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def test_keywordarg_passes_through_classicalnode(self, qubit_device_2_wires, tol):
"Tests that qnodes' keyword arguments pass through classical nodes."
def circuit(w, x=None):
qml.RX(w, wires=[0])
qml.RX(x, wires=[1])
return (qml.expval(qml.PauliZ(0)), qml.expval(qml.PauliZ(1)))
circuit = qml.QNode(circuit, qubit_device_2_wires).to_tf()
def classnode(w, x=None):
return circuit(w, x=x)
c = classnode(tf.constant(0.0), x=np.pi)
assert np.allclose(c.numpy(), [1.0, (- 1.0)], atol=tol, rtol=0) | -8,997,125,060,598,245,000 | Tests that qnodes' keyword arguments pass through classical nodes. | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_keywordarg_passes_through_classicalnode | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_keywordarg_passes_through_classicalnode(self, qubit_device_2_wires, tol):
def circuit(w, x=None):
qml.RX(w, wires=[0])
qml.RX(x, wires=[1])
return (qml.expval(qml.PauliZ(0)), qml.expval(qml.PauliZ(1)))
circuit = qml.QNode(circuit, qubit_device_2_wires).to_tf()
def classnode(w, x=None):
return circuit(w, x=x)
c = classnode(tf.constant(0.0), x=np.pi)
assert np.allclose(c.numpy(), [1.0, (- 1.0)], atol=tol, rtol=0) |
def test_keywordarg_gradient(self, qubit_device_2_wires, tol):
"Tests that qnodes' keyword arguments work with gradients"
def circuit(x, y, input_state=np.array([0, 0])):
qml.BasisState(input_state, wires=[0, 1])
qml.RX(x, wires=[0])
qml.RY(y, wires=[0])
return qml.expval(qml.PauliZ(0))
circuit = qml.QNode(circuit, qubit_device_2_wires).to_tf()
x = 0.543
y = 0.45632
expected_grad = np.array([(np.sin(x) * np.cos(y)), (np.sin(y) * np.cos(x))])
x_t = Variable(x)
y_t = Variable(y)
with tf.GradientTape() as tape:
c = circuit(x_t, y_t, input_state=np.array([0, 0]))
grads = np.array(tape.gradient(c, [x_t, y_t]))
assert np.allclose(grads, (- expected_grad), atol=tol, rtol=0)
with tf.GradientTape() as tape:
c = circuit(x_t, y_t, input_state=np.array([1, 0]))
grads = np.array(tape.gradient(c, [x_t, y_t]))
assert np.allclose(grads, expected_grad, atol=tol, rtol=0)
with tf.GradientTape() as tape:
c = circuit(x_t, y_t)
grads = np.array(tape.gradient(c, [x_t, y_t]))
assert np.allclose(grads, (- expected_grad), atol=tol, rtol=0) | 8,919,149,541,014,781,000 | Tests that qnodes' keyword arguments work with gradients | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_keywordarg_gradient | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_keywordarg_gradient(self, qubit_device_2_wires, tol):
def circuit(x, y, input_state=np.array([0, 0])):
qml.BasisState(input_state, wires=[0, 1])
qml.RX(x, wires=[0])
qml.RY(y, wires=[0])
return qml.expval(qml.PauliZ(0))
circuit = qml.QNode(circuit, qubit_device_2_wires).to_tf()
x = 0.543
y = 0.45632
expected_grad = np.array([(np.sin(x) * np.cos(y)), (np.sin(y) * np.cos(x))])
x_t = Variable(x)
y_t = Variable(y)
with tf.GradientTape() as tape:
c = circuit(x_t, y_t, input_state=np.array([0, 0]))
grads = np.array(tape.gradient(c, [x_t, y_t]))
assert np.allclose(grads, (- expected_grad), atol=tol, rtol=0)
with tf.GradientTape() as tape:
c = circuit(x_t, y_t, input_state=np.array([1, 0]))
grads = np.array(tape.gradient(c, [x_t, y_t]))
assert np.allclose(grads, expected_grad, atol=tol, rtol=0)
with tf.GradientTape() as tape:
c = circuit(x_t, y_t)
grads = np.array(tape.gradient(c, [x_t, y_t]))
assert np.allclose(grads, (- expected_grad), atol=tol, rtol=0) |
def test_qnode_evaluation_agrees(self, qubit_device_2_wires, tol):
'Tests that simple example is consistent.'
@qml.qnode(qubit_device_2_wires, interface='autograd')
def circuit(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
@qml.qnode(qubit_device_2_wires, interface='tf')
def circuit_tf(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
phi = [0.5, 0.1]
theta = [0.2]
phi_t = Variable(phi)
theta_t = Variable(theta)
autograd_eval = circuit(phi, theta)
tf_eval = circuit_tf(phi_t, theta_t)
assert np.allclose(autograd_eval, tf_eval.numpy(), atol=tol, rtol=0) | 4,092,149,334,003,494,000 | Tests that simple example is consistent. | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_qnode_evaluation_agrees | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_qnode_evaluation_agrees(self, qubit_device_2_wires, tol):
@qml.qnode(qubit_device_2_wires, interface='autograd')
def circuit(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
@qml.qnode(qubit_device_2_wires, interface='tf')
def circuit_tf(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
phi = [0.5, 0.1]
theta = [0.2]
phi_t = Variable(phi)
theta_t = Variable(theta)
autograd_eval = circuit(phi, theta)
tf_eval = circuit_tf(phi_t, theta_t)
assert np.allclose(autograd_eval, tf_eval.numpy(), atol=tol, rtol=0) |
def test_qnode_gradient_agrees(self, qubit_device_2_wires, tol):
'Tests that simple gradient example is consistent.'
@qml.qnode(qubit_device_2_wires, interface='autograd')
def circuit(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
@qml.qnode(qubit_device_2_wires, interface='tf')
def circuit_tf(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
phi = [0.5, 0.1]
theta = [0.2]
phi_t = Variable(phi)
theta_t = Variable(theta)
dcircuit = qml.grad(circuit, [0, 1])
autograd_grad = dcircuit(phi, theta)
with tf.GradientTape() as g:
g.watch([phi_t, theta_t])
y = circuit_tf(phi_t, theta_t)
tf_grad = g.gradient(y, [phi_t, theta_t])
assert np.allclose(autograd_grad[0], tf_grad[0], atol=tol, rtol=0)
assert np.allclose(autograd_grad[1], tf_grad[1], atol=tol, rtol=0) | -1,064,862,785,118,787,500 | Tests that simple gradient example is consistent. | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_qnode_gradient_agrees | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_qnode_gradient_agrees(self, qubit_device_2_wires, tol):
@qml.qnode(qubit_device_2_wires, interface='autograd')
def circuit(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
@qml.qnode(qubit_device_2_wires, interface='tf')
def circuit_tf(phi, theta):
qml.RX(phi[0], wires=0)
qml.RY(phi[1], wires=1)
qml.CNOT(wires=[0, 1])
qml.PhaseShift(theta[0], wires=0)
return qml.expval(qml.PauliZ(0))
phi = [0.5, 0.1]
theta = [0.2]
phi_t = Variable(phi)
theta_t = Variable(theta)
dcircuit = qml.grad(circuit, [0, 1])
autograd_grad = dcircuit(phi, theta)
with tf.GradientTape() as g:
g.watch([phi_t, theta_t])
y = circuit_tf(phi_t, theta_t)
tf_grad = g.gradient(y, [phi_t, theta_t])
assert np.allclose(autograd_grad[0], tf_grad[0], atol=tol, rtol=0)
assert np.allclose(autograd_grad[1], tf_grad[1], atol=tol, rtol=0) |
@pytest.fixture
def qnodes(self):
'Two QNodes to be used for the gradient tests'
dev = qml.device('default.qubit', wires=2)
@qml.qnode(dev, interface='tf')
def f(x):
qml.RX(x, wires=0)
return qml.expval(qml.PauliZ(0))
@qml.qnode(dev, interface='tf')
def g(y):
qml.RY(y, wires=0)
return qml.expval(qml.PauliX(0))
return (f, g) | -7,397,888,158,913,202,000 | Two QNodes to be used for the gradient tests | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | qnodes | MattePalte/Bugs-Quantum-Computing-Platforms | python | @pytest.fixture
def qnodes(self):
dev = qml.device('default.qubit', wires=2)
@qml.qnode(dev, interface='tf')
def f(x):
qml.RX(x, wires=0)
return qml.expval(qml.PauliZ(0))
@qml.qnode(dev, interface='tf')
def g(y):
qml.RY(y, wires=0)
return qml.expval(qml.PauliX(0))
return (f, g) |
@pytest.mark.parametrize('x, y', gradient_test_data)
def test_addition_qnodes_gradient(self, qnodes, x, y):
'Test the gradient of addition of two QNode circuits'
(f, g) = qnodes
def add(a, b):
return (a + b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = add(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == 1.0)
assert (grad[1].numpy() == 1.0)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
y = add(a, a)
grad = tape.gradient(y, [a, a])
assert (grad[0].numpy() == 2.0)
assert (grad[1].numpy() == 2.0)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(xt)
y = add(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == 1.0)
assert (grad[1].numpy() == 1.0) | -4,094,283,874,855,288,300 | Test the gradient of addition of two QNode circuits | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_addition_qnodes_gradient | MattePalte/Bugs-Quantum-Computing-Platforms | python | @pytest.mark.parametrize('x, y', gradient_test_data)
def test_addition_qnodes_gradient(self, qnodes, x, y):
(f, g) = qnodes
def add(a, b):
return (a + b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = add(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == 1.0)
assert (grad[1].numpy() == 1.0)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
y = add(a, a)
grad = tape.gradient(y, [a, a])
assert (grad[0].numpy() == 2.0)
assert (grad[1].numpy() == 2.0)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(xt)
y = add(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == 1.0)
assert (grad[1].numpy() == 1.0) |
@pytest.mark.parametrize('x, y', gradient_test_data)
def test_subtraction_qnodes_gradient(self, qnodes, x, y):
'Test the gradient of subtraction of two QNode circuits'
(f, g) = qnodes
def subtract(a, b):
return (a - b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = subtract(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == 1.0)
assert (grad[1].numpy() == (- 1.0)) | 2,051,418,203,866,679,300 | Test the gradient of subtraction of two QNode circuits | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_subtraction_qnodes_gradient | MattePalte/Bugs-Quantum-Computing-Platforms | python | @pytest.mark.parametrize('x, y', gradient_test_data)
def test_subtraction_qnodes_gradient(self, qnodes, x, y):
(f, g) = qnodes
def subtract(a, b):
return (a - b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = subtract(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == 1.0)
assert (grad[1].numpy() == (- 1.0)) |
@pytest.mark.parametrize('x, y', gradient_test_data)
def test_multiplication_qnodes_gradient(self, qnodes, x, y):
'Test the gradient of multiplication of two QNode circuits'
(f, g) = qnodes
def mult(a, b):
return (a * b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = mult(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == b.numpy())
assert (grad[1].numpy() == a.numpy()) | -5,933,840,820,186,481,000 | Test the gradient of multiplication of two QNode circuits | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_multiplication_qnodes_gradient | MattePalte/Bugs-Quantum-Computing-Platforms | python | @pytest.mark.parametrize('x, y', gradient_test_data)
def test_multiplication_qnodes_gradient(self, qnodes, x, y):
(f, g) = qnodes
def mult(a, b):
return (a * b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = mult(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == b.numpy())
assert (grad[1].numpy() == a.numpy()) |
@pytest.mark.parametrize('x, y', gradient_test_data)
def test_division_qnodes_gradient(self, qnodes, x, y, tol):
'Test the gradient of division of two QNode circuits'
(f, g) = qnodes
def div(a, b):
return (a / b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = div(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == (1 / b.numpy()))
assert np.allclose(grad[1].numpy(), ((- a.numpy()) / (b.numpy() ** 2)), atol=tol, rtol=0) | -7,874,686,265,030,168,000 | Test the gradient of division of two QNode circuits | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_division_qnodes_gradient | MattePalte/Bugs-Quantum-Computing-Platforms | python | @pytest.mark.parametrize('x, y', gradient_test_data)
def test_division_qnodes_gradient(self, qnodes, x, y, tol):
(f, g) = qnodes
def div(a, b):
return (a / b)
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt, yt])
a = f(xt)
b = g(yt)
y = div(a, b)
grad = tape.gradient(y, [a, b])
assert (grad[0].numpy() == (1 / b.numpy()))
assert np.allclose(grad[1].numpy(), ((- a.numpy()) / (b.numpy() ** 2)), atol=tol, rtol=0) |
@pytest.mark.parametrize('x, y', gradient_test_data)
def test_composition_qnodes_gradient(self, qnodes, x, y):
'Test the gradient of composition of two QNode circuits'
(f, g) = qnodes
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt])
y = f(xt)
grad1 = tape.gradient(y, xt)
with tf.GradientTape() as tape:
tape.watch([xt])
y = f(xt)
grad2 = tape.gradient(y, xt)
assert tf.equal(grad1, grad2)
with tf.GradientTape() as tape:
tape.watch([xt])
a = f(xt)
y = f(a)
grad1 = tape.gradient(y, a)
with tf.GradientTape() as tape:
tape.watch([xt])
a = f(xt)
y = f(a)
grad2 = tape.gradient(y, a)
assert tf.equal(grad1, grad2)
with tf.GradientTape() as tape:
tape.watch([xt])
b = g(xt)
y = g(b)
grad1 = tape.gradient(y, b)
with tf.GradientTape() as tape:
tape.watch([xt])
b = g(xt)
y = g(b)
grad2 = tape.gradient(y, b)
assert tf.equal(grad1, grad2) | 5,884,952,253,218,689,000 | Test the gradient of composition of two QNode circuits | artifacts/old_dataset_versions/minimal_commits/pennylane/pennylane#385/after/test_tf.py | test_composition_qnodes_gradient | MattePalte/Bugs-Quantum-Computing-Platforms | python | @pytest.mark.parametrize('x, y', gradient_test_data)
def test_composition_qnodes_gradient(self, qnodes, x, y):
(f, g) = qnodes
xt = Variable(x)
yt = Variable(y)
with tf.GradientTape() as tape:
tape.watch([xt])
y = f(xt)
grad1 = tape.gradient(y, xt)
with tf.GradientTape() as tape:
tape.watch([xt])
y = f(xt)
grad2 = tape.gradient(y, xt)
assert tf.equal(grad1, grad2)
with tf.GradientTape() as tape:
tape.watch([xt])
a = f(xt)
y = f(a)
grad1 = tape.gradient(y, a)
with tf.GradientTape() as tape:
tape.watch([xt])
a = f(xt)
y = f(a)
grad2 = tape.gradient(y, a)
assert tf.equal(grad1, grad2)
with tf.GradientTape() as tape:
tape.watch([xt])
b = g(xt)
y = g(b)
grad1 = tape.gradient(y, b)
with tf.GradientTape() as tape:
tape.watch([xt])
b = g(xt)
y = g(b)
grad2 = tape.gradient(y, b)
assert tf.equal(grad1, grad2) |
def tearDown(self):
'\n Clean up all the event sources left behind by either directly by\n test methods or indirectly via some distrib API.\n '
dl = [defer.Deferred(), defer.Deferred()]
if ((self.f1 is not None) and (self.f1.proto is not None)):
self.f1.proto.notifyOnDisconnect((lambda : dl[0].callback(None)))
else:
dl[0].callback(None)
if ((self.sub is not None) and (self.sub.publisher is not None)):
self.sub.publisher.broker.notifyOnDisconnect((lambda : dl[1].callback(None)))
self.sub.publisher.broker.transport.loseConnection()
else:
dl[1].callback(None)
if (self.port1 is not None):
dl.append(self.port1.stopListening())
if (self.port2 is not None):
dl.append(self.port2.stopListening())
return defer.gatherResults(dl) | 3,693,195,591,005,340,700 | Clean up all the event sources left behind by either directly by
test methods or indirectly via some distrib API. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | tearDown | 12123ads/learn_python3_spider | python | def tearDown(self):
'\n Clean up all the event sources left behind by either directly by\n test methods or indirectly via some distrib API.\n '
dl = [defer.Deferred(), defer.Deferred()]
if ((self.f1 is not None) and (self.f1.proto is not None)):
self.f1.proto.notifyOnDisconnect((lambda : dl[0].callback(None)))
else:
dl[0].callback(None)
if ((self.sub is not None) and (self.sub.publisher is not None)):
self.sub.publisher.broker.notifyOnDisconnect((lambda : dl[1].callback(None)))
self.sub.publisher.broker.transport.loseConnection()
else:
dl[1].callback(None)
if (self.port1 is not None):
dl.append(self.port1.stopListening())
if (self.port2 is not None):
dl.append(self.port2.stopListening())
return defer.gatherResults(dl) |
def _setupDistribServer(self, child):
'\n Set up a resource on a distrib site using L{ResourcePublisher}.\n\n @param child: The resource to publish using distrib.\n\n @return: A tuple consisting of the host and port on which to contact\n the created site.\n '
distribRoot = resource.Resource()
distribRoot.putChild(b'child', child)
distribSite = server.Site(distribRoot)
self.f1 = distribFactory = PBServerFactory(distrib.ResourcePublisher(distribSite))
distribPort = reactor.listenTCP(0, distribFactory, interface='127.0.0.1')
self.addCleanup(distribPort.stopListening)
addr = distribPort.getHost()
self.sub = mainRoot = distrib.ResourceSubscription(addr.host, addr.port)
mainSite = server.Site(mainRoot)
mainPort = reactor.listenTCP(0, mainSite, interface='127.0.0.1')
self.addCleanup(mainPort.stopListening)
mainAddr = mainPort.getHost()
return (mainPort, mainAddr) | -8,420,973,455,920,807,000 | Set up a resource on a distrib site using L{ResourcePublisher}.
@param child: The resource to publish using distrib.
@return: A tuple consisting of the host and port on which to contact
the created site. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | _setupDistribServer | 12123ads/learn_python3_spider | python | def _setupDistribServer(self, child):
'\n Set up a resource on a distrib site using L{ResourcePublisher}.\n\n @param child: The resource to publish using distrib.\n\n @return: A tuple consisting of the host and port on which to contact\n the created site.\n '
distribRoot = resource.Resource()
distribRoot.putChild(b'child', child)
distribSite = server.Site(distribRoot)
self.f1 = distribFactory = PBServerFactory(distrib.ResourcePublisher(distribSite))
distribPort = reactor.listenTCP(0, distribFactory, interface='127.0.0.1')
self.addCleanup(distribPort.stopListening)
addr = distribPort.getHost()
self.sub = mainRoot = distrib.ResourceSubscription(addr.host, addr.port)
mainSite = server.Site(mainRoot)
mainPort = reactor.listenTCP(0, mainSite, interface='127.0.0.1')
self.addCleanup(mainPort.stopListening)
mainAddr = mainPort.getHost()
return (mainPort, mainAddr) |
def _requestTest(self, child, **kwargs):
'\n Set up a resource on a distrib site using L{ResourcePublisher} and\n then retrieve it from a L{ResourceSubscription} via an HTTP client.\n\n @param child: The resource to publish using distrib.\n @param **kwargs: Extra keyword arguments to pass to L{Agent.request} when\n requesting the resource.\n\n @return: A L{Deferred} which fires with the result of the request.\n '
(mainPort, mainAddr) = self._setupDistribServer(child)
agent = client.Agent(reactor)
url = ('http://%s:%s/child' % (mainAddr.host, mainAddr.port))
url = url.encode('ascii')
d = agent.request(b'GET', url, **kwargs)
d.addCallback(client.readBody)
return d | 8,997,882,814,128,054,000 | Set up a resource on a distrib site using L{ResourcePublisher} and
then retrieve it from a L{ResourceSubscription} via an HTTP client.
@param child: The resource to publish using distrib.
@param **kwargs: Extra keyword arguments to pass to L{Agent.request} when
requesting the resource.
@return: A L{Deferred} which fires with the result of the request. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | _requestTest | 12123ads/learn_python3_spider | python | def _requestTest(self, child, **kwargs):
'\n Set up a resource on a distrib site using L{ResourcePublisher} and\n then retrieve it from a L{ResourceSubscription} via an HTTP client.\n\n @param child: The resource to publish using distrib.\n @param **kwargs: Extra keyword arguments to pass to L{Agent.request} when\n requesting the resource.\n\n @return: A L{Deferred} which fires with the result of the request.\n '
(mainPort, mainAddr) = self._setupDistribServer(child)
agent = client.Agent(reactor)
url = ('http://%s:%s/child' % (mainAddr.host, mainAddr.port))
url = url.encode('ascii')
d = agent.request(b'GET', url, **kwargs)
d.addCallback(client.readBody)
return d |
def _requestAgentTest(self, child, **kwargs):
'\n Set up a resource on a distrib site using L{ResourcePublisher} and\n then retrieve it from a L{ResourceSubscription} via an HTTP client.\n\n @param child: The resource to publish using distrib.\n @param **kwargs: Extra keyword arguments to pass to L{Agent.request} when\n requesting the resource.\n\n @return: A L{Deferred} which fires with a tuple consisting of a\n L{twisted.test.proto_helpers.AccumulatingProtocol} containing the\n body of the response and an L{IResponse} with the response itself.\n '
(mainPort, mainAddr) = self._setupDistribServer(child)
url = 'http://{}:{}/child'.format(mainAddr.host, mainAddr.port)
url = url.encode('ascii')
d = client.Agent(reactor).request(b'GET', url, **kwargs)
def cbCollectBody(response):
protocol = proto_helpers.AccumulatingProtocol()
response.deliverBody(protocol)
d = protocol.closedDeferred = defer.Deferred()
d.addCallback((lambda _: (protocol, response)))
return d
d.addCallback(cbCollectBody)
return d | -3,814,017,065,179,760,000 | Set up a resource on a distrib site using L{ResourcePublisher} and
then retrieve it from a L{ResourceSubscription} via an HTTP client.
@param child: The resource to publish using distrib.
@param **kwargs: Extra keyword arguments to pass to L{Agent.request} when
requesting the resource.
@return: A L{Deferred} which fires with a tuple consisting of a
L{twisted.test.proto_helpers.AccumulatingProtocol} containing the
body of the response and an L{IResponse} with the response itself. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | _requestAgentTest | 12123ads/learn_python3_spider | python | def _requestAgentTest(self, child, **kwargs):
'\n Set up a resource on a distrib site using L{ResourcePublisher} and\n then retrieve it from a L{ResourceSubscription} via an HTTP client.\n\n @param child: The resource to publish using distrib.\n @param **kwargs: Extra keyword arguments to pass to L{Agent.request} when\n requesting the resource.\n\n @return: A L{Deferred} which fires with a tuple consisting of a\n L{twisted.test.proto_helpers.AccumulatingProtocol} containing the\n body of the response and an L{IResponse} with the response itself.\n '
(mainPort, mainAddr) = self._setupDistribServer(child)
url = 'http://{}:{}/child'.format(mainAddr.host, mainAddr.port)
url = url.encode('ascii')
d = client.Agent(reactor).request(b'GET', url, **kwargs)
def cbCollectBody(response):
protocol = proto_helpers.AccumulatingProtocol()
response.deliverBody(protocol)
d = protocol.closedDeferred = defer.Deferred()
d.addCallback((lambda _: (protocol, response)))
return d
d.addCallback(cbCollectBody)
return d |
def test_requestHeaders(self):
"\n The request headers are available on the request object passed to a\n distributed resource's C{render} method.\n "
requestHeaders = {}
logObserver = proto_helpers.EventLoggingObserver()
globalLogPublisher.addObserver(logObserver)
req = [None]
class ReportRequestHeaders(resource.Resource):
def render(self, request):
req[0] = request
requestHeaders.update(dict(request.requestHeaders.getAllRawHeaders()))
return b''
def check_logs():
msgs = [e['log_format'] for e in logObserver]
self.assertIn('connected to publisher', msgs)
self.assertIn('could not connect to distributed web service: {msg}', msgs)
self.assertIn(req[0], msgs)
globalLogPublisher.removeObserver(logObserver)
request = self._requestTest(ReportRequestHeaders(), headers=Headers({'foo': ['bar']}))
def cbRequested(result):
self.f1.proto.notifyOnDisconnect(check_logs)
self.assertEqual(requestHeaders[b'Foo'], [b'bar'])
request.addCallback(cbRequested)
return request | 6,032,571,273,442,479,000 | The request headers are available on the request object passed to a
distributed resource's C{render} method. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_requestHeaders | 12123ads/learn_python3_spider | python | def test_requestHeaders(self):
"\n The request headers are available on the request object passed to a\n distributed resource's C{render} method.\n "
requestHeaders = {}
logObserver = proto_helpers.EventLoggingObserver()
globalLogPublisher.addObserver(logObserver)
req = [None]
class ReportRequestHeaders(resource.Resource):
def render(self, request):
req[0] = request
requestHeaders.update(dict(request.requestHeaders.getAllRawHeaders()))
return b
def check_logs():
msgs = [e['log_format'] for e in logObserver]
self.assertIn('connected to publisher', msgs)
self.assertIn('could not connect to distributed web service: {msg}', msgs)
self.assertIn(req[0], msgs)
globalLogPublisher.removeObserver(logObserver)
request = self._requestTest(ReportRequestHeaders(), headers=Headers({'foo': ['bar']}))
def cbRequested(result):
self.f1.proto.notifyOnDisconnect(check_logs)
self.assertEqual(requestHeaders[b'Foo'], [b'bar'])
request.addCallback(cbRequested)
return request |
def test_requestResponseCode(self):
"\n The response code can be set by the request object passed to a\n distributed resource's C{render} method.\n "
class SetResponseCode(resource.Resource):
def render(self, request):
request.setResponseCode(200)
return ''
request = self._requestAgentTest(SetResponseCode())
def cbRequested(result):
self.assertEqual(result[0].data, b'')
self.assertEqual(result[1].code, 200)
self.assertEqual(result[1].phrase, b'OK')
request.addCallback(cbRequested)
return request | 1,863,444,923,536,960,300 | The response code can be set by the request object passed to a
distributed resource's C{render} method. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_requestResponseCode | 12123ads/learn_python3_spider | python | def test_requestResponseCode(self):
"\n The response code can be set by the request object passed to a\n distributed resource's C{render} method.\n "
class SetResponseCode(resource.Resource):
def render(self, request):
request.setResponseCode(200)
return
request = self._requestAgentTest(SetResponseCode())
def cbRequested(result):
self.assertEqual(result[0].data, b)
self.assertEqual(result[1].code, 200)
self.assertEqual(result[1].phrase, b'OK')
request.addCallback(cbRequested)
return request |
def test_requestResponseCodeMessage(self):
"\n The response code and message can be set by the request object passed to\n a distributed resource's C{render} method.\n "
class SetResponseCode(resource.Resource):
def render(self, request):
request.setResponseCode(200, b'some-message')
return ''
request = self._requestAgentTest(SetResponseCode())
def cbRequested(result):
self.assertEqual(result[0].data, b'')
self.assertEqual(result[1].code, 200)
self.assertEqual(result[1].phrase, b'some-message')
request.addCallback(cbRequested)
return request | 2,802,432,140,346,846,700 | The response code and message can be set by the request object passed to
a distributed resource's C{render} method. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_requestResponseCodeMessage | 12123ads/learn_python3_spider | python | def test_requestResponseCodeMessage(self):
"\n The response code and message can be set by the request object passed to\n a distributed resource's C{render} method.\n "
class SetResponseCode(resource.Resource):
def render(self, request):
request.setResponseCode(200, b'some-message')
return
request = self._requestAgentTest(SetResponseCode())
def cbRequested(result):
self.assertEqual(result[0].data, b)
self.assertEqual(result[1].code, 200)
self.assertEqual(result[1].phrase, b'some-message')
request.addCallback(cbRequested)
return request |
def test_largeWrite(self):
'\n If a string longer than the Banana size limit is passed to the\n L{distrib.Request} passed to the remote resource, it is broken into\n smaller strings to be transported over the PB connection.\n '
class LargeWrite(resource.Resource):
def render(self, request):
request.write(((b'x' * SIZE_LIMIT) + b'y'))
request.finish()
return server.NOT_DONE_YET
request = self._requestTest(LargeWrite())
request.addCallback(self.assertEqual, ((b'x' * SIZE_LIMIT) + b'y'))
return request | -5,210,885,590,019,892,000 | If a string longer than the Banana size limit is passed to the
L{distrib.Request} passed to the remote resource, it is broken into
smaller strings to be transported over the PB connection. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_largeWrite | 12123ads/learn_python3_spider | python | def test_largeWrite(self):
'\n If a string longer than the Banana size limit is passed to the\n L{distrib.Request} passed to the remote resource, it is broken into\n smaller strings to be transported over the PB connection.\n '
class LargeWrite(resource.Resource):
def render(self, request):
request.write(((b'x' * SIZE_LIMIT) + b'y'))
request.finish()
return server.NOT_DONE_YET
request = self._requestTest(LargeWrite())
request.addCallback(self.assertEqual, ((b'x' * SIZE_LIMIT) + b'y'))
return request |
def test_largeReturn(self):
'\n Like L{test_largeWrite}, but for the case where C{render} returns a\n long string rather than explicitly passing it to L{Request.write}.\n '
class LargeReturn(resource.Resource):
def render(self, request):
return ((b'x' * SIZE_LIMIT) + b'y')
request = self._requestTest(LargeReturn())
request.addCallback(self.assertEqual, ((b'x' * SIZE_LIMIT) + b'y'))
return request | -9,676,789,066,152,152 | Like L{test_largeWrite}, but for the case where C{render} returns a
long string rather than explicitly passing it to L{Request.write}. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_largeReturn | 12123ads/learn_python3_spider | python | def test_largeReturn(self):
'\n Like L{test_largeWrite}, but for the case where C{render} returns a\n long string rather than explicitly passing it to L{Request.write}.\n '
class LargeReturn(resource.Resource):
def render(self, request):
return ((b'x' * SIZE_LIMIT) + b'y')
request = self._requestTest(LargeReturn())
request.addCallback(self.assertEqual, ((b'x' * SIZE_LIMIT) + b'y'))
return request |
def test_connectionLost(self):
'\n If there is an error issuing the request to the remote publisher, an\n error response is returned.\n '
self.f1 = serverFactory = PBServerFactory(pb.Root())
self.port1 = serverPort = reactor.listenTCP(0, serverFactory)
self.sub = subscription = distrib.ResourceSubscription('127.0.0.1', serverPort.getHost().port)
request = DummyRequest([b''])
d = _render(subscription, request)
def cbRendered(ignored):
self.assertEqual(request.responseCode, 500)
errors = self.flushLoggedErrors(pb.NoSuchMethod)
self.assertEqual(len(errors), 1)
expected = [b'', b'<html>', b' <head><title>500 - Server Connection Lost</title></head>', b' <body>', b' <h1>Server Connection Lost</h1>', b' <p>Connection to distributed server lost:<pre>[Failure instance: Traceback from remote host -- twisted.spread.flavors.NoSuchMethod: No such method: remote_request', b']</pre></p>', b' </body>', b'</html>', b'']
self.assertEqual([b'\n'.join(expected)], request.written)
d.addCallback(cbRendered)
return d | -6,647,387,831,302,386,000 | If there is an error issuing the request to the remote publisher, an
error response is returned. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_connectionLost | 12123ads/learn_python3_spider | python | def test_connectionLost(self):
'\n If there is an error issuing the request to the remote publisher, an\n error response is returned.\n '
self.f1 = serverFactory = PBServerFactory(pb.Root())
self.port1 = serverPort = reactor.listenTCP(0, serverFactory)
self.sub = subscription = distrib.ResourceSubscription('127.0.0.1', serverPort.getHost().port)
request = DummyRequest([b])
d = _render(subscription, request)
def cbRendered(ignored):
self.assertEqual(request.responseCode, 500)
errors = self.flushLoggedErrors(pb.NoSuchMethod)
self.assertEqual(len(errors), 1)
expected = [b, b'<html>', b' <head><title>500 - Server Connection Lost</title></head>', b' <body>', b' <h1>Server Connection Lost</h1>', b' <p>Connection to distributed server lost:<pre>[Failure instance: Traceback from remote host -- twisted.spread.flavors.NoSuchMethod: No such method: remote_request', b']</pre></p>', b' </body>', b'</html>', b]
self.assertEqual([b'\n'.join(expected)], request.written)
d.addCallback(cbRendered)
return d |
def test_logFailed(self):
'\n When a request fails, the string form of the failure is logged.\n '
logObserver = proto_helpers.EventLoggingObserver.createWithCleanup(self, globalLogPublisher)
f = failure.Failure(ArbitraryError())
request = DummyRequest([b''])
issue = distrib.Issue(request)
issue.failed(f)
self.assertEquals(1, len(logObserver))
self.assertIn('Failure instance', logObserver[0]['log_format']) | 117,272,590,343,925,780 | When a request fails, the string form of the failure is logged. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_logFailed | 12123ads/learn_python3_spider | python | def test_logFailed(self):
'\n \n '
logObserver = proto_helpers.EventLoggingObserver.createWithCleanup(self, globalLogPublisher)
f = failure.Failure(ArbitraryError())
request = DummyRequest([b])
issue = distrib.Issue(request)
issue.failed(f)
self.assertEquals(1, len(logObserver))
self.assertIn('Failure instance', logObserver[0]['log_format']) |
def test_requestFail(self):
"\n When L{twisted.web.distrib.Request}'s fail is called, the failure\n is logged.\n "
logObserver = proto_helpers.EventLoggingObserver.createWithCleanup(self, globalLogPublisher)
err = ArbitraryError()
f = failure.Failure(err)
req = distrib.Request(DummyChannel())
req.fail(f)
self.flushLoggedErrors(ArbitraryError)
self.assertEquals(1, len(logObserver))
self.assertIs(logObserver[0]['log_failure'], f) | 4,460,541,986,423,108,000 | When L{twisted.web.distrib.Request}'s fail is called, the failure
is logged. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_requestFail | 12123ads/learn_python3_spider | python | def test_requestFail(self):
"\n When L{twisted.web.distrib.Request}'s fail is called, the failure\n is logged.\n "
logObserver = proto_helpers.EventLoggingObserver.createWithCleanup(self, globalLogPublisher)
err = ArbitraryError()
f = failure.Failure(err)
req = distrib.Request(DummyChannel())
req.fail(f)
self.flushLoggedErrors(ArbitraryError)
self.assertEquals(1, len(logObserver))
self.assertIs(logObserver[0]['log_failure'], f) |
def test_interface(self):
'\n L{UserDirectory} instances provide L{resource.IResource}.\n '
self.assertTrue(verifyObject(resource.IResource, self.directory)) | 2,984,908,371,918,376,400 | L{UserDirectory} instances provide L{resource.IResource}. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_interface | 12123ads/learn_python3_spider | python | def test_interface(self):
'\n \n '
self.assertTrue(verifyObject(resource.IResource, self.directory)) |
def _404Test(self, name):
'\n Verify that requesting the C{name} child of C{self.directory} results\n in a 404 response.\n '
request = DummyRequest([name])
result = self.directory.getChild(name, request)
d = _render(result, request)
def cbRendered(ignored):
self.assertEqual(request.responseCode, 404)
d.addCallback(cbRendered)
return d | -7,691,561,648,553,702,000 | Verify that requesting the C{name} child of C{self.directory} results
in a 404 response. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | _404Test | 12123ads/learn_python3_spider | python | def _404Test(self, name):
'\n Verify that requesting the C{name} child of C{self.directory} results\n in a 404 response.\n '
request = DummyRequest([name])
result = self.directory.getChild(name, request)
d = _render(result, request)
def cbRendered(ignored):
self.assertEqual(request.responseCode, 404)
d.addCallback(cbRendered)
return d |
def test_getInvalidUser(self):
'\n L{UserDirectory.getChild} returns a resource which renders a 404\n response when passed a string which does not correspond to any known\n user.\n '
return self._404Test('carol') | 524,398,963,170,523,840 | L{UserDirectory.getChild} returns a resource which renders a 404
response when passed a string which does not correspond to any known
user. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_getInvalidUser | 12123ads/learn_python3_spider | python | def test_getInvalidUser(self):
'\n L{UserDirectory.getChild} returns a resource which renders a 404\n response when passed a string which does not correspond to any known\n user.\n '
return self._404Test('carol') |
def test_getUserWithoutResource(self):
'\n L{UserDirectory.getChild} returns a resource which renders a 404\n response when passed a string which corresponds to a known user who has\n neither a user directory nor a user distrib socket.\n '
return self._404Test('alice') | 2,095,579,798,873,494,500 | L{UserDirectory.getChild} returns a resource which renders a 404
response when passed a string which corresponds to a known user who has
neither a user directory nor a user distrib socket. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_getUserWithoutResource | 12123ads/learn_python3_spider | python | def test_getUserWithoutResource(self):
'\n L{UserDirectory.getChild} returns a resource which renders a 404\n response when passed a string which corresponds to a known user who has\n neither a user directory nor a user distrib socket.\n '
return self._404Test('alice') |
def test_getPublicHTMLChild(self):
'\n L{UserDirectory.getChild} returns a L{static.File} instance when passed\n the name of a user with a home directory containing a I{public_html}\n directory.\n '
home = filepath.FilePath(self.bob[(- 2)])
public_html = home.child('public_html')
public_html.makedirs()
request = DummyRequest(['bob'])
result = self.directory.getChild('bob', request)
self.assertIsInstance(result, static.File)
self.assertEqual(result.path, public_html.path) | 8,963,394,596,767,200,000 | L{UserDirectory.getChild} returns a L{static.File} instance when passed
the name of a user with a home directory containing a I{public_html}
directory. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_getPublicHTMLChild | 12123ads/learn_python3_spider | python | def test_getPublicHTMLChild(self):
'\n L{UserDirectory.getChild} returns a L{static.File} instance when passed\n the name of a user with a home directory containing a I{public_html}\n directory.\n '
home = filepath.FilePath(self.bob[(- 2)])
public_html = home.child('public_html')
public_html.makedirs()
request = DummyRequest(['bob'])
result = self.directory.getChild('bob', request)
self.assertIsInstance(result, static.File)
self.assertEqual(result.path, public_html.path) |
def test_getDistribChild(self):
'\n L{UserDirectory.getChild} returns a L{ResourceSubscription} instance\n when passed the name of a user suffixed with C{".twistd"} who has a\n home directory containing a I{.twistd-web-pb} socket.\n '
home = filepath.FilePath(self.bob[(- 2)])
home.makedirs()
web = home.child('.twistd-web-pb')
request = DummyRequest(['bob'])
result = self.directory.getChild('bob.twistd', request)
self.assertIsInstance(result, distrib.ResourceSubscription)
self.assertEqual(result.host, 'unix')
self.assertEqual(abspath(result.port), web.path) | 2,114,948,889,774,105,000 | L{UserDirectory.getChild} returns a L{ResourceSubscription} instance
when passed the name of a user suffixed with C{".twistd"} who has a
home directory containing a I{.twistd-web-pb} socket. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_getDistribChild | 12123ads/learn_python3_spider | python | def test_getDistribChild(self):
'\n L{UserDirectory.getChild} returns a L{ResourceSubscription} instance\n when passed the name of a user suffixed with C{".twistd"} who has a\n home directory containing a I{.twistd-web-pb} socket.\n '
home = filepath.FilePath(self.bob[(- 2)])
home.makedirs()
web = home.child('.twistd-web-pb')
request = DummyRequest(['bob'])
result = self.directory.getChild('bob.twistd', request)
self.assertIsInstance(result, distrib.ResourceSubscription)
self.assertEqual(result.host, 'unix')
self.assertEqual(abspath(result.port), web.path) |
def test_invalidMethod(self):
'\n L{UserDirectory.render} raises L{UnsupportedMethod} in response to a\n non-I{GET} request.\n '
request = DummyRequest([''])
request.method = 'POST'
self.assertRaises(server.UnsupportedMethod, self.directory.render, request) | 6,040,538,577,880,428,000 | L{UserDirectory.render} raises L{UnsupportedMethod} in response to a
non-I{GET} request. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_invalidMethod | 12123ads/learn_python3_spider | python | def test_invalidMethod(self):
'\n L{UserDirectory.render} raises L{UnsupportedMethod} in response to a\n non-I{GET} request.\n '
request = DummyRequest([])
request.method = 'POST'
self.assertRaises(server.UnsupportedMethod, self.directory.render, request) |
def test_render(self):
'\n L{UserDirectory} renders a list of links to available user content\n in response to a I{GET} request.\n '
public_html = filepath.FilePath(self.alice[(- 2)]).child('public_html')
public_html.makedirs()
web = filepath.FilePath(self.bob[(- 2)])
web.makedirs()
web.child('.twistd-web-pb').setContent(b'')
request = DummyRequest([''])
result = _render(self.directory, request)
def cbRendered(ignored):
document = parseString(b''.join(request.written))
[alice, bob] = document.getElementsByTagName('li')
self.assertEqual(alice.firstChild.tagName, 'a')
self.assertEqual(alice.firstChild.getAttribute('href'), 'alice/')
self.assertEqual(alice.firstChild.firstChild.data, 'Alice (file)')
self.assertEqual(bob.firstChild.tagName, 'a')
self.assertEqual(bob.firstChild.getAttribute('href'), 'bob.twistd/')
self.assertEqual(bob.firstChild.firstChild.data, 'Bob (twistd)')
result.addCallback(cbRendered)
return result | -8,024,123,066,555,492,000 | L{UserDirectory} renders a list of links to available user content
in response to a I{GET} request. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_render | 12123ads/learn_python3_spider | python | def test_render(self):
'\n L{UserDirectory} renders a list of links to available user content\n in response to a I{GET} request.\n '
public_html = filepath.FilePath(self.alice[(- 2)]).child('public_html')
public_html.makedirs()
web = filepath.FilePath(self.bob[(- 2)])
web.makedirs()
web.child('.twistd-web-pb').setContent(b)
request = DummyRequest([])
result = _render(self.directory, request)
def cbRendered(ignored):
document = parseString(b.join(request.written))
[alice, bob] = document.getElementsByTagName('li')
self.assertEqual(alice.firstChild.tagName, 'a')
self.assertEqual(alice.firstChild.getAttribute('href'), 'alice/')
self.assertEqual(alice.firstChild.firstChild.data, 'Alice (file)')
self.assertEqual(bob.firstChild.tagName, 'a')
self.assertEqual(bob.firstChild.getAttribute('href'), 'bob.twistd/')
self.assertEqual(bob.firstChild.firstChild.data, 'Bob (twistd)')
result.addCallback(cbRendered)
return result |
def test_passwordDatabase(self):
'\n If L{UserDirectory} is instantiated with no arguments, it uses the\n L{pwd} module as its password database.\n '
directory = distrib.UserDirectory()
self.assertIdentical(directory._pwd, pwd) | -2,410,661,611,890,471,400 | If L{UserDirectory} is instantiated with no arguments, it uses the
L{pwd} module as its password database. | stackoverflow/venv/lib/python3.6/site-packages/twisted/web/test/test_distrib.py | test_passwordDatabase | 12123ads/learn_python3_spider | python | def test_passwordDatabase(self):
'\n If L{UserDirectory} is instantiated with no arguments, it uses the\n L{pwd} module as its password database.\n '
directory = distrib.UserDirectory()
self.assertIdentical(directory._pwd, pwd) |
def on_train_begin(self, **kwargs):
'Call watch method to log model topology, gradients & weights'
super().on_train_begin()
if (not WandbCallback._watch_called):
WandbCallback._watch_called = True
wandb.watch(self.learn.model, log=self.log) | 8,583,803,843,895,094,000 | Call watch method to log model topology, gradients & weights | wandb/fastai/__init__.py | on_train_begin | MPGek/client | python | def on_train_begin(self, **kwargs):
super().on_train_begin()
if (not WandbCallback._watch_called):
WandbCallback._watch_called = True
wandb.watch(self.learn.model, log=self.log) |
def on_epoch_end(self, epoch, smooth_loss, last_metrics, **kwargs):
'Logs training loss, validation loss and custom metrics & log prediction samples & save model'
if self.save_model:
current = self.get_monitor_value()
if ((current is not None) and self.operator(current, self.best)):
print('Better model found at epoch {} with {} value: {}.'.format(epoch, self.monitor, current))
self.best = current
with self.model_path.open('wb') as model_file:
self.learn.save(model_file)
if self.validation_data:
try:
self._wandb_log_predictions()
except FastaiError as e:
wandb.termwarn(e.message)
self.validation_data = None
except Exception as e:
wandb.termwarn('Unable to log prediction samples.\n{}'.format(e))
self.validation_data = None
logs = {name: stat for (name, stat) in list(zip(self.learn.recorder.names, ([epoch, smooth_loss] + last_metrics)))}
wandb.log(logs) | -2,929,695,461,219,322,000 | Logs training loss, validation loss and custom metrics & log prediction samples & save model | wandb/fastai/__init__.py | on_epoch_end | MPGek/client | python | def on_epoch_end(self, epoch, smooth_loss, last_metrics, **kwargs):
if self.save_model:
current = self.get_monitor_value()
if ((current is not None) and self.operator(current, self.best)):
print('Better model found at epoch {} with {} value: {}.'.format(epoch, self.monitor, current))
self.best = current
with self.model_path.open('wb') as model_file:
self.learn.save(model_file)
if self.validation_data:
try:
self._wandb_log_predictions()
except FastaiError as e:
wandb.termwarn(e.message)
self.validation_data = None
except Exception as e:
wandb.termwarn('Unable to log prediction samples.\n{}'.format(e))
self.validation_data = None
logs = {name: stat for (name, stat) in list(zip(self.learn.recorder.names, ([epoch, smooth_loss] + last_metrics)))}
wandb.log(logs) |
def on_train_end(self, **kwargs):
'Load the best model.'
if self.save_model:
if self.model_path.is_file():
with self.model_path.open('rb') as model_file:
self.learn.load(model_file, purge=False)
print('Loaded best saved model from {}'.format(self.model_path)) | -5,013,564,440,215,056,000 | Load the best model. | wandb/fastai/__init__.py | on_train_end | MPGek/client | python | def on_train_end(self, **kwargs):
if self.save_model:
if self.model_path.is_file():
with self.model_path.open('rb') as model_file:
self.learn.load(model_file, purge=False)
print('Loaded best saved model from {}'.format(self.model_path)) |
def _wandb_log_predictions(self):
'Log prediction samples'
pred_log = []
for (x, y) in self.validation_data:
try:
pred = self.learn.predict(x)
except:
raise FastaiError('Unable to run "predict" method from Learner to log prediction samples.')
if (not pred[1].shape):
pred_log.append(wandb.Image(x.data, caption='Ground Truth: {}\nPrediction: {}'.format(y, pred[0])))
elif hasattr(x, 'show'):
pred_log.append(wandb.Image(x.data, caption='Input data', grouping=3))
for (im, capt) in ((pred[0], 'Prediction'), (y, 'Ground Truth')):
my_dpi = 100
fig = plt.figure(frameon=False, dpi=my_dpi)
(h, w) = x.size
fig.set_size_inches((w / my_dpi), (h / my_dpi))
ax = plt.Axes(fig, [0.0, 0.0, 1.0, 1.0])
ax.set_axis_off()
fig.add_axes(ax)
x.show(ax=ax, y=im)
pred_log.append(wandb.Image(fig, caption=capt))
plt.close(fig)
elif (hasattr(y, 'shape') and ((len(y.shape) == 2) or ((len(y.shape) == 3) and (y.shape[0] in [1, 3, 4])))):
pred_log.extend([wandb.Image(x.data, caption='Input data', grouping=3), wandb.Image(pred[0].data, caption='Prediction'), wandb.Image(y.data, caption='Ground Truth')])
else:
pred_log.append(wandb.Image(x.data, caption='Input data'))
wandb.log({'Prediction Samples': pred_log}, commit=False) | -7,904,175,559,029,698,000 | Log prediction samples | wandb/fastai/__init__.py | _wandb_log_predictions | MPGek/client | python | def _wandb_log_predictions(self):
pred_log = []
for (x, y) in self.validation_data:
try:
pred = self.learn.predict(x)
except:
raise FastaiError('Unable to run "predict" method from Learner to log prediction samples.')
if (not pred[1].shape):
pred_log.append(wandb.Image(x.data, caption='Ground Truth: {}\nPrediction: {}'.format(y, pred[0])))
elif hasattr(x, 'show'):
pred_log.append(wandb.Image(x.data, caption='Input data', grouping=3))
for (im, capt) in ((pred[0], 'Prediction'), (y, 'Ground Truth')):
my_dpi = 100
fig = plt.figure(frameon=False, dpi=my_dpi)
(h, w) = x.size
fig.set_size_inches((w / my_dpi), (h / my_dpi))
ax = plt.Axes(fig, [0.0, 0.0, 1.0, 1.0])
ax.set_axis_off()
fig.add_axes(ax)
x.show(ax=ax, y=im)
pred_log.append(wandb.Image(fig, caption=capt))
plt.close(fig)
elif (hasattr(y, 'shape') and ((len(y.shape) == 2) or ((len(y.shape) == 3) and (y.shape[0] in [1, 3, 4])))):
pred_log.extend([wandb.Image(x.data, caption='Input data', grouping=3), wandb.Image(pred[0].data, caption='Prediction'), wandb.Image(y.data, caption='Ground Truth')])
else:
pred_log.append(wandb.Image(x.data, caption='Input data'))
wandb.log({'Prediction Samples': pred_log}, commit=False) |
def find_in_path(name, path):
'Find a file in a search path'
for dir in path.split(os.pathsep):
binpath = pjoin(dir, name)
if os.path.exists(binpath):
return os.path.abspath(binpath)
return None | -4,401,254,251,811,251,000 | Find a file in a search path | swig_muesli/muesli/da/setup_da.py | find_in_path | NinaHerrmann/muesli2py | python | def find_in_path(name, path):
for dir in path.split(os.pathsep):
binpath = pjoin(dir, name)
if os.path.exists(binpath):
return os.path.abspath(binpath)
return None |
def length_normalize(matrix):
'Length normalize the matrix\n\n Args:\n matrix (np.ndarray): Input matrix that needs to be normalized\n\n Returns:\n Normalized matrix\n '
norms = np.sqrt(np.sum((matrix ** 2), axis=1))
norms[(norms == 0)] = 1
return (matrix / norms[:, np.newaxis]) | -9,094,982,554,804,503,000 | Length normalize the matrix
Args:
matrix (np.ndarray): Input matrix that needs to be normalized
Returns:
Normalized matrix | reco_utils/recommender/geoimc/geoimc_utils.py | length_normalize | 154King154/recommenders | python | def length_normalize(matrix):
'Length normalize the matrix\n\n Args:\n matrix (np.ndarray): Input matrix that needs to be normalized\n\n Returns:\n Normalized matrix\n '
norms = np.sqrt(np.sum((matrix ** 2), axis=1))
norms[(norms == 0)] = 1
return (matrix / norms[:, np.newaxis]) |
def mean_center(matrix):
'Performs mean centering across axis 0\n\n Args:\n matrix (np.ndarray): Input matrix that needs to be mean centered\n '
avg = np.mean(matrix, axis=0)
matrix -= avg | 313,667,976,247,406,600 | Performs mean centering across axis 0
Args:
matrix (np.ndarray): Input matrix that needs to be mean centered | reco_utils/recommender/geoimc/geoimc_utils.py | mean_center | 154King154/recommenders | python | def mean_center(matrix):
'Performs mean centering across axis 0\n\n Args:\n matrix (np.ndarray): Input matrix that needs to be mean centered\n '
avg = np.mean(matrix, axis=0)
matrix -= avg |
def reduce_dims(matrix, target_dim):
'Reduce dimensionality of the data using PCA.\n\n Args:\n matrix (np.ndarray): Matrix of the form (n_sampes, n_features)\n target_dim (uint): Dimension to which n_features should be reduced to.\n\n '
model = PCA(n_components=target_dim)
model.fit(matrix)
return model.transform(matrix) | 8,133,367,132,709,024,000 | Reduce dimensionality of the data using PCA.
Args:
matrix (np.ndarray): Matrix of the form (n_sampes, n_features)
target_dim (uint): Dimension to which n_features should be reduced to. | reco_utils/recommender/geoimc/geoimc_utils.py | reduce_dims | 154King154/recommenders | python | def reduce_dims(matrix, target_dim):
'Reduce dimensionality of the data using PCA.\n\n Args:\n matrix (np.ndarray): Matrix of the form (n_sampes, n_features)\n target_dim (uint): Dimension to which n_features should be reduced to.\n\n '
model = PCA(n_components=target_dim)
model.fit(matrix)
return model.transform(matrix) |
def longestCommonSubsequence(self, text1: str, text2: str) -> int:
'\n #最长连续公共子串\n l1=len(text1)\n l2=len(text2)\n\n if l1==0 or l2==0:\n return 0\n dp = [[0 for i in range(l2)] for i in range(l1)]\n res = 0\n if text1[0]==text2[0]:\n dp[0][0]=1\n res=1\n for i in range(1,l2):\n if text2[i]==text1[0]:\n dp[0][i]=1\n res=1\n for i in range(1,l1):\n if text1[i]==text2[0]:\n dp[i][0]=1\n res=1\n\n\n for i in range(1,l1):\n for j in range(1,l2):\n if text1[i]==text2[j]:\n dp[i][j]=dp[i-1][j-1]+1\n res=max(res,dp[i][j])\n\n return res\n '
'\n #最长子串（可不连续）：其实就是在问text1[:i+1]和text2[:j+1]有多少个相同的字母\n l1 = len(text1)\n l2 = len(text2)\n\n if l1 == 0 or l2 == 0:\n return 0\n dp = [[0 for i in range(l2)] for i in range(l1)]\n if text1[0] == text2[0]:\n dp[0][0] = 1\n for i in range(1, l2):\n if text2[i] == text1[0] or dp[0][0]==1 or dp[0][i-1]==1:\n dp[0][i] = 1\n for i in range(1, l1):\n if text1[i] == text2[0] or dp[0][0]==1 or dp[i-1][0]==1:\n dp[i][0] = 1\n\n for i in range(1, l1):\n for j in range(1, l2):\n if text1[i] == text2[j]:\n dp[i][j] = dp[i - 1][j - 1] + 1\n else:\n dp[i][j]=max(dp[i][j-1],dp[i-1][j])\n\n return dp[-1][-1]\n '
if ((len(text1) == 0) or (len(text2) == 0)):
return 0
if (text1[(- 1)] == text2[(- 1)]):
return (1 + self.longestCommonSubsequence(text1[:(- 1)], text2[:(- 1)]))
else:
return max(self.longestCommonSubsequence(text1[:(- 1)], text2), self.longestCommonSubsequence(text1, text2[:(- 1)])) | -8,524,905,220,200,732,000 | #最长连续公共子串
l1=len(text1)
l2=len(text2)
if l1==0 or l2==0:
return 0
dp = [[0 for i in range(l2)] for i in range(l1)]
res = 0
if text1[0]==text2[0]:
dp[0][0]=1
res=1
for i in range(1,l2):
if text2[i]==text1[0]:
dp[0][i]=1
res=1
for i in range(1,l1):
if text1[i]==text2[0]:
dp[i][0]=1
res=1
for i in range(1,l1):
for j in range(1,l2):
if text1[i]==text2[j]:
dp[i][j]=dp[i-1][j-1]+1
res=max(res,dp[i][j])
return res | DP/Leetcode1143.py | longestCommonSubsequence | Rylie-W/LeetRecord | python | def longestCommonSubsequence(self, text1: str, text2: str) -> int:
'\n #最长连续公共子串\n l1=len(text1)\n l2=len(text2)\n\n if l1==0 or l2==0:\n return 0\n dp = [[0 for i in range(l2)] for i in range(l1)]\n res = 0\n if text1[0]==text2[0]:\n dp[0][0]=1\n res=1\n for i in range(1,l2):\n if text2[i]==text1[0]:\n dp[0][i]=1\n res=1\n for i in range(1,l1):\n if text1[i]==text2[0]:\n dp[i][0]=1\n res=1\n\n\n for i in range(1,l1):\n for j in range(1,l2):\n if text1[i]==text2[j]:\n dp[i][j]=dp[i-1][j-1]+1\n res=max(res,dp[i][j])\n\n return res\n '
'\n #最长子串（可不连续）：其实就是在问text1[:i+1]和text2[:j+1]有多少个相同的字母\n l1 = len(text1)\n l2 = len(text2)\n\n if l1 == 0 or l2 == 0:\n return 0\n dp = [[0 for i in range(l2)] for i in range(l1)]\n if text1[0] == text2[0]:\n dp[0][0] = 1\n for i in range(1, l2):\n if text2[i] == text1[0] or dp[0][0]==1 or dp[0][i-1]==1:\n dp[0][i] = 1\n for i in range(1, l1):\n if text1[i] == text2[0] or dp[0][0]==1 or dp[i-1][0]==1:\n dp[i][0] = 1\n\n for i in range(1, l1):\n for j in range(1, l2):\n if text1[i] == text2[j]:\n dp[i][j] = dp[i - 1][j - 1] + 1\n else:\n dp[i][j]=max(dp[i][j-1],dp[i-1][j])\n\n return dp[-1][-1]\n '
if ((len(text1) == 0) or (len(text2) == 0)):
return 0
if (text1[(- 1)] == text2[(- 1)]):
return (1 + self.longestCommonSubsequence(text1[:(- 1)], text2[:(- 1)]))
else:
return max(self.longestCommonSubsequence(text1[:(- 1)], text2), self.longestCommonSubsequence(text1, text2[:(- 1)])) |
def initialize_weights(model):
'\n Initializes the weights of a model in place.\n\n :param model: An nn.Module.\n '
for param in model.parameters():
if (param.dim() > 1):
nn.init.xavier_normal_(param) | -4,855,580,883,977,360,000 | Initializes the weights of a model in place.
:param model: An nn.Module. | Repeat/CoMPT/utils_node.py | initialize_weights | jcchan23/SAIL | python | def initialize_weights(model):
'\n Initializes the weights of a model in place.\n\n :param model: An nn.Module.\n '
for param in model.parameters():
if (param.dim() > 1):
nn.init.xavier_normal_(param) |
def __init__(self, optimizer, warmup_epochs, total_epochs, steps_per_epoch, init_lr, max_lr, final_lr):
'\n Initializes the learning rate scheduler.\n\n :param optimizer: A PyTorch optimizer.\n :param warmup_epochs: The number of epochs during which to linearly increase the learning rate.\n :param total_epochs: The total number of epochs.\n :param steps_per_epoch: The number of steps (batches) per epoch.\n :param init_lr: The initial learning rate.\n :param max_lr: The maximum learning rate (achieved after warmup_epochs).\n :param final_lr: The final learning rate (achieved after total_epochs).\n '
assert (len(optimizer.param_groups) == len(warmup_epochs) == len(total_epochs) == len(init_lr) == len(max_lr) == len(final_lr))
self.num_lrs = len(optimizer.param_groups)
self.optimizer = optimizer
self.warmup_epochs = np.array(warmup_epochs)
self.total_epochs = np.array(total_epochs)
self.steps_per_epoch = steps_per_epoch
self.init_lr = np.array(init_lr)
self.max_lr = np.array(max_lr)
self.final_lr = np.array(final_lr)
self.current_step = 0
self.lr = init_lr
self.warmup_steps = (self.warmup_epochs * self.steps_per_epoch).astype(int)
self.total_steps = (self.total_epochs * self.steps_per_epoch)
self.linear_increment = ((self.max_lr - self.init_lr) / self.warmup_steps)
self.exponential_gamma = ((self.final_lr / self.max_lr) ** (1 / (self.total_steps - self.warmup_steps)))
super(NoamLR, self).__init__(optimizer) | 8,412,762,859,212,071,000 | Initializes the learning rate scheduler.
:param optimizer: A PyTorch optimizer.
:param warmup_epochs: The number of epochs during which to linearly increase the learning rate.
:param total_epochs: The total number of epochs.
:param steps_per_epoch: The number of steps (batches) per epoch.
:param init_lr: The initial learning rate.
:param max_lr: The maximum learning rate (achieved after warmup_epochs).
:param final_lr: The final learning rate (achieved after total_epochs). | Repeat/CoMPT/utils_node.py | __init__ | jcchan23/SAIL | python | def __init__(self, optimizer, warmup_epochs, total_epochs, steps_per_epoch, init_lr, max_lr, final_lr):
'\n Initializes the learning rate scheduler.\n\n :param optimizer: A PyTorch optimizer.\n :param warmup_epochs: The number of epochs during which to linearly increase the learning rate.\n :param total_epochs: The total number of epochs.\n :param steps_per_epoch: The number of steps (batches) per epoch.\n :param init_lr: The initial learning rate.\n :param max_lr: The maximum learning rate (achieved after warmup_epochs).\n :param final_lr: The final learning rate (achieved after total_epochs).\n '
assert (len(optimizer.param_groups) == len(warmup_epochs) == len(total_epochs) == len(init_lr) == len(max_lr) == len(final_lr))
self.num_lrs = len(optimizer.param_groups)
self.optimizer = optimizer
self.warmup_epochs = np.array(warmup_epochs)
self.total_epochs = np.array(total_epochs)
self.steps_per_epoch = steps_per_epoch
self.init_lr = np.array(init_lr)
self.max_lr = np.array(max_lr)
self.final_lr = np.array(final_lr)
self.current_step = 0
self.lr = init_lr
self.warmup_steps = (self.warmup_epochs * self.steps_per_epoch).astype(int)
self.total_steps = (self.total_epochs * self.steps_per_epoch)
self.linear_increment = ((self.max_lr - self.init_lr) / self.warmup_steps)
self.exponential_gamma = ((self.final_lr / self.max_lr) ** (1 / (self.total_steps - self.warmup_steps)))
super(NoamLR, self).__init__(optimizer) |
def get_lr(self):
'Gets a list of the current learning rates.'
return list(self.lr) | -3,543,556,912,278,854,700 | Gets a list of the current learning rates. | Repeat/CoMPT/utils_node.py | get_lr | jcchan23/SAIL | python | def get_lr(self):
return list(self.lr) |
def step(self, current_step: int=None):
'\n Updates the learning rate by taking a step.\n\n :param current_step: Optionally specify what step to set the learning rate to.\n If None, current_step = self.current_step + 1.\n '
if (current_step is not None):
self.current_step = current_step
else:
self.current_step += 1
for i in range(self.num_lrs):
if (self.current_step <= self.warmup_steps[i]):
self.lr[i] = (self.init_lr[i] + (self.current_step * self.linear_increment[i]))
elif (self.current_step <= self.total_steps[i]):
self.lr[i] = (self.max_lr[i] * (self.exponential_gamma[i] ** (self.current_step - self.warmup_steps[i])))
else:
self.lr[i] = self.final_lr[i]
self.optimizer.param_groups[i]['lr'] = self.lr[i] | -2,704,965,584,552,467,000 | Updates the learning rate by taking a step.
:param current_step: Optionally specify what step to set the learning rate to.
If None, current_step = self.current_step + 1. | Repeat/CoMPT/utils_node.py | step | jcchan23/SAIL | python | def step(self, current_step: int=None):
'\n Updates the learning rate by taking a step.\n\n :param current_step: Optionally specify what step to set the learning rate to.\n If None, current_step = self.current_step + 1.\n '
if (current_step is not None):
self.current_step = current_step
else:
self.current_step += 1
for i in range(self.num_lrs):
if (self.current_step <= self.warmup_steps[i]):
self.lr[i] = (self.init_lr[i] + (self.current_step * self.linear_increment[i]))
elif (self.current_step <= self.total_steps[i]):
self.lr[i] = (self.max_lr[i] * (self.exponential_gamma[i] ** (self.current_step - self.warmup_steps[i])))
else:
self.lr[i] = self.final_lr[i]
self.optimizer.param_groups[i]['lr'] = self.lr[i] |
def setUp(self):
'Get all the PROTO files to be tested.'
self.version = None
with open(((((os.environ['WEBOTS_HOME'] + os.sep) + 'resources') + os.sep) + 'version.txt')) as file:
content = file.read()
self.version = content.splitlines()[0].strip().split()[0]
self.files = []
for (rootPath, dirNames, fileNames) in os.walk(os.environ['WEBOTS_HOME']):
dirNames[:] = [d for d in dirNames if (d not in skippedDirectories)]
for fileName in fnmatch.filter(fileNames, '*.proto'):
proto = os.path.join(rootPath, fileName)
shouldIgnore = False
for ignoredProto in ignoredProtos:
path = ((os.environ['WEBOTS_HOME'] + os.sep) + ignoredProto.replace('/', os.sep))
if (proto == path):
shouldIgnore = True
break
if (not shouldIgnore):
self.files.append((proto, ('#VRML_SIM %s utf8' % self.version)))
for (rootPath, dirNames, fileNames) in os.walk(os.environ['WEBOTS_HOME']):
dirNames[:] = [d for d in dirNames if (d not in skippedDirectories)]
for fileName in fnmatch.filter(fileNames, '*.wbt'):
world = os.path.join(rootPath, fileName)
self.files.append((world, ('#VRML_SIM %s utf8' % self.version)))
for (rootPath, dirNames, fileNames) in os.walk(os.environ['WEBOTS_HOME']):
dirNames[:] = [d for d in dirNames if (d not in skippedDirectories)]
for fileName in fnmatch.filter(fileNames, '*.wbproj'):
projFile = os.path.join(rootPath, fileName)
self.files.append((projFile, ('Webots Project File version %s' % self.version))) | -3,331,968,831,251,895,300 | Get all the PROTO files to be tested. | tests/sources/test_header_version.py | setUp | junjihashimoto/webots | python | def setUp(self):
self.version = None
with open(((((os.environ['WEBOTS_HOME'] + os.sep) + 'resources') + os.sep) + 'version.txt')) as file:
content = file.read()
self.version = content.splitlines()[0].strip().split()[0]
self.files = []
for (rootPath, dirNames, fileNames) in os.walk(os.environ['WEBOTS_HOME']):
dirNames[:] = [d for d in dirNames if (d not in skippedDirectories)]
for fileName in fnmatch.filter(fileNames, '*.proto'):
proto = os.path.join(rootPath, fileName)
shouldIgnore = False
for ignoredProto in ignoredProtos:
path = ((os.environ['WEBOTS_HOME'] + os.sep) + ignoredProto.replace('/', os.sep))
if (proto == path):
shouldIgnore = True
break
if (not shouldIgnore):
self.files.append((proto, ('#VRML_SIM %s utf8' % self.version)))
for (rootPath, dirNames, fileNames) in os.walk(os.environ['WEBOTS_HOME']):
dirNames[:] = [d for d in dirNames if (d not in skippedDirectories)]
for fileName in fnmatch.filter(fileNames, '*.wbt'):
world = os.path.join(rootPath, fileName)
self.files.append((world, ('#VRML_SIM %s utf8' % self.version)))
for (rootPath, dirNames, fileNames) in os.walk(os.environ['WEBOTS_HOME']):
dirNames[:] = [d for d in dirNames if (d not in skippedDirectories)]
for fileName in fnmatch.filter(fileNames, '*.wbproj'):
projFile = os.path.join(rootPath, fileName)
self.files.append((projFile, ('Webots Project File version %s' % self.version))) |
def test_header_version(self):
'Test that the PROTO and world files have the correct header.'
for currentFile in self.files:
fileToTest = currentFile[0]
with open(fileToTest) as file:
content = file.read()
if (content == ''):
continue
line = content.splitlines()[0].strip()
self.assertTrue(line.startswith(currentFile[1]), msg=('Wrong header in file: "%s"' % fileToTest)) | -272,396,101,947,376,400 | Test that the PROTO and world files have the correct header. | tests/sources/test_header_version.py | test_header_version | junjihashimoto/webots | python | def test_header_version(self):
for currentFile in self.files:
fileToTest = currentFile[0]
with open(fileToTest) as file:
content = file.read()
if (content == ):
continue
line = content.splitlines()[0].strip()
self.assertTrue(line.startswith(currentFile[1]), msg=('Wrong header in file: "%s"' % fileToTest)) |
def float_with_error(x):
'\n some value in cif accompanies error like "1.234(5)\n '
if ('?' in x):
return 0
pos = x.find('(')
if (pos >= 0):
x = x[:pos]
return float(x) | -7,629,848,625,370,556,000 | some value in cif accompanies error like "1.234(5) | cif_tools.py | float_with_error | cwaitt/zse | python | def float_with_error(x):
'\n \n '
if ('?' in x):
return 0
pos = x.find('(')
if (pos >= 0):
x = x[:pos]
return float(x) |
def get_indices(cif):
'\n This is a tool that will read a CIF file and return the unique T-sites,\n their multiplicities, and an example atom index.\n\n It also does the same for the unique O-sites in the framework.\n\n This tool only works on CIFs that are formatted the same way as the IZA\n Structure Database CIFs.\n '
(tsites, tmults, osites, omults) = get_mults(cif)
f = open(cif, 'r')
alllines = f.read()
f.close()
for (i, line) in enumerate(alllines):
if ('IT_coordinate_system_code' in line):
fields = line.split()
alllines[i] = '_symmetry_space_group_setting {0}'.format(fields[(- 1)])
atoms = read(cif)
oinds = [atom.index for atom in atoms if (atom.symbol == 'O')]
index = 0
first_os = []
for (i, m) in enumerate(omults):
first_os.append(oinds[index])
index += m
tinds = [atom.index for atom in atoms if (atom.symbol != 'O')]
index = 0
first_ts = []
for (i, m) in enumerate(tmults):
first_ts.append(tinds[index])
index += m
return (tsites, tmults, first_ts, osites, omults, first_os) | -8,522,372,167,062,766,000 | This is a tool that will read a CIF file and return the unique T-sites,
their multiplicities, and an example atom index.
It also does the same for the unique O-sites in the framework.
This tool only works on CIFs that are formatted the same way as the IZA
Structure Database CIFs. | cif_tools.py | get_indices | cwaitt/zse | python | def get_indices(cif):
'\n This is a tool that will read a CIF file and return the unique T-sites,\n their multiplicities, and an example atom index.\n\n It also does the same for the unique O-sites in the framework.\n\n This tool only works on CIFs that are formatted the same way as the IZA\n Structure Database CIFs.\n '
(tsites, tmults, osites, omults) = get_mults(cif)
f = open(cif, 'r')
alllines = f.read()
f.close()
for (i, line) in enumerate(alllines):
if ('IT_coordinate_system_code' in line):
fields = line.split()
alllines[i] = '_symmetry_space_group_setting {0}'.format(fields[(- 1)])
atoms = read(cif)
oinds = [atom.index for atom in atoms if (atom.symbol == 'O')]
index = 0
first_os = []
for (i, m) in enumerate(omults):
first_os.append(oinds[index])
index += m
tinds = [atom.index for atom in atoms if (atom.symbol != 'O')]
index = 0
first_ts = []
for (i, m) in enumerate(tmults):
first_ts.append(tinds[index])
index += m
return (tsites, tmults, first_ts, osites, omults, first_os) |
@classmethod
def from_service_account_file(cls, filename, *args, **kwargs):
'Creates an instance of this client using the provided credentials\n file.\n\n Args:\n filename (str): The path to the service account private key json\n file.\n args: Additional arguments to pass to the constructor.\n kwargs: Additional arguments to pass to the constructor.\n\n Returns:\n TextToSpeechClient: The constructed client.\n '
credentials = service_account.Credentials.from_service_account_file(filename)
kwargs['credentials'] = credentials
return cls(*args, **kwargs) | 8,165,111,019,497,557,000 | Creates an instance of this client using the provided credentials
file.
Args:
filename (str): The path to the service account private key json
file.
args: Additional arguments to pass to the constructor.
kwargs: Additional arguments to pass to the constructor.
Returns:
TextToSpeechClient: The constructed client. | texttospeech/google/cloud/texttospeech_v1beta1/gapic/text_to_speech_client.py | from_service_account_file | Abd-Elrazek/google-cloud-python | python | @classmethod
def from_service_account_file(cls, filename, *args, **kwargs):
'Creates an instance of this client using the provided credentials\n file.\n\n Args:\n filename (str): The path to the service account private key json\n file.\n args: Additional arguments to pass to the constructor.\n kwargs: Additional arguments to pass to the constructor.\n\n Returns:\n TextToSpeechClient: The constructed client.\n '
credentials = service_account.Credentials.from_service_account_file(filename)
kwargs['credentials'] = credentials
return cls(*args, **kwargs) |
def __init__(self, transport=None, channel=None, credentials=None, client_config=None, client_info=None):
"Constructor.\n\n Args:\n transport (Union[~.TextToSpeechGrpcTransport,\n Callable[[~.Credentials, type], ~.TextToSpeechGrpcTransport]): A transport\n instance, responsible for actually making the API calls.\n The default transport uses the gRPC protocol.\n This argument may also be a callable which returns a\n transport instance. Callables will be sent the credentials\n as the first argument and the default transport class as\n the second argument.\n channel (grpc.Channel): DEPRECATED. A ``Channel`` instance\n through which to make calls. This argument is mutually exclusive\n with ``credentials``; providing both will raise an exception.\n credentials (google.auth.credentials.Credentials): The\n authorization credentials to attach to requests. These\n credentials identify this application to the service. If none\n are specified, the client will attempt to ascertain the\n credentials from the environment.\n This argument is mutually exclusive with providing a\n transport instance to ``transport``; doing so will raise\n an exception.\n client_config (dict): DEPRECATED. A dictionary of call options for\n each method. If not specified, the default configuration is used.\n client_info (google.api_core.gapic_v1.client_info.ClientInfo):\n The client info used to send a user-agent string along with\n API requests. If ``None``, then default info will be used.\n Generally, you only need to set this if you're developing\n your own client library.\n "
if (client_config is not None):
warnings.warn('The `client_config` argument is deprecated.', PendingDeprecationWarning, stacklevel=2)
else:
client_config = text_to_speech_client_config.config
if channel:
warnings.warn('The `channel` argument is deprecated; use `transport` instead.', PendingDeprecationWarning, stacklevel=2)
if transport:
if callable(transport):
self.transport = transport(credentials=credentials, default_class=text_to_speech_grpc_transport.TextToSpeechGrpcTransport)
else:
if credentials:
raise ValueError('Received both a transport instance and credentials; these are mutually exclusive.')
self.transport = transport
else:
self.transport = text_to_speech_grpc_transport.TextToSpeechGrpcTransport(address=self.SERVICE_ADDRESS, channel=channel, credentials=credentials)
if (client_info is None):
client_info = google.api_core.gapic_v1.client_info.ClientInfo(gapic_version=_GAPIC_LIBRARY_VERSION)
else:
client_info.gapic_version = _GAPIC_LIBRARY_VERSION
self._client_info = client_info
self._method_configs = google.api_core.gapic_v1.config.parse_method_configs(client_config['interfaces'][self._INTERFACE_NAME])
self._inner_api_calls = {} | -6,464,139,821,673,658,000 | Constructor.
Args:
transport (Union[~.TextToSpeechGrpcTransport,
Callable[[~.Credentials, type], ~.TextToSpeechGrpcTransport]): A transport
instance, responsible for actually making the API calls.
The default transport uses the gRPC protocol.
This argument may also be a callable which returns a
transport instance. Callables will be sent the credentials
as the first argument and the default transport class as
the second argument.
channel (grpc.Channel): DEPRECATED. A ``Channel`` instance
through which to make calls. This argument is mutually exclusive
with ``credentials``; providing both will raise an exception.
credentials (google.auth.credentials.Credentials): The
authorization credentials to attach to requests. These
credentials identify this application to the service. If none
are specified, the client will attempt to ascertain the
credentials from the environment.
This argument is mutually exclusive with providing a
transport instance to ``transport``; doing so will raise
an exception.
client_config (dict): DEPRECATED. A dictionary of call options for
each method. If not specified, the default configuration is used.
client_info (google.api_core.gapic_v1.client_info.ClientInfo):
The client info used to send a user-agent string along with
API requests. If ``None``, then default info will be used.
Generally, you only need to set this if you're developing
your own client library. | texttospeech/google/cloud/texttospeech_v1beta1/gapic/text_to_speech_client.py | __init__ | Abd-Elrazek/google-cloud-python | python | def __init__(self, transport=None, channel=None, credentials=None, client_config=None, client_info=None):
"Constructor.\n\n Args:\n transport (Union[~.TextToSpeechGrpcTransport,\n Callable[[~.Credentials, type], ~.TextToSpeechGrpcTransport]): A transport\n instance, responsible for actually making the API calls.\n The default transport uses the gRPC protocol.\n This argument may also be a callable which returns a\n transport instance. Callables will be sent the credentials\n as the first argument and the default transport class as\n the second argument.\n channel (grpc.Channel): DEPRECATED. A ``Channel`` instance\n through which to make calls. This argument is mutually exclusive\n with ``credentials``; providing both will raise an exception.\n credentials (google.auth.credentials.Credentials): The\n authorization credentials to attach to requests. These\n credentials identify this application to the service. If none\n are specified, the client will attempt to ascertain the\n credentials from the environment.\n This argument is mutually exclusive with providing a\n transport instance to ``transport``; doing so will raise\n an exception.\n client_config (dict): DEPRECATED. A dictionary of call options for\n each method. If not specified, the default configuration is used.\n client_info (google.api_core.gapic_v1.client_info.ClientInfo):\n The client info used to send a user-agent string along with\n API requests. If ``None``, then default info will be used.\n Generally, you only need to set this if you're developing\n your own client library.\n "
if (client_config is not None):
warnings.warn('The `client_config` argument is deprecated.', PendingDeprecationWarning, stacklevel=2)
else:
client_config = text_to_speech_client_config.config
if channel:
warnings.warn('The `channel` argument is deprecated; use `transport` instead.', PendingDeprecationWarning, stacklevel=2)
if transport:
if callable(transport):
self.transport = transport(credentials=credentials, default_class=text_to_speech_grpc_transport.TextToSpeechGrpcTransport)
else:
if credentials:
raise ValueError('Received both a transport instance and credentials; these are mutually exclusive.')
self.transport = transport
else:
self.transport = text_to_speech_grpc_transport.TextToSpeechGrpcTransport(address=self.SERVICE_ADDRESS, channel=channel, credentials=credentials)
if (client_info is None):
client_info = google.api_core.gapic_v1.client_info.ClientInfo(gapic_version=_GAPIC_LIBRARY_VERSION)
else:
client_info.gapic_version = _GAPIC_LIBRARY_VERSION
self._client_info = client_info
self._method_configs = google.api_core.gapic_v1.config.parse_method_configs(client_config['interfaces'][self._INTERFACE_NAME])
self._inner_api_calls = {} |
def list_voices(self, language_code=None, retry=google.api_core.gapic_v1.method.DEFAULT, timeout=google.api_core.gapic_v1.method.DEFAULT, metadata=None):
'\n Returns a list of ``Voice`` supported for synthesis.\n\n Example:\n >>> from google.cloud import texttospeech_v1beta1\n >>>\n >>> client = texttospeech_v1beta1.TextToSpeechClient()\n >>>\n >>> response = client.list_voices()\n\n Args:\n language_code (str): Optional (but recommended)\n `BCP-47 <https://www.rfc-editor.org/rfc/bcp/bcp47.txt>`__ language tag.\n If specified, the ListVoices call will only return voices that can be\n used to synthesize this language\\_code. E.g. when specifying "en-NZ",\n you will get supported "en-*" voices; when specifying "no", you will get\n supported "no-*" (Norwegian) and "nb-*" (Norwegian Bokmal) voices;\n specifying "zh" will also get supported "cmn-*" voices; specifying\n "zh-hk" will also get supported "yue-\\*" voices.\n retry (Optional[google.api_core.retry.Retry]): A retry object used\n to retry requests. If ``None`` is specified, requests will not\n be retried.\n timeout (Optional[float]): The amount of time, in seconds, to wait\n for the request to complete. Note that if ``retry`` is\n specified, the timeout applies to each individual attempt.\n metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata\n that is provided to the method.\n\n Returns:\n A :class:`~google.cloud.texttospeech_v1beta1.types.ListVoicesResponse` instance.\n\n Raises:\n google.api_core.exceptions.GoogleAPICallError: If the request\n failed for any reason.\n google.api_core.exceptions.RetryError: If the request failed due\n to a retryable error and retry attempts failed.\n ValueError: If the parameters are invalid.\n '
if ('list_voices' not in self._inner_api_calls):
self._inner_api_calls['list_voices'] = google.api_core.gapic_v1.method.wrap_method(self.transport.list_voices, default_retry=self._method_configs['ListVoices'].retry, default_timeout=self._method_configs['ListVoices'].timeout, client_info=self._client_info)
request = cloud_tts_pb2.ListVoicesRequest(language_code=language_code)
return self._inner_api_calls['list_voices'](request, retry=retry, timeout=timeout, metadata=metadata) | 3,337,317,461,552,284,700 | Returns a list of ``Voice`` supported for synthesis.
Example:
>>> from google.cloud import texttospeech_v1beta1
>>>
>>> client = texttospeech_v1beta1.TextToSpeechClient()
>>>
>>> response = client.list_voices()
Args:
language_code (str): Optional (but recommended)
`BCP-47 <https://www.rfc-editor.org/rfc/bcp/bcp47.txt>`__ language tag.
If specified, the ListVoices call will only return voices that can be
used to synthesize this language\_code. E.g. when specifying "en-NZ",
you will get supported "en-*" voices; when specifying "no", you will get
supported "no-*" (Norwegian) and "nb-*" (Norwegian Bokmal) voices;
specifying "zh" will also get supported "cmn-*" voices; specifying
"zh-hk" will also get supported "yue-\*" voices.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.texttospeech_v1beta1.types.ListVoicesResponse` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid. | texttospeech/google/cloud/texttospeech_v1beta1/gapic/text_to_speech_client.py | list_voices | Abd-Elrazek/google-cloud-python | python | def list_voices(self, language_code=None, retry=google.api_core.gapic_v1.method.DEFAULT, timeout=google.api_core.gapic_v1.method.DEFAULT, metadata=None):
'\n Returns a list of ``Voice`` supported for synthesis.\n\n Example:\n >>> from google.cloud import texttospeech_v1beta1\n >>>\n >>> client = texttospeech_v1beta1.TextToSpeechClient()\n >>>\n >>> response = client.list_voices()\n\n Args:\n language_code (str): Optional (but recommended)\n `BCP-47 <https://www.rfc-editor.org/rfc/bcp/bcp47.txt>`__ language tag.\n If specified, the ListVoices call will only return voices that can be\n used to synthesize this language\\_code. E.g. when specifying "en-NZ",\n you will get supported "en-*" voices; when specifying "no", you will get\n supported "no-*" (Norwegian) and "nb-*" (Norwegian Bokmal) voices;\n specifying "zh" will also get supported "cmn-*" voices; specifying\n "zh-hk" will also get supported "yue-\\*" voices.\n retry (Optional[google.api_core.retry.Retry]): A retry object used\n to retry requests. If ``None`` is specified, requests will not\n be retried.\n timeout (Optional[float]): The amount of time, in seconds, to wait\n for the request to complete. Note that if ``retry`` is\n specified, the timeout applies to each individual attempt.\n metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata\n that is provided to the method.\n\n Returns:\n A :class:`~google.cloud.texttospeech_v1beta1.types.ListVoicesResponse` instance.\n\n Raises:\n google.api_core.exceptions.GoogleAPICallError: If the request\n failed for any reason.\n google.api_core.exceptions.RetryError: If the request failed due\n to a retryable error and retry attempts failed.\n ValueError: If the parameters are invalid.\n '
if ('list_voices' not in self._inner_api_calls):
self._inner_api_calls['list_voices'] = google.api_core.gapic_v1.method.wrap_method(self.transport.list_voices, default_retry=self._method_configs['ListVoices'].retry, default_timeout=self._method_configs['ListVoices'].timeout, client_info=self._client_info)
request = cloud_tts_pb2.ListVoicesRequest(language_code=language_code)
return self._inner_api_calls['list_voices'](request, retry=retry, timeout=timeout, metadata=metadata) |
def synthesize_speech(self, input_, voice, audio_config, retry=google.api_core.gapic_v1.method.DEFAULT, timeout=google.api_core.gapic_v1.method.DEFAULT, metadata=None):
'\n Synthesizes speech synchronously: receive results after all text input\n has been processed.\n\n Example:\n >>> from google.cloud import texttospeech_v1beta1\n >>>\n >>> client = texttospeech_v1beta1.TextToSpeechClient()\n >>>\n >>> # TODO: Initialize `input_`:\n >>> input_ = {}\n >>>\n >>> # TODO: Initialize `voice`:\n >>> voice = {}\n >>>\n >>> # TODO: Initialize `audio_config`:\n >>> audio_config = {}\n >>>\n >>> response = client.synthesize_speech(input_, voice, audio_config)\n\n Args:\n input_ (Union[dict, ~google.cloud.texttospeech_v1beta1.types.SynthesisInput]): Required. The Synthesizer requires either plain text or SSML as input.\n\n If a dict is provided, it must be of the same form as the protobuf\n message :class:`~google.cloud.texttospeech_v1beta1.types.SynthesisInput`\n voice (Union[dict, ~google.cloud.texttospeech_v1beta1.types.VoiceSelectionParams]): Required. The desired voice of the synthesized audio.\n\n If a dict is provided, it must be of the same form as the protobuf\n message :class:`~google.cloud.texttospeech_v1beta1.types.VoiceSelectionParams`\n audio_config (Union[dict, ~google.cloud.texttospeech_v1beta1.types.AudioConfig]): Required. The configuration of the synthesized audio.\n\n If a dict is provided, it must be of the same form as the protobuf\n message :class:`~google.cloud.texttospeech_v1beta1.types.AudioConfig`\n retry (Optional[google.api_core.retry.Retry]): A retry object used\n to retry requests. If ``None`` is specified, requests will not\n be retried.\n timeout (Optional[float]): The amount of time, in seconds, to wait\n for the request to complete. Note that if ``retry`` is\n specified, the timeout applies to each individual attempt.\n metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata\n that is provided to the method.\n\n Returns:\n A :class:`~google.cloud.texttospeech_v1beta1.types.SynthesizeSpeechResponse` instance.\n\n Raises:\n google.api_core.exceptions.GoogleAPICallError: If the request\n failed for any reason.\n google.api_core.exceptions.RetryError: If the request failed due\n to a retryable error and retry attempts failed.\n ValueError: If the parameters are invalid.\n '
if ('synthesize_speech' not in self._inner_api_calls):
self._inner_api_calls['synthesize_speech'] = google.api_core.gapic_v1.method.wrap_method(self.transport.synthesize_speech, default_retry=self._method_configs['SynthesizeSpeech'].retry, default_timeout=self._method_configs['SynthesizeSpeech'].timeout, client_info=self._client_info)
request = cloud_tts_pb2.SynthesizeSpeechRequest(input=input_, voice=voice, audio_config=audio_config)
return self._inner_api_calls['synthesize_speech'](request, retry=retry, timeout=timeout, metadata=metadata) | -245,552,770,767,781,020 | Synthesizes speech synchronously: receive results after all text input
has been processed.
Example:
>>> from google.cloud import texttospeech_v1beta1
>>>
>>> client = texttospeech_v1beta1.TextToSpeechClient()
>>>
>>> # TODO: Initialize `input_`:
>>> input_ = {}
>>>
>>> # TODO: Initialize `voice`:
>>> voice = {}
>>>
>>> # TODO: Initialize `audio_config`:
>>> audio_config = {}
>>>
>>> response = client.synthesize_speech(input_, voice, audio_config)
Args:
input_ (Union[dict, ~google.cloud.texttospeech_v1beta1.types.SynthesisInput]): Required. The Synthesizer requires either plain text or SSML as input.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.texttospeech_v1beta1.types.SynthesisInput`
voice (Union[dict, ~google.cloud.texttospeech_v1beta1.types.VoiceSelectionParams]): Required. The desired voice of the synthesized audio.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.texttospeech_v1beta1.types.VoiceSelectionParams`
audio_config (Union[dict, ~google.cloud.texttospeech_v1beta1.types.AudioConfig]): Required. The configuration of the synthesized audio.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.texttospeech_v1beta1.types.AudioConfig`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.texttospeech_v1beta1.types.SynthesizeSpeechResponse` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid. | texttospeech/google/cloud/texttospeech_v1beta1/gapic/text_to_speech_client.py | synthesize_speech | Abd-Elrazek/google-cloud-python | python | def synthesize_speech(self, input_, voice, audio_config, retry=google.api_core.gapic_v1.method.DEFAULT, timeout=google.api_core.gapic_v1.method.DEFAULT, metadata=None):
'\n Synthesizes speech synchronously: receive results after all text input\n has been processed.\n\n Example:\n >>> from google.cloud import texttospeech_v1beta1\n >>>\n >>> client = texttospeech_v1beta1.TextToSpeechClient()\n >>>\n >>> # TODO: Initialize `input_`:\n >>> input_ = {}\n >>>\n >>> # TODO: Initialize `voice`:\n >>> voice = {}\n >>>\n >>> # TODO: Initialize `audio_config`:\n >>> audio_config = {}\n >>>\n >>> response = client.synthesize_speech(input_, voice, audio_config)\n\n Args:\n input_ (Union[dict, ~google.cloud.texttospeech_v1beta1.types.SynthesisInput]): Required. The Synthesizer requires either plain text or SSML as input.\n\n If a dict is provided, it must be of the same form as the protobuf\n message :class:`~google.cloud.texttospeech_v1beta1.types.SynthesisInput`\n voice (Union[dict, ~google.cloud.texttospeech_v1beta1.types.VoiceSelectionParams]): Required. The desired voice of the synthesized audio.\n\n If a dict is provided, it must be of the same form as the protobuf\n message :class:`~google.cloud.texttospeech_v1beta1.types.VoiceSelectionParams`\n audio_config (Union[dict, ~google.cloud.texttospeech_v1beta1.types.AudioConfig]): Required. The configuration of the synthesized audio.\n\n If a dict is provided, it must be of the same form as the protobuf\n message :class:`~google.cloud.texttospeech_v1beta1.types.AudioConfig`\n retry (Optional[google.api_core.retry.Retry]): A retry object used\n to retry requests. If ``None`` is specified, requests will not\n be retried.\n timeout (Optional[float]): The amount of time, in seconds, to wait\n for the request to complete. Note that if ``retry`` is\n specified, the timeout applies to each individual attempt.\n metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata\n that is provided to the method.\n\n Returns:\n A :class:`~google.cloud.texttospeech_v1beta1.types.SynthesizeSpeechResponse` instance.\n\n Raises:\n google.api_core.exceptions.GoogleAPICallError: If the request\n failed for any reason.\n google.api_core.exceptions.RetryError: If the request failed due\n to a retryable error and retry attempts failed.\n ValueError: If the parameters are invalid.\n '
if ('synthesize_speech' not in self._inner_api_calls):
self._inner_api_calls['synthesize_speech'] = google.api_core.gapic_v1.method.wrap_method(self.transport.synthesize_speech, default_retry=self._method_configs['SynthesizeSpeech'].retry, default_timeout=self._method_configs['SynthesizeSpeech'].timeout, client_info=self._client_info)
request = cloud_tts_pb2.SynthesizeSpeechRequest(input=input_, voice=voice, audio_config=audio_config)
return self._inner_api_calls['synthesize_speech'](request, retry=retry, timeout=timeout, metadata=metadata) |
@noPosargs
@permittedKwargs({})
def symbols_have_underscore_prefix_method(self, args, kwargs):
'\n Check if the compiler prefixes _ (underscore) to global C symbols\n See: https://en.wikipedia.org/wiki/Name_mangling#C\n '
return self.compiler.symbols_have_underscore_prefix(self.environment) | 362,288,032,390,152,640 | Check if the compiler prefixes _ (underscore) to global C symbols
See: https://en.wikipedia.org/wiki/Name_mangling#C | mesonbuild/interpreter.py | symbols_have_underscore_prefix_method | tolnaisz/meson | python | @noPosargs
@permittedKwargs({})
def symbols_have_underscore_prefix_method(self, args, kwargs):
'\n Check if the compiler prefixes _ (underscore) to global C symbols\n See: https://en.wikipedia.org/wiki/Name_mangling#C\n '
return self.compiler.symbols_have_underscore_prefix(self.environment) |
@noPosargs
@permittedKwargs({})
def unittest_args_method(self, args, kwargs):
'\n This function is deprecated and should not be used.\n It can be removed in a future version of Meson.\n '
if (not hasattr(self.compiler, 'get_feature_args')):
raise InterpreterException('This {} compiler has no feature arguments.'.format(self.compiler.get_display_language()))
build_to_src = os.path.relpath(self.environment.get_source_dir(), self.environment.get_build_dir())
return self.compiler.get_feature_args({'unittest': 'true'}, build_to_src) | -1,227,826,540,872,375,300 | This function is deprecated and should not be used.
It can be removed in a future version of Meson. | mesonbuild/interpreter.py | unittest_args_method | tolnaisz/meson | python | @noPosargs
@permittedKwargs({})
def unittest_args_method(self, args, kwargs):
'\n This function is deprecated and should not be used.\n It can be removed in a future version of Meson.\n '
if (not hasattr(self.compiler, 'get_feature_args')):
raise InterpreterException('This {} compiler has no feature arguments.'.format(self.compiler.get_display_language()))
build_to_src = os.path.relpath(self.environment.get_source_dir(), self.environment.get_build_dir())
return self.compiler.get_feature_args({'unittest': 'true'}, build_to_src) |
def _handle_featurenew_dependencies(self, name):
'Do a feature check on dependencies used by this subproject'
if (name == 'mpi'):
FeatureNew('MPI Dependency', '0.42.0').use(self.subproject)
elif (name == 'pcap'):
FeatureNew('Pcap Dependency', '0.42.0').use(self.subproject)
elif (name == 'vulkan'):
FeatureNew('Vulkan Dependency', '0.42.0').use(self.subproject)
elif (name == 'libwmf'):
FeatureNew('LibWMF Dependency', '0.44.0').use(self.subproject)
elif (name == 'openmp'):
FeatureNew('OpenMP Dependency', '0.46.0').use(self.subproject) | -4,183,288,055,773,951,000 | Do a feature check on dependencies used by this subproject | mesonbuild/interpreter.py | _handle_featurenew_dependencies | tolnaisz/meson | python | def _handle_featurenew_dependencies(self, name):
if (name == 'mpi'):
FeatureNew('MPI Dependency', '0.42.0').use(self.subproject)
elif (name == 'pcap'):
FeatureNew('Pcap Dependency', '0.42.0').use(self.subproject)
elif (name == 'vulkan'):
FeatureNew('Vulkan Dependency', '0.42.0').use(self.subproject)
elif (name == 'libwmf'):
FeatureNew('LibWMF Dependency', '0.44.0').use(self.subproject)
elif (name == 'openmp'):
FeatureNew('OpenMP Dependency', '0.46.0').use(self.subproject) |
def _func_custom_target_impl(self, node, args, kwargs):
'Implementation-only, without FeatureNew checks, for internal use'
name = args[0]
kwargs['install_mode'] = self._get_kwarg_install_mode(kwargs)
if ('input' in kwargs):
try:
kwargs['input'] = self.source_strings_to_files(extract_as_list(kwargs, 'input'))
except mesonlib.MesonException:
mlog.warning(("Custom target input '%s' can't be converted to File object(s).\nThis will become a hard error in the future." % kwargs['input']), location=self.current_node)
tg = CustomTargetHolder(build.CustomTarget(name, self.subdir, self.subproject, kwargs, backend=self.backend), self)
self.add_target(name, tg.held_object)
return tg | -1,760,694,228,567,836,000 | Implementation-only, without FeatureNew checks, for internal use | mesonbuild/interpreter.py | _func_custom_target_impl | tolnaisz/meson | python | def _func_custom_target_impl(self, node, args, kwargs):
name = args[0]
kwargs['install_mode'] = self._get_kwarg_install_mode(kwargs)
if ('input' in kwargs):
try:
kwargs['input'] = self.source_strings_to_files(extract_as_list(kwargs, 'input'))
except mesonlib.MesonException:
mlog.warning(("Custom target input '%s' can't be converted to File object(s).\nThis will become a hard error in the future." % kwargs['input']), location=self.current_node)
tg = CustomTargetHolder(build.CustomTarget(name, self.subdir, self.subproject, kwargs, backend=self.backend), self)
self.add_target(name, tg.held_object)
return tg |
def keras_convert_hdf5_model_to_tf_saved_model(model_path: InputPath('KerasModelHdf5'), converted_model_path: OutputPath('TensorflowSavedModel')):
'Converts Keras HDF5 model to Tensorflow SavedModel format.\n\n Args:\n model_path: Keras model in HDF5 format.\n converted_model_path: Keras model in Tensorflow SavedModel format.\n\n Annotations:\n author: Alexey Volkov <[email protected]>\n '
from pathlib import Path
from tensorflow import keras
model = keras.models.load_model(filepath=model_path)
keras.models.save_model(model=model, filepath=converted_model_path, save_format='tf') | 6,726,971,064,905,890,000 | Converts Keras HDF5 model to Tensorflow SavedModel format.
Args:
model_path: Keras model in HDF5 format.
converted_model_path: Keras model in Tensorflow SavedModel format.
Annotations:
author: Alexey Volkov <[email protected]> | components/_converters/KerasModelHdf5/to_TensorflowSavedModel/component.py | keras_convert_hdf5_model_to_tf_saved_model | 9rince/kfp | python | def keras_convert_hdf5_model_to_tf_saved_model(model_path: InputPath('KerasModelHdf5'), converted_model_path: OutputPath('TensorflowSavedModel')):
'Converts Keras HDF5 model to Tensorflow SavedModel format.\n\n Args:\n model_path: Keras model in HDF5 format.\n converted_model_path: Keras model in Tensorflow SavedModel format.\n\n Annotations:\n author: Alexey Volkov <[email protected]>\n '
from pathlib import Path
from tensorflow import keras
model = keras.models.load_model(filepath=model_path)
keras.models.save_model(model=model, filepath=converted_model_path, save_format='tf') |
def __init__(self, Token, URL, get_all_field=False):
'\n Create a project using PyCap\n :param Token:\n :param URL:\n :return:\n '
self.project = Project(URL, Token)
fields_keyid = ['patientID', 'cf_p_cnnpatientui']
self.data = self.get_fields(fields_keyid)
if get_all_field:
self.data = self.project.export_records() | 8,593,968,137,652,244,000 | Create a project using PyCap
:param Token:
:param URL:
:return: | query_CNFUN.py | __init__ | CNBP/RCAPI | python | def __init__(self, Token, URL, get_all_field=False):
'\n Create a project using PyCap\n :param Token:\n :param URL:\n :return:\n '
self.project = Project(URL, Token)
fields_keyid = ['patientID', 'cf_p_cnnpatientui']
self.data = self.get_fields(fields_keyid)
if get_all_field:
self.data = self.project.export_records() |
def filter_with_CNNPatientUI(self, CNNPatientUI: (str or List[str])):
'\n Check the list, only retain the relevant records with matching PatientID are retained.\n :param dataset: CNBPIDs & record ID correspondence list.\n :param CNNPatientUI:\n :return:\n '
list_filtered = None
filtered_field = 'cf_p_cnnpatientui'
if (type(CNNPatientUI) is str):
CNNPatientUI = [CNNPatientUI]
list_filtered = filter_records(self.data, filtered_field, CNNPatientUI)
return list_filtered | 2,923,195,438,025,086,500 | Check the list, only retain the relevant records with matching PatientID are retained.
:param dataset: CNBPIDs & record ID correspondence list.
:param CNNPatientUI:
:return: | query_CNFUN.py | filter_with_CNNPatientUI | CNBP/RCAPI | python | def filter_with_CNNPatientUI(self, CNNPatientUI: (str or List[str])):
'\n Check the list, only retain the relevant records with matching PatientID are retained.\n :param dataset: CNBPIDs & record ID correspondence list.\n :param CNNPatientUI:\n :return:\n '
list_filtered = None
filtered_field = 'cf_p_cnnpatientui'
if (type(CNNPatientUI) is str):
CNNPatientUI = [CNNPatientUI]
list_filtered = filter_records(self.data, filtered_field, CNNPatientUI)
return list_filtered |
def get_PatientID_with_CNNPatientUI(self, CNNPatientUI: (str or List[str])):
'\n PatientID has 1:1 correspondence with CNNPatientUI which is the same as PatientUI from CNN Baby table.\n :return:\n '
if (type(CNNPatientUI) is str):
CNNPatientUI = [CNNPatientUI]
list_filtered_dict = self.filter_with_CNNPatientUI(CNNPatientUI)
list_PatientID = []
for case in list_filtered_dict:
list_PatientID.append(case['patientid'])
return list_PatientID | 6,397,022,490,869,362,000 | PatientID has 1:1 correspondence with CNNPatientUI which is the same as PatientUI from CNN Baby table.
:return: | query_CNFUN.py | get_PatientID_with_CNNPatientUI | CNBP/RCAPI | python | def get_PatientID_with_CNNPatientUI(self, CNNPatientUI: (str or List[str])):
'\n PatientID has 1:1 correspondence with CNNPatientUI which is the same as PatientUI from CNN Baby table.\n :return:\n '
if (type(CNNPatientUI) is str):
CNNPatientUI = [CNNPatientUI]
list_filtered_dict = self.filter_with_CNNPatientUI(CNNPatientUI)
list_PatientID = []
for case in list_filtered_dict:
list_PatientID.append(case['patientid'])
return list_PatientID |
def get_records_CNFUN(self, PatientID: (str or List[str])):
'\n Retrieve the cases based on their INDEX which is the\n :param cases:\n :return:\n '
if (type(PatientID) is str):
PatientID = [PatientID]
cases_data = self.project.export_records(records=PatientID)
return cases_data | -8,302,587,750,901,383,000 | Retrieve the cases based on their INDEX which is the
:param cases:
:return: | query_CNFUN.py | get_records_CNFUN | CNBP/RCAPI | python | def get_records_CNFUN(self, PatientID: (str or List[str])):
'\n Retrieve the cases based on their INDEX which is the\n :param cases:\n :return:\n '
if (type(PatientID) is str):
PatientID = [PatientID]
cases_data = self.project.export_records(records=PatientID)
return cases_data |
def __init__(self, id=None, name=None, created_at=None, updated_at=None):
'\n Role - a model defined in Swagger\n\n :param dict swaggerTypes: The key is attribute name\n and the value is attribute type.\n :param dict attributeMap: The key is attribute name\n and the value is json key in definition.\n '
self.swagger_types = {'id': 'int', 'name': 'str', 'created_at': 'datetime', 'updated_at': 'datetime'}
self.attribute_map = {'id': 'id', 'name': 'name', 'created_at': 'created_at', 'updated_at': 'updated_at'}
self._id = id
self._name = name
self._created_at = created_at
self._updated_at = updated_at | -3,533,986,126,233,254,000 | Role - a model defined in Swagger
:param dict swaggerTypes: The key is attribute name
and the value is attribute type.
:param dict attributeMap: The key is attribute name
and the value is json key in definition. | esp_sdk/models/role.py | __init__ | EvidentSecurity/esp-sdk-python | python | def __init__(self, id=None, name=None, created_at=None, updated_at=None):
'\n Role - a model defined in Swagger\n\n :param dict swaggerTypes: The key is attribute name\n and the value is attribute type.\n :param dict attributeMap: The key is attribute name\n and the value is json key in definition.\n '
self.swagger_types = {'id': 'int', 'name': 'str', 'created_at': 'datetime', 'updated_at': 'datetime'}
self.attribute_map = {'id': 'id', 'name': 'name', 'created_at': 'created_at', 'updated_at': 'updated_at'}
self._id = id
self._name = name
self._created_at = created_at
self._updated_at = updated_at |
@property
def id(self):
'\n Gets the id of this Role.\n Unique ID\n\n :return: The id of this Role.\n :rtype: int\n '
return self._id | -4,175,835,661,677,043,700 | Gets the id of this Role.
Unique ID
:return: The id of this Role.
:rtype: int | esp_sdk/models/role.py | id | EvidentSecurity/esp-sdk-python | python | @property
def id(self):
'\n Gets the id of this Role.\n Unique ID\n\n :return: The id of this Role.\n :rtype: int\n '
return self._id |
@id.setter
def id(self, id):
'\n Sets the id of this Role.\n Unique ID\n\n :param id: The id of this Role.\n :type: int\n '
self._id = id | -3,053,184,595,672,948,000 | Sets the id of this Role.
Unique ID
:param id: The id of this Role.
:type: int | esp_sdk/models/role.py | id | EvidentSecurity/esp-sdk-python | python | @id.setter
def id(self, id):
'\n Sets the id of this Role.\n Unique ID\n\n :param id: The id of this Role.\n :type: int\n '
self._id = id |
@property
def name(self):
'\n Gets the name of this Role.\n The name of the role\n\n :return: The name of this Role.\n :rtype: str\n '
return self._name | -3,958,561,292,520,585,000 | Gets the name of this Role.
The name of the role
:return: The name of this Role.
:rtype: str | esp_sdk/models/role.py | name | EvidentSecurity/esp-sdk-python | python | @property
def name(self):
'\n Gets the name of this Role.\n The name of the role\n\n :return: The name of this Role.\n :rtype: str\n '
return self._name |
@name.setter
def name(self, name):
'\n Sets the name of this Role.\n The name of the role\n\n :param name: The name of this Role.\n :type: str\n '
self._name = name | 8,241,518,132,240,190,000 | Sets the name of this Role.
The name of the role
:param name: The name of this Role.
:type: str | esp_sdk/models/role.py | name | EvidentSecurity/esp-sdk-python | python | @name.setter
def name(self, name):
'\n Sets the name of this Role.\n The name of the role\n\n :param name: The name of this Role.\n :type: str\n '
self._name = name |
@property
def created_at(self):
'\n Gets the created_at of this Role.\n ISO 8601 timestamp when the resource was created\n\n :return: The created_at of this Role.\n :rtype: datetime\n '
return self._created_at | 5,446,404,519,584,327,000 | Gets the created_at of this Role.
ISO 8601 timestamp when the resource was created
:return: The created_at of this Role.
:rtype: datetime | esp_sdk/models/role.py | created_at | EvidentSecurity/esp-sdk-python | python | @property
def created_at(self):
'\n Gets the created_at of this Role.\n ISO 8601 timestamp when the resource was created\n\n :return: The created_at of this Role.\n :rtype: datetime\n '
return self._created_at |
@created_at.setter
def created_at(self, created_at):
'\n Sets the created_at of this Role.\n ISO 8601 timestamp when the resource was created\n\n :param created_at: The created_at of this Role.\n :type: datetime\n '
self._created_at = created_at | 7,548,933,885,825,973,000 | Sets the created_at of this Role.
ISO 8601 timestamp when the resource was created
:param created_at: The created_at of this Role.
:type: datetime | esp_sdk/models/role.py | created_at | EvidentSecurity/esp-sdk-python | python | @created_at.setter
def created_at(self, created_at):
'\n Sets the created_at of this Role.\n ISO 8601 timestamp when the resource was created\n\n :param created_at: The created_at of this Role.\n :type: datetime\n '
self._created_at = created_at |
@property
def updated_at(self):
'\n Gets the updated_at of this Role.\n ISO 8601 timestamp when the resource was updated\n\n :return: The updated_at of this Role.\n :rtype: datetime\n '
return self._updated_at | 107,710,952,778,185,120 | Gets the updated_at of this Role.
ISO 8601 timestamp when the resource was updated
:return: The updated_at of this Role.
:rtype: datetime | esp_sdk/models/role.py | updated_at | EvidentSecurity/esp-sdk-python | python | @property
def updated_at(self):
'\n Gets the updated_at of this Role.\n ISO 8601 timestamp when the resource was updated\n\n :return: The updated_at of this Role.\n :rtype: datetime\n '
return self._updated_at |
@updated_at.setter
def updated_at(self, updated_at):
'\n Sets the updated_at of this Role.\n ISO 8601 timestamp when the resource was updated\n\n :param updated_at: The updated_at of this Role.\n :type: datetime\n '
self._updated_at = updated_at | 2,238,393,510,890,466,300 | Sets the updated_at of this Role.
ISO 8601 timestamp when the resource was updated
:param updated_at: The updated_at of this Role.
:type: datetime | esp_sdk/models/role.py | updated_at | EvidentSecurity/esp-sdk-python | python | @updated_at.setter
def updated_at(self, updated_at):
'\n Sets the updated_at of this Role.\n ISO 8601 timestamp when the resource was updated\n\n :param updated_at: The updated_at of this Role.\n :type: datetime\n '
self._updated_at = updated_at |
def to_dict(self):
'\n Returns the model properties as a dict\n '
result = {}
for (attr, _) in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
return result | 2,191,974,537,531,847,000 | Returns the model properties as a dict | esp_sdk/models/role.py | to_dict | EvidentSecurity/esp-sdk-python | python | def to_dict(self):
'\n \n '
result = {}
for (attr, _) in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
return result |
def to_str(self):
'\n Returns the string representation of the model\n '
return pformat(self.to_dict()) | -3,531,024,894,346,511,000 | Returns the string representation of the model | esp_sdk/models/role.py | to_str | EvidentSecurity/esp-sdk-python | python | def to_str(self):
'\n \n '
return pformat(self.to_dict()) |
def __repr__(self):
'\n For `print` and `pprint`\n '
return self.to_str() | 5,853,962,500,611,353,000 | For `print` and `pprint` | esp_sdk/models/role.py | __repr__ | EvidentSecurity/esp-sdk-python | python | def __repr__(self):
'\n \n '
return self.to_str() |
def __eq__(self, other):
'\n Returns true if both objects are equal\n '
if (not isinstance(other, Role)):
return False
return (self.__dict__ == other.__dict__) | -4,678,687,099,986,198,000 | Returns true if both objects are equal | esp_sdk/models/role.py | __eq__ | EvidentSecurity/esp-sdk-python | python | def __eq__(self, other):
'\n \n '
if (not isinstance(other, Role)):
return False
return (self.__dict__ == other.__dict__) |
def __ne__(self, other):
'\n Returns true if both objects are not equal\n '
return (not (self == other)) | 3,600,423,175,817,510,400 | Returns true if both objects are not equal | esp_sdk/models/role.py | __ne__ | EvidentSecurity/esp-sdk-python | python | def __ne__(self, other):
'\n \n '
return (not (self == other)) |
def testDashboard(self):
'Test Dashboard'
pass | 6,571,422,790,749,848,000 | Test Dashboard | test/test_dashboard.py | testDashboard | PowerOlive/python-client | python | def testDashboard(self):
pass |
def get_gif():
'Return gif.'
gif = BytesIO(b'GIF87a\x01\x00\x01\x00\x80\x01\x00\x00\x00\x00ccc,\x00\x00\x00\x00\x01\x00\x01\x00\x00\x02\x02D\x01\x00;')
gif.name = 'image.gif'
return gif | 2,126,571,613,711,030,800 | Return gif. | modoboa_webmail/tests/test_views.py | get_gif | modoboa/modoboa-webmail | python | def get_gif():
gif = BytesIO(b'GIF87a\x01\x00\x01\x00\x80\x01\x00\x00\x00\x00ccc,\x00\x00\x00\x00\x01\x00\x01\x00\x00\x02\x02D\x01\x00;')
gif.name = 'image.gif'
return gif |
@classmethod
def setUpTestData(cls):
'Create some users.'
super(WebmailTestCase, cls).setUpTestData()
admin_factories.populate_database()
cls.user = core_models.User.objects.get(username='[email protected]') | 5,195,052,972,593,634,000 | Create some users. | modoboa_webmail/tests/test_views.py | setUpTestData | modoboa/modoboa-webmail | python | @classmethod
def setUpTestData(cls):
super(WebmailTestCase, cls).setUpTestData()
admin_factories.populate_database()
cls.user = core_models.User.objects.get(username='[email protected]') |
def setUp(self):
'Connect with a simpler user.'
patcher = mock.patch('imaplib.IMAP4')
self.mock_imap4 = patcher.start()
self.mock_imap4.return_value = IMAP4Mock()
self.addCleanup(patcher.stop)
self.set_global_parameter('imap_port', 1435)
self.workdir = tempfile.mkdtemp()
os.mkdir('{}/webmail'.format(self.workdir))
self.set_global_parameter('update_scheme', False, app='core')
url = reverse('core:login')
data = {'username': self.user.username, 'password': 'toto'}
self.client.post(url, data) | 8,880,333,680,631,719,000 | Connect with a simpler user. | modoboa_webmail/tests/test_views.py | setUp | modoboa/modoboa-webmail | python | def setUp(self):
patcher = mock.patch('imaplib.IMAP4')
self.mock_imap4 = patcher.start()
self.mock_imap4.return_value = IMAP4Mock()
self.addCleanup(patcher.stop)
self.set_global_parameter('imap_port', 1435)
self.workdir = tempfile.mkdtemp()
os.mkdir('{}/webmail'.format(self.workdir))
self.set_global_parameter('update_scheme', False, app='core')
url = reverse('core:login')
data = {'username': self.user.username, 'password': 'toto'}
self.client.post(url, data) |
def tearDown(self):
'Cleanup.'
shutil.rmtree(self.workdir) | 6,105,586,400,696,134,000 | Cleanup. | modoboa_webmail/tests/test_views.py | tearDown | modoboa/modoboa-webmail | python | def tearDown(self):
shutil.rmtree(self.workdir) |
def test_listmailbox(self):
'Check listmailbox action.'
url = reverse('modoboa_webmail:index')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
response = self.client.get('{}?action=listmailbox'.format(url), HTTP_X_REQUESTED_WITH='XMLHttpRequest')
self.assertEqual(response.status_code, 200)
self.assertIn('[email protected]', response.json()['listing'])
response = self.client.get('{}?action=listmailbox&pattern=Réception&criteria=Subject'.format(url), HTTP_X_REQUESTED_WITH='XMLHttpRequest')
self.assertEqual(response.status_code, 200)
self.assertIn('[email protected]', response.json()['listing']) | -4,219,483,767,522,329,600 | Check listmailbox action. | modoboa_webmail/tests/test_views.py | test_listmailbox | modoboa/modoboa-webmail | python | def test_listmailbox(self):
url = reverse('modoboa_webmail:index')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
response = self.client.get('{}?action=listmailbox'.format(url), HTTP_X_REQUESTED_WITH='XMLHttpRequest')
self.assertEqual(response.status_code, 200)
self.assertIn('[email protected]', response.json()['listing'])
response = self.client.get('{}?action=listmailbox&pattern=Réception&criteria=Subject'.format(url), HTTP_X_REQUESTED_WITH='XMLHttpRequest')
self.assertEqual(response.status_code, 200)
self.assertIn('[email protected]', response.json()['listing']) |
def test_attachments(self):
'Check attachments.'
url = reverse('modoboa_webmail:index')
response = self.client.get('{}?action=compose'.format(url))
self.assertEqual(response.status_code, 200)
self.assertIn('compose_mail', self.client.session)
url = reverse('modoboa_webmail:attachment_list')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
self.set_global_parameters({'max_attachment_size': '10'})
with self.settings(MEDIA_ROOT=self.workdir):
response = self.client.post(url, {'attachment': get_gif()})
self.assertContains(response, 'Attachment is too big')
self.set_global_parameters({'max_attachment_size': '10K'})
with self.settings(MEDIA_ROOT=self.workdir):
response = self.client.post(url, {'attachment': get_gif()})
self.assertContains(response, 'upload_success')
self.assertEqual(len(self.client.session['compose_mail']['attachments']), 1)
name = self.client.session['compose_mail']['attachments'][0]['tmpname']
path = '{}/webmail/{}'.format(self.workdir, name)
self.assertTrue(os.path.exists(path))
url = reverse('modoboa_webmail:attachment_delete')
with self.settings(MEDIA_ROOT=self.workdir):
self.ajax_get('{}?name={}'.format(url, name))
self.assertFalse(os.path.exists(path)) | 621,653,214,064,495,600 | Check attachments. | modoboa_webmail/tests/test_views.py | test_attachments | modoboa/modoboa-webmail | python | def test_attachments(self):
url = reverse('modoboa_webmail:index')
response = self.client.get('{}?action=compose'.format(url))
self.assertEqual(response.status_code, 200)
self.assertIn('compose_mail', self.client.session)
url = reverse('modoboa_webmail:attachment_list')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
self.set_global_parameters({'max_attachment_size': '10'})
with self.settings(MEDIA_ROOT=self.workdir):
response = self.client.post(url, {'attachment': get_gif()})
self.assertContains(response, 'Attachment is too big')
self.set_global_parameters({'max_attachment_size': '10K'})
with self.settings(MEDIA_ROOT=self.workdir):
response = self.client.post(url, {'attachment': get_gif()})
self.assertContains(response, 'upload_success')
self.assertEqual(len(self.client.session['compose_mail']['attachments']), 1)
name = self.client.session['compose_mail']['attachments'][0]['tmpname']
path = '{}/webmail/{}'.format(self.workdir, name)
self.assertTrue(os.path.exists(path))
url = reverse('modoboa_webmail:attachment_delete')
with self.settings(MEDIA_ROOT=self.workdir):
self.ajax_get('{}?name={}'.format(url, name))
self.assertFalse(os.path.exists(path)) |
def test_delattachment_errors(self):
'Check error cases.'
url = reverse('modoboa_webmail:index')
response = self.client.get('{}?action=compose'.format(url))
self.assertEqual(response.status_code, 200)
self.assertIn('compose_mail', self.client.session)
url = reverse('modoboa_webmail:attachment_delete')
with self.settings(MEDIA_ROOT=self.workdir):
response = self.ajax_get('{}?name='.format(url))
self.assertEqual(response['status'], 'ko')
self.assertEqual(response['respmsg'], 'Bad query')
with self.settings(MEDIA_ROOT=self.workdir):
response = self.ajax_get('{}?name=test'.format(url))
self.assertEqual(response['status'], 'ko')
self.assertEqual(response['respmsg'], 'Unknown attachment') | -4,068,887,393,520,834,600 | Check error cases. | modoboa_webmail/tests/test_views.py | test_delattachment_errors | modoboa/modoboa-webmail | python | def test_delattachment_errors(self):
url = reverse('modoboa_webmail:index')
response = self.client.get('{}?action=compose'.format(url))
self.assertEqual(response.status_code, 200)
self.assertIn('compose_mail', self.client.session)
url = reverse('modoboa_webmail:attachment_delete')
with self.settings(MEDIA_ROOT=self.workdir):
response = self.ajax_get('{}?name='.format(url))
self.assertEqual(response['status'], 'ko')
self.assertEqual(response['respmsg'], 'Bad query')
with self.settings(MEDIA_ROOT=self.workdir):
response = self.ajax_get('{}?name=test'.format(url))
self.assertEqual(response['status'], 'ko')
self.assertEqual(response['respmsg'], 'Unknown attachment') |
def test_send_mail(self):
'Check compose form.'
url = '{}?action=compose'.format(reverse('modoboa_webmail:index'))
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': 'Test'})
self.assertEqual(len(mail.outbox), 1)
self.assertEqual(mail.outbox[0].from_email, '[email protected]')
self.user.first_name = 'Antoine'
self.user.last_name = 'Nguyen'
self.user.parameters.set_value('editor', 'html')
self.user.save()
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
mail.outbox = []
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': '<p>Test</p>'})
self.assertEqual(len(mail.outbox), 1)
self.assertEqual(mail.outbox[0].from_email, '"Antoine Nguyen" <[email protected]>') | -1,387,542,173,281,891,300 | Check compose form. | modoboa_webmail/tests/test_views.py | test_send_mail | modoboa/modoboa-webmail | python | def test_send_mail(self):
url = '{}?action=compose'.format(reverse('modoboa_webmail:index'))
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': 'Test'})
self.assertEqual(len(mail.outbox), 1)
self.assertEqual(mail.outbox[0].from_email, '[email protected]')
self.user.first_name = 'Antoine'
self.user.last_name = 'Nguyen'
self.user.parameters.set_value('editor', 'html')
self.user.save()
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
mail.outbox = []
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': '<p>Test</p>'})
self.assertEqual(len(mail.outbox), 1)
self.assertEqual(mail.outbox[0].from_email, '"Antoine Nguyen" <[email protected]>') |
def test_signature(self):
'Check signature in different formats.'
signature = 'Antoine Nguyen'
self.user.parameters.set_value('signature', signature)
self.user.save()
response = self.client.get(reverse('modoboa_webmail:index'))
self.assertEqual(response.status_code, 200)
url = '{}?action=compose'.format(reverse('modoboa_webmail:index'))
response = self.ajax_get(url)
self.assertIn(signature, response['listing']) | 848,823,360,628,905,700 | Check signature in different formats. | modoboa_webmail/tests/test_views.py | test_signature | modoboa/modoboa-webmail | python | def test_signature(self):
signature = 'Antoine Nguyen'
self.user.parameters.set_value('signature', signature)
self.user.save()
response = self.client.get(reverse('modoboa_webmail:index'))
self.assertEqual(response.status_code, 200)
url = '{}?action=compose'.format(reverse('modoboa_webmail:index'))
response = self.ajax_get(url)
self.assertIn(signature, response['listing']) |
def test_custom_js_in_preferences(self):
'Check that custom js is included.'
url = reverse('core:user_index')
response = self.client.get(url)
self.assertContains(response, 'function toggleSignatureEditor()') | 8,341,938,609,019,007,000 | Check that custom js is included. | modoboa_webmail/tests/test_views.py | test_custom_js_in_preferences | modoboa/modoboa-webmail | python | def test_custom_js_in_preferences(self):
url = reverse('core:user_index')
response = self.client.get(url)
self.assertContains(response, 'function toggleSignatureEditor()') |
def test_send_mail_errors(self):
'Check error cases.'
url = '{}?action=compose'.format(reverse('modoboa_webmail:index'))
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
response = self.ajax_post(url, {'to': '', 'subject': 'test', 'body': 'Test'}, 400)
self.assertEqual(len(mail.outbox), 0) | -4,056,351,638,885,951,500 | Check error cases. | modoboa_webmail/tests/test_views.py | test_send_mail_errors | modoboa/modoboa-webmail | python | def test_send_mail_errors(self):
url = '{}?action=compose'.format(reverse('modoboa_webmail:index'))
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
response = self.ajax_post(url, {'to': , 'subject': 'test', 'body': 'Test'}, 400)
self.assertEqual(len(mail.outbox), 0) |
def test_new_folder(self):
'Test folder creation.'
url = reverse('modoboa_webmail:folder_add')
response = self.client.get(url)
self.assertContains(response, 'Create a new folder')
response = self.ajax_post(url, {'name': 'Test'})
self.assertIn('newmb', response) | 5,715,399,611,297,225,000 | Test folder creation. | modoboa_webmail/tests/test_views.py | test_new_folder | modoboa/modoboa-webmail | python | def test_new_folder(self):
url = reverse('modoboa_webmail:folder_add')
response = self.client.get(url)
self.assertContains(response, 'Create a new folder')
response = self.ajax_post(url, {'name': 'Test'})
self.assertIn('newmb', response) |
def test_edit_folder(self):
'Test folder edition.'
url = reverse('modoboa_webmail:folder_change')
response = self.client.get(url)
self.assertContains(response, 'Invalid request')
url = '{}?name=Test'.format(url)
response = self.client.get(url)
self.assertContains(response, 'Edit folder')
session = self.client.session
session['webmail_navparams'] = {'inbox': 'Test'}
session.save()
response = self.ajax_post(url, {'oldname': 'Test', 'name': 'Toto'})
self.assertEqual(response['respmsg'], 'Folder updated') | -7,015,717,075,723,713,000 | Test folder edition. | modoboa_webmail/tests/test_views.py | test_edit_folder | modoboa/modoboa-webmail | python | def test_edit_folder(self):
url = reverse('modoboa_webmail:folder_change')
response = self.client.get(url)
self.assertContains(response, 'Invalid request')
url = '{}?name=Test'.format(url)
response = self.client.get(url)
self.assertContains(response, 'Edit folder')
session = self.client.session
session['webmail_navparams'] = {'inbox': 'Test'}
session.save()
response = self.ajax_post(url, {'oldname': 'Test', 'name': 'Toto'})
self.assertEqual(response['respmsg'], 'Folder updated') |
def test_delete_folder(self):
'Test folder removal.'
url = reverse('modoboa_webmail:folder_delete')
self.ajax_get(url, status=400)
url = '{}?name=Test'.format(url)
session = self.client.session
session['webmail_navparams'] = {'inbox': 'Test'}
session.save()
self.ajax_get(url) | -7,600,897,677,307,676,000 | Test folder removal. | modoboa_webmail/tests/test_views.py | test_delete_folder | modoboa/modoboa-webmail | python | def test_delete_folder(self):
url = reverse('modoboa_webmail:folder_delete')
self.ajax_get(url, status=400)
url = '{}?name=Test'.format(url)
session = self.client.session
session['webmail_navparams'] = {'inbox': 'Test'}
session.save()
self.ajax_get(url) |
def test_reply_to_email(self):
'Test reply form.'
url = '{}?action=reply&mbox=INBOX&mailid=46931'.format(reverse('modoboa_webmail:index'))
session = self.client.session
session['lastaction'] = 'compose'
session.save()
response = self.ajax_get(url)
self.assertIn('id="id_origmsgid"', response['listing'])
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': 'Test', 'origmsgid': '<id@localhost>'})
self.assertEqual(len(mail.outbox), 1)
self.assertEqual(mail.outbox[0].from_email, '[email protected]')
self.assertIn('References', mail.outbox[0].extra_headers) | 8,669,863,298,764,621,000 | Test reply form. | modoboa_webmail/tests/test_views.py | test_reply_to_email | modoboa/modoboa-webmail | python | def test_reply_to_email(self):
url = '{}?action=reply&mbox=INBOX&mailid=46931'.format(reverse('modoboa_webmail:index'))
session = self.client.session
session['lastaction'] = 'compose'
session.save()
response = self.ajax_get(url)
self.assertIn('id="id_origmsgid"', response['listing'])
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': 'Test', 'origmsgid': '<id@localhost>'})
self.assertEqual(len(mail.outbox), 1)
self.assertEqual(mail.outbox[0].from_email, '[email protected]')
self.assertIn('References', mail.outbox[0].extra_headers) |
def test_forward_email(self):
'Test forward form.'
url = '{}?action=forward&mbox=INBOX&mailid=46932'.format(reverse('modoboa_webmail:index'))
session = self.client.session
session['lastaction'] = 'compose'
session.save()
with self.settings(MEDIA_ROOT=self.workdir):
response = self.client.get(url, HTTP_X_REQUESTED_WITH='XMLHttpRequest')
response = response.json()
self.assertIn('id="id_origmsgid"', response['listing'])
self.assertEqual(len(self.client.session['compose_mail']['attachments']), 1)
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': 'Test', 'origmsgid': '<id@localhost>'})
self.assertEqual(len(mail.outbox), 1) | 4,625,502,241,085,917,000 | Test forward form. | modoboa_webmail/tests/test_views.py | test_forward_email | modoboa/modoboa-webmail | python | def test_forward_email(self):
url = '{}?action=forward&mbox=INBOX&mailid=46932'.format(reverse('modoboa_webmail:index'))
session = self.client.session
session['lastaction'] = 'compose'
session.save()
with self.settings(MEDIA_ROOT=self.workdir):
response = self.client.get(url, HTTP_X_REQUESTED_WITH='XMLHttpRequest')
response = response.json()
self.assertIn('id="id_origmsgid"', response['listing'])
self.assertEqual(len(self.client.session['compose_mail']['attachments']), 1)
response = self.client.post(url, {'from_': self.user.email, 'to': '[email protected]', 'subject': 'test', 'body': 'Test', 'origmsgid': '<id@localhost>'})
self.assertEqual(len(mail.outbox), 1) |
def test_getmailcontent_empty_mail(self):
'Try to display an empty email.'
url = '{}?action=reply&mbox=INBOX&mailid=33'.format(reverse('modoboa_webmail:mailcontent_get'))
response = self.client.get(url)
self.assertEqual(response.status_code, 200) | -5,638,293,346,663,087,000 | Try to display an empty email. | modoboa_webmail/tests/test_views.py | test_getmailcontent_empty_mail | modoboa/modoboa-webmail | python | def test_getmailcontent_empty_mail(self):
url = '{}?action=reply&mbox=INBOX&mailid=33'.format(reverse('modoboa_webmail:mailcontent_get'))
response = self.client.get(url)
self.assertEqual(response.status_code, 200) |
def test_getmailsource(self):
"Try to display a message's source."
url = '{}?mbox=INBOX&mailid=133872'.format(reverse('modoboa_webmail:mailsource_get'))
response = self.client.get(url)
self.assertContains(response, 'Message-ID') | 4,267,383,935,041,959,000 | Try to display a message's source. | modoboa_webmail/tests/test_views.py | test_getmailsource | modoboa/modoboa-webmail | python | def test_getmailsource(self):
url = '{}?mbox=INBOX&mailid=133872'.format(reverse('modoboa_webmail:mailsource_get'))
response = self.client.get(url)
self.assertContains(response, 'Message-ID') |
def get_args():
' Get script argument '
parser = argparse.ArgumentParser(description='Show current weather on polybar')
parser.add_argument('log', nargs='?', help='Logging for debugging or not')
parser.add_argument('-u', '--unit', default='metric', nargs='?', help='unit: metric or imperial. Default: metric')
return parser.parse_args() | 4,760,475,130,287,260,000 | Get script argument | .config/polybar/weather/weather.py | get_args | NearHuscarl/dotfiles | python | def get_args():
' '
parser = argparse.ArgumentParser(description='Show current weather on polybar')
parser.add_argument('log', nargs='?', help='Logging for debugging or not')
parser.add_argument('-u', '--unit', default='metric', nargs='?', help='unit: metric or imperial. Default: metric')
return parser.parse_args() |
def set_up_logging():
' Set some logging parameter '
if importlib.util.find_spec('requests'):
logging.getLogger('requests').setLevel(logging.WARNING)
logging.getLogger('urllib3').setLevel(logging.WARNING)
logging.basicConfig(format='[%(levelname)s] %(message)s', level=logging.DEBUG) | 7,073,323,484,583,997,000 | Set some logging parameter | .config/polybar/weather/weather.py | set_up_logging | NearHuscarl/dotfiles | python | def set_up_logging():
' '
if importlib.util.find_spec('requests'):
logging.getLogger('requests').setLevel(logging.WARNING)
logging.getLogger('urllib3').setLevel(logging.WARNING)
logging.basicConfig(format='[%(levelname)s] %(message)s', level=logging.DEBUG) |
def get_day_or_night():
" return 'day' or 'night' based on current hour "
hour = int(datetime.datetime.now().strftime('%H'))
if ((hour >= 18) or (hour <= 5)):
return 'night'
return 'day' | 9,053,619,928,646,817,000 | return 'day' or 'night' based on current hour | .config/polybar/weather/weather.py | get_day_or_night | NearHuscarl/dotfiles | python | def get_day_or_night():
" "
hour = int(datetime.datetime.now().strftime('%H'))
if ((hour >= 18) or (hour <= 5)):
return 'night'
return 'day' |
def get_weather_icon(weather_id):
' Get weather icon based on weather condition '
day_night_status = get_day_or_night()
weather = {'thunderstorm': (200 <= weather_id <= 232), 'rain': (300 <= weather_id <= 531), 'snow': (600 <= weather_id <= 622), 'atmosphere': (701 <= weather_id <= 781), 'squall': (weather_id == 771), 'tornado': ((weather_id == 781) or (weather_id == 900)), 'clear_day': ((weather_id == 800) and (day_night_status == 'day')), 'clear_night': ((weather_id == 800) and (day_night_status == 'night')), 'tropical storm': (weather_id == 901), 'hurricane': (weather_id == 902), 'cold': (weather_id == 903), 'hot': (weather_id == 904), 'windy': (weather_id == 905), 'cloudy': (801 <= weather_id <= 804), 'hail': (weather_id == 906)}
if weather['thunderstorm']:
return '\uf0e7'
elif weather['rain']:
return '\uf043'
elif (weather['snow'] or weather['cold']):
return '\uf2dc'
elif (weather['atmosphere'] or weather['windy']):
return '\ue8de'
elif (weather['squall'] or weather['tornado'] or weather['tropical storm'] or weather['hurricane']):
return '\uf2dd'
elif (weather['clear_day'] or weather['hot']):
return '\ue430'
elif weather['clear_night']:
return '\uf186'
elif weather['cloudy']:
return '\uf0c2'
elif weather['hail']:
return '\ue3ea' | -2,874,299,759,056,601,600 | Get weather icon based on weather condition | .config/polybar/weather/weather.py | get_weather_icon | NearHuscarl/dotfiles | python | def get_weather_icon(weather_id):
' '
day_night_status = get_day_or_night()
weather = {'thunderstorm': (200 <= weather_id <= 232), 'rain': (300 <= weather_id <= 531), 'snow': (600 <= weather_id <= 622), 'atmosphere': (701 <= weather_id <= 781), 'squall': (weather_id == 771), 'tornado': ((weather_id == 781) or (weather_id == 900)), 'clear_day': ((weather_id == 800) and (day_night_status == 'day')), 'clear_night': ((weather_id == 800) and (day_night_status == 'night')), 'tropical storm': (weather_id == 901), 'hurricane': (weather_id == 902), 'cold': (weather_id == 903), 'hot': (weather_id == 904), 'windy': (weather_id == 905), 'cloudy': (801 <= weather_id <= 804), 'hail': (weather_id == 906)}
if weather['thunderstorm']:
return '\uf0e7'
elif weather['rain']:
return '\uf043'
elif (weather['snow'] or weather['cold']):
return '\uf2dc'
elif (weather['atmosphere'] or weather['windy']):
return '\ue8de'
elif (weather['squall'] or weather['tornado'] or weather['tropical storm'] or weather['hurricane']):
return '\uf2dd'
elif (weather['clear_day'] or weather['hot']):
return '\ue430'
elif weather['clear_night']:
return '\uf186'
elif weather['cloudy']:
return '\uf0c2'
elif weather['hail']:
return '\ue3ea' |
def get_thermo_icon(temp_value, temp_unit):
' Get thermometer icon based on temperature '
if (temp_unit == 'F'):
temp_value = convert_temp_unit(temp_unit, 'C')
if (temp_value <= (- 15)):
return '\uf2cb'
elif ((- 15) < temp_value <= 0):
return '\uf2ca'
elif (0 < temp_value <= 15):
return '\uf2c9'
elif (15 < temp_value <= 30):
return '\uf2c8'
elif (temp_value > 30):
return '\uf2c7' | -6,282,912,500,564,119,000 | Get thermometer icon based on temperature | .config/polybar/weather/weather.py | get_thermo_icon | NearHuscarl/dotfiles | python | def get_thermo_icon(temp_value, temp_unit):
' '
if (temp_unit == 'F'):
temp_value = convert_temp_unit(temp_unit, 'C')
if (temp_value <= (- 15)):
return '\uf2cb'
elif ((- 15) < temp_value <= 0):
return '\uf2ca'
elif (0 < temp_value <= 15):
return '\uf2c9'
elif (15 < temp_value <= 30):
return '\uf2c8'
elif (temp_value > 30):
return '\uf2c7' |
def convert_temp_unit(temp_value, temp_unit):
' Convert current temp_value to temp_unit '
if (temp_unit == 'C'):
return round(((temp_value - 32) / 1.8))
elif (temp_unit == 'F'):
return round(((temp_value * 1.8) + 32)) | -1,498,469,046,806,664,200 | Convert current temp_value to temp_unit | .config/polybar/weather/weather.py | convert_temp_unit | NearHuscarl/dotfiles | python | def convert_temp_unit(temp_value, temp_unit):
' '
if (temp_unit == 'C'):
return round(((temp_value - 32) / 1.8))
elif (temp_unit == 'F'):
return round(((temp_value * 1.8) + 32)) |
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