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phodge/homely | homely/_cli.py | https://github.com/phodge/homely/blob/98ddcf3e4f29b0749645817b4866baaea8376085/homely/_cli.py#L146-L174 | def forget(identifier):
'''
Tells homely to forget about a dotfiles repository that was previously
added. You can then run `homely update` to have homely perform automatic
cleanup of anything that was installed by that dotfiles repo.
REPO
This should be the path to a local dotfiles repository that has already
been registered using `homely add`. You may specify multiple REPOs to
remove at once.
'''
errors = False
for one in identifier:
cfg = RepoListConfig()
info = cfg.find_by_any(one, "ilc")
if not info:
warn("No repos matching %r" % one)
errors = True
continue
# update the config ...
note("Removing record of repo [%s] at %s" % (
info.shortid(), info.localrepo.repo_path))
with saveconfig(RepoListConfig()) as cfg:
cfg.remove_repo(info.repoid)
# if there were errors, then don't try and do an update
if errors:
sys.exit(1) | [
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| python | train |
saltstack/salt | salt/utils/vmware.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/utils/vmware.py#L755-L874 | def get_content(service_instance, obj_type, property_list=None,
container_ref=None, traversal_spec=None,
local_properties=False):
'''
Returns the content of the specified type of object for a Service Instance.
For more information, please see:
http://pubs.vmware.com/vsphere-50/index.jsp?topic=%2Fcom.vmware.wssdk.pg.doc_50%2FPG_Ch5_PropertyCollector.7.6.html
service_instance
The Service Instance from which to obtain content.
obj_type
The type of content to obtain.
property_list
An optional list of object properties to used to return even more filtered content results.
container_ref
An optional reference to the managed object to search under. Can either be an object of type Folder, Datacenter,
ComputeResource, Resource Pool or HostSystem. If not specified, default behaviour is to search under the inventory
rootFolder.
traversal_spec
An optional TraversalSpec to be used instead of the standard
``Traverse All`` spec.
local_properties
Flag specifying whether the properties to be retrieved are local to the
container. If that is the case, the traversal spec needs to be None.
'''
# Start at the rootFolder if container starting point not specified
if not container_ref:
container_ref = get_root_folder(service_instance)
# By default, the object reference used as the starting poing for the filter
# is the container_ref passed in the function
obj_ref = container_ref
local_traversal_spec = False
if not traversal_spec and not local_properties:
local_traversal_spec = True
# We don't have a specific traversal spec override so we are going to
# get everything using a container view
try:
obj_ref = service_instance.content.viewManager.CreateContainerView(
container_ref, [obj_type], True)
except vim.fault.NoPermission as exc:
log.exception(exc)
raise salt.exceptions.VMwareApiError(
'Not enough permissions. Required privilege: '
'{}'.format(exc.privilegeId))
except vim.fault.VimFault as exc:
log.exception(exc)
raise salt.exceptions.VMwareApiError(exc.msg)
except vmodl.RuntimeFault as exc:
log.exception(exc)
raise salt.exceptions.VMwareRuntimeError(exc.msg)
# Create 'Traverse All' traversal spec to determine the path for
# collection
traversal_spec = vmodl.query.PropertyCollector.TraversalSpec(
name='traverseEntities',
path='view',
skip=False,
type=vim.view.ContainerView
)
# Create property spec to determine properties to be retrieved
property_spec = vmodl.query.PropertyCollector.PropertySpec(
type=obj_type,
all=True if not property_list else False,
pathSet=property_list
)
# Create object spec to navigate content
obj_spec = vmodl.query.PropertyCollector.ObjectSpec(
obj=obj_ref,
skip=True if not local_properties else False,
selectSet=[traversal_spec] if not local_properties else None
)
# Create a filter spec and specify object, property spec in it
filter_spec = vmodl.query.PropertyCollector.FilterSpec(
objectSet=[obj_spec],
propSet=[property_spec],
reportMissingObjectsInResults=False
)
# Retrieve the contents
try:
content = service_instance.content.propertyCollector.RetrieveContents([filter_spec])
except vim.fault.NoPermission as exc:
log.exception(exc)
raise salt.exceptions.VMwareApiError(
'Not enough permissions. Required privilege: '
'{}'.format(exc.privilegeId))
except vim.fault.VimFault as exc:
log.exception(exc)
raise salt.exceptions.VMwareApiError(exc.msg)
except vmodl.RuntimeFault as exc:
log.exception(exc)
raise salt.exceptions.VMwareRuntimeError(exc.msg)
# Destroy the object view
if local_traversal_spec:
try:
obj_ref.Destroy()
except vim.fault.NoPermission as exc:
log.exception(exc)
raise salt.exceptions.VMwareApiError(
'Not enough permissions. Required privilege: '
'{}'.format(exc.privilegeId))
except vim.fault.VimFault as exc:
log.exception(exc)
raise salt.exceptions.VMwareApiError(exc.msg)
except vmodl.RuntimeFault as exc:
log.exception(exc)
raise salt.exceptions.VMwareRuntimeError(exc.msg)
return content | [
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The Service Instance from which to obtain content.
obj_type
The type of content to obtain.
property_list
An optional list of object properties to used to return even more filtered content results.
container_ref
An optional reference to the managed object to search under. Can either be an object of type Folder, Datacenter,
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rootFolder.
traversal_spec
An optional TraversalSpec to be used instead of the standard
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local_properties
Flag specifying whether the properties to be retrieved are local to the
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| python | train |
sdcooke/django_bundles | django_bundles/core.py | https://github.com/sdcooke/django_bundles/blob/2810fc455ec7391283792c1f108f4e8340f5d12f/django_bundles/core.py#L221-L235 | def get_bundle_versions():
"""
Used to cache the bundle versions rather than loading them from the bundle versions file every time they're used
"""
global _cached_versions
if not bundles_settings.BUNDLES_VERSION_FILE:
_cached_versions = {}
if _cached_versions is None:
locs = {}
try:
execfile(bundles_settings.BUNDLES_VERSION_FILE, locs)
_cached_versions = locs['BUNDLES_VERSIONS']
except IOError:
_cached_versions = {}
return _cached_versions | [
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| python | train |
emlazzarin/acrylic | acrylic/datatable.py | https://github.com/emlazzarin/acrylic/blob/08c6702d73b9660ead1024653f4fa016f6340e46/acrylic/datatable.py#L579-L623 | def join(self, right_table, on=None, right_prefix='R.', outer=False):
"""
Inner-joins another DataTable to this one using `on` (iterable of join
keys). If two tables share columns other than the join keys, appends
right_prefix to the right table's column name. If `on` is not
provided, performs a 'natural join' using all columns of the same name.
"""
if on is None: # if no 'on', perform natural join
on = list(set(self.fields).intersection(set(right_table.fields)))
if isinstance(on, basestring):
on = [on]
def get_join_key(row):
return tuple(row[header] for header in on)
keymap = defaultdict(list)
for right_row in right_table:
keymap[get_join_key(right_row)].append(right_row)
new_table = []
for left_row in self:
left_key = get_join_key(left_row)
if left_key in keymap:
left_dict = dict(left_row.items())
for right_row in keymap[left_key]:
left_dict_copy = left_dict.copy()
for field, val in right_row.items():
if field in on:
continue
elif field in left_row:
left_dict_copy[right_prefix + field] = val
else:
left_dict_copy[field] = val
new_table.append(left_dict_copy)
elif outer:
left_dict_copy = dict(left_row.items()).copy()
for field in right_table.fields:
if field in on:
continue
elif field in left_row:
left_dict_copy[right_prefix + field] = None
else:
left_dict_copy[field] = None
new_table.append(left_dict_copy)
return DataTable(new_table) | [
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| python | train |
crytic/slither | slither/printers/summary/require_calls.py | https://github.com/crytic/slither/blob/04c147f7e50223c6af458ca430befae747ccd259/slither/printers/summary/require_calls.py#L25-L42 | def output(self, _filename):
"""
_filename is not used
Args:
_filename(string)
"""
for contract in self.slither.contracts_derived:
txt = "\nContract %s"%contract.name
table = PrettyTable(["Function",
"require or assert"])
for function in contract.functions:
require = function.all_slithir_operations()
require = [ir for ir in require if isinstance(ir, SolidityCall) and ir.function in require_or_assert]
require = [ir.node for ir in require]
table.add_row([function.name, self._convert([str(m.expression) for m in set(require)])])
txt += "\n"+str(table)
self.info(txt) | [
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| python | train |
yougov/pmxbot | pmxbot/irc.py | https://github.com/yougov/pmxbot/blob/5da84a3258a0fd73cb35b60e39769a5d7bfb2ba7/pmxbot/irc.py#L79-L85 | def _get_wrapper():
"""
Get a socket wrapper based on SSL config.
"""
if not pmxbot.config.get('use_ssl', False):
return lambda x: x
return importlib.import_module('ssl').wrap_socket | [
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| python | train |
openego/ding0 | ding0/core/network/grids.py | https://github.com/openego/ding0/blob/e2d6528f96255e4bb22ba15514a4f1883564ed5d/ding0/core/network/grids.py#L856-L863 | def add_station(self, lv_station):
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if not isinstance(lv_station, LVStationDing0):
raise Exception('Given LV station is not a LVStationDing0 object.')
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self._station = lv_station
self.graph_add_node(lv_station)
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| python | train |
miniconfig/python-openevse-wifi | openevsewifi/__init__.py | https://github.com/miniconfig/python-openevse-wifi/blob/42fabeae052a9f82092fa9220201413732e38bb4/openevsewifi/__init__.py#L92-L97 | def getServiceLevel(self):
"""Returns the service level"""
command = '$GE'
settings = self.sendCommand(command)
flags = int(settings[2], 16)
return (flags & 0x0001) + 1 | [
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| python | train |
locationlabs/gusset | gusset/colortable.py | https://github.com/locationlabs/gusset/blob/c2e6a58e9eec5a00da2231c1e3e7247c65263edf/gusset/colortable.py#L59-L64 | def separator(self):
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Generate a separator row using current column widths.
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cells = dict([(column, "-" * self.column_widths[column]) for column in self.columns])
return ColorRow(self, **cells) | [
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| python | train |
BoboTiG/python-mss | mss/darwin.py | https://github.com/BoboTiG/python-mss/blob/56347f781edb38a0e7a5104080bd683f49c6f074/mss/darwin.py#L175-L230 | def grab(self, monitor):
# type: (Monitor) -> ScreenShot
"""
See :meth:`MSSMixin.grab <mss.base.MSSMixin.grab>` for full details.
"""
# pylint: disable=too-many-locals
# Convert PIL bbox style
if isinstance(monitor, tuple):
monitor = {
"left": monitor[0],
"top": monitor[1],
"width": monitor[2] - monitor[0],
"height": monitor[3] - monitor[1],
}
core = self.core
rect = CGRect(
(monitor["left"], monitor["top"]), (monitor["width"], monitor["height"])
)
image_ref = core.CGWindowListCreateImage(rect, 1, 0, 0)
if not image_ref:
raise ScreenShotError("CoreGraphics.CGWindowListCreateImage() failed.")
width = int(core.CGImageGetWidth(image_ref))
height = int(core.CGImageGetHeight(image_ref))
prov = copy_data = None
try:
prov = core.CGImageGetDataProvider(image_ref)
copy_data = core.CGDataProviderCopyData(prov)
data_ref = core.CFDataGetBytePtr(copy_data)
buf_len = core.CFDataGetLength(copy_data)
raw = ctypes.cast(data_ref, ctypes.POINTER(ctypes.c_ubyte * buf_len))
data = bytearray(raw.contents)
# Remove padding per row
bytes_per_row = int(core.CGImageGetBytesPerRow(image_ref))
bytes_per_pixel = int(core.CGImageGetBitsPerPixel(image_ref))
bytes_per_pixel = (bytes_per_pixel + 7) // 8
if bytes_per_pixel * width != bytes_per_row:
cropped = bytearray()
for row in range(height):
start = row * bytes_per_row
end = start + width * bytes_per_pixel
cropped.extend(data[start:end])
data = cropped
finally:
if prov:
core.CGDataProviderRelease(prov)
if copy_data:
core.CFRelease(copy_data)
return self.cls_image(data, monitor, size=Size(width, height)) | [
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| python | train |
nwilming/ocupy | ocupy/utils.py | https://github.com/nwilming/ocupy/blob/a0bd64f822576feaa502939d6bafd1183b237d16/ocupy/utils.py#L130-L148 | def dict_fun(data, function):
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Apply a function to all values in a dictionary, return a dictionary with
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Parameters
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data : dict
a dictionary whose values are adequate input to the second argument
of this function.
function : function
a function that takes one argument
Returns
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a dictionary with the same keys as data, such that
result[key] = function(data[key])
"""
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| python | train |
openstack/python-saharaclient | saharaclient/api/clusters.py | https://github.com/openstack/python-saharaclient/blob/c53831d686d9e94187ce5dfdbfa43883b792280e/saharaclient/api/clusters.py#L157-L176 | def create(self, name, plugin_name, plugin_version,
cluster_template_id=None, default_image_id=None,
is_transient=None, description=None, cluster_configs=None,
node_groups=None, user_keypair_id=None,
anti_affinity=None, net_id=None, count=None,
use_autoconfig=None, shares=None,
is_public=None, is_protected=None):
"""Launch a Cluster."""
data = {
'name': name,
'plugin_name': plugin_name,
'plugin_version': plugin_version,
}
return self._do_create(data, cluster_template_id, default_image_id,
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| python | train |
Legobot/Legobot | Legobot/Connectors/Slack.py | https://github.com/Legobot/Legobot/blob/d13da172960a149681cb5151ce34b2f3a58ad32b/Legobot/Connectors/Slack.py#L428-L487 | def handle(self, message):
'''Attempts to send a message to the specified destination in Slack.
Extends Legobot.Lego.handle()
Args:
message (Legobot.Message): message w/ metadata to send.
'''
logger.debug(message)
if Utilities.isNotEmpty(message['metadata']['opts']):
target = message['metadata']['opts']['target']
thread = message['metadata']['opts'].get('thread')
# pattern = re.compile('@([a-zA-Z0-9._-]+)')
pattern = re.compile('^@([a-zA-Z0-9._-]+)|\s@([a-zA-Z0-9._-]+)')
matches = re.findall(pattern, message['text'])
matches = set(matches)
logger.debug('MATCHES!!!! {}'.format(matches))
for match in matches:
if isinstance(match, tuple):
if match[0] != '':
match = match[0]
else:
match = match[1]
if not match.startswith('@'):
match = '@' + match
message['text'] = message['text'].replace(
match,
'<{}>'.format(match)
)
pattern = re.compile('#([A-Za-z0-9-]+)')
matches = re.findall(pattern, message['text'])
matches = set(matches)
for match in matches:
channel_id = self.botThread.get_channel_id_by_name(match)
if channel_id:
message['text'] = message['text'].replace(
'#' + match,
'<#{}|{}>'.format(
channel_id,
match
)
)
if (message['text'].find('<<@') != -1
or message['text'].find('<<#') != -1):
message['text'] = message['text'].replace('<<', '<')
message['text'] = message['text'].replace('>>', '>')
if target.startswith('U'):
target = self.botThread.get_dm_channel(target)
attachment = message['metadata']['opts'].get('attachment')
if attachment:
text = message['metadata']['opts'].get('fallback')
attachment = self.build_attachment(
text, target, attachment, thread)
self.botThread.post_attachment(attachment)
else:
self.botThread.slack_client.rtm_send_message(
target, message['text'], thread=thread) | [
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Extends Legobot.Lego.handle()
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| python | train |
lingthio/Flask-User | flask_user/db_manager.py | https://github.com/lingthio/Flask-User/blob/a379fa0a281789618c484b459cb41236779b95b1/flask_user/db_manager.py#L99-L105 | def add_user(self, **kwargs):
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user = self.UserClass(**kwargs)
if hasattr(user, 'active'):
user.active = True
self.db_adapter.add_object(user)
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| python | train |
maxpumperla/elephas | elephas/worker.py | https://github.com/maxpumperla/elephas/blob/84605acdc9564673c487637dcb27f5def128bcc7/elephas/worker.py#L26-L49 | def train(self, data_iterator):
"""Train a keras model on a worker
"""
optimizer = get_optimizer(self.master_optimizer)
self.model = model_from_yaml(self.yaml, self.custom_objects)
self.model.compile(optimizer=optimizer,
loss=self.master_loss, metrics=self.master_metrics)
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feature_iterator, label_iterator = tee(data_iterator, 2)
x_train = np.asarray([x for x, y in feature_iterator])
y_train = np.asarray([y for x, y in label_iterator])
self.model.compile(optimizer=self.master_optimizer,
loss=self.master_loss,
metrics=self.master_metrics)
weights_before_training = self.model.get_weights()
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self.model.fit(x_train, y_train, **self.train_config)
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deltas = subtract_params(
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yield deltas | [
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| python | train |
pygobject/pgi | pgi/util.py | https://github.com/pygobject/pgi/blob/2090435df6241a15ec2a78379a36b738b728652c/pgi/util.py#L134-L139 | def lookup_name_slow(self, name):
"""Returns a struct if one exists"""
for index in xrange(self.__get_count_cached()):
if self.__get_name_cached(index) == name:
return self.__get_info_cached(index) | [
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| python | train |
gatkin/declxml | declxml.py | https://github.com/gatkin/declxml/blob/3a2324b43aee943e82a04587fbb68932c6f392ba/declxml.py#L945-L959 | def parse_at_element(
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# type: (...) -> Any
"""Parse the provided element as a dictionary."""
parsed_dict = {}
for child in self._child_processors:
state.push_location(child.element_path)
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state.pop_location()
return parsed_dict | [
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| python | train |
oceanprotocol/squid-py | squid_py/ddo/public_key_rsa.py | https://github.com/oceanprotocol/squid-py/blob/43a5b7431627e4c9ab7382ed9eb8153e96ed4483/squid_py/ddo/public_key_rsa.py#L27-L32 | def set_encode_key_value(self, value, store_type=PUBLIC_KEY_STORE_TYPE_BASE64):
"""Set the value based on the type of encoding supported by RSA."""
if store_type == PUBLIC_KEY_STORE_TYPE_PEM:
PublicKeyBase.set_encode_key_value(self, value.exportKey('PEM').decode(), store_type)
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| python | train |
psd-tools/psd-tools | src/psd_tools/api/shape.py | https://github.com/psd-tools/psd-tools/blob/4952b57bcf1cf2c1f16fd9d6d51d4fa0b53bce4e/src/psd_tools/api/shape.py#L220-L223 | def line_alignment(self):
"""Alignment, one of `inner`, `outer`, `center`."""
key = self._data.get(b'strokeStyleLineAlignment').enum
return self.STROKE_STYLE_LINE_ALIGNMENTS.get(key, str(key)) | [
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| python | train |
bitesofcode/projexui | projexui/xsettings.py | https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/xsettings.py#L508-L517 | def childKeys(self):
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| python | train |
PyPSA/PyPSA | pypsa/graph.py | https://github.com/PyPSA/PyPSA/blob/46954b1b3c21460550f7104681517065279a53b7/pypsa/graph.py#L92-L155 | def adjacency_matrix(network, branch_components=None, busorder=None, weights=None):
"""
Construct a sparse adjacency matrix (directed)
Parameters
----------
branch_components : iterable sublist of `branch_components`
Buses connected by any of the selected branches are adjacent
(default: branch_components (network) or passive_branch_components (sub_network))
busorder : pd.Index subset of network.buses.index
Basis to use for the matrix representation of the adjacency matrix
(default: buses.index (network) or buses_i() (sub_network))
weights : pd.Series or None (default)
If given must provide a weight for each branch, multi-indexed
on branch_component name and branch name.
Returns
-------
adjacency_matrix : sp.sparse.coo_matrix
Directed adjacency matrix
"""
from . import components
if isinstance(network, components.Network):
if branch_components is None:
branch_components = network.branch_components
if busorder is None:
busorder = network.buses.index
elif isinstance(network, components.SubNetwork):
if branch_components is None:
branch_components = network.network.passive_branch_components
if busorder is None:
busorder = network.buses_i()
else:
raise TypeError(" must be called with a Network or a SubNetwork")
no_buses = len(busorder)
no_branches = 0
bus0_inds = []
bus1_inds = []
weight_vals = []
for c in network.iterate_components(branch_components):
if c.ind is None:
sel = slice(None)
no_branches = len(c.df)
else:
sel = c.ind
no_branches = len(c.ind)
bus0_inds.append(busorder.get_indexer(c.df.loc[sel, "bus0"]))
bus1_inds.append(busorder.get_indexer(c.df.loc[sel, "bus1"]))
weight_vals.append(np.ones(no_branches)
if weights is None
else weights[c.name][sel].values)
if no_branches == 0:
return sp.sparse.coo_matrix((no_buses, no_buses))
bus0_inds = np.concatenate(bus0_inds)
bus1_inds = np.concatenate(bus1_inds)
weight_vals = np.concatenate(weight_vals)
return sp.sparse.coo_matrix((weight_vals, (bus0_inds, bus1_inds)),
shape=(no_buses, no_buses)) | [
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busorder : pd.Index subset of network.buses.index
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| python | train |
apple/turicreate | deps/src/cmake-3.13.4/Source/cmConvertMSBuildXMLToJSON.py | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/cmake-3.13.4/Source/cmConvertMSBuildXMLToJSON.py#L173-L198 | def __merge_json_values(current, previous):
"""Merges the values between the current and previous run of the script."""
for value in current:
name = value['name']
# Find the previous value
previous_value = __find_and_remove_value(previous, value)
if previous_value is not None:
flags = value['flags']
previous_flags = previous_value['flags']
if flags != previous_flags:
logging.warning(
'Flags for %s are different. Using previous value.', name)
value['flags'] = previous_flags
else:
logging.warning('Value %s is a new value', name)
for value in previous:
name = value['name']
logging.warning(
'Value %s not present in current run. Appending value.', name)
current.append(value) | [
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| python | train |
empymod/empymod | empymod/utils.py | https://github.com/empymod/empymod/blob/4a78ca4191ed4b4d42d019ce715a9a3889dba1bc/empymod/utils.py#L824-L897 | def check_opt(opt, loop, ht, htarg, verb):
r"""Check optimization parameters.
This check-function is called from one of the modelling routines in
:mod:`model`. Consult these modelling routines for a detailed description
of the input parameters.
Parameters
----------
opt : {None, 'parallel'}
Optimization flag; use ``numexpr`` or not.
loop : {None, 'freq', 'off'}
Loop flag.
ht : str
Flag to choose the Hankel transform.
htarg : array_like,
Depends on the value for ``ht``.
verb : {0, 1, 2, 3, 4}
Level of verbosity.
Returns
-------
use_ne_eval : bool
Boolean if to use ``numexpr``.
loop_freq : bool
Boolean if to loop over frequencies.
loop_off : bool
Boolean if to loop over offsets.
"""
# Check optimization flag
use_ne_eval = False
if opt == 'parallel':
if numexpr:
use_ne_eval = numexpr.evaluate
elif verb > 0:
print(numexpr_msg)
# Define if to loop over frequencies or over offsets
lagged_splined_fht = False
if ht == 'fht':
if htarg[1] != 0:
lagged_splined_fht = True
if ht in ['hqwe', 'hquad'] or lagged_splined_fht:
loop_freq = True
loop_off = False
else:
loop_off = loop == 'off'
loop_freq = loop == 'freq'
# If verbose, print optimization information
if verb > 2:
if use_ne_eval:
print(" Kernel Opt. : Use parallel")
else:
print(" Kernel Opt. : None")
if loop_off:
print(" Loop over : Offsets")
elif loop_freq:
print(" Loop over : Frequencies")
else:
print(" Loop over : None (all vectorized)")
return use_ne_eval, loop_freq, loop_off | [
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Optimization flag; use ``numexpr`` or not.
loop : {None, 'freq', 'off'}
Loop flag.
ht : str
Flag to choose the Hankel transform.
htarg : array_like,
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verb : {0, 1, 2, 3, 4}
Level of verbosity.
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use_ne_eval : bool
Boolean if to use ``numexpr``.
loop_freq : bool
Boolean if to loop over frequencies.
loop_off : bool
Boolean if to loop over offsets. | [
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| python | train |
cloud-custodian/cloud-custodian | c7n/actions/network.py | https://github.com/cloud-custodian/cloud-custodian/blob/52ef732eb3d7bc939d1579faf519314814695c08/c7n/actions/network.py#L184-L198 | def resolve_remove_symbols(self, r, target_group_ids, rgroups):
"""Resolve the resources security groups that need be modified.
Specifically handles symbolic names that match annotations from policy filters
for groups being removed.
"""
if 'matched' in target_group_ids:
return r.get('c7n:matched-security-groups', ())
elif 'network-location' in target_group_ids:
for reason in r.get('c7n:NetworkLocation', ()):
if reason['reason'] == 'SecurityGroupMismatch':
return list(reason['security-groups'])
elif 'all' in target_group_ids:
return rgroups
return target_group_ids | [
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| python | train |
pandas-dev/pandas | pandas/core/indexes/base.py | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/base.py#L958-L969 | def _format_data(self, name=None):
"""
Return the formatted data as a unicode string.
"""
# do we want to justify (only do so for non-objects)
is_justify = not (self.inferred_type in ('string', 'unicode') or
(self.inferred_type == 'categorical' and
is_object_dtype(self.categories)))
return format_object_summary(self, self._formatter_func,
is_justify=is_justify, name=name) | [
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| python | train |
chrislit/abydos | abydos/distance/_eudex.py | https://github.com/chrislit/abydos/blob/165466b3ff6afd8024a4c8660421b0c4e7773db9/abydos/distance/_eudex.py#L202-L236 | def dist(self, src, tar, weights='exponential', max_length=8):
"""Return normalized distance between the Eudex hashes of two terms.
This is Eudex distance normalized to [0, 1].
Parameters
----------
src : str
Source string for comparison
tar : str
Target string for comparison
weights : str, iterable, or generator function
The weights or weights generator function
max_length : int
The number of characters to encode as a eudex hash
Returns
-------
int
The normalized Eudex Hamming distance
Examples
--------
>>> cmp = Eudex()
>>> round(cmp.dist('cat', 'hat'), 12)
0.062745098039
>>> round(cmp.dist('Niall', 'Neil'), 12)
0.000980392157
>>> round(cmp.dist('Colin', 'Cuilen'), 12)
0.004901960784
>>> round(cmp.dist('ATCG', 'TAGC'), 12)
0.197549019608
"""
return self.dist_abs(src, tar, weights, max_length, True) | [
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Target string for comparison
weights : str, iterable, or generator function
The weights or weights generator function
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The number of characters to encode as a eudex hash
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| python | valid |
LionelR/pyair | pyair/stats.py | https://github.com/LionelR/pyair/blob/467e8a843ca9f882f8bb2958805b7293591996ad/pyair/stats.py#L113-L116 | def foex(a, b):
"""Returns the factor of exceedance
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return (np.sum(a > b, dtype=float) / len(a) - 0.5) * 100 | [
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| python | valid |
SCIP-Interfaces/PySCIPOpt | examples/finished/flp.py | https://github.com/SCIP-Interfaces/PySCIPOpt/blob/9c960b40d94a48b0304d73dbe28b467b9c065abe/examples/finished/flp.py#L11-L46 | def flp(I,J,d,M,f,c):
"""flp -- model for the capacitated facility location problem
Parameters:
- I: set of customers
- J: set of facilities
- d[i]: demand for customer i
- M[j]: capacity of facility j
- f[j]: fixed cost for using a facility in point j
- c[i,j]: unit cost of servicing demand point i from facility j
Returns a model, ready to be solved.
"""
model = Model("flp")
x,y = {},{}
for j in J:
y[j] = model.addVar(vtype="B", name="y(%s)"%j)
for i in I:
x[i,j] = model.addVar(vtype="C", name="x(%s,%s)"%(i,j))
for i in I:
model.addCons(quicksum(x[i,j] for j in J) == d[i], "Demand(%s)"%i)
for j in M:
model.addCons(quicksum(x[i,j] for i in I) <= M[j]*y[j], "Capacity(%s)"%i)
for (i,j) in x:
model.addCons(x[i,j] <= d[i]*y[j], "Strong(%s,%s)"%(i,j))
model.setObjective(
quicksum(f[j]*y[j] for j in J) +
quicksum(c[i,j]*x[i,j] for i in I for j in J),
"minimize")
model.data = x,y
return model | [
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- c[i,j]: unit cost of servicing demand point i from facility j
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| python | train |
openstack/networking-arista | networking_arista/ml2/mechanism_arista.py | https://github.com/openstack/networking-arista/blob/07ce6b1fc62ff74308a6eabfc4cc0ee09fb7b0fe/networking_arista/ml2/mechanism_arista.py#L117-L130 | def get_instance_type(self, port):
"""Determine the port type based on device owner and vnic type"""
if port[portbindings.VNIC_TYPE] == portbindings.VNIC_BAREMETAL:
return a_const.BAREMETAL_RESOURCE
owner_to_type = {
n_const.DEVICE_OWNER_DHCP: a_const.DHCP_RESOURCE,
n_const.DEVICE_OWNER_DVR_INTERFACE: a_const.ROUTER_RESOURCE,
trunk_consts.TRUNK_SUBPORT_OWNER: a_const.VM_RESOURCE}
if port['device_owner'] in owner_to_type.keys():
return owner_to_type[port['device_owner']]
elif port['device_owner'].startswith(
n_const.DEVICE_OWNER_COMPUTE_PREFIX):
return a_const.VM_RESOURCE
return None | [
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| python | train |
KungAlex/pbkdf2helper | pbkdf2helper/helper.py | https://github.com/KungAlex/pbkdf2helper/blob/4719878d6f8cada486415b111ed72164b4ac6f57/pbkdf2helper/helper.py#L66-L73 | def split(encoded):
"""
Split a PBKDF2 hashed Password into algorithm, iterations, salt and hash
:param encoded: PBKDF2 hashed Password
:return: algorithm, iterations, salt, hash
"""
algorithm, iterations, salt, h = encoded.split('$', 3)
return algorithm, iterations, salt, h | [
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| python | train |
globocom/GloboNetworkAPI-client-python | networkapiclient/ClientFactory.py | https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/ClientFactory.py#L352-L358 | def create_equipamento(self):
"""Get an instance of equipamento services facade."""
return Equipamento(
self.networkapi_url,
self.user,
self.password,
self.user_ldap) | [
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| python | train |
vtkiorg/vtki | vtki/renderer.py | https://github.com/vtkiorg/vtki/blob/5ccad7ae6d64a03e9594c9c7474c8aab3eb22dd1/vtki/renderer.py#L61-L126 | def add_actor(self, uinput, reset_camera=False, name=None, loc=None,
culling=False):
"""
Adds an actor to render window. Creates an actor if input is
a mapper.
Parameters
----------
uinput : vtk.vtkMapper or vtk.vtkActor
vtk mapper or vtk actor to be added.
reset_camera : bool, optional
Resets the camera when true.
loc : int, tuple, or list
Index of the renderer to add the actor to. For example,
``loc=2`` or ``loc=(1, 1)``.
culling : bool optional
Does not render faces that should not be visible to the
plotter. This can be helpful for dense surface meshes,
especially when edges are visible, but can cause flat
meshes to be partially displayed. Default False.
Returns
-------
actor : vtk.vtkActor
The actor.
actor_properties : vtk.Properties
Actor properties.
"""
# Remove actor by that name if present
rv = self.remove_actor(name, reset_camera=False)
if isinstance(uinput, vtk.vtkMapper):
actor = vtk.vtkActor()
actor.SetMapper(uinput)
else:
actor = uinput
self.AddActor(actor)
actor.renderer = proxy(self)
if name is None:
name = str(hex(id(actor)))
self._actors[name] = actor
if reset_camera:
self.reset_camera()
elif not self.camera_set and reset_camera is None and not rv:
self.reset_camera()
else:
self.parent._render()
self.update_bounds_axes()
if culling:
try:
actor.GetProperty().BackfaceCullingOn()
except AttributeError: # pragma: no cover
pass
return actor, actor.GetProperty() | [
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vtk mapper or vtk actor to be added.
reset_camera : bool, optional
Resets the camera when true.
loc : int, tuple, or list
Index of the renderer to add the actor to. For example,
``loc=2`` or ``loc=(1, 1)``.
culling : bool optional
Does not render faces that should not be visible to the
plotter. This can be helpful for dense surface meshes,
especially when edges are visible, but can cause flat
meshes to be partially displayed. Default False.
Returns
-------
actor : vtk.vtkActor
The actor.
actor_properties : vtk.Properties
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| python | train |
suds-community/suds | suds/sax/enc.py | https://github.com/suds-community/suds/blob/6fb0a829337b5037a66c20aae6f89b41acd77e40/suds/sax/enc.py#L81-L94 | def __needs_encoding(self, s):
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| python | train |
loli/medpy | medpy/graphcut/energy_label.py | https://github.com/loli/medpy/blob/95216b9e22e7ce301f0edf953ee2a2f1b6c6aee5/medpy/graphcut/energy_label.py#L111-L193 | def boundary_stawiaski(graph, label_image, gradient_image): # label image is not required to hold continuous ids or to start from 1
r"""
Boundary term based on the sum of border voxel pairs differences.
An implementation of the boundary term in [1]_, suitable to be used with the `~medpy.graphcut.generate.graph_from_labels` function.
Determines for each two supplied regions the voxels forming their border assuming
:math:`ndim*2`-connectedness (e.g. :math:`3*2=6` for 3D). From the gradient magnitude values of each
end-point voxel the border-voxel pairs, the highest one is selected and passed to a
strictly positive and decreasing function :math:`g(x)`, which is defined as:
.. math::
g(x) = \left(\frac{1}{1+|x|}\right)^k
,where :math:`k=2`. The final weight :math:`w_{i,j}` between two regions :math:`r_i` and
:math:`r_j` is then determined by the sum of all these neighbour values:
.. math::
w_{i,j} = \sum_{e_{m,n}\in F_{(r_i,r_j)}}g(\max(|I(m)|,|I(n)|))
, where :math:`F_{(r_i,r_j)}` is the set of border voxel-pairs :math:`e_{m,n}` between
the regions :math:`r_i` and :math:`r_j` and :math:`|I(p)|` the absolute of the gradient
magnitude at the voxel :math:`p`
This boundary_function works as an edge indicator in the original image. In simpler
words the weight (and therefore the energy) is obtained by summing the local contrast
along the boundaries between two regions.
Parameters
----------
graph : GCGraph
The graph to add the weights to.
label_image : ndarray
The label image. Must contain consecutively labelled regions starting from index 1.
gradient_image : ndarray
The gradient image.
Notes
-----
This function requires the gradient magnitude image of the original image to be passed
along. That means that `~medpy.graphcut.generate.graph_from_labels` has to be called
with ``boundary_term_args`` set to the gradient image. This can be obtained e.g. with
`generic_gradient_magnitude` and `prewitt` from `scipy.ndimage`.
This function is tested on 2D and 3D images and theoretically works for all dimensionalities.
References
----------
.. [1] Stawiaski J., Decenciere E., Bidlaut F. "Interactive Liver Tumor Segmentation
Using Graph-cuts and watershed" MICCAI 2008 participation
"""
# convert to arrays if necessary
label_image = scipy.asarray(label_image)
gradient_image = scipy.asarray(gradient_image)
if label_image.flags['F_CONTIGUOUS']: # strangely, this one is required to be ctype ordering
label_image = scipy.ascontiguousarray(label_image)
__check_label_image(label_image)
for dim in range(label_image.ndim):
# prepare slicer for all minus last and all minus first "row"
slicer_from = [slice(None)] * label_image.ndim
slicer_to = [slice(None)] * label_image.ndim
slicer_from[dim] = slice(None, -1)
slicer_to[dim] = slice(1, None)
# slice views of keys
keys_from = label_image[slicer_from]
keys_to = label_image[slicer_to]
# determine not equal keys
valid_edges = keys_from != keys_to
# determine largest gradient
gradient_max = numpy.maximum(numpy.abs(gradient_image[slicer_from]), numpy.abs(gradient_image[slicer_to]))[valid_edges]
# determine key order
keys_max = numpy.maximum(keys_from, keys_to)[valid_edges]
keys_min = numpy.minimum(keys_from, keys_to)[valid_edges]
# set edges / nweights
for k1, k2, val in zip(keys_min, keys_max, gradient_max):
weight = math.pow(1./(1. + val), 2) # weight contribution of a single pixel
weight = max(weight, sys.float_info.min)
graph.set_nweight(k1 - 1 , k2 - 1, weight, weight) | [
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g(x) = \left(\frac{1}{1+|x|}\right)^k
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:math:`r_j` is then determined by the sum of all these neighbour values:
.. math::
w_{i,j} = \sum_{e_{m,n}\in F_{(r_i,r_j)}}g(\max(|I(m)|,|I(n)|))
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the regions :math:`r_i` and :math:`r_j` and :math:`|I(p)|` the absolute of the gradient
magnitude at the voxel :math:`p`
This boundary_function works as an edge indicator in the original image. In simpler
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Parameters
----------
graph : GCGraph
The graph to add the weights to.
label_image : ndarray
The label image. Must contain consecutively labelled regions starting from index 1.
gradient_image : ndarray
The gradient image.
Notes
-----
This function requires the gradient magnitude image of the original image to be passed
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References
----------
.. [1] Stawiaski J., Decenciere E., Bidlaut F. "Interactive Liver Tumor Segmentation
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| python | train |
tanghaibao/jcvi | jcvi/formats/gff.py | https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/formats/gff.py#L2409-L2462 | def note(args):
"""
%prog note gffile > tabfile
Extract certain attribute field for each feature.
"""
p = OptionParser(note.__doc__)
p.add_option("--type", default=None,
help="Only process certain types, multiple types allowed with comma")
p.add_option("--attribute", default="Parent,Note",
help="Attribute field to extract, multiple fields allowd with comma")
p.add_option("--AED", type="float", help="Only extract lines with AED score <=")
p.add_option("--exoncount", default=False, action="store_true",
help="Get the exon count for each mRNA feat")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
gffile, = args
type = opts.type
if type:
type = type.split(",")
g = make_index(gffile)
exoncounts = {}
if opts.exoncount:
for feat in g.features_of_type("mRNA"):
nexons = 0
for c in g.children(feat.id, 1):
if c.featuretype != "exon":
continue
nexons += 1
exoncounts[feat.id] = nexons
attrib = opts.attribute.split(",")
gff = Gff(gffile)
seen = set()
AED = opts.AED
for g in gff:
if type and g.type not in type:
continue
if AED is not None and float(g.attributes["_AED"][0]) > AED:
continue
keyval = [g.accn] + [",".join(g.attributes[x]) \
for x in attrib if x in g.attributes]
if exoncounts:
nexons = exoncounts.get(g.accn, 0)
keyval.append(str(nexons))
keyval = tuple(keyval)
if keyval not in seen:
print("\t".join(keyval))
seen.add(keyval) | [
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| python | train |
XuShaohua/bcloud | bcloud/UploadPage.py | https://github.com/XuShaohua/bcloud/blob/4b54e0fdccf2b3013285fef05c97354cfa31697b/bcloud/UploadPage.py#L697-L711 | def operate_selected_rows(self, operator):
'''对选中的条目进行操作.
operator - 处理函数
'''
model, tree_paths = self.selection.get_selected_rows()
if not tree_paths:
return
fids = []
for tree_path in tree_paths:
fids.append(model[tree_path][FID_COL])
for fid in fids:
row = self.get_row_by_fid(fid)
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operator(row) | [
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| python | train |
ciena/afkak | afkak/client.py | https://github.com/ciena/afkak/blob/6f5e05ba6f135ea3c29cdb80efda009f7845569a/afkak/client.py#L803-L846 | def _make_request_to_broker(self, broker, requestId, request, **kwArgs):
"""Send a request to the specified broker."""
def _timeout_request(broker, requestId):
"""The time we allotted for the request expired, cancel it."""
try:
# FIXME: This should be done by calling .cancel() on the Deferred
# returned by the broker client.
broker.cancelRequest(requestId, reason=RequestTimedOutError(
'Request: {} cancelled due to timeout'.format(requestId)))
except KeyError: # pragma: no cover This should never happen...
log.exception('ERROR: Failed to find key for timed-out '
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broker, requestId)
raise
if self._disconnect_on_timeout:
broker.disconnect()
def _alert_blocked_reactor(timeout, start):
"""Complain if this timer didn't fire before the timeout elapsed"""
now = self.reactor.seconds()
if now >= (start + timeout):
log.warning('Reactor was starved for %r seconds', now - start)
def _cancel_timeout(result, dc):
"""Request completed/cancelled, cancel the timeout delayedCall."""
if dc.active():
dc.cancel()
return result
# Make the request to the specified broker
log.debug('_mrtb: sending request: %d to broker: %r',
requestId, broker)
d = broker.makeRequest(requestId, request, **kwArgs)
# Set a delayedCall to fire if we don't get a reply in time
dc = self.reactor.callLater(
self.timeout, _timeout_request, broker, requestId)
# Set a delayedCall to complain if the reactor has been blocked
rc = self.reactor.callLater(
(self.timeout * 0.9), _alert_blocked_reactor, self.timeout,
self.reactor.seconds())
# Setup a callback on the request deferred to cancel both callLater
d.addBoth(_cancel_timeout, dc)
d.addBoth(_cancel_timeout, rc)
return d | [
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| python | train |
pantsbuild/pants | src/python/pants/backend/jvm/tasks/classpath_util.py | https://github.com/pantsbuild/pants/blob/b72e650da0df685824ffdcc71988b8c282d0962d/src/python/pants/backend/jvm/tasks/classpath_util.py#L68-L78 | def classpath(cls, targets, classpath_products, confs=('default',)):
"""Return the classpath as a list of paths covering all the passed targets.
:param targets: Targets to build an aggregated classpath for.
:param ClasspathProducts classpath_products: Product containing classpath elements.
:param confs: The list of confs for use by this classpath.
:returns: The classpath as a list of path elements.
:rtype: list of string
"""
classpath_iter = cls._classpath_iter(classpath_products.get_for_targets(targets), confs=confs)
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| python | train |
juju/python-libjuju | juju/model.py | https://github.com/juju/python-libjuju/blob/58f0011f4c57cd68830258952fa952eaadca6b38/juju/model.py#L597-L615 | async def add_local_charm_dir(self, charm_dir, series):
"""Upload a local charm to the model.
This will automatically generate an archive from
the charm dir.
:param charm_dir: Path to the charm directory
:param series: Charm series
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fh = tempfile.NamedTemporaryFile()
CharmArchiveGenerator(charm_dir).make_archive(fh.name)
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log.debug('Uploaded local charm: %s -> %s', charm_dir, charm_url)
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| python | train |
Accelize/pycosio | pycosio/_core/io_base_raw.py | https://github.com/Accelize/pycosio/blob/1cc1f8fdf5394d92918b7bae2bfa682169ccc48c/pycosio/_core/io_base_raw.py#L246-L260 | def _peek(self, size=-1):
"""
Return bytes from the stream without advancing the position.
Args:
size (int): Number of bytes to read. -1 to read the full
stream.
Returns:
bytes: bytes read
"""
with self._seek_lock:
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| python | train |
jorahn/icy | icy/icy.py | https://github.com/jorahn/icy/blob/d0bd765c933b2d9bff4d7d646c0938348b9c5c25/icy/icy.py#L543-L550 | def _find_key_cols(df):
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keys = []
for col in df:
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keys.append(col)
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| python | train |
peri-source/peri | peri/comp/comp.py | https://github.com/peri-source/peri/blob/61beed5deaaf978ab31ed716e8470d86ba639867/peri/comp/comp.py#L101-L111 | def set_values(self, params, values):
"""
Directly set the values corresponding to certain parameters.
This does not necessarily trigger and update of the calculation,
See also
--------
:func:`~peri.comp.comp.ParameterGroup.update` : full update func
"""
for p, v in zip(util.listify(params), util.listify(values)):
self.param_dict[p] = v | [
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See also
--------
:func:`~peri.comp.comp.ParameterGroup.update` : full update func | [
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| python | valid |
rigetti/grove | grove/tomography/utils.py | https://github.com/rigetti/grove/blob/dc6bf6ec63e8c435fe52b1e00f707d5ce4cdb9b3/grove/tomography/utils.py#L244-L268 | def plot_pauli_transfer_matrix(ptransfermatrix, ax, labels, title):
"""
Visualize the Pauli Transfer Matrix of a process.
:param numpy.ndarray ptransfermatrix: The Pauli Transfer Matrix
:param ax: The matplotlib axes.
:param labels: The labels for the operator basis states.
:param title: The title for the plot
:return: The modified axis object.
:rtype: AxesSubplot
"""
im = ax.imshow(ptransfermatrix, interpolation="nearest", cmap=rigetti_3_color_cm, vmin=-1,
vmax=1)
dim = len(labels)
plt.colorbar(im, ax=ax)
ax.set_xticks(range(dim))
ax.set_xlabel("Input Pauli Operator", fontsize=20)
ax.set_yticks(range(dim))
ax.set_ylabel("Output Pauli Operator", fontsize=20)
ax.set_title(title, fontsize=25)
ax.set_xticklabels(labels, rotation=45)
ax.set_yticklabels(labels)
ax.grid(False)
return ax | [
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| Visualize the Pauli Transfer Matrix of a process.
:param numpy.ndarray ptransfermatrix: The Pauli Transfer Matrix
:param ax: The matplotlib axes.
:param labels: The labels for the operator basis states.
:param title: The title for the plot
:return: The modified axis object.
:rtype: AxesSubplot | [
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| python | train |
angr/angr | angr/analyses/cfg/cfg_emulated.py | https://github.com/angr/angr/blob/4e2f97d56af5419ee73bdb30482c8dd8ff5f3e40/angr/analyses/cfg/cfg_emulated.py#L975-L1016 | def _get_one_pending_job(self):
"""
Retrieve a pending job.
:return: A CFGJob instance or None
"""
pending_job_key, pending_job = self._pending_jobs.popitem()
pending_job_state = pending_job.state
pending_job_call_stack = pending_job.call_stack
pending_job_src_block_id = pending_job.src_block_id
pending_job_src_exit_stmt_idx = pending_job.src_exit_stmt_idx
self._deregister_analysis_job(pending_job.caller_func_addr, pending_job)
# Let's check whether this address has been traced before.
if pending_job_key in self._nodes:
node = self._nodes[pending_job_key]
if node in self.graph:
pending_exit_addr = self._block_id_addr(pending_job_key)
# That block has been traced before. Let's forget about it
l.debug("Target 0x%08x has been traced before. Trying the next one...", pending_exit_addr)
# However, we should still create the FakeRet edge
self._graph_add_edge(pending_job_src_block_id, pending_job_key, jumpkind="Ijk_FakeRet",
stmt_idx=pending_job_src_exit_stmt_idx, ins_addr=pending_job.src_exit_ins_addr)
return None
pending_job_state.history.jumpkind = 'Ijk_FakeRet'
job = CFGJob(pending_job_state.addr,
pending_job_state,
self._context_sensitivity_level,
src_block_id=pending_job_src_block_id,
src_exit_stmt_idx=pending_job_src_exit_stmt_idx,
src_ins_addr=pending_job.src_exit_ins_addr,
call_stack=pending_job_call_stack,
)
l.debug("Tracing a missing return exit %s", self._block_id_repr(pending_job_key))
return job | [
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| Retrieve a pending job.
:return: A CFGJob instance or None | [
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]
| python | train |
tensorpack/tensorpack | tensorpack/tfutils/common.py | https://github.com/tensorpack/tensorpack/blob/d7a13cb74c9066bc791d7aafc3b744b60ee79a9f/tensorpack/tfutils/common.py#L113-L125 | def get_tensors_by_names(names):
"""
Get a list of tensors in the default graph by a list of names.
Args:
names (list):
"""
ret = []
G = tfv1.get_default_graph()
for n in names:
opn, varn = get_op_tensor_name(n)
ret.append(G.get_tensor_by_name(varn))
return ret | [
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| Get a list of tensors in the default graph by a list of names.
Args:
names (list): | [
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| python | train |
saltstack/salt | salt/modules/consul.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/consul.py#L471-L504 | def agent_members(consul_url=None, token=None, **kwargs):
'''
Returns the members as seen by the local serf agent
:param consul_url: The Consul server URL.
:return: Returns the members as seen by the local serf agent
CLI Example:
.. code-block:: bash
salt '*' consul.agent_members
'''
ret = {}
query_params = {}
if not consul_url:
consul_url = _get_config()
if not consul_url:
log.error('No Consul URL found.')
ret['message'] = 'No Consul URL found.'
ret['res'] = False
return ret
if 'wan' in kwargs:
query_params['wan'] = kwargs['wan']
function = 'agent/members'
ret = _query(consul_url=consul_url,
function=function,
token=token,
method='GET',
query_params=query_params)
return ret | [
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:param consul_url: The Consul server URL.
:return: Returns the members as seen by the local serf agent
CLI Example:
.. code-block:: bash
salt '*' consul.agent_members | [
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| python | train |
GoogleCloudPlatform/datastore-ndb-python | demo/app/fibo.py | https://github.com/GoogleCloudPlatform/datastore-ndb-python/blob/cf4cab3f1f69cd04e1a9229871be466b53729f3f/demo/app/fibo.py#L32-L37 | def fibonacci(n):
"""A recursive Fibonacci to exercise task switching."""
if n <= 1:
raise ndb.Return(n)
a, b = yield fibonacci(n - 1), fibonacci(n - 2)
raise ndb.Return(a + b) | [
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| A recursive Fibonacci to exercise task switching. | [
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| python | train |
ransford/sllurp | sllurp/llrp.py | https://github.com/ransford/sllurp/blob/d744b7e17d7ba64a24d9a31bde6cba65d91ad9b1/sllurp/llrp.py#L408-L699 | def handleMessage(self, lmsg):
"""Implements the LLRP client state machine."""
logger.debug('LLRPMessage received in state %s: %s', self.state, lmsg)
msgName = lmsg.getName()
lmsg.proto = self
lmsg.peername = self.peername
# call per-message callbacks
logger.debug('starting message callbacks for %s', msgName)
for fn in self._message_callbacks[msgName]:
fn(lmsg)
logger.debug('done with message callbacks for %s', msgName)
# keepalives can occur at any time
if msgName == 'KEEPALIVE':
self.send_KEEPALIVE_ACK()
return
if msgName == 'RO_ACCESS_REPORT' and \
self.state != LLRPClient.STATE_INVENTORYING:
logger.debug('ignoring RO_ACCESS_REPORT because not inventorying')
return
if msgName == 'READER_EVENT_NOTIFICATION' and \
self.state >= LLRPClient.STATE_CONNECTED:
logger.debug('Got reader event notification')
return
logger.debug('in handleMessage(%s), there are %d Deferreds',
msgName, len(self._deferreds[msgName]))
#######
# LLRP client state machine follows. Beware: gets thorny. Note the
# order of the LLRPClient.STATE_* fields.
#######
# in DISCONNECTED, CONNECTING, and CONNECTED states, expect only
# READER_EVENT_NOTIFICATION messages.
if self.state in (LLRPClient.STATE_DISCONNECTED,
LLRPClient.STATE_CONNECTING,
LLRPClient.STATE_CONNECTED):
if msgName != 'READER_EVENT_NOTIFICATION':
logger.error('unexpected message %s while connecting', msgName)
return
if not lmsg.isSuccess():
rend = lmsg.msgdict[msgName]['ReaderEventNotificationData']
try:
status = rend['ConnectionAttemptEvent']['Status']
except KeyError:
status = '(unknown status)'
logger.fatal('Could not start session on reader: %s', status)
return
self.processDeferreds(msgName, lmsg.isSuccess())
# a Deferred to call when we get GET_READER_CAPABILITIES_RESPONSE
d = defer.Deferred()
d.addCallback(self._setState_wrapper, LLRPClient.STATE_CONNECTED)
d.addErrback(self.panic, 'GET_READER_CAPABILITIES failed')
if (self.impinj_search_mode or
self.impinj_tag_content_selector or
self.impinj_extended_configuration or
self.impinj_fixed_frequency_param):
caps = defer.Deferred()
caps.addCallback(self.send_GET_READER_CAPABILITIES,
onCompletion=d)
caps.addErrback(self.panic, 'ENABLE_IMPINJ_EXTENSIONS failed')
self.send_ENABLE_IMPINJ_EXTENSIONS(onCompletion=caps)
else:
self.send_GET_READER_CAPABILITIES(self, onCompletion=d)
elif self.state == LLRPClient.STATE_SENT_ENABLE_IMPINJ_EXTENSIONS:
logger.debug(lmsg)
if msgName != 'CUSTOM_MESSAGE':
logger.error('unexpected response %s while enabling Impinj'
'extensions', msgName)
return
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.fatal('Error %s enabling Impinj extensions: %s',
status, err)
return
logger.debug('Successfully enabled Impinj extensions')
self.processDeferreds(msgName, lmsg.isSuccess())
# in state SENT_GET_CAPABILITIES, expect GET_CAPABILITIES_RESPONSE;
# respond to this message by advancing to state CONNECTED.
elif self.state == LLRPClient.STATE_SENT_GET_CAPABILITIES:
if msgName != 'GET_READER_CAPABILITIES_RESPONSE':
logger.error('unexpected response %s getting capabilities',
msgName)
return
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.fatal('Error %s getting capabilities: %s', status, err)
return
self.capabilities = \
lmsg.msgdict['GET_READER_CAPABILITIES_RESPONSE']
logger.debug('Capabilities: %s', pprint.pformat(self.capabilities))
try:
self.parseCapabilities(self.capabilities)
except LLRPError as err:
logger.exception('Capabilities mismatch')
raise err
self.processDeferreds(msgName, lmsg.isSuccess())
d = defer.Deferred()
d.addCallback(self._setState_wrapper,
LLRPClient.STATE_SENT_GET_CONFIG)
d.addErrback(self.panic, 'GET_READER_CONFIG failed')
self.send_GET_READER_CONFIG(onCompletion=d)
elif self.state == LLRPClient.STATE_SENT_GET_CONFIG:
if msgName not in ('GET_READER_CONFIG_RESPONSE',
'DELETE_ACCESSSPEC_RESPONSE',
'DELETE_ROSPEC_RESPONSE'):
logger.error('unexpected response %s getting config',
msgName)
return
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.fatal('Error %s getting reader config: %s', status, err)
return
if msgName == 'GET_READER_CONFIG_RESPONSE':
config = lmsg.msgdict['GET_READER_CONFIG_RESPONSE']
self.configuration = self.parseReaderConfig(config)
logger.debug('Reader configuration: %s', self.configuration)
self.processDeferreds(msgName, lmsg.isSuccess())
d = defer.Deferred()
d.addCallback(self._setState_wrapper,
LLRPClient.STATE_SENT_SET_CONFIG)
d.addErrback(self.panic, 'SET_READER_CONFIG failed')
self.send_ENABLE_EVENTS_AND_REPORTS()
self.send_SET_READER_CONFIG(onCompletion=d)
elif self.state == LLRPClient.STATE_SENT_SET_CONFIG:
if msgName not in ('SET_READER_CONFIG_RESPONSE',
'GET_READER_CONFIG_RESPONSE',
'DELETE_ACCESSSPEC_RESPONSE'):
logger.error('unexpected response %s setting config',
msgName)
return
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.fatal('Error %s setting reader config: %s', status, err)
return
self.processDeferreds(msgName, lmsg.isSuccess())
if self.reset_on_connect:
d = self.stopPolitely(disconnect=False)
if self.start_inventory:
d.addCallback(self.startInventory)
elif self.start_inventory:
self.startInventory()
# in state SENT_ADD_ROSPEC, expect only ADD_ROSPEC_RESPONSE; respond to
# favorable ADD_ROSPEC_RESPONSE by enabling the added ROSpec and
# advancing to state SENT_ENABLE_ROSPEC.
elif self.state == LLRPClient.STATE_SENT_ADD_ROSPEC:
if msgName != 'ADD_ROSPEC_RESPONSE':
logger.error('unexpected response %s when adding ROSpec',
msgName)
return
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.fatal('Error %s adding ROSpec: %s', status, err)
return
self.processDeferreds(msgName, lmsg.isSuccess())
# in state SENT_ENABLE_ROSPEC, expect only ENABLE_ROSPEC_RESPONSE;
# respond to favorable ENABLE_ROSPEC_RESPONSE by starting the enabled
# ROSpec and advancing to state SENT_START_ROSPEC.
elif self.state == LLRPClient.STATE_SENT_ENABLE_ROSPEC:
if msgName != 'ENABLE_ROSPEC_RESPONSE':
logger.error('unexpected response %s when enabling ROSpec',
msgName)
return
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.fatal('Error %s enabling ROSpec: %s', status, err)
return
self.processDeferreds(msgName, lmsg.isSuccess())
# in state PAUSING, we have sent a DISABLE_ROSPEC, so expect only
# DISABLE_ROSPEC_RESPONSE. advance to state PAUSED.
elif self.state == LLRPClient.STATE_PAUSING:
if msgName != 'DISABLE_ROSPEC_RESPONSE':
logger.error('unexpected response %s '
' when disabling ROSpec', msgName)
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.error('DISABLE_ROSPEC failed with status %s: %s',
status, err)
logger.warn('Error %s disabling ROSpec: %s', status, err)
self.processDeferreds(msgName, lmsg.isSuccess())
# in state SENT_START_ROSPEC, expect only START_ROSPEC_RESPONSE;
# respond to favorable START_ROSPEC_RESPONSE by advancing to state
# INVENTORYING.
elif self.state == LLRPClient.STATE_SENT_START_ROSPEC:
if msgName == 'RO_ACCESS_REPORT':
return
if msgName == 'READER_EVENT_NOTIFICATION':
return
if msgName != 'START_ROSPEC_RESPONSE':
logger.error('unexpected response %s when starting ROSpec',
msgName)
if not lmsg.isSuccess():
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.error('START_ROSPEC failed with status %s: %s',
status, err)
logger.fatal('Error %s starting ROSpec: %s', status, err)
return
self.processDeferreds(msgName, lmsg.isSuccess())
elif self.state == LLRPClient.STATE_INVENTORYING:
if msgName not in ('RO_ACCESS_REPORT',
'READER_EVENT_NOTIFICATION',
'ADD_ACCESSSPEC_RESPONSE',
'ENABLE_ACCESSSPEC_RESPONSE',
'DISABLE_ACCESSSPEC_RESPONSE',
'DELETE_ACCESSSPEC_RESPONSE'):
logger.error('unexpected message %s while inventorying',
msgName)
return
self.processDeferreds(msgName, lmsg.isSuccess())
elif self.state == LLRPClient.STATE_SENT_DELETE_ACCESSSPEC:
if msgName != 'DELETE_ACCESSSPEC_RESPONSE':
logger.error('unexpected response %s when deleting AccessSpec',
msgName)
self.processDeferreds(msgName, lmsg.isSuccess())
elif self.state == LLRPClient.STATE_SENT_DELETE_ROSPEC:
if msgName != 'DELETE_ROSPEC_RESPONSE':
logger.error('unexpected response %s when deleting ROSpec',
msgName)
if lmsg.isSuccess():
if self.disconnecting:
self.setState(LLRPClient.STATE_DISCONNECTED)
else:
self.setState(LLRPClient.STATE_CONNECTED)
else:
status = lmsg.msgdict[msgName]['LLRPStatus']['StatusCode']
err = lmsg.msgdict[msgName]['LLRPStatus']['ErrorDescription']
logger.error('DELETE_ROSPEC failed with status %s: %s',
status, err)
self.processDeferreds(msgName, lmsg.isSuccess())
if self.disconnecting:
logger.info('disconnecting')
self.transport.loseConnection()
else:
logger.warn('message %s received in unknown state!', msgName)
if self._deferreds[msgName]:
logger.error('there should NOT be Deferreds left for %s,'
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| python | train |
Komnomnomnom/swigibpy | swigibpy.py | https://github.com/Komnomnomnom/swigibpy/blob/cfd307fdbfaffabc69a2dc037538d7e34a8b8daf/swigibpy.py#L1250-L1252 | def reqScannerSubscription(self, tickerId, subscription, scannerSubscriptionOptions):
"""reqScannerSubscription(EClient self, int tickerId, ScannerSubscription subscription, TagValueListSPtr const & scannerSubscriptionOptions)"""
return _swigibpy.EClient_reqScannerSubscription(self, tickerId, subscription, scannerSubscriptionOptions) | [
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| python | train |
Murali-group/halp | halp/undirected_hypergraph.py | https://github.com/Murali-group/halp/blob/6eb27466ba84e2281e18f93b62aae5efb21ef8b3/halp/undirected_hypergraph.py#L489-L522 | def remove_hyperedge(self, hyperedge_id):
"""Removes a hyperedge and its attributes from the hypergraph.
:param hyperedge_id: ID of the hyperedge to be removed.
:raises: ValueError -- No such hyperedge exists.
Examples:
::
>>> H = UndirectedHypergraph()
>>> hyperedge_list = (["A", "B", "C"],
("A", "D"),
set(["B", "D"]))
>>> hyperedge_ids = H.add_hyperedges(hyperedge_list)
>>> H.remove_hyperedge(hyperedge_ids[0])
>>> BD_id = H.get_hyperedge_id(set(["B", "D"]))
>>> H.remove_hyperedge(BD_id)
"""
if not self.has_hyperedge_id(hyperedge_id):
raise ValueError("No such hyperedge exists.")
frozen_nodes = \
self._hyperedge_attributes[hyperedge_id]["__frozen_nodes"]
# Remove this hyperedge from the star of every node in the hyperedge
for node in frozen_nodes:
self._star[node].remove(hyperedge_id)
# Remove this set as the composer of the hyperedge
del self._node_set_to_hyperedge[frozen_nodes]
# Remove hyperedge's attributes dictionary
del self._hyperedge_attributes[hyperedge_id] | [
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| python | train |
bastikr/boolean.py | boolean/boolean.py | https://github.com/bastikr/boolean.py/blob/e984df480afc60605e9501a0d3d54d667e8f7dbf/boolean/boolean.py#L1031-L1038 | def literalize(self):
"""
Return an expression where NOTs are only occurring as literals.
"""
expr = self.demorgan()
if isinstance(expr, self.__class__):
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| python | train |
inasafe/inasafe | safe/common/utilities.py | https://github.com/inasafe/inasafe/blob/831d60abba919f6d481dc94a8d988cc205130724/safe/common/utilities.py#L466-L477 | def create_label(label_tuple, extra_label=None):
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a and b are string.
The output will be something like:
[a - b] extra_label
"""
if extra_label is not None:
return '[' + ' - '.join(label_tuple) + '] ' + str(extra_label)
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| python | train |
Azure/blobxfer | blobxfer/models/download.py | https://github.com/Azure/blobxfer/blob/3eccbe7530cc6a20ab2d30f9e034b6f021817f34/blobxfer/models/download.py#L132-L149 | def ensure_path_exists(self):
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"""Ensure path exists
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"""
if self._is_dir is None:
raise RuntimeError('is_dir not set')
if self._is_dir:
self._path.mkdir(mode=0o750, parents=True, exist_ok=True)
else:
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raise RuntimeError(
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| python | train |
espressif/esptool | esptool.py | https://github.com/espressif/esptool/blob/c583756c118039cfcfe256f7a3285618914d16a5/esptool.py#L888-L904 | def read_status(self, num_bytes=2):
"""Read up to 24 bits (num_bytes) of SPI flash status register contents
via RDSR, RDSR2, RDSR3 commands
Not all SPI flash supports all three commands. The upper 1 or 2
bytes may be 0xFF.
"""
SPIFLASH_RDSR = 0x05
SPIFLASH_RDSR2 = 0x35
SPIFLASH_RDSR3 = 0x15
status = 0
shift = 0
for cmd in [SPIFLASH_RDSR, SPIFLASH_RDSR2, SPIFLASH_RDSR3][0:num_bytes]:
status += self.run_spiflash_command(cmd, read_bits=8) << shift
shift += 8
return status | [
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| python | train |
thiezn/iperf3-python | iperf3/iperf3.py | https://github.com/thiezn/iperf3-python/blob/094a6e043f44fb154988348603661b1473c23a50/iperf3/iperf3.py#L552-L555 | def num_streams(self):
"""The number of streams to use."""
self._num_streams = self.lib.iperf_get_test_num_streams(self._test)
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| python | train |
drj11/pypng | code/iccp.py | https://github.com/drj11/pypng/blob/b8220ca9f58e4c5bc1d507e713744fcb8c049225/code/iccp.py#L159-L204 | def writeHeader(self, out, size=999):
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profile must be specified using the `size` argument.
"""
def defaultkey(d, key, value):
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"""
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colourspace=z,
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acsp='acsp',
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intent=0,
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# Convert to struct.pack input
hl[1] = int(hl[1], 16)
out.write(struct.pack('>L4sL4s4s4s12s4s4sL4sLQL12s4s', size, *hl))
out.write('\x00' * 44)
return self | [
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| python | train |
rGunti/CarPi-OBDDaemon | obddaemon/custom/Obd2DataParser.py | https://github.com/rGunti/CarPi-OBDDaemon/blob/6831c477b2a00617a0d2ea98b28f3bc5c1ba8e5f/obddaemon/custom/Obd2DataParser.py#L266-L280 | def parse_0134_013b(v):
"""
Parses the O2 Sensor Value (0134 - 013B) and returns two values parsed from it:
1. Fuel-Air Equivalence [Ratio] as a float from 0 - 2
2. Current in [mA] as a float from -128 - 128
:param str v:
:return tuple of float, float:
"""
try:
trim_val = trim_obd_value(v)
val_ab = int(trim_val[0:2], 16)
val_cd = int(trim_val[2:4], 16)
return (2 / 65536) * val_ab, val_cd - 128
except ValueError:
return None, None | [
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| python | train |
GiulioRossetti/ndlib | ndlib/models/DynamicCompostiteModel.py | https://github.com/GiulioRossetti/ndlib/blob/23ecf50c0f76ff2714471071ab9ecb600f4a9832/ndlib/models/DynamicCompostiteModel.py#L30-L70 | def iteration(self, node_status=True):
"""
Execute a single model iteration
:return: Iteration_id, Incremental node status (dictionary node->status)
"""
self.clean_initial_status(self.available_statuses.values())
actual_status = {node: nstatus for node, nstatus in future.utils.iteritems(self.status)}
if self.actual_iteration == 0:
self.actual_iteration += 1
delta, node_count, status_delta = self.status_delta(actual_status)
if node_status:
return {"iteration": 0, "status": actual_status.copy(),
"node_count": node_count.copy(), "status_delta": status_delta.copy()}
else:
return {"iteration": 0, "status": {},
"node_count": node_count.copy(), "status_delta": status_delta.copy()}
for u in self.graph.nodes():
u_status = self.status[u]
for i in range(0, self.compartment_progressive):
if u_status == self.available_statuses[self.compartment[i][0]]:
rule = self.compartment[i][2]
test = rule.execute(node=u, graph=self.graph, status=self.status,
status_map=self.available_statuses, params=self.params)
if test:
actual_status[u] = self.available_statuses[self.compartment[i][1]]
break
delta, node_count, status_delta = self.status_delta(actual_status)
self.status = actual_status
self.actual_iteration += 1
if node_status:
return {"iteration": self.actual_iteration - 1, "status": delta.copy(),
"node_count": node_count.copy(), "status_delta": status_delta.copy()}
else:
return {"iteration": self.actual_iteration - 1, "status": {},
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| python | train |
FutunnOpen/futuquant | futuquant/trade/trade_query.py | https://github.com/FutunnOpen/futuquant/blob/1512b321845f92ec9c578ce2689aa4e8482669e4/futuquant/trade/trade_query.py#L143-L158 | def pack_req(cls, code, pl_ratio_min,
pl_ratio_max, trd_env, acc_id, trd_mkt, conn_id):
"""Convert from user request for trading days to PLS request"""
from futuquant.common.pb.Trd_GetPositionList_pb2 import Request
req = Request()
req.c2s.header.trdEnv = TRD_ENV_MAP[trd_env]
req.c2s.header.accID = acc_id
req.c2s.header.trdMarket = TRD_MKT_MAP[trd_mkt]
if code:
req.c2s.filterConditions.codeList.append(code)
if pl_ratio_min is not None:
req.c2s.filterPLRatioMin = float(pl_ratio_min) / 100.0
if pl_ratio_max is not None:
req.c2s.filterPLRatioMax = float(pl_ratio_max) / 100.0
return pack_pb_req(req, ProtoId.Trd_GetPositionList, conn_id) | [
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| python | train |
theislab/scanpy | scanpy/_exporting.py | https://github.com/theislab/scanpy/blob/9e4e5ee02e04cf618872d9b098e24f0542e8b227/scanpy/_exporting.py#L231-L250 | def write_hdf5_genes(E, gene_list, filename):
'''SPRING standard: filename = main_spring_dir + "counts_norm_sparse_genes.hdf5"'''
E = E.tocsc()
hf = h5py.File(filename, 'w')
counts_group = hf.create_group('counts')
cix_group = hf.create_group('cell_ix')
hf.attrs['ncells'] = E.shape[0]
hf.attrs['ngenes'] = E.shape[1]
for iG, g in enumerate(gene_list):
counts = E[:,iG].A.squeeze()
cell_ix = np.nonzero(counts)[0]
counts = counts[cell_ix]
counts_group.create_dataset(g, data = counts)
cix_group.create_dataset(g, data = cell_ix)
hf.close() | [
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| python | train |
Unidata/MetPy | metpy/plots/_util.py | https://github.com/Unidata/MetPy/blob/16f68a94919b9a82dcf9cada2169cf039129e67b/metpy/plots/_util.py#L103-L128 | def add_metpy_logo(fig, x=10, y=25, zorder=100, size='small', **kwargs):
"""Add the MetPy logo to a figure.
Adds an image of the MetPy logo to the figure.
Parameters
----------
fig : `matplotlib.figure`
The `figure` instance used for plotting
x : int
x position padding in pixels
y : float
y position padding in pixels
zorder : int
The zorder of the logo
size : str
Size of logo to be used. Can be 'small' for 75 px square or 'large' for
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Returns
-------
`matplotlib.image.FigureImage`
The `matplotlib.image.FigureImage` instance created
"""
return _add_logo(fig, x=x, y=y, zorder=zorder, which='metpy', size=size, **kwargs) | [
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| python | train |
estnltk/estnltk | estnltk/wordnet/eurown.py | https://github.com/estnltk/estnltk/blob/28ae334a68a0673072febc318635f04da0dcc54a/estnltk/wordnet/eurown.py#L2037-L2045 | def addInternalLink(self, link):
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| python | train |
brainiak/brainiak | brainiak/fcma/voxelselector.py | https://github.com/brainiak/brainiak/blob/408f12dec2ff56559a26873a848a09e4c8facfeb/brainiak/fcma/voxelselector.py#L255-L282 | def _worker(self, clf):
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clf: classification function
the classifier to be used in cross validation
Returns
-------
None
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comm = MPI.COMM_WORLD
status = MPI.Status()
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comm.send(self._voxel_scoring(task, clf),
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| python | train |
nugget/python-insteonplm | insteonplm/tools.py | https://github.com/nugget/python-insteonplm/blob/65548041f1b0729ae1ae904443dd81b0c6cbf1bf/insteonplm/tools.py#L127-L131 | def async_aldb_loaded_callback(self):
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self.aldb_load_lock.release()
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| python | train |
pytorch/text | torchtext/vocab.py | https://github.com/pytorch/text/blob/26bfce6869dc704f1d86792f9a681d453d7e7bb8/torchtext/vocab.py#L167-L189 | def set_vectors(self, stoi, vectors, dim, unk_init=torch.Tensor.zero_):
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Set the vectors for the Vocab instance from a collection of Tensors.
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stoi: A dictionary of string to the index of the associated vector
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if wv_index is not None:
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self.vectors[i] = unk_init(self.vectors[i]) | [
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| python | train |
core/uricore | uricore/wkz_wsgi.py | https://github.com/core/uricore/blob/dc5ef4be7bd93da4c39e5c1cbd1ae4f3ad3f1f2a/uricore/wkz_wsgi.py#L119-L134 | def readline(self, size=None):
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try:
line = self._readline(size)
except (ValueError, IOError):
return self.on_disconnect()
if size and not line:
return self.on_disconnect()
self._pos += len(line)
return line | [
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| python | train |
ladybug-tools/ladybug | ladybug/datacollection.py | https://github.com/ladybug-tools/ladybug/blob/c08b7308077a48d5612f644943f92d5b5dade583/ladybug/datacollection.py#L540-L551 | def from_json(cls, data):
"""Create a Data Collection from a dictionary.
Args:
{
"header": A Ladybug Header,
"values": An array of values,
}
"""
assert 'header' in data, 'Required keyword "header" is missing!'
assert 'values' in data, 'Required keyword "values" is missing!'
return cls(Header.from_json(data['header']), data['values']) | [
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| python | train |
mikedh/trimesh | trimesh/base.py | https://github.com/mikedh/trimesh/blob/25e059bf6d4caa74f62ffd58ce4f61a90ee4e518/trimesh/base.py#L1084-L1121 | def update_faces(self, mask):
"""
In many cases, we will want to remove specific faces.
However, there is additional bookkeeping to do this cleanly.
This function updates the set of faces with a validity mask,
as well as keeping track of normals and colors.
Parameters
---------
valid : (m) int or (len(self.faces)) bool
Mask to remove faces
"""
# if the mesh is already empty we can't remove anything
if self.is_empty:
return
mask = np.asanyarray(mask)
if mask.dtype.name == 'bool' and mask.all():
# mask removes no faces so exit early
return
# try to save face normals before dumping cache
cached_normals = self._cache['face_normals']
faces = self._data['faces']
# if Trimesh has been subclassed and faces have been moved from data
# to cache, get faces from cache.
if not util.is_shape(faces, (-1, 3)):
faces = self._cache['faces']
# actually apply the mask
self.faces = faces[mask]
# apply the mask to the visual object
self.visual.update_faces(mask)
# if our normals were the correct shape apply them
if util.is_shape(cached_normals, (-1, 3)):
self.face_normals = cached_normals[mask] | [
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| python | train |
robotools/fontParts | Lib/fontParts/base/font.py | https://github.com/robotools/fontParts/blob/d2ff106fe95f9d566161d936a645157626568712/Lib/fontParts/base/font.py#L490-L531 | def _getFlatKerning(self):
"""
This is the environment implementation of
:meth:`BaseFont.getFlatKerning`.
Subclasses may override this method.
"""
kernOrder = {
(True, True): 0, # group group
(True, False): 1, # group glyph
(False, True): 2, # glyph group
(False, False): 3, # glyph glyph
}
def kerningSortKeyFunc(pair):
g1, g2 = pair
g1grp = g1.startswith("public.kern1.")
g2grp = g2.startswith("public.kern2.")
return (kernOrder[g1grp, g2grp], pair)
flatKerning = dict()
kerning = self.kerning
groups = self.groups
for pair in sorted(self.kerning.keys(), key=kerningSortKeyFunc):
kern = kerning[pair]
(left, right) = pair
if left.startswith("public.kern1."):
left = groups.get(left, [])
else:
left = [left]
if right.startswith("public.kern2."):
right = groups.get(right, [])
else:
right = [right]
for r in right:
for l in left:
flatKerning[(l, r)] = kern
return flatKerning | [
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| python | train |
neighbordog/deviantart | deviantart/api.py | https://github.com/neighbordog/deviantart/blob/5612f1d5e2139a48c9d793d7fd19cde7e162d7b1/deviantart/api.py#L222-L295 | def browse(self, endpoint="hot", category_path="", seed="", q="", timerange="24hr", tag="", offset=0, limit=10):
"""Fetch deviations from public endpoints
:param endpoint: The endpoint from which the deviations will be fetched (hot/morelikethis/newest/undiscovered/popular/tags)
:param category_path: category path to fetch from
:param q: Search query term
:param timerange: The timerange
:param tag: The tag to browse
:param offset: the pagination offset
:param limit: the pagination limit
"""
if endpoint == "hot":
response = self._req('/browse/hot', {
"category_path":category_path,
"offset":offset,
"limit":limit
})
elif endpoint == "morelikethis":
if seed:
response = self._req('/browse/morelikethis', {
"seed":seed,
"category_path":category_path,
"offset":offset,
"limit":limit
})
else:
raise DeviantartError("No seed defined.")
elif endpoint == "newest":
response = self._req('/browse/newest', {
"category_path":category_path,
"q":q,
"offset":offset,
"limit":limit
})
elif endpoint == "undiscovered":
response = self._req('/browse/undiscovered', {
"category_path":category_path,
"offset":offset,
"limit":limit
})
elif endpoint == "popular":
response = self._req('/browse/popular', {
"category_path":category_path,
"q":q,
"timerange":timerange,
"offset":offset,
"limit":limit
})
elif endpoint == "tags":
if tag:
response = self._req('/browse/tags', {
"tag":tag,
"offset":offset,
"limit":limit
})
else:
raise DeviantartError("No tag defined.")
else:
raise DeviantartError("Unknown endpoint.")
deviations = []
for item in response['results']:
d = Deviation()
d.from_dict(item)
deviations.append(d)
return {
"results" : deviations,
"has_more" : response['has_more'],
"next_offset" : response['next_offset']
} | [
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| python | train |
SeleniumHQ/selenium | py/selenium/webdriver/common/action_chains.py | https://github.com/SeleniumHQ/selenium/blob/df40c28b41d4b3953f90eaff84838a9ac052b84a/py/selenium/webdriver/common/action_chains.py#L310-L325 | def release(self, on_element=None):
"""
Releasing a held mouse button on an element.
:Args:
- on_element: The element to mouse up.
If None, releases on current mouse position.
"""
if on_element:
self.move_to_element(on_element)
if self._driver.w3c:
self.w3c_actions.pointer_action.release()
self.w3c_actions.key_action.pause()
else:
self._actions.append(lambda: self._driver.execute(Command.MOUSE_UP, {}))
return self | [
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| python | train |
adrianliaw/PyCuber | pycuber/solver/cfop/f2l.py | https://github.com/adrianliaw/PyCuber/blob/e44b5ba48c831b964ce73d046fb813222771853f/pycuber/solver/cfop/f2l.py#L44-L53 | def estimated_position(self):
"""
Get the estimated cubie of solved pair.
"""
corner = {"D":self.cube["D"]["D"]}
edge = {}
for cubie in (corner, edge):
for face in self.pair:
cubie.update({face:self.cube[face][face]})
return (Corner(**corner), Edge(**edge)) | [
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| python | train |
umutbozkurt/django-rest-framework-mongoengine | rest_framework_mongoengine/generics.py | https://github.com/umutbozkurt/django-rest-framework-mongoengine/blob/2fe6de53907b31a5e8b742e4c6b728942b5fa4f0/rest_framework_mongoengine/generics.py#L8-L13 | def get_object_or_404(queryset, *args, **kwargs):
""" replacement of rest_framework.generics and django.shrtcuts analogues """
try:
return queryset.get(*args, **kwargs)
except (ValueError, TypeError, DoesNotExist, ValidationError):
raise Http404() | [
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| python | train |
scikit-tda/kepler-mapper | kmapper/visuals.py | https://github.com/scikit-tda/kepler-mapper/blob/d4ed39f6392b0a134dd573d7d9c4aa65fbef3a7d/kmapper/visuals.py#L212-L236 | def build_histogram(data, colorscale=None, nbins=10):
""" Build histogram of data based on values of color_function
"""
if colorscale is None:
colorscale = colorscale_default
# TODO: we should weave this method of handling colors into the normal build_histogram and combine both functions
colorscale = _colors_to_rgb(colorscale)
h_min, h_max = 0, 1
hist, bin_edges = np.histogram(data, range=(h_min, h_max), bins=nbins)
bin_mids = np.mean(np.array(list(zip(bin_edges, bin_edges[1:]))), axis=1)
histogram = []
max_bucket_value = max(hist)
sum_bucket_value = sum(hist)
for bar, mid in zip(hist, bin_mids):
height = np.floor(((bar / max_bucket_value) * 100) + 0.5)
perc = round((bar / sum_bucket_value) * 100.0, 1)
color = _map_val2color(mid, 0.0, 1.0, colorscale)
histogram.append({"height": height, "perc": perc, "color": color})
return histogram | [
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| python | train |
kivy/python-for-android | pythonforandroid/bootstraps/pygame/build/buildlib/jinja2.egg/jinja2/filters.py | https://github.com/kivy/python-for-android/blob/8e0e8056bc22e4d5bd3398a6b0301f38ff167933/pythonforandroid/bootstraps/pygame/build/buildlib/jinja2.egg/jinja2/filters.py#L338-L353 | def do_indent(s, width=4, indentfirst=False):
"""Return a copy of the passed string, each line indented by
4 spaces. The first line is not indented. If you want to
change the number of spaces or indent the first line too
you can pass additional parameters to the filter:
.. sourcecode:: jinja
{{ mytext|indent(2, true) }}
indent by two spaces and indent the first line too.
"""
indention = u' ' * width
rv = (u'\n' + indention).join(s.splitlines())
if indentfirst:
rv = indention + rv
return rv | [
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| python | train |
senaite/senaite.core | bika/lims/browser/batchfolder.py | https://github.com/senaite/senaite.core/blob/7602ce2ea2f9e81eb34e20ce17b98a3e70713f85/bika/lims/browser/batchfolder.py#L114-L120 | def before_render(self):
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| python | train |
inspirehep/refextract | refextract/documents/text.py | https://github.com/inspirehep/refextract/blob/d70e3787be3c495a3a07d1517b53f81d51c788c7/refextract/documents/text.py#L139-L164 | def remove_and_record_multiple_spaces_in_line(line):
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@param line: (string) the text line to be processed for multiple
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@return: (tuple) countaining a dictionary and a string. The
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The string that is also returned in this tuple is the line after
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"""
removed_spaces = {}
# get a collection of match objects for all instances of
# multiple-spaces found in the line:
multispace_matches = re_group_captured_multiple_space.finditer(line)
# record the number of spaces found at each match position:
for multispace in multispace_matches:
removed_spaces[multispace.start()] = \
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# now remove the multiple-spaces from the line, replacing with a
# single space at each position:
line = re_group_captured_multiple_space.sub(u' ', line)
return (removed_spaces, line) | [
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| python | train |
cloudera/cm_api | python/src/cm_api/http_client.py | https://github.com/cloudera/cm_api/blob/5d2512375bd94684b4da36df9e0d9177865ffcbb/python/src/cm_api/http_client.py#L150-L183 | def execute(self, http_method, path, params=None, data=None, headers=None):
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Submit an HTTP request.
@param http_method: GET, POST, PUT, DELETE
@param path: The path of the resource.
@param params: Key-value parameter data.
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url = self._make_url(path, params)
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self.logger.warn(
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data = None
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request = urllib2.Request(url, data)
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request.get_method = lambda: http_method
headers = self._get_headers(headers)
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request.add_header(k, v)
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self.logger.debug("%s %s" % (http_method, url))
try:
return self._opener.open(request)
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| python | train |
pydata/xarray | xarray/plot/utils.py | https://github.com/pydata/xarray/blob/6d93a95d05bdbfc33fff24064f67d29dd891ab58/xarray/plot/utils.py#L624-L649 | def _infer_interval_breaks(coord, axis=0, check_monotonic=False):
"""
>>> _infer_interval_breaks(np.arange(5))
array([-0.5, 0.5, 1.5, 2.5, 3.5, 4.5])
>>> _infer_interval_breaks([[0, 1], [3, 4]], axis=1)
array([[-0.5, 0.5, 1.5],
[ 2.5, 3.5, 4.5]])
"""
coord = np.asarray(coord)
if check_monotonic and not _is_monotonic(coord, axis=axis):
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"the `seaborn` statistical plotting library." % axis)
deltas = 0.5 * np.diff(coord, axis=axis)
if deltas.size == 0:
deltas = np.array(0.0)
first = np.take(coord, [0], axis=axis) - np.take(deltas, [0], axis=axis)
last = np.take(coord, [-1], axis=axis) + np.take(deltas, [-1], axis=axis)
trim_last = tuple(slice(None, -1) if n == axis else slice(None)
for n in range(coord.ndim))
return np.concatenate([first, coord[trim_last] + deltas, last], axis=axis) | [
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>>> _infer_interval_breaks([[0, 1], [3, 4]], axis=1)
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| python | train |
pri22296/beautifultable | beautifultable/beautifultable.py | https://github.com/pri22296/beautifultable/blob/c9638f73dff4bb1f341c9ee783e4e47f26efba0b/beautifultable/beautifultable.py#L1188-L1205 | def get_table_width(self):
"""Get the width of the table as number of characters.
Column width should be set prior to calling this method.
Returns
-------
int
Width of the table as number of characters.
"""
if self.column_count == 0:
return 0
width = sum(self._column_widths)
width += ((self._column_count - 1)
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width += termwidth(self.left_border_char)
width += termwidth(self.right_border_char)
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| python | train |
projectshift/shift-boiler | boiler/user/views_social.py | https://github.com/projectshift/shift-boiler/blob/8e6f3a3e4b9493fb6c8bd16bed160ede153bfb0b/boiler/user/views_social.py#L60-L66 | def next(self):
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next = request.args.get('next')
if next is None:
params = self.default_redirect_params
next = url_for(self.default_redirect_endpoint, **params)
return next | [
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| python | train |
tanghaibao/jcvi | jcvi/apps/bwa.py | https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/apps/bwa.py#L208-L233 | def sampe(args, opts):
"""
%prog sampe database.fasta read1.fq read2.fq
Wrapper for `bwa sampe`. Output will be read1.sam.
"""
dbfile, read1file, read2file = args
dbfile = check_index(dbfile)
sai1file = check_aln(dbfile, read1file, cpus=opts.cpus)
sai2file = check_aln(dbfile, read2file, cpus=opts.cpus)
samfile, _, unmapped = get_samfile(read1file, dbfile,
bam=opts.bam, unmapped=opts.unmapped)
if not need_update((dbfile, sai1file, sai2file), samfile):
logging.error("`{0}` exists. `bwa samse` already run.".format(samfile))
return "", samfile
cmd = "bwa sampe " + " ".join((dbfile, sai1file, sai2file,
read1file, read2file))
cmd += " " + opts.extra
if opts.cutoff:
cmd += " -a {0}".format(opts.cutoff)
if opts.uniq:
cmd += " -n 1"
return cmd, samfile | [
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| python | train |
acutesoftware/virtual-AI-simulator | vais/battle.py | https://github.com/acutesoftware/virtual-AI-simulator/blob/57de679a5b1a58c38fefe6aea58af1f3a7e79c58/vais/battle.py#L129-L145 | def show_message(self, c_attack, c_defend, result, dmg, print_console='Yes'):
"""
function to wrap the display of the battle messages
"""
perc_health_att = '[' + str(round((c_attack.stats['Health']*100) / c_attack.stats['max_health'] )) + '%]'
perc_health_def = '[' + str(round((c_defend.stats['Health']*100) / c_defend.stats['max_health'] )) + '%]'
if result == 'Miss':
txt = c_attack.name + ' ' + perc_health_att.rjust(6) + ' miss ' + c_defend.name + ' ' + perc_health_def.rjust(6)
elif result == 'Crit':
txt = c_attack.name + ' ' + perc_health_att.rjust(6) + ' CRIT ' + c_defend.name + ' ' + perc_health_def.rjust(6)
txt += ' for ' + str(dmg)
else:
txt = c_attack.name + ' ' + perc_health_att.rjust(6) + ' hits ' + c_defend.name + ' ' + perc_health_def.rjust(6)
txt += ' for ' + str(dmg)
if print_console == 'Yes':
print(txt) | [
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| python | train |
blockcypher/blockcypher-python | blockcypher/api.py | https://github.com/blockcypher/blockcypher-python/blob/7601ea21916957ff279384fd699527ff9c28a56e/blockcypher/api.py#L1143-L1171 | def get_wallet_addresses(wallet_name, api_key, is_hd_wallet=False,
zero_balance=None, used=None, omit_addresses=False, coin_symbol='btc'):
'''
Returns a list of wallet addresses as well as some meta-data
'''
assert is_valid_coin_symbol(coin_symbol)
assert api_key
assert len(wallet_name) <= 25, wallet_name
assert zero_balance in (None, True, False)
assert used in (None, True, False)
assert isinstance(omit_addresses, bool), omit_addresses
params = {'token': api_key}
kwargs = {'hd/' if is_hd_wallet else '': wallet_name} # hack!
url = make_url(coin_symbol, 'wallets', **kwargs)
if zero_balance is True:
params['zerobalance'] = 'true'
elif zero_balance is False:
params['zerobalance'] = 'false'
if used is True:
params['used'] = 'true'
elif used is False:
params['used'] = 'false'
if omit_addresses:
params['omitWalletAddresses'] = 'true'
r = requests.get(url, params=params, verify=True, timeout=TIMEOUT_IN_SECONDS)
return get_valid_json(r) | [
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| python | train |
ynop/audiomate | audiomate/corpus/io/voxforge.py | https://github.com/ynop/audiomate/blob/61727920b23a708293c3d526fa3000d4de9c6c21/audiomate/corpus/io/voxforge.py#L188-L234 | def parse_speaker_info(readme_path):
""" Parse speaker info and return tuple (idx, gender). """
idx = None
gender = issuers.Gender.UNKNOWN
age_group = issuers.AgeGroup.UNKNOWN
native_lang = None
with open(readme_path, 'r', errors='ignore') as f:
for raw_line in f:
line = raw_line.strip()
if line is not None and line is not '':
line = line.rstrip(';.')
parts = line.split(':', maxsplit=1)
if len(parts) > 1:
key = parts[0].strip().lower()
value = parts[1].strip()
if key == 'user name':
idx = value
value = value.lower()
if key == 'gender':
if value in ['männlich', 'male', 'mnnlich']:
gender = issuers.Gender.MALE
elif value in ['weiblich', 'female', '[female]']:
gender = issuers.Gender.FEMALE
if key == 'age range':
if value in ['erwachsener', 'adult', '[adult]', '[erwachsener]']:
age_group = issuers.AgeGroup.ADULT
elif value in ['senior', '[senior']:
age_group = issuers.AgeGroup.SENIOR
elif value in ['youth', 'jugendlicher', '[youth]', '[jugendlicher]']:
age_group = issuers.AgeGroup.YOUTH
elif value in ['kind', 'child']:
age_group = issuers.AgeGroup.CHILD
if key == 'language':
if value in ['de', 'ger', 'deu', '[de]']:
native_lang = 'deu'
elif value in ['en', 'eng', '[en]']:
native_lang = 'eng'
return issuers.Speaker(idx, gender=gender, age_group=age_group, native_language=native_lang) | [
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| python | train |
digidotcom/python-devicecloud | devicecloud/monitor_tcp.py | https://github.com/digidotcom/python-devicecloud/blob/32529684a348a7830a269c32601604c78036bcb8/devicecloud/monitor_tcp.py#L320-L345 | def _consume_queue(self):
"""
Continually blocks until data is on the internal queue, then calls
the session's registered callback and sends a PublishMessageReceived
if callback returned True.
"""
while True:
session, block_id, raw_data = self._queue.get()
data = json.loads(raw_data.decode('utf-8')) # decode as JSON
try:
result = session.callback(data)
if result is None:
self.log.warn("Callback %r returned None, expected boolean. Messages "
"are not marked as received unless True is returned", session.callback)
elif result:
# Send a Successful PublishMessageReceived with the
# block id sent in request
if self._write_queue is not None:
response_message = struct.pack('!HHH',
PUBLISH_MESSAGE_RECEIVED,
block_id, 200)
self._write_queue.put((session.socket, response_message))
except Exception as exception:
self.log.exception(exception)
self._queue.task_done() | [
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| python | train |
kelproject/pykube | pykube/config.py | https://github.com/kelproject/pykube/blob/e8a46298a592ad9037587afb707ac75b3114eff9/pykube/config.py#L184-L188 | def user(self):
"""
Returns the current user set by current context
"""
return self.users.get(self.contexts[self.current_context].get("user", ""), {}) | [
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| python | train |
lacava/few | few/variation.py | https://github.com/lacava/few/blob/5c72044425e9a5d73b8dc2cbb9b96e873dcb5b4a/few/variation.py#L174-L176 | def mutate(self,p_i,func_set,term_set): #, max_depth=2
"""point mutation, addition, removal"""
self.point_mutate(p_i,func_set,term_set) | [
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| python | train |
pivotal-energy-solutions/django-datatable-view | datatableview/helpers.py | https://github.com/pivotal-energy-solutions/django-datatable-view/blob/00b77a9b5051c34e258c51b06c020e92edf15034/datatableview/helpers.py#L289-L399 | def make_xeditable(instance=None, extra_attrs=[], *args, **kwargs):
"""
Converts the contents of the column into an ``<a>`` tag with the required DOM attributes to
power the X-Editable UI.
The following keyword arguments are all optional, but may be provided when pre-calling the
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* ``type`` - Defaults to the basic type of the HTML input ("text", "number", "datetime")
* ``title`` - Defaults to an empty string, controls the HTML "title" attribute.
* ``placeholder`` - Defaults to whatever "title" is, controls the HTML "placeholder" attribute.
* ``url`` - Defaults to the ``request.path`` of the view, which will automatically serve the X-Editable interface as long as it inherits from ``XEditableDatatableView``.
* ``source`` - Defaults to the ``request.path`` of the view, which will automatically serve X-Editable requests for ``choices`` data about a field.
Supplying a list of names via ``extra_attrs`` will enable arbitrary other keyword arguments to
be rendered in the HTML as attribute as well. ``extra_attrs`` serves as a whitelist of extra
names so that unintended kwargs don't get rendered without your permission.
"""
if instance is None:
# Preloading kwargs into the helper for deferred execution
helper = partial(make_xeditable, extra_attrs=extra_attrs, *args, **kwargs)
return helper
# Immediate finalization, return the xeditable structure
data = kwargs.get('default_value', instance)
rich_data = kwargs.get('rich_value', data)
# Compile values to appear as "data-*" attributes on the anchor tag
default_attr_names = ['pk', 'type', 'url', 'source', 'title', 'placeholder']
valid_attr_names = set(default_attr_names + list(extra_attrs))
attrs = {}
for k, v in kwargs.items():
if k in valid_attr_names:
if k.startswith('data_'):
k = k[5:]
attrs['data-{0}'.format(k)] = v
attrs['data-xeditable'] = "xeditable"
# Assign default values where they are not provided
field_name = kwargs['field_name'] # sent as a default kwarg to helpers
if isinstance(field_name, (tuple, list)):
# Legacy syntax
field_name = field_name[1]
if isinstance(field_name, (tuple, list)):
raise ValueError("'make_xeditable' helper needs a single-field data column,"
" not {0!r}".format(field_name))
attrs['data-name'] = field_name
if isinstance(rich_data, Model):
attrs['data-value'] = rich_data.pk
else:
attrs['data-value'] = rich_data
if 'data-pk' not in attrs:
attrs['data-pk'] = instance.pk
if 'data-url' not in attrs:
# Look for a backup data-url
provider_name = 'get_update_url'
url_provider = getattr(kwargs.get('view'), provider_name, None)
if not url_provider:
url_provider = getattr(instance, provider_name, None)
if not url_provider and 'view' in kwargs:
url_provider = lambda field_name: kwargs['view'].request.path
else:
raise ValueError("'make_xeditable' cannot determine a value for 'url'.")
if url_provider:
attrs['data-url'] = url_provider(field_name=field_name)
if 'data-placeholder' not in attrs:
attrs['data-placeholder'] = attrs.get('data-title', "")
if 'data-type' not in attrs:
if hasattr(instance, '_meta'):
# Try to fetch a reasonable type from the field's class
if field_name == 'pk': # special field name not in Model._meta.fields
field = instance._meta.pk
else:
field = resolve_orm_path(instance, field_name)
if field.choices:
field_type = 'select'
else:
field_type = XEDITABLE_FIELD_TYPES.get(field.get_internal_type(), 'text')
else:
field_type = 'text'
attrs['data-type'] = field_type
# type=select elements need to fetch their valid choice options from an AJAX endpoint.
# Register the view for this lookup.
if attrs['data-type'] in ('select', 'select2'):
if 'data-source' not in attrs:
if 'view' in kwargs:
attrs['data-source'] = "{url}?{field_param}={fieldname}".format(**{
'url': kwargs['view'].request.path,
'field_param': kwargs['view'].xeditable_fieldname_param,
'fieldname': field_name,
})
if attrs['data-type'] == 'select2':
attrs['data-source'] += '&select2=true'
else:
raise ValueError("'make_xeditable' cannot determine a value for 'source'.")
# Choice fields will want to display their readable label instead of db data
data = getattr(instance, 'get_{0}_display'.format(field_name), lambda: data)()
data = u"""<a href="#"{attrs}>{data}</a>""".format(attrs=flatatt(attrs), data=data)
return data | [
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* ``source`` - Defaults to the ``request.path`` of the view, which will automatically serve X-Editable requests for ``choices`` data about a field.
Supplying a list of names via ``extra_attrs`` will enable arbitrary other keyword arguments to
be rendered in the HTML as attribute as well. ``extra_attrs`` serves as a whitelist of extra
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| python | train |
xolox/python-vcs-repo-mgr | vcs_repo_mgr/backends/git.py | https://github.com/xolox/python-vcs-repo-mgr/blob/fdad2441a3e7ba5deeeddfa1c2f5ebc00c393aed/vcs_repo_mgr/backends/git.py#L55-L58 | def get_vcs_directory(context, directory):
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nested = os.path.join(directory, '.git')
return nested if context.is_directory(nested) else directory | [
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| python | train |
Cologler/fsoopify-python | fsoopify/nodes.py | https://github.com/Cologler/fsoopify-python/blob/83d45f16ae9abdea4fcc829373c32df501487dda/fsoopify/nodes.py#L299-L303 | def has_file(self, name: str):
'''
check whether this directory contains the file.
'''
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| python | train |
JdeRobot/base | src/drivers/MAVLinkServer/MAVProxy/modules/mavproxy_map/__init__.py | https://github.com/JdeRobot/base/blob/303b18992785b2fe802212f2d758a60873007f1f/src/drivers/MAVLinkServer/MAVProxy/modules/mavproxy_map/__init__.py#L79-L92 | def show_position(self):
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pos = self.click_position
dms = (mp_util.degrees_to_dms(pos[0]), mp_util.degrees_to_dms(pos[1]))
msg = "Coordinates in WGS84\n"
msg += "Decimal: %.6f %.6f\n" % (pos[0], pos[1])
msg += "DMS: %s %s\n" % (dms[0], dms[1])
msg += "Grid: %s\n" % mp_util.latlon_to_grid(pos)
if self.logdir:
logf = open(os.path.join(self.logdir, "positions.txt"), "a")
logf.write("Position: %.6f %.6f at %s\n" % (pos[0], pos[1], time.ctime()))
logf.close()
posbox = MPMenuChildMessageDialog('Position', msg, font_size=32)
posbox.show() | [
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| python | train |
vxgmichel/aiostream | aiostream/stream/select.py | https://github.com/vxgmichel/aiostream/blob/43bdf04ab19108a3f1b5a472062e1392a26cbcf8/aiostream/stream/select.py#L82-L93 | async def filterindex(source, func):
"""Filter an asynchronous sequence using the index of the elements.
The given function is synchronous, takes the index as an argument,
and returns ``True`` if the corresponding should be forwarded,
``False`` otherwise.
"""
source = transform.enumerate.raw(source)
async with streamcontext(source) as streamer:
async for i, item in streamer:
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| python | train |
Rapptz/discord.py | discord/client.py | https://github.com/Rapptz/discord.py/blob/05d4f7f9620ef33635d6ac965b26528e09cdaf5b/discord/client.py#L740-L767 | def event(self, coro):
"""A decorator that registers an event to listen to.
You can find more info about the events on the :ref:`documentation below <discord-api-events>`.
The events must be a |corourl|_, if not, :exc:`TypeError` is raised.
Example
---------
.. code-block:: python3
@client.event
async def on_ready():
print('Ready!')
Raises
--------
TypeError
The coroutine passed is not actually a coroutine.
"""
if not asyncio.iscoroutinefunction(coro):
raise TypeError('event registered must be a coroutine function')
setattr(self, coro.__name__, coro)
log.debug('%s has successfully been registered as an event', coro.__name__)
return coro | [
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You can find more info about the events on the :ref:`documentation below <discord-api-events>`.
The events must be a |corourl|_, if not, :exc:`TypeError` is raised.
Example
---------
.. code-block:: python3
@client.event
async def on_ready():
print('Ready!')
Raises
--------
TypeError
The coroutine passed is not actually a coroutine. | [
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| python | train |
sundarnagarajan/cffi_utils | cffi_utils/py2to3.py | https://github.com/sundarnagarajan/cffi_utils/blob/1d5ab2d2fcb962372228033106bc23f1d73d31fa/cffi_utils/py2to3.py#L306-L336 | def get_rand_int(encoding='latin1', avoid=[]):
'''
encoding-->str: one of ENCODINGS
avoid-->list of int: to void (unprintable chars etc)
Returns-->int that can be converted to requested encoding
which is NOT in avoid
'''
UNICODE_LIMIT = 0x10ffff
# See: https://en.wikipedia.org/wiki/UTF-8#Invalid_code_points
SURROGATE_RANGE = (0xD800, 0xDFFF)
if encoding not in ENCODINGS:
raise ValueError('Unsupported encoding: ' + str(encoding))
if encoding == 'ascii':
maxord = 2 ** 7
elif encoding == 'latin1':
maxord = 2 ** 8
elif encoding == 'utf16':
maxord = 2 ** 16
elif encoding == 'utf8':
maxord = 2 ** 32
elif encoding == 'utf32':
maxord = 2 ** 32
rndint = random.randrange(0, min(maxord, UNICODE_LIMIT))
while (
(rndint in avoid) or
(SURROGATE_RANGE[0] <= rndint <= SURROGATE_RANGE[1])
):
rndint = random.randrange(0, min(maxord, UNICODE_LIMIT))
return rndint | [
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| python | test |
cmutel/constructive_geometries | constructive_geometries/cg.py | https://github.com/cmutel/constructive_geometries/blob/d38d7e8d5bf943a6499f3000004f1953af5970de/constructive_geometries/cg.py#L22-L27 | def has_gis(wrapped, instance, args, kwargs):
"""Skip function execution if there are no presamples"""
if gis:
return wrapped(*args, **kwargs)
else:
warn(MISSING_GIS) | [
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| python | train |
lemieuxl/pyGenClean | pyGenClean/SexCheck/sex_check.py | https://github.com/lemieuxl/pyGenClean/blob/6173a48ccc0cf3a3bd711b1f2a1fa16248b8bf55/pyGenClean/SexCheck/sex_check.py#L127-L154 | def createGenderPlot(bfile, intensities, problematic_samples, format,
out_prefix):
"""Creates the gender plot.
:param bfile: the prefix of the input binary file.
:param intensities: the file containing the intensities.
:param problematic_samples: the file containing the problematic samples.
:param format: the format of the output plot.
:param out_prefix: the prefix of the output file.
:type bfile: str
:type intensities: str
:type problematic_samples: str
:type format: str
:type out_prefix: str
Creates the gender plot of the samples using the
:py:mod:`pyGenClean.SexCheck.gender_plot` module.
"""
gender_plot_options = ["--bfile", bfile, "--intensities", intensities,
"--sex-problems", problematic_samples, "--format",
format, "--out", out_prefix]
try:
gender_plot.main(gender_plot_options)
except gender_plot.ProgramError as e:
msg = "gender plot: {}".format(e)
raise ProgramError(msg) | [
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| python | train |
Neurita/boyle | boyle/dicom/sets.py | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L151-L171 | def get_dcm_reader(store_metadata=True, header_fields=None):
"""
Creates a lambda function to read DICOM files.
If store_store_metadata is False, will only return the file path.
Else if you give header_fields, will return only the set of of
header_fields within a DicomFile object or the whole DICOM file if
None.
:return: function
This function has only one parameter: file_path
"""
if not store_metadata:
return lambda fpath: fpath
if header_fields is None:
build_dcm = lambda fpath: DicomFile(fpath)
else:
dicom_header = namedtuple('DicomHeader', header_fields)
build_dcm = lambda fpath: dicom_header._make(DicomFile(fpath).get_attributes(header_fields))
return build_dcm | [
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| python | valid |
robhowley/nhlscrapi | nhlscrapi/games/playbyplay.py | https://github.com/robhowley/nhlscrapi/blob/2273683497ff27b0e92c8d1557ff0ce962dbf43b/nhlscrapi/games/playbyplay.py#L84-L102 | def compute_stats(self):
"""
Compute the stats defined in ``self.cum_stats``.
:returns: collection of all computed :py:class:`.AccumulateStats`
:rtype: dict
"""
if not self.__have_stats:
if self.init_cs_teams and self.cum_stats:
self.__init_cs_teams()
for play in self._rep_reader.parse_plays_stream():
p = Play(**play)
self.__wrapped_plays.append(p)
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self.__process(p, self.cum_stats, 'update')
self.__have_stats = True
return self.cum_stats | [
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| python | train |
Kortemme-Lab/klab | klab/bio/uniprot.py | https://github.com/Kortemme-Lab/klab/blob/6d410ad08f1bd9f7cbbb28d7d946e94fbaaa2b6b/klab/bio/uniprot.py#L52-L122 | def uniprot_map(from_scheme, to_scheme, list_of_from_ids, cache_dir = None, silent = True):
'''Maps from one ID scheme to another using the UniProt service.
list_of_ids should be a list of strings.
This function was adapted from http://www.uniprot.org/faq/28#id_mapping_examples which also gives examples of
valid values for from_scheme and to_scheme.
Note that some conversions are not directly possible e.g. PDB_ID (PDB) to UPARC (UniParc). They need to go through
an intermediary format like ACC (UniProtKB AC) or ID (UniProtKB ID).
This function returns a dict mapping the IDs in from_scheme to a list of sorted IDs in to_scheme.
'''
try:
assert(hasattr(list_of_from_ids, '__iter__'))
except:
raise Exception('The list_of_from_ids argument should be an iterable type (e.g. list).')
full_mapping = {}
cached_mapping_file = None
if cache_dir:
cached_mapping_file = os.path.join(cache_dir, '%s.%s' % (from_scheme, to_scheme))
if os.path.exists(cached_mapping_file):
full_mapping = simplejson.loads(read_file(cached_mapping_file))
list_of_from_ids = set(list_of_from_ids)
requested_mapping = {}
remaining_ids = []
for id in list_of_from_ids:
if full_mapping.get(id):
requested_mapping[id] = full_mapping[id]
else:
remaining_ids.append(id)
assert(set(remaining_ids + requested_mapping.keys()) == set(list_of_from_ids))
if remaining_ids:
if not silent:
print("Getting %s->%s mapping" % (from_scheme, to_scheme))
url = 'http://www.uniprot.org/mapping/'
params = {
'from' : from_scheme,
'to' : to_scheme,
'format' : 'tab',
'query' : ' '.join(sorted(list(list_of_from_ids))),
}
data = urllib.urlencode(params)
request = urllib2.Request(url, data)
contact = "" # Please set your email address here to help us debug in case of problems.
request.add_header('User-Agent', 'Python %s' % contact)
response = urllib2.urlopen(request)
page = response.read(200000)
lines = page.split("\n")
assert(lines[-1] == '')
assert(lines[0].split("\t") == ['From', 'To'])
for line in lines[1:-1]:
tokens = line.split("\t")
assert(len(tokens) == 2)
assert(tokens[0] in list_of_from_ids)
full_mapping[tokens[0]] = full_mapping.get(tokens[0], [])
full_mapping[tokens[0]].append(tokens[1])
requested_mapping[tokens[0]] = requested_mapping.get(tokens[0], [])
requested_mapping[tokens[0]].append(tokens[1])
# Sort the IDs
for k, v in requested_mapping.iteritems():
#assert(len(v) == len(set(v)))
requested_mapping[k] = sorted(set(v))
for k, v in full_mapping.iteritems():
#assert(len(v) == len(set(v)))
full_mapping[k] = sorted(set(v))
if remaining_ids and cached_mapping_file:
write_file(cached_mapping_file, simplejson.dumps(full_mapping))
return requested_mapping | [
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| Maps from one ID scheme to another using the UniProt service.
list_of_ids should be a list of strings.
This function was adapted from http://www.uniprot.org/faq/28#id_mapping_examples which also gives examples of
valid values for from_scheme and to_scheme.
Note that some conversions are not directly possible e.g. PDB_ID (PDB) to UPARC (UniParc). They need to go through
an intermediary format like ACC (UniProtKB AC) or ID (UniProtKB ID).
This function returns a dict mapping the IDs in from_scheme to a list of sorted IDs in to_scheme. | [
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| python | train |
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