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value | identifier stringlengths 1 140 | parameters stringlengths 0 87.7k | argument_list stringclasses 1
value | return_statement stringlengths 0 426k | docstring stringlengths 0 64.3k | docstring_summary stringlengths 0 26.3k | docstring_tokens list | function stringlengths 18 4.83M | function_tokens list | url stringlengths 83 304 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
arviz-devs/arviz | 17b1a48b577ba9776a31e7e57a8a8af63e826901 | arviz/plots/backends/bokeh/densityplot.py | python | plot_density | (
ax,
all_labels,
to_plot,
colors,
bw,
circular,
figsize,
length_plotters,
rows,
cols,
textsize,
labeller,
hdi_prob,
point_estimate,
hdi_markers,
outline,
shade,
n_data,
data_labels,
backend_kwargs,
show,
) | return ax | Bokeh density plot. | Bokeh density plot. | [
"Bokeh",
"density",
"plot",
"."
] | def plot_density(
ax,
all_labels,
to_plot,
colors,
bw,
circular,
figsize,
length_plotters,
rows,
cols,
textsize,
labeller,
hdi_prob,
point_estimate,
hdi_markers,
outline,
shade,
n_data,
data_labels,
backend_kwargs,
show,
):
"""Bokeh density plot."""
if backend_kwargs is None:
backend_kwargs = {}
backend_kwargs = {
**backend_kwarg_defaults(),
**backend_kwargs,
}
if colors == "cycle":
colors = [
prop
for _, prop in zip(
range(n_data), cycle(plt.rcParams["axes.prop_cycle"].by_key()["color"])
)
]
elif isinstance(colors, str):
colors = [colors for _ in range(n_data)]
colors = vectorized_to_hex(colors)
(figsize, _, _, _, line_width, markersize) = _scale_fig_size(figsize, textsize, rows, cols)
if ax is None:
ax = create_axes_grid(
length_plotters,
rows,
cols,
figsize=figsize,
squeeze=False,
backend_kwargs=backend_kwargs,
)
else:
ax = np.atleast_2d(ax)
axis_map = {
label: ax_
for label, ax_ in zip(all_labels, (item for item in ax.flatten() if item is not None))
}
if data_labels is None:
data_labels = {}
legend_items = defaultdict(list)
for m_idx, plotters in enumerate(to_plot):
for var_name, selection, isel, values in plotters:
label = labeller.make_label_vert(var_name, selection, isel)
if data_labels:
data_label = data_labels[m_idx]
else:
data_label = None
plotted = _d_helper(
values.flatten(),
label,
colors[m_idx],
bw,
circular,
line_width,
markersize,
hdi_prob,
point_estimate,
hdi_markers,
outline,
shade,
axis_map[label],
)
if data_label is not None:
legend_items[axis_map[label]].append((data_label, plotted))
for ax1, legend in legend_items.items():
legend = Legend(
items=legend,
location="center_right",
orientation="horizontal",
)
ax1.add_layout(legend, "above")
ax1.legend.click_policy = "hide"
show_layout(ax, show)
return ax | [
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androguard/androguard | 8d091cbb309c0c50bf239f805cc1e0931b8dcddc | androguard/session.py | python | Session.show | (self) | Print information to stdout about the current session.
Gets all APKs, all DEX files and all Analysis objects. | Print information to stdout about the current session.
Gets all APKs, all DEX files and all Analysis objects. | [
"Print",
"information",
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"stdout",
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".",
"Gets",
"all",
"APKs",
"all",
"DEX",
"files",
"and",
"all",
"Analysis",
"objects",
"."
] | def show(self):
"""
Print information to stdout about the current session.
Gets all APKs, all DEX files and all Analysis objects.
"""
print("APKs in Session: {}".format(len(self.analyzed_apk)))
for d, a in self.analyzed_apk.items():
print("\t{}: {}".format(d, a))
print("DEXs in Session: {}".format(len(self.analyzed_dex)))
for d, dex in self.analyzed_dex.items():
print("\t{}: {}".format(d, dex))
print("Analysis in Session: {}".format(len(self.analyzed_vms)))
for d, a in self.analyzed_vms.items():
print("\t{}: {}".format(d, a)) | [
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... | https://github.com/androguard/androguard/blob/8d091cbb309c0c50bf239f805cc1e0931b8dcddc/androguard/session.py#L166-L181 | ||
Lonero-Team/Decentralized-Internet | 3cb157834fcc19ff8c2316e66bf07b103c137068 | clusterpost/bigchaindb/bigchaindb/lib.py | python | BigchainDB.get_block | (self, block_id) | return result | Get the block with the specified `block_id`.
Returns the block corresponding to `block_id` or None if no match is
found.
Args:
block_id (int): block id of the block to get. | Get the block with the specified `block_id`. | [
"Get",
"the",
"block",
"with",
"the",
"specified",
"block_id",
"."
] | def get_block(self, block_id):
"""Get the block with the specified `block_id`.
Returns the block corresponding to `block_id` or None if no match is
found.
Args:
block_id (int): block id of the block to get.
"""
block = backend.query.get_block(self.connection, block_id)
latest_block = self.get_latest_block()
latest_block_height = latest_block['height'] if latest_block else 0
if not block and block_id > latest_block_height:
return
result = {'height': block_id,
'transactions': []}
if block:
transactions = backend.query.get_transactions(self.connection, block['transactions'])
result['transactions'] = [t.to_dict() for t in Transaction.from_db(self, transactions)]
return result | [
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tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-windows/x86/ldap3/core/connection.py | python | Connection.search | (self,
search_base,
search_filter,
search_scope=SUBTREE,
dereference_aliases=DEREF_ALWAYS,
attributes=None,
size_limit=0,
time_limit=0,
types_only=False,
get_operational_attributes=False,
controls=None,
paged_size=None,
paged_criticality=False,
paged_cookie=None,
auto_escape=None) | Perform an ldap search:
- If attributes is empty noRFC2696 with the specified size
- If paged is 0 and cookie is present the search is abandoned on
server attribute is returned
- If attributes is ALL_ATTRIBUTES all attributes are returned
- If paged_size is an int greater than 0 a simple paged search
is tried as described in
- Cookie is an opaque string received in the last paged search
and must be used on the next paged search response
- If lazy == True open and bind will be deferred until another
LDAP operation is performed
- If mssing_attributes == True then an attribute not returned by the server is set to None
- If auto_escape is set it overrides the Connection auto_escape | Perform an ldap search: | [
"Perform",
"an",
"ldap",
"search",
":"
] | def search(self,
search_base,
search_filter,
search_scope=SUBTREE,
dereference_aliases=DEREF_ALWAYS,
attributes=None,
size_limit=0,
time_limit=0,
types_only=False,
get_operational_attributes=False,
controls=None,
paged_size=None,
paged_criticality=False,
paged_cookie=None,
auto_escape=None):
"""
Perform an ldap search:
- If attributes is empty noRFC2696 with the specified size
- If paged is 0 and cookie is present the search is abandoned on
server attribute is returned
- If attributes is ALL_ATTRIBUTES all attributes are returned
- If paged_size is an int greater than 0 a simple paged search
is tried as described in
- Cookie is an opaque string received in the last paged search
and must be used on the next paged search response
- If lazy == True open and bind will be deferred until another
LDAP operation is performed
- If mssing_attributes == True then an attribute not returned by the server is set to None
- If auto_escape is set it overrides the Connection auto_escape
"""
conf_attributes_excluded_from_check = [v.lower() for v in get_config_parameter('ATTRIBUTES_EXCLUDED_FROM_CHECK')]
if log_enabled(BASIC):
log(BASIC, 'start SEARCH operation via <%s>', self)
if self.check_names and search_base:
search_base = safe_dn(search_base)
if log_enabled(EXTENDED):
log(EXTENDED, 'search base sanitized to <%s> for SEARCH operation via <%s>', search_base, self)
with self.connection_lock:
self._fire_deferred()
if not attributes:
attributes = [NO_ATTRIBUTES]
elif attributes == ALL_ATTRIBUTES:
attributes = [ALL_ATTRIBUTES]
if isinstance(attributes, STRING_TYPES):
attributes = [attributes]
if get_operational_attributes and isinstance(attributes, list):
attributes.append(ALL_OPERATIONAL_ATTRIBUTES)
elif get_operational_attributes and isinstance(attributes, tuple):
attributes += (ALL_OPERATIONAL_ATTRIBUTES, ) # concatenate tuple
if isinstance(paged_size, int):
if log_enabled(PROTOCOL):
log(PROTOCOL, 'performing paged search for %d items with cookie <%s> for <%s>', paged_size, escape_bytes(paged_cookie), self)
if controls is None:
controls = []
else:
# Copy the controls to prevent modifying the original object
controls = list(controls)
controls.append(paged_search_control(paged_criticality, paged_size, paged_cookie))
if self.server and self.server.schema and self.check_names:
for attribute_name in attributes:
if ';' in attribute_name: # remove tags
attribute_name_to_check = attribute_name.split(';')[0]
else:
attribute_name_to_check = attribute_name
if self.server.schema and attribute_name_to_check.lower() not in conf_attributes_excluded_from_check and attribute_name_to_check not in self.server.schema.attribute_types:
raise LDAPAttributeError('invalid attribute type ' + attribute_name_to_check)
request = search_operation(search_base,
search_filter,
search_scope,
dereference_aliases,
attributes,
size_limit,
time_limit,
types_only,
self.auto_escape if auto_escape is None else auto_escape,
self.auto_encode,
self.server.schema if self.server else None,
validator=self.server.custom_validator,
check_names=self.check_names)
if log_enabled(PROTOCOL):
log(PROTOCOL, 'SEARCH request <%s> sent via <%s>', search_request_to_dict(request), self)
response = self.post_send_search(self.send('searchRequest', request, controls))
self._entries = []
if isinstance(response, int): # asynchronous strategy
return_value = response
if log_enabled(PROTOCOL):
log(PROTOCOL, 'async SEARCH response id <%s> received via <%s>', return_value, self)
else:
return_value = True if self.result['type'] == 'searchResDone' and len(response) > 0 else False
if not return_value and self.result['result'] not in [RESULT_SUCCESS] and not self.last_error:
self.last_error = self.result['description']
if log_enabled(PROTOCOL):
for entry in response:
if entry['type'] == 'searchResEntry':
log(PROTOCOL, 'SEARCH response entry <%s> received via <%s>', entry, self)
elif entry['type'] == 'searchResRef':
log(PROTOCOL, 'SEARCH response reference <%s> received via <%s>', entry, self)
if log_enabled(BASIC):
log(BASIC, 'done SEARCH operation, result <%s>', return_value)
return return_value | [
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fluentpython/notebooks | 0f6e1e8d1686743dacd9281df7c5b5921812010a | 18-asyncio/spinner_thread.py | python | slow_function | () | return 42 | [] | def slow_function(): # <7>
# pretend waiting a long time for I/O
time.sleep(3) # <8>
return 42 | [
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] | https://github.com/fluentpython/notebooks/blob/0f6e1e8d1686743dacd9281df7c5b5921812010a/18-asyncio/spinner_thread.py#L31-L34 | |||
Sense-X/TSD | fb1fdd7f14f3c136f4b849914977fae1d8d49398 | mmdet/ops/roi_align/roi_align.py | python | RoIAlign.forward | (self, features, rois) | Args:
features: NCHW images
rois: Bx5 boxes. First column is the index into N. The other 4
columns are xyxy. | Args:
features: NCHW images
rois: Bx5 boxes. First column is the index into N. The other 4
columns are xyxy. | [
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":",
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"NCHW",
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"into",
"N",
".",
"The",
"other",
"4",
"columns",
"are",
"xyxy",
"."
] | def forward(self, features, rois):
"""
Args:
features: NCHW images
rois: Bx5 boxes. First column is the index into N. The other 4
columns are xyxy.
"""
assert rois.dim() == 2 and rois.size(1) == 5
if self.use_torchvision:
from torchvision.ops import roi_align as tv_roi_align
return tv_roi_align(
features, rois, self.out_size, self.spatial_scale, self.sample_num
)
else:
return roi_align(
features,
rois,
self.out_size,
self.spatial_scale,
self.sample_num,
self.aligned,
) | [
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internetarchive/openlibrary | 33b9b005ecb0adeda690c67952f5ae5f1fe3a8d8 | openlibrary/core/models.py | python | User.get_loan_for | (self, ocaid) | Returns the loan object for given ocaid.
Returns None if this user hasn't borrowed the given book. | Returns the loan object for given ocaid. | [
"Returns",
"the",
"loan",
"object",
"for",
"given",
"ocaid",
"."
] | def get_loan_for(self, ocaid):
"""Returns the loan object for given ocaid.
Returns None if this user hasn't borrowed the given book.
"""
from ..plugins.upstream import borrow
loans = borrow.get_loans(self)
for loan in loans:
if ocaid == loan['ocaid']:
return loan | [
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biolab/orange3 | 41685e1c7b1d1babe680113685a2d44bcc9fec0b | Orange/widgets/visualize/owpythagorastree.py | python | OWPythagorasTree.invalidate_tree | (self) | When the tree needs to be completely recalculated. | When the tree needs to be completely recalculated. | [
"When",
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"tree",
"needs",
"to",
"be",
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"recalculated",
"."
] | def invalidate_tree(self):
"""When the tree needs to be completely recalculated."""
if self.model is not None:
self.ptree.set_tree(
self.tree_adapter,
weight_adjustment=self.SIZE_CALCULATION[self.size_calc_idx][1],
target_class_index=self.target_class_index,
)
self.ptree.set_depth_limit(self.depth_limit)
self._update_main_area() | [
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jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/venv/lib/python3.7/site-packages/pip/_internal/req/req_file.py | python | join_lines | (lines_enum) | Joins a line ending in '\' with the previous line (except when following
comments). The joined line takes on the index of the first line. | Joins a line ending in '\' with the previous line (except when following
comments). The joined line takes on the index of the first line. | [
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"."
] | def join_lines(lines_enum):
# type: (ReqFileLines) -> ReqFileLines
"""Joins a line ending in '\' with the previous line (except when following
comments). The joined line takes on the index of the first line.
"""
primary_line_number = None
new_line = [] # type: List[Text]
for line_number, line in lines_enum:
if not line.endswith('\\') or COMMENT_RE.match(line):
if COMMENT_RE.match(line):
# this ensures comments are always matched later
line = ' ' + line
if new_line:
new_line.append(line)
yield primary_line_number, ''.join(new_line)
new_line = []
else:
yield line_number, line
else:
if not new_line:
primary_line_number = line_number
new_line.append(line.strip('\\'))
# last line contains \
if new_line:
yield primary_line_number, ''.join(new_line) | [
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pymedusa/Medusa | 1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38 | medusa/providers/torrent/html/nordicbits.py | python | NordicBitsProvider.__init__ | (self) | Initialize the class. | Initialize the class. | [
"Initialize",
"the",
"class",
"."
] | def __init__(self):
"""Initialize the class."""
super(NordicBitsProvider, self).__init__('NordicBits')
# Credentials
self.username = None
self.password = None
# URLs
self.url = 'https://nordicb.org'
self.urls = {
'login': urljoin(self.url, 'takelogin.php'),
'search': urljoin(self.url, 'browse.php'),
}
# Proper Strings
self.proper_strings = ['PROPER', 'REPACK', 'REAL', 'RERIP']
# Miscellaneous Options
self.freeleech = False
# Cache
self.cache = tv.Cache(self) | [
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TalwalkarLab/leaf | 09ec454a5675e32e1f0546b456b77857fdece018 | models/server.py | python | Server.update_model | (self) | [] | def update_model(self):
total_weight = 0.
base = [0] * len(self.updates[0][1])
for (client_samples, client_model) in self.updates:
total_weight += client_samples
for i, v in enumerate(client_model):
base[i] += (client_samples * v.astype(np.float64))
averaged_soln = [v / total_weight for v in base]
self.model = averaged_soln
self.updates = [] | [
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SteveDoyle2/pyNastran | eda651ac2d4883d95a34951f8a002ff94f642a1a | pyNastran/op2/tables/oes_stressStrain/random/oes_solids.py | python | RandomSolidArray.build | (self) | sizes the vectorized attributes of the RealSolidArray | sizes the vectorized attributes of the RealSolidArray | [
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"""sizes the vectorized attributes of the RealSolidArray"""
#print('ntimes=%s nelements=%s ntotal=%s' % (self.ntimes, self.nelements, self.ntotal))
assert self.ntimes > 0, 'ntimes=%s' % self.ntimes
assert self.nelements > 0, 'nelements=%s' % self.nelements
assert self.ntotal > 0, 'ntotal=%s' % self.ntotal
#self.names = []
self.nelements //= self.ntimes
self.itime = 0
self.ielement = 0
self.itotal = 0
#self.ntimes = 0
#self.nelements = 0
#print("ntimes=%s nelements=%s ntotal=%s" % (self.ntimes, self.nelements, self.ntotal))
dtype, idtype, fdtype = get_times_dtype(self.nonlinear_factor, self.size, self.analysis_fmt)
if self.is_sort1:
ntimes = self.ntimes
nelements = self.nelements
ntotal = self.ntotal
else:
nelements = self.ntimes
ntimes = self.nelements
ntotal = self.ntotal
dtype = self._get_analysis_code_dtype()
self._times = zeros(ntimes, dtype=dtype)
# TODO: could be more efficient by using nelements for cid
self.element_node = zeros((ntotal, 2), dtype='int32')
self.element_cid = zeros((nelements, 2), dtype='int32')
#if self.element_name == 'CTETRA':
#nnodes = 4
#elif self.element_name == 'CPENTA':
#nnodes = 6
#elif self.element_name == 'CHEXA':
#nnodes = 8
#self.element_node = zeros((self.ntotal, nnodes, 2), 'int32')
#[oxx, oyy, ozz, txy, tyz, txz]
self.data = zeros((self.ntimes, self.ntotal, 6), 'float32')
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shunyaoshih/TPA-LSTM | 598cfc90f778856084f0ca80b463894e7ea26481 | lib/model.py | python | PolyRNN._build_graph | (self) | [] | def _build_graph(self):
logging.debug("Building graph")
# rnn_inputs: [batch_size, max_len, input_size]
# rnn_inputs_len: [batch_size]
# target_outputs: [batch_size, max_len, output_size]
self.rnn_inputs, self.rnn_inputs_len, self.target_outputs = self.data_generator.inputs(
self.para.mode, self.para.batch_size)
# rnn_inputs_embed: [batch_size, max_len, num_units]
self.rnn_inputs_embed = tf.nn.relu(
dense(self.rnn_inputs, self.para.num_units))
# all_rnn_states: [batch_size, max_len, num_units]
# final_rnn_states: [LSTMStateTuple], len = num_layers
# LSTMStateTuple: (c: [batch_size, num_units],
# h: [batch_size, num_units])
self.rnn_inputs_embed = tf.unstack(self.rnn_inputs_embed, axis=1)
self.all_rnn_states, self.final_rnn_states = tf.nn.static_rnn(
cell=self._build_rnn_cell(),
inputs=self.rnn_inputs_embed,
sequence_length=self.rnn_inputs_len,
dtype=self.dtype,
)
# final_rnn_states: [batch_size, num_units]
self.final_rnn_states = tf.concat(
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1,
)
# all_rnn_outputs: [batch_size, output_size]
self.all_rnn_outputs = dense(self.final_rnn_states,
self.para.output_size)
if self.para.highway > 0:
reg_outputs = tf.transpose(
self.rnn_inputs[:, -self.para.highway:, :], [0, 2, 1])
reg_outputs = dense(reg_outputs, 1)
self.all_rnn_outputs += tf.squeeze(reg_outputs)
if self.para.mode == "train" or self.para.mode == "validation":
self.labels = self.target_outputs[:, self.para.max_len - 1, :]
self.loss = self._compute_loss(
outputs=self.all_rnn_outputs, labels=self.labels)
elif self.para.mode == "test":
self.labels = self.target_outputs[:, self.para.max_len - 1, :]
if not self.para.mts:
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kamalgill/flask-appengine-template | 11760f83faccbb0d0afe416fc58e67ecfb4643c2 | src/lib/flask/app.py | python | Flask.handle_http_exception | (self, e) | return handler(e) | Handles an HTTP exception. By default this will invoke the
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.. versionadded:: 0.3
"""
# Proxy exceptions don't have error codes. We want to always return
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Robot-Will/Stino | a94831cd1bf40a59587a7b6cc2e9b5c4306b1bf2 | libs/serial/serialwin32.py | python | Serial._update_dtr_state | (self) | Set terminal status line: Data Terminal Ready | Set terminal status line: Data Terminal Ready | [
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Lapis-Hong/wide_deep | 19d4b03daffc0778fa60f9b10ff6844c559dc126 | python/train.py | python | dynamic_train | (model) | Dynamic train mode.
For example:
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train mode:
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then keep training take 0302 as train data, 0303 as test data ... | Dynamic train mode.
For example:
train_data_files: [0301, 0302, 0303, ...]
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"""Dynamic train mode.
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train mode:
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then keep training take 0302 as train data, 0303 as test data ...
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data_files.sort()
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train_data = data_files[i]
test_data = data_files[i+1]
tf.logging.info('=' * 30 + ' START TRAINING DATA: {} '.format(train_data) + '=' * 30 + '\n')
for n in range(FLAGS.train_epochs):
t0 = time.time()
tf.logging.info('START TRAIN DATA <{}> <EPOCH {}>'.format(train_data, n + 1))
model.train(
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max_steps=None,
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tf.logging.info('FINISH TRAIN DATA <{}> <EPOCH {}> take {} mins'.format(train_data, n + 1, elapse_time(t0)))
print('-' * 80)
tf.logging.info('START EVALUATE TEST DATA <{}> <EPOCH {}>'.format(test_data, n + 1))
t0 = time.time()
results = model.evaluate(
input_fn=lambda: input_fn(test_data, FLAGS.image_eval_data, 'eval', FLAGS.batch_size),
steps=None, # Number of steps for which to evaluate model.
hooks=None,
checkpoint_path=None, # latest checkpoint in model_dir is used.
name=None)
tf.logging.info('FINISH EVALUATE TEST DATA <{}> <EPOCH {}>: take {} mins'.format(test_data, n + 1, elapse_time(t0)))
print('-' * 80)
# Display evaluation metrics
for key in sorted(results):
print('{}: {}'.format(key, results[key])) | [
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/notify/v1/service/binding.py | python | BindingList.list | (self, start_date=values.unset, end_date=values.unset,
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"""
Lists BindingInstance records from the API as a list.
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:param date start_date: Only include usage that has occurred on or after this date
:param date end_date: Only include usage that occurred on or before this date
:param list[unicode] identity: The `identity` value of the resources to read
:param list[unicode] tag: Only list Bindings that have all of the specified Tags
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:rtype: list[twilio.rest.notify.v1.service.binding.BindingInstance]
"""
return list(self.stream(
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end_date=end_date,
identity=identity,
tag=tag,
limit=limit,
page_size=page_size,
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/common/mutagen/_file.py | python | FileType.mime | (self) | return mimes | A list of mime types (:class:`mutagen.text`) | A list of mime types (:class:`mutagen.text`) | [
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KhronosGroup/NNEF-Tools | c913758ca687dab8cb7b49e8f1556819a2d0ca25 | nnef_tools/io/tf/lite/writer.py | python | _ensure_numpy_array | (x, dtype) | [] | def _ensure_numpy_array(x, dtype):
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/pip/_vendor/pyparsing.py | python | ZeroOrMore.__init__ | ( self, expr, stopOn=None) | [] | def __init__( self, expr, stopOn=None):
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demisto/content | 5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07 | Packs/Lacework/Integrations/Lacework/Lacework.py | python | create_entry | (title, data, ec, human_readable=None) | return {
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'Contents': data,
'ReadableContentsFormat': formats['markdown'],
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'EntryContext': ec
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return {
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mehulj94/BrainDamage | 49a29c2606d5f7c0d9705ae5f4201a6bb25cfe73 | eclipse.py | python | help | () | [] | def help():
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gusibi/python-weixin | db997152673b205966146b6aab304ba6e4755bec | weixin/helper.py | python | smart_bytes | (s, encoding="utf-8", strings_only=False, errors="strict") | return force_bytes(s, encoding, strings_only, errors) | Returns a bytestring version of 's', encoded as specified in 'encoding'.
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/forms/widgets.py | python | Select.use_required_attribute | (self, initial) | return use_required_attribute and first_choice is not None and self._choice_has_empty_value(first_choice) | Don't render 'required' if the first <option> has a value, as that's
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google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/client/grr_response_client/comms.py | python | ClientCommunicator.InitPrivateKey | (self) | return key | Makes sure this client has a private key set.
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"""
if self.private_key:
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self.common_name = rdf_client.ClientURN.FromPrivateKey(self.private_key)
logging.info("Starting client %s", self.common_name)
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key = rdf_crypto.RSAPrivateKey.GenerateKey(
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self.common_name = rdf_client.ClientURN.FromPrivateKey(key)
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jopohl/urh | 9a7836698b8156687c0ed2d16f56d653cb847c22 | src/urh/controller/dialogs/ProjectDialog.py | python | ProjectDialog.participants | (self) | return self.participant_table_model.participants | :rtype: list of Participant | [] | def participants(self):
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KalleHallden/AutoTimer | 2d954216700c4930baa154e28dbddc34609af7ce | env/lib/python2.7/site-packages/objc/_properties.py | python | set_proxy.remove | (self, item) | [] | def remove(self, item):
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | win32_event_log/datadog_checks/win32_event_log/legacy/win32_event_log.py | python | Win32EventLogWMI.__init__ | (self, name, init_config, instances) | [] | def __init__(self, name, init_config, instances):
super(Win32EventLogWMI, self).__init__(name, init_config, instances)
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self._tag_event_id = is_affirmative(self.instance.get('tag_event_id', init_config.get('tag_event_id')))
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self._default_event_priority = init_config.get('default_event_priority', 'normal')
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self.last_ts = {}
self.check_initializations.append(
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santhoshkolloju/Abstractive-Summarization-With-Transfer-Learning | 97ff2ae3ba9f2d478e174444c4e0f5349f28c319 | texar_repo/examples/transformer/bleu_tool.py | python | bleu_tokenize | (string) | return string.split() | r"""Tokenize a string following the official BLEU implementation.
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string: the input string
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string = uregex.symbol_re.sub(r" \1 ", string)
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/idlelib/RemoteDebugger.py | python | IdbAdapter.frame_globals | (self, fid) | return did | [] | def frame_globals(self, fid):
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uqfoundation/multiprocess | 028cc73f02655e6451d92e5147d19d8c10aebe50 | py3.11/multiprocess/context.py | python | BaseContext.reducer | (self) | return globals().get('reduction') | Controls how objects will be reduced to a form that can be
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PaddlePaddle/models | 511e2e282960ed4c7440c3f1d1e62017acb90e11 | tutorials/mobilenetv3_prod/Step1-5/mobilenetv3_ref/utils.py | python | SmoothedValue.max | (self) | return max(self.deque) | [] | def max(self):
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esdalmaijer/markovbot | 24f44ba0e9ed29de374be02efeea18a9badd5394 | markovbot/markovbot35.py | python | MarkovBot._check_file | (self, filename, allowedext=None) | return ok | Checks whether a file exists, and has a certain extension.
Arguments
filename - String that indicates the path to a .txt file
that should be read by the bot.
Keyword Arguments
allowedext - List of allowed extensions, or None to allow all
extensions. Default value is None.
Returns
ok - Boolean that indicates whether the file exists,
andhas an allowed extension (True), or does not
(False) | Checks whether a file exists, and has a certain extension.
Arguments
filename - String that indicates the path to a .txt file
that should be read by the bot.
Keyword Arguments
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fab-jul/L3C-PyTorch | 469d43b74583976895923138145e0bf4436e5dc9 | src/criterion/logistic_mixture.py | python | DiscretizedMixLogisticLoss.__init__ | (self, rgb_scale: bool, x_min=0, x_max=255, L=256) | :param rgb_scale: Whether this is the loss for the RGB scale. In that case,
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super(DiscretizedMixLogisticLoss, self).__init__()
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self.x_min = x_min
self.x_max = x_max
self.L = L
# whether to use coefficients lambda to weight means depending on previously outputed means.
self.use_coeffs = rgb_scale
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self._num_params = _NUM_PARAMS_RGB if rgb_scale else _NUM_PARAMS_OTHER
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self._nonshared_coeffs_act = torch.sigmoid
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self.x_upper_bound = x_max - 0.001
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robotframework/RIDE | 6e8a50774ff33dead3a2757a11b0b4418ab205c0 | src/robotide/lib/robot/libraries/Telnet.py | python | TelnetConnection.set_prompt | (self, prompt, prompt_is_regexp=False) | return old | Sets the prompt used by `Read Until Prompt` and `Login` in the current connection.
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| `Do Something` |
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Example:
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| `Do Something` |
| `Set Prompt` | ${prompt} | ${regexp} |
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self._verify_connection()
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vsjha18/nsetools | b0e99c8decac0cba0bc19427428fd2d7b8836eaf | nse.py | python | Nse.nse_opener | (self) | return build_opener(HTTPCookieProcessor(cj)) | builds opener for urllib2
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cj = CookieJar()
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ronreiter/interactive-tutorials | d026d1ae58941863d60eb30a8a94a8650d2bd4bf | suds/sax/element.py | python | PrefixNormalizer.genPrefixes | (self) | return prefixes | Generate a I{reverse} mapping of unique prefixes for all namespaces.
@return: A referse dict of prefixes.
@rtype: {u, p} | Generate a I{reverse} mapping of unique prefixes for all namespaces. | [
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@return: A referse dict of prefixes.
@rtype: {u, p}
"""
prefixes = {}
n = 0
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openstack/cinder | 23494a6d6c51451688191e1847a458f1d3cdcaa5 | cinder/volume/drivers/dell_emc/powermax/common.py | python | PowerMaxCommon._check_and_add_tags_to_storage_array | (
self, serial_number, array_tag_list, extra_specs) | Add tags to a storage group.
:param serial_number: the array serial number
:param array_tag_list: the array tag list
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self, serial_number, array_tag_list, extra_specs):
"""Add tags to a storage group.
:param serial_number: the array serial number
:param array_tag_list: the array tag list
:param extra_specs: the extra specifications
"""
if array_tag_list:
existing_array_tags = self.rest.get_array_tags(serial_number)
new_tag_list = self.utils.get_new_tags(
self.utils.convert_list_to_string(array_tag_list),
self.utils.convert_list_to_string(existing_array_tags))
if not new_tag_list:
LOG.warning("No new tags to add. Existing tags "
"associated with %(array)s are "
"%(tags)s.",
{'array': serial_number,
'tags': existing_array_tags})
else:
self._validate_array_tag_list(new_tag_list)
LOG.info("Adding the tags %(tag_list)s to %(array)s",
{'tag_list': new_tag_list,
'array': serial_number})
try:
self.rest.add_storage_array_tags(
serial_number, new_tag_list, extra_specs)
except Exception as ex:
LOG.warning("Unexpected error: %(ex)s. If you still "
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django/django | 0a17666045de6739ae1c2ac695041823d5f827f7 | django/contrib/gis/gdal/srs.py | python | SpatialReference.projected | (self) | return bool(capi.isprojected(self.ptr)) | Return True if this SpatialReference is a projected coordinate system
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out0fmemory/GoAgent-Always-Available | c4254984fea633ce3d1893fe5901debd9f22c2a9 | server/lib/google/appengine/_internal/antlr3/recognizers.py | python | Lexer.emit | (self, token=None) | return token | The standard method called to automatically emit a token at the
outermost lexical rule. The token object should point into the
char buffer start..stop. If there is a text override in 'text',
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PyHDI/veriloggen | 2382d200deabf59cfcfd741f5eba371010aaf2bb | veriloggen/stream/stream.py | python | Stream.to_module | (self, name, clock='CLK', reset='RST', aswire=False, seq_name=None) | return m | generate a Module definion | generate a Module definion | [
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flan/staticdhcpd | 40ef788908beb9355aa06cabd5ff628a577d8595 | libpydhcpserver/libpydhcpserver/dhcp_types/conversion.py | python | ipsToList | (ips) | return output | Converts a IPv4 addresses into a flat list of multiples of four bytes in
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:param list ips: A list of any valid IPv4 formats (string, 32-bit integer,
list of bytes, :class:`IPv4 <dhcp_types.IPv4>`).
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translate/translate | 72816df696b5263abfe80ab59129b299b85ae749 | translate/storage/tmx.py | python | tmxfile.addtranslation | (self, source, srclang, translation, translang, comment=None) | addtranslation method for testing old unit tests | addtranslation method for testing old unit tests | [
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unit.target = translation
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tuvs = unit.xmlelement.iterdescendants(self.namespaced("tuv"))
setXMLlang(next(tuvs), srclang)
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nvaccess/nvda | 20d5a25dced4da34338197f0ef6546270ebca5d0 | source/visionEnhancementProviders/NVDAHighlighter.py | python | NVDAHighlighter.updateContextRect | (self, context, rect=None, obj=None) | Updates the position rectangle of the highlight for the specified context.
If rect is specified, the method directly writes the rectangle to the contextToRectMap.
Otherwise, it will call L{getContextRect} | Updates the position rectangle of the highlight for the specified context.
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Scalsol/mega.pytorch | a6aa6e0537b82d70da94228100a51e6a53d98f82 | mega_core/modeling/backbone/fbnet_builder.py | python | FBNetBuilder._add_ir_block | (
self, dim_in, dim_out, stride, expand_ratio, block_op_type, **kwargs
) | return ret, ret.output_depth | [] | def _add_ir_block(
self, dim_in, dim_out, stride, expand_ratio, block_op_type, **kwargs
):
ret = PRIMITIVES[block_op_type](
dim_in,
dim_out,
expansion=expand_ratio,
stride=stride,
bn_type=self.bn_type,
width_divisor=self.width_divisor,
dw_skip_bn=self.dw_skip_bn,
dw_skip_relu=self.dw_skip_relu,
**kwargs
)
return ret, ret.output_depth | [
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eth-sri/eran | 973e3b52d297d079d5402edec8f7922d824b8cc2 | tf_verify/deeppoly_nodes.py | python | DeeppolyPoolNode.transformer | (self, nn, man, element, nlb, nub, relu_groups, refine, timeout_lp, timeout_milp, use_default_heuristic, testing) | return element | transformer for a maxpool/averagepool layer, this can't be the first layer of a network
Arguments
---------
man : ElinaManagerPtr
man to which element belongs
element : ElinaAbstract0Ptr
abstract element onto which the transformer gets applied
Return
------
output : ElinaAbstract0Ptr
abstract element after the transformer | transformer for a maxpool/averagepool layer, this can't be the first layer of a network
Arguments
---------
man : ElinaManagerPtr
man to which element belongs
element : ElinaAbstract0Ptr
abstract element onto which the transformer gets applied
Return
------
output : ElinaAbstract0Ptr
abstract element after the transformer | [
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"""
transformer for a maxpool/averagepool layer, this can't be the first layer of a network
Arguments
---------
man : ElinaManagerPtr
man to which element belongs
element : ElinaAbstract0Ptr
abstract element onto which the transformer gets applied
Return
------
output : ElinaAbstract0Ptr
abstract element after the transformer
"""
h, w = self.window_size
H, W, C = self.input_shape
#assert self.pad_top==self.pad_bottom==self.pad_right==self.pad_left==0, "Padded pooling not implemented"
handle_pool_layer(man, element, (c_size_t *3)(h,w,1), (c_size_t *3)(H, W, C), (c_size_t *2)(self.strides[0], self.strides[1]), self.pad_top, self.pad_left, self.pad_bottom, self.pad_right, self.output_shape, self.predecessors, len(self.predecessors), self.is_maxpool)
calc_bounds(man, element, nn, nlb, nub, relu_groups, is_refine_layer=True, destroy=False)
nn.pool_counter += 1
if testing:
return element, nlb[-1], nub[-1]
return element | [
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openstack/neutron | fb229fb527ac8b95526412f7762d90826ac41428 | neutron/services/logapi/common/db_api.py | python | _create_sg_rule_dict | (rule_in_db) | return rule_dict | Return a dict of a security group rule | Return a dict of a security group rule | [
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"""Return a dict of a security group rule"""
direction = rule_in_db['direction']
rule_dict = {
'direction': direction,
'ethertype': rule_in_db['ethertype']}
rule_dict.update({
key: rule_in_db[key]
for key in ('protocol', 'port_range_min', 'port_range_max',
'remote_group_id') if rule_in_db[key] is not None})
remote_ip_prefix = rule_in_db['remote_ip_prefix']
if remote_ip_prefix is not None:
direction_ip_prefix = constants.DIRECTION_IP_PREFIX[direction]
rule_dict[direction_ip_prefix] = remote_ip_prefix
rule_dict['security_group_id'] = rule_in_db['security_group_id']
return rule_dict | [
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constverum/ProxyBroker | d21aae8575fc3a95493233ecfd2c7cf47b36b069 | proxybroker/proxy.py | python | Proxy.send | (self, req) | [] | async def send(self, req):
msg, err = '', None
_req = req.encode() if not isinstance(req, bytes) else req
try:
self.writer.write(_req)
await self.writer.drain()
except ConnectionResetError:
msg = '; Sending: failed'
err = ProxySendError(msg)
raise err
finally:
self.log('Request: %s%s' % (req, msg), err=err) | [
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veusz/veusz | 5a1e2af5f24df0eb2a2842be51f2997c4999c7fb | veusz/widgets/axisbroken.py | python | AxisBroken.switchBreak | (self, num, posn, otherposition=None) | Switch to break given (or None to disable). | Switch to break given (or None to disable). | [
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] | def switchBreak(self, num, posn, otherposition=None):
"""Switch to break given (or None to disable)."""
self.rangeswitch = num
if num is None:
self.plottedrange = self.orig_plottedrange
else:
self.plottedrange = [self.breakvstarts[num], self.breakvstops[num]]
self.updateAxisLocation(posn, otherposition=otherposition) | [
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sethmlarson/virtualbox-python | 984a6e2cb0e8996f4df40f4444c1528849f1c70d | virtualbox/library.py | python | IStringFormValue.clipboard_string | (self) | return ret | Get str value for 'clipboardString'
Intnded for cases when a read-only string value is used to
display information and different string is to be used when
copying to the clipboard. | Get str value for 'clipboardString'
Intnded for cases when a read-only string value is used to
display information and different string is to be used when
copying to the clipboard. | [
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"""Get str value for 'clipboardString'
Intnded for cases when a read-only string value is used to
display information and different string is to be used when
copying to the clipboard.
"""
ret = self._get_attr("clipboardString")
return ret | [
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JetBrains/python-skeletons | 95ad24b666e475998e5d1cc02ed53a2188036167 | numpy/core/__init__.py | python | int8.__rrshift__ | (self, *args, **kwargs) | Return value>>self. | Return value>>self. | [
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] | def __rrshift__(self, *args, **kwargs): # real signature unknown
""" Return value>>self. """
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unkn0wnh4ckr/hackers-tool-kit | 34dbabf3e94825684fd1a684f522d3dc3565eb2d | plugins/discovery/IPy.py | python | IP.__repr__ | (self) | return("IP('%s')" % (self.strCompressed(1))) | Print a representation of the Object.
>>> IP('10.0.0.0/8')
IP('10.0.0.0/8') | Print a representation of the Object. | [
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] | def __repr__(self):
"""Print a representation of the Object.
>>> IP('10.0.0.0/8')
IP('10.0.0.0/8')
"""
return("IP('%s')" % (self.strCompressed(1))) | [
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runfalk/spans | db18d6d6a77c35f513095f47ea6929f609da3dff | spans/types.py | python | Range.lower_inf | (self) | return self._range.lower is None and not self._range.empty | Returns True if lower bound is unbounded.
>>> intrange(1, 5).lower_inf
False
>>> intrange(upper=5).lower_inf
True
This is the same as the ``lower_inf(self)`` in PostgreSQL. | Returns True if lower bound is unbounded. | [
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] | def lower_inf(self):
"""
Returns True if lower bound is unbounded.
>>> intrange(1, 5).lower_inf
False
>>> intrange(upper=5).lower_inf
True
This is the same as the ``lower_inf(self)`` in PostgreSQL.
"""
return self._range.lower is None and not self._range.empty | [
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] | https://github.com/runfalk/spans/blob/db18d6d6a77c35f513095f47ea6929f609da3dff/spans/types.py#L324-L336 | |
ukdtom/ExportTools.bundle | 49aba4292a2897f640162a833c2792480aa4f0b6 | Contents/Libraries/Shared/xlsxwriter/chart_pie.py | python | ChartPie.__init__ | (self, options=None) | Constructor. | Constructor. | [
"Constructor",
"."
] | def __init__(self, options=None):
"""
Constructor.
"""
super(ChartPie, self).__init__()
if options is None:
options = {}
self.vary_data_color = 1
self.rotation = 0
# Set the available data label positions for this chart type.
self.label_position_default = 'best_fit'
self.label_positions = {
'center': 'ctr',
'inside_end': 'inEnd',
'outside_end': 'outEnd',
'best_fit': 'bestFit'} | [
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standardebooks/tools | f57af3c5938a9aeed9e97e82b2c130424f6033e5 | se/se_epub_generate_toc.py | python | TocItem.landmark_link | (self, work_type: str = "fiction", work_title: str = "WORK_TITLE") | return out_string | Generates the landmark item (including list item tags) for the ToC item
INPUTS:
work_type: ("fiction" or "non-fiction")
work_title: the title of the book, eg "Don Quixote"
OUTPUTS:
the linking string to be included in landmarks section. | Generates the landmark item (including list item tags) for the ToC item | [
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] | def landmark_link(self, work_type: str = "fiction", work_title: str = "WORK_TITLE") -> str:
"""
Generates the landmark item (including list item tags) for the ToC item
INPUTS:
work_type: ("fiction" or "non-fiction")
work_title: the title of the book, eg "Don Quixote"
OUTPUTS:
the linking string to be included in landmarks section.
"""
out_string = ""
if self.place == Position.FRONT:
out_string = f"<li>\n<a href=\"text/{self.file_link}\" epub:type=\"frontmatter {self.epub_type}\">{self.title}</a>\n</li>\n"
if self.place == Position.BODY:
out_string = f"<li>\n<a href=\"text/{self.file_link}\" epub:type=\"bodymatter z3998:{work_type}\">{work_title}</a>\n</li>\n"
if self.place == Position.BACK:
out_string = f"<li>\n<a href=\"text/{self.file_link}\" epub:type=\"backmatter {self.epub_type}\">{self.title}</a>\n</li>\n"
return out_string | [
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inducer/loopy | 55143b21711a534c07bbb14aaa63ff3879a93433 | loopy/transform/callable.py | python | _inline_call_instruction | (caller_knl, callee_knl, call_insn) | return caller_knl.copy(instructions=new_insns,
temporary_variables=new_temps,
domains=caller_knl.domains+new_domains,
assumptions=(old_assumptions.params()
& new_assumptions.params()),
inames=new_inames) | Returns a copy of *caller_knl* with the *call_insn* in the *kernel*
replaced by inlining *callee_knl* into it within it.
:arg call_insn: An instance of `loopy.CallInstruction` of the call-site. | Returns a copy of *caller_knl* with the *call_insn* in the *kernel*
replaced by inlining *callee_knl* into it within it. | [
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] | def _inline_call_instruction(caller_knl, callee_knl, call_insn):
"""
Returns a copy of *caller_knl* with the *call_insn* in the *kernel*
replaced by inlining *callee_knl* into it within it.
:arg call_insn: An instance of `loopy.CallInstruction` of the call-site.
"""
import pymbolic.primitives as prim
from pymbolic.mapper.substitutor import make_subst_func
from loopy.kernel.data import ValueArg
# {{{ sanity checks
assert call_insn.expression.function.name == callee_knl.name
# }}}
callee_label = callee_knl.name[:4] + "_"
vng = caller_knl.get_var_name_generator()
ing = caller_knl.get_instruction_id_generator()
# {{{ construct callee->caller name mappings
# name_map: Mapping[str, str]
# A mapping from variable names in the callee kernel's namespace to
# the ones they would be referred by in the caller's namespace post inlining.
name_map = {}
# only consider temporary variables and inames, arguments would be mapping
# according to the invocation in call_insn.
for name in (callee_knl.all_inames()
| set(callee_knl.temporary_variables.keys())):
new_name = vng(callee_label+name)
name_map[name] = new_name
# }}}
# {{{ iname_to_tags
# new_inames: caller's inames post inlining
new_inames = caller_knl.inames
for old_name, callee_iname in callee_knl.inames.items():
new_name = name_map[old_name]
new_inames[new_name] = callee_iname.copy(name=new_name)
# }}}
# {{{ register callee's temps as caller's
# new_temps: caller's temps post inlining
new_temps = caller_knl.temporary_variables.copy()
for name, tv in callee_knl.temporary_variables.items():
new_temps[name_map[name]] = tv.copy(name=name_map[name])
# }}}
# {{{ get callee args -> parameters passed to the call
arg_map = {} # callee arg name -> caller symbols (e.g. SubArrayRef)
assignees = call_insn.assignees # writes
parameters = call_insn.expression.parameters # reads
from loopy.kernel.function_interface import get_kw_pos_association
kw_to_pos, pos_to_kw = get_kw_pos_association(callee_knl)
for i, par in enumerate(parameters):
arg_map[pos_to_kw[i]] = par
for i, assignee in enumerate(assignees):
arg_map[pos_to_kw[-i-1]] = assignee
# }}}
# {{{ process domains/assumptions
# rename inames
new_domains = callee_knl.domains.copy()
for old_iname in callee_knl.all_inames():
new_domains = [rename_iname(dom, old_iname, name_map[old_iname])
for dom in new_domains]
# realize domains' dim params in terms of caller's variables
new_assumptions = callee_knl.assumptions
for callee_arg_name, param_expr in arg_map.items():
if isinstance(callee_knl.arg_dict[callee_arg_name],
ValueArg):
new_domains = [
substitute_into_domain(
dom,
callee_arg_name,
param_expr, get_valid_domain_param_names(caller_knl))
for dom in new_domains]
new_assumptions = substitute_into_domain(
new_assumptions,
callee_arg_name,
param_expr, get_valid_domain_param_names(caller_knl))
# }}}
# {{{ rename inames/temporaries in the program
rule_mapping_context = SubstitutionRuleMappingContext(callee_knl.substitutions,
vng)
subst_func = make_subst_func({old_name: prim.Variable(new_name)
for old_name, new_name in name_map.items()})
inames_temps_renamer = RuleAwareSubstitutionMapper(rule_mapping_context,
subst_func,
within=lambda *args: True)
callee_knl = rule_mapping_context.finish_kernel(inames_temps_renamer
.map_kernel(callee_knl))
# }}}
# {{{ map callee's expressions to get expressions after inlining
rule_mapping_context = SubstitutionRuleMappingContext(callee_knl.substitutions,
vng)
smap = KernelArgumentSubstitutor(rule_mapping_context, caller_knl,
callee_knl, arg_map)
callee_knl = rule_mapping_context.finish_kernel(smap.map_kernel(callee_knl))
# }}}
# {{{ generate new ids for instructions
insn_id_map = {}
for insn in callee_knl.instructions:
insn_id_map[insn.id] = ing(callee_label+insn.id)
# }}}
# {{{ use NoOp to mark the start and end of callee kernel
from loopy.kernel.instruction import NoOpInstruction
noop_start = NoOpInstruction(
id=ing(callee_label+"_start"),
within_inames=call_insn.within_inames,
depends_on=call_insn.depends_on
)
noop_end = NoOpInstruction(
id=call_insn.id,
within_inames=call_insn.within_inames,
depends_on=frozenset(insn_id_map.values())
)
# }}}
# {{{ map callee's instruction ids
inlined_insns = [noop_start]
for insn in callee_knl.instructions:
new_within_inames = (frozenset(name_map[iname]
for iname in insn.within_inames)
| call_insn.within_inames)
new_depends_on = (frozenset(insn_id_map[dep] for dep in insn.depends_on)
| {noop_start.id})
new_no_sync_with = frozenset((insn_id_map[id], scope)
for id, scope in insn.no_sync_with)
new_id = insn_id_map[insn.id]
if isinstance(insn, Assignment):
new_atomicity = tuple(type(atomicity)(name_map[atomicity.var_name])
for atomicity in insn.atomicity)
insn = insn.copy(
id=insn_id_map[insn.id],
within_inames=new_within_inames,
depends_on=new_depends_on,
tags=insn.tags | call_insn.tags,
atomicity=new_atomicity,
no_sync_with=new_no_sync_with
)
else:
insn = insn.copy(
id=new_id,
within_inames=new_within_inames,
depends_on=new_depends_on,
tags=insn.tags | call_insn.tags,
no_sync_with=new_no_sync_with
)
inlined_insns.append(insn)
inlined_insns.append(noop_end)
# }}}
# {{{ swap out call_insn with inlined_instructions
idx = caller_knl.instructions.index(call_insn)
new_insns = (caller_knl.instructions[:idx]
+ inlined_insns
+ caller_knl.instructions[idx+1:])
# }}}
old_assumptions, new_assumptions = isl.align_two(
caller_knl.assumptions, new_assumptions)
return caller_knl.copy(instructions=new_insns,
temporary_variables=new_temps,
domains=caller_knl.domains+new_domains,
assumptions=(old_assumptions.params()
& new_assumptions.params()),
inames=new_inames) | [
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markovmodel/PyEMMA | e9d08d715dde17ceaa96480a9ab55d5e87d3a4b3 | pyemma/coordinates/transform/nystroem_tica.py | python | oASIS_Nystroem.column_indices | (self) | return np.array(self._columns) | The selected column indices | The selected column indices | [
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nopernik/mpDNS | b17dc39e7068406df82cb3431b3042e74e520cf9 | circuits/protocols/irc/replies.py | python | RPL_UMODEIS | (modes) | return _M(u("221"), modes) | [] | def RPL_UMODEIS(modes):
return _M(u("221"), modes) | [
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SirFroweey/PyDark | 617c2bfda360afa7750c4707ecacd4ec82fa29af | PyDark/engine.py | python | Scene.Update | (self, item=None) | Update all our self.objects on our Scene() view. | Update all our self.objects on our Scene() view. | [
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if item is None:
for item in self.objects:
# Handle collisions for DarkSprites.
item.Update()
if self.surface.internal_collision_checking is True:
self.process_collisions(item)
for player in self.players:
player.Update()
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lohriialo/photoshop-scripting-python | 6b97da967a5d0a45e54f7c99631b29773b923f09 | api_reference/photoshop_2021.py | python | _SolidColor.IsEqual | (self, Color=defaultNamedNotOptArg) | return self._oleobj_.InvokeTypes(1129406828, LCID, 1, (11, 0), ((9, 1),),Color
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'return true if the provided color is visually equal to this color'
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earhian/Humpback-Whale-Identification-1st- | 2bcb126fb255670b0da57b8a104e47267a8c3a17 | models/triplet_loss.py | python | normalize | (x, axis=-1) | return x | Normalizing to unit length along the specified dimension.
Args:
x: pytorch Variable
Returns:
x: pytorch Variable, same shape as input | Normalizing to unit length along the specified dimension.
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x: pytorch Variable
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x: pytorch Variable, same shape as input | [
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x: pytorch Variable
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x: pytorch Variable, same shape as input
"""
x = 1. * x / (torch.norm(x, 2, axis, keepdim=True).expand_as(x) + 1e-12)
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sharppy/SHARPpy | 19175269ab11fe06c917b5d10376862a4716e1db | sutils/async.py | python | AsyncThreads.post | (self, func, callback, *args, **kwargs) | return thd_id | Post a thread to be run.
func: The function to run in a separate thread
callback: The function to run once func() is done. It will be passed the output from func() as a single tuple.
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thd_id = self._genThreadId()
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if 'background' in kwargs:
del kwargs['background']
thd = self._threadFactory(func, thd_id, *args, **kwargs)
thd.finished.connect(self.finish)
priority = 1 if background else 0
self.queue.put((priority, thd_id))
self.threads[thd_id] = thd
if callback is None:
callback = lambda x: x
self.callbacks[thd_id] = callback
if not background or self.running < self.max_threads:
self.startNext()
return thd_id | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/spc/alarm_control_panel.py | python | SpcAlarm.async_alarm_arm_home | (self, code=None) | Send arm home command. | Send arm home command. | [
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] | async def async_alarm_arm_home(self, code=None):
"""Send arm home command."""
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KhronosGroup/NNEF-Tools | c913758ca687dab8cb7b49e8f1556819a2d0ca25 | nnef_tools/conversion/tflite_to_nnef.py | python | Converter._fix_quantization_attribs | (self, graph) | [] | def _fix_quantization_attribs(self, graph):
for tensor in graph.tensors:
if tensor.quant:
scale = tensor.quant.get('scale')
if scale is not None and not self._is_zero(scale):
if 'min' in tensor.quant:
del tensor.quant['min']
if 'max' in tensor.quant:
del tensor.quant['max']
tensor.quant['op-name'] = 'zero_point_linear_quantize'
tensor.quant['bits'] = 32 if self._is_conv_bias(tensor) else 8
assert tensor.dtype == np.uint8 or tensor.dtype == np.int8 or \
tensor.dtype == np.uint32 or tensor.dtype == np.int32, \
"unknown quantized dtype '{}'".format(tensor.dtype)
tensor.quant['signed'] = tensor.dtype == np.int8 or tensor.dtype == np.int32
tensor.quant['symmetric'] = self._is_conv_filter(tensor) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/bin/pildriver.py | python | PILDriver.do_difference | (self) | usage: difference <image:pic1> <image:pic2>
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Pop the two top images, push the difference image
"""
from PIL import ImageChops
image1 = self.do_pop()
image2 = self.do_pop()
self.push(ImageChops.difference(image1, image2)) | [
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PMEAL/OpenPNM | c9514b858d1361b2090b2f9579280cbcd476c9b0 | openpnm/utils/_project.py | python | Project.save_object | (self, obj) | r"""
Saves the given object or list of objects to a pickle file
Parameters
----------
obj : Base or list[Base]
The objects to be saved. Depending on the object type, the
file extension will be one of 'net', 'geo', 'phase', 'phys'
or 'alg'.
Returns
-------
None | r"""
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r"""
Saves the given object or list of objects to a pickle file
Parameters
----------
obj : Base or list[Base]
The objects to be saved. Depending on the object type, the
file extension will be one of 'net', 'geo', 'phase', 'phys'
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Returns
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"""
from openpnm.io import Pickle
Pickle.save_object_to_file(objs=obj) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/pip/commands/wheel.py | python | WheelCommand.check_required_packages | (self) | [] | def check_required_packages(self):
import_or_raise(
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CommandError,
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)
pkg_resources = import_or_raise(
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if not hasattr(pkg_resources, 'DistInfoDistribution'):
raise CommandError(
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baidu/CUP | 79ab2f3ad6eaab1461aa3b4cca37d3262240194a | cup/util/conf.py | python | Configure2Dict._strip_value | (self, value) | return rev | strip the value | strip the value | [
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"""
strip the value
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if self._remove_comments:
rev = value.split('#')[0].strip()
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rev = value
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itailang/SampleNet | 442459abc54f9e14f0966a169a094a98febd32eb | classification/utils/plyfile.py | python | PlyElement._get_properties | (self) | return self._properties | [] | def _get_properties(self):
return self._properties | [
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jliljebl/flowblade | 995313a509b80e99eb1ad550d945bdda5995093b | flowblade-trunk/Flowblade/keyframeeditor.py | python | PositionNumericalEntries.__init__ | (self, geom_editor, parent_editor, editor_buttons) | [] | def __init__(self, geom_editor, parent_editor, editor_buttons):
GObject.GObject.__init__(self)
self.parent_editor = parent_editor
if isinstance(geom_editor, keyframeeditcanvas.RotatingEditCanvas):
self.rotating_geom = True
self.init_for_roto_geom(editor_buttons)
else:
self.rotating_geom = False
self.init_for_box_geom(editor_buttons) | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | tokumx/datadog_checks/tokumx/vendor/gridfs/__init__.py | python | GridFS.find | (self, *args, **kwargs) | return GridOutCursor(self.__collection, *args, **kwargs) | Query GridFS for files.
Returns a cursor that iterates across files matching
arbitrary queries on the files collection. Can be combined
with other modifiers for additional control. For example::
for grid_out in fs.find({"filename": "lisa.txt"},
no_cursor_timeout=True):
data = grid_out.read()
would iterate through all versions of "lisa.txt" stored in GridFS.
Note that setting no_cursor_timeout to True may be important to
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work.
As another example, the call::
most_recent_three = fs.find().sort("uploadDate", -1).limit(3)
would return a cursor to the three most recently uploaded files
in GridFS.
Follows a similar interface to
:meth:`~pymongo.collection.Collection.find`
in :class:`~pymongo.collection.Collection`.
:Parameters:
- `filter` (optional): a SON object specifying elements which
must be present for a document to be included in the
result set
- `skip` (optional): the number of files to omit (from
the start of the result set) when returning the results
- `limit` (optional): the maximum number of results to
return
- `no_cursor_timeout` (optional): if False (the default), any
returned cursor is closed by the server after 10 minutes of
inactivity. If set to True, the returned cursor will never
time out on the server. Care should be taken to ensure that
cursors with no_cursor_timeout turned on are properly closed.
- `sort` (optional): a list of (key, direction) pairs
specifying the sort order for this query. See
:meth:`~pymongo.cursor.Cursor.sort` for details.
Raises :class:`TypeError` if any of the arguments are of
improper type. Returns an instance of
:class:`~gridfs.grid_file.GridOutCursor`
corresponding to this query.
.. versionchanged:: 3.0
Removed the read_preference, tag_sets, and
secondary_acceptable_latency_ms options.
.. versionadded:: 2.7
.. mongodoc:: find | Query GridFS for files. | [
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] | def find(self, *args, **kwargs):
"""Query GridFS for files.
Returns a cursor that iterates across files matching
arbitrary queries on the files collection. Can be combined
with other modifiers for additional control. For example::
for grid_out in fs.find({"filename": "lisa.txt"},
no_cursor_timeout=True):
data = grid_out.read()
would iterate through all versions of "lisa.txt" stored in GridFS.
Note that setting no_cursor_timeout to True may be important to
prevent the cursor from timing out during long multi-file processing
work.
As another example, the call::
most_recent_three = fs.find().sort("uploadDate", -1).limit(3)
would return a cursor to the three most recently uploaded files
in GridFS.
Follows a similar interface to
:meth:`~pymongo.collection.Collection.find`
in :class:`~pymongo.collection.Collection`.
:Parameters:
- `filter` (optional): a SON object specifying elements which
must be present for a document to be included in the
result set
- `skip` (optional): the number of files to omit (from
the start of the result set) when returning the results
- `limit` (optional): the maximum number of results to
return
- `no_cursor_timeout` (optional): if False (the default), any
returned cursor is closed by the server after 10 minutes of
inactivity. If set to True, the returned cursor will never
time out on the server. Care should be taken to ensure that
cursors with no_cursor_timeout turned on are properly closed.
- `sort` (optional): a list of (key, direction) pairs
specifying the sort order for this query. See
:meth:`~pymongo.cursor.Cursor.sort` for details.
Raises :class:`TypeError` if any of the arguments are of
improper type. Returns an instance of
:class:`~gridfs.grid_file.GridOutCursor`
corresponding to this query.
.. versionchanged:: 3.0
Removed the read_preference, tag_sets, and
secondary_acceptable_latency_ms options.
.. versionadded:: 2.7
.. mongodoc:: find
"""
return GridOutCursor(self.__collection, *args, **kwargs) | [
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roclark/sportsipy | c19f545d3376d62ded6304b137dc69238ac620a9 | sportsipy/nba/boxscore.py | python | Boxscore.home_free_throw_attempts | (self) | return self._home_free_throw_attempts | Returns an ``int`` of the total number of free throw attempts by the
home team. | Returns an ``int`` of the total number of free throw attempts by the
home team. | [
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] | def home_free_throw_attempts(self):
"""
Returns an ``int`` of the total number of free throw attempts by the
home team.
"""
return self._home_free_throw_attempts | [
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lemonhu/open-entity-relation-extraction | 760a7cbf583c60896f7d6053e6fb183fb5fabeb8 | code/core/extract_by_dsnf.py | python | ExtractByDSNF.build_triple | (self, entity1, entity2, relation) | return True | 建立三元组，写入json文件
Args:
entity1: WordUnit，实体1
entity2: WordUnit，实体2
relation: str list，关系列表
num: int，知识三元组编号
Returns:
True: 获得三元组(True) | 建立三元组，写入json文件
Args:
entity1: WordUnit，实体1
entity2: WordUnit，实体2
relation: str list，关系列表
num: int，知识三元组编号
Returns:
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"""建立三元组，写入json文件
Args:
entity1: WordUnit，实体1
entity2: WordUnit，实体2
relation: str list，关系列表
num: int，知识三元组编号
Returns:
True: 获得三元组(True)
"""
triple = dict()
triple['编号'] = self.num
self.num += 1
triple['句子'] = self.origin_sentence
entity1_str = self.element_connect(entity1)
entity2_str = self.element_connect(entity2)
relation_str = self.element_connect(relation)
triple['知识'] = [entity1_str, relation_str, entity2_str]
AppendToJson().append(self.file_path, triple)
print('triple: ' + entity1_str + '\t' + relation_str + '\t' + entity2_str)
return True | [
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PMEAL/OpenPNM | c9514b858d1361b2090b2f9579280cbcd476c9b0 | openpnm/models/geometry/pore_size/_funcs.py | python | equivalent_diameter | (target, pore_volume='pore.volume',
pore_shape='sphere') | return value | r"""
Calculate the diameter of a sphere or edge-length of a cube with same
volume as the pore.
Parameters
----------
%(models.target.parameters)s
pore_volume : str
Name of the dictionary key on ``target`` where the array containing
pore volume values is stored
pore_shape : str
The shape of the pore body to assume when back-calculating from
volume. Options are 'sphere' (default) or 'cube'.
Returns
-------
diameters : ndarray
A number ndarray containing pore diameter values | r"""
Calculate the diameter of a sphere or edge-length of a cube with same
volume as the pore. | [
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pore_shape='sphere'):
r"""
Calculate the diameter of a sphere or edge-length of a cube with same
volume as the pore.
Parameters
----------
%(models.target.parameters)s
pore_volume : str
Name of the dictionary key on ``target`` where the array containing
pore volume values is stored
pore_shape : str
The shape of the pore body to assume when back-calculating from
volume. Options are 'sphere' (default) or 'cube'.
Returns
-------
diameters : ndarray
A number ndarray containing pore diameter values
"""
from scipy.special import cbrt
pore_vols = target[pore_volume]
if pore_shape.startswith('sph'):
value = cbrt(6*pore_vols/_np.pi)
elif pore_shape.startswith('cub'):
value = cbrt(pore_vols)
return value | [
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Kkevsterrr/geneva | 36d3585545d4cb3450ea0b166d8d5f20a64ed8d8 | layers/ip_layer.py | python | IPLayer.gen_ip | (self, field) | return RandIP()._fix() | Generates an IP address. | Generates an IP address. | [
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"""
Generates an IP address.
"""
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spesmilo/electrum | bdbd59300fbd35b01605e66145458e5f396108e8 | electrum/transaction.py | python | PartialTransaction.inputs | (self) | return self._inputs | [] | def inputs(self) -> Sequence[PartialTxInput]:
return self._inputs | [
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Xen0ph0n/YaraGenerator | 48f529f0d85e7fff62405d9367901487e29aa28f | modules/pefile.py | python | PE.get_section_by_rva | (self, rva) | return None | Get the section containing the given address. | Get the section containing the given address. | [
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sections = [s for s in self.sections if s.contains_rva(rva)]
if sections:
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return None | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/wav/v20210129/models.py | python | QueryActivityJoinListResponse.__init__ | (self) | r"""
:param NextCursor: 分页游标
注意：此字段可能返回 null，表示取不到有效值。
:type NextCursor: str
:param PageData: 活码列表响应参数
注意：此字段可能返回 null，表示取不到有效值。
:type PageData: list of ActivityJoinDetail
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
:type RequestId: str | r"""
:param NextCursor: 分页游标
注意：此字段可能返回 null，表示取不到有效值。
:type NextCursor: str
:param PageData: 活码列表响应参数
注意：此字段可能返回 null，表示取不到有效值。
:type PageData: list of ActivityJoinDetail
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
:type RequestId: str | [
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:type NextCursor: str
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self.NextCursor = None
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self.RequestId = None | [
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pyg-team/pytorch_geometric | b920e9a3a64e22c8356be55301c88444ff051cae | torch_geometric/nn/pool/max_pool.py | python | max_pool_x | (cluster, x, batch, size: Optional[int] = None) | return x, batch | r"""Max-Pools node features according to the clustering defined in
:attr:`cluster`.
Args:
cluster (LongTensor): Cluster vector :math:`\mathbf{c} \in \{ 0,
\ldots, N - 1 \}^N`, which assigns each node to a specific cluster.
x (Tensor): Node feature matrix
:math:`\mathbf{X} \in \mathbb{R}^{(N_1 + \ldots + N_B) \times F}`.
batch (LongTensor): Batch vector :math:`\mathbf{b} \in {\{ 0, \ldots,
B-1\}}^N`, which assigns each node to a specific example.
size (int, optional): The maximum number of clusters in a single
example. This property is useful to obtain a batch-wise dense
representation, *e.g.* for applying FC layers, but should only be
used if the size of the maximum number of clusters per example is
known in advance. (default: :obj:`None`)
:rtype: (:class:`Tensor`, :class:`LongTensor`) if :attr:`size` is
:obj:`None`, else :class:`Tensor` | r"""Max-Pools node features according to the clustering defined in
:attr:`cluster`. | [
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r"""Max-Pools node features according to the clustering defined in
:attr:`cluster`.
Args:
cluster (LongTensor): Cluster vector :math:`\mathbf{c} \in \{ 0,
\ldots, N - 1 \}^N`, which assigns each node to a specific cluster.
x (Tensor): Node feature matrix
:math:`\mathbf{X} \in \mathbb{R}^{(N_1 + \ldots + N_B) \times F}`.
batch (LongTensor): Batch vector :math:`\mathbf{b} \in {\{ 0, \ldots,
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example. This property is useful to obtain a batch-wise dense
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known in advance. (default: :obj:`None`)
:rtype: (:class:`Tensor`, :class:`LongTensor`) if :attr:`size` is
:obj:`None`, else :class:`Tensor`
"""
if size is not None:
batch_size = int(batch.max().item()) + 1
return _max_pool_x(cluster, x, batch_size * size), None
cluster, perm = consecutive_cluster(cluster)
x = _max_pool_x(cluster, x)
batch = pool_batch(perm, batch)
return x, batch | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/ast.py | python | fix_missing_locations | (node) | return node | When you compile a node tree with compile(), the compiler expects lineno and
col_offset attributes for every node that supports them. This is rather
tedious to fill in for generated nodes, so this helper adds these attributes
recursively where not already set, by setting them to the values of the
parent node. It works recursively starting at *node*. | When you compile a node tree with compile(), the compiler expects lineno and
col_offset attributes for every node that supports them. This is rather
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zbyte64/django-hyperadmin | 9ac2ae284b76efb3c50a1c2899f383a27154cb54 | hyperadmin/resources/wizard/resources.py | python | Wizard.__init__ | (self, **kwargs) | [] | def __init__(self, **kwargs):
kwargs.setdefault('resource_adaptor', None)
super(Wizard, self).__init__(**kwargs) | [
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ring04h/wyportmap | c4201e2313504e780a7f25238eba2a2d3223e739 | sqlalchemy/dialects/drizzle/base.py | python | BIGINT.__init__ | (self, **kw) | Construct a BIGINTEGER. | Construct a BIGINTEGER. | [
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iGio90/Dwarf | bb3011cdffd209c7e3f5febe558053bf649ca69c | dwarf_debugger/lib/database.py | python | Database.get_module_info | (self, address) | return None | [] | def get_module_info(self, address):
address = self.sanify_address(address)
if address:
try:
address = int(address, 16)
except ValueError:
return None
for module_info in self.modules_info:
_module = self.modules_info[module_info]
if _module:
if _module.base <= address <= _module.base + _module.size:
return _module
return None | [
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riannevdberg/gc-mc | 722f37dde381f9a2c2aa1f91e1e79a63dfba5c03 | gcmc/initializations.py | python | orthogonal | (shape, scale=1.1, name=None) | return tf.Variable(scale * q[:shape[0], :shape[1]], name=name, dtype=tf.float32) | From Lasagne. Reference: Saxe et al., http://arxiv.org/abs/1312.6120 | From Lasagne. Reference: Saxe et al., http://arxiv.org/abs/1312.6120 | [
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"""
From Lasagne. Reference: Saxe et al., http://arxiv.org/abs/1312.6120
"""
flat_shape = (shape[0], np.prod(shape[1:]))
a = np.random.normal(0.0, 1.0, flat_shape)
u, _, v = np.linalg.svd(a, full_matrices=False)
# pick the one with the correct shape
q = u if u.shape == flat_shape else v
q = q.reshape(shape)
return tf.Variable(scale * q[:shape[0], :shape[1]], name=name, dtype=tf.float32) | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | snmp/datadog_checks/snmp/snmp.py | python | SnmpCheck._start_discovery | (self) | [] | def _start_discovery(self):
# type: () -> None
cache = read_persistent_cache(self.check_id)
if cache:
hosts = json.loads(cache)
for host in hosts:
try:
ipaddress.ip_address(host)
except ValueError:
write_persistent_cache(self.check_id, json.dumps([]))
break
self._config.discovered_instances[host] = self._build_autodiscovery_config(self.instance, host)
raw_discovery_interval = self._config.instance.get('discovery_interval', 3600)
try:
discovery_interval = float(raw_discovery_interval)
except (ValueError, TypeError):
message = 'discovery_interval could not be parsed as a number: {!r}'.format(raw_discovery_interval)
raise ConfigurationError(message)
# Pass a weakref to the discovery function to not have a reference cycle
self._thread = self._thread_factory(
target=discover_instances, args=(self._config, discovery_interval, weakref.ref(self)), name=self.name
)
self._thread.daemon = True
self._thread.start()
self._executor = futures.ThreadPoolExecutor(max_workers=self._config.workers) | [
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open-mmlab/mmclassification | 5232965b17b6c050f9b328b3740c631ed4034624 | mmcls/models/builder.py | python | build_head | (cfg) | return HEADS.build(cfg) | Build head. | Build head. | [
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"""Build head."""
return HEADS.build(cfg) | [
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IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/smtplib.py | python | _quote_periods | (bindata) | return re.sub(br'(?m)^\.', b'..', bindata) | [] | def _quote_periods(bindata):
return re.sub(br'(?m)^\.', b'..', bindata) | [
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Bogdanp/dramatiq | 53147a39a14bf56d690644d1ef75b206e69e8982 | dramatiq/cli.py | python | try_unblock_signals | () | Unblocks HANDLED_SIGNALS on platforms that support it. | Unblocks HANDLED_SIGNALS on platforms that support it. | [
"Unblocks",
"HANDLED_SIGNALS",
"on",
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] | def try_unblock_signals():
"""Unblocks HANDLED_SIGNALS on platforms that support it."""
if hasattr(signal, "pthread_sigmask"):
signal.pthread_sigmask(signal.SIG_UNBLOCK, HANDLED_SIGNALS) | [
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TheSouthFrog/stylealign | 910632d2fccc9db61b00c265ae18a88913113c1d | landmark_detection/lib/utils/time_utils.py | python | LossRecorderMeter.min_loss | (self, Train=True) | [] | def min_loss(self, Train=True):
if Train:
idx = np.argmin(self.epoch_losses[:self.current_epoch, 0])
return idx, self.epoch_losses[idx, 0]
else:
idx = np.argmin(self.epoch_losses[:self.current_epoch, 1])
if self.epoch_losses[idx, 1] >= sys.float_info.max / 10:
return idx, -1.
else:
return idx, self.epoch_losses[idx, 1] | [
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... | https://github.com/TheSouthFrog/stylealign/blob/910632d2fccc9db61b00c265ae18a88913113c1d/landmark_detection/lib/utils/time_utils.py#L63-L72 | ||||
CouchPotato/CouchPotatoServer | 7260c12f72447ddb6f062367c6dfbda03ecd4e9c | libs/qbittorrent/client.py | python | QBittorrentClient.global_transfer_info | (self) | return self._get('query/transferInfo') | Get JSON data of the global transfer info of qBittorrent. | Get JSON data of the global transfer info of qBittorrent. | [
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] | def global_transfer_info(self):
"""
Get JSON data of the global transfer info of qBittorrent.
"""
return self._get('query/transferInfo') | [
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urwid/urwid | e2423b5069f51d318ea1ac0f355a0efe5448f7eb | urwid/container.py | python | Columns._set_widget_list | (self, widgets) | [] | def _set_widget_list(self, widgets):
focus_position = self.focus_position
self.contents = [
(new, options) for (new, (w, options)) in zip(widgets,
# need to grow contents list if widgets is longer
chain(self.contents, repeat((None, (WEIGHT, 1, False)))))]
if focus_position < len(widgets):
self.focus_position = focus_position | [
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/idlelib/EditorWindow.py | python | _sphinx_version | () | return release | Format sys.version_info to produce the Sphinx version string used to install the chm docs | Format sys.version_info to produce the Sphinx version string used to install the chm docs | [
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] | def _sphinx_version():
"Format sys.version_info to produce the Sphinx version string used to install the chm docs"
major, minor, micro, level, serial = sys.version_info
release = '%s%s' % (major, minor)
if micro:
release += '%s' % (micro,)
if level == 'candidate':
release += 'rc%s' % (serial,)
elif level != 'final':
release += '%s%s' % (level[0], serial)
return release | [
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msg-systems/holmes-extractor | fc536f32a5cd02a53d1c32f771adc14227d09f38 | holmes_extractor/classification.py | python | SupervisedTopicModelTrainer.filter | (self, labels_to_classification_frequencies, phraselet_infos) | return new_labels_to_classification_frequencies, new_phraselet_infos | Filters the phraselets in memory based on minimum_occurrences and cv_threshold. | Filters the phraselets in memory based on minimum_occurrences and cv_threshold. | [
"Filters",
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"phraselets",
"in",
"memory",
"based",
"on",
"minimum_occurrences",
"and",
"cv_threshold",
"."
] | def filter(self, labels_to_classification_frequencies, phraselet_infos):
""" Filters the phraselets in memory based on minimum_occurrences and cv_threshold. """
accepted = 0
underminimum_occurrences = 0
under_minimum_cv = 0
new_labels_to_classification_frequencies = {}
for label, classification_frequencies in labels_to_classification_frequencies.items():
at_least_minimum = False
working_classification_frequencies = classification_frequencies.copy()
for classification in working_classification_frequencies:
if working_classification_frequencies[classification] >= self.minimum_occurrences:
at_least_minimum = True
if not at_least_minimum:
underminimum_occurrences += 1
continue
frequency_list = list(working_classification_frequencies.values())
# We only want to take explicit classification labels into account, i.e. ignore the
# classification ontology.
number_of_classification_labels = \
len(set(
self.training_basis.training_documents_labels_to_classifications_dict.values())
)
frequency_list.extend([0] * number_of_classification_labels)
frequency_list = frequency_list[:number_of_classification_labels]
if statistics.pstdev(frequency_list) / statistics.mean(frequency_list) >= \
self.cv_threshold:
accepted += 1
new_labels_to_classification_frequencies[label] = classification_frequencies
else:
under_minimum_cv += 1
if self.training_basis.verbose:
print(
'Filtered: accepted', accepted, '; removed minimum occurrences',
underminimum_occurrences, '; removed cv threshold',
under_minimum_cv)
new_phraselet_infos = [
phraselet_info for phraselet_info in phraselet_infos if
phraselet_info.label in new_labels_to_classification_frequencies.keys()]
return new_labels_to_classification_frequencies, new_phraselet_infos | [
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oracle/oci-python-sdk | 3c1604e4e212008fb6718e2f68cdb5ef71fd5793 | src/oci/key_management/kms_crypto_client.py | python | KmsCryptoClient.decrypt | (self, decrypt_data_details, **kwargs) | Decrypts data using the given `DecryptDataDetails`__ resource.
__ https://docs.cloud.oracle.com/api/#/en/key/latest/datatypes/DecryptDataDetails
:param oci.key_management.models.DecryptDataDetails decrypt_data_details: (required)
DecryptDataDetails
:param str opc_request_id: (optional)
Unique identifier for the request. If provided, the returned request ID
will include this value. Otherwise, a random request ID will be
generated by the service.
:param obj retry_strategy: (optional)
A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level.
This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it.
The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__.
To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`.
:return: A :class:`~oci.response.Response` object with data of type :class:`~oci.key_management.models.DecryptedData`
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/keymanagement/decrypt.py.html>`__ to see an example of how to use decrypt API. | Decrypts data using the given `DecryptDataDetails`__ resource. | [
"Decrypts",
"data",
"using",
"the",
"given",
"DecryptDataDetails",
"__",
"resource",
"."
] | def decrypt(self, decrypt_data_details, **kwargs):
"""
Decrypts data using the given `DecryptDataDetails`__ resource.
__ https://docs.cloud.oracle.com/api/#/en/key/latest/datatypes/DecryptDataDetails
:param oci.key_management.models.DecryptDataDetails decrypt_data_details: (required)
DecryptDataDetails
:param str opc_request_id: (optional)
Unique identifier for the request. If provided, the returned request ID
will include this value. Otherwise, a random request ID will be
generated by the service.
:param obj retry_strategy: (optional)
A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level.
This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it.
The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__.
To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`.
:return: A :class:`~oci.response.Response` object with data of type :class:`~oci.key_management.models.DecryptedData`
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/keymanagement/decrypt.py.html>`__ to see an example of how to use decrypt API.
"""
resource_path = "/20180608/decrypt"
method = "POST"
# Don't accept unknown kwargs
expected_kwargs = [
"retry_strategy",
"opc_request_id"
]
extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]
if extra_kwargs:
raise ValueError(
"decrypt got unknown kwargs: {!r}".format(extra_kwargs))
header_params = {
"accept": "application/json",
"content-type": "application/json",
"opc-request-id": kwargs.get("opc_request_id", missing)
}
header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}
retry_strategy = self.base_client.get_preferred_retry_strategy(
operation_retry_strategy=kwargs.get('retry_strategy'),
client_retry_strategy=self.retry_strategy
)
if retry_strategy:
if not isinstance(retry_strategy, retry.NoneRetryStrategy):
self.base_client.add_opc_client_retries_header(header_params)
retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback)
return retry_strategy.make_retrying_call(
self.base_client.call_api,
resource_path=resource_path,
method=method,
header_params=header_params,
body=decrypt_data_details,
response_type="DecryptedData")
else:
return self.base_client.call_api(
resource_path=resource_path,
method=method,
header_params=header_params,
body=decrypt_data_details,
response_type="DecryptedData") | [
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jython/frozen-mirror | b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99 | Lib/distutils/sysconfig.py | python | customize_compiler | (compiler) | Do any platform-specific customization of a CCompiler instance.
Mainly needed on Unix, so we can plug in the information that
varies across Unices and is stored in Python's Makefile. | Do any platform-specific customization of a CCompiler instance. | [
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] | def customize_compiler(compiler):
"""Do any platform-specific customization of a CCompiler instance.
Mainly needed on Unix, so we can plug in the information that
varies across Unices and is stored in Python's Makefile.
"""
if compiler.compiler_type == "unix":
if sys.platform == "darwin":
# Perform first-time customization of compiler-related
# config vars on OS X now that we know we need a compiler.
# This is primarily to support Pythons from binary
# installers. The kind and paths to build tools on
# the user system may vary significantly from the system
# that Python itself was built on. Also the user OS
# version and build tools may not support the same set
# of CPU architectures for universal builds.
global _config_vars
# Use get_config_var() to ensure _config_vars is initialized.
if not get_config_var('CUSTOMIZED_OSX_COMPILER'):
import _osx_support
_osx_support.customize_compiler(_config_vars)
_config_vars['CUSTOMIZED_OSX_COMPILER'] = 'True'
(cc, cxx, opt, cflags, ccshared, ldshared, so_ext, ar, ar_flags) = \
get_config_vars('CC', 'CXX', 'OPT', 'CFLAGS',
'CCSHARED', 'LDSHARED', 'SO', 'AR',
'ARFLAGS')
if 'CC' in os.environ:
newcc = os.environ['CC']
if (sys.platform == 'darwin'
and 'LDSHARED' not in os.environ
and ldshared.startswith(cc)):
# On OS X, if CC is overridden, use that as the default
# command for LDSHARED as well
ldshared = newcc + ldshared[len(cc):]
cc = newcc
if 'CXX' in os.environ:
cxx = os.environ['CXX']
if 'LDSHARED' in os.environ:
ldshared = os.environ['LDSHARED']
if 'CPP' in os.environ:
cpp = os.environ['CPP']
else:
cpp = cc + " -E" # not always
if 'LDFLAGS' in os.environ:
ldshared = ldshared + ' ' + os.environ['LDFLAGS']
if 'CFLAGS' in os.environ:
cflags = opt + ' ' + os.environ['CFLAGS']
ldshared = ldshared + ' ' + os.environ['CFLAGS']
if 'CPPFLAGS' in os.environ:
cpp = cpp + ' ' + os.environ['CPPFLAGS']
cflags = cflags + ' ' + os.environ['CPPFLAGS']
ldshared = ldshared + ' ' + os.environ['CPPFLAGS']
if 'AR' in os.environ:
ar = os.environ['AR']
if 'ARFLAGS' in os.environ:
archiver = ar + ' ' + os.environ['ARFLAGS']
else:
archiver = ar + ' ' + ar_flags
cc_cmd = cc + ' ' + cflags
compiler.set_executables(
preprocessor=cpp,
compiler=cc_cmd,
compiler_so=cc_cmd + ' ' + ccshared,
compiler_cxx=cxx,
linker_so=ldshared,
linker_exe=cc,
archiver=archiver)
compiler.shared_lib_extension = so_ext | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/manifolds/manifold_homset.py | python | TopologicalManifoldHomset._coerce_map_from_ | (self, other) | return False | r"""
Determine whether coercion to ``self`` exists from parent ``other``.
EXAMPLES::
sage: M = Manifold(2, 'M', structure='topological')
sage: X.<x,y> = M.chart()
sage: N = Manifold(3, 'N', structure='topological')
sage: Y.<u,v,w> = N.chart()
sage: H = Hom(M,N)
sage: H._coerce_map_from_(ZZ)
False
sage: H._coerce_map_from_(M)
False
sage: H._coerce_map_from_(N)
False
sage: H._coerce_map_from_(H)
True | r"""
Determine whether coercion to ``self`` exists from parent ``other``. | [
"r",
"Determine",
"whether",
"coercion",
"to",
"self",
"exists",
"from",
"parent",
"other",
"."
] | def _coerce_map_from_(self, other):
r"""
Determine whether coercion to ``self`` exists from parent ``other``.
EXAMPLES::
sage: M = Manifold(2, 'M', structure='topological')
sage: X.<x,y> = M.chart()
sage: N = Manifold(3, 'N', structure='topological')
sage: Y.<u,v,w> = N.chart()
sage: H = Hom(M,N)
sage: H._coerce_map_from_(ZZ)
False
sage: H._coerce_map_from_(M)
False
sage: H._coerce_map_from_(N)
False
sage: H._coerce_map_from_(H)
True
"""
if isinstance(other, TopologicalManifoldHomset):
return (other.domain().has_coerce_map_from(self.domain())
and self.codomain().has_coerce_map_from(other.codomain()))
return False | [
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/layout/ternary/_baxis.py | python | Baxis.showticklabels | (self) | return self["showticklabels"] | Determines whether or not the tick labels are drawn.
The 'showticklabels' property must be specified as a bool
(either True, or False)
Returns
-------
bool | Determines whether or not the tick labels are drawn.
The 'showticklabels' property must be specified as a bool
(either True, or False) | [
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"""
Determines whether or not the tick labels are drawn.
The 'showticklabels' property must be specified as a bool
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Returns
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bool
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return self["showticklabels"] | [
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XKNX/xknx | 1deeeb3dc0978aebacf14492a84e1f1eaf0970ed | xknx/io/gateway_scanner.py | python | GatewayScanFilter.__init__ | (
self,
name: str | None = None,
tunnelling: bool | None = None,
routing: bool | None = None,
) | Initialize GatewayScanFilter class. | Initialize GatewayScanFilter class. | [
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] | def __init__(
self,
name: str | None = None,
tunnelling: bool | None = None,
routing: bool | None = None,
):
"""Initialize GatewayScanFilter class."""
self.name = name
self.tunnelling = tunnelling
self.routing = routing | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/ex-submodules/dimagi/utils/dates.py | python | safe_strftime | (val, fmt) | return safe_val.strftime(fmt
.replace("%Y", str(val.year))
.replace("%y", str(val.year)[-2:])) | conceptually the same as val.strftime(fmt), but this works even with
dates pre-1900.
(For some reason, '%Y' and others do not work for pre-1900 dates
in python stdlib datetime.[date|datetime].strftime.)
This function strictly asserts that fmt does not contain directives whose
value is dependent on the year, such as week number of the year ('%W'). | conceptually the same as val.strftime(fmt), but this works even with
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"""
conceptually the same as val.strftime(fmt), but this works even with
dates pre-1900.
(For some reason, '%Y' and others do not work for pre-1900 dates
in python stdlib datetime.[date|datetime].strftime.)
This function strictly asserts that fmt does not contain directives whose
value is dependent on the year, such as week number of the year ('%W').
"""
assert '%a' not in fmt # short weekday name
assert '%A' not in fmt # full weekday name
assert '%w' not in fmt # weekday (Sun-Sat) as a number (0-6)
assert '%U' not in fmt # week number of the year (weeks starting on Sun)
assert '%W' not in fmt # week number of the year (weeks starting on Mon)
assert '%c' not in fmt # full date and time representation
assert '%x' not in fmt # date representation
assert '%X' not in fmt # time representation
# important that our dummy year is a leap year
# so that it has Feb. 29 in it
a_leap_year = 2012
if isinstance(val, datetime.datetime):
safe_val = datetime.datetime(
a_leap_year, val.month, val.day, hour=val.hour,
minute=val.minute, second=val.second,
microsecond=val.microsecond, tzinfo=val.tzinfo)
else:
safe_val = datetime.date(a_leap_year, val.month, val.day)
return safe_val.strftime(fmt
.replace("%Y", str(val.year))
.replace("%y", str(val.year)[-2:])) | [
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