename
+
+from noiser.noise import white_noise
+from noiser.utils import copy_image
+
+
+def main():
+    path = resource_filename('noiser', os.path.join('images', 'baboon_kandinsky.png'))
+    print(path)
+    img = imread(path)
+    noisy = copy_image(white_noise(img, 20))
+    plt.imshow(noisy)
+    plt.draw()
+    plt.show()
+
+
+if __name__ == '__main__':
+    main()

extra_slides/packaging/noiser_project_final/noiser/noise.py

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+import numpy as np
+
+
+def white_noise(image, std):
+    noise = np.random.normal(scale=std, size=image.shape).astype(image.dtype)
+    noisy = image + noise
+    return noisy

extra_slides/packaging/noiser_project_final/noiser/setup.py

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+from setuptools import setup, find_packages
+
+setup(
+    name='Noiser',
+    version='1.0',
+    packages=find_packages(),
+)
+

extra_slides/packaging/noiser_project_final/noiser/tests/test_noise.py

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+import numpy as np
+from numpy.testing import assert_allclose
+
+from noiser.noise import white_noise
+
+
+def test_white_noise():
+    n_images, height, width = 201, 101, 102
+    dtype = np.float32
+
+    # Create ``n_images`` identical image.
+    base_image = np.random.rand(1, height, width, 3).astype(dtype) - 0.5
+    images = np.repeat(base_image, n_images, axis=0)
+
+    std = 0.13
+    noisy = white_noise(images, std=std)
+
+    # dtype and shape are preserved.
+    assert noisy.dtype == dtype
+    assert noisy.shape == images.shape
+
+    # Mean and std of noisy image match expectations.
+    assert_allclose(images.mean(0), base_image[0], atol=1e-4)
+    assert np.isclose((noisy - images).std(), std, atol=1e-4)

extra_slides/packaging/noiser_project_final/noiser/tests/test_utils.py

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+import numpy as np
+from numpy.testing import assert_array_equal
+
+from noiser.utils import copy_image
+
+
+def test_copy_image():
+    height, width = 101, 102
+    dtype = np.float32
+
+    image = np.random.rand(height, width, 3).astype(dtype)
+    copy = copy_image(image)
+    assert_array_equal(copy, image)
+

extra_slides/packaging/noiser_project_final/noiser/utils.pyx

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+import numpy as np
+cimport numpy as np
+
+
+def copy_image(np.ndarray img):
+    cdef int h = img.shape[0]
+    cdef int w = img.shape[1]
+    cdef int c = img.shape[2]
+    cdef np.ndarray copy = np.empty([h, w, c], dtype=img.dtype)
+
+    for i in range(h):
+        for j in range(w):
+            for k in range(c):
+                copy[i, j, k] = img[i, j, k]
+    return copy

extra_slides/packaging/noiser_project_final/setup.py

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+from Cython.Build import cythonize
+import numpy
+from setuptools import setup, find_packages
+from setuptools.extension import Extension
+
+
+extensions = [
+    Extension(
+        'noiser.utils',
+        ["noiser/utils.pyx"],
+        include_dirs=[numpy.get_include()],
+    )
+]
+
+
+setup(
+    name='Noiser',
+    version='1.0',
+    packages=find_packages(),
+    ext_modules=cythonize(extensions),
+    entry_points={
+        'console_scripts': [
+            'baboon=noiser.main:main',
+        ]
+    },
+    package_data={
+        'noiser': ['images/*.png'],
+    }
+)

extra_slides/profiling/residuals.py

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+import numpy as np
+import theano
+from theano import tensor as T
+
+
+SLOPE = 3.1
+INTERCEPT = -1.2
+
+
+def residual_stats_theano(x, y):
+    expected = SLOPE * x + INTERCEPT
+    residuals = y - expected
+    return residuals.mean(), residuals.std()
+
+
+x_var = T.vector()
+y_var = T.vector()
+
+residual_stats = theano.function(
+    inputs=[x_var, y_var],
+    outputs=residual_stats_theano(x_var, y_var),
+    allow_input_downcast=True,
+)
+
+
+if __name__ == '__main__':
+    x = np.linspace(-10, 10, 1000)
+    y = SLOPE * x + INTERCEPT
+    y += np.random.normal(loc=0.1, scale=0.5, size=x.shape)
+    mn, std = residual_stats(x, y)
+    print('Residual mean=', mn, ', std=', std)

extra_slides/profiling/residuals_profile.py

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+import numpy as np
+import theano
+from theano import tensor as T
+
+theano.config.profile_memory = True
+theano.config.profile = True
+
+
+SLOPE = 3.1
+INTERCEPT = -1.2
+
+
+def residual_stats_theano(x, y):
+    expected = SLOPE * x + INTERCEPT
+    residuals = y - expected
+    return residuals.mean(), residuals.std()
+
+
+x_var = T.vector()
+y_var = T.vector()
+
+residual_stats = theano.function(
+    inputs=[x_var, y_var],
+    outputs=residual_stats_theano(x_var, y_var),
+    allow_input_downcast=True,
+    profile=True,
+)
+
+
+if __name__ == '__main__':
+    x = np.linspace(-10, 10, 1000)
+    y = SLOPE * x + INTERCEPT
+    y += np.random.normal(loc=0.1, scale=0.5, size=x.shape)
+    mn, std = residual_stats(x, y)
+    print('Residual mean=', mn, ', std=', std)