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malwaredllc/byob | 3924dd6aea6d0421397cdf35f692933b340bfccf | web-gui/buildyourownbotnet/core/util.py | python | public_ip | () | return urlopen('http://api.ipify.org').read().decode() | Return public IP address of host machine | Return public IP address of host machine | [
"Return",
"public",
"IP",
"address",
"of",
"host",
"machine"
] | def public_ip():
"""
Return public IP address of host machine
"""
import sys
if sys.version_info[0] > 2:
from urllib.request import urlopen
else:
from urllib import urlopen
return urlopen('http://api.ipify.org').read().decode() | [
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OCA/l10n-spain | 99050907670a70307fcd8cdfb6f3400d9e120df4 | l10n_es_vat_book/models/l10n_es_vat_book.py | python | L10nEsVatBook._prepare_vat_book_tax_summary | (self, tax_lines, book_type) | return tax_summary_data_recs | [] | def _prepare_vat_book_tax_summary(self, tax_lines, book_type):
tax_summary_data_recs = {}
for tax_line in tax_lines:
if tax_line.tax_id not in tax_summary_data_recs:
tax_summary_data_recs[tax_line.tax_id] = {
"book_type": book_type,
"base_amount": 0.0,
"tax_amount": 0.0,
"total_amount": 0.0,
"tax_id": tax_line.tax_id.id,
"vat_book_id": self.id,
"special_tax_group": tax_line.special_tax_group,
}
tax_summary_data_recs[tax_line.tax_id][
"base_amount"
] += tax_line.base_amount
tax_summary_data_recs[tax_line.tax_id]["tax_amount"] += tax_line.tax_amount
tax_summary_data_recs[tax_line.tax_id][
"total_amount"
] += tax_line.total_amount
return tax_summary_data_recs | [
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mozillazg/pypy | 2ff5cd960c075c991389f842c6d59e71cf0cb7d0 | pypy/objspace/std/bytearrayobject.py | python | BytearrayDocstrings.__init__ | () | x.__init__(...) initializes x; see help(type(x)) for signature | x.__init__(...) initializes x; see help(type(x)) for signature | [
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"""x.__init__(...) initializes x; see help(type(x)) for signature""" | [
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pwnieexpress/pwn_plug_sources | 1a23324f5dc2c3de20f9c810269b6a29b2758cad | src/metagoofil/pdfminer/pdffont.py | python | PDFFont.decode | (self, bytes) | return map(ord, bytes) | [] | def decode(self, bytes):
return map(ord, bytes) | [
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telegraphic/hickle | a5aac2db4e236d90990e3387c5822b466e8e84fa | hickle/lookup.py | python | ExpandReferenceContainer.convert | (self) | return self._content[0] | returns the object the reference was pointing to | returns the object the reference was pointing to | [
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"""
returns the object the reference was pointing to
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tendenci/tendenci | 0f2c348cc0e7d41bc56f50b00ce05544b083bf1d | tendenci/apps/recurring_payments/authnet/cim.py | python | CIMCustomerPaymentProfile.delete | (self, **kwargs) | return self.process_request(xml_root) | Delete a customer payment profile from an existing customer profile.
Input fields:
ref_id - optional
customer_profile_id
customer_payment_profile_id
Output fields:
ref_id - if included in the input | Delete a customer payment profile from an existing customer profile. | [
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] | def delete(self, **kwargs):
"""
Delete a customer payment profile from an existing customer profile.
Input fields:
ref_id - optional
customer_profile_id
customer_payment_profile_id
Output fields:
ref_id - if included in the input
"""
if not self.customer_profile_id or not self.customer_payment_profile_id:
raise AttributeError(_("Missing customer_profile_id or customer_payment_profile_id."))
root_name = 'deleteCustomerPaymentProfileRequest'
xml_root = self.create_base_xml(root_name)
customer_profile_id_node = ET.SubElement(xml_root, 'customerProfileId')
customer_profile_id_node.text = self.customer_profile_id
customer_payment_profile_id_node = ET.SubElement(xml_root, 'customerPaymentProfileId')
customer_payment_profile_id_node.text = self.customer_payment_profile_id
return self.process_request(xml_root) | [
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feedly/transfer-nlp | 85515b73165c299b7a9b96d3608bd4e8ee567154 | transfer_nlp/embeddings/utils.py | python | pretty_print | (results: List[Tuple[str, torch.Tensor]]) | Pretty print embedding results. | Pretty print embedding results. | [
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] | def pretty_print(results: List[Tuple[str, torch.Tensor]]):
"""
Pretty print embedding results.
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for item in results:
print("...[%.2f] - %s" % (item[1], item[0])) | [
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baidu/Senta | e5294c00a6ffc4b1284f38000f0fbf24d6554c22 | pretraining.py | python | PretrainingTrainer.__init__ | (self, params, data_set_reader, model_class) | :param params:
:param data_set_reader:
:param model_class: | :param params:
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"""
:param params:
:param data_set_reader:
:param model_class:
"""
BaseTrainer.__init__(self, params, data_set_reader, model_class) | [
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google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/server/grr_response_server/gui/api_call_router_with_approval_checks.py | python | ApiCallRouterWithApprovalChecks.CreateHuntApproval | (self, args, context=None) | return self.delegate.CreateHuntApproval(args, context=context) | [] | def CreateHuntApproval(self, args, context=None):
# Everybody can request a hunt approval.
return self.delegate.CreateHuntApproval(args, context=context) | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/tke/v20180525/models.py | python | DeleteClusterRouteTableRequest.__init__ | (self) | r"""
:param RouteTableName: 路由表名称
:type RouteTableName: str | r"""
:param RouteTableName: 路由表名称
:type RouteTableName: str | [
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r"""
:param RouteTableName: 路由表名称
:type RouteTableName: str
"""
self.RouteTableName = None | [
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Pymol-Scripts/Pymol-script-repo | bcd7bb7812dc6db1595953dfa4471fa15fb68c77 | modules/pdb2pqr/contrib/numpy-1.1.0/numpy/distutils/system_info.py | python | system_info.check_libs | (self,lib_dir,libs,opt_libs =[]) | return info | If static or shared libraries are available then return
their info dictionary.
Checks for all libraries as shared libraries first, then
static (or vice versa if self.search_static_first is True). | If static or shared libraries are available then return
their info dictionary. | [
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"""If static or shared libraries are available then return
their info dictionary.
Checks for all libraries as shared libraries first, then
static (or vice versa if self.search_static_first is True).
"""
exts = self.library_extensions()
info = None
for ext in exts:
info = self._check_libs(lib_dir,libs,opt_libs,[ext])
if info is not None:
break
if not info:
log.info(' libraries %s not found in %s', ','.join(libs), lib_dir)
return info | [
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/scipy/interpolate/fitpack2.py | python | SphereBivariateSpline.__call__ | (self, theta, phi, dtheta=0, dphi=0, grid=True) | return _BivariateSplineBase.__call__(self, theta, phi,
dx=dtheta, dy=dphi, grid=grid) | Evaluate the spline or its derivatives at given positions.
Parameters
----------
theta, phi : array_like
Input coordinates.
If `grid` is False, evaluate the spline at points
``(theta[i], phi[i]), i=0, ..., len(x)-1``. Standard
Numpy broadcasting is obeyed.
If `grid` is True: evaluate spline at the grid points
defined by the coordinate arrays theta, phi. The arrays
must be sorted to increasing order.
dtheta : int, optional
Order of theta-derivative
.. versionadded:: 0.14.0
dphi : int
Order of phi-derivative
.. versionadded:: 0.14.0
grid : bool
Whether to evaluate the results on a grid spanned by the
input arrays, or at points specified by the input arrays.
.. versionadded:: 0.14.0 | Evaluate the spline or its derivatives at given positions. | [
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"""
Evaluate the spline or its derivatives at given positions.
Parameters
----------
theta, phi : array_like
Input coordinates.
If `grid` is False, evaluate the spline at points
``(theta[i], phi[i]), i=0, ..., len(x)-1``. Standard
Numpy broadcasting is obeyed.
If `grid` is True: evaluate spline at the grid points
defined by the coordinate arrays theta, phi. The arrays
must be sorted to increasing order.
dtheta : int, optional
Order of theta-derivative
.. versionadded:: 0.14.0
dphi : int
Order of phi-derivative
.. versionadded:: 0.14.0
grid : bool
Whether to evaluate the results on a grid spanned by the
input arrays, or at points specified by the input arrays.
.. versionadded:: 0.14.0
"""
theta = np.asarray(theta)
phi = np.asarray(phi)
if theta.size > 0 and (theta.min() < 0. or theta.max() > np.pi):
raise ValueError("requested theta out of bounds.")
if phi.size > 0 and (phi.min() < 0. or phi.max() > 2. * np.pi):
raise ValueError("requested phi out of bounds.")
return _BivariateSplineBase.__call__(self, theta, phi,
dx=dtheta, dy=dphi, grid=grid) | [
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oracle/oci-python-sdk | 3c1604e4e212008fb6718e2f68cdb5ef71fd5793 | src/oci/_vendor/urllib3/_collections.py | python | HTTPHeaderDict.__setitem__ | (self, key, val) | return self._container[key.lower()] | [] | def __setitem__(self, key, val):
self._container[key.lower()] = [key, val]
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vaguileradiaz/tinfoleak | c45c33ec8faaff8cf8be4423e1d52533d8a45a96 | tinfoleak.py | python | get_information_for_timeline | () | Search info about the global timeline | Search info about the global timeline | [
"Search",
"info",
"about",
"the",
"global",
"timeline"
] | def get_information_for_timeline():
"""Search info about the global timeline"""
try:
source = Sources()
hashtag = Hashtags()
mentions = Mentions()
user_images = User_Images()
geolocation = Geolocation()
user = User()
search = Search_GeoTweets()
user_tweets = User_Tweets()
user_conversations = User_Conversations()
user_relations = User_Relations()
social_networks = Social_Networks()
followers = Followers()
friends = Friends()
lists = Lists()
collections = Collections()
favorites = Favorites()
top_words = Words_Tweets()
activity = Activity()
coordinates = ui.tb_place_lat.text() + "," + ui.tb_place_lon.text() + "," + ui.tb_place_km.text() + "km"
show_ui_message("Looking info at <b>global timeline</b>:", "INFO", 1)
show_ui_message("Getting timeline information...", "INFO", 1)
tmp_api = api.get_user("vaguileradiaz")
user.set_user_information(tmp_api)
results = search.set_search_information(hashtag, mentions, user_images, user_tweets, source, activity, top_words)
show_ui_message("Timeline information: OK", "INFO", 1)
if results:
if ui.cb_hashtags.isChecked():
hashtag.set_global_information()
if ui.cb_mentions.isChecked():
mentions.set_global_information()
if ui.cb_source_apps.isChecked():
# Get info about the source apps
show_ui_message("Getting source apps...", "INFO", br=1)
source.set_global_information()
show_ui_message("Source apps: OK", "INFO", br=1)
if ui.cb_activity.isChecked():
# Get info about the user activity
show_ui_message("Getting user activity...", "INFO", br=1)
activity.set_global_information()
show_ui_message("User activity: OK", "INFO", br=1)
if ui.cb_words_frequency.isChecked():
# Get words most used
if not ui.tb_words_frequency_number.text():
show_alert_field(field=ui.tb_words_frequency_number, message="You need to specify a words number",
type="WARNING", br=1)
else:
show_ui_message("Getting words...", "INFO", br=1)
wordlist = sorted(top_words.top_words.items(), key=operator.itemgetter(1))
wordlist.reverse()
max = int(ui.tb_words_frequency_number.text())
if max > len(wordlist) - 1:
max = len(wordlist) - 1
top_words.ordered_words = wordlist[0:max]
for n in top_words.ordered_words:
top_words.total_occurrences += n[1]
show_ui_message("Words: OK", "INFO", br=1)
parameters = Parameters()
show_ui_message("Generating report...", "INFO", 1)
# Generates HTML file
generates_HTML_file(parameters, user, source, social_networks, hashtag, mentions, geolocation, user_images, user_tweets, search, user_conversations, favorites, top_words, activity, user_relations)
strPath = os.path.dirname(os.path.abspath(__file__))
strDir = parameters.html_output_directory
strFile = str(ui.tb_report_filename.text())
html_dir = strPath + "/" + strDir + "/" + strFile
show_ui_message("Report: OK", "INFO", 1)
show_ui_message("Your HTML report: <b>" + html_dir + "</b><br>", "INFO", 1)
except Exception as e:
show_ui_message(str(e) + "<br>", "ERROR", 1) | [
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daid/LegacyCura | eceece558df51845988bed55a4e667638654f7c4 | Cura/avr_isp/stk500v2.py | python | main | () | Entry point to call the stk500v2 programmer from the commandline. | Entry point to call the stk500v2 programmer from the commandline. | [
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""" Entry point to call the stk500v2 programmer from the commandline. """
import threading
if sys.argv[1] == 'AUTO':
print portList()
for port in portList():
threading.Thread(target=runProgrammer, args=(port,sys.argv[2])).start()
time.sleep(5)
else:
programmer = Stk500v2()
programmer.connect(port = sys.argv[1])
programmer.programChip(intelHex.readHex(sys.argv[2]))
sys.exit(1) | [
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spesmilo/electrum | bdbd59300fbd35b01605e66145458e5f396108e8 | electrum/gui/qt/util.py | python | ElectrumItemDelegate.__init__ | (self, tv: 'MyTreeView') | [] | def __init__(self, tv: 'MyTreeView'):
super().__init__(tv)
self.tv = tv
self.opened = None
def on_closeEditor(editor: QLineEdit, hint):
self.opened = None
self.tv.is_editor_open = False
if self.tv._pending_update:
self.tv.update()
def on_commitData(editor: QLineEdit):
new_text = editor.text()
idx = QModelIndex(self.opened)
row, col = idx.row(), idx.column()
edit_key = self.tv.get_edit_key_from_coordinate(row, col)
assert edit_key is not None, (idx.row(), idx.column())
self.tv.on_edited(idx, edit_key=edit_key, text=new_text)
self.closeEditor.connect(on_closeEditor)
self.commitData.connect(on_commitData) | [
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mudpi/mudpi-core | fb206b1136f529c7197f1e6b29629ed05630d377 | mudpi/extensions/char_display/__init__.py | python | CharDisplay.get_next_message | (self) | return self.cached_message if self.persist_display else \
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yuxiaokui/Intranet-Penetration | f57678a204840c83cbf3308e3470ae56c5ff514b | proxy/XX-Net/code/default/gae_proxy/server/lib/google/appengine/api/appinfo.py | python | ValidateHandlers | (handlers, is_include_file=False) | Validates a list of handler (URLMap) objects.
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handlers: A list of a handler (URLMap) objects.
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Args:
handlers: A list of a handler (URLMap) objects.
is_include_file: If true, indicates the we are performing validation
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"""
if not handlers:
return
for handler in handlers:
handler.FixSecureDefaults()
handler.WarnReservedURLs()
if not is_include_file:
handler.ErrorOnPositionForAppInfo() | [
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n1nj4sec/pupy | a5d766ea81fdfe3bc2c38c9bdaf10e9b75af3b39 | pupy/packages/all/pupyutils/netcreds.py | python | Netcreds.get_http_searches | (self, http_url_req, body, host) | Find search terms from URLs. Prone to false positives but rather err on that side than false negatives
search, query, ?s, &q, ?q, search?p, searchTerm, keywords, command | Find search terms from URLs. Prone to false positives but rather err on that side than false negatives
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'''
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search, query, ?s, &q, ?q, search?p, searchTerm, keywords, command
'''
false_pos = ['i.stack.imgur.com']
searched = None
if http_url_req is not None:
searched = re.search(http_search_re, http_url_req, re.IGNORECASE)
if searched is None:
searched = re.search(http_search_re, body, re.IGNORECASE)
if searched is not None and host not in false_pos:
searched = searched.group(3)
# Eliminate some false+
try:
# if it doesn't decode to utf8 it's probably not user input
searched = searched.decode('utf8')
except UnicodeDecodeError:
return
# some add sites trigger this function with single digits
if searched in [str(num) for num in range(0,10)]:
return
# nobody's making >100 character searches
if len(searched) > 100:
return
msg = 'Searched %s: %s' % (host, unquote(searched.encode('utf8')).replace('+', ' '))
return msg | [
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/models/v1_service_status.py | python | V1ServiceStatus.__eq__ | (self, other) | return self.to_dict() == other.to_dict() | Returns true if both objects are equal | Returns true if both objects are equal | [
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Fizzadar/pyinfra | ff0913d6a172966760b63fe59e55dff9ea852e0d | pyinfra/api/connectors/sshuserclient/client.py | python | SSHClient.connect | (
self,
hostname,
_pyinfra_force_forward_agent=None,
_pyinfra_ssh_config_file=None,
**kwargs
) | [] | def connect(
self,
hostname,
_pyinfra_force_forward_agent=None,
_pyinfra_ssh_config_file=None,
**kwargs
):
hostname, config, forward_agent = self.parse_config(
hostname,
kwargs,
ssh_config_file=_pyinfra_ssh_config_file,
)
config.update(kwargs)
super(SSHClient, self).connect(hostname, **config)
if _pyinfra_force_forward_agent is not None:
forward_agent = _pyinfra_force_forward_agent
if forward_agent:
# Enable SSH forwarding
session = self.get_transport().open_session()
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omz/PythonistaAppTemplate | f560f93f8876d82a21d108977f90583df08d55af | PythonistaAppTemplate/PythonistaKit.framework/pylib/site-packages/werkzeug/debug/tbtools.py | python | Frame.sourcelines | (self) | return source.decode(charset, 'replace').splitlines() | The sourcecode of the file as list of unicode strings. | The sourcecode of the file as list of unicode strings. | [
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# get sourcecode from loader or file
source = None
if self.loader is not None:
try:
if hasattr(self.loader, 'get_source'):
source = self.loader.get_source(self.module)
elif hasattr(self.loader, 'get_source_by_code'):
source = self.loader.get_source_by_code(self.code)
except Exception:
# we munch the exception so that we don't cause troubles
# if the loader is broken.
pass
if source is None:
try:
f = open(self.filename)
except IOError:
return []
try:
source = f.read()
finally:
f.close()
# already unicode? return right away
if isinstance(source, text_type):
return source.splitlines()
# yes. it should be ascii, but we don't want to reject too many
# characters in the debugger if something breaks
charset = 'utf-8'
if source.startswith(UTF8_COOKIE):
source = source[3:]
else:
for idx, match in enumerate(_line_re.finditer(source)):
match = _line_re.search(match.group())
if match is not None:
charset = match.group(1)
break
if idx > 1:
break
# on broken cookies we fall back to utf-8 too
try:
codecs.lookup(charset)
except LookupError:
charset = 'utf-8'
return source.decode(charset, 'replace').splitlines() | [
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SamSchott/maestral | a32653bac7b5a76cb326d4fd5a4fb2c11f19a2fc | src/maestral/client.py | python | DropboxClient.namespace_id | (self) | return self._namespace_id | The namespace ID of the path root currently used by the DropboxClient. All
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:meth:`update_path_root` to update the root namespace after the user joins or
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demisto/content | 5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07 | Packs/MongoDB/Integrations/MongoDBLog/MongoDBLog.py | python | read_log_json | () | return 'MongoDB - no documents/records - Log collection is empty', {}, {} | Get all log documents/records from MondoDB | Get all log documents/records from MondoDB | [
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"/",
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] | def read_log_json():
""" Get all log documents/records from MondoDB """
limit = int(demisto.args().get('limit'))
# Point to all the documents
cursor = COLLECTION.find({}, {'_id': False}).limit(limit)
# Create an empty log list
entries = []
# Iterate through those documents
if cursor is not None:
for i in cursor:
# Append log entry to list
entries.append(i)
return_json = {COLLECTION_NAME: entries}
human_readable = tableToMarkdown(f'The log documents/records for collection "{COLLECTION_NAME}"', return_json)
return human_readable, {}, {}
return 'MongoDB - no documents/records - Log collection is empty', {}, {} | [
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Nuitka/Nuitka | 39262276993757fa4e299f497654065600453fc9 | nuitka/build/inline_copy/lib/scons-3.1.2/SCons/Executor.py | python | get_NullEnvironment | () | return nullenv | Use singleton pattern for Null Environments. | Use singleton pattern for Null Environments. | [
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"""Use singleton pattern for Null Environments."""
global nullenv
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return nullenv | [
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iduta/iresnet | babdc4f5946f64905710cd64a5bd6c164a805c9e | models/iresnet.py | python | iresnet200 | (pretrained=False, **kwargs) | return model | Constructs a iResNet-200 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | Constructs a iResNet-200 model. | [
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] | def iresnet200(pretrained=False, **kwargs):
"""Constructs a iResNet-200 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = iResNet(Bottleneck, [3, 24, 36, 3], **kwargs)
if pretrained:
os.makedirs(default_cache_path, exist_ok=True)
model.load_state_dict(torch.load(download_from_url(model_urls['iresnet200'],
root=default_cache_path)))
return model | [
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plaid/plaid-python | 8c60fca608e426f3ff30da8857775946d29e122c | plaid/model/processor_balance_get_response.py | python | ProcessorBalanceGetResponse.__init__ | (self, account, request_id, *args, **kwargs) | ProcessorBalanceGetResponse - a model defined in OpenAPI
Args:
account (AccountBase):
request_id (str): A unique identifier for the request, which can be used for troubleshooting. This identifier, like all Plaid identifiers, is case sensitive.
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
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once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,) | ProcessorBalanceGetResponse - a model defined in OpenAPI | [
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"""ProcessorBalanceGetResponse - a model defined in OpenAPI
Args:
account (AccountBase):
request_id (str): A unique identifier for the request, which can be used for troubleshooting. This identifier, like all Plaid identifiers, is case sensitive.
Keyword Args:
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
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_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
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When traveling through a discriminator, the
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"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
self.account = account
self.request_id = request_id
for var_name, var_value in kwargs.items():
if var_name not in self.attribute_map and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self.additional_properties_type is None:
# discard variable.
continue
setattr(self, var_name, var_value) | [
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demisto/content | 5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07 | Packs/PrismaCloudCompute/Integrations/PaloAltoNetworks_PrismaCloudCompute/PaloAltoNetworks_PrismaCloudCompute.py | python | get_container_profile_list | (client: PrismaCloudComputeClient, args: dict) | return CommandResults(
outputs_prefix='PrismaCloudCompute.ProfileContainer',
outputs_key_field='_id',
outputs=containers_info,
readable_output=table,
raw_response=containers_info
) | Get information about the containers and their profile events.
Implement the command 'prisma-cloud-compute-profile-container-list'
Args:
client (PrismaCloudComputeClient): prisma-cloud-compute client.
args (dict): prisma-cloud-compute-profile-container-list command arguments.
Returns:
CommandResults: command-results object. | Get information about the containers and their profile events.
Implement the command 'prisma-cloud-compute-profile-container-list' | [
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"""
Get information about the containers and their profile events.
Implement the command 'prisma-cloud-compute-profile-container-list'
Args:
client (PrismaCloudComputeClient): prisma-cloud-compute client.
args (dict): prisma-cloud-compute-profile-container-list command arguments.
Returns:
CommandResults: command-results object.
"""
if "image_id" in args:
args["imageID"] = args.pop("image_id")
args["limit"], args["offset"] = parse_limit_and_offset_values(
limit=args.get("limit", "15"), offset=args.get("offset", "0")
)
if containers_info := client.get_container_profiles(params=assign_params(**args)):
container_description_headers = ["ContainerID", "Image", "Os", "State", "Created", "EntryPoint"]
if len(containers_info) == 1: # means we have only one container
container_info = containers_info[0]
container_description_table = tableToMarkdown(
name="Container Description",
t=get_container_description_info(container_info=container_info),
headers=container_description_headers,
removeNull=True
)
processes_table = tableToMarkdown(
name="Processes",
t=[
{
"Type": process_type,
"Md5": process.get("md5"),
"Path": process.get("path"),
"DetectionTime": parse_date_string_format(date_string=process.get("time"))
} for process_type in ["static", "behavioral"]
for process in container_info.get("processes", {}).get(process_type, "")
],
headers=["Type", "Path", "DetectionTime", "Md5"],
removeNull=True
)
table = container_description_table + processes_table
else:
table = tableToMarkdown(
name="Container Description",
t=[get_container_description_info(container_info=container_info) for container_info in containers_info],
headers=container_description_headers,
removeNull=True
)
else:
table = "No results found."
return CommandResults(
outputs_prefix='PrismaCloudCompute.ProfileContainer',
outputs_key_field='_id',
outputs=containers_info,
readable_output=table,
raw_response=containers_info
) | [
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3b1b/manim | 3ffe300f9625fea563553c4f7d16cbee81e4844e | manimlib/utils/color.py | python | get_colormap_list | (map_name="viridis", n_colors=9) | return resize_with_interpolation(np.array(rgbs), n_colors) | Options for map_name:
3b1b_colormap
magma
inferno
plasma
viridis
cividis
twilight
twilight_shifted
turbo | Options for map_name:
3b1b_colormap
magma
inferno
plasma
viridis
cividis
twilight
twilight_shifted
turbo | [
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] | def get_colormap_list(map_name="viridis", n_colors=9):
"""
Options for map_name:
3b1b_colormap
magma
inferno
plasma
viridis
cividis
twilight
twilight_shifted
turbo
"""
from matplotlib.cm import get_cmap
if map_name == "3b1b_colormap":
rgbs = [color_to_rgb(color) for color in COLORMAP_3B1B]
else:
rgbs = get_cmap(map_name).colors # Make more general?
return resize_with_interpolation(np.array(rgbs), n_colors) | [
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CGCookie/retopoflow | 3d8b3a47d1d661f99ab0aeb21d31370bf15de35e | retopoflow/rf/rf_ui.py | python | RetopoFlow_UI.update_main_tiny_ui_windows | (self) | [] | def update_main_tiny_ui_windows(self):
if self.ui_hide: return
pre = self._ui_windows_updating
self._ui_windows_updating = True
self.ui_main.is_visible = options['show main window']
self.ui_tiny.is_visible = not options['show main window']
self._ui_windows_updating = pre | [
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trakt/Plex-Trakt-Scrobbler | aeb0bfbe62fad4b06c164f1b95581da7f35dce0b | Trakttv.bundle/Contents/Libraries/Linux/armv5_hf/ucs4/cryptography/x509/base.py | python | CertificateBuilder.public_key | (self, key) | return CertificateBuilder(
self._issuer_name, self._subject_name, key,
self._serial_number, self._not_valid_before,
self._not_valid_after, self._extensions
) | Sets the requestor's public key (as found in the signing request). | Sets the requestor's public key (as found in the signing request). | [
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"""
Sets the requestor's public key (as found in the signing request).
"""
if not isinstance(key, (dsa.DSAPublicKey, rsa.RSAPublicKey,
ec.EllipticCurvePublicKey)):
raise TypeError('Expecting one of DSAPublicKey, RSAPublicKey,'
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if self._public_key is not None:
raise ValueError('The public key may only be set once.')
return CertificateBuilder(
self._issuer_name, self._subject_name, key,
self._serial_number, self._not_valid_before,
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Pymol-Scripts/Pymol-script-repo | bcd7bb7812dc6db1595953dfa4471fa15fb68c77 | modules/pdb2pqr/contrib/ZSI-2.1-a1/ZSI/twisted/client.py | python | Binding.Receive | (self, replytype, chain=None, **kw) | return pyobj | This method allows code to act in a synchronous manner, it waits to
return until the deferred fires but it doesn't prevent other queued
calls from being executed. Send must be called first, which sets up
the chain/factory.
WARNING: If defer is set to True, must either call Receive
immediately after Send (ie. no intervening Sends) or pass
chain in as a paramter.
Parameters:
replytype -- TypeCode
KeyWord Parameters:
chain -- processing chain, optional | This method allows code to act in a synchronous manner, it waits to
return until the deferred fires but it doesn't prevent other queued
calls from being executed. Send must be called first, which sets up
the chain/factory.
WARNING: If defer is set to True, must either call Receive
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Parameters:
replytype -- TypeCode
KeyWord Parameters:
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calls from being executed. Send must be called first, which sets up
the chain/factory.
WARNING: If defer is set to True, must either call Receive
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Parameters:
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chain -- processing chain, optional
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chain = chain or self.chain
d = chain.flow.deferred
if self.trace:
def trace(soapdata):
print >>self.trace, "_" * 33, time.ctime(time.time()), "RESPONSE:"
print >>self.trace, soapdata
return soapdata
d.addCallback(trace)
chain.processResponse(d, replytype, **kw)
if self.defer:
return d
failure = []
append = failure.append
def errback(result):
"""Used with Response method to suppress 'Unhandled error in
Deferred' messages by adding an errback.
"""
append(result)
return None
d.addErrback(errback)
# spin reactor
while not d.called:
reactor.runUntilCurrent()
t2 = reactor.timeout()
t = reactor.running and t2
reactor.doIteration(t)
pyobj = d.result
if len(failure):
failure[0].raiseException()
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FabriceSalvaire/CodeReview | c48433467ac2a9a14b9c9026734f8c494af4aa95 | CodeReview/Diff/RawTextDocument.py | python | RawTextDocumentAbc.__init__ | (self, text_buffer, flat_slice, line_start_locations, line_separators) | r"""The parameter *text_buffer* specifies the text buffer. It must implement the method
**__getitem__** to index and slice the characters.
The parameter *flat_slice* specifies the flat slice corresponding to the text chunk.
The list *line_start_locations* contains the position of the new lines in the text chunk and
the list *line_separators* contains the corresponding new line separators. The standard
separators (``\r\n``, ``\r``, ``\n``) are supported. The list *line_start_locations* ends
by a sentinel that corresponds to the number of characters in the text chunk and the list
*line_separators* by an empty string. This sentinel corresponds to a virtual line at the
end of the text buffer. | r"""The parameter *text_buffer* specifies the text buffer. It must implement the method
**__getitem__** to index and slice the characters. | [
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r"""The parameter *text_buffer* specifies the text buffer. It must implement the method
**__getitem__** to index and slice the characters.
The parameter *flat_slice* specifies the flat slice corresponding to the text chunk.
The list *line_start_locations* contains the position of the new lines in the text chunk and
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"""
self._text_buffer = text_buffer
self._flat_slice = flat_slice
self._line_start_locations = line_start_locations
self._line_separators = line_separators | [
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riga/tfdeploy | 22aea652fe12f081be43414e0f1f76c7d9aaf53c | tfdeploy.py | python | Unique | (a, t) | return np.copy(a)[np.sort(idxs)], idxs[inv].astype(dtype_map[t]) | Unique op. | Unique op. | [
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"""
Unique op.
"""
_, idxs, inv = np.unique(a, return_index=True, return_inverse=True)
return np.copy(a)[np.sort(idxs)], idxs[inv].astype(dtype_map[t]) | [
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pika/pika | 12dcdf15d0932c388790e0fa990810bfd21b1a32 | pika/adapters/utils/selector_ioloop_adapter.py | python | _SelectorIOLoopIOHandle.cancel | (self) | return self._cancel() | Cancel pending operation
:returns: False if was already done or cancelled; True otherwise
:rtype: bool | Cancel pending operation | [
"Cancel",
"pending",
"operation"
] | def cancel(self):
"""Cancel pending operation
:returns: False if was already done or cancelled; True otherwise
:rtype: bool
"""
return self._cancel() | [
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vmware/pyvcloud | d72c615fa41b8ea5ab049a929e18d8ba6460fc59 | pyvcloud/vcd/vdc.py | python | VDC.add_access_settings | (self, access_settings_list=None) | return acl.add_access_settings(access_settings_list) | Add access settings to the vdc.
:param list access_settings_list: list of dictionaries, where each
dictionary represents a single access setting. The dictionary
structure is as follows,
- type: (str): type of the subject. One of 'org' or 'user'.
- name: (str): name of the user or org.
- access_level: (str): access_level of the particular subject.
Allowed values are 'ReadOnly', 'Change' or 'FullControl'.
:return: an object containing EntityType.CONTROL_ACCESS_PARAMS XML
data representing the updated Access Control List of the vdc.
:rtype: lxml.objectify.ObjectifiedElement | Add access settings to the vdc. | [
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"""Add access settings to the vdc.
:param list access_settings_list: list of dictionaries, where each
dictionary represents a single access setting. The dictionary
structure is as follows,
- type: (str): type of the subject. One of 'org' or 'user'.
- name: (str): name of the user or org.
- access_level: (str): access_level of the particular subject.
Allowed values are 'ReadOnly', 'Change' or 'FullControl'.
:return: an object containing EntityType.CONTROL_ACCESS_PARAMS XML
data representing the updated Access Control List of the vdc.
:rtype: lxml.objectify.ObjectifiedElement
"""
acl = Acl(self.client, self.get_resource())
return acl.add_access_settings(access_settings_list) | [
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cloudera/impyla | 0c736af4cad2bade9b8e313badc08ec50e81c948 | impala/_thrift_gen/hive_metastore/ThriftHiveMetastore.py | python | abort_txns_result.__eq__ | (self, other) | return isinstance(other, self.__class__) and self.__dict__ == other.__dict__ | [] | def __eq__(self, other):
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cisco/mindmeld | 809c36112e9ea8019fe29d54d136ca14eb4fd8db | mindmeld/components/dialogue.py | python | DialogueFlow._apply_flow_handler_sync | (self, request, responder) | return {"dialogue_state": dialogue_state, "directives": responder.directives} | Applies the dialogue state handler for the dialogue flow and set the target dialogue
state to the flow state.
Args:
request (Request): The request object.
responder (DialogueResponder): The responder object.
Returns:
(dict): A dict containing the dialogue state and directives. | Applies the dialogue state handler for the dialogue flow and set the target dialogue
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Args:
request (Request): The request object.
responder (DialogueResponder): The responder object.
Returns:
(dict): A dict containing the dialogue state and directives.
"""
dialogue_state = self._get_dialogue_state(request)
handler = self._get_dialogue_handler(dialogue_state)
if dialogue_state not in self.exit_flow_states:
responder.params.target_dialogue_state = self.flow_state
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HoverHell/RedditImageGrab | eb23ee516c98bccaa0904b9b420d603109dac37e | redditdownload/img_scrap_stuff.py | python | setdiff | (set_a, set_b) | return set_a - set_b, set_a & set_b, set_b - set_a | RTFS | RTFS | [
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""" RTFS """
set_a, set_b = set(set_a), set(set_b)
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tendenci/tendenci | 0f2c348cc0e7d41bc56f50b00ce05544b083bf1d | tendenci/apps/accounts/views.py | python | password_reset | (request) | return auth_password_reset(request, extra_context=extra_context) | [] | def password_reset(request):
from_registration = request.GET.get('registration', False)
extra_context = {
'from_registration': from_registration,
}
auth_password_reset = PasswordResetView.as_view(
form_class = PasswordResetForm,
template_name='accounts/password_reset_form.html',
email_template_name='registration/password_reset_email_user_list.html')
return auth_password_reset(request, extra_context=extra_context) | [
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PreOS-Security/fwaudit | f38d8ace3c1be487edc2d66d689aa5bb9ff07f56 | fwaudit.py | python | chipsec_test_memconfig | (toolns, tool, prd, ptd, erc) | return spawn_process(cmd, ptd, erc, toolns) | Call chipsec_main -m memconfig | Call chipsec_main -m memconfig | [
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info('Executing ' + toolns + ' variation of tool: ' + tool)
cmd = ['python', '-i', '-m', 'chipsec_main', '-m', 'memconfig']
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keiffster/program-y | 8c99b56f8c32f01a7b9887b5daae9465619d0385 | src/programy/storage/stores/nosql/mongo/store/maps.py | python | MongoMapsStore.load_all | (self, collector) | [] | def load_all(self, collector):
YLogger.info(self, "Loading all maps from Mongo")
collection = self.collection()
collector.empty()
maps = collection.find({})
for amap in maps:
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fffonion/xeHentai | 26063154a238d4df280f8d17f14d090e679084ec | xeHentai/filters.py | python | login_exhentai | (r, suc, fail) | [] | def login_exhentai(r, suc, fail):
# input login response
# add cookies if suc; log error fail
try:
coo = r.headers.get('set-cookie')
cooid = re.findall('ipb_member_id=(.*?);', coo)[0]
coopw = re.findall('ipb_pass_hash=(.*?);', coo)[0]
except (IndexError, ) as ex:
errmsg = re.findall('<span class="postcolor">([^<]+)</span>', r.text)
if errmsg:
fail(errmsg[0])
else:
fail("ex: %s" % ex)
return FAIL
else:
suc({'ipb_member_id':cooid, 'ipb_pass_hash':coopw})
return SUC | [
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gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/plugins/view/pedigreeview.py | python | PedigreeView.attach_widget | (self, table, widget, xmax, right, left, top, bottom) | Attach a widget to the table. | Attach a widget to the table. | [
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] | def attach_widget(self, table, widget, xmax, right, left, top, bottom):
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Attach a widget to the table.
"""
if self.tree_direction == 0: # Vertical (top to bottom)
table.attach(widget, top, right, bottom-top, left-right)
elif self.tree_direction == 1: # Vertical (bottom to top)
table.attach(widget, top, xmax - left + 1, bottom-top, left - right)
elif self.tree_direction == 2: # Horizontal (left to right)
table.attach(widget, right, top, left-right, bottom-top)
elif self.tree_direction == 3: # Horizontal (right to left)
table.attach(widget, xmax - left + 1, top, left - right, bottom-top) | [
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veusz/veusz | 5a1e2af5f24df0eb2a2842be51f2997c4999c7fb | veusz/setting/controls.py | python | _EditBox.closeEvent | (self, event) | Tell the calling widget that we are closing, and provide
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text = self.toPlainText()
text = text.replace('\n', '')
self.closing.emit(text)
event.accept() | [
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jbjorne/TEES | caf19a4a1352ac59f5dc13a8684cc42ce4342d9d | Utils/Libraries/progressbar.py | python | Bar.update | (self, pbar, width) | return bar | [] | def update(self, pbar, width):
percent = pbar.percentage()
cwidth = width - len(self.left) - len(self.right)
marked_width = int(percent * cwidth / 100)
m = self._format_marker(pbar)
bar = (self.left + (m*marked_width).ljust(cwidth) + self.right)
return bar | [
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thu-coai/ConvLab-2 | ad32b76022fa29cbc2f24cbefbb855b60492985e | convlab2/evaluator/evaluator.py | python | Evaluator.add_goal | (self, goal) | init goal and array.
args:
goal:
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"""init goal and array.
args:
goal:
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"""
raise NotImplementedError | [
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dulwich/dulwich | 1f66817d712e3563ce1ff53b1218491a2eae39da | dulwich/repo.py | python | BaseRepo.get_refs | (self) | return self.refs.as_dict() | Get dictionary with all refs.
Returns: A ``dict`` mapping ref names to SHA1s | Get dictionary with all refs. | [
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] | def get_refs(self) -> Dict[bytes, bytes]:
"""Get dictionary with all refs.
Returns: A ``dict`` mapping ref names to SHA1s
"""
return self.refs.as_dict() | [
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wikimedia/pywikibot | 81a01ffaec7271bf5b4b170f85a80388420a4e78 | scripts/archivebot.py | python | PageArchiver.should_archive_thread | (self, thread: DiscussionThread
) | return None | Check whether a thread has to be archived.
:return: the archivation reason as a tuple of localization args | Check whether a thread has to be archived. | [
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Check whether a thread has to be archived.
:return: the archivation reason as a tuple of localization args
"""
# Archived by timestamp
algo = self.get_attr('algo')
re_t = re.fullmatch(r'old\((.*)\)', algo)
if re_t:
if not thread.timestamp:
return None
# TODO: handle unsigned
maxage = str2time(re_t.group(1), thread.timestamp)
if self.now - thread.timestamp > maxage:
duration = str2localized_duration(self.site, re_t.group(1))
return ('duration', duration)
# TODO: handle marked with template
return None | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/app_manager/management/commands/build_apps.py | python | record_performance_stats | (filepath, slug) | [] | def record_performance_stats(filepath, slug):
hp = hpy()
before = hp.heap()
start = time.clock()
try:
yield
finally:
end = time.clock()
after = hp.heap()
leftover = after - before
with open(filepath, 'a', encoding='utf-8') as f:
f.write('{},{},{}\n'.format(slug, leftover.size, end - start)) | [
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/contrib/admin/filters.py | python | SimpleListFilter.value | (self) | return self.used_parameters.get(self.parameter_name) | Returns the value (in string format) provided in the request's
query string for this filter, if any. If the value wasn't provided then
returns None. | Returns the value (in string format) provided in the request's
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"""
Returns the value (in string format) provided in the request's
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"""
return self.used_parameters.get(self.parameter_name) | [
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ZhihengCV/Bayesian-Crowd-Counting | 5f10bfc50ff3cb6e424e17fa970600d55094dd9f | datasets/crowd_sh.py | python | Crowd.train_transform | (self, img, keypoints) | return self.trans(img), torch.from_numpy(keypoints.copy()).float(), \
torch.from_numpy(target.copy()).float(), st_size | random crop image patch and find people in it | random crop image patch and find people in it | [
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"""random crop image patch and find people in it"""
wd, ht = img.size
st_size = min(wd, ht)
assert st_size >= self.c_size
assert len(keypoints) > 0
i, j, h, w = random_crop(ht, wd, self.c_size, self.c_size)
img = F.crop(img, i, j, h, w)
nearest_dis = np.clip(0.8*keypoints[:, 2], 4.0, 40.0)
points_left_up = keypoints[:, :2] - nearest_dis[:, None] / 2.0
points_right_down = keypoints[:, :2] + nearest_dis[:, None] / 2.0
bbox = np.concatenate((points_left_up, points_right_down), axis=1)
inner_area = cal_innner_area(j, i, j+w, i+h, bbox)
origin_area = nearest_dis * nearest_dis
ratio = np.clip(1.0 * inner_area / origin_area, 0.0, 1.0)
mask = (ratio >= 0.5)
keypoints = keypoints[mask]
keypoints = keypoints[:, :2] - [j, i] # change coodinate
target = np.ones(len(keypoints))
if len(keypoints) > 0:
if random.random() > 0.5:
img = F.hflip(img)
keypoints[:, 0] = w - keypoints[:, 0]
else:
if random.random() > 0.5:
img = F.hflip(img)
return self.trans(img), torch.from_numpy(keypoints.copy()).float(), \
torch.from_numpy(target.copy()).float(), st_size | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/pip/_vendor/requests/packages/urllib3/util/ssl_.py | python | _const_compare_digest_backport | (a, b) | return result == 0 | Compare two digests of equal length in constant time.
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"""
result = abs(len(a) - len(b))
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numba/numba | bf480b9e0da858a65508c2b17759a72ee6a44c51 | numba/core/ir.py | python | SetAttr.__init__ | (self, target, attr, value, loc) | [] | def __init__(self, target, attr, value, loc):
assert isinstance(target, Var)
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quantOS-org/JAQS | 959762a518c22592f96433c573d1f99ec0c89152 | jaqs/trade/tradeapi/trade_api.py | python | TradeApi.query_net_position | (self, mode="all", securities="", format="") | return utils.extract_result(cr, data_format=data_format, class_name="NetPosition") | securities: seperate by ","
return pd.dataframe | securities: seperate by ","
return pd.dataframe | [
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securities: seperate by ","
return pd.dataframe
"""
r, msg = self._check_session()
if not r: return (None, msg)
rpc_params = {"mode" : mode,
"security" : securities}
data_format = self._get_format(format, "pandas")
if data_format == "pandas":
rpc_params["format"] = "columnset"
cr = self._remote.call("oms.query_net_position", rpc_params)
return utils.extract_result(cr, data_format=data_format, class_name="NetPosition") | [
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thenetcircle/dino | 1047c3458e91a1b4189e9f48f1393b3a68a935b3 | dino/cache/__init__.py | python | ICache.set_global_ban_timestamp | (self, user_id: str, duration: str, timestamp: str, username: str) | set the global ban timestamp for a user to a given timestamp
:param user_id: the id of the user
:param duration: the duration, e.g. 12d
:param timestamp: the timestamp
:param username: the username of this user
:return: nothing | set the global ban timestamp for a user to a given timestamp | [
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"""
set the global ban timestamp for a user to a given timestamp
:param user_id: the id of the user
:param duration: the duration, e.g. 12d
:param timestamp: the timestamp
:param username: the username of this user
:return: nothing
""" | [
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openstack/cinder | 23494a6d6c51451688191e1847a458f1d3cdcaa5 | cinder/volume/drivers/ibm/ibm_storage/ds8k_proxy.py | python | DS8KProxy.terminate_connection | (self, volume, connector, force=False, **kwargs) | Detach a volume from a host. | Detach a volume from a host. | [
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] | def terminate_connection(self, volume, connector, force=False, **kwargs):
"""Detach a volume from a host."""
ret_info = {
'driver_volume_type': 'fibre_channel',
'data': {}
}
lun = Lun(volume)
if (lun.group and lun.failed_over) and not self._active_backend_id:
backend_helper = self._replication.get_target_helper()
else:
backend_helper = self._helper
if isinstance(backend_helper, helper.DS8KECKDHelper):
LOG.info('Detach the volume %s.', lun.ds_id)
return backend_helper.terminate_connection(lun.ds_id, connector,
force, **kwargs)
else:
vol_mapped, host_id, map_info = (
backend_helper.check_vol_mapped_to_host(connector, lun.ds_id))
if host_id is None or not vol_mapped:
if host_id is None and not lun.type_replication:
LOG.warning('Failed to find the Host information.')
return ret_info
if host_id and not lun.type_replication and not vol_mapped:
LOG.warning("Volume %(vol)s is already not mapped to "
"host %(host)s.",
{'vol': lun.ds_id, 'host': host_id})
return ret_info
if lun.type_replication:
if backend_helper == self._replication.get_target_helper():
backend_helper = self._replication.get_source_helper()
else:
backend_helper = self._replication.get_target_helper()
try:
if backend_helper.lun_exists(lun.replica_ds_id):
LOG.info('Detaching volume %s from the '
'Secondary site.', lun.replica_ds_id)
mapped, host_id, map_info = (
backend_helper.check_vol_mapped_to_host(
connector, lun.replica_ds_id))
else:
msg = (_('Failed to find the attached '
'Volume %s.') % lun.ds_id)
LOG.error(msg)
raise exception.VolumeDriverException(message=msg)
except Exception as ex:
LOG.warning('Failed to get host mapping for volume '
'%(volume)s in the secondary site. '
'Exception: %(err)s.',
{'volume': lun.replica_ds_id, 'err': ex})
return ret_info
if not mapped:
return ret_info
else:
LOG.info('Detach the volume %s.', lun.replica_ds_id)
return backend_helper.terminate_connection(
lun.replica_ds_id, host_id, connector, map_info)
elif host_id and vol_mapped:
LOG.info('Detaching volume %s.', lun.ds_id)
return backend_helper.terminate_connection(lun.ds_id, host_id,
connector, map_info) | [
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kensho-technologies/graphql-compiler | 4318443b7b2512a059f3616112bfc40bbf8eec06 | graphql_compiler/cost_estimation/statistics.py | python | LocalStatistics.__init__ | (
self,
class_counts: Dict[str, int],
*,
vertex_edge_vertex_counts: Optional[Dict[Tuple[str, str, str], int]] = None,
distinct_field_values_counts: Optional[Dict[Tuple[str, str], int]] = None,
field_quantiles: Optional[Dict[Tuple[str, str], List[Any]]] = None,
sampling_summaries: Optional[Dict[str, VertexSamplingSummary]] = None,
) | Initialize statistics with the given data.
Args:
class_counts: dict, str -> int, mapping vertex/edge class name to count of
instances of that class.
vertex_edge_vertex_counts: optional dict, (str, str, str) -> int, mapping tuple of
(vertex source class name, edge class name, vertex target
class name) to count of edge instances of given class
connecting instances of two vertex classes.
distinct_field_values_counts: optional dict, (str, str) -> int, mapping vertex class
name and property field name to the count of distinct
values of that vertex class's property field.
field_quantiles: optional dict, (str, str) -> list, mapping vertex class name
and property field name to a list of N quantiles, a sorted list of
values separating the values of the field into N-1 groups of almost
equal size. The first element of the list is the smallest known value,
and the last element is the largest known value. The i-th
element is a value greater than or equal to i/N of all present
values. The number N can be different for each entry. N has to be at
least 2 for every entry present in the dict.
sampling_summaries: optional SamplingSummaries for some classes
TODO(bojanserafimov): Enforce a canonical representation for quantile values and
sampling summaries. Datetimes should be in utc, decimals should
have type float, etc.
TODO(bojanserafimov): Validate class_counts against sample_ratio * num_samples | Initialize statistics with the given data. | [
"Initialize",
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"with",
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"."
] | def __init__(
self,
class_counts: Dict[str, int],
*,
vertex_edge_vertex_counts: Optional[Dict[Tuple[str, str, str], int]] = None,
distinct_field_values_counts: Optional[Dict[Tuple[str, str], int]] = None,
field_quantiles: Optional[Dict[Tuple[str, str], List[Any]]] = None,
sampling_summaries: Optional[Dict[str, VertexSamplingSummary]] = None,
):
"""Initialize statistics with the given data.
Args:
class_counts: dict, str -> int, mapping vertex/edge class name to count of
instances of that class.
vertex_edge_vertex_counts: optional dict, (str, str, str) -> int, mapping tuple of
(vertex source class name, edge class name, vertex target
class name) to count of edge instances of given class
connecting instances of two vertex classes.
distinct_field_values_counts: optional dict, (str, str) -> int, mapping vertex class
name and property field name to the count of distinct
values of that vertex class's property field.
field_quantiles: optional dict, (str, str) -> list, mapping vertex class name
and property field name to a list of N quantiles, a sorted list of
values separating the values of the field into N-1 groups of almost
equal size. The first element of the list is the smallest known value,
and the last element is the largest known value. The i-th
element is a value greater than or equal to i/N of all present
values. The number N can be different for each entry. N has to be at
least 2 for every entry present in the dict.
sampling_summaries: optional SamplingSummaries for some classes
TODO(bojanserafimov): Enforce a canonical representation for quantile values and
sampling summaries. Datetimes should be in utc, decimals should
have type float, etc.
TODO(bojanserafimov): Validate class_counts against sample_ratio * num_samples
"""
if vertex_edge_vertex_counts is None:
vertex_edge_vertex_counts = dict()
if distinct_field_values_counts is None:
distinct_field_values_counts = dict()
if field_quantiles is None:
field_quantiles = dict()
if sampling_summaries is None:
sampling_summaries = dict()
# Validate arguments
for (vertex_name, field_name), quantile_list in six.iteritems(field_quantiles):
if len(quantile_list) < 2:
raise AssertionError(
f"The number of quantiles should be at least 2. Field "
f"{vertex_name}.{field_name} has {len(quantile_list)}."
)
for quantile in quantile_list:
if isinstance(quantile, datetime.datetime):
if quantile.tzinfo is not None:
raise NotImplementedError(
f"Range reasoning for tz-aware datetimes is not implemented. "
f"found tz-aware quantiles for {vertex_name}.{field_name}."
)
self._class_counts = class_counts
self._vertex_edge_vertex_counts = vertex_edge_vertex_counts
self._distinct_field_values_counts = distinct_field_values_counts
self._field_quantiles = field_quantiles
self._sampling_summaries = sampling_summaries | [
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Bitmessage/PyBitmessage | 97612b049e0453867d6d90aa628f8e7b007b4d85 | src/network/bmobject.py | python | BMObject.checkObjectByType | (self) | Call a object type specific check
(objects can have additional checks based on their types) | Call a object type specific check
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"""Call a object type specific check
(objects can have additional checks based on their types)"""
if self.objectType == protocol.OBJECT_GETPUBKEY:
self.checkGetpubkey()
elif self.objectType == protocol.OBJECT_PUBKEY:
self.checkPubkey()
elif self.objectType == protocol.OBJECT_MSG:
self.checkMessage()
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self.checkBroadcast() | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/calculus/transforms/dft.py | python | IndexedSequence.list | (self) | return self._list | Return the list of ``self``.
EXAMPLES::
sage: J = list(range(10))
sage: A = [1/10 for j in J]
sage: s = IndexedSequence(A,J)
sage: s.list()
[1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10] | Return the list of ``self``. | [
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"""
Return the list of ``self``.
EXAMPLES::
sage: J = list(range(10))
sage: A = [1/10 for j in J]
sage: s = IndexedSequence(A,J)
sage: s.list()
[1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10, 1/10]
"""
return self._list | [
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stopstalk/stopstalk-deployment | 10c3ab44c4ece33ae515f6888c15033db2004bb1 | aws_lambda/spoj_aws_lambda_function/lambda_code/pip/_internal/utils/misc.py | python | consume | (iterator) | Consume an iterable at C speed. | Consume an iterable at C speed. | [
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] | def consume(iterator):
"""Consume an iterable at C speed."""
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robhagemans/pcbasic | c3a043b46af66623a801e18a38175be077251ada | pcbasic/basic/devices/devicebase.py | python | TextFileBase.__init__ | (self, fhandle, filetype, mode) | Setup the basic properties of the file. | Setup the basic properties of the file. | [
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] | def __init__(self, fhandle, filetype, mode):
"""Setup the basic properties of the file."""
RawFile.__init__(self, fhandle, filetype, mode)
# width=255 means line wrap
self.width = 255
self.col = 1
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self._current, self._previous = b'', b'' | [
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Asana/python-asana | 9b54ab99423208bd6aa87dbfaa628c069430b127 | asana/client.py | python | Client.get_collection | (self, path, query, **options) | Get a collection from a collection endpoint.
Parses GET request options for a collection endpoint and dispatches a
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] | def get_collection(self, path, query, **options):
"""Get a collection from a collection endpoint.
Parses GET request options for a collection endpoint and dispatches a
request.
"""
options = self._merge_options(options)
if options['iterator_type'] == 'items':
return CollectionPageIterator(self, path, query, options).items()
if options['iterator_type'] is None:
return self.get(path, query, **options)
raise Exception('Unknown value for "iterator_type" option: {}'.format(
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/cast/helpers.py | python | CastStatusListener.multizone_new_media_status | (self, group_uuid, media_status) | Handle reception of a new MediaStatus for a group. | Handle reception of a new MediaStatus for a group. | [
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microsoft/azure-devops-python-api | 451cade4c475482792cbe9e522c1fee32393139e | azure-devops/azure/devops/v5_1/service_hooks/service_hooks_client.py | python | ServiceHooksClient.list_subscriptions | (self, publisher_id=None, event_type=None, consumer_id=None, consumer_action_id=None) | return self._deserialize('[Subscription]', self._unwrap_collection(response)) | ListSubscriptions.
Get a list of subscriptions.
:param str publisher_id: ID for a subscription.
:param str event_type: The event type to filter on (if any).
:param str consumer_id: ID for a consumer.
:param str consumer_action_id: ID for a consumerActionId.
:rtype: [Subscription] | ListSubscriptions.
Get a list of subscriptions.
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:param str event_type: The event type to filter on (if any).
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:param str consumer_action_id: ID for a consumerActionId.
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Get a list of subscriptions.
:param str publisher_id: ID for a subscription.
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if consumer_id is not None:
query_parameters['consumerId'] = self._serialize.query('consumer_id', consumer_id, 'str')
if consumer_action_id is not None:
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response = self._send(http_method='GET',
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return self._deserialize('[Subscription]', self._unwrap_collection(response)) | [
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liaopeiyuan/ml-arsenal-public | f8938ce3cb58b35fc7cc20d096c39a85ec9780b2 | external/heng/tgs/code/sync_batchnorm/batchnorm.py | python | _unsqueeze_ft | (tensor) | return tensor.unsqueeze(0).unsqueeze(-1) | add new dementions at the front and the tail | add new dementions at the front and the tail | [
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hfaran/piazza-api | 48756f4150c94276d14c2504f1c2d09a330efb20 | piazza_api/network.py | python | Network.create_reply | (self, post, content, anonymous=False) | return self._rpc.content_create(params) | Create a reply to a followup
It seems like if the post has `<p>` tags, then it's treated as HTML,
but is treated as text otherwise. You'll want to provide `content`
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:type post: dict|str|int
:param post: Either the post dict returned by another API method, or
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:type subject: str
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"""Create a reply to a followup
It seems like if the post has `<p>` tags, then it's treated as HTML,
but is treated as text otherwise. You'll want to provide `content`
accordingly.
:type post: dict|str|int
:param post: Either the post dict returned by another API method, or
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:type subject: str
:param content: The content of the followup.
:type anonymous: bool
:param anonymous: Whether or not to post anonymously.
:rtype: dict
:returns: Dictionary with information about the created follow-up.
"""
try:
cid = post["id"]
except KeyError:
cid = post
params = {
"cid": cid,
"type": "feedback",
# For replies, the content is actually put into the subject.
"subject": content,
"content": "",
"anonymous": "yes" if anonymous else "no",
}
return self._rpc.content_create(params) | [
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lovelylain/pyctp | fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d | stock/ctp/Level2ApiStruct.py | python | L2MarketDataBid8.__init__ | (self, BidPx8=0.0, BidOrderQty8=0, BidNumOrder8=0) | [] | def __init__(self, BidPx8=0.0, BidOrderQty8=0, BidNumOrder8=0):
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POSTECH-CVLab/PyTorch-StudioGAN | bebb33f612759b86a224392f6fe941d0cc81d3c4 | src/models/big_resnet.py | python | DiscBlock.forward | (self, x) | return out | [] | def forward(self, x):
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awslabs/aws-servicebroker | c301912e7df3a2f09a9c34d3ae7ffe67c55aa3a0 | sample-apps/rds/sample-app/src/pymysql/connections.py | python | Connection.commit | (self) | Commit changes to stable storage | Commit changes to stable storage | [
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IdentityPython/pysaml2 | 6badb32d212257bd83ffcc816f9b625f68281b47 | src/saml2/schema/wsdl.py | python | TFault_.__init__ | (self,
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google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/server/grr_response_server/gui/api_call_router.py | python | ApiCallRouterStub.ListKbFields | (self, args, context=None) | List all available KnowledgeBase fields. | List all available KnowledgeBase fields. | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Mac/Demo/mlte/mlted.py | python | Mlted.clear | (self, *args) | [] | def clear(self, *args):
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fmoralesc/vim-pad | 2a39b6857ada72f1f81b12c85baf7f067cb90739 | pythonx/pad/vim_interface.py | python | Vim.__add__ | (self, cmd) | The idea is to allow using
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InvestmentSystems/static-frame | 0b19d6969bf6c17fb0599871aca79eb3b52cf2ed | static_frame/core/index_hierarchy.py | python | IndexHierarchy.from_tree | (cls: tp.Type[IH],
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edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/androguard/core/bytecodes/dvm.py | python | EncodedAnnotation.get_size | (self) | return self.size | Return the number of name-value mappings in this annotation
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pybliometrics-dev/pybliometrics | 26ad9656e5a1d4c80774937706a0df85776f07d0 | pybliometrics/scopus/abstract_retrieval.py | python | AbstractRetrieval.confsponsor | (self) | return sponsors | Sponsor(s) of the conference the document belongs to. | Sponsor(s) of the conference the document belongs to. | [
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laughingman7743/PyAthena | 417749914247cabca2325368c6eda337b28b47f0 | pyathena/common.py | python | CursorIterator.__next__ | (self) | [] | def __next__(self):
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acm5656/ssd_pytorch | 95bab2f080f4d7b9beb1ba0f5f9163ec84a110f2 | utils.py | python | nms | (boxes, scores, overlap=0.5, top_k=200) | return keep, count | Apply non-maximum suppression at test time to avoid detecting too many
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ganeti/ganeti | d340a9ddd12f501bef57da421b5f9b969a4ba905 | lib/tools/cfgupgrade.py | python | CfgUpgrade.UpgradeDiskDevType | (self, disk) | Upgrades the disks' device type. | Upgrades the disks' device type. | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/cwp/v20180228/models.py | python | ExportVulDetectionExcelRequest.__init__ | (self) | r"""
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/_osx_support.py | python | _read_output | (commandstring) | Output from successful command execution or None | Output from successful command execution or None | [
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openmc-dev/openmc | 0cf7d9283786677e324bfbdd0984a54d1c86dacc | openmc/filter_expansion.py | python | SphericalHarmonicsFilter.to_xml_element | (self) | return element | Return XML Element representing the filter.
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apple/ccs-calendarserver | 13c706b985fb728b9aab42dc0fef85aae21921c3 | twistedcaldav/directory/augment.py | python | AugmentDB.refresh | (self) | return None | Refresh any cached data.
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"""
Refresh any cached data.
@return: L{Deferred}
"""
self.cachedRecords.clear()
return None | [
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scikit-image/scikit-image | ed642e2bc822f362504d24379dee94978d6fa9de | skimage/future/manual_segmentation.py | python | manual_lasso_segmentation | (image, alpha=0.4, return_all=False) | Return a label image based on freeform selections made with the mouse.
Parameters
----------
image : (M, N[, 3]) array
Grayscale or RGB image.
alpha : float, optional
Transparency value for polygons drawn over the image.
return_all : bool, optional
If True, an array containing each separate polygon drawn is returned.
(The polygons may overlap.) If False (default), latter polygons
"overwrite" earlier ones where they overlap.
Returns
-------
labels : array of int, shape ([Q, ]M, N)
The segmented regions. If mode is `'separate'`, the leading dimension
of the array corresponds to the number of regions that the user drew.
Notes
-----
Press and hold the left mouse button to draw around each object.
Examples
--------
>>> from skimage import data, future, io
>>> camera = data.camera()
>>> mask = future.manual_lasso_segmentation(camera) # doctest: +SKIP
>>> io.imshow(mask) # doctest: +SKIP
>>> io.show() # doctest: +SKIP | Return a label image based on freeform selections made with the mouse. | [
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] | def manual_lasso_segmentation(image, alpha=0.4, return_all=False):
"""Return a label image based on freeform selections made with the mouse.
Parameters
----------
image : (M, N[, 3]) array
Grayscale or RGB image.
alpha : float, optional
Transparency value for polygons drawn over the image.
return_all : bool, optional
If True, an array containing each separate polygon drawn is returned.
(The polygons may overlap.) If False (default), latter polygons
"overwrite" earlier ones where they overlap.
Returns
-------
labels : array of int, shape ([Q, ]M, N)
The segmented regions. If mode is `'separate'`, the leading dimension
of the array corresponds to the number of regions that the user drew.
Notes
-----
Press and hold the left mouse button to draw around each object.
Examples
--------
>>> from skimage import data, future, io
>>> camera = data.camera()
>>> mask = future.manual_lasso_segmentation(camera) # doctest: +SKIP
>>> io.imshow(mask) # doctest: +SKIP
>>> io.show() # doctest: +SKIP
"""
import matplotlib
import matplotlib.pyplot as plt
list_of_vertex_lists = []
polygons_drawn = []
if image.ndim not in (2, 3):
raise ValueError('Only 2D grayscale or RGB images are supported.')
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.imshow(image, cmap="gray")
ax.set_axis_off()
def _undo(*args, **kwargs):
if list_of_vertex_lists:
list_of_vertex_lists.pop()
# Remove last polygon from list of polygons...
last_poly = polygons_drawn.pop()
# ... then from the plot
last_poly.remove()
fig.canvas.draw_idle()
undo_pos = fig.add_axes([0.85, 0.05, 0.075, 0.075])
undo_button = matplotlib.widgets.Button(undo_pos, u'\u27F2')
undo_button.on_clicked(_undo)
def _on_lasso_selection(vertices):
if len(vertices) < 3:
return
list_of_vertex_lists.append(vertices)
polygon_object = _draw_polygon(ax, vertices, alpha=alpha)
polygons_drawn.append(polygon_object)
plt.draw()
matplotlib.widgets.LassoSelector(ax, _on_lasso_selection)
plt.show(block=True)
labels = (_mask_from_vertices(vertices, image.shape[:2], i)
for i, vertices in enumerate(list_of_vertex_lists, start=1))
if return_all:
return np.stack(labels)
else:
return reduce(np.maximum, labels, np.broadcast_to(0, image.shape[:2])) | [
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readthedocs/readthedocs.org | 0852d7c10d725d954d3e9a93513171baa1116d9f | readthedocs/projects/tasks.py | python | UpdateDocsTaskStep.run_setup | (self, record=True) | return True | Run setup in a build environment.
Return True if successful. | Run setup in a build environment. | [
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] | def run_setup(self, record=True):
"""
Run setup in a build environment.
Return True if successful.
"""
# Reset build only if it has some commands already.
if self.build.get('commands'):
api_v2.build(self.build['id']).reset.post()
if settings.DOCKER_ENABLE:
env_cls = DockerBuildEnvironment
else:
env_cls = LocalBuildEnvironment
environment = env_cls(
project=self.project,
version=self.version,
build=self.build,
record=record,
update_on_success=False,
environment=self.get_vcs_env_vars(),
)
self.build_start_time = environment.start_time
# TODO: Remove.
# There is code that still depends of this attribute
# outside this function. Don't use self.setup_env for new code.
self.setup_env = environment
# Environment used for code checkout & initial configuration reading
with environment:
before_vcs.send(sender=self.version, environment=environment)
if self.project.skip:
raise ProjectBuildsSkippedError
try:
with self.project.repo_nonblockinglock(version=self.version):
self.pull_cached_environment()
self.setup_vcs(environment)
except vcs_support_utils.LockTimeout as e:
self.task.retry(exc=e, throw=False)
raise VersionLockedError
try:
self.config = load_yaml_config(version=self.version)
except ConfigError as e:
raise YAMLParseError(
YAMLParseError.GENERIC_WITH_PARSE_EXCEPTION.format(
exception=str(e),
),
)
self.save_build_config()
self.additional_vcs_operations(environment)
if environment.failure or self.config is None:
log.info(
'Failing build because of setup failure.',
failure=environment.failure,
project_slug=self.project.slug,
version_slug=self.version.slug,
)
# Send notification to users only if the build didn't fail because
# of VersionLockedError: this exception occurs when a build is
# triggered before the previous one has finished (e.g. two webhooks,
# one after the other)
if not isinstance(environment.failure, VersionLockedError):
self.send_notifications(
self.version.pk,
self.build['id'],
event=WebHookEvent.BUILD_FAILED,
)
return False
if environment.successful and not self.project.has_valid_clone:
self.set_valid_clone()
return True | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/django/db/backends/oracle/features.py | python | DatabaseFeatures.introspected_boolean_field_type | (self, field=None, created_separately=False) | return super(DatabaseFeatures, self).introspected_boolean_field_type(field, created_separately) | Some versions of Oracle -- we've seen this on 11.2.0.1 and suspect
it goes back -- have a weird bug where, when an integer column is
added to an existing table with a default, its precision is later
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For Django introspection, this means that such columns are reported
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The bug is solved in Oracle 11.2.0.2 and up. | Some versions of Oracle -- we've seen this on 11.2.0.1 and suspect
it goes back -- have a weird bug where, when an integer column is
added to an existing table with a default, its precision is later
reported on introspection as 0, regardless of the real precision.
For Django introspection, this means that such columns are reported
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"""
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it goes back -- have a weird bug where, when an integer column is
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For Django introspection, this means that such columns are reported
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if self.connection.oracle_full_version < '11.2.0.2' and field and field.has_default() and created_separately:
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holoviz/param | c4a9e3252456ad368146140e1fc52cf6bba9f1f0 | param/version.py | python | OldDeprecatedVersion.abbrev | (self,dev_suffix="") | return '.'.join(str(el) for el in self.release) + \
(dev_suffix if self.commit_count > 0 or self.dirty else "") | Abbreviated string representation, optionally declaring whether it is
a development version. | Abbreviated string representation, optionally declaring whether it is
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"""
Abbreviated string representation, optionally declaring whether it is
a development version.
"""
return '.'.join(str(el) for el in self.release) + \
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alan-turing-institute/CleverCSV | a7c7c812f2dc220b8f45f3409daac6e933bc44a2 | clevercsv/break_ties.py | python | tie_breaker | (data, dialects) | return None | Break ties between dialects.
This function is used to break ties where possible between two, three, or
four dialects that receive the same value for the data consistency measure.
Parameters
----------
data: str
The data as a single string
dialects: list
Dialects that are tied
Returns
-------
dialect: SimpleDialect
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"""
Break ties between dialects.
This function is used to break ties where possible between two, three, or
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Parameters
----------
data: str
The data as a single string
dialects: list
Dialects that are tied
Returns
-------
dialect: SimpleDialect
One of the dialects from the list provided or None.
"""
if len(dialects) == 2:
return break_ties_two(data, dialects[0], dialects[1])
elif len(dialects) == 3:
return break_ties_three(data, dialects[0], dialects[1], dialects[2])
elif len(dialects) == 4:
return break_ties_four(data, dialects)
return None | [
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kpe/bert-for-tf2 | 55f6a6fd5d8ea14f96ee19938b7a1bf0cb26aaea | bert/tokenization/albert_tokenization.py | python | BasicTokenizer._run_split_on_punc | (self, text) | return ["".join(x) for x in output] | Splits punctuation on a piece of text. | Splits punctuation on a piece of text. | [
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chars = list(text)
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start_new_word = True
output = []
while i < len(chars):
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unknown-horizons/unknown-horizons | 7397fb333006d26c3d9fe796c7bd9cb8c3b43a49 | horizons/ai/aiplayer/villagebuilder.py | python | VillageBuilder.remove_building | (self, building) | Called when a building is removed from the area (the building still exists during the call). | Called when a building is removed from the area (the building still exists during the call). | [
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if building.id == BUILDINGS.RESIDENTIAL:
self._recreate_tent_queue(building.position.origin.to_tuple())
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wucng/TensorExpand | 4ea58f64f5c5082b278229b799c9f679536510b7 | TensorExpand/Object detection/faster rcnn/CharlesShang-TFFRCNN-master/lib/datasets/kittivoc.py | python | kittivoc._write_voc_results_file | (self, all_boxes) | [] | def _write_voc_results_file(self, all_boxes):
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
print 'Writing {} VOC results file'.format(cls)
filename = self._get_voc_results_file_template().format(cls)
with open(filename, 'wt') as f:
for im_ind, index in enumerate(self.image_index):
dets = all_boxes[cls_ind][im_ind]
if dets == []:
continue
# the VOCdevkit expects 1-based indices
for k in xrange(dets.shape[0]):
f.write('{:s} {:.3f} {:.1f} {:.1f} {:.1f} {:.1f}\n'.
format(index, dets[k, -1], # filename(stem), score
dets[k, 0] + 1, dets[k, 1] + 1, # x1, y1, x2, y2
dets[k, 2] + 1, dets[k, 3] + 1)) | [
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rlworkgroup/garage | b4abe07f0fa9bac2cb70e4a3e315c2e7e5b08507 | src/garage/tf/models/model.py | python | Model.network_output_spec | (self) | return [] | Network output spec.
Return:
list[str]: List of key(str) for the network outputs. | Network output spec. | [
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"""
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LeGoffLoic/Nodz | 0ee255c62883f7a374a9de6cbcf555e3352e5dec | nodz_main.py | python | NodeScene.dropEvent | (self, event) | Create a node from the dropped item. | Create a node from the dropped item. | [
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] | def dropEvent(self, event):
"""
Create a node from the dropped item.
"""
# Emit signal.
self.signal_Dropped.emit(event.scenePos())
event.accept() | [
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apple/coremltools | 141a83af482fcbdd5179807c9eaff9a7999c2c49 | coremltools/converters/keras/_layers2.py | python | default_skip | (builder, layer, input_names, output_names, keras_layer, respect_train) | return | Layers that can be skipped. | Layers that can be skipped. | [
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] | def default_skip(builder, layer, input_names, output_names, keras_layer, respect_train):
"""
Layers that can be skipped.
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pwnieexpress/pwn_plug_sources | 1a23324f5dc2c3de20f9c810269b6a29b2758cad | src/wifitap/scapy.py | python | IPoptionsField.getfield | (self, pkt, s) | return s[opsz:],s[:opsz] | [] | def getfield(self, pkt, s):
opsz = (pkt.ihl-5)*4
if opsz < 0:
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geopython/OWSLib | 414375413c9e2bab33a2d09608ab209875ce6daf | owslib/ogcapi/__init__.py | python | Collections.collection | (self, collection_id: str) | return self._request(path) | implements /collections/{collectionId}
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path = 'collections/{}'.format(collection_id)
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facebookresearch/detectron2 | cb92ae1763cd7d3777c243f07749574cdaec6cb8 | detectron2/modeling/roi_heads/keypoint_head.py | python | keypoint_rcnn_inference | (pred_keypoint_logits: torch.Tensor, pred_instances: List[Instances]) | Post process each predicted keypoint heatmap in `pred_keypoint_logits` into (x, y, score)
and add it to the `pred_instances` as a `pred_keypoints` field.
Args:
pred_keypoint_logits (Tensor): A tensor of shape (R, K, S, S) where R is the total number
of instances in the batch, K is the number of keypoints, and S is the side length of
the keypoint heatmap. The values are spatial logits.
pred_instances (list[Instances]): A list of N Instances, where N is the number of images.
Returns:
None. Each element in pred_instances will contain extra "pred_keypoints" and
"pred_keypoint_heatmaps" fields. "pred_keypoints" is a tensor of shape
(#instance, K, 3) where the last dimension corresponds to (x, y, score).
The scores are larger than 0. "pred_keypoint_heatmaps" contains the raw
keypoint logits as passed to this function. | Post process each predicted keypoint heatmap in `pred_keypoint_logits` into (x, y, score)
and add it to the `pred_instances` as a `pred_keypoints` field. | [
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"""
Post process each predicted keypoint heatmap in `pred_keypoint_logits` into (x, y, score)
and add it to the `pred_instances` as a `pred_keypoints` field.
Args:
pred_keypoint_logits (Tensor): A tensor of shape (R, K, S, S) where R is the total number
of instances in the batch, K is the number of keypoints, and S is the side length of
the keypoint heatmap. The values are spatial logits.
pred_instances (list[Instances]): A list of N Instances, where N is the number of images.
Returns:
None. Each element in pred_instances will contain extra "pred_keypoints" and
"pred_keypoint_heatmaps" fields. "pred_keypoints" is a tensor of shape
(#instance, K, 3) where the last dimension corresponds to (x, y, score).
The scores are larger than 0. "pred_keypoint_heatmaps" contains the raw
keypoint logits as passed to this function.
"""
# flatten all bboxes from all images together (list[Boxes] -> Rx4 tensor)
bboxes_flat = cat([b.pred_boxes.tensor for b in pred_instances], dim=0)
pred_keypoint_logits = pred_keypoint_logits.detach()
keypoint_results = heatmaps_to_keypoints(pred_keypoint_logits, bboxes_flat.detach())
num_instances_per_image = [len(i) for i in pred_instances]
keypoint_results = keypoint_results[:, :, [0, 1, 3]].split(num_instances_per_image, dim=0)
heatmap_results = pred_keypoint_logits.split(num_instances_per_image, dim=0)
for keypoint_results_per_image, heatmap_results_per_image, instances_per_image in zip(
keypoint_results, heatmap_results, pred_instances
):
# keypoint_results_per_image is (num instances)x(num keypoints)x(x, y, score)
# heatmap_results_per_image is (num instances)x(num keypoints)x(side)x(side)
instances_per_image.pred_keypoints = keypoint_results_per_image
instances_per_image.pred_keypoint_heatmaps = heatmap_results_per_image | [
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XX-net/XX-Net | a9898cfcf0084195fb7e69b6bc834e59aecdf14f | python3.8.2/Lib/site.py | python | _init_pathinfo | () | return d | Return a set containing all existing file system items from sys.path. | Return a set containing all existing file system items from sys.path. | [
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"""Return a set containing all existing file system items from sys.path."""
d = set()
for item in sys.path:
try:
if os.path.exists(item):
_, itemcase = makepath(item)
d.add(itemcase)
except TypeError:
continue
return d | [
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nucleic/enaml | 65c2a2a2d765e88f2e1103046680571894bb41ed | enaml/widgets/image_view.py | python | ImageView._update_proxy | (self, change) | An observer which sends state change to the proxy. | An observer which sends state change to the proxy. | [
"An",
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] | def _update_proxy(self, change):
""" An observer which sends state change to the proxy.
"""
# The superclass handler implementation is sufficient.
super(ImageView, self)._update_proxy(change) | [
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