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jliljebl/flowblade | 995313a509b80e99eb1ad550d945bdda5995093b | flowblade-trunk/Flowblade/medialog.py | python | media_log_filtering_changed | () | [] | def media_log_filtering_changed():
widgets.media_log_view.fill_data_model() | [
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||||
bikalims/bika.lims | 35e4bbdb5a3912cae0b5eb13e51097c8b0486349 | bika/lims/validators.py | python | ResultOptionsValidator.__call__ | (self, value, *args, **kwargs) | return True | [] | def __call__(self, value, *args, **kwargs):
instance = kwargs['instance']
fieldname = kwargs['field'].getName()
request = kwargs.get('REQUEST', {})
form = request.form
form_value = form.get(fieldname)
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return True | [
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lmb-freiburg/netdef_models | 7d3311579cf712b31d05ec29f3dc63df067aa07b | FlowNetH/Pred-Merged-FT-KITTI/controller.py | python | Controller.__init__ | (self, net_actions=NetActions) | [] | def __init__(self, net_actions=NetActions):
super().__init__(net_actions=net_actions) | [
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||||
metamorphose/metamorphose2 | d2bdd6a86340b9668e93b35a6a568894c9909d68 | src/mutagen/aiff.py | python | delete | (filename) | Completely removes the ID3 chunk from the AIFF file | Completely removes the ID3 chunk from the AIFF file | [
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"""Completely removes the ID3 chunk from the AIFF file"""
with open(filename, "rb+") as file_:
try:
del IFFFile(file_)[u'ID3']
except KeyError:
pass | [
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||
sunpy/sunpy | 528579df0a4c938c133bd08971ba75c131b189a7 | sunpy/net/base_client.py | python | BaseClient.check_attr_types_in_query | (query, required_attrs={}, optional_attrs={}) | return required_attrs.issubset(query_attrs) and query_attrs.issubset(all_attrs) | Check a query againsted required and optional attributes.
Returns `True` if *query* contains all the attrs in *required_attrs*,
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"""
Check a query againsted required and optional attributes.
Returns `True` if *query* contains all the attrs in *required_attrs*,
and if *query* contains only attrs in both *required_attrs* and *optional_attrs*.
"""
query_attrs = {type(x) for x in query}
all_attrs = required_attrs.union(optional_attrs)
return required_attrs.issubset(query_attrs) and query_attrs.issubset(all_attrs) | [
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|
pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/site-packages/ipython-4.0.0-py3.3.egg/IPython/core/formatters.py | python | JSONFormatter._check_return | (self, r, obj) | return super(JSONFormatter, self)._check_return(r, obj) | Check that a return value is appropriate
Return the value if so, None otherwise, warning if invalid. | Check that a return value is appropriate
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"""Check that a return value is appropriate
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"""
if r is None:
return
md = None
if isinstance(r, tuple):
# unpack data, metadata tuple for type checking on first element
r, md = r
# handle deprecated JSON-as-string form from IPython < 3
if isinstance(r, string_types):
warnings.warn("JSON expects JSONable list/dict containers, not JSON strings",
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r = json.loads(r)
if md is not None:
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r = (r, md)
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|
realpython/book2-exercises | cde325eac8e6d8cff2316601c2e5b36bb46af7d0 | web2py-rest/gluon/contrib/aes.py | python | AES.setkey | (self, key) | Sets the key and performs key expansion. | Sets the key and performs key expansion. | [
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"""Sets the key and performs key expansion."""
self.key = key
self.key_size = len(key)
if self.key_size == 16:
self.rounds = 10
elif self.key_size == 24:
self.rounds = 12
elif self.key_size == 32:
self.rounds = 14
else:
raise ValueError("Key length must be 16, 24 or 32 bytes")
self.expand_key() | [
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||
MDAnalysis/mdanalysis | 3488df3cdb0c29ed41c4fb94efe334b541e31b21 | package/MDAnalysis/analysis/waterdynamics.py | python | MeanSquareDisplacement._sameMolecTandDT | (self, selection, t0d, tf) | return sort | Compare the molecules in the t0d selection and the t0d+dt selection and
select only the particles that are repeated in both frame. This is to
consider only the molecules that remains in the selection after the dt
time has elapsed. The result is a list with the indexs of the atoms. | Compare the molecules in the t0d selection and the t0d+dt selection and
select only the particles that are repeated in both frame. This is to
consider only the molecules that remains in the selection after the dt
time has elapsed. The result is a list with the indexs of the atoms. | [
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select only the particles that are repeated in both frame. This is to
consider only the molecules that remains in the selection after the dt
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a = set(selection[t0d])
b = set(selection[tf])
sort = sorted(list(a.intersection(b)))
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|
apeterswu/RL4NMT | 3c66a2d8142abc5ce73db63e05d3cc9bf4663b65 | tensor2tensor/data_generators/generator_utils.py | python | generate_files_distributed | (generator,
output_name,
output_dir,
num_shards=1,
max_cases=None,
task_id=0) | return output_file | generate_files but with a single writer writing to shard task_id. | generate_files but with a single writer writing to shard task_id. | [
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output_name,
output_dir,
num_shards=1,
max_cases=None,
task_id=0):
"""generate_files but with a single writer writing to shard task_id."""
assert task_id < num_shards
output_filename = sharded_name(output_name, task_id, num_shards)
output_file = os.path.join(output_dir, output_filename)
tf.logging.info("Writing to file %s", output_file)
writer = tf.python_io.TFRecordWriter(output_file)
counter = 0
for case in generator:
if counter % 100000 == 0:
tf.logging.info("Generating case %d for %s." % (counter, output_name))
counter += 1
if max_cases and counter > max_cases:
break
sequence_example = to_example(case)
writer.write(sequence_example.SerializeToString())
writer.close()
return output_file | [
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|
hkust-vgd/scanobjectnn | fe60aeade9ceb8882bc3f1bc40612e65469d7e77 | pointnet/utils/tf_util.py | python | conv2d | (inputs,
num_output_channels,
kernel_size,
scope,
stride=[1, 1],
padding='SAME',
use_xavier=True,
stddev=1e-3,
weight_decay=0.0,
activation_fn=tf.nn.relu,
bn=False,
bn_decay=None,
is_training=None) | 2D convolution with non-linear operation.
Args:
inputs: 4-D tensor variable BxHxWxC
num_output_channels: int
kernel_size: a list of 2 ints
scope: string
stride: a list of 2 ints
padding: 'SAME' or 'VALID'
use_xavier: bool, use xavier_initializer if true
stddev: float, stddev for truncated_normal init
weight_decay: float
activation_fn: function
bn: bool, whether to use batch norm
bn_decay: float or float tensor variable in [0,1]
is_training: bool Tensor variable
Returns:
Variable tensor | 2D convolution with non-linear operation. | [
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] | def conv2d(inputs,
num_output_channels,
kernel_size,
scope,
stride=[1, 1],
padding='SAME',
use_xavier=True,
stddev=1e-3,
weight_decay=0.0,
activation_fn=tf.nn.relu,
bn=False,
bn_decay=None,
is_training=None):
""" 2D convolution with non-linear operation.
Args:
inputs: 4-D tensor variable BxHxWxC
num_output_channels: int
kernel_size: a list of 2 ints
scope: string
stride: a list of 2 ints
padding: 'SAME' or 'VALID'
use_xavier: bool, use xavier_initializer if true
stddev: float, stddev for truncated_normal init
weight_decay: float
activation_fn: function
bn: bool, whether to use batch norm
bn_decay: float or float tensor variable in [0,1]
is_training: bool Tensor variable
Returns:
Variable tensor
"""
with tf.variable_scope(scope) as sc:
kernel_h, kernel_w = kernel_size
num_in_channels = inputs.get_shape()[-1].value
kernel_shape = [kernel_h, kernel_w,
num_in_channels, num_output_channels]
kernel = _variable_with_weight_decay('weights',
shape=kernel_shape,
use_xavier=use_xavier,
stddev=stddev,
wd=weight_decay)
stride_h, stride_w = stride
outputs = tf.nn.conv2d(inputs, kernel,
[1, stride_h, stride_w, 1],
padding=padding)
biases = _variable_on_cpu('biases', [num_output_channels],
tf.constant_initializer(0.0))
outputs = tf.nn.bias_add(outputs, biases)
if bn:
outputs = batch_norm_for_conv2d(outputs, is_training,
bn_decay=bn_decay, scope='bn')
if activation_fn is not None:
outputs = activation_fn(outputs)
return outputs | [
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||
healpy/healpy | c34d032edaef6e1b755929aa76cf0cc933fcc677 | setup.py | python | custom_build_ext.run | (self) | [] | def run(self):
# If we were asked to build any C/C++ libraries, add the directory
# where we built them to the include path. (It's already on the library
# path.)
if self.distribution.has_c_libraries():
self.run_command("build_clib")
build_clib = self.get_finalized_command("build_clib")
for key, value in build_clib.build_args.items():
for ext in self.extensions:
if not hasattr(ext, key) or getattr(ext, key) is None:
setattr(ext, key, value)
else:
getattr(ext, key).extend(value)
build_ext.run(self) | [
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||||
DLTK/DLTK | f94d3bb509eb0741164149acbef0788769a869e4 | examples/applications/IXI_HH_sex_classification_resnet/train.py | python | model_fn | (features, labels, mode, params) | return tf.estimator.EstimatorSpec(mode=mode,
predictions=net_output_ops,
loss=loss,
train_op=train_op,
eval_metric_ops=eval_metric_ops) | Model function to construct a tf.estimator.EstimatorSpec. It creates a
network given input features (e.g. from a dltk.io.abstract_reader) and
training targets (labels). Further, loss, optimiser, evaluation ops and
custom tensorboard summary ops can be added. For additional information,
please refer to https://www.tensorflow.org/api_docs/python/tf/estimator/Estimator#model_fn.
Args:
features (tf.Tensor): Tensor of input features to train from. Required
rank and dimensions are determined by the subsequent ops
(i.e. the network).
labels (tf.Tensor): Tensor of training targets or labels. Required rank
and dimensions are determined by the network output.
mode (str): One of the tf.estimator.ModeKeys: TRAIN, EVAL or PREDICT
params (dict, optional): A dictionary to parameterise the model_fn
(e.g. learning_rate)
Returns:
tf.estimator.EstimatorSpec: A custom EstimatorSpec for this experiment | Model function to construct a tf.estimator.EstimatorSpec. It creates a
network given input features (e.g. from a dltk.io.abstract_reader) and
training targets (labels). Further, loss, optimiser, evaluation ops and
custom tensorboard summary ops can be added. For additional information,
please refer to https://www.tensorflow.org/api_docs/python/tf/estimator/Estimator#model_fn. | [
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"""Model function to construct a tf.estimator.EstimatorSpec. It creates a
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training targets (labels). Further, loss, optimiser, evaluation ops and
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please refer to https://www.tensorflow.org/api_docs/python/tf/estimator/Estimator#model_fn.
Args:
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rank and dimensions are determined by the subsequent ops
(i.e. the network).
labels (tf.Tensor): Tensor of training targets or labels. Required rank
and dimensions are determined by the network output.
mode (str): One of the tf.estimator.ModeKeys: TRAIN, EVAL or PREDICT
params (dict, optional): A dictionary to parameterise the model_fn
(e.g. learning_rate)
Returns:
tf.estimator.EstimatorSpec: A custom EstimatorSpec for this experiment
"""
# 1. create a model and its outputs
net_output_ops = resnet_3d(
features['x'],
num_res_units=2,
num_classes=NUM_CLASSES,
filters=(16, 32, 64, 128, 256),
strides=((1, 1, 1), (2, 2, 2), (2, 2, 2), (2, 2, 2), (2, 2, 2)),
mode=mode,
kernel_regularizer=tf.contrib.layers.l2_regularizer(1e-3))
# 1.1 Generate predictions only (for `ModeKeys.PREDICT`)
if mode == tf.estimator.ModeKeys.PREDICT:
return tf.estimator.EstimatorSpec(
mode=mode,
predictions=net_output_ops,
export_outputs={'out': tf.estimator.export.PredictOutput(net_output_ops)})
# 2. set up a loss function
one_hot_labels = tf.reshape(tf.one_hot(labels['y'], depth=NUM_CLASSES), [-1, NUM_CLASSES])
loss = tf.losses.softmax_cross_entropy(
onehot_labels=one_hot_labels,
logits=net_output_ops['logits'])
# 3. define a training op and ops for updating moving averages (i.e. for
# batch normalisation)
global_step = tf.train.get_global_step()
optimiser = tf.train.AdamOptimizer(
learning_rate=params["learning_rate"],
epsilon=1e-5)
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
with tf.control_dependencies(update_ops):
train_op = optimiser.minimize(loss, global_step=global_step)
# 4.1 (optional) create custom image summaries for tensorboard
my_image_summaries = {}
my_image_summaries['feat_t1'] = features['x'][0, 32, :, :, 0]
expected_output_size = [1, 96, 96, 1] # [B, W, H, C]
[tf.summary.image(name, tf.reshape(image, expected_output_size))
for name, image in my_image_summaries.items()]
# 4.2 (optional) track the rmse (scaled back by 100, see reader.py)
acc = tf.metrics.accuracy
prec = tf.metrics.precision
eval_metric_ops = {"accuracy": acc(labels['y'], net_output_ops['y_']),
"precision": prec(labels['y'], net_output_ops['y_'])}
# 5. Return EstimatorSpec object
return tf.estimator.EstimatorSpec(mode=mode,
predictions=net_output_ops,
loss=loss,
train_op=train_op,
eval_metric_ops=eval_metric_ops) | [
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|
MozillaSecurity/grizzly | 1c41478e32f323189a2c322ec041c3e0902a158a | grizzly/common/status.py | python | ReductionStatus._construct_milestone | (self, name, start, attempts, iterations, successes) | return _MilestoneTimer() | [] | def _construct_milestone(self, name, start, attempts, iterations, successes):
# pylint: disable=no-self-argument
class _MilestoneTimer:
def __init__(sub):
sub.name = name
sub._start_time = start
sub._start_attempts = attempts
sub._start_iterations = iterations
sub._start_successes = successes
@property
def size(sub):
return self._testcase_size() # pylint: disable=protected-access
@property
def attempts(sub):
return self.attempts - sub._start_attempts
@property
def iterations(sub):
return self.iterations - sub._start_iterations
@property
def successes(sub):
return self.successes - sub._start_successes
@property
def duration(sub):
if self._db_file is None: # pylint: disable=protected-access
return self.timestamp - sub._start_time
return time() - sub._start_time
def serialize(sub):
return (
sub.name,
sub._start_time,
sub._start_attempts,
sub._start_iterations,
sub._start_successes,
)
return _MilestoneTimer() | [
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|||
pantsbuild/pex | 473c6ac732ed4bc338b4b20a9ec930d1d722c9b4 | pex/vendor/_vendored/packaging/pyparsing.py | python | MatchFirst.parseImpl | (self, instring, loc, doActions=True) | [] | def parseImpl(self, instring, loc, doActions=True):
maxExcLoc = -1
maxException = None
for e in self.exprs:
try:
ret = e._parse(instring, loc, doActions)
return ret
except ParseException as err:
if err.loc > maxExcLoc:
maxException = err
maxExcLoc = err.loc
except IndexError:
if len(instring) > maxExcLoc:
maxException = ParseException(instring, len(instring), e.errmsg, self)
maxExcLoc = len(instring)
# only got here if no expression matched, raise exception for match that made it the furthest
else:
if maxException is not None:
maxException.msg = self.errmsg
raise maxException
else:
raise ParseException(instring, loc, "no defined alternatives to match", self) | [
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||||
AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.4/django/contrib/gis/maps/google/gmap.py | python | GoogleMap.js | (self) | return self.render() | Returns only the generated Google Maps JavaScript (no <script> tags). | Returns only the generated Google Maps JavaScript (no <script> tags). | [
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] | https://github.com/AppScale/gts/blob/46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9/AppServer/lib/django-1.4/django/contrib/gis/maps/google/gmap.py#L127-L129 |
|
openatx/uiautomator2 | a6ebc2446a8babb4ce14dc62cfdb5590ea95c709 | uiautomator2/__init__.py | python | _Device.set_orientation | (self, value) | setter of orientation property. | setter of orientation property. | [
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"property",
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] | def set_orientation(self, value):
'''setter of orientation property.'''
for values in self.__orientation:
if value in values:
# can not set upside-down until api level 18.
self.jsonrpc.setOrientation(values[1])
break
else:
raise ValueError("Invalid orientation.") | [
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||
wxWidgets/Phoenix | b2199e299a6ca6d866aa6f3d0888499136ead9d6 | wx/lib/agw/ribbon/buttonbar.py | python | RibbonButtonBar.OnMouseMove | (self, event) | Handles the ``wx.EVT_MOTION`` event for :class:`RibbonButtonBar`.
:param `event`: a :class:`MouseEvent` event to be processed. | Handles the ``wx.EVT_MOTION`` event for :class:`RibbonButtonBar`. | [
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"""
Handles the ``wx.EVT_MOTION`` event for :class:`RibbonButtonBar`.
:param `event`: a :class:`MouseEvent` event to be processed.
"""
cursor = event.GetPosition()
new_hovered = None
new_hovered_state = 0
layout = self._layouts[self._current_layout]
for instance in layout.buttons:
size = instance.base.sizes[instance.size]
btn_rect = wx.Rect()
btn_rect.SetTopLeft(self._layout_offset + instance.position)
btn_rect.SetSize(size.size)
if btn_rect.Contains(cursor) and self.IsButtonEnabled(instance.base.id):
new_hovered = instance
new_hovered_state = instance.base.state
new_hovered_state &= ~RIBBON_BUTTONBAR_BUTTON_HOVER_MASK
offset = wx.Point(*cursor)
offset -= btn_rect.GetTopLeft()
if size.normal_region.Contains(offset):
new_hovered_state |= RIBBON_BUTTONBAR_BUTTON_NORMAL_HOVERED
if size.dropdown_region.Contains(offset):
new_hovered_state |= RIBBON_BUTTONBAR_BUTTON_DROPDOWN_HOVERED
break
if new_hovered is None and self.GetToolTip():
self.SetToolTip("")
if new_hovered != self._hovered_button or (self._hovered_button is not None and \
new_hovered_state != self._hovered_button.base.state):
if self._hovered_button is not None:
self._hovered_button.base.state &= ~RIBBON_BUTTONBAR_BUTTON_HOVER_MASK
self._hovered_button = new_hovered
if self._hovered_button is not None:
self._hovered_button.base.state = new_hovered_state
self.SetToolTip(self._hovered_button.base.help_string)
self.Refresh(False)
if self._active_button and not self._lock_active_state:
new_active_state = self._active_button.base.state
new_active_state &= ~RIBBON_BUTTONBAR_BUTTON_ACTIVE_MASK
size = self._active_button.base.sizes[self._active_button.size]
btn_rect = wx.Rect()
btn_rect.SetTopLeft(self._layout_offset + self._active_button.position)
btn_rect.SetSize(size.size)
if btn_rect.Contains(cursor):
offset = wx.Point(*cursor)
offset -= btn_rect.GetTopLeft()
if size.normal_region.Contains(offset):
new_active_state |= RIBBON_BUTTONBAR_BUTTON_NORMAL_ACTIVE
if size.dropdown_region.Contains(offset):
new_active_state |= RIBBON_BUTTONBAR_BUTTON_DROPDOWN_ACTIVE
if new_active_state != self._active_button.base.state:
self._active_button.base.state = new_active_state
self.Refresh(False) | [
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||
PaddlePaddle/Research | 2da0bd6c72d60e9df403aff23a7802779561c4a1 | NLP/MRQA2019-BASELINE/src/model/transformer_encoder.py | python | encoder | (enc_input,
attn_bias,
n_layer,
n_head,
d_key,
d_value,
d_model,
d_inner_hid,
prepostprocess_dropout,
attention_dropout,
relu_dropout,
hidden_act,
preprocess_cmd="n",
postprocess_cmd="da",
param_initializer=None,
name='') | return enc_output | The encoder is composed of a stack of identical layers returned by calling
encoder_layer. | The encoder is composed of a stack of identical layers returned by calling
encoder_layer. | [
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"encoder_layer",
"."
] | def encoder(enc_input,
attn_bias,
n_layer,
n_head,
d_key,
d_value,
d_model,
d_inner_hid,
prepostprocess_dropout,
attention_dropout,
relu_dropout,
hidden_act,
preprocess_cmd="n",
postprocess_cmd="da",
param_initializer=None,
name=''):
"""
The encoder is composed of a stack of identical layers returned by calling
encoder_layer.
"""
for i in range(n_layer):
enc_output = encoder_layer(
enc_input,
attn_bias,
n_head,
d_key,
d_value,
d_model,
d_inner_hid,
prepostprocess_dropout,
attention_dropout,
relu_dropout,
hidden_act,
preprocess_cmd,
postprocess_cmd,
param_initializer=param_initializer,
name=name + '_layer_' + str(i))
enc_input = enc_output
enc_output = pre_process_layer(
enc_output, preprocess_cmd, prepostprocess_dropout, name="post_encoder")
return enc_output | [
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|
AstroPrint/AstroBox | e7e3b8a7d33ea85fcb6b2696869c0d719ceb8b75 | src/ext/makerbot_driver/EEPROM/EepromAnalyzer.py | python | eeprom_analyzer.parse_out_name_and_location | (self, line) | return name, location | Given a line in the form of:
const static uint16_t <name> = <location>;
parses out the name and location.
If we get a line not of this form, we will fail.
@param str line: the line we want information from
@return tuple: Information in the form of (name, location) | Given a line in the form of:
const static uint16_t <name> = <location>;
parses out the name and location.
If we get a line not of this form, we will fail. | [
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"""
Given a line in the form of:
const static uint16_t <name> = <location>;
parses out the name and location.
If we get a line not of this form, we will fail.
@param str line: the line we want information from
@return tuple: Information in the form of (name, location)
"""
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substring = substring.replace('\t', '')
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return name, location | [
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|
AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.4/django/views/defaults.py | python | permission_denied | (request, template_name='403.html') | return http.HttpResponseForbidden(template.render(RequestContext(request))) | Permission denied (403) handler.
Templates: `403.html`
Context: None
If the template does not exist, an Http403 response containing the text
"403 Forbidden" (as per RFC 2616) will be returned. | Permission denied (403) handler. | [
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] | def permission_denied(request, template_name='403.html'):
"""
Permission denied (403) handler.
Templates: `403.html`
Context: None
If the template does not exist, an Http403 response containing the text
"403 Forbidden" (as per RFC 2616) will be returned.
"""
try:
template = loader.get_template(template_name)
except TemplateDoesNotExist:
return http.HttpResponseForbidden('<h1>403 Forbidden</h1>')
return http.HttpResponseForbidden(template.render(RequestContext(request))) | [
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|
evennia/evennia | fa79110ba6b219932f22297838e8ac72ebc0be0e | evennia/contrib/tutorial_examples/cmdset_red_button.py | python | CmdPush.func | (self) | Note that we choose to implement this with checking for
if the lid is open/closed. This is because this command
is likely to be tried regardless of the state of the lid.
An alternative would be to make two versions of this command
and tuck them into the cmdset linked to the Open and Closed
lid-state respectively. | Note that we choose to implement this with checking for
if the lid is open/closed. This is because this command
is likely to be tried regardless of the state of the lid. | [
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"""
Note that we choose to implement this with checking for
if the lid is open/closed. This is because this command
is likely to be tried regardless of the state of the lid.
An alternative would be to make two versions of this command
and tuck them into the cmdset linked to the Open and Closed
lid-state respectively.
"""
if self.obj.db.lid_open:
string = "You reach out to press the big red button ..."
string += "\n\nA BOOM! A bright light blinds you!"
string += "\nThe world goes dark ..."
self.caller.msg(string)
self.caller.location.msg_contents(
"%s presses the button. BOOM! %s is blinded by a flash!"
% (self.caller.name, self.caller.name),
exclude=self.caller,
)
# the button's method will handle all setup of scripts etc.
self.obj.press_button(self.caller)
else:
string = "You cannot push the button - there is a glass lid covering it."
self.caller.msg(string) | [
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] | https://github.com/evennia/evennia/blob/fa79110ba6b219932f22297838e8ac72ebc0be0e/evennia/contrib/tutorial_examples/cmdset_red_button.py#L62-L88 |
||
geekan/scrapy-examples | edb1cb116bd6def65a6ef01f953b58eb43e54305 | sinanews/sinanews/spiders/spider.py | python | sinanewsSpider.parse_0 | (self, response) | [] | def parse_0(self, response):
info('Parse 0 '+response.url)
x = self.parse_with_rules(response, self.list_css_rules, dict)
pp.pprint(x) | [
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4shadoww/hakkuframework | 409a11fc3819d251f86faa3473439f8c19066a21 | lib/scapy/layers/tls/session.py | python | tlsSession.mirror | (self) | return self | This function takes a tlsSession object and swaps the IP addresses,
ports, connection ends and connection states. The triggered_commit are
also swapped (though it is probably overkill, it is cleaner this way).
It is useful for static analysis of a series of messages from both the
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vice versa. For instance you could do:
client_hello = open('client_hello.raw').read()
<read other messages>
m1 = TLS(client_hello)
m2 = TLS(server_hello, tls_session=m1.tls_session.mirror())
m3 = TLS(server_cert, tls_session=m2.tls_session)
m4 = TLS(client_keyexchange, tls_session=m3.tls_session.mirror()) | This function takes a tlsSession object and swaps the IP addresses,
ports, connection ends and connection states. The triggered_commit are
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"""
This function takes a tlsSession object and swaps the IP addresses,
ports, connection ends and connection states. The triggered_commit are
also swapped (though it is probably overkill, it is cleaner this way).
It is useful for static analysis of a series of messages from both the
client and the server. In such a situation, it should be used every
time the message being read comes from a different side than the one
read right before, as the reading state becomes the writing state, and
vice versa. For instance you could do:
client_hello = open('client_hello.raw').read()
<read other messages>
m1 = TLS(client_hello)
m2 = TLS(server_hello, tls_session=m1.tls_session.mirror())
m3 = TLS(server_cert, tls_session=m2.tls_session)
m4 = TLS(client_keyexchange, tls_session=m3.tls_session.mirror())
"""
self.ipdst, self.ipsrc = self.ipsrc, self.ipdst
self.dport, self.sport = self.sport, self.dport
self.rcs, self.wcs = self.wcs, self.rcs
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self.rcs.row = "read"
if self.wcs:
self.wcs.row = "write"
self.prcs, self.pwcs = self.pwcs, self.prcs
if self.prcs:
self.prcs.row = "read"
if self.pwcs:
self.pwcs.row = "write"
self.triggered_prcs_commit, self.triggered_pwcs_commit = \
self.triggered_pwcs_commit, self.triggered_prcs_commit
if self.connection_end == "client":
self.connection_end = "server"
elif self.connection_end == "server":
self.connection_end = "client"
return self | [
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|
andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/plugins/evasion/rnd_param.py | python | rnd_param.get_long_desc | (self) | return """
This evasion plugin adds a random parameter.
Example:
Input: '/bar/foo.asp'
Output: '/bar/foo.asp?alsfkj=f09'
""" | :return: A DETAILED description of the plugin functions and features. | :return: A DETAILED description of the plugin functions and features. | [
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"""
:return: A DETAILED description of the plugin functions and features.
"""
return """
This evasion plugin adds a random parameter.
Example:
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|
qibinlou/SinaWeibo-Emotion-Classification | f336fc104abd68b0ec4180fe2ed80fafe49cb790 | nltk/inference/nonmonotonic.py | python | ClosedWorldProver._make_predicate_dict | (self, assumptions) | return predicates | Create a dictionary of predicates from the assumptions.
:param assumptions: a list of ``Expression``s
:return: dict mapping ``AbstractVariableExpression`` to ``PredHolder`` | Create a dictionary of predicates from the assumptions. | [
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Create a dictionary of predicates from the assumptions.
:param assumptions: a list of ``Expression``s
:return: dict mapping ``AbstractVariableExpression`` to ``PredHolder``
"""
predicates = defaultdict(PredHolder)
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self._map_predicates(a, predicates)
return predicates | [
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|
theotherp/nzbhydra | 4b03d7f769384b97dfc60dade4806c0fc987514e | libs/pycparser/c_parser.py | python | CParser.p_external_declaration_4 | (self, p) | external_declaration : SEMI | external_declaration : SEMI | [
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||
ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/bin/x86/Debug/Lib/smtplib.py | python | SMTP.docmd | (self, cmd, args="") | return self.getreply() | Send a command, and return its response code. | Send a command, and return its response code. | [
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|
Jenyay/outwiker | 50530cf7b3f71480bb075b2829bc0669773b835b | plugins/source/source/pygments/__init__.py | python | lex | (code, lexer) | Lex ``code`` with ``lexer`` and return an iterable of tokens. | Lex ``code`` with ``lexer`` and return an iterable of tokens. | [
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"""
Lex ``code`` with ``lexer`` and return an iterable of tokens.
"""
try:
return lexer.get_tokens(code)
except TypeError as err:
if (isinstance(err.args[0], str) and
('unbound method get_tokens' in err.args[0] or
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raise TypeError('lex() argument must be a lexer instance, '
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||
Xilinx/finn | d1cc9cf94f1c33354cc169c5a6517314d0e94e3b | src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py | python | StreamingMaxPool_Batch.get_number_output_values | (self) | return np.prod(folded_oshape[:-1]) | [] | def get_number_output_values(self):
folded_oshape = self.get_folded_output_shape()
return np.prod(folded_oshape[:-1]) | [
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|||
allenai/allennlp | a3d71254fcc0f3615910e9c3d48874515edf53e0 | scripts/check_links.py | python | url_ok | (match_tuple: MatchTuple) | Check if a URL is reachable. | Check if a URL is reachable. | [
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return (
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||
scipy/scipy | e0a749f01e79046642ccfdc419edbf9e7ca141ad | scipy/optimize/_shgo_lib/triangulation.py | python | Complex.add_centroid | (self) | return | Split the central edge between the origin and supremum of
a cell and add the new vertex to the complex | Split the central edge between the origin and supremum of
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|
titusjan/argos | 5a9c31a8a9a2ca825bbf821aa1e685740e3682d7 | argos/qt/treemodels.py | python | BaseTreeModel.hasChildren | (self, parentIndex=QtCore.QModelIndex()) | return parentItem.hasChildren() | Returns true if parent has any children; otherwise returns false.
Use rowCount() on the parent to find out the number of children. | Returns true if parent has any children; otherwise returns false.
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parentItem = self.getItem(parentIndex, altItem=self.invisibleRootTreeItem)
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|
IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/CPython/27/Lib/json/__init__.py | python | load | (fp, encoding=None, cls=None, object_hook=None, parse_float=None,
parse_int=None, parse_constant=None, object_pairs_hook=None, **kw) | return loads(fp.read(),
encoding=encoding, cls=cls, object_hook=object_hook,
parse_float=parse_float, parse_int=parse_int,
parse_constant=parse_constant, object_pairs_hook=object_pairs_hook,
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] | def load(fp, encoding=None, cls=None, object_hook=None, parse_float=None,
parse_int=None, parse_constant=None, object_pairs_hook=None, **kw):
"""Deserialize ``fp`` (a ``.read()``-supporting file-like object containing
a JSON document) to a Python object.
If the contents of ``fp`` is encoded with an ASCII based encoding other
than utf-8 (e.g. latin-1), then an appropriate ``encoding`` name must
be specified. Encodings that are not ASCII based (such as UCS-2) are
not allowed, and should be wrapped with
``codecs.getreader(fp)(encoding)``, or simply decoded to a ``unicode``
object and passed to ``loads()``
``object_hook`` is an optional function that will be called with the
result of any object literal decode (a ``dict``). The return value of
``object_hook`` will be used instead of the ``dict``. This feature
can be used to implement custom decoders (e.g. JSON-RPC class hinting).
``object_pairs_hook`` is an optional function that will be called with the
result of any object literal decoded with an ordered list of pairs. The
return value of ``object_pairs_hook`` will be used instead of the ``dict``.
This feature can be used to implement custom decoders that rely on the
order that the key and value pairs are decoded (for example,
collections.OrderedDict will remember the order of insertion). If
``object_hook`` is also defined, the ``object_pairs_hook`` takes priority.
To use a custom ``JSONDecoder`` subclass, specify it with the ``cls``
kwarg; otherwise ``JSONDecoder`` is used.
"""
return loads(fp.read(),
encoding=encoding, cls=cls, object_hook=object_hook,
parse_float=parse_float, parse_int=parse_int,
parse_constant=parse_constant, object_pairs_hook=object_pairs_hook,
**kw) | [
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|
jython/frozen-mirror | b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99 | Lib/dbexts.py | python | dbexts.close | (self) | close the connection to the database | close the connection to the database | [
"close",
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"database"
] | def close(self):
""" close the connection to the database """
self.db.close() | [
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||
aouyar/PyMunin | 94624d4f56340cb2ed7e96ca3c5d9533a0721306 | pysysinfo/diskio.py | python | DiskIOinfo.getSwapList | (self) | return self._swapList | Returns list of disk devices used for paging.
@return: List of disk devices. | Returns list of disk devices used for paging. | [
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] | def getSwapList(self):
"""Returns list of disk devices used for paging.
@return: List of disk devices.
"""
if self._swapList is None:
self._initSwapInfo()
return self._swapList | [
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|
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/celery/bin/upgrade.py | python | upgrade._to_new_key | (self, line, keyfilter=pass1, source=defaults._TO_NEW_KEY) | return 0, line | [] | def _to_new_key(self, line, keyfilter=pass1, source=defaults._TO_NEW_KEY):
# sort by length to avoid, for example, broker_transport overriding
# broker_transport_options.
for old_key in reversed(sorted(source, key=lambda x: len(x))):
new_line = line.replace(old_key, keyfilter(source[old_key]))
if line != new_line and 'CELERY_CELERY' not in new_line:
return 1, new_line # only one match per line.
return 0, line | [
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|||
yandex/yandex-tank | b41bcc04396c4ed46fc8b28a261197320854fd33 | yandextank/common/util.py | python | get_callstack | () | return '.'.join(cleaned[1:]) | Get call stack, clean wrapper functions from it and present
in dotted notation form | Get call stack, clean wrapper functions from it and present
in dotted notation form | [
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] | def get_callstack():
"""
Get call stack, clean wrapper functions from it and present
in dotted notation form
"""
stack = inspect.stack(context=0)
cleaned = [frame[3] for frame in stack if frame[3] != 'wrapper']
return '.'.join(cleaned[1:]) | [
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|
pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/fractions.py | python | Fraction.__gt__ | (a, b) | return a._richcmp(b, operator.gt) | a > b | a > b | [
"a",
">",
"b"
] | def __gt__(a, b):
"""a > b"""
return a._richcmp(b, operator.gt) | [
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|
CGATOxford/cgat | 326aad4694bdfae8ddc194171bb5d73911243947 | obsolete/pipeline_species_conservation.py | python | nmiConservationFisherTest | ( infile, outfile ) | Plot heatmap of pairwise scores in R | Plot heatmap of pairwise scores in R | [
"Plot",
"heatmap",
"of",
"pairwise",
"scores",
"in",
"R"
] | def nmiConservationFisherTest( infile, outfile ):
'''Plot heatmap of pairwise scores in R'''
scriptsdir = PARAMS["scriptsdir"]
R('''source("%(scriptsdir)s/R/proj007/proj007.R")''' % locals() )
#print '''nmi_conservation(infile="%(infile)s", outfile="%(outfile)s") ''' % locals()
R('''nmi_conservation(infile="%(infile)s", outfile="%(outfile)s") ''' % locals() ) | [
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||
fictorial/pygameui | af6a35f347d6fafa66c4255bbbe38736d842ff65 | pygameui/textfield.py | python | TextField.key_down | (self, key, code) | [] | def key_down(self, key, code):
if key == pygame.K_BACKSPACE:
self.text = self.text[0:-1]
elif key == pygame.K_RETURN:
can_submit = True
if self.placeholder and self.text == self.placeholder:
can_submit = False
if can_submit:
self.on_return(self, self.text)
else:
try:
self.text = '%s%s' % (self.text, str(code))
except:
pass
self.on_text_change(self, self.text)
if self.max_len:
self.text = self.text[0:self.max_len]
self._update_text()
self.label.shrink_wrap()
self.label.layout()
if self.label.frame.right > self.frame.w - self.padding[0] * 2:
self.label.frame.right = self.frame.w - self.padding[0] * 2
else:
self.label.frame.left = self.padding[0] | [
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||||
openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/twisted/twisted/internet/defer.py | python | Deferred.__init__ | (self, canceller=None) | Initialize a L{Deferred}.
@param canceller: a callable used to stop the pending operation
scheduled by this L{Deferred} when L{Deferred.cancel} is
invoked. The canceller will be passed the deferred whose
cancelation is requested (i.e., self).
If a canceller is not given, or does not invoke its argument's
C{callback} or C{errback} method, L{Deferred.cancel} will
invoke L{Deferred.errback} with a L{CancelledError}.
Note that if a canceller is not given, C{callback} or
C{errback} may still be invoked exactly once, even though
defer.py will have already invoked C{errback}, as described
above. This allows clients of code which returns a L{Deferred}
to cancel it without requiring the L{Deferred} instantiator to
provide any specific implementation support for cancellation.
New in 10.1.
@type canceller: a 1-argument callable which takes a L{Deferred}. The
return result is ignored. | Initialize a L{Deferred}. | [
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] | def __init__(self, canceller=None):
"""
Initialize a L{Deferred}.
@param canceller: a callable used to stop the pending operation
scheduled by this L{Deferred} when L{Deferred.cancel} is
invoked. The canceller will be passed the deferred whose
cancelation is requested (i.e., self).
If a canceller is not given, or does not invoke its argument's
C{callback} or C{errback} method, L{Deferred.cancel} will
invoke L{Deferred.errback} with a L{CancelledError}.
Note that if a canceller is not given, C{callback} or
C{errback} may still be invoked exactly once, even though
defer.py will have already invoked C{errback}, as described
above. This allows clients of code which returns a L{Deferred}
to cancel it without requiring the L{Deferred} instantiator to
provide any specific implementation support for cancellation.
New in 10.1.
@type canceller: a 1-argument callable which takes a L{Deferred}. The
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"""
self.callbacks = []
self._canceller = canceller
if self.debug:
self._debugInfo = DebugInfo()
self._debugInfo.creator = traceback.format_stack()[:-1] | [
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||
openai/random-network-distillation | f75c0f1efa473d5109d487062fd8ed49ddce6634 | tf_util.py | python | switch | (condition, then_expression, else_expression) | return x | Switches between two operations depending on a scalar value (int or bool).
Note that both `then_expression` and `else_expression`
should be symbolic tensors of the *same shape*.
# Arguments
condition: scalar tensor.
then_expression: TensorFlow operation.
else_expression: TensorFlow operation. | Switches between two operations depending on a scalar value (int or bool).
Note that both `then_expression` and `else_expression`
should be symbolic tensors of the *same shape*. | [
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] | def switch(condition, then_expression, else_expression):
"""Switches between two operations depending on a scalar value (int or bool).
Note that both `then_expression` and `else_expression`
should be symbolic tensors of the *same shape*.
# Arguments
condition: scalar tensor.
then_expression: TensorFlow operation.
else_expression: TensorFlow operation.
"""
x_shape = copy.copy(then_expression.get_shape())
x = tf.cond(tf.cast(condition, 'bool'),
lambda: then_expression,
lambda: else_expression)
x.set_shape(x_shape)
return x | [
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|
OpenEIT/OpenEIT | 0448694e8092361ae5ccb45fba81dee543a6244b | OpenEIT/backend/bluetooth/old/build/dlib/Adafruit_BluefruitLE/bluez_dbus/gatt.py | python | BluezGattCharacteristic.start_notify | (self, on_change) | Enable notification of changes for this characteristic on the
specified on_change callback. on_change should be a function that takes
one parameter which is the value (as a string of bytes) of the changed
characteristic value. | Enable notification of changes for this characteristic on the
specified on_change callback. on_change should be a function that takes
one parameter which is the value (as a string of bytes) of the changed
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] | def start_notify(self, on_change):
"""Enable notification of changes for this characteristic on the
specified on_change callback. on_change should be a function that takes
one parameter which is the value (as a string of bytes) of the changed
characteristic value.
"""
# Setup a closure to be the first step in handling the on change callback.
# This closure will verify the characteristic is changed and pull out the
# new value to pass to the user's on change callback.
def characteristic_changed(iface, changed_props, invalidated_props):
# Check that this change is for a GATT characteristic and it has a
# new value.
if iface != _CHARACTERISTIC_INTERFACE:
return
if 'Value' not in changed_props:
return
# Send the new value to the on_change callback.
on_change(''.join(map(chr, changed_props['Value'])))
# Hook up the property changed signal to call the closure above.
self._props.connect_to_signal('PropertiesChanged', characteristic_changed)
# Enable notifications for changes on the characteristic.
self._characteristic.StartNotify() | [
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] | https://github.com/OpenEIT/OpenEIT/blob/0448694e8092361ae5ccb45fba81dee543a6244b/OpenEIT/backend/bluetooth/old/build/dlib/Adafruit_BluefruitLE/bluez_dbus/gatt.py#L84-L105 |
||
TalwalkarLab/leaf | 09ec454a5675e32e1f0546b456b77857fdece018 | data/reddit/source/preprocess.py | python | order_data | (user_data) | return {'x': [z[0] for z in zipped], 'y': [z[1] for z in zipped]} | [] | def order_data(user_data):
zipped = list(zip(user_data['x'], user_data['y']))
zipped = sorted(zipped, key=lambda x: x[1]['created_utc'])
return {'x': [z[0] for z in zipped], 'y': [z[1] for z in zipped]} | [
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|||
ZZUTK/SRNTT | c9a2cf95534e2d3c2c2210718c9903c9f389d67d | SRNTT/tensorlayer/ops.py | python | set_gpu_fraction | (sess=None, gpu_fraction=0.3) | return sess | Set the GPU memory fraction for the application.
Parameters
----------
sess : a session instance of TensorFlow
TensorFlow session
gpu_fraction : a float
Fraction of GPU memory, (0 ~ 1]
References
----------
- `TensorFlow using GPU <https://www.tensorflow.org/versions/r0.9/how_tos/using_gpu/index.html>`_ | Set the GPU memory fraction for the application. | [
"Set",
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] | def set_gpu_fraction(sess=None, gpu_fraction=0.3):
"""Set the GPU memory fraction for the application.
Parameters
----------
sess : a session instance of TensorFlow
TensorFlow session
gpu_fraction : a float
Fraction of GPU memory, (0 ~ 1]
References
----------
- `TensorFlow using GPU <https://www.tensorflow.org/versions/r0.9/how_tos/using_gpu/index.html>`_
"""
print(" tensorlayer: GPU MEM Fraction %f" % gpu_fraction)
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=gpu_fraction)
sess = tf.Session(config = tf.ConfigProto(gpu_options = gpu_options))
return sess | [
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|
magenta/magenta | be6558f1a06984faff6d6949234f5fe9ad0ffdb5 | magenta/interfaces/midi/midi_hub.py | python | MidiHub._handle_message | (self, msg) | Handles a single incoming MIDI message.
-If the message is being used as a signal, notifies threads waiting on the
appropriate condition variable.
-Adds the message to any capture queues.
-Passes the message through to the output port, if appropriate.
Args:
msg: The mido.Message MIDI message to handle. | Handles a single incoming MIDI message. | [
"Handles",
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] | def _handle_message(self, msg):
"""Handles a single incoming MIDI message.
-If the message is being used as a signal, notifies threads waiting on the
appropriate condition variable.
-Adds the message to any capture queues.
-Passes the message through to the output port, if appropriate.
Args:
msg: The mido.Message MIDI message to handle.
"""
# Notify any threads waiting for this message.
msg_str = str(msg)
for regex in list(self._signals):
if regex.match(msg_str) is not None:
self._signals[regex].notify_all()
del self._signals[regex]
# Call any callbacks waiting for this message.
for regex in list(self._callbacks):
if regex.match(msg_str) is not None:
for fn in self._callbacks[regex]:
threading.Thread(target=fn, args=(msg,)).start()
del self._callbacks[regex]
# Remove any captors that are no longer alive.
self._captors[:] = [t for t in self._captors if t.is_alive()]
# Add a different copy of the message to the receive queue of each live
# capture thread.
for t in self._captors:
t.receive(msg.copy())
# Update control values if this is a control change message.
if msg.type == 'control_change':
if self._control_values.get(msg.control, None) != msg.value:
tf.logging.debug('Control change %d: %d', msg.control, msg.value)
self._control_values[msg.control] = msg.value
# Pass the message through to the output port, if appropriate.
if not self._passthrough:
pass
elif self._texture_type == TextureType.POLYPHONIC:
if msg.type == 'note_on' and msg.velocity > 0:
self._open_notes.add(msg.note)
elif (msg.type == 'note_off' or
(msg.type == 'note_on' and msg.velocity == 0)):
self._open_notes.discard(msg.note)
self._outport.send(msg)
elif self._texture_type == TextureType.MONOPHONIC:
assert len(self._open_notes) <= 1
if msg.type not in ['note_on', 'note_off']:
self._outport.send(msg)
elif ((msg.type == 'note_off' or
msg.type == 'note_on' and msg.velocity == 0) and
msg.note in self._open_notes):
self._outport.send(msg)
self._open_notes.remove(msg.note)
elif msg.type == 'note_on' and msg.velocity > 0:
if self._open_notes:
self._outport.send(
mido.Message('note_off', note=self._open_notes.pop()))
self._outport.send(msg)
self._open_notes.add(msg.note) | [
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] | https://github.com/magenta/magenta/blob/be6558f1a06984faff6d6949234f5fe9ad0ffdb5/magenta/interfaces/midi/midi_hub.py#L973-L1036 |
||
open-mmlab/mmsegmentation | af9ccd3d47fda8c7b50eee3675072692e3e54da5 | mmseg/models/losses/lovasz_loss.py | python | lovasz_grad | (gt_sorted) | return jaccard | Computes gradient of the Lovasz extension w.r.t sorted errors.
See Alg. 1 in paper. | Computes gradient of the Lovasz extension w.r.t sorted errors. | [
"Computes",
"gradient",
"of",
"the",
"Lovasz",
"extension",
"w",
".",
"r",
".",
"t",
"sorted",
"errors",
"."
] | def lovasz_grad(gt_sorted):
"""Computes gradient of the Lovasz extension w.r.t sorted errors.
See Alg. 1 in paper.
"""
p = len(gt_sorted)
gts = gt_sorted.sum()
intersection = gts - gt_sorted.float().cumsum(0)
union = gts + (1 - gt_sorted).float().cumsum(0)
jaccard = 1. - intersection / union
if p > 1: # cover 1-pixel case
jaccard[1:p] = jaccard[1:p] - jaccard[0:-1]
return jaccard | [
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|
lisa-lab/pylearn2 | af81e5c362f0df4df85c3e54e23b2adeec026055 | pylearn2/training_algorithms/sgd.py | python | LinearDecayOverEpoch.on_monitor | (self, model, dataset, algorithm) | Updates the learning rate based on the linear decay schedule.
Parameters
----------
model : a Model instance
dataset : Dataset
algorithm : WRITEME | Updates the learning rate based on the linear decay schedule. | [
"Updates",
"the",
"learning",
"rate",
"based",
"on",
"the",
"linear",
"decay",
"schedule",
"."
] | def on_monitor(self, model, dataset, algorithm):
"""
Updates the learning rate based on the linear decay schedule.
Parameters
----------
model : a Model instance
dataset : Dataset
algorithm : WRITEME
"""
self._count += 1
self._apply_learning_rate(algorithm) | [
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||
openstack/keystone | 771c943ad2116193e7bb118c74993c829d93bd71 | keystone/server/flask/common.py | python | ResourceBase.query_filter_is_true | (filter_name) | return val | Determine if bool query param is 'True'.
We treat this the same way as we do for policy
enforcement:
{bool_param}=0 is treated as False
Any other value is considered to be equivalent to
True, including the absence of a value (but existence
as a parameter).
False Examples for param named `p`:
* http://host/url
* http://host/url?p=0
All other forms of the param 'p' would be result in a True value
including: `http://host/url?param`. | Determine if bool query param is 'True'. | [
"Determine",
"if",
"bool",
"query",
"param",
"is",
"True",
"."
] | def query_filter_is_true(filter_name):
"""Determine if bool query param is 'True'.
We treat this the same way as we do for policy
enforcement:
{bool_param}=0 is treated as False
Any other value is considered to be equivalent to
True, including the absence of a value (but existence
as a parameter).
False Examples for param named `p`:
* http://host/url
* http://host/url?p=0
All other forms of the param 'p' would be result in a True value
including: `http://host/url?param`.
"""
val = False
if filter_name in flask.request.args:
filter_value = flask.request.args.get(filter_name)
if (isinstance(filter_value, str) and
filter_value == '0'):
val = False
else:
val = True
return val | [
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|
GluuFederation/community-edition-setup | d0c9427ed9e3ea3d95691677b73c1402ed9ca4db | setup_app/pylib/ldif4/ldif.py | python | LDIFWriter.unparse | (self, dn, record) | Write an entry or change record to the output file.
:type dn: string
:param dn: distinguished name
:type record: Union[Dict[string, List[string]], List[Tuple]]
:param record: Either a dictionary holding an entry or a list of
additions (2-tuple) or modifications (3-tuple). | Write an entry or change record to the output file. | [
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] | def unparse(self, dn, record):
"""Write an entry or change record to the output file.
:type dn: string
:param dn: distinguished name
:type record: Union[Dict[string, List[string]], List[Tuple]]
:param record: Either a dictionary holding an entry or a list of
additions (2-tuple) or modifications (3-tuple).
"""
self._unparse_attr("dn", dn)
if isinstance(record, dict):
self._unparse_entry_record(record)
elif isinstance(record, list):
self._unparse_change_record(record)
else:
raise ValueError("Argument record must be dictionary or list")
self._output_file.write(self._line_sep)
self.records_written += 1 | [
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||
PowerScript/KatanaFramework | 0f6ad90a88de865d58ec26941cb4460501e75496 | lib/future/src/future/backports/http/cookiejar.py | python | CookieJar.__len__ | (self) | return i | Return number of contained cookies. | Return number of contained cookies. | [
"Return",
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"cookies",
"."
] | def __len__(self):
"""Return number of contained cookies."""
i = 0
for cookie in self: i = i + 1
return i | [
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|
abhishekkr/gmail-helper | f3f4e586cd19a920a70d689d301e0519ed91fdb0 | _google_/gmail/__init__.py | python | delete_mail | (messages_obj, msg_id, user_id='me') | Delete a message from GMail by id.
Args:
messages_obj: Authenticated GMail user object.
msg_id: ID of Message to delete.
user_id: User's email address. The special value "me"
can be used to indicate the authenticated user. | Delete a message from GMail by id. | [
"Delete",
"a",
"message",
"from",
"GMail",
"by",
"id",
"."
] | def delete_mail(messages_obj, msg_id, user_id='me'):
"""Delete a message from GMail by id.
Args:
messages_obj: Authenticated GMail user object.
msg_id: ID of Message to delete.
user_id: User's email address. The special value "me"
can be used to indicate the authenticated user.
"""
try:
messages_obj.delete(userId=user_id, id=msg_id).execute()
_log.logger.info('Message with id: %s deleted successfully.' % msg_id)
except Exception as e:
_log.logger.error('An error occurred: %s' % str(e)) | [
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||
SpiderClub/haipproxy | ab30ccf4b1d78e9304c27830006cc5800fe41bb3 | haipproxy/scheduler/scheduler.py | python | squid_conf_update | (usage, interval) | Timertask for updating proxies for squid config file | Timertask for updating proxies for squid config file | [
"Timertask",
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] | def squid_conf_update(usage, interval):
"""Timertask for updating proxies for squid config file"""
# client_logger.info('the updating task is starting...')
client = SquidClient(usage)
client.update_conf()
schedule.every(interval).minutes.do(client.update_conf)
while True:
schedule.run_pending()
time.sleep(1) | [
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||
LabPy/lantz | 3e878e3f765a4295b0089d04e241d4beb7b8a65b | lantz/drivers/labjack/_internal/u12.py | python | U12.reEnum | (self, idNum=None) | return {"idnum":idNum.value} | Name: U12.reEnum(idNum=None)
Args: See section 4.29 of the User's Guide
Desc: Causes the LabJack to electrically detach from and re-attach to the USB so it will re-enumerate
>>> dev = U12()
>>> dev.reEnum()
>>> {'idnum': 1} | Name: U12.reEnum(idNum=None)
Args: See section 4.29 of the User's Guide
Desc: Causes the LabJack to electrically detach from and re-attach to the USB so it will re-enumerate
>>> dev = U12()
>>> dev.reEnum()
>>> {'idnum': 1} | [
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"""
Name: U12.reEnum(idNum=None)
Args: See section 4.29 of the User's Guide
Desc: Causes the LabJack to electrically detach from and re-attach to the USB so it will re-enumerate
>>> dev = U12()
>>> dev.reEnum()
>>> {'idnum': 1}
"""
#Check id number
if idNum is None:
idNum = self.id
idNum = ctypes.c_long(idNum)
ecode = staticLib.ReEnum(ctypes.byref(idNum))
if ecode != 0: raise U12Exception(ecode)
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|
lad1337/XDM | 0c1b7009fe00f06f102a6f67c793478f515e7efe | site-packages/logilab/common/table.py | python | TableWriter.set_renderer | (self, renderer) | sets the way to render cell | sets the way to render cell | [
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] | def set_renderer(self, renderer):
"""sets the way to render cell
"""
self.renderer = renderer | [
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||
ipython/traitlets | 34f596dd03b98434900a7d31c912fc168342bb80 | traitlets/config/loader.py | python | ArgParseConfigLoader.load_config | (self, argv=None, aliases=None, flags=_deprecated, classes=None) | return self.config | Parse command line arguments and return as a Config object.
Parameters
----------
argv : optional, list
If given, a list with the structure of sys.argv[1:] to parse
arguments from. If not given, the instance's self.argv attribute
(given at construction time) is used.
flags
Deprecated in traitlets 5.0, instanciate the config loader with the flags. | Parse command line arguments and return as a Config object. | [
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] | def load_config(self, argv=None, aliases=None, flags=_deprecated, classes=None):
"""Parse command line arguments and return as a Config object.
Parameters
----------
argv : optional, list
If given, a list with the structure of sys.argv[1:] to parse
arguments from. If not given, the instance's self.argv attribute
(given at construction time) is used.
flags
Deprecated in traitlets 5.0, instanciate the config loader with the flags.
"""
if flags is not _deprecated:
warnings.warn(
"The `flag` argument to load_config is deprecated since Traitlets "
f"5.0 and will be ignored, pass flags the `{type(self)}` constructor.",
DeprecationWarning,
stacklevel=2,
)
self.clear()
if argv is None:
argv = self.argv
if aliases is not None:
self.aliases = aliases
if classes is not None:
self.classes = classes
self._create_parser()
self._parse_args(argv)
self._convert_to_config()
return self.config | [
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|
buke/GreenOdoo | 3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df | source/openerp/tools/convert.py | python | convert_csv_import | (cr, module, fname, csvcontent, idref=None, mode='init',
noupdate=False) | Import csv file :
quote: "
delimiter: ,
encoding: utf-8 | Import csv file :
quote: "
delimiter: ,
encoding: utf-8 | [
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":",
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"-",
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] | def convert_csv_import(cr, module, fname, csvcontent, idref=None, mode='init',
noupdate=False):
'''Import csv file :
quote: "
delimiter: ,
encoding: utf-8'''
if not idref:
idref={}
model = ('.'.join(fname.split('.')[:-1]).split('-'))[0]
#remove folder path from model
head, model = os.path.split(model)
input = cStringIO.StringIO(csvcontent) #FIXME
reader = csv.reader(input, quotechar='"', delimiter=',')
fields = reader.next()
fname_partial = ""
if config.get('import_partial'):
fname_partial = module + '/'+ fname
if not os.path.isfile(config.get('import_partial')):
pickle.dump({}, file(config.get('import_partial'),'w+'))
else:
data = pickle.load(file(config.get('import_partial')))
if fname_partial in data:
if not data[fname_partial]:
return
else:
for i in range(data[fname_partial]):
reader.next()
if not (mode == 'init' or 'id' in fields):
_logger.error("Import specification does not contain 'id' and we are in init mode, Cannot continue.")
return
uid = 1
datas = []
for line in reader:
if not (line and any(line)):
continue
try:
datas.append(map(misc.ustr, line))
except:
_logger.error("Cannot import the line: %s", line)
registry = openerp.registry(cr.dbname)
result, rows, warning_msg, dummy = registry[model].import_data(cr, uid, fields, datas,mode, module, noupdate, filename=fname_partial)
if result < 0:
# Report failed import and abort module install
raise Exception(_('Module loading %s failed: file %s could not be processed:\n %s') % (module, fname, warning_msg))
if config.get('import_partial'):
data = pickle.load(file(config.get('import_partial')))
data[fname_partial] = 0
pickle.dump(data, file(config.get('import_partial'),'wb'))
cr.commit() | [
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||
acarabott/ChromeREPL | 009ab7884b14fb8536bf0066436cb532b1b5b43c | libs/six.py | python | _add_doc | (func, doc) | Add documentation to a function. | Add documentation to a function. | [
"Add",
"documentation",
"to",
"a",
"function",
"."
] | def _add_doc(func, doc):
"""Add documentation to a function."""
func.__doc__ = doc | [
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||
mnooner256/pyqrcode | 674a77b5eaf850d063f518bd90c243ee34ad6b5d | pyqrcode/__init__.py | python | QRCode.show | (self, wait=1.2, scale=10, module_color=(0, 0, 0, 255),
background=(255, 255, 255, 255), quiet_zone=4) | Displays this QR code.
This method is mainly intended for debugging purposes.
This method saves the output of the :py:meth:`png` method (with a default
scaling factor of 10) to a temporary file and opens it with the
standard PNG viewer application or within the standard webbrowser. The
temporary file is deleted afterwards.
If this method does not show any result, try to increase the `wait`
parameter. This parameter specifies the time in seconds to wait till
the temporary file is deleted. Note, that this method does not return
until the provided amount of seconds (default: 1.2) has passed.
The other parameters are simply passed on to the `png` method. | Displays this QR code. | [
"Displays",
"this",
"QR",
"code",
"."
] | def show(self, wait=1.2, scale=10, module_color=(0, 0, 0, 255),
background=(255, 255, 255, 255), quiet_zone=4):
"""Displays this QR code.
This method is mainly intended for debugging purposes.
This method saves the output of the :py:meth:`png` method (with a default
scaling factor of 10) to a temporary file and opens it with the
standard PNG viewer application or within the standard webbrowser. The
temporary file is deleted afterwards.
If this method does not show any result, try to increase the `wait`
parameter. This parameter specifies the time in seconds to wait till
the temporary file is deleted. Note, that this method does not return
until the provided amount of seconds (default: 1.2) has passed.
The other parameters are simply passed on to the `png` method.
"""
import os
import time
import tempfile
import webbrowser
try: # Python 2
from urlparse import urljoin
from urllib import pathname2url
except ImportError: # Python 3
from urllib.parse import urljoin
from urllib.request import pathname2url
f = tempfile.NamedTemporaryFile('wb', suffix='.png', delete=False)
self.png(f, scale=scale, module_color=module_color,
background=background, quiet_zone=quiet_zone)
f.close()
webbrowser.open_new_tab(urljoin('file:', pathname2url(f.name)))
time.sleep(wait)
os.unlink(f.name) | [
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] | https://github.com/mnooner256/pyqrcode/blob/674a77b5eaf850d063f518bd90c243ee34ad6b5d/pyqrcode/__init__.py#L353-L389 |
||
openstack/neutron | fb229fb527ac8b95526412f7762d90826ac41428 | neutron/services/network_ip_availability/plugin.py | python | NetworkIPAvailabilityPlugin.get_network_ip_availabilities | (self, context, filters=None,
fields=None) | return [db_utils.resource_fields(net_ip_availability, fields)
for net_ip_availability in net_ip_availabilities] | Returns ip availability data for a collection of networks. | Returns ip availability data for a collection of networks. | [
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fields=None):
"""Returns ip availability data for a collection of networks."""
net_ip_availabilities = super(
NetworkIPAvailabilityPlugin, self
).get_network_ip_availabilities(context, filters)
return [db_utils.resource_fields(net_ip_availability, fields)
for net_ip_availability in net_ip_availabilities] | [
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|
DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | gitlab/datadog_checks/gitlab/config_models/defaults.py | python | instance_aws_host | (field, value) | return get_default_field_value(field, value) | [] | def instance_aws_host(field, value):
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IronLanguages/ironpython2 | 51fdedeeda15727717fb8268a805f71b06c0b9f1 | Src/StdLib/Lib/fractions.py | python | Fraction.__neg__ | (a) | return Fraction(-a._numerator, a._denominator) | -a | -a | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/whoosh/src/whoosh/fields.py | python | Schema.scorable_names | (self) | return [name for name, field in self.items() if field.scorable] | Returns a list of the names of fields that store field
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nneonneo/ffsend | 4595be598c8397751681f1e9f2811fe716b8f420 | ffsend.py | python | FFSendAPI.get_metadata | (self, id, auth_key) | return resp | GET /api/metadata/:id
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''' GET /api/metadata/:id
id: file id
auth_key: file's auth key
The response's json will include raw encrypted file metadata.
'''
# TODO configurable retries
for i in range(5):
nonce = self._get_nonce(id)
resp = requests.get(self.baseurl + "api/metadata/" + id,
headers={'Authorization': self._auth_header(auth_key, nonce)})
self._set_nonce(id, resp)
if resp.status_code == 401:
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return resp
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lunixbochs/ActualVim | 1f555ce719e49d6584f0e35e9f0db2f216b98fa5 | lib/asyncio/selectors.py | python | _BaseSelectorImpl._fileobj_lookup | (self, fileobj) | Return a file descriptor from a file object.
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is used by unregister() so we can unregister an object that
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"""
try:
return _fileobj_to_fd(fileobj)
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nortikin/sverchok | 7b460f01317c15f2681bfa3e337c5e7346f3711b | nodes/matrix/matrix_track_to.py | python | SvMatrixTrackToNode.split_columns | (self, panel, ratios, aligns) | return cols | Splits the given panel into columns based on the given set of ratios.
e.g ratios = [1, 2, 1] or [.2, .3, .2] etc
Note: The sum of all ratio numbers doesn't need to be normalized | Splits the given panel into columns based on the given set of ratios.
e.g ratios = [1, 2, 1] or [.2, .3, .2] etc
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for n in range(ns):
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n2 = sum(ratios[n + 1:]) # size of all remaining columns
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|
naftaliharris/tauthon | 5587ceec329b75f7caf6d65a036db61ac1bae214 | Lib/threading.py | python | BoundedSemaphore | (*args, **kwargs) | return _BoundedSemaphore(*args, **kwargs) | A factory function that returns a new bounded semaphore.
A bounded semaphore checks to make sure its current value doesn't exceed its
initial value. If it does, ValueError is raised. In most situations
semaphores are used to guard resources with limited capacity.
If the semaphore is released too many times it's a sign of a bug. If not
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"""A factory function that returns a new bounded semaphore.
A bounded semaphore checks to make sure its current value doesn't exceed its
initial value. If it does, ValueError is raised. In most situations
semaphores are used to guard resources with limited capacity.
If the semaphore is released too many times it's a sign of a bug. If not
given, value defaults to 1.
Like regular semaphores, bounded semaphores manage a counter representing
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return _BoundedSemaphore(*args, **kwargs) | [
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buke/GreenOdoo | 3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df | runtime/python/lib/python2.7/decimal.py | python | Decimal.__mod__ | (self, other, context=None) | return remainder | self % other | self % other | [
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bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/min/fileinput.py | python | filelineno | () | return _state.filelineno() | Return the line number in the current file. Before the first line
has been read, returns 0. After the last line of the last file has
been read, returns the line number of that line within the file. | Return the line number in the current file. Before the first line
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if not _state:
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|
kornia/kornia | b12d6611b1c41d47b2c93675f0ea344b5314a688 | kornia/feature/loftr/utils/supervision.py | python | spvs_fine | (data, config) | Update:
data (dict):{
"expec_f_gt": [M, 2]} | Update:
data (dict):{
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Update:
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# w_pt0_i, pt1_i = data.pop('spv_w_pt0_i'), data.pop('spv_pt1_i')
w_pt0_i, pt1_i = data['spv_w_pt0_i'], data['spv_pt1_i']
scale = config['LOFTR']['RESOLUTION'][1]
radius = config['LOFTR']['FINE_WINDOW_SIZE'] // 2
# 2. get coarse prediction
b_ids, i_ids, j_ids = data['b_ids'], data['i_ids'], data['j_ids']
# 3. compute gt
scale = scale * data['scale1'][b_ids] if 'scale0' in data else scale
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expec_f_gt = (w_pt0_i[b_ids, i_ids] - pt1_i[b_ids, j_ids]) / scale / radius # [M, 2]
data.update({"expec_f_gt": expec_f_gt}) | [
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||
LMFDB/lmfdb | 6cf48a4c18a96e6298da6ae43f587f96845bcb43 | lmfdb/verify/mf_newforms.py | python | mf_newforms.check_self_twist_type | (self) | return (self.check_non_null(['is_cm', 'is_rm']) +
self.check_iff({'self_twist_type':0}, {'is_cm':False, 'is_rm':False}) +
self.check_iff({'self_twist_type':1}, {'is_cm':True, 'is_rm':False}) +
self.check_iff({'self_twist_type':2}, {'is_cm':False, 'is_rm':True}) +
self.check_iff({'self_twist_type':3}, {'is_cm':True, 'is_rm':True})) | check that self_twist_type is in {0,1,2,3} and matches is_cm and is_rm | check that self_twist_type is in {0,1,2,3} and matches is_cm and is_rm | [
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] | def check_self_twist_type(self):
"""
check that self_twist_type is in {0,1,2,3} and matches is_cm and is_rm
"""
# TIME about 6s
return (self.check_non_null(['is_cm', 'is_rm']) +
self.check_iff({'self_twist_type':0}, {'is_cm':False, 'is_rm':False}) +
self.check_iff({'self_twist_type':1}, {'is_cm':True, 'is_rm':False}) +
self.check_iff({'self_twist_type':2}, {'is_cm':False, 'is_rm':True}) +
self.check_iff({'self_twist_type':3}, {'is_cm':True, 'is_rm':True})) | [
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|
mchristopher/PokemonGo-DesktopMap | ec37575f2776ee7d64456e2a1f6b6b78830b4fe0 | app/pywin/Lib/encodings/hex_codec.py | python | hex_decode | (input,errors='strict') | return (output, len(input)) | Decodes the object input and returns a tuple (output
object, length consumed).
input must be an object which provides the bf_getreadbuf
buffer slot. Python strings, buffer objects and memory
mapped files are examples of objects providing this slot.
errors defines the error handling to apply. It defaults to
'strict' handling which is the only currently supported
error handling for this codec. | Decodes the object input and returns a tuple (output
object, length consumed). | [
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] | def hex_decode(input,errors='strict'):
""" Decodes the object input and returns a tuple (output
object, length consumed).
input must be an object which provides the bf_getreadbuf
buffer slot. Python strings, buffer objects and memory
mapped files are examples of objects providing this slot.
errors defines the error handling to apply. It defaults to
'strict' handling which is the only currently supported
error handling for this codec.
"""
assert errors == 'strict'
output = binascii.a2b_hex(input)
return (output, len(input)) | [
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|
pybuilder/pybuilder | 12ea2f54e04f97daada375dc3309a3f525f1b5e1 | src/main/python/pybuilder/_vendor/filelock/_api.py | python | BaseFileLock.is_locked | (self) | return self._lock_file_fd is not None | :return: A boolean indicating if the lock file is holding the lock currently.
.. versionchanged:: 2.0.0
This was previously a method and is now a property. | [] | def is_locked(self) -> bool:
"""
:return: A boolean indicating if the lock file is holding the lock currently.
.. versionchanged:: 2.0.0
This was previously a method and is now a property.
"""
return self._lock_file_fd is not None | [
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||
joxeankoret/diaphora | dcb5a25ac9fe23a285b657e5389cf770de7ac928 | pygments/lexer.py | python | RegexLexerMeta._process_new_state | (cls, new_state, unprocessed, processed) | Preprocess the state transition action of a token definition. | Preprocess the state transition action of a token definition. | [
"Preprocess",
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] | def _process_new_state(cls, new_state, unprocessed, processed):
"""Preprocess the state transition action of a token definition."""
if isinstance(new_state, str):
# an existing state
if new_state == '#pop':
return -1
elif new_state in unprocessed:
return (new_state,)
elif new_state == '#push':
return new_state
elif new_state[:5] == '#pop:':
return -int(new_state[5:])
else:
assert False, 'unknown new state %r' % new_state
elif isinstance(new_state, combined):
# combine a new state from existing ones
tmp_state = '_tmp_%d' % cls._tmpname
cls._tmpname += 1
itokens = []
for istate in new_state:
assert istate != new_state, 'circular state ref %r' % istate
itokens.extend(cls._process_state(unprocessed,
processed, istate))
processed[tmp_state] = itokens
return (tmp_state,)
elif isinstance(new_state, tuple):
# push more than one state
for istate in new_state:
assert (istate in unprocessed or
istate in ('#pop', '#push')), \
'unknown new state ' + istate
return new_state
else:
assert False, 'unknown new state def %r' % new_state | [
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||
reviewboard/reviewboard | 7395902e4c181bcd1d633f61105012ffb1d18e1b | reviewboard/hostingsvcs/service.py | python | HostingService.get_remote_repository | (self, repository_id) | Return the remote repository for the ID.
This method should be implemented by subclasses.
Args:
repository_id (unicode):
The repository's identifier. This is unique to each hosting
service.
Returns:
reviewboard.hostingsvcs.repository.RemoteRepository:
The remote repository.
Raises:
django.core.excptions.ObjectDoesNotExist:
If the remote repository does not exist. | Return the remote repository for the ID. | [
"Return",
"the",
"remote",
"repository",
"for",
"the",
"ID",
"."
] | def get_remote_repository(self, repository_id):
"""Return the remote repository for the ID.
This method should be implemented by subclasses.
Args:
repository_id (unicode):
The repository's identifier. This is unique to each hosting
service.
Returns:
reviewboard.hostingsvcs.repository.RemoteRepository:
The remote repository.
Raises:
django.core.excptions.ObjectDoesNotExist:
If the remote repository does not exist.
"""
raise NotImplementedError | [
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] | https://github.com/reviewboard/reviewboard/blob/7395902e4c181bcd1d633f61105012ffb1d18e1b/reviewboard/hostingsvcs/service.py#L1850-L1868 |
||
allenai/allennlp-models | b6923c362095a82829646912353425143f757143 | allennlp_models/structured_prediction/predictors/openie.py | python | join_mwp | (tags: List[str]) | return ret | Join multi-word predicates to a single
predicate ('V') token. | Join multi-word predicates to a single
predicate ('V') token. | [
"Join",
"multi",
"-",
"word",
"predicates",
"to",
"a",
"single",
"predicate",
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"V",
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"token",
"."
] | def join_mwp(tags: List[str]) -> List[str]:
"""
Join multi-word predicates to a single
predicate ('V') token.
"""
ret = []
verb_flag = False
for tag in tags:
if "V" in tag:
# Create a continuous 'V' BIO span
prefix, _ = tag.split("-", 1)
if verb_flag:
# Continue a verb label across the different predicate parts
prefix = "I"
ret.append(f"{prefix}-V")
verb_flag = True
else:
ret.append(tag)
verb_flag = False
return ret | [
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|
Alephbet/gimel | e4814f378c749b78f37a4613220d2f909bf30db2 | gimel/vendor/redis/client.py | python | StrictRedis.brpoplpush | (self, src, dst, timeout=0) | return self.execute_command('BRPOPLPUSH', src, dst, timeout) | Pop a value off the tail of ``src``, push it on the head of ``dst``
and then return it.
This command blocks until a value is in ``src`` or until ``timeout``
seconds elapse, whichever is first. A ``timeout`` value of 0 blocks
forever. | Pop a value off the tail of ``src``, push it on the head of ``dst``
and then return it. | [
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"and",
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"return",
"it",
"."
] | def brpoplpush(self, src, dst, timeout=0):
"""
Pop a value off the tail of ``src``, push it on the head of ``dst``
and then return it.
This command blocks until a value is in ``src`` or until ``timeout``
seconds elapse, whichever is first. A ``timeout`` value of 0 blocks
forever.
"""
if timeout is None:
timeout = 0
return self.execute_command('BRPOPLPUSH', src, dst, timeout) | [
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|
bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/full/encodings/cp1140.py | python | Codec.decode | (self,input,errors='strict') | return codecs.charmap_decode(input,errors,decoding_table) | [] | def decode(self,input,errors='strict'):
return codecs.charmap_decode(input,errors,decoding_table) | [
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|||
CedricGuillemet/Imogen | ee417b42747ed5b46cb11b02ef0c3630000085b3 | bin/Lib/http/cookiejar.py | python | time2netscape | (t=None) | return "%s, %02d-%s-%04d %02d:%02d:%02d GMT" % (
DAYS[dt.weekday()], dt.day, MONTHS[dt.month-1],
dt.year, dt.hour, dt.minute, dt.second) | Return a string representing time in seconds since epoch, t.
If the function is called without an argument, it will use the current
time.
The format of the returned string is like this:
Wed, DD-Mon-YYYY HH:MM:SS GMT | Return a string representing time in seconds since epoch, t. | [
"Return",
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"string",
"representing",
"time",
"in",
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"since",
"epoch",
"t",
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] | def time2netscape(t=None):
"""Return a string representing time in seconds since epoch, t.
If the function is called without an argument, it will use the current
time.
The format of the returned string is like this:
Wed, DD-Mon-YYYY HH:MM:SS GMT
"""
if t is None:
dt = datetime.datetime.utcnow()
else:
dt = datetime.datetime.utcfromtimestamp(t)
return "%s, %02d-%s-%04d %02d:%02d:%02d GMT" % (
DAYS[dt.weekday()], dt.day, MONTHS[dt.month-1],
dt.year, dt.hour, dt.minute, dt.second) | [
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|
PowerScript/KatanaFramework | 0f6ad90a88de865d58ec26941cb4460501e75496 | lib/setuptools/setuptools/command/easy_install.py | python | CommandSpec._extract_options | (orig_script) | return options.strip() | Extract any options from the first line of the script. | Extract any options from the first line of the script. | [
"Extract",
"any",
"options",
"from",
"the",
"first",
"line",
"of",
"the",
"script",
"."
] | def _extract_options(orig_script):
"""
Extract any options from the first line of the script.
"""
first = (orig_script + '\n').splitlines()[0]
match = _first_line_re().match(first)
options = match.group(1) or '' if match else ''
return options.strip() | [
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|
jython/frozen-mirror | b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99 | Lib/inspect.py | python | getargspec | (func) | return ArgSpec(args, varargs, varkw, func.func_defaults) | Get the names and default values of a function's arguments.
A tuple of four things is returned: (args, varargs, varkw, defaults).
'args' is a list of the argument names (it may contain nested lists).
'varargs' and 'varkw' are the names of the * and ** arguments or None.
'defaults' is an n-tuple of the default values of the last n arguments. | Get the names and default values of a function's arguments. | [
"Get",
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"values",
"of",
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] | def getargspec(func):
"""Get the names and default values of a function's arguments.
A tuple of four things is returned: (args, varargs, varkw, defaults).
'args' is a list of the argument names (it may contain nested lists).
'varargs' and 'varkw' are the names of the * and ** arguments or None.
'defaults' is an n-tuple of the default values of the last n arguments.
"""
if ismethod(func):
func = func.im_func
if not isfunction(func):
raise TypeError('{!r} is not a Python function'.format(func))
args, varargs, varkw = getargs(func.func_code)
return ArgSpec(args, varargs, varkw, func.func_defaults) | [
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] | https://github.com/jython/frozen-mirror/blob/b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99/Lib/inspect.py#L815-L829 |
|
SheffieldML/GPy | bb1bc5088671f9316bc92a46d356734e34c2d5c0 | GPy/core/gp.py | python | GP.save_model | (self, output_filename, compress=True, save_data=True) | [] | def save_model(self, output_filename, compress=True, save_data=True):
self._save_model(output_filename, compress=True, save_data=True) | [
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||||
PaddlePaddle/PaddleFL | 583691acd5db0a7ca331cc9a72415017b18669b8 | python/paddle_fl/paddle_fl/core/strategy/details/vars_distributed.py | python | VarDistributed.equal | (var1, var2) | return var1.name == var2.name and \
var1.type == var2.type and \
var1.shape == var2.shape and \
var1.dtype == var2.dtype and \
var1.lod_level == var2.lod_level and \
var1.persistable == var2.persistable | the two var is equal or not.
Returns:
bool: equal will return True else False | the two var is equal or not.
Returns:
bool: equal will return True else False | [
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"""
the two var is equal or not.
Returns:
bool: equal will return True else False
"""
assert isinstance(var1, VarStruct) and isinstance(var2, VarStruct)
return var1.name == var2.name and \
var1.type == var2.type and \
var1.shape == var2.shape and \
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|
great-expectations/great_expectations | 45224cb890aeae725af25905923d0dbbab2d969d | great_expectations/execution_engine/sparkdf_execution_engine.py | python | SparkDFExecutionEngine._split_on_divided_integer | (
df, column_name: str, divisor: int, batch_identifiers: dict
) | return res | Divide the values in the named column by `divisor`, and split on that | Divide the values in the named column by `divisor`, and split on that | [
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] | def _split_on_divided_integer(
df, column_name: str, divisor: int, batch_identifiers: dict
):
"""Divide the values in the named column by `divisor`, and split on that"""
matching_divisor = batch_identifiers[column_name]
res = (
df.withColumn(
"div_temp",
(F.col(column_name) / divisor).cast(sparktypes.IntegerType()),
)
.filter(F.col("div_temp") == matching_divisor)
.drop("div_temp")
)
return res | [
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|
hatRiot/zarp | 2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad | src/lib/libmproxy/flow.py | python | Request.set_url | (self, url) | return True | Parses a URL specification, and updates the Request's information
accordingly.
Returns False if the URL was invalid, True if the request succeeded. | Parses a URL specification, and updates the Request's information
accordingly. | [
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] | def set_url(self, url):
"""
Parses a URL specification, and updates the Request's information
accordingly.
Returns False if the URL was invalid, True if the request succeeded.
"""
parts = http.parse_url(url)
if not parts:
return False
self.scheme, self.host, self.port, self.path = parts
return True | [
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|
edgedb/edgedb | 872bf5abbb10f7c72df21f57635238ed27b9f280 | edb/pgsql/compiler/pathctx.py | python | _find_in_output_tuple | (
rel: pgast.Query,
path_id: irast.PathId,
aspect: str,
env: context.Environment) | return None | Try indirecting a source tuple already present as an output.
Normally tuple indirections are handled by
process_set_as_tuple_indirection, but UNIONing an explicit tuple with a
tuple coming from a base relation (like `(Foo.bar UNION (1,2)).0`)
can lead to us looking for a tuple path in relations that only have
the actual full tuple.
(See test_edgeql_coalesce_tuple_{08,09}).
We handle this by checking whether some prefix of the tuple path
is present in the path_outputs.
This is sufficient because the relevant cases are all caused by
set ops, and the "fixup" done in set op cases ensures that the
tuple will be already present. | Try indirecting a source tuple already present as an output. | [
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] | def _find_in_output_tuple(
rel: pgast.Query,
path_id: irast.PathId,
aspect: str,
env: context.Environment) -> Optional[pgast.BaseExpr]:
"""Try indirecting a source tuple already present as an output.
Normally tuple indirections are handled by
process_set_as_tuple_indirection, but UNIONing an explicit tuple with a
tuple coming from a base relation (like `(Foo.bar UNION (1,2)).0`)
can lead to us looking for a tuple path in relations that only have
the actual full tuple.
(See test_edgeql_coalesce_tuple_{08,09}).
We handle this by checking whether some prefix of the tuple path
is present in the path_outputs.
This is sufficient because the relevant cases are all caused by
set ops, and the "fixup" done in set op cases ensures that the
tuple will be already present.
"""
steps = []
src_path_id = path_id.src_path()
ptrref = path_id.rptr()
while (
src_path_id
and src_path_id.is_tuple_path()
and isinstance(ptrref, irast.TupleIndirectionPointerRef)
):
steps.append((ptrref.shortname.name, src_path_id))
if (
(var := rel.path_namespace.get((src_path_id, aspect)))
and not isinstance(var, pgast.TupleVarBase)
):
for name, src in reversed(steps):
var = astutils.tuple_getattr(var, src.target, name)
put_path_var(rel, path_id, var, aspect=aspect, env=env)
return var
ptrref = src_path_id.rptr()
src_path_id = src_path_id.src_path()
return None | [
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|
GoogleCloudPlatform/python-docs-samples | 937297c6a31bf4e598c660169d4fb6265eef565a | healthcare/api-client/v1/hl7v2/hl7v2_messages.py | python | create_hl7v2_message | (
project_id, location, dataset_id, hl7v2_store_id, hl7v2_message_file
) | return response | Creates an HL7v2 message and sends a notification to the
Cloud Pub/Sub topic.
See https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-client/v1/hl7v2
before running the sample. | Creates an HL7v2 message and sends a notification to the
Cloud Pub/Sub topic. | [
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] | def create_hl7v2_message(
project_id, location, dataset_id, hl7v2_store_id, hl7v2_message_file
):
"""Creates an HL7v2 message and sends a notification to the
Cloud Pub/Sub topic.
See https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/healthcare/api-client/v1/hl7v2
before running the sample."""
# Imports the Google API Discovery Service.
from googleapiclient import discovery
# Imports Python's built-in "json" module
import json
api_version = "v1"
service_name = "healthcare"
# Returns an authorized API client by discovering the Healthcare API
# and using GOOGLE_APPLICATION_CREDENTIALS environment variable.
client = discovery.build(service_name, api_version)
# TODO(developer): Uncomment these lines and replace with your values.
# project_id = 'my-project' # replace with your GCP project ID
# location = 'us-central1' # replace with the parent dataset's location
# dataset_id = 'my-dataset' # replace with the HL7v2 store's parent dataset ID
# hl7v2_store_id = 'my-hl7v2-store' # replace with the HL7v2 store's ID
# hl7v2_message_file = 'hl7v2-message.json' # replace with the path to the HL7v2 file
hl7v2_parent = "projects/{}/locations/{}".format(project_id, location)
hl7v2_store_name = "{}/datasets/{}/hl7V2Stores/{}".format(
hl7v2_parent, dataset_id, hl7v2_store_id
)
with open(hl7v2_message_file) as hl7v2_message:
hl7v2_message_content = json.load(hl7v2_message)
request = (
client.projects()
.locations()
.datasets()
.hl7V2Stores()
.messages()
.create(parent=hl7v2_store_name, body=hl7v2_message_content)
)
response = request.execute()
print("Created HL7v2 message from file: {}".format(hl7v2_message_file))
return response | [
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|
Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/packages/site-packages/pygments/formatters/img.py | python | FontManager.get_font | (self, bold, oblique) | Get the font based on bold and italic flags. | Get the font based on bold and italic flags. | [
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] | def get_font(self, bold, oblique):
"""
Get the font based on bold and italic flags.
"""
if bold and oblique:
return self.fonts['BOLDITALIC']
elif bold:
return self.fonts['BOLD']
elif oblique:
return self.fonts['ITALIC']
else:
return self.fonts['NORMAL'] | [
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||
charlesq34/frustum-pointnets | 2ffdd345e1fce4775ecb508d207e0ad465bcca80 | models/pointnet_util.py | python | sample_and_group_all | (xyz, points, use_xyz=True) | return new_xyz, new_points, idx, grouped_xyz | Inputs:
xyz: (batch_size, ndataset, 3) TF tensor
points: (batch_size, ndataset, channel) TF tensor, if None will just use xyz as points
use_xyz: bool, if True concat XYZ with local point features, otherwise just use point features
Outputs:
new_xyz: (batch_size, 1, 3) as (0,0,0)
new_points: (batch_size, 1, ndataset, 3+channel) TF tensor
Note:
Equivalent to sample_and_group with npoint=1, radius=inf, use (0,0,0) as the centroid | Inputs:
xyz: (batch_size, ndataset, 3) TF tensor
points: (batch_size, ndataset, channel) TF tensor, if None will just use xyz as points
use_xyz: bool, if True concat XYZ with local point features, otherwise just use point features
Outputs:
new_xyz: (batch_size, 1, 3) as (0,0,0)
new_points: (batch_size, 1, ndataset, 3+channel) TF tensor
Note:
Equivalent to sample_and_group with npoint=1, radius=inf, use (0,0,0) as the centroid | [
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'''
Inputs:
xyz: (batch_size, ndataset, 3) TF tensor
points: (batch_size, ndataset, channel) TF tensor, if None will just use xyz as points
use_xyz: bool, if True concat XYZ with local point features, otherwise just use point features
Outputs:
new_xyz: (batch_size, 1, 3) as (0,0,0)
new_points: (batch_size, 1, ndataset, 3+channel) TF tensor
Note:
Equivalent to sample_and_group with npoint=1, radius=inf, use (0,0,0) as the centroid
'''
batch_size = xyz.get_shape()[0].value
nsample = xyz.get_shape()[1].value
new_xyz = tf.constant(np.tile(np.array([0,0,0]).reshape((1,1,3)), (batch_size,1,1)),dtype=tf.float32) # (batch_size, 1, 3)
idx = tf.constant(np.tile(np.array(range(nsample)).reshape((1,1,nsample)), (batch_size,1,1)))
grouped_xyz = tf.reshape(xyz, (batch_size, 1, nsample, 3)) # (batch_size, npoint=1, nsample, 3)
if points is not None:
if use_xyz:
new_points = tf.concat([xyz, points], axis=2) # (batch_size, 16, 259)
else:
new_points = points
new_points = tf.expand_dims(new_points, 1) # (batch_size, 1, 16, 259)
else:
new_points = grouped_xyz
return new_xyz, new_points, idx, grouped_xyz | [
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|
seemoo-lab/internalblue | ba6ba0b99f835964395d6dd1b1eb7dd850398fd6 | internalblue/core.py | python | InternalBlue.fuzzLmp | (self) | return True | Installs a patch inside the sendLmp HCI handler that allows sending arbitrary
LMP payloads. Afterwards, use sendLmpPacket as before.
Basically, this ignores LM_LmpInfoTable and LM_LmpInfoTableEsc4 contents, but
only via sendLmp HCI and not during normal Link Manager operation. | Installs a patch inside the sendLmp HCI handler that allows sending arbitrary
LMP payloads. Afterwards, use sendLmpPacket as before. | [
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] | def fuzzLmp(self):
# type: ()-> bool
"""
Installs a patch inside the sendLmp HCI handler that allows sending arbitrary
LMP payloads. Afterwards, use sendLmpPacket as before.
Basically, this ignores LM_LmpInfoTable and LM_LmpInfoTableEsc4 contents, but
only via sendLmp HCI and not during normal Link Manager operation.
"""
# Check if constants are defined in fw.py
for const in [
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"FUZZLMP_ASM_CODE",
"FUZZLMP_HOOK_ADDRESS",
]:
if const not in dir(self.fw):
self.logger.warning(
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)
return False
# Assemble the snippet and write it to FUZZLMP_CODE_BASE_ADDRESS
code = asm(
self.fw.FUZZLMP_ASM_CODE,
vma=self.fw.FUZZLMP_CODE_BASE_ADDRESS,
arch="thumb",
)
self.writeMem(self.fw.FUZZLMP_CODE_BASE_ADDRESS, code)
# Install a patch in the end of the original sendLmpPdu HCI handler
patch = asm(
"b 0x%x" % self.fw.FUZZLMP_CODE_BASE_ADDRESS,
vma=self.fw.FUZZLMP_HOOK_ADDRESS,
)
if not self.patchRom(self.fw.FUZZLMP_HOOK_ADDRESS, patch):
self.logger.warning("Error writing to patchram when installing fuzzLmp patch!")
return False
return True | [
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|
lehrblogger/where-do-you-go | 51c1fb3a66d8babe00a9412c72ebbd66fe348d88 | httplib2/__init__.py | python | _parse_www_authenticate | (headers, headername='www-authenticate') | return retval | Returns a dictionary of dictionaries, one dict
per auth_scheme. | Returns a dictionary of dictionaries, one dict
per auth_scheme. | [
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] | def _parse_www_authenticate(headers, headername='www-authenticate'):
"""Returns a dictionary of dictionaries, one dict
per auth_scheme."""
retval = {}
if headers.has_key(headername):
authenticate = headers[headername].strip()
www_auth = USE_WWW_AUTH_STRICT_PARSING and WWW_AUTH_STRICT or WWW_AUTH_RELAXED
while authenticate:
# Break off the scheme at the beginning of the line
if headername == 'authentication-info':
(auth_scheme, the_rest) = ('digest', authenticate)
else:
(auth_scheme, the_rest) = authenticate.split(" ", 1)
# Now loop over all the key value pairs that come after the scheme,
# being careful not to roll into the next scheme
match = www_auth.search(the_rest)
auth_params = {}
while match:
if match and len(match.groups()) == 3:
(key, value, the_rest) = match.groups()
auth_params[key.lower()] = UNQUOTE_PAIRS.sub(r'\1', value) # '\\'.join([x.replace('\\', '') for x in value.split('\\\\')])
match = www_auth.search(the_rest)
retval[auth_scheme.lower()] = auth_params
authenticate = the_rest.strip()
return retval | [
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|
census-instrumentation/opencensus-python | 15c122dd7e0187b35f956f5d3b77b78455a2aadb | opencensus/tags/validation.py | python | is_valid_tag_value | (value) | return is_legal_chars(value) if len(value) <= 255 else False | Checks if the value is valid
:type value: str
:param value: the value to be checked
:rtype: bool
:returns: True if valid, if not, False. | Checks if the value is valid | [
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"if",
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] | def is_valid_tag_value(value):
"""Checks if the value is valid
:type value: str
:param value: the value to be checked
:rtype: bool
:returns: True if valid, if not, False.
"""
return is_legal_chars(value) if len(value) <= 255 else False | [
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|
mouna99/dien | 1f314d16aa1700ee02777e6163fb8ca94e3d2810 | script/utils.py | python | VecAttGRUCell.state_size | (self) | return self._num_units | [] | def state_size(self):
return self._num_units | [
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|||
mesalock-linux/mesapy | ed546d59a21b36feb93e2309d5c6b75aa0ad95c9 | lib-python/2.7/xml/dom/minidom.py | python | ElementInfo.isId | (self, aname) | return False | Returns true iff the named attribute is a DTD-style ID. | Returns true iff the named attribute is a DTD-style ID. | [
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"""Returns true iff the named attribute is a DTD-style ID."""
return False | [
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|
gwastro/pycbc | 1e1c85534b9dba8488ce42df693230317ca63dea | pycbc/distributions/mass.py | python | QfromUniformMass1Mass2._pdf | (self, **kwargs) | Returns the pdf at the given values. The keyword arguments must
contain all of parameters in self's params. Unrecognized arguments are
ignored. | Returns the pdf at the given values. The keyword arguments must
contain all of parameters in self's params. Unrecognized arguments are
ignored. | [
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"""Returns the pdf at the given values. The keyword arguments must
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"""
for p in self._params:
if p not in kwargs.keys():
raise ValueError(
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if kwargs in self:
pdf = self._norm * \
numpy.prod([(1.+kwargs[p])**(2./5)/kwargs[p]**(6./5)
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return float(pdf)
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||
chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/pandas/tools/plotting.py | python | SeriesPlotMethods.hist | (self, bins=10, **kwds) | return self(kind='hist', bins=bins, **kwds) | Histogram
.. versionadded:: 0.17.0
Parameters
----------
bins: integer, default 10
Number of histogram bins to be used
**kwds : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Returns
-------
axes : matplotlib.AxesSubplot or np.array of them | Histogram | [
"Histogram"
] | def hist(self, bins=10, **kwds):
"""
Histogram
.. versionadded:: 0.17.0
Parameters
----------
bins: integer, default 10
Number of histogram bins to be used
**kwds : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Returns
-------
axes : matplotlib.AxesSubplot or np.array of them
"""
return self(kind='hist', bins=bins, **kwds) | [
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|
googlearchive/appengine-flask-skeleton | 8c25461d003a0bd99a9ff3b339c2791ee6919242 | lib/werkzeug/http.py | python | remove_entity_headers | (headers, allowed=('expires', 'content-location')) | Remove all entity headers from a list or :class:`Headers` object. This
operation works in-place. `Expires` and `Content-Location` headers are
by default not removed. The reason for this is :rfc:`2616` section
10.3.5 which specifies some entity headers that should be sent.
.. versionchanged:: 0.5
added `allowed` parameter.
:param headers: a list or :class:`Headers` object.
:param allowed: a list of headers that should still be allowed even though
they are entity headers. | Remove all entity headers from a list or :class:`Headers` object. This
operation works in-place. `Expires` and `Content-Location` headers are
by default not removed. The reason for this is :rfc:`2616` section
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"""Remove all entity headers from a list or :class:`Headers` object. This
operation works in-place. `Expires` and `Content-Location` headers are
by default not removed. The reason for this is :rfc:`2616` section
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"""
allowed = set(x.lower() for x in allowed)
headers[:] = [(key, value) for key, value in headers if
not is_entity_header(key) or key.lower() in allowed] | [
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||
google-research/language | 61fa7260ac7d690d11ef72ca863e45a37c0bdc80 | language/question_answering/bert_joint/run_nq.py | python | convert_examples_to_features | (examples, tokenizer, is_training, output_fn) | return num_spans_to_ids | Converts a list of NqExamples into InputFeatures. | Converts a list of NqExamples into InputFeatures. | [
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] | def convert_examples_to_features(examples, tokenizer, is_training, output_fn):
"""Converts a list of NqExamples into InputFeatures."""
num_spans_to_ids = collections.defaultdict(list)
for example in examples:
example_index = example.example_id
features = convert_single_example(example, tokenizer, is_training)
num_spans_to_ids[len(features)].append(example.qas_id)
for feature in features:
feature.example_index = example_index
feature.unique_id = feature.example_index + feature.doc_span_index
output_fn(feature)
return num_spans_to_ids | [
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tomplus/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | kubernetes_asyncio/client/models/v1_limit_range_list.py | python | V1LimitRangeList.items | (self, items) | Sets the items of this V1LimitRangeList.
Items is a list of LimitRange objects. More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/ # noqa: E501
:param items: The items of this V1LimitRangeList. # noqa: E501
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"""Sets the items of this V1LimitRangeList.
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:param items: The items of this V1LimitRangeList. # noqa: E501
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if self.local_vars_configuration.client_side_validation and items is None: # noqa: E501
raise ValueError("Invalid value for `items`, must not be `None`") # noqa: E501
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googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v7/services/services/feed_placeholder_view_service/client.py | python | FeedPlaceholderViewServiceClient.feed_placeholder_view_path | (
customer_id: str, placeholder_type: str,
) | return "customers/{customer_id}/feedPlaceholderViews/{placeholder_type}".format(
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