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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/nova/nova/utils.py | python | is_valid_ipv4 | (address) | Verify that address represents a valid IPv4 address. | Verify that address represents a valid IPv4 address. | [
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] | def is_valid_ipv4(address):
"""Verify that address represents a valid IPv4 address."""
try:
return netaddr.valid_ipv4(address)
except Exception:
return False | [
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ucsb-seclab/karonte | 427ac313e596f723e40768b95d13bd7a9fc92fd8 | tool/taint_analysis/coretaint.py | python | CoreTaint.do_recursive_untaint | (self, dst, path) | return self._do_recursive_untaint_core(dst, path) | Perform the untaint operation (see do_recursive_untaint_core)
:param dst: variable to untaint
:param path: angr path
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"""
Perform the untaint operation (see do_recursive_untaint_core)
:param dst: variable to untaint
:param path: angr path
:return:
"""
return self._do_recursive_untaint_core(dst, path) | [
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PaddlePaddle/PaddleSlim | f895aebe441b2bef79ecc434626d3cac4b3cbd09 | paddleslim/nas/early_stop/median_stop/median_stop.py | python | MedianStop._convert_running2completed | (self, exp_name, status) | Convert experiment record from running to complete.
Args:
exp_name<str>: the name of experiment.
status<str>: the status of this experiment. | Convert experiment record from running to complete. | [
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"""
Convert experiment record from running to complete.
Args:
exp_name<str>: the name of experiment.
status<str>: the status of this experiment.
"""
_logger.debug('the status of this experiment is {}'.format(status))
completed_avg_history = dict()
if exp_name in self._running_history:
if status == "GOOD":
count = 0
history_sum = 0
result = []
for res in self._running_history[exp_name]:
count += 1
history_sum += res
result.append(history_sum / count)
completed_avg_history[exp_name] = result
self._running_history.pop(exp_name)
if len(completed_avg_history) > 0:
while True:
try:
new_dict = self._manager.get_completed_history()
new_dict.update(completed_avg_history)
break
except Exception as err:
_logger.error("update data error: {}".format(err)) | [
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PaddlePaddle/PaddleSpeech | 26524031d242876b7fdb71582b0b3a7ea45c7d9d | utils/utility.py | python | download | (url, md5sum, target_dir) | return filepath | Download file from url to target_dir, and check md5sum. | Download file from url to target_dir, and check md5sum. | [
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"""Download file from url to target_dir, and check md5sum."""
if not os.path.exists(target_dir):
os.makedirs(target_dir)
filepath = os.path.join(target_dir, url.split("/")[-1])
if not (os.path.exists(filepath) and md5file(filepath) == md5sum):
print("Downloading %s ..." % url)
os.system("wget -c " + url + " -P " + target_dir)
print("\nMD5 Chesksum %s ..." % filepath)
if not md5file(filepath) == md5sum:
raise RuntimeError("MD5 checksum failed.")
else:
print("File exists, skip downloading. (%s)" % filepath)
return filepath | [
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rhinstaller/anaconda | 63edc8680f1b05cbfe11bef28703acba808c5174 | pyanaconda/modules/storage/partitioning/custom/custom_module.py | python | CustomPartitioningModule.for_publication | (self) | return CustomPartitioningInterface(self) | Return a DBus representation. | Return a DBus representation. | [
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wistbean/learn_python3_spider | 73c873f4845f4385f097e5057407d03dd37a117b | stackoverflow/venv/lib/python3.6/site-packages/pip-19.0.3-py3.6.egg/pip/_vendor/requests/models.py | python | Response.content | (self) | return self._content | Content of the response, in bytes. | Content of the response, in bytes. | [
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"""Content of the response, in bytes."""
if self._content is False:
# Read the contents.
if self._content_consumed:
raise RuntimeError(
'The content for this response was already consumed')
if self.status_code == 0 or self.raw is None:
self._content = None
else:
self._content = b''.join(self.iter_content(CONTENT_CHUNK_SIZE)) or b''
self._content_consumed = True
# don't need to release the connection; that's been handled by urllib3
# since we exhausted the data.
return self._content | [
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OpenAgricultureFoundation/openag-device-software | a51d2de399c0a6781ae51d0dcfaae1583d75f346 | device/controllers/modules/pid/pid.py | python | PID.setKi | (self, integral_gain: float) | Determines how aggressively the PID reacts to the current error
with setting Integral Gain | Determines how aggressively the PID reacts to the current error
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"""Determines how aggressively the PID reacts to the current error
with setting Integral Gain"""
self.Ki = integral_gain | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/configparser.py | python | RawConfigParser.defaults | (self) | return self._defaults | [] | def defaults(self):
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amonapp/amon | 61ae3575ad98ec4854ea87c213aa8dfbb29a0199 | amon/templatetags/math.py | python | substract | (element, second_element) | return result | [] | def substract(element, second_element):
result = float(element)-float(second_element)
return result | [
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gaojiuli/gain | 2c8160c92943837613a773f681fb190a8c434bb2 | gain/result/file_result.py | python | FileResult.save_to_file | (self, results) | save results to file Asynchronous
:param results: str
:return: None | save results to file Asynchronous
:param results: str
:return: None | [
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"""
save results to file Asynchronous
:param results: str
:return: None
"""
async with aiofiles.open(self.path, 'a+') as f:
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learningequality/ka-lite | 571918ea668013dcf022286ea85eff1c5333fb8b | kalite/packages/bundled/django/contrib/gis/geos/io.py | python | WKTReader.read | (self, wkt) | return GEOSGeometry(super(WKTReader, self).read(wkt)) | Returns a GEOSGeometry for the given WKT string. | Returns a GEOSGeometry for the given WKT string. | [
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microsoft/azure-devops-python-api | 451cade4c475482792cbe9e522c1fee32393139e | azure-devops/azure/devops/v5_1/build/build_client.py | python | BuildClient.restore_webhooks | (self, trigger_types, project, provider_name, service_endpoint_id=None, repository=None) | RestoreWebhooks.
[Preview API] Recreates the webhooks for the specified triggers in the given source code repository.
:param [DefinitionTriggerType] trigger_types: The types of triggers to restore webhooks for.
:param str project: Project ID or project name
:param str provider_name: The name of the source provider.
:param str service_endpoint_id: If specified, the ID of the service endpoint to query. Can only be omitted for providers that do not use service endpoints, e.g. TFVC or TFGit.
:param str repository: If specified, the vendor-specific identifier or the name of the repository to get webhooks. Can only be omitted for providers that do not support multiple repositories. | RestoreWebhooks.
[Preview API] Recreates the webhooks for the specified triggers in the given source code repository.
:param [DefinitionTriggerType] trigger_types: The types of triggers to restore webhooks for.
:param str project: Project ID or project name
:param str provider_name: The name of the source provider.
:param str service_endpoint_id: If specified, the ID of the service endpoint to query. Can only be omitted for providers that do not use service endpoints, e.g. TFVC or TFGit.
:param str repository: If specified, the vendor-specific identifier or the name of the repository to get webhooks. Can only be omitted for providers that do not support multiple repositories. | [
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[Preview API] Recreates the webhooks for the specified triggers in the given source code repository.
:param [DefinitionTriggerType] trigger_types: The types of triggers to restore webhooks for.
:param str project: Project ID or project name
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"""
route_values = {}
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route_values['project'] = self._serialize.url('project', project, 'str')
if provider_name is not None:
route_values['providerName'] = self._serialize.url('provider_name', provider_name, 'str')
query_parameters = {}
if service_endpoint_id is not None:
query_parameters['serviceEndpointId'] = self._serialize.query('service_endpoint_id', service_endpoint_id, 'str')
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/ocr/v20181119/models.py | python | EstateCertOCRResponse.__init__ | (self) | r"""
:param Obligee: 权利人
:type Obligee: str
:param Ownership: 共有情况
:type Ownership: str
:param Location: 坐落
:type Location: str
:param Unit: 不动产单元号
:type Unit: str
:param Type: 权利类型
:type Type: str
:param Property: 权利性质
:type Property: str
:param Usage: 用途
:type Usage: str
:param Area: 面积
:type Area: str
:param Term: 使用期限
:type Term: str
:param Other: 权利其他状况，多行会用换行符\n连接。
:type Other: str
:param Angle: 图片旋转角度
:type Angle: float
:param Number: 不动产权号
:type Number: str
:param RequestId: 唯一请求 ID，每次请求都会返回。定位问题时需要提供该次请求的 RequestId。
:type RequestId: str | r"""
:param Obligee: 权利人
:type Obligee: str
:param Ownership: 共有情况
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:param Location: 坐落
:type Location: str
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:param Usage: 用途
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:param Term: 使用期限
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:param Other: 权利其他状况，多行会用换行符\n连接。
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:param Angle: 图片旋转角度
:type Angle: float
:param Number: 不动产权号
:type Number: str
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:type RequestId: str | [
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fooying/3102 | 0faee38c30b2e24154f41e68457cfd8f7a61c040 | thirdparty/attrdict/__init__.py | python | AttrDict.__delitem__ | (self, key) | del adict[key]
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riptideio/pymodbus | c5772b35ae3f29d1947f3ab453d8d00df846459f | pymodbus/transaction.py | python | ModbusTransactionManager.getNextTID | (self) | return self.tid | Retrieve the next unique transaction identifier
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self.tid = (self.tid + 1) & 0xffff
return self.tid | [
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jython/jython3 | def4f8ec47cb7a9c799ea4c745f12badf92c5769 | lib-python/3.5.1/tkinter/__init__.py | python | Misc.winfo_rooty | (self) | return self.tk.getint(
self.tk.call('winfo', 'rooty', self._w)) | Return y coordinate of upper left corner of this widget on the
root window. | Return y coordinate of upper left corner of this widget on the
root window. | [
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"""Return y coordinate of upper left corner of this widget on the
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return self.tk.getint(
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CMA-ES/pycma | f6eed1ef7e747cec1ab2e5c835d6f2fd1ebc097f | cma/transformations.py | python | BoxConstraintsLinQuadTransformation.is_loosely_feasible_i | (self, x, i) | return lb - 2 * al - (ub - lb) / 2.0 <= x <= ub + 2 * au + (ub - lb) / 2.0 | never used | never used | [
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lb = self._lb[self._index(i)]
ub = self._ub[self._index(i)]
al = self._al[self._index(i)]
au = self._au[self._index(i)]
return lb - 2 * al - (ub - lb) / 2.0 <= x <= ub + 2 * au + (ub - lb) / 2.0 | [
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/pip/_vendor/requests/packages/urllib3/packages/ordered_dict.py | python | OrderedDict.viewkeys | (self) | return KeysView(self) | od.viewkeys() -> a set-like object providing a view on od's keys | od.viewkeys() -> a set-like object providing a view on od's keys | [
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krintoxi/NoobSec-Toolkit | 38738541cbc03cedb9a3b3ed13b629f781ad64f6 | NoobSecToolkit /scripts/sshbackdoors/backdoors/shell/pupy/pupy/packages/windows/all/pupwinutils/processes.py | python | is_process_64_from_handle | (hProcess) | return not iswow64.value | Take a process handle. return True if process is 64 bits, and False otherwise. | Take a process handle. return True if process is 64 bits, and False otherwise. | [
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] | def is_process_64_from_handle(hProcess):
""" Take a process handle. return True if process is 64 bits, and False otherwise. """
iswow64 = c_bool(False)
if not hasattr(windll.kernel32,'IsWow64Process'):
return False
windll.kernel32.IsWow64Process(hProcess, byref(iswow64))
return not iswow64.value | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/lib-tk/Tkinter.py | python | Canvas.select_clear | (self) | Clear the selection if it is in this widget. | Clear the selection if it is in this widget. | [
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"""Clear the selection if it is in this widget."""
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Garvit244/Leetcode | a1d31ff0f9f251f3dd0bee5cc8b191b7ebbccc29 | 1-100q/45.py | python | Solution.jump | (self, nums) | return steps if maxReach == len(nums) - 1 else 0 | :type nums: List[int]
:rtype: int | :type nums: List[int]
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"""
:type nums: List[int]
:rtype: int
"""
steps, lastRearch, maxReach = 0, 0 ,0
for index in range(len(nums)):
if index > lastRearch:
lastRearch = maxReach
steps += 1
maxReach = max(maxReach, index + nums[index])
return steps if maxReach == len(nums) - 1 else 0 | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/site-packages/pkg_resources/_vendor/pyparsing.py | python | ParserElement.__rxor__ | (self, other ) | return other ^ self | Implementation of ^ operator when left operand is not a C{L{ParserElement}} | Implementation of ^ operator when left operand is not a C{L{ParserElement}} | [
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"""
Implementation of ^ operator when left operand is not a C{L{ParserElement}}
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if isinstance( other, basestring ):
other = ParserElement._literalStringClass( other )
if not isinstance( other, ParserElement ):
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Tautulli/Tautulli | 2410eb33805aaac4bd1c5dad0f71e4f15afaf742 | lib/future/backports/email/_header_value_parser.py | python | WhiteSpaceTerminal.value | (self) | return ' ' | [] | def value(self):
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iniqua/plecost | ef0d89bfdf1ef870bd11b1d8bdf93a8ce9ec6ca0 | plecost_lib/libs/wordlist.py | python | get_wordlist | (wordlist_name) | Get and iterator of specified word list.
:param wordlist_name: Word list name
:type wordlist_name: basestring
:return: iterator with each line of file.
:rtype: str | Get and iterator of specified word list. | [
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"""
Get and iterator of specified word list.
:param wordlist_name: Word list name
:type wordlist_name: basestring
:return: iterator with each line of file.
:rtype: str
"""
if not isinstance(wordlist_name, str):
raise TypeError("Expected basestring, got '%s' instead" % type(wordlist_name))
word_list_name = join(get_data_folder(), wordlist_name)
try:
with open(word_list_name, "rU") as f:
for word in f:
yield word.replace("\n", "").replace("\r", "")
except IOError as e:
raise PlecostWordListNotFound("Wordlist '%s' not found. Error: %s" % (wordlist_name, e)) | [
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dipy/dipy | be956a529465b28085f8fc435a756947ddee1c89 | dipy/reconst/qtdmri.py | python | QtdmriFit.norm_of_laplacian_signal | (self) | return norm_laplacian | Calculates the norm of the laplacian of the fitted signal [1]_.
This information could be useful to assess if the extrapolation of the
fitted signal contains spurious oscillations. A high laplacian norm may
indicate that these are present, and any q-space indices that
use integrals of the signal may be corrupted (e.g. RTOP, RTAP, RTPP,
QIV). In contrast to [1], the Laplacian now describes oscillations in
the 4-dimensional qt-signal [2].
References
----------
.. [1]_ Fick, Rutger HJ, et al. "MAPL: Tissue microstructure estimation
using Laplacian-regularized MAP-MRI and its application to HCP
data." NeuroImage (2016).
.. [2] Fick, Rutger HJ, et al. "Non-Parametric GraphNet-Regularized
Representation of dMRI in Space and Time", Medical Image Analysis,
2017. | Calculates the norm of the laplacian of the fitted signal [1]_.
This information could be useful to assess if the extrapolation of the
fitted signal contains spurious oscillations. A high laplacian norm may
indicate that these are present, and any q-space indices that
use integrals of the signal may be corrupted (e.g. RTOP, RTAP, RTPP,
QIV). In contrast to [1], the Laplacian now describes oscillations in
the 4-dimensional qt-signal [2]. | [
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""" Calculates the norm of the laplacian of the fitted signal [1]_.
This information could be useful to assess if the extrapolation of the
fitted signal contains spurious oscillations. A high laplacian norm may
indicate that these are present, and any q-space indices that
use integrals of the signal may be corrupted (e.g. RTOP, RTAP, RTPP,
QIV). In contrast to [1], the Laplacian now describes oscillations in
the 4-dimensional qt-signal [2].
References
----------
.. [1]_ Fick, Rutger HJ, et al. "MAPL: Tissue microstructure estimation
using Laplacian-regularized MAP-MRI and its application to HCP
data." NeuroImage (2016).
.. [2] Fick, Rutger HJ, et al. "Non-Parametric GraphNet-Regularized
Representation of dMRI in Space and Time", Medical Image Analysis,
2017.
"""
if self.model.cartesian:
lap_matrix = qtdmri_laplacian_reg_matrix(
self.model.ind_mat, self.us, self.ut,
self.model.S_mat, self.model.T_mat, self.model.U_mat,
self.model.part1_reg_mat_tau,
self.model.part23_reg_mat_tau,
self.model.part4_reg_mat_tau,
normalization=self.model.normalization
)
else:
lap_matrix = qtdmri_isotropic_laplacian_reg_matrix(
self.model.ind_mat, self.us, self.ut,
self.model.part1_uq_iso_precomp,
self.model.part1_reg_mat_tau,
self.model.part23_reg_mat_tau,
self.model.part4_reg_mat_tau,
normalization=self.model.normalization
)
norm_laplacian = np.dot(self._qtdmri_coef,
np.dot(self._qtdmri_coef, lap_matrix))
return norm_laplacian | [
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tern-tools/tern | 723f43dcaae2f2f0a08a63e5e8de3938031a386e | tern/load/docker_api.py | python | build_and_dump | (dockerfile) | return image_metadata | Given a path to the dockerfile, use the Docker API to build the
container image and extract the image into a working directory. Return
true if this succeeded and false if it didn't | Given a path to the dockerfile, use the Docker API to build the
container image and extract the image into a working directory. Return
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true if this succeeded and false if it didn't"""
image_metadata = None
# open up a client first
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client = check_docker_setup()
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BMW-InnovationLab/BMW-TensorFlow-Training-GUI | 4f10d1f00f9ac312ca833e5b28fd0f8952cfee17 | training_api/research/object_detection/predictors/heads/mask_head.py | python | MaskRCNNMaskHead._get_mask_predictor_conv_depth | (self,
num_feature_channels,
num_classes,
class_weight=3.0,
feature_weight=2.0) | return int(math.pow(2.0, num_conv_channels_log)) | Computes the depth of the mask predictor convolutions.
Computes the depth of the mask predictor convolutions given feature channels
and number of classes by performing a weighted average of the two in
log space to compute the number of convolution channels. The weights that
are used for computing the weighted average do not need to sum to 1.
Args:
num_feature_channels: An integer containing the number of feature
channels.
num_classes: An integer containing the number of classes.
class_weight: Class weight used in computing the weighted average.
feature_weight: Feature weight used in computing the weighted average.
Returns:
An integer containing the number of convolution channels used by mask
predictor. | Computes the depth of the mask predictor convolutions. | [
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num_feature_channels,
num_classes,
class_weight=3.0,
feature_weight=2.0):
"""Computes the depth of the mask predictor convolutions.
Computes the depth of the mask predictor convolutions given feature channels
and number of classes by performing a weighted average of the two in
log space to compute the number of convolution channels. The weights that
are used for computing the weighted average do not need to sum to 1.
Args:
num_feature_channels: An integer containing the number of feature
channels.
num_classes: An integer containing the number of classes.
class_weight: Class weight used in computing the weighted average.
feature_weight: Feature weight used in computing the weighted average.
Returns:
An integer containing the number of convolution channels used by mask
predictor.
"""
num_feature_channels_log = math.log(float(num_feature_channels), 2.0)
num_classes_log = math.log(float(num_classes), 2.0)
weighted_num_feature_channels_log = (
num_feature_channels_log * feature_weight)
weighted_num_classes_log = num_classes_log * class_weight
total_weight = feature_weight + class_weight
num_conv_channels_log = round(
(weighted_num_feature_channels_log + weighted_num_classes_log) /
total_weight)
return int(math.pow(2.0, num_conv_channels_log)) | [
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/modules/x509.py | python | create_certificate | (path=None, text=False, overwrite=True, ca_server=None, **kwargs) | Create an X509 certificate.
path:
Path to write the certificate to.
text:
If ``True``, return the PEM text without writing to a file.
Default ``False``.
overwrite:
If ``True`` (default), create_certificate will overwrite the entire PEM
file. Set False to preserve existing private keys and dh params that
may exist in the PEM file.
kwargs:
Any of the properties below can be included as additional
keyword arguments.
ca_server:
Request a remotely signed certificate from ca_server. For this to
work, a ``signing_policy`` must be specified, and that same policy
must be configured on the ca_server. See ``signing_policy`` for
details. Also, the salt master must permit peers to call the
``sign_remote_certificate`` function.
Example:
/etc/salt/master.d/peer.conf
.. code-block:: yaml
peer:
.*:
- x509.sign_remote_certificate
subject properties:
Any of the values below can be included to set subject properties
Any other subject properties supported by OpenSSL should also work.
C:
2 letter Country code
CN:
Certificate common name, typically the FQDN.
Email:
Email address
GN:
Given Name
L:
Locality
O:
Organization
OU:
Organization Unit
SN:
SurName
ST:
State or Province
signing_private_key:
A path or string of the private key in PEM format that will be used
to sign this certificate. If neither ``signing_cert``, ``public_key``,
or ``csr`` are included, it will be assumed that this is a self-signed
certificate, and the public key matching ``signing_private_key`` will
be used to create the certificate.
signing_private_key_passphrase:
Passphrase used to decrypt the signing_private_key.
signing_cert:
A certificate matching the private key that will be used to sign this
certificate. This is used to populate the issuer values in the
resulting certificate. Do not include this value for
self-signed certificates.
public_key:
The public key to be included in this certificate. This can be sourced
from a public key, certificate, CSR or private key. If a private key
is used, the matching public key from the private key will be
generated before any processing is done. This means you can request a
certificate from a remote CA using a private key file as your
public_key and only the public key will be sent across the network to
the CA. If neither ``public_key`` or ``csr`` are specified, it will be
assumed that this is a self-signed certificate, and the public key
derived from ``signing_private_key`` will be used. Specify either
``public_key`` or ``csr``, not both. Because you can input a CSR as a
public key or as a CSR, it is important to understand the difference.
If you import a CSR as a public key, only the public key will be added
to the certificate, subject or extension information in the CSR will
be lost.
public_key_passphrase:
If the public key is supplied as a private key, this is the passphrase
used to decrypt it.
csr:
A file or PEM string containing a certificate signing request. This
will be used to supply the subject, extensions and public key of a
certificate. Any subject or extensions specified explicitly will
overwrite any in the CSR.
basicConstraints:
X509v3 Basic Constraints extension.
extensions:
The following arguments set X509v3 Extension values. If the value
starts with ``critical``, the extension will be marked as critical.
Some special extensions are ``subjectKeyIdentifier`` and
``authorityKeyIdentifier``.
``subjectKeyIdentifier`` can be an explicit value or it can be the
special string ``hash``. ``hash`` will set the subjectKeyIdentifier
equal to the SHA1 hash of the modulus of the public key in this
certificate. Note that this is not the exact same hashing method used
by OpenSSL when using the hash value.
``authorityKeyIdentifier`` Use values acceptable to the openssl CLI
tools. This will automatically populate ``authorityKeyIdentifier``
with the ``subjectKeyIdentifier`` of ``signing_cert``. If this is a
self-signed cert these values will be the same.
basicConstraints:
X509v3 Basic Constraints
keyUsage:
X509v3 Key Usage
extendedKeyUsage:
X509v3 Extended Key Usage
subjectKeyIdentifier:
X509v3 Subject Key Identifier
issuerAltName:
X509v3 Issuer Alternative Name
subjectAltName:
X509v3 Subject Alternative Name
crlDistributionPoints:
X509v3 CRL Distribution Points
issuingDistributionPoint:
X509v3 Issuing Distribution Point
certificatePolicies:
X509v3 Certificate Policies
policyConstraints:
X509v3 Policy Constraints
inhibitAnyPolicy:
X509v3 Inhibit Any Policy
nameConstraints:
X509v3 Name Constraints
noCheck:
X509v3 OCSP No Check
nsComment:
Netscape Comment
nsCertType:
Netscape Certificate Type
days_valid:
The number of days this certificate should be valid. This sets the
``notAfter`` property of the certificate. Defaults to 365.
version:
The version of the X509 certificate. Defaults to 3. This is
automatically converted to the version value, so ``version=3``
sets the certificate version field to 0x2.
serial_number:
The serial number to assign to this certificate. If omitted a random
serial number of size ``serial_bits`` is generated.
serial_bits:
The number of bits to use when randomly generating a serial number.
Defaults to 64.
algorithm:
The hashing algorithm to be used for signing this certificate.
Defaults to sha256.
copypath:
An additional path to copy the resulting certificate to. Can be used
to maintain a copy of all certificates issued for revocation purposes.
prepend_cn:
If set to True, the CN and a dash will be prepended to the copypath's filename.
Example:
/etc/pki/issued_certs/www.example.com-DE:CA:FB:AD:00:00:00:00.crt
signing_policy:
A signing policy that should be used to create this certificate.
Signing policies should be defined in the minion configuration, or in
a minion pillar. It should be a YAML formatted list of arguments
which will override any arguments passed to this function. If the
``minions`` key is included in the signing policy, only minions
matching that pattern (see match.glob and match.compound) will be
permitted to remotely request certificates from that policy.
In order to ``match.compound`` to work salt master must peers permit
peers to call it.
Example:
/etc/salt/master.d/peer.conf
.. code-block:: yaml
peer:
.*:
- match.compound
Example:
.. code-block:: yaml
x509_signing_policies:
www:
- minions: 'www*'
- signing_private_key: /etc/pki/ca.key
- signing_cert: /etc/pki/ca.crt
- C: US
- ST: Utah
- L: Salt Lake City
- basicConstraints: "critical CA:false"
- keyUsage: "critical cRLSign, keyCertSign"
- subjectKeyIdentifier: hash
- authorityKeyIdentifier: keyid,issuer:always
- days_valid: 90
- copypath: /etc/pki/issued_certs/
The above signing policy can be invoked with ``signing_policy=www``
not_before:
Initial validity date for the certificate. This date must be specified
in the format '%Y-%m-%d %H:%M:%S'.
.. versionadded:: 3001
not_after:
Final validity date for the certificate. This date must be specified in
the format '%Y-%m-%d %H:%M:%S'.
.. versionadded:: 3001
CLI Example:
.. code-block:: bash
salt '*' x509.create_certificate path=/etc/pki/myca.crt signing_private_key='/etc/pki/myca.key' csr='/etc/pki/myca.csr'} | Create an X509 certificate. | [
"Create",
"an",
"X509",
"certificate",
"."
] | def create_certificate(path=None, text=False, overwrite=True, ca_server=None, **kwargs):
"""
Create an X509 certificate.
path:
Path to write the certificate to.
text:
If ``True``, return the PEM text without writing to a file.
Default ``False``.
overwrite:
If ``True`` (default), create_certificate will overwrite the entire PEM
file. Set False to preserve existing private keys and dh params that
may exist in the PEM file.
kwargs:
Any of the properties below can be included as additional
keyword arguments.
ca_server:
Request a remotely signed certificate from ca_server. For this to
work, a ``signing_policy`` must be specified, and that same policy
must be configured on the ca_server. See ``signing_policy`` for
details. Also, the salt master must permit peers to call the
``sign_remote_certificate`` function.
Example:
/etc/salt/master.d/peer.conf
.. code-block:: yaml
peer:
.*:
- x509.sign_remote_certificate
subject properties:
Any of the values below can be included to set subject properties
Any other subject properties supported by OpenSSL should also work.
C:
2 letter Country code
CN:
Certificate common name, typically the FQDN.
Email:
Email address
GN:
Given Name
L:
Locality
O:
Organization
OU:
Organization Unit
SN:
SurName
ST:
State or Province
signing_private_key:
A path or string of the private key in PEM format that will be used
to sign this certificate. If neither ``signing_cert``, ``public_key``,
or ``csr`` are included, it will be assumed that this is a self-signed
certificate, and the public key matching ``signing_private_key`` will
be used to create the certificate.
signing_private_key_passphrase:
Passphrase used to decrypt the signing_private_key.
signing_cert:
A certificate matching the private key that will be used to sign this
certificate. This is used to populate the issuer values in the
resulting certificate. Do not include this value for
self-signed certificates.
public_key:
The public key to be included in this certificate. This can be sourced
from a public key, certificate, CSR or private key. If a private key
is used, the matching public key from the private key will be
generated before any processing is done. This means you can request a
certificate from a remote CA using a private key file as your
public_key and only the public key will be sent across the network to
the CA. If neither ``public_key`` or ``csr`` are specified, it will be
assumed that this is a self-signed certificate, and the public key
derived from ``signing_private_key`` will be used. Specify either
``public_key`` or ``csr``, not both. Because you can input a CSR as a
public key or as a CSR, it is important to understand the difference.
If you import a CSR as a public key, only the public key will be added
to the certificate, subject or extension information in the CSR will
be lost.
public_key_passphrase:
If the public key is supplied as a private key, this is the passphrase
used to decrypt it.
csr:
A file or PEM string containing a certificate signing request. This
will be used to supply the subject, extensions and public key of a
certificate. Any subject or extensions specified explicitly will
overwrite any in the CSR.
basicConstraints:
X509v3 Basic Constraints extension.
extensions:
The following arguments set X509v3 Extension values. If the value
starts with ``critical``, the extension will be marked as critical.
Some special extensions are ``subjectKeyIdentifier`` and
``authorityKeyIdentifier``.
``subjectKeyIdentifier`` can be an explicit value or it can be the
special string ``hash``. ``hash`` will set the subjectKeyIdentifier
equal to the SHA1 hash of the modulus of the public key in this
certificate. Note that this is not the exact same hashing method used
by OpenSSL when using the hash value.
``authorityKeyIdentifier`` Use values acceptable to the openssl CLI
tools. This will automatically populate ``authorityKeyIdentifier``
with the ``subjectKeyIdentifier`` of ``signing_cert``. If this is a
self-signed cert these values will be the same.
basicConstraints:
X509v3 Basic Constraints
keyUsage:
X509v3 Key Usage
extendedKeyUsage:
X509v3 Extended Key Usage
subjectKeyIdentifier:
X509v3 Subject Key Identifier
issuerAltName:
X509v3 Issuer Alternative Name
subjectAltName:
X509v3 Subject Alternative Name
crlDistributionPoints:
X509v3 CRL Distribution Points
issuingDistributionPoint:
X509v3 Issuing Distribution Point
certificatePolicies:
X509v3 Certificate Policies
policyConstraints:
X509v3 Policy Constraints
inhibitAnyPolicy:
X509v3 Inhibit Any Policy
nameConstraints:
X509v3 Name Constraints
noCheck:
X509v3 OCSP No Check
nsComment:
Netscape Comment
nsCertType:
Netscape Certificate Type
days_valid:
The number of days this certificate should be valid. This sets the
``notAfter`` property of the certificate. Defaults to 365.
version:
The version of the X509 certificate. Defaults to 3. This is
automatically converted to the version value, so ``version=3``
sets the certificate version field to 0x2.
serial_number:
The serial number to assign to this certificate. If omitted a random
serial number of size ``serial_bits`` is generated.
serial_bits:
The number of bits to use when randomly generating a serial number.
Defaults to 64.
algorithm:
The hashing algorithm to be used for signing this certificate.
Defaults to sha256.
copypath:
An additional path to copy the resulting certificate to. Can be used
to maintain a copy of all certificates issued for revocation purposes.
prepend_cn:
If set to True, the CN and a dash will be prepended to the copypath's filename.
Example:
/etc/pki/issued_certs/www.example.com-DE:CA:FB:AD:00:00:00:00.crt
signing_policy:
A signing policy that should be used to create this certificate.
Signing policies should be defined in the minion configuration, or in
a minion pillar. It should be a YAML formatted list of arguments
which will override any arguments passed to this function. If the
``minions`` key is included in the signing policy, only minions
matching that pattern (see match.glob and match.compound) will be
permitted to remotely request certificates from that policy.
In order to ``match.compound`` to work salt master must peers permit
peers to call it.
Example:
/etc/salt/master.d/peer.conf
.. code-block:: yaml
peer:
.*:
- match.compound
Example:
.. code-block:: yaml
x509_signing_policies:
www:
- minions: 'www*'
- signing_private_key: /etc/pki/ca.key
- signing_cert: /etc/pki/ca.crt
- C: US
- ST: Utah
- L: Salt Lake City
- basicConstraints: "critical CA:false"
- keyUsage: "critical cRLSign, keyCertSign"
- subjectKeyIdentifier: hash
- authorityKeyIdentifier: keyid,issuer:always
- days_valid: 90
- copypath: /etc/pki/issued_certs/
The above signing policy can be invoked with ``signing_policy=www``
not_before:
Initial validity date for the certificate. This date must be specified
in the format '%Y-%m-%d %H:%M:%S'.
.. versionadded:: 3001
not_after:
Final validity date for the certificate. This date must be specified in
the format '%Y-%m-%d %H:%M:%S'.
.. versionadded:: 3001
CLI Example:
.. code-block:: bash
salt '*' x509.create_certificate path=/etc/pki/myca.crt signing_private_key='/etc/pki/myca.key' csr='/etc/pki/myca.csr'}
"""
if (
not path
and not text
and ("testrun" not in kwargs or kwargs["testrun"] is False)
):
raise salt.exceptions.SaltInvocationError(
"Either path or text must be specified."
)
if path and text:
raise salt.exceptions.SaltInvocationError(
"Either path or text must be specified, not both."
)
if "public_key_passphrase" not in kwargs:
kwargs["public_key_passphrase"] = None
if ca_server:
if "signing_policy" not in kwargs:
raise salt.exceptions.SaltInvocationError(
"signing_policy must be specified"
"if requesting remote certificate from ca_server {}.".format(ca_server)
)
if "csr" in kwargs:
kwargs["csr"] = salt.utils.stringutils.to_str(
get_pem_entry(kwargs["csr"], pem_type="CERTIFICATE REQUEST")
).replace("\n", "")
if "public_key" in kwargs:
# Strip newlines to make passing through as cli functions easier
kwargs["public_key"] = salt.utils.stringutils.to_str(
get_public_key(
kwargs["public_key"], passphrase=kwargs["public_key_passphrase"]
)
).replace("\n", "")
# Remove system entries in kwargs
# Including listen_in and prerequired because they are not included
# in STATE_INTERNAL_KEYWORDS
# for salt 2014.7.2
for ignore in list(_STATE_INTERNAL_KEYWORDS) + [
"listen_in",
"prerequired",
"__prerequired__",
]:
kwargs.pop(ignore, None)
# TODO: Make timeout configurable in 3000
certs = __salt__["publish.publish"](
tgt=ca_server,
fun="x509.sign_remote_certificate",
arg=salt.utils.data.decode_dict(kwargs, to_str=True),
timeout=30,
)
if not any(certs):
raise salt.exceptions.SaltInvocationError(
"ca_server did not respond"
" salt master must permit peers to"
" call the sign_remote_certificate function."
)
cert_txt = certs[ca_server]
if isinstance(cert_txt, str):
if not _valid_pem(cert_txt, "CERTIFICATE"):
raise salt.exceptions.SaltInvocationError(cert_txt)
if path:
return write_pem(
text=cert_txt, overwrite=overwrite, path=path, pem_type="CERTIFICATE"
)
else:
return cert_txt
signing_policy = {}
if "signing_policy" in kwargs:
signing_policy = _get_signing_policy(kwargs["signing_policy"])
if isinstance(signing_policy, list):
dict_ = {}
for item in signing_policy:
dict_.update(item)
signing_policy = dict_
# Overwrite any arguments in kwargs with signing_policy
kwargs.update(signing_policy)
for prop, default in CERT_DEFAULTS.items():
if prop not in kwargs:
kwargs[prop] = default
cert = M2Crypto.X509.X509()
# X509 Version 3 has a value of 2 in the field.
# Version 2 has a value of 1.
# https://tools.ietf.org/html/rfc5280#section-4.1.2.1
cert.set_version(kwargs["version"] - 1)
# Random serial number if not specified
if "serial_number" not in kwargs:
kwargs["serial_number"] = _dec2hex(random.getrandbits(kwargs["serial_bits"]))
serial_number = int(kwargs["serial_number"].replace(":", ""), 16)
# With Python3 we occasionally end up with an INT that is greater than a C
# long max_value. This causes an overflow error due to a bug in M2Crypto.
# See issue: https://gitlab.com/m2crypto/m2crypto/issues/232
# Remove this after M2Crypto fixes the bug.
if salt.utils.platform.is_windows():
INT_MAX = 2147483647
if serial_number >= INT_MAX:
serial_number -= int(serial_number / INT_MAX) * INT_MAX
else:
if serial_number >= sys.maxsize:
serial_number -= int(serial_number / sys.maxsize) * sys.maxsize
cert.set_serial_number(serial_number)
# Handle not_before and not_after dates for custom certificate validity
fmt = "%Y-%m-%d %H:%M:%S"
if "not_before" in kwargs:
try:
time = datetime.datetime.strptime(kwargs["not_before"], fmt)
except:
raise salt.exceptions.SaltInvocationError(
"not_before: {} is not in required format {}".format(
kwargs["not_before"], fmt
)
)
# If we do not set an explicit timezone to this naive datetime object,
# the M2Crypto code will assume it is from the local machine timezone
# and will try to adjust the time shift.
time = time.replace(tzinfo=M2Crypto.ASN1.UTC)
asn1_not_before = M2Crypto.ASN1.ASN1_UTCTIME()
asn1_not_before.set_datetime(time)
cert.set_not_before(asn1_not_before)
if "not_after" in kwargs:
try:
time = datetime.datetime.strptime(kwargs["not_after"], fmt)
except:
raise salt.exceptions.SaltInvocationError(
"not_after: {} is not in required format {}".format(
kwargs["not_after"], fmt
)
)
# Forcing the datetime to have an explicit tzinfo here as well.
time = time.replace(tzinfo=M2Crypto.ASN1.UTC)
asn1_not_after = M2Crypto.ASN1.ASN1_UTCTIME()
asn1_not_after.set_datetime(time)
cert.set_not_after(asn1_not_after)
# Set validity dates
# if no 'not_before' or 'not_after' dates are setup, both of the following
# dates will be the date of today. then the days_valid offset makes sense.
not_before = M2Crypto.m2.x509_get_not_before(cert.x509)
not_after = M2Crypto.m2.x509_get_not_after(cert.x509)
# Only process the dynamic dates if start and end are not specified.
if "not_before" not in kwargs:
M2Crypto.m2.x509_gmtime_adj(not_before, 0)
if "not_after" not in kwargs:
valid_seconds = 60 * 60 * 24 * kwargs["days_valid"] # 60s * 60m * 24 * days
M2Crypto.m2.x509_gmtime_adj(not_after, valid_seconds)
# If neither public_key or csr are included, this cert is self-signed
if "public_key" not in kwargs and "csr" not in kwargs:
kwargs["public_key"] = kwargs["signing_private_key"]
if "signing_private_key_passphrase" in kwargs:
kwargs["public_key_passphrase"] = kwargs["signing_private_key_passphrase"]
csrexts = {}
if "csr" in kwargs:
kwargs["public_key"] = kwargs["csr"]
csr = _get_request_obj(kwargs["csr"])
cert.set_subject(csr.get_subject())
csrexts = read_csr(kwargs["csr"])["X509v3 Extensions"]
cert.set_pubkey(
get_public_key(
kwargs["public_key"], passphrase=kwargs["public_key_passphrase"], asObj=True
)
)
subject = cert.get_subject()
for entry in sorted(subject.nid):
if entry in kwargs:
setattr(subject, entry, kwargs[entry])
if "signing_cert" in kwargs:
signing_cert = _get_certificate_obj(kwargs["signing_cert"])
else:
signing_cert = cert
cert.set_issuer(signing_cert.get_subject())
for extname, extlongname in EXT_NAME_MAPPINGS.items():
if (
extname in kwargs
or extlongname in kwargs
or extname in csrexts
or extlongname in csrexts
) is False:
continue
# Use explicitly set values first, fall back to CSR values.
extval = (
kwargs.get(extname)
or kwargs.get(extlongname)
or csrexts.get(extname)
or csrexts.get(extlongname)
)
critical = False
if extval.startswith("critical "):
critical = True
extval = extval[9:]
if extname == "subjectKeyIdentifier" and "hash" in extval:
extval = extval.replace("hash", _get_pubkey_hash(cert))
issuer = None
if extname == "authorityKeyIdentifier":
issuer = signing_cert
if extname == "subjectAltName":
extval = extval.replace("IP Address", "IP")
ext = _new_extension(
name=extname, value=extval, critical=critical, issuer=issuer
)
if not ext.x509_ext:
log.info("Invalid X509v3 Extension. %s: %s", extname, extval)
continue
cert.add_ext(ext)
if "signing_private_key_passphrase" not in kwargs:
kwargs["signing_private_key_passphrase"] = None
if "testrun" in kwargs and kwargs["testrun"] is True:
cert_props = read_certificate(cert)
cert_props["Issuer Public Key"] = get_public_key(
kwargs["signing_private_key"],
passphrase=kwargs["signing_private_key_passphrase"],
)
return cert_props
if not verify_private_key(
private_key=kwargs["signing_private_key"],
passphrase=kwargs["signing_private_key_passphrase"],
public_key=signing_cert,
):
raise salt.exceptions.SaltInvocationError(
"signing_private_key: {} does no match signing_cert: {}".format(
kwargs["signing_private_key"], kwargs.get("signing_cert", "")
)
)
cert.sign(
_get_private_key_obj(
kwargs["signing_private_key"],
passphrase=kwargs["signing_private_key_passphrase"],
),
kwargs["algorithm"],
)
if not verify_signature(cert, signing_pub_key=signing_cert):
raise salt.exceptions.SaltInvocationError(
"failed to verify certificate signature"
)
if "copypath" in kwargs:
if "prepend_cn" in kwargs and kwargs["prepend_cn"] is True:
prepend = str(kwargs["CN"]) + "-"
else:
prepend = ""
write_pem(
text=cert.as_pem(),
path=os.path.join(
kwargs["copypath"], prepend + kwargs["serial_number"] + ".crt"
),
pem_type="CERTIFICATE",
)
if path:
return write_pem(
text=cert.as_pem(), overwrite=overwrite, path=path, pem_type="CERTIFICATE"
)
else:
return salt.utils.stringutils.to_str(cert.as_pem()) | [
"def",
"create_certificate",
"(",
"path",
"=",
"None",
",",
"text",
"=",
"False",
",",
"overwrite",
"=",
"True",
",",
"ca_server",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"(",
"not",
"path",
"and",
"not",
"text",
"and",
"(",
"\"testrun\... | https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/modules/x509.py#L1135-L1688 | ||
isce-framework/isce2 | 0e5114a8bede3caf1d533d98e44dfe4b983e3f48 | components/isceobj/TopsProc/runPrepESD.py | python | runPrepESD | (self) | Create additional layers for performing ESD. | Create additional layers for performing ESD. | [
"Create",
"additional",
"layers",
"for",
"performing",
"ESD",
"."
] | def runPrepESD(self):
'''
Create additional layers for performing ESD.
'''
if not self.doESD:
return
swathList = self._insar.getValidSwathList(self.swaths)
for swath in swathList:
if self._insar.numberOfCommonBursts[swath-1] < 2:
print('Skipping prepesd for swath IW{0}'.format(swath))
continue
minBurst, maxBurst = self._insar.commonReferenceBurstLimits(swath-1)
secondaryBurstStart, secondaryBurstEnd = self._insar.commonSecondaryBurstLimits(swath-1)
####Load full products
reference = self._insar.loadProduct( os.path.join(self._insar.referenceSlcProduct, 'IW{0}.xml'.format(swath)))
secondary = self._insar.loadProduct( os.path.join(self._insar.secondarySlcProduct, 'IW{0}.xml'.format(swath)))
####Estimate relative shifts
relShifts = getRelativeShifts(reference, secondary, minBurst, maxBurst, secondaryBurstStart)
maxBurst = maxBurst - 1 ###For overlaps
####Load metadata for burst IFGs
ifgTop = self._insar.loadProduct( os.path.join(self._insar.coarseIfgOverlapProduct, 'top_IW{0}.xml'.format(swath)))
ifgBottom = self._insar.loadProduct( os.path.join(self._insar.coarseIfgOverlapProduct, 'bottom_IW{0}.xml'.format(swath)))
print('Relative shifts for swath {0}:'.format(swath))
pprint.pprint(relShifts)
####Create ESD output directory
esddir = self._insar.esdDirname
os.makedirs(esddir, exist_ok=True)
####Overlap offsets directory
offdir = os.path.join( self._insar.coarseOffsetsDirname, self._insar.overlapsSubDirname, 'IW{0}'.format(swath))
ifglist = []
factorlist = []
offsetlist = []
cohlist = []
for ii in range(minBurst, maxBurst):
ind = ii - minBurst ###Index into overlaps
sind = secondaryBurstStart + ind ###Index into secondary
topShift = relShifts[sind]
botShift = relShifts[sind+1]
topBurstIfg = ifgTop.bursts[ind]
botBurstIfg = ifgBottom.bursts[ind]
####Double difference interferograms
topInt = np.memmap( topBurstIfg.image.filename,
dtype=np.complex64, mode='r',
shape = (topBurstIfg.numberOfLines, topBurstIfg.numberOfSamples))
botInt = np.memmap( botBurstIfg.image.filename,
dtype=np.complex64, mode='r',
shape = (botBurstIfg.numberOfLines, botBurstIfg.numberOfSamples))
intName = os.path.join(esddir, 'overlap_IW%d_%02d.int'%(swath,ii+1))
freqName = os.path.join(esddir, 'freq_IW%d_%02d.bin'%(swath,ii+1))
with open(intName, 'wb') as fid:
fid.write( topInt * np.conj(botInt))
img = isceobj.createIntImage()
img.setFilename(intName)
img.setLength(topBurstIfg.numberOfLines)
img.setWidth(topBurstIfg.numberOfSamples)
img.setAccessMode('READ')
img.renderHdr()
multIntName= multilook(intName, alks = self.esdAzimuthLooks, rlks=self.esdRangeLooks)
ifglist.append(multIntName)
####Estimate coherence of double different interferograms
multCor = createCoherence(multIntName)
cohlist.append(multCor)
####Estimate the frequency difference
azTop = os.path.join(offdir, 'azimuth_top_%02d_%02d.off'%(ii+1,ii+2))
rgTop = os.path.join(offdir, 'range_top_%02d_%02d.off'%(ii+1,ii+2))
azBot = os.path.join(offdir, 'azimuth_bot_%02d_%02d.off'%(ii+1,ii+2))
rgBot = os.path.join(offdir, 'range_bot_%02d_%02d.off'%(ii+1,ii+2))
mFullTop = reference.bursts[ii]
mFullBot = reference.bursts[ii+1]
sFullTop = secondary.bursts[sind]
sFullBot = secondary.bursts[sind+1]
freqdiff = overlapSpectralSeparation(topBurstIfg, botBurstIfg, mFullTop, mFullBot, sFullTop, sFullBot, azTop, rgTop, azBot, rgBot)
with open(freqName, 'wb') as fid:
(freqdiff * 2 * np.pi * mFullTop.azimuthTimeInterval).astype(np.float32).tofile(fid)
img = isceobj.createImage()
img.setFilename(freqName)
img.setWidth(topBurstIfg.numberOfSamples)
img.setLength(topBurstIfg.numberOfLines)
img.setAccessMode('READ')
img.bands = 1
img.dataType = 'FLOAT'
img.renderHdr()
multConstName = multilook(freqName, alks = self.esdAzimuthLooks, rlks = self.esdRangeLooks)
factorlist.append(multConstName) | [
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dropbox/changes | 37e23c3141b75e4785cf398d015e3dbca41bdd56 | changes/queue/task.py | python | TrackedTask._update | (self, kwargs) | return bool(count) | Update's the state of this Task.
>>> task._update(status=Status.finished)
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Update's the state of this Task.
>>> task._update(status=Status.finished)
Returns:
bool: Whether anything was updated.
"""
assert self.task_id
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wistbean/fxxkpython | 88e16d79d8dd37236ba6ecd0d0ff11d63143968c | vip/qyxuan/projects/venv/lib/python3.6/site-packages/pygame/examples/arraydemo.py | python | surfdemo_show | (array_img, name) | displays a surface, waits for user to continue | displays a surface, waits for user to continue | [
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"waits",
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] | def surfdemo_show(array_img, name):
"displays a surface, waits for user to continue"
screen = pygame.display.set_mode(array_img.shape[:2], 0, 32)
surfarray.blit_array(screen, array_img)
pygame.display.flip()
pygame.display.set_caption(name)
while 1:
e = pygame.event.wait()
if e.type == MOUSEBUTTONDOWN: break
elif e.type == KEYDOWN and e.key == K_s:
#pygame.image.save(screen, name+'.bmp')
#s = pygame.Surface(screen.get_size(), 0, 32)
#s = s.convert_alpha()
#s.fill((0,0,0,255))
#s.blit(screen, (0,0))
#s.fill((222,0,0,50), (0,0,40,40))
#pygame.image.save_extended(s, name+'.png')
#pygame.image.save(s, name+'.png')
#pygame.image.save(screen, name+'_screen.png')
#pygame.image.save(s, name+'.tga')
pygame.image.save(screen, name+'.png')
elif e.type == QUIT:
raise SystemExit() | [
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bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/full/dbm/dumb.py | python | _Database._setval | (self, pos, val) | return (pos, len(val)) | [] | def _setval(self, pos, val):
with _io.open(self._datfile, 'rb+') as f:
f.seek(pos)
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rhinstaller/anaconda | 63edc8680f1b05cbfe11bef28703acba808c5174 | pyanaconda/core/configuration/anaconda.py | python | AnacondaConfiguration.set_from_opts | (self, opts) | Set the configuration from the Anaconda cmdline options.
This code is too related to the Anaconda cmdline options, so it shouldn't
be part of this class. We should find a better, more universal, way to change
the Anaconda configuration.
FIXME: This is a temporary solution.
:param opts: a namespace of options | Set the configuration from the Anaconda cmdline options. | [
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] | def set_from_opts(self, opts):
"""Set the configuration from the Anaconda cmdline options.
This code is too related to the Anaconda cmdline options, so it shouldn't
be part of this class. We should find a better, more universal, way to change
the Anaconda configuration.
FIXME: This is a temporary solution.
:param opts: a namespace of options
"""
if opts.debug:
self.anaconda._set_option("debug", True)
# Set "nosave flags".
if "can_copy_input_kickstart" in opts:
self.target._set_option("can_copy_input_kickstart", opts.can_copy_input_kickstart)
if "can_save_output_kickstart" in opts:
self.target._set_option("can_save_output_kickstart", opts.can_save_output_kickstart)
if "can_save_installation_logs" in opts:
self.target._set_option("can_save_installation_logs", opts.can_save_installation_logs)
# Set the bootloader type.
if opts.extlinux:
self.bootloader._set_option("type", BootloaderType.EXTLINUX.value)
# Set the boot loader flags.
self.bootloader._set_option("nonibft_iscsi_boot", opts.nonibftiscsiboot)
# Set the storage flags.
self.storage._set_option("dmraid", opts.dmraid)
self.storage._set_option("ibft", opts.ibft)
if hasattr(opts, "gpt"):
self.storage._set_option("gpt", opts.gpt)
self.storage._set_option("multipath_friendly_names", opts.multipath_friendly_names)
# Set up the rescue mode.
if opts.rescue:
self.storage._set_option("allow_imperfect_devices", True)
# Set the security flags.
self.security._set_option("selinux", opts.selinux)
# Set the type of the installation system.
if opts.liveinst:
self.system._set_option("type", SystemType.LIVE_OS.value)
elif opts.images or opts.dirinstall:
self.system._set_option("type", SystemType.UNKNOWN.value)
else:
self.system._set_option("type", SystemType.BOOT_ISO.value)
# Set the type of the installation target.
if opts.images:
# The image installation is requested.
self.target._set_option("type", TargetType.IMAGE.value)
elif opts.dirinstall:
# The dir installation is requested.
self.target._set_option("type", TargetType.DIRECTORY.value)
self.target._set_option("physical_root", opts.dirinstall)
# Set the payload flags.
if opts.noverifyssl:
self.payload._set_option("verify_ssl", not opts.noverifyssl)
self.validate() | [
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shapely/shapely | 9258e6dd4dcca61699d69c2a5853a486b132ed86 | shapely/geometry/base.py | python | BaseGeometry.minimum_clearance | (self) | return float(shapely.minimum_clearance(self)) | Unitless distance by which a node could be moved to produce an invalid geometry (float) | Unitless distance by which a node could be moved to produce an invalid geometry (float) | [
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] | def minimum_clearance(self):
"""Unitless distance by which a node could be moved to produce an invalid geometry (float)"""
return float(shapely.minimum_clearance(self)) | [
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dropbox/dropbox-sdk-python | 015437429be224732990041164a21a0501235db1 | dropbox/team_log.py | python | EventDetails.get_sharing_change_link_enforce_password_policy_details | (self) | return self._value | Only call this if :meth:`is_sharing_change_link_enforce_password_policy_details` is true.
:rtype: SharingChangeLinkEnforcePasswordPolicyDetails | Only call this if :meth:`is_sharing_change_link_enforce_password_policy_details` is true. | [
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"""
Only call this if :meth:`is_sharing_change_link_enforce_password_policy_details` is true.
:rtype: SharingChangeLinkEnforcePasswordPolicyDetails
"""
if not self.is_sharing_change_link_enforce_password_policy_details():
raise AttributeError("tag 'sharing_change_link_enforce_password_policy_details' not set")
return self._value | [
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ni/nidaqmx-python | 62fc6b48cbbb330fe1bcc9aedadc86610a1269b6 | nidaqmx/_task_modules/channels/ci_channel.py | python | CIChannel.ci_velocity_a_input_dig_fltr_enable | (self) | [] | def ci_velocity_a_input_dig_fltr_enable(self):
cfunc = (lib_importer.windll.
DAQmxResetCIVelocityEncoderAInputDigFltrEnable)
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
lib_importer.task_handle, ctypes_byte_str]
error_code = cfunc(
self._handle, self._name)
check_for_error(error_code) | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | ansible/roles/lib_oa_openshift/library/oc_adm_router.py | python | RoleBindingConfig.create_dict | (self) | create a default rolebinding as a dict | create a default rolebinding as a dict | [
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] | def create_dict(self):
''' create a default rolebinding as a dict '''
self.data['apiVersion'] = 'v1'
self.data['kind'] = 'RoleBinding'
self.data['groupNames'] = self.group_names
self.data['metadata']['name'] = self.name
self.data['metadata']['namespace'] = self.namespace
self.data['roleRef'] = self.role_ref
self.data['subjects'] = self.subjects
self.data['userNames'] = self.usernames | [
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eleurent/highway-env | 9d63973da854584fe51b00ccee7b24b1bf031418 | highway_env/envs/common/abstract.py | python | AbstractEnv._reset | (self) | Reset the scene: roads and vehicles.
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] | def _reset(self) -> None:
"""
Reset the scene: roads and vehicles.
This method must be overloaded by the environments.
"""
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spl0k/supysonic | 62bad3b9878a1d22cf040f25dab0fa28a252ba38 | supysonic/daemon/client.py | python | AddWatchedFolderCommand.apply | (self, connection, daemon) | [] | def apply(self, connection, daemon):
if daemon.watcher is not None:
daemon.watcher.add_folder(self._folder) | [
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nschloe/quadpy | c4c076d8ddfa968486a2443a95e2fb3780dcde0f | src/quadpy/c3/_classical.py | python | face_midpoint | () | return C3Scheme("Face-Midpoint", d, 3) | [] | def face_midpoint():
d = {"symm_r00": [[frac(1, 6)], [1]]}
return C3Scheme("Face-Midpoint", d, 3) | [
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mehulj94/BrainDamage | 49a29c2606d5f7c0d9705ae5f4201a6bb25cfe73 | Echoes/ftpnavigator.py | python | FtpNavigator.read_file | (self, filepath) | return pwdFound | [] | def read_file(self, filepath):
f = open(filepath, 'r')
pwdFound = []
for ff in f.readlines():
values = {}
info = ff.split(';')
for i in info:
i = i.split('=')
if i[0] == 'Name':
values['Name'] = i[1]
if i[0] == 'Server':
values['Server'] = i[1]
if i[0] == 'Port':
values['Port'] = i[1]
if i[0] == 'User':
values['User'] = i[1]
if i[0] == "Password":
if i[1] != '1' and i[1] != '0':
values['Password'] = self.decode(i[1])
# used to save the password if it is an anonymous authentication
if values['User'] == 'anonymous' and 'Password' not in values.keys():
values['Password'] = 'anonymous'
pwdFound.append(values)
# print the results
return pwdFound | [
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betamaxpy/betamax | f06fe32d657a8c78b6e5a00048dff7fa50ad9be6 | src/betamax/matchers/base.py | python | BaseMatcher.match | (self, request, recorded_request) | A method that must be implemented by the user.
:param PreparedRequest request: A requests PreparedRequest object
:param dict recorded_request: A dictionary containing the serialized
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careermonk/data-structures-and-algorithmic-thinking-with-python | 3c07d9dcec4fd06d0958a96fecd5e228f0378112 | src/chapter06trees/FindMaxInBSTRecursive.py | python | BSTNode.rotateLeft | (self) | Q P
/ \ / \
C P ==> Q B
/ \ / \
A B C A | Q P
/ \ / \
C P ==> Q B
/ \ / \
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'''
Q P
/ \ / \
C P ==> Q B
/ \ / \
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'''
# If you do not understand at first, note that instead of
# moving Q to C's position, I move P instead. So think on
# terms of "P will be future Q"
Q, P = self, self.right
if not P: return
Q.right = P.right
P.right = P.left
P.left = Q.left
Q.left = P
if P.left: P.left.parent = P
if Q.right: Q.right.parent = Q
P.data, Q.data = Q.data, P.data | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.40/roles/openshift_facts/library/openshift_facts.py | python | delete_empty_keys | (keylist) | Delete dictionary elements from keylist where "value" is empty.
Args:
keylist(list): A list of builddefault configuration envs.
Returns:
none
Example:
keylist = [{'name': 'HTTP_PROXY', 'value': 'http://file.rdu.redhat.com:3128'},
{'name': 'HTTPS_PROXY', 'value': 'http://file.rdu.redhat.com:3128'},
{'name': 'NO_PROXY', 'value': ''}]
After calling delete_empty_keys the provided list is modified to become:
[{'name': 'HTTP_PROXY', 'value': 'http://file.rdu.redhat.com:3128'},
{'name': 'HTTPS_PROXY', 'value': 'http://file.rdu.redhat.com:3128'}] | Delete dictionary elements from keylist where "value" is empty. | [
"Delete",
"dictionary",
"elements",
"from",
"keylist",
"where",
"value",
"is",
"empty",
"."
] | def delete_empty_keys(keylist):
""" Delete dictionary elements from keylist where "value" is empty.
Args:
keylist(list): A list of builddefault configuration envs.
Returns:
none
Example:
keylist = [{'name': 'HTTP_PROXY', 'value': 'http://file.rdu.redhat.com:3128'},
{'name': 'HTTPS_PROXY', 'value': 'http://file.rdu.redhat.com:3128'},
{'name': 'NO_PROXY', 'value': ''}]
After calling delete_empty_keys the provided list is modified to become:
[{'name': 'HTTP_PROXY', 'value': 'http://file.rdu.redhat.com:3128'},
{'name': 'HTTPS_PROXY', 'value': 'http://file.rdu.redhat.com:3128'}]
"""
count = 0
for i in range(0, len(keylist)):
if len(keylist[i - count]['value']) == 0:
del keylist[i - count]
count += 1 | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/whoosh/fields.py | python | ReverseField.subfields | (self) | [] | def subfields(self):
yield "", self.subfield
yield self.name_prefix, self | [
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/scattergeo/selected/_textfont.py | python | Textfont.color | (self) | return self["color"] | Sets the text font color of selected points.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
Returns
-------
str | Sets the text font color of selected points.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen | [
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"""
Sets the text font color of selected points.
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
Returns
-------
str
"""
return self["color"] | [
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] | https://github.com/plotly/plotly.py/blob/cfad7862594b35965c0e000813bd7805e8494a5b/packages/python/plotly/plotly/graph_objs/scattergeo/selected/_textfont.py#L16-L66 | |
IndicoDataSolutions/finetune | 83ba222eed331df64b2fa7157bb64f0a2eef4a2c | finetune/optimizers/recompute_grads.py | python | underlying_variable_ref | (t) | Find the underlying variable ref.
Traverses through Identity, ReadVariableOp, and Enter ops.
Stops when op type has Variable or VarHandle in name.
Args:
t: a Tensor
Returns:
a Tensor that is a variable ref, or None on error. | Find the underlying variable ref.
Traverses through Identity, ReadVariableOp, and Enter ops.
Stops when op type has Variable or VarHandle in name.
Args:
t: a Tensor
Returns:
a Tensor that is a variable ref, or None on error. | [
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"""Find the underlying variable ref.
Traverses through Identity, ReadVariableOp, and Enter ops.
Stops when op type has Variable or VarHandle in name.
Args:
t: a Tensor
Returns:
a Tensor that is a variable ref, or None on error.
"""
while t.op.type in ["Identity", "ReadVariableOp", "Enter"]:
t = t.op.inputs[0]
op_type = t.op.type
if "Variable" in op_type or "VarHandle" in op_type:
return t
else:
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microsoft/debugpy | be8dd607f6837244e0b565345e497aff7a0c08bf | src/debugpy/_vendored/pydevd/third_party/pep8/autopep8.py | python | FixPEP8.fix_long_line_logically | (self, result, logical) | Try to make lines fit within --max-line-length characters. | Try to make lines fit within --max-line-length characters. | [
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"fit",
"within",
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"-",
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"length",
"characters",
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] | def fix_long_line_logically(self, result, logical):
"""Try to make lines fit within --max-line-length characters."""
if (
not logical or
len(logical[2]) == 1 or
self.source[result['line'] - 1].lstrip().startswith('#')
):
return self.fix_long_line_physically(result)
start_line_index = logical[0][0]
end_line_index = logical[1][0]
logical_lines = logical[2]
previous_line = get_item(self.source, start_line_index - 1, default='')
next_line = get_item(self.source, end_line_index + 1, default='')
single_line = join_logical_line(''.join(logical_lines))
try:
fixed = self.fix_long_line(
target=single_line,
previous_line=previous_line,
next_line=next_line,
original=''.join(logical_lines))
except (SyntaxError, tokenize.TokenError):
return self.fix_long_line_physically(result)
if fixed:
for line_index in range(start_line_index, end_line_index + 1):
self.source[line_index] = ''
self.source[start_line_index] = fixed
return range(start_line_index + 1, end_line_index + 1)
else:
return [] | [
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aws/aws-xray-sdk-python | 71436ad7f275c603298da68bee072af7c214cfc3 | aws_xray_sdk/core/models/dummy_entities.py | python | DummySubsegment.add_exception | (self, exception, stack, remote=False) | No-op | No-op | [
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"""
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ronf/asyncssh | ee1714c598d8c2ea6f5484e465443f38b68714aa | asyncssh/sftp.py | python | SFTPServerHandler._process_rename | (self, packet: SSHPacket) | Process an incoming SFTP rename request | Process an incoming SFTP rename request | [
"Process",
"an",
"incoming",
"SFTP",
"rename",
"request"
] | async def _process_rename(self, packet: SSHPacket) -> None:
"""Process an incoming SFTP rename request"""
oldpath = packet.get_string()
newpath = packet.get_string()
if self._version >= 5:
flags = packet.get_uint32()
flag_text = ', flags=0x%08x' % flags
else:
flags = 0
flag_text = ''
if self._version < 6:
packet.check_end()
self.logger.debug1('Received rename request from %s to %s%s',
oldpath, newpath, flag_text)
if flags:
result = self._server.posix_rename(oldpath, newpath)
else:
result = self._server.rename(oldpath, newpath)
if inspect.isawaitable(result):
assert result is not None
await result | [
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... | https://github.com/ronf/asyncssh/blob/ee1714c598d8c2ea6f5484e465443f38b68714aa/asyncssh/sftp.py#L5887-L5913 | ||
MrH0wl/Cloudmare | 65e5bc9888f9d362ab2abfb103ea6c1e869d67aa | thirdparty/bs4/element.py | python | NavigableString.__getattr__ | (self, attr) | text.string gives you text. This is for backwards
compatibility for Navigable*String, but for CData* it lets you
get the string without the CData wrapper. | text.string gives you text. This is for backwards
compatibility for Navigable*String, but for CData* it lets you
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] | def __getattr__(self, attr):
"""text.string gives you text. This is for backwards
compatibility for Navigable*String, but for CData* it lets you
get the string without the CData wrapper."""
if attr == 'string':
return self
else:
raise AttributeError(
"'%s' object has no attribute '%s'" % (
self.__class__.__name__, attr)) | [
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jacoxu/encoder_decoder | 6829c3bc42105aedfd1b8a81c81be19df4326c0a | keras/old_models.py | python | Sequential.save_weights | (self, filepath, overwrite=False) | Dump all layer weights to a HDF5 file. | Dump all layer weights to a HDF5 file. | [
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] | def save_weights(self, filepath, overwrite=False):
'''Dump all layer weights to a HDF5 file.
'''
import h5py
import os.path
# if file exists and should not be overwritten
if not overwrite and os.path.isfile(filepath):
import sys
get_input = input
if sys.version_info[:2] <= (2, 7):
get_input = raw_input
overwrite = get_input('[WARNING] %s already exists - overwrite? '
'[y/n]' % (filepath))
while overwrite not in ['y', 'n']:
overwrite = get_input('Enter "y" (overwrite) or "n" (cancel).')
if overwrite == 'n':
return
print('[TIP] Next time specify overwrite=True in save_weights!')
f = h5py.File(filepath, 'w')
f.attrs['nb_layers'] = len(self.layers)
for k, l in enumerate(self.layers):
g = f.create_group('layer_{}'.format(k))
weights = l.get_weights()
g.attrs['nb_params'] = len(weights)
for n, param in enumerate(weights):
param_name = 'param_{}'.format(n)
param_dset = g.create_dataset(param_name, param.shape,
dtype=param.dtype)
param_dset[:] = param
f.flush()
f.close() | [
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"... | https://github.com/jacoxu/encoder_decoder/blob/6829c3bc42105aedfd1b8a81c81be19df4326c0a/keras/old_models.py#L865-L896 | ||
edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/tencentcloud/vpc/v20170312/vpc_client.py | python | VpcClient.ModifySubnetAttribute | (self, request) | 本接口（ModifySubnetAttribute）用于修改子网属性。
:param request: 调用ModifySubnetAttribute所需参数的结构体。
:type request: :class:`tencentcloud.vpc.v20170312.models.ModifySubnetAttributeRequest`
:rtype: :class:`tencentcloud.vpc.v20170312.models.ModifySubnetAttributeResponse` | 本接口（ModifySubnetAttribute）用于修改子网属性。 | [
"本接口（ModifySubnetAttribute）用于修改子网属性。"
] | def ModifySubnetAttribute(self, request):
"""本接口（ModifySubnetAttribute）用于修改子网属性。
:param request: 调用ModifySubnetAttribute所需参数的结构体。
:type request: :class:`tencentcloud.vpc.v20170312.models.ModifySubnetAttributeRequest`
:rtype: :class:`tencentcloud.vpc.v20170312.models.ModifySubnetAttributeResponse`
"""
try:
params = request._serialize()
body = self.call("ModifySubnetAttribute", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifySubnetAttributeResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise e
else:
raise TencentCloudSDKException(e.message, e.message) | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/returns/estimators.py | python | AdvantageEstimator.__init__ | (self, storage, value, q_value, gamma=1., standardize=False) | Initialize the Advantage estimator.
Args:
storage (RolloutStorage): rollout storage
value (Value): value function approximator.
q_value (QValue, Estimator): Q-value function approximator, or estimator.
gamma (float): discount factor
standardize (bool): If True, it will standardize the advantage estimates. | Initialize the Advantage estimator. | [
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"""
Initialize the Advantage estimator.
Args:
storage (RolloutStorage): rollout storage
value (Value): value function approximator.
q_value (QValue, Estimator): Q-value function approximator, or estimator.
gamma (float): discount factor
standardize (bool): If True, it will standardize the advantage estimates.
"""
super(AdvantageEstimator, self).__init__(storage=storage, gamma=gamma)
# check value function
if not isinstance(value, Value):
raise TypeError("Expecting the given value to be an instance of `Value`, instead got: "
"{}".format(type(value)))
self._value = value
# check q-value
if not isinstance(q_value, (QValue, Estimator)):
raise TypeError("Expecting the given q_value to be an instance of `QValue` or `Estimator`, instead got: "
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self._q_value = q_value
# set if we should standardize or not
self._standardize = bool(standardize) | [
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skelsec/pypykatz | dd129ff36e00593d1340776b517f7e749ad8d314 | pypykatz/crypto/des.py | python | triple_des.decrypt | (self, data, pad=None, padmode=None) | return self._unpadData(data, pad, padmode) | decrypt(data, [pad], [padmode]) -> bytes
data : bytes to be encrypted
pad : Optional argument for decryption padding. Must only be one byte
padmode : Optional argument for overriding the padding mode.
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"""decrypt(data, [pad], [padmode]) -> bytes
data : bytes to be encrypted
pad : Optional argument for decryption padding. Must only be one byte
padmode : Optional argument for overriding the padding mode.
The data must be a multiple of 8 bytes and will be decrypted
with the already specified key. In PAD_NORMAL mode, if the
optional padding character is supplied, then the un-encrypted
data will have the padding characters removed from the end of
the bytes. This pad removal only occurs on the last 8 bytes of
the data (last data block). In PAD_PKCS5 mode, the special
padding end markers will be removed from the data after
decrypting, no pad character is required for PAD_PKCS5.
"""
ENCRYPT = des.ENCRYPT
DECRYPT = des.DECRYPT
data = self._guardAgainstUnicode(data)
if pad is not None:
pad = self._guardAgainstUnicode(pad)
if self.getMode() == CBC:
self.__key1.setIV(self.getIV())
self.__key2.setIV(self.getIV())
self.__key3.setIV(self.getIV())
i = 0
result = []
while i < len(data):
iv = data[i:i+8]
block = self.__key3.crypt(iv, DECRYPT)
block = self.__key2.crypt(block, ENCRYPT)
block = self.__key1.crypt(block, DECRYPT)
self.__key1.setIV(iv)
self.__key2.setIV(iv)
self.__key3.setIV(iv)
result.append(block)
i += 8
if _pythonMajorVersion < 3:
data = ''.join(result)
else:
data = bytes.fromhex('').join(result)
else:
data = self.__key3.crypt(data, DECRYPT)
data = self.__key2.crypt(data, ENCRYPT)
data = self.__key1.crypt(data, DECRYPT)
return self._unpadData(data, pad, padmode) | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/packages/site-packages/sqlalchemy/sql/operators.py | python | ColumnOperators.__le__ | (self, other) | return self.operate(le, other) | Implement the ``<=`` operator.
In a column context, produces the clause ``a <= b``. | Implement the ``<=`` operator. | [
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"""Implement the ``<=`` operator.
In a column context, produces the clause ``a <= b``.
"""
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MenglinLu/Chinese-clinical-NER | 9614593ee2e1ba38d0985c44e957d316e178b93c | bert_sklearn_bioes/bert_sklearn/finetune.py | python | eval_model | (model, dataloader, config, desc="Validation") | return res | Evaluate model on validation data.
Parameters
----------
model : BertPlusMLP
Bert model plus mlp head
dataloader : Dataloader
validation dataloader
device : torch.device
device to run validation on
model_type : string
'text_classifier' | 'text_regressor' | 'token_classifier'
Returns
-------
loss : float
Loss calculated on eval data
accy : float
Classification accuracy for classifiers.
Pearson coorelation for regressors. | Evaluate model on validation data. | [
"Evaluate",
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"on",
"validation",
"data",
"."
] | def eval_model(model, dataloader, config, desc="Validation"):
"""
Evaluate model on validation data.
Parameters
----------
model : BertPlusMLP
Bert model plus mlp head
dataloader : Dataloader
validation dataloader
device : torch.device
device to run validation on
model_type : string
'text_classifier' | 'text_regressor' | 'token_classifier'
Returns
-------
loss : float
Loss calculated on eval data
accy : float
Classification accuracy for classifiers.
Pearson coorelation for regressors.
"""
device = config.device
model_type = config.model_type
ignore_label = config.ignore_label_id
regression_stats = OnlinePearson()
stats = OnlineF1(ignore_label=ignore_label)
model.to(device)
model.eval()
loss = accy = 0.
total_evals = 0
res = {}
batch_iter = tqdm(dataloader, desc=desc, leave=False)
for eval_steps, batch in enumerate(batch_iter):
batch = tuple(t.to(device) for t in batch)
_, _, _, y = batch
with torch.no_grad():
tmp_eval_loss, output = model(*batch)
loss += tmp_eval_loss.mean().item()
if model_type == "text_classifier":
_, y_pred = torch.max(output, 1)
accy += torch.sum(y_pred == y)
elif model_type == "text_regressor":
y_pred = output
# add to online stats calculator
for xi, yi in zip(y.detach().cpu().numpy(),
y_pred.detach().cpu().numpy()):
regression_stats.add(xi, yi)
elif model_type == "token_classifier":
output = output.view(-1, output.shape[-1])
y_true = y.view(-1)
valid_tokens = y_true != -1
_, y_pred = torch.max(output, 1)
accy += torch.sum(y_pred[valid_tokens] == y_true[valid_tokens])
total_evals += torch.sum(valid_tokens).item()
y_true = y_true[valid_tokens].detach().cpu().numpy()
y_pred = y_pred[valid_tokens].detach().cpu().numpy()
# add to online stats calculator
stats.add(y_true=y_true, y_pred=y_pred)
loss = loss/(eval_steps+1)
if model_type == "text_classifier":
accy = 100 * (accy.item() / len(dataloader.dataset))
elif model_type == "text_regressor":
accy = 100 * regression_stats.pearson
elif model_type == "token_classifier":
accy = 100 * (accy.item() / total_evals)
res['f1'] = stats.f1
res['precision'] = stats.precision
res['recall'] = stats.recall
res['loss'] = loss
res['accy'] = accy
return res | [
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facebookresearch/pytext | 1a4e184b233856fcfb9997d74f167cbf5bbbfb8d | pytext/data/data_handler.py | python | DataHandler.preprocess_row | (self, row_data: Dict[str, Any]) | return row_data | preprocess steps for a single input row, sub class should override it | preprocess steps for a single input row, sub class should override it | [
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"""
preprocess steps for a single input row, sub class should override it
"""
return row_data | [
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commonsense/conceptnet | 57e783facbff63a1ef5c581fe2e4a899f97a0ad1 | conceptnet/concepttools/concepttools.py | python | ConceptTools.project_spatial | (self,textnode_list) | return self.spreading_activation(textnode_list,linktype_weights=linktype_weights_dict) | -inputs a list of concepts
-computes the spatial projection, which consists of
relevant locations, relevant objects in the same scene.
-returns a rank-ordered list of concepts and their scores
e.g.: (('concept1',score1), ('concept2,score2), ...) | -inputs a list of concepts
-computes the spatial projection, which consists of
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e.g.: (('concept1',score1), ('concept2,score2), ...)
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linktype_weights_dict = ({
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return self.spreading_activation(textnode_list,linktype_weights=linktype_weights_dict) | [
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suavecode/SUAVE | 4f83c467c5662b6cc611ce2ab6c0bdd25fd5c0a5 | trunk/SUAVE/Core/Data.py | python | Data.append | (self,value,key=None) | Adds new values to the classes. Can also change an already appended key
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/kombu-4.3.0/kombu/log.py | python | get_loglevel | (level) | return level | Get loglevel by name. | Get loglevel by name. | [
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"""Get loglevel by name."""
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rackerlabs/mimic | efd34108b6aa3eb7ecd26e22f1aa155c14a7885e | mimic/model/rackspace_images.py | python | RackspaceOnMetalCentOSImage.metadata_json | (self) | return {
"flavor_classes": "onmetal",
"image_type": "base",
"os_type": "linux",
"org.openstack__1__os_distro": "org.centos",
"vm_mode": "metal",
"auto_disk_config": "disabled"
} | Create a JSON-serializable data structure describing
``metadata`` for an image. | Create a JSON-serializable data structure describing
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"""
Create a JSON-serializable data structure describing
``metadata`` for an image.
"""
return {
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"os_type": "linux",
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openstack/cinder | 23494a6d6c51451688191e1847a458f1d3cdcaa5 | cinder/volume/drivers/nimble.py | python | NimbleBaseVolumeDriver.delete_group | (self, context, group, volumes) | return model_updates, volume_model_updates | Deletes a group. | Deletes a group. | [
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] | def delete_group(self, context, group, volumes):
"""Deletes a group."""
if not volume_utils.is_group_a_cg_snapshot_type(group):
raise NotImplementedError()
LOG.info("Delete Consistency Group %s.", group.id)
model_updates = {"status": fields.GroupStatus.DELETED}
error_statuses = [
fields.GroupStatus.ERROR,
fields.GroupStatus.ERROR_DELETING,
]
volume_model_updates = []
for tmp_volume in volumes:
update_item = {"id": tmp_volume.id}
try:
self.delete_volume(tmp_volume)
update_item["status"] = "deleted"
except exception.VolumeBackendAPIException:
update_item["status"] = fields.VolumeStatus.ERROR_DELETING
if model_updates["status"] not in error_statuses:
model_updates["status"] = fields.GroupStatus.ERROR_DELETING
LOG.error("Failed to delete volume %(vol_id)s of "
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{"vol_id": tmp_volume.id, "group_id": group.id})
volume_model_updates.append(update_item)
cg_name = group.id
cg_id = self.APIExecutor.get_volcoll_id_by_name(cg_name)
self.APIExecutor.delete_volcoll(cg_id)
return model_updates, volume_model_updates | [
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glouppe/info8006-introduction-to-ai | 8360cc9a8c418559e402be1454ec885b6c1062d7 | projects/project1/pacman_module/graphicsDisplay.py | python | PacmanGraphics.updateDistributions | (self, distributions) | Draws an agent's belief distributions | Draws an agent's belief distributions | [
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"Draws an agent's belief distributions"
# copy all distributions so we don't change their state
distributions = [np.copy(x) for x in distributions]
if self.distributionImages is None:
self.drawDistributions(self.previousState)
for x in range(len(self.distributionImages)):
for y in range(len(self.distributionImages[0])):
image = self.distributionImages[x][y]
weights = [dist[x][y] for dist in distributions]
if sum(weights) != 0:
pass
# Fog of war
color = [0.0, 0.0, 0.0]
colors = GHOST_VEC_COLORS[1:] # With Pacman
if self.capture:
colors = GHOST_VEC_COLORS
for weight, gcolor in zip(weights, colors):
color = [min(1.0, c + 0.95 * g * weight ** .3)
for c, g in zip(color, gcolor)]
changeColor(image, formatColor(*color))
refresh() | [
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dask/dask | c2b962fec1ba45440fe928869dc64cfe9cc36506 | dask/array/reductions.py | python | make_arg_reduction | (func, argfunc, is_nan_func=False) | return derived_from(np)(wrapped) | Create an argreduction callable
Parameters
----------
func : callable
The reduction (e.g. ``min``)
argfunc : callable
The argreduction (e.g. ``argmin``) | Create an argreduction callable | [
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"""Create an argreduction callable
Parameters
----------
func : callable
The reduction (e.g. ``min``)
argfunc : callable
The argreduction (e.g. ``argmin``)
"""
chunk = partial(arg_chunk, func, argfunc)
combine = partial(arg_combine, func, argfunc)
if is_nan_func:
agg = partial(nanarg_agg, func, argfunc)
else:
agg = partial(arg_agg, func, argfunc)
def wrapped(x, axis=None, split_every=None, out=None):
return arg_reduction(
x, chunk, combine, agg, axis, split_every=split_every, out=out
)
wrapped.__name__ = func.__name__
return derived_from(np)(wrapped) | [
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jython/jython3 | def4f8ec47cb7a9c799ea4c745f12badf92c5769 | lib-python/3.5.1/_collections_abc.py | python | MutableSet.discard | (self, value) | Remove an element. Do not raise an exception if absent. | Remove an element. Do not raise an exception if absent. | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/site-packages/pip/_vendor/colorama/ansi.py | python | AnsiCursor.UP | (self, n=1) | return CSI + str(n) + 'A' | [] | def UP(self, n=1):
return CSI + str(n) + 'A' | [
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kupferlauncher/kupfer | 1c1e9bcbce05a82f503f68f8b3955c20b02639b3 | waflib/Build.py | python | BuildContext.add_post_fun | (self, meth) | Binds a callback method to execute immediately after the build is successful::
def call_ldconfig(bld):
bld.exec_command('/sbin/ldconfig')
def build(bld):
if bld.cmd == 'install':
bld.add_pre_fun(call_ldconfig) | Binds a callback method to execute immediately after the build is successful:: | [
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"""
Binds a callback method to execute immediately after the build is successful::
def call_ldconfig(bld):
bld.exec_command('/sbin/ldconfig')
def build(bld):
if bld.cmd == 'install':
bld.add_pre_fun(call_ldconfig)
"""
try:
self.post_funs.append(meth)
except AttributeError:
self.post_funs = [meth] | [
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HymanLiuTS/flaskTs | 286648286976e85d9b9a5873632331efcafe0b21 | flasky/lib/python2.7/site-packages/sqlalchemy/sql/operators.py | python | ColumnOperators.__lt__ | (self, other) | return self.operate(lt, other) | Implement the ``<`` operator.
In a column context, produces the clause ``a < b``. | Implement the ``<`` operator. | [
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] | def __lt__(self, other):
"""Implement the ``<`` operator.
In a column context, produces the clause ``a < b``.
"""
return self.operate(lt, other) | [
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qxf2/qxf2-page-object-model | 8b2978e5bd2a5413d581f9e29a2098e5f5e742fd | utils/email_util.py | python | Email_Util.login | (self,username,password) | return result_flag | Login to the email | Login to the email | [
"Login",
"to",
"the",
"email"
] | def login(self,username,password):
"Login to the email"
result_flag = False
try:
self.mail.login(username,password)
except Exception as e:
print('\nException in Email_Util.login')
print('PYTHON SAYS:')
print(e)
print('\n')
else:
result_flag = True
return result_flag | [
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saic-vul/image_harmonization | 7f71cc131cd81f7a9dc7116c52428d4d75046085 | iharm/model/modeling/conv_autoencoder.py | python | DeconvDecoder.__init__ | (self, depth, encoder_blocks_channels, norm_layer, attend_from=-1, image_fusion=False) | [] | def __init__(self, depth, encoder_blocks_channels, norm_layer, attend_from=-1, image_fusion=False):
super(DeconvDecoder, self).__init__()
self.image_fusion = image_fusion
self.deconv_blocks = nn.ModuleList()
in_channels = encoder_blocks_channels.pop()
out_channels = in_channels
for d in range(depth):
out_channels = encoder_blocks_channels.pop() if len(encoder_blocks_channels) else in_channels // 2
self.deconv_blocks.append(SEDeconvBlock(
in_channels, out_channels,
norm_layer=norm_layer,
padding=0 if d == 0 else 1,
with_se=0 <= attend_from <= d
))
in_channels = out_channels
if self.image_fusion:
self.conv_attention = nn.Conv2d(out_channels, 1, kernel_size=1)
self.to_rgb = nn.Conv2d(out_channels, 3, kernel_size=1) | [
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sergioburdisso/pyss3 | 70c37853f3f56a60c3df9b94b678ca3f0db843de | pyss3/server.py | python | get_http_body | (http_request) | return http_request.split("\r\n\r\n")[1] | Given a HTTP request, return the body. | Given a HTTP request, return the body. | [
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"""Given a HTTP request, return the body."""
return http_request.split("\r\n\r\n")[1] | [
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aiff22/PyNET-PyTorch | b05d817408cf729582b52a3fee214775ccab800c | msssim.py | python | SSIM.forward | (self, img1, img2) | return ssim(img1, img2, window=window, window_size=self.window_size, size_average=self.size_average) | [] | def forward(self, img1, img2):
(_, channel, _, _) = img1.size()
if channel == self.channel and self.window.dtype == img1.dtype:
window = self.window
else:
window = create_window(self.window_size, channel).to(img1.device).type(img1.dtype)
self.window = window
self.channel = channel
return ssim(img1, img2, window=window, window_size=self.window_size, size_average=self.size_average) | [
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Tencent/bk-bcs-saas | 2b437bf2f5fd5ce2078f7787c3a12df609f7679d | bcs-app/backend/container_service/observability/log_stream/views.py | python | LogStreamHandler.receive | (self, text_data) | 获取消息, 目前只有推送, 只打印日志 | 获取消息, 目前只有推送, 只打印日志 | [
"获取消息",
"目前只有推送",
"只打印日志"
] | async def receive(self, text_data):
"""获取消息, 目前只有推送, 只打印日志"""
logger.info("receive message: %s", text_data) | [
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rowliny/DiffHelper | ab3a96f58f9579d0023aed9ebd785f4edf26f8af | Tool/SitePackages/urllib3/response.py | python | HTTPResponse.stream | (self, amt=2**16, decode_content=None) | A generator wrapper for the read() method. A call will block until
``amt`` bytes have been read from the connection or until the
connection is closed.
:param amt:
How much of the content to read. The generator will return up to
much data per iteration, but may return less. This is particularly
likely when using compressed data. However, the empty string will
never be returned.
:param decode_content:
If True, will attempt to decode the body based on the
'content-encoding' header. | A generator wrapper for the read() method. A call will block until
``amt`` bytes have been read from the connection or until the
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] | def stream(self, amt=2**16, decode_content=None):
"""
A generator wrapper for the read() method. A call will block until
``amt`` bytes have been read from the connection or until the
connection is closed.
:param amt:
How much of the content to read. The generator will return up to
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"""
if self.chunked and self.supports_chunked_reads():
for line in self.read_chunked(amt, decode_content=decode_content):
yield line
else:
while not is_fp_closed(self._fp):
data = self.read(amt=amt, decode_content=decode_content)
if data:
yield data | [
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wxWidgets/Phoenix | b2199e299a6ca6d866aa6f3d0888499136ead9d6 | wx/lib/ogl/basic.py | python | Shape.SetFormatMode | (self, mode, regionId = 0) | Set the format mode of the region.
:param `mode`: can be a bit list of the following
============================== ==============================
Format mode Description
============================== ==============================
`FORMAT_NONE` No formatting
`FORMAT_CENTRE_HORIZ` Horizontal centring
`FORMAT_CENTRE_VERT` Vertical centring
============================== ==============================
:param `regionId`: the region identifier, default=0 | Set the format mode of the region. | [
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] | def SetFormatMode(self, mode, regionId = 0):
"""
Set the format mode of the region.
:param `mode`: can be a bit list of the following
============================== ==============================
Format mode Description
============================== ==============================
`FORMAT_NONE` No formatting
`FORMAT_CENTRE_HORIZ` Horizontal centring
`FORMAT_CENTRE_VERT` Vertical centring
============================== ==============================
:param `regionId`: the region identifier, default=0
"""
if regionId < len(self._regions):
self._regions[regionId].SetFormatMode(mode) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/werkzeug/contrib/sessions.py | python | FilesystemSessionStore.delete | (self, session) | [] | def delete(self, session):
fn = self.get_session_filename(session.sid)
try:
os.unlink(fn)
except OSError:
pass | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/imghdr.py | python | test_xbm | (h, f) | X bitmap (X10 or X11) | X bitmap (X10 or X11) | [
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] | def test_xbm(h, f):
"""X bitmap (X10 or X11)"""
s = '#define '
if h[:len(s)] == s:
return 'xbm' | [
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mininet/mininet | 8a50d3867c49781c60b6171acc6e4b46954b4281 | examples/miniedit.py | python | MiniEdit.newTopology | ( self ) | New command. | New command. | [
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] | def newTopology( self ):
"New command."
for widget in tuple( self.widgetToItem ):
self.deleteItem( self.widgetToItem[ widget ] )
self.hostCount = 0
self.switchCount = 0
self.controllerCount = 0
self.links = {}
self.hostOpts = {}
self.switchOpts = {}
self.controllers = {}
self.appPrefs["ipBase"]= self.defaultIpBase | [
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awslabs/deeplearning-benchmark | 3e9a906422b402869537f91056ae771b66487a8e | tensorflow/inception/inception/slim/scopes.py | python | _get_arg_stack | () | [] | def _get_arg_stack():
stack = ops.get_collection(_ARGSTACK_KEY)
if stack:
return stack[0]
else:
stack = [{}]
ops.add_to_collection(_ARGSTACK_KEY, stack)
return stack | [
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c3nav/c3nav | 0f4e699e3733459b1c70935a4c813959cffd86bd | src/c3nav/editor/wrappers.py | python | BaseWrapper._wrap_manager | (self, manager) | return ManagerWrapper(self._changeset, manager) | Wrap a manager with same changeset as this wrapper.
Detects RelatedManager or ManyRelatedmanager instances and chooses the Wrapper accordingly. | Wrap a manager with same changeset as this wrapper.
Detects RelatedManager or ManyRelatedmanager instances and chooses the Wrapper accordingly. | [
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"""
Wrap a manager with same changeset as this wrapper.
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"""
assert isinstance(manager, Manager)
if hasattr(manager, 'through'):
return ManyRelatedManagerWrapper(self._changeset, manager)
if hasattr(manager, 'instance'):
return RelatedManagerWrapper(self._changeset, manager)
return ManagerWrapper(self._changeset, manager) | [
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kengz/SLM-Lab | 667ba73349ad00c6f4b3e428dcd10eebbdab4c70 | slm_lab/env/vec_env.py | python | DummyVecEnv.__init__ | (self, env_fns) | @param env_fns iterable of functions that build environments | [] | def __init__(self, env_fns):
'''
@param env_fns iterable of functions that build environments
'''
self.envs = [fn() for fn in env_fns]
env = self.envs[0]
VecEnv.__init__(self, len(env_fns), env.observation_space, env.action_space)
obs_space = env.observation_space
self.keys, shapes, dtypes = obs_space_info(obs_space)
self.buf_obs = {k: np.zeros((self.num_envs,) + tuple(shapes[k]), dtype=dtypes[k]) for k in self.keys}
self.buf_dones = np.zeros((self.num_envs,), dtype=np.bool)
self.buf_rews = np.zeros((self.num_envs,), dtype=np.float32)
self.buf_infos = [{} for _ in range(self.num_envs)]
self.actions = None
self.spec = self.envs[0].spec | [
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"(",... | https://github.com/kengz/SLM-Lab/blob/667ba73349ad00c6f4b3e428dcd10eebbdab4c70/slm_lab/env/vec_env.py#L272-L287 | |||
python/cpython | e13cdca0f5224ec4e23bdd04bb3120506964bc8b | Lib/venv/__init__.py | python | EnvBuilder.setup_python | (self, context) | Set up a Python executable in the environment.
:param context: The information for the environment creation request
being processed. | Set up a Python executable in the environment. | [
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] | def setup_python(self, context):
"""
Set up a Python executable in the environment.
:param context: The information for the environment creation request
being processed.
"""
binpath = context.bin_path
path = context.env_exe
copier = self.symlink_or_copy
dirname = context.python_dir
if os.name != 'nt':
copier(context.executable, path)
if not os.path.islink(path):
os.chmod(path, 0o755)
for suffix in ('python', 'python3', f'python3.{sys.version_info[1]}'):
path = os.path.join(binpath, suffix)
if not os.path.exists(path):
# Issue 18807: make copies if
# symlinks are not wanted
copier(context.env_exe, path, relative_symlinks_ok=True)
if not os.path.islink(path):
os.chmod(path, 0o755)
else:
if self.symlinks:
# For symlinking, we need a complete copy of the root directory
# If symlinks fail, you'll get unnecessary copies of files, but
# we assume that if you've opted into symlinks on Windows then
# you know what you're doing.
suffixes = [
f for f in os.listdir(dirname) if
os.path.normcase(os.path.splitext(f)[1]) in ('.exe', '.dll')
]
if sysconfig.is_python_build(True):
suffixes = [
f for f in suffixes if
os.path.normcase(f).startswith(('python', 'vcruntime'))
]
else:
suffixes = {'python.exe', 'python_d.exe', 'pythonw.exe', 'pythonw_d.exe'}
base_exe = os.path.basename(context.env_exe)
suffixes.add(base_exe)
for suffix in suffixes:
src = os.path.join(dirname, suffix)
if os.path.lexists(src):
copier(src, os.path.join(binpath, suffix))
if sysconfig.is_python_build(True):
# copy init.tcl
for root, dirs, files in os.walk(context.python_dir):
if 'init.tcl' in files:
tcldir = os.path.basename(root)
tcldir = os.path.join(context.env_dir, 'Lib', tcldir)
if not os.path.exists(tcldir):
os.makedirs(tcldir)
src = os.path.join(root, 'init.tcl')
dst = os.path.join(tcldir, 'init.tcl')
shutil.copyfile(src, dst)
break | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/tensor/modules/free_module_automorphism.py | python | FreeModuleAutomorphism._del_derived | (self) | r"""
Delete the derived quantities.
EXAMPLES::
sage: M = FiniteRankFreeModule(QQ, 3, name='M')
sage: e = M.basis('e')
sage: a = M.automorphism(name='a')
sage: a[e,:] = [[1,0,-1], [0,3,0], [0,0,2]]
sage: b = a.inverse()
sage: a._inverse
Automorphism a^(-1) of the 3-dimensional vector space M over the
Rational Field
sage: a._del_derived()
sage: a._inverse # has been reset to None | r"""
Delete the derived quantities. | [
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] | def _del_derived(self):
r"""
Delete the derived quantities.
EXAMPLES::
sage: M = FiniteRankFreeModule(QQ, 3, name='M')
sage: e = M.basis('e')
sage: a = M.automorphism(name='a')
sage: a[e,:] = [[1,0,-1], [0,3,0], [0,0,2]]
sage: b = a.inverse()
sage: a._inverse
Automorphism a^(-1) of the 3-dimensional vector space M over the
Rational Field
sage: a._del_derived()
sage: a._inverse # has been reset to None
"""
# First delete the derived quantities pertaining to FreeModuleTensor:
FreeModuleTensor._del_derived(self)
# Then reset the inverse automorphism to None:
if self._inverse is not None:
self._inverse._inverse = None # (it was set to self)
self._inverse = None
# and delete the matrices:
self._matrices.clear() | [
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007gzs/dingtalk-sdk | 7979da2e259fdbc571728cae2425a04dbc65850a | dingtalk/client/api/microapp.py | python | MicroApp.update | (self, agent_id, app_icon=None, app_name=None, app_desc=None,
homepage_url=None, pc_homepage_url=None, omp_link=None) | return self._post(
'/microapp/update',
{
"agentId": agent_id,
"appIcon": app_icon,
"appName": app_name,
"appDesc": app_desc,
"homepageUrl": homepage_url,
"pcHomepageUrl": pc_homepage_url,
"ompLink": omp_link
},
result_processor=lambda x: x['agentId']
) | 更新微应用
:param agent_id: 微应用实例化id
:param app_icon: 微应用的图标。需要调用上传接口将图标上传到钉钉服务器后获取到的mediaId
:param app_name: 微应用的名称。长度限制为1~10个字符
:param app_desc: 微应用的描述。长度限制为1~20个字符
:param homepage_url: 微应用的移动端主页，必须以http开头或https开头
:param pc_homepage_url: 微应用的PC端主页，必须以http开头或https开头，如果不为空则必须与homepageUrl的域名一致
:param omp_link: 微应用的OA后台管理主页，必须以http开头或https开头。
:return: 微应用实例化id | 更新微应用 | [
"更新微应用"
] | def update(self, agent_id, app_icon=None, app_name=None, app_desc=None,
homepage_url=None, pc_homepage_url=None, omp_link=None):
"""
更新微应用
:param agent_id: 微应用实例化id
:param app_icon: 微应用的图标。需要调用上传接口将图标上传到钉钉服务器后获取到的mediaId
:param app_name: 微应用的名称。长度限制为1~10个字符
:param app_desc: 微应用的描述。长度限制为1~20个字符
:param homepage_url: 微应用的移动端主页，必须以http开头或https开头
:param pc_homepage_url: 微应用的PC端主页，必须以http开头或https开头，如果不为空则必须与homepageUrl的域名一致
:param omp_link: 微应用的OA后台管理主页，必须以http开头或https开头。
:return: 微应用实例化id
"""
return self._post(
'/microapp/update',
{
"agentId": agent_id,
"appIcon": app_icon,
"appName": app_name,
"appDesc": app_desc,
"homepageUrl": homepage_url,
"pcHomepageUrl": pc_homepage_url,
"ompLink": omp_link
},
result_processor=lambda x: x['agentId']
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geopython/pywps | 7f228ff17594912664073a629b2c2ed9d4f5f615 | pywps/app/Service.py | python | Service.create_complex_inputs | (self, source, inputs) | return outinputs | Create new ComplexInput as clone of original ComplexInput
because of inputs can be more than one, take it just as Prototype.
:param source: The process's input definition.
:param inputs: The request input data.
:return collections.deque: | Create new ComplexInput as clone of original ComplexInput
because of inputs can be more than one, take it just as Prototype. | [
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"""Create new ComplexInput as clone of original ComplexInput
because of inputs can be more than one, take it just as Prototype.
:param source: The process's input definition.
:param inputs: The request input data.
:return collections.deque:
"""
outinputs = deque(maxlen=source.max_occurs)
for inpt in inputs:
data_input = source.clone()
frmt = data_input.supported_formats[0]
if 'mimeType' in inpt:
if inpt['mimeType']:
frmt = data_input.get_format(inpt['mimeType'])
else:
frmt = data_input.data_format
if frmt:
data_input.data_format = frmt
else:
raise InvalidParameterValue(
'Invalid mimeType value {} for input {}'.format(inpt.get('mimeType'), source.identifier),
'mimeType')
data_input.method = inpt.get('method', 'GET')
data_input.process(inpt)
outinputs.append(data_input)
if len(outinputs) < source.min_occurs:
description = "At least {} inputs are required. You provided {}.".format(
source.min_occurs,
len(outinputs),
)
raise MissingParameterValue(description=description, locator=source.identifier)
return outinputs | [
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topydo/topydo | 57d7577c987515d4b49d5500f666da29080ca3c2 | topydo/lib/TodoBase.py | python | TodoBase.source | (self) | return self.text(True) | Returns the source text of the todo. This is the raw text with all
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | couch/datadog_checks/couch/config_models/defaults.py | python | instance_auth_token | (field, value) | return get_default_field_value(field, value) | [] | def instance_auth_token(field, value):
return get_default_field_value(field, value) | [
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awslabs/autogluon | 7309118f2ab1c9519f25acf61a283a95af95842b | tabular/src/autogluon/tabular/models/rf/rf_model.py | python | RFModel._fit | (self,
X,
y,
num_cpus=-1,
time_limit=None,
sample_weight=None,
**kwargs) | [] | def _fit(self,
X,
y,
num_cpus=-1,
time_limit=None,
sample_weight=None,
**kwargs):
time_start = time.time()
model_cls = self._get_model_type()
max_memory_usage_ratio = self.params_aux['max_memory_usage_ratio']
self._set_cpu_params(num_cpus)
params = self._get_model_params()
n_estimators_final = params['n_estimators']
n_estimators_minimum = min(40, n_estimators_final)
n_estimators_test = min(4, max(1, math.floor(n_estimators_minimum/5)))
X = self.preprocess(X)
n_estimator_increments = [n_estimators_final]
num_trees_per_estimator = self._get_num_trees_per_estimator()
bytes_per_estimator = num_trees_per_estimator * len(X) / 60000 * 1e6 # Underestimates by 3x on ExtraTrees
available_mem = psutil.virtual_memory().available
expected_memory_usage = n_estimators_final * bytes_per_estimator / available_mem
if n_estimators_final > n_estimators_test * 2:
if self.problem_type == MULTICLASS:
n_estimator_increments = [n_estimators_test, n_estimators_final]
params['warm_start'] = True
else:
if expected_memory_usage > (0.05 * max_memory_usage_ratio): # Somewhat arbitrary, consider finding a better value, should it scale by cores?
# Causes ~10% training slowdown, so try to avoid if memory is not an issue
n_estimator_increments = [n_estimators_test, n_estimators_final]
params['warm_start'] = True
params['n_estimators'] = n_estimator_increments[0]
if self._daal:
if params.get('warm_start', False):
params['warm_start'] = False
model = model_cls(**params)
time_train_start = time.time()
for i, n_estimators in enumerate(n_estimator_increments):
if i != 0:
if params.get('warm_start', False):
model.n_estimators = n_estimators
else:
params['n_estimators'] = n_estimators
model = model_cls(**params)
model = model.fit(X, y, sample_weight=sample_weight)
if (i == 0) and (len(n_estimator_increments) > 1):
time_elapsed = time.time() - time_train_start
model_size_bytes = 0
for estimator in model.estimators_: # Uses far less memory than pickling the entire forest at once
model_size_bytes += sys.getsizeof(pickle.dumps(estimator))
expected_final_model_size_bytes = model_size_bytes * (n_estimators_final / model.n_estimators)
available_mem = psutil.virtual_memory().available
model_memory_ratio = expected_final_model_size_bytes / available_mem
ideal_memory_ratio = 0.15 * max_memory_usage_ratio
n_estimators_ideal = min(n_estimators_final, math.floor(ideal_memory_ratio / model_memory_ratio * n_estimators_final))
if n_estimators_final > n_estimators_ideal:
if n_estimators_ideal < n_estimators_minimum:
logger.warning(f'\tWarning: Model is expected to require {round(model_memory_ratio*100, 2)}% of available memory...')
raise NotEnoughMemoryError # don't train full model to avoid OOM error
logger.warning(f'\tWarning: Reducing model \'n_estimators\' from {n_estimators_final} -> {n_estimators_ideal} due to low memory. Expected memory usage reduced from {round(model_memory_ratio*100, 2)}% -> {round(ideal_memory_ratio*100, 2)}% of available memory...')
if time_limit is not None:
time_expected = time_train_start - time_start + (time_elapsed * n_estimators_ideal / n_estimators)
n_estimators_time = math.floor((time_limit - time_train_start + time_start) * n_estimators / time_elapsed)
if n_estimators_time < n_estimators_ideal:
if n_estimators_time < n_estimators_minimum:
logger.warning(f'\tWarning: Model is expected to require {round(time_expected, 1)}s to train, which exceeds the maximum time limit of {round(time_limit, 1)}s, skipping model...')
raise TimeLimitExceeded
logger.warning(f'\tWarning: Reducing model \'n_estimators\' from {n_estimators_ideal} -> {n_estimators_time} due to low time. Expected time usage reduced from {round(time_expected, 1)}s -> {round(time_limit, 1)}s...')
n_estimators_ideal = n_estimators_time
for j in range(len(n_estimator_increments)):
if n_estimator_increments[j] > n_estimators_ideal:
n_estimator_increments[j] = n_estimators_ideal
self.model = model
self.params_trained['n_estimators'] = self.model.n_estimators | [
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petercorke/robotics-toolbox-python | 51aa8bbb3663a7c815f9880d538d61e7c85bc470 | roboticstoolbox/tools/urdf/urdf.py | python | URDFType._parse_simple_attribs | (cls, node) | return kwargs | Parse all attributes in the _ATTRIBS array for this class.
Parameters
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node : :class:`lxml.etree.Element`
The node to parse attributes for.
Returns
-------
kwargs : dict
Map from attribute name to value. If the attribute is not
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spotify/luigi | c3b66f4a5fa7eaa52f9a72eb6704b1049035c789 | luigi/task.py | python | Task.process_resources | (self) | return self.resources | Override in "template" tasks which provide common resource functionality
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/lib-tk/ttk.py | python | Treeview.detach | (self, *items) | Unlinks all of the specified items from the tree.
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ArangoDB-Community/python-arango | 77cbc6813b75daa1a6e232e2327259e56b0228ca | arango/formatter.py | python | format_replication_applier_config | (body: Json) | return verify_format(body, result) | Format replication applier configuration data.
:param body: Input body.
:type body: dict
:return: Formatted body.
:rtype: dict | Format replication applier configuration data. | [
"Format",
"replication",
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"data",
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] | def format_replication_applier_config(body: Json) -> Json:
"""Format replication applier configuration data.
:param body: Input body.
:type body: dict
:return: Formatted body.
:rtype: dict
"""
result: Json = {}
if "endpoint" in body:
result["endpoint"] = body["endpoint"]
if "database" in body:
result["database"] = body["database"]
if "username" in body:
result["username"] = body["username"]
if "verbose" in body:
result["verbose"] = body["verbose"]
if "incremental" in body:
result["incremental"] = body["incremental"]
if "requestTimeout" in body:
result["request_timeout"] = body["requestTimeout"]
if "connectTimeout" in body:
result["connect_timeout"] = body["connectTimeout"]
if "ignoreErrors" in body:
result["ignore_errors"] = body["ignoreErrors"]
if "maxConnectRetries" in body:
result["max_connect_retries"] = body["maxConnectRetries"]
if "lockTimeoutRetries" in body:
result["lock_timeout_retries"] = body["lockTimeoutRetries"]
if "sslProtocol" in body:
result["ssl_protocol"] = body["sslProtocol"]
if "chunkSize" in body:
result["chunk_size"] = body["chunkSize"]
if "skipCreateDrop" in body:
result["skip_create_drop"] = body["skipCreateDrop"]
if "autoStart" in body:
result["auto_start"] = body["autoStart"]
if "adaptivePolling" in body:
result["adaptive_polling"] = body["adaptivePolling"]
if "autoResync" in body:
result["auto_resync"] = body["autoResync"]
if "autoResyncRetries" in body:
result["auto_resync_retries"] = body["autoResyncRetries"]
if "maxPacketSize" in body:
result["max_packet_size"] = body["maxPacketSize"]
if "includeSystem" in body:
result["include_system"] = body["includeSystem"]
if "includeFoxxQueues" in body:
result["include_foxx_queues"] = body["includeFoxxQueues"]
if "requireFromPresent" in body:
result["require_from_present"] = body["requireFromPresent"]
if "restrictType" in body:
result["restrict_type"] = body["restrictType"]
if "restrictCollections" in body:
result["restrict_collections"] = body["restrictCollections"]
if "connectionRetryWaitTime" in body:
result["connection_retry_wait_time"] = body["connectionRetryWaitTime"]
if "initialSyncMaxWaitTime" in body:
result["initial_sync_max_wait_time"] = body["initialSyncMaxWaitTime"]
if "idleMinWaitTime" in body:
result["idle_min_wait_time"] = body["idleMinWaitTime"]
if "idleMaxWaitTime" in body:
result["idle_max_wait_time"] = body["idleMaxWaitTime"]
return verify_format(body, result) | [
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openstack/manila | 142990edc027e14839d5deaf4954dd6fc88de15e | manila/api/views/share_groups.py | python | ShareGroupViewBuilder.summary | (self, request, share_group) | return {
'share_group': {
'id': share_group.get('id'),
'name': share_group.get('name'),
'links': self._get_links(request, share_group['id'])
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] | def summary(self, request, share_group):
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return {
'share_group': {
'id': share_group.get('id'),
'name': share_group.get('name'),
'links': self._get_links(request, share_group['id'])
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9miao/G-Firefly | 8fbeeb3ef9782600560be48228c91cfb8f5ff87d | gfirefly/gfirefly/utils/services.py | python | CommandService.unMapTarget | (self, target) | Remove a target from the service. | Remove a target from the service. | [
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] | def unMapTarget(self, target):
"""Remove a target from the service.
"""
key = int((target.__name__).split('_')[-1])
if key in self._targets:
del self._targets[key] | [
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xMistt/fortnitepy-bot | 407a4fa9cf37e61533054389dea355335bcdb2a7 | partybot/party.py | python | PartyCommands.bp | (self, ctx: fortnitepy.ext.commands.Context, tier: int) | [] | async def bp(self, ctx: fortnitepy.ext.commands.Context, tier: int) -> None:
await self.bot.party.me.set_battlepass_info(
has_purchased=True,
level=tier,
)
await ctx.send(f'Set battle pass tier to {tier}.') | [
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accel-brain/accel-brain-code | 86f489dc9be001a3bae6d053f48d6b57c0bedb95 | Accel-Brain-Base/accelbrainbase/observabledata/_mxnet/transformermodel/transformer_encoder.py | python | TransformerEncoder.hybrid_forward | (self, F, x, m=None) | return self.forward_propagation(F, x, m) | Hybrid forward with Gluon API.
Args:
F: `mxnet.ndarray` or `mxnet.symbol`.
x: `mxnet.ndarray` of observed data points.
m: `mxnet.ndarray` of self-attention masks.
Returns:
`mxnet.ndarray` or `mxnet.symbol` of inferenced feature points. | Hybrid forward with Gluon API. | [
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] | def hybrid_forward(self, F, x, m=None):
'''
Hybrid forward with Gluon API.
Args:
F: `mxnet.ndarray` or `mxnet.symbol`.
x: `mxnet.ndarray` of observed data points.
m: `mxnet.ndarray` of self-attention masks.
Returns:
`mxnet.ndarray` or `mxnet.symbol` of inferenced feature points.
'''
# rank-3
return self.forward_propagation(F, x, m) | [
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nlloyd/SubliminalCollaborator | 5c619e17ddbe8acb9eea8996ec038169ddcd50a1 | libs/twisted/words/xish/domish.py | python | Element.__str__ | (self) | return "" | Retrieve the first CData (content) node | Retrieve the first CData (content) node | [
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] | def __str__(self):
""" Retrieve the first CData (content) node
"""
for n in self.children:
if isinstance(n, types.StringTypes): return n
return "" | [
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rowliny/DiffHelper | ab3a96f58f9579d0023aed9ebd785f4edf26f8af | Tool/SitePackages/nltk/draw/util.py | python | CanvasWidget.hidden | (self) | return self.__hidden | :return: True if this canvas widget is hidden.
:rtype: bool | :return: True if this canvas widget is hidden.
:rtype: bool | [
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"""
:return: True if this canvas widget is hidden.
:rtype: bool
"""
return self.__hidden | [
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Cisco-Talos/BASS | 6dd8b7aa4b13ddcd48f0c8fbd64ac43955157420 | funcdb/server.py | python | _function_count_transitions | (func) | return sum(1 for bb in func.basic_blocks for _ in bb.successors) | Count the number of transitions between basic blocks in a function | Count the number of transitions between basic blocks in a function | [
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] | def _function_count_transitions(func):
"""Count the number of transitions between basic blocks in a function"""
return sum(1 for bb in func.basic_blocks for _ in bb.successors) | [
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