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oanda/v20-python
src/v20/order.py
https://github.com/oanda/v20-python/blob/f28192f4a31bce038cf6dfa302f5878bec192fe5/src/v20/order.py#L4051-L4237
def replace( self, accountID, orderSpecifier, **kwargs ): """ Replace an Order in an Account by simultaneously cancelling it and creating a replacement Order Args: accountID: Account Identifier orderSpecifier: The Order Specifier order: Specification of the replacing Order Returns: v20.response.Response containing the results from submitting the request """ request = Request( 'PUT', '/v3/accounts/{accountID}/orders/{orderSpecifier}' ) request.set_path_param( 'accountID', accountID ) request.set_path_param( 'orderSpecifier', orderSpecifier ) body = EntityDict() if 'order' in kwargs: body.set('order', kwargs['order']) request.set_body_dict(body.dict) response = self.ctx.request(request) if response.content_type is None: return response if not response.content_type.startswith("application/json"): return response jbody = json.loads(response.raw_body) parsed_body = {} # # Parse responses as defined by the API specification # if str(response.status) == "201": if jbody.get('orderCancelTransaction') is not None: parsed_body['orderCancelTransaction'] = \ self.ctx.transaction.OrderCancelTransaction.from_dict( jbody['orderCancelTransaction'], self.ctx ) if jbody.get('orderCreateTransaction') is not None: parsed_body['orderCreateTransaction'] = \ self.ctx.transaction.Transaction.from_dict( jbody['orderCreateTransaction'], self.ctx ) if jbody.get('orderFillTransaction') is not None: parsed_body['orderFillTransaction'] = \ self.ctx.transaction.OrderFillTransaction.from_dict( jbody['orderFillTransaction'], self.ctx ) if jbody.get('orderReissueTransaction') is not None: parsed_body['orderReissueTransaction'] = \ self.ctx.transaction.Transaction.from_dict( jbody['orderReissueTransaction'], self.ctx ) if jbody.get('orderReissueRejectTransaction') is not None: parsed_body['orderReissueRejectTransaction'] = \ self.ctx.transaction.Transaction.from_dict( jbody['orderReissueRejectTransaction'], self.ctx ) if jbody.get('replacingOrderCancelTransaction') is not None: parsed_body['replacingOrderCancelTransaction'] = \ self.ctx.transaction.OrderCancelTransaction.from_dict( jbody['replacingOrderCancelTransaction'], self.ctx ) if jbody.get('relatedTransactionIDs') is not None: parsed_body['relatedTransactionIDs'] = \ jbody.get('relatedTransactionIDs') if jbody.get('lastTransactionID') is not None: parsed_body['lastTransactionID'] = \ jbody.get('lastTransactionID') elif str(response.status) == "400": if jbody.get('orderRejectTransaction') is not None: parsed_body['orderRejectTransaction'] = \ self.ctx.transaction.Transaction.from_dict( jbody['orderRejectTransaction'], self.ctx ) if jbody.get('relatedTransactionIDs') is not None: parsed_body['relatedTransactionIDs'] = \ jbody.get('relatedTransactionIDs') if jbody.get('lastTransactionID') is not None: parsed_body['lastTransactionID'] = \ jbody.get('lastTransactionID') if jbody.get('errorCode') is not None: parsed_body['errorCode'] = \ jbody.get('errorCode') if jbody.get('errorMessage') is not None: parsed_body['errorMessage'] = \ jbody.get('errorMessage') elif str(response.status) == "401": if jbody.get('errorCode') is not None: parsed_body['errorCode'] = \ jbody.get('errorCode') if jbody.get('errorMessage') is not None: parsed_body['errorMessage'] = \ jbody.get('errorMessage') elif str(response.status) == "404": if jbody.get('orderCancelRejectTransaction') is not None: parsed_body['orderCancelRejectTransaction'] = \ self.ctx.transaction.Transaction.from_dict( jbody['orderCancelRejectTransaction'], self.ctx ) if jbody.get('relatedTransactionIDs') is not None: parsed_body['relatedTransactionIDs'] = \ jbody.get('relatedTransactionIDs') if jbody.get('lastTransactionID') is not None: parsed_body['lastTransactionID'] = \ jbody.get('lastTransactionID') if jbody.get('errorCode') is not None: parsed_body['errorCode'] = \ jbody.get('errorCode') if jbody.get('errorMessage') is not None: parsed_body['errorMessage'] = \ jbody.get('errorMessage') elif str(response.status) == "405": if jbody.get('errorCode') is not None: parsed_body['errorCode'] = \ jbody.get('errorCode') if jbody.get('errorMessage') is not None: parsed_body['errorMessage'] = \ jbody.get('errorMessage') # # Unexpected response status # else: parsed_body = jbody response.body = parsed_body return response
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Replace an Order in an Account by simultaneously cancelling it and creating a replacement Order Args: accountID: Account Identifier orderSpecifier: The Order Specifier order: Specification of the replacing Order Returns: v20.response.Response containing the results from submitting the request
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python
train
onelogin/python-saml
src/onelogin/saml2/settings.py
https://github.com/onelogin/python-saml/blob/9fe7a72da5b4caa1529c1640b52d2649447ce49b/src/onelogin/saml2/settings.py#L250-L307
def __add_default_values(self): """ Add default values if the settings info is not complete """ self.__sp.setdefault('assertionConsumerService', {}) self.__sp['assertionConsumerService'].setdefault('binding', OneLogin_Saml2_Constants.BINDING_HTTP_POST) self.__sp.setdefault('attributeConsumingService', {}) self.__sp.setdefault('singleLogoutService', {}) self.__sp['singleLogoutService'].setdefault('binding', OneLogin_Saml2_Constants.BINDING_HTTP_REDIRECT) # Related to nameID self.__sp.setdefault('NameIDFormat', OneLogin_Saml2_Constants.NAMEID_UNSPECIFIED) self.__security.setdefault('nameIdEncrypted', False) # Metadata format self.__security.setdefault('metadataValidUntil', None) # None means use default self.__security.setdefault('metadataCacheDuration', None) # None means use default # Sign provided self.__security.setdefault('authnRequestsSigned', False) self.__security.setdefault('logoutRequestSigned', False) self.__security.setdefault('logoutResponseSigned', False) self.__security.setdefault('signMetadata', False) # Sign expected self.__security.setdefault('wantMessagesSigned', False) self.__security.setdefault('wantAssertionsSigned', False) # NameID element expected self.__security.setdefault('wantNameId', True) # SAML responses with a InResponseTo attribute not rejected when requestId not passed self.__security.setdefault('rejectUnsolicitedResponsesWithInResponseTo', False) # Encrypt expected self.__security.setdefault('wantAssertionsEncrypted', False) self.__security.setdefault('wantNameIdEncrypted', False) # Signature Algorithm self.__security.setdefault('signatureAlgorithm', OneLogin_Saml2_Constants.RSA_SHA1) # Digest Algorithm self.__security.setdefault('digestAlgorithm', OneLogin_Saml2_Constants.SHA1) # AttributeStatement required by default self.__security.setdefault('wantAttributeStatement', True) self.__idp.setdefault('x509cert', '') self.__idp.setdefault('certFingerprint', '') self.__idp.setdefault('certFingerprintAlgorithm', 'sha1') self.__sp.setdefault('x509cert', '') self.__sp.setdefault('privateKey', '') self.__security.setdefault('requestedAuthnContext', True) self.__security.setdefault('failOnAuthnContextMismatch', False)
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Add default values if the settings info is not complete
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python
train
spotify/luigi
luigi/worker.py
https://github.com/spotify/luigi/blob/c5eca1c3c3ee2a7eb612486192a0da146710a1e9/luigi/worker.py#L561-L583
def _add_task(self, *args, **kwargs): """ Call ``self._scheduler.add_task``, but store the values too so we can implement :py:func:`luigi.execution_summary.summary`. """ task_id = kwargs['task_id'] status = kwargs['status'] runnable = kwargs['runnable'] task = self._scheduled_tasks.get(task_id) if task: self._add_task_history.append((task, status, runnable)) kwargs['owners'] = task._owner_list() if task_id in self._batch_running_tasks: for batch_task in self._batch_running_tasks.pop(task_id): self._add_task_history.append((batch_task, status, True)) if task and kwargs.get('params'): kwargs['param_visibilities'] = task._get_param_visibilities() self._scheduler.add_task(*args, **kwargs) logger.info('Informed scheduler that task %s has status %s', task_id, status)
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Call ``self._scheduler.add_task``, but store the values too so we can implement :py:func:`luigi.execution_summary.summary`.
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python
train
quantopian/zipline
zipline/pipeline/factors/factor.py
https://github.com/quantopian/zipline/blob/77ad15e6dc4c1cbcdc133653bac8a63fc704f7fe/zipline/pipeline/factors/factor.py#L402-L524
def demean(self, mask=NotSpecified, groupby=NotSpecified): """ Construct a Factor that computes ``self`` and subtracts the mean from row of the result. If ``mask`` is supplied, ignore values where ``mask`` returns False when computing row means, and output NaN anywhere the mask is False. If ``groupby`` is supplied, compute by partitioning each row based on the values produced by ``groupby``, de-meaning the partitioned arrays, and stitching the sub-results back together. Parameters ---------- mask : zipline.pipeline.Filter, optional A Filter defining values to ignore when computing means. groupby : zipline.pipeline.Classifier, optional A classifier defining partitions over which to compute means. Examples -------- Let ``f`` be a Factor which would produce the following output:: AAPL MSFT MCD BK 2017-03-13 1.0 2.0 3.0 4.0 2017-03-14 1.5 2.5 3.5 1.0 2017-03-15 2.0 3.0 4.0 1.5 2017-03-16 2.5 3.5 1.0 2.0 Let ``c`` be a Classifier producing the following output:: AAPL MSFT MCD BK 2017-03-13 1 1 2 2 2017-03-14 1 1 2 2 2017-03-15 1 1 2 2 2017-03-16 1 1 2 2 Let ``m`` be a Filter producing the following output:: AAPL MSFT MCD BK 2017-03-13 False True True True 2017-03-14 True False True True 2017-03-15 True True False True 2017-03-16 True True True False Then ``f.demean()`` will subtract the mean from each row produced by ``f``. :: AAPL MSFT MCD BK 2017-03-13 -1.500 -0.500 0.500 1.500 2017-03-14 -0.625 0.375 1.375 -1.125 2017-03-15 -0.625 0.375 1.375 -1.125 2017-03-16 0.250 1.250 -1.250 -0.250 ``f.demean(mask=m)`` will subtract the mean from each row, but means will be calculated ignoring values on the diagonal, and NaNs will written to the diagonal in the output. Diagonal values are ignored because they are the locations where the mask ``m`` produced False. :: AAPL MSFT MCD BK 2017-03-13 NaN -1.000 0.000 1.000 2017-03-14 -0.500 NaN 1.500 -1.000 2017-03-15 -0.166 0.833 NaN -0.666 2017-03-16 0.166 1.166 -1.333 NaN ``f.demean(groupby=c)`` will subtract the group-mean of AAPL/MSFT and MCD/BK from their respective entries. The AAPL/MSFT are grouped together because both assets always produce 1 in the output of the classifier ``c``. Similarly, MCD/BK are grouped together because they always produce 2. :: AAPL MSFT MCD BK 2017-03-13 -0.500 0.500 -0.500 0.500 2017-03-14 -0.500 0.500 1.250 -1.250 2017-03-15 -0.500 0.500 1.250 -1.250 2017-03-16 -0.500 0.500 -0.500 0.500 ``f.demean(mask=m, groupby=c)`` will also subtract the group-mean of AAPL/MSFT and MCD/BK, but means will be calculated ignoring values on the diagonal , and NaNs will be written to the diagonal in the output. :: AAPL MSFT MCD BK 2017-03-13 NaN 0.000 -0.500 0.500 2017-03-14 0.000 NaN 1.250 -1.250 2017-03-15 -0.500 0.500 NaN 0.000 2017-03-16 -0.500 0.500 0.000 NaN Notes ----- Mean is sensitive to the magnitudes of outliers. When working with factor that can potentially produce large outliers, it is often useful to use the ``mask`` parameter to discard values at the extremes of the distribution:: >>> base = MyFactor(...) # doctest: +SKIP >>> normalized = base.demean( ... mask=base.percentile_between(1, 99), ... ) # doctest: +SKIP ``demean()`` is only supported on Factors of dtype float64. See Also -------- :meth:`pandas.DataFrame.groupby` """ return GroupedRowTransform( transform=demean, transform_args=(), factor=self, groupby=groupby, dtype=self.dtype, missing_value=self.missing_value, window_safe=self.window_safe, mask=mask, )
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Construct a Factor that computes ``self`` and subtracts the mean from row of the result. If ``mask`` is supplied, ignore values where ``mask`` returns False when computing row means, and output NaN anywhere the mask is False. If ``groupby`` is supplied, compute by partitioning each row based on the values produced by ``groupby``, de-meaning the partitioned arrays, and stitching the sub-results back together. Parameters ---------- mask : zipline.pipeline.Filter, optional A Filter defining values to ignore when computing means. groupby : zipline.pipeline.Classifier, optional A classifier defining partitions over which to compute means. Examples -------- Let ``f`` be a Factor which would produce the following output:: AAPL MSFT MCD BK 2017-03-13 1.0 2.0 3.0 4.0 2017-03-14 1.5 2.5 3.5 1.0 2017-03-15 2.0 3.0 4.0 1.5 2017-03-16 2.5 3.5 1.0 2.0 Let ``c`` be a Classifier producing the following output:: AAPL MSFT MCD BK 2017-03-13 1 1 2 2 2017-03-14 1 1 2 2 2017-03-15 1 1 2 2 2017-03-16 1 1 2 2 Let ``m`` be a Filter producing the following output:: AAPL MSFT MCD BK 2017-03-13 False True True True 2017-03-14 True False True True 2017-03-15 True True False True 2017-03-16 True True True False Then ``f.demean()`` will subtract the mean from each row produced by ``f``. :: AAPL MSFT MCD BK 2017-03-13 -1.500 -0.500 0.500 1.500 2017-03-14 -0.625 0.375 1.375 -1.125 2017-03-15 -0.625 0.375 1.375 -1.125 2017-03-16 0.250 1.250 -1.250 -0.250 ``f.demean(mask=m)`` will subtract the mean from each row, but means will be calculated ignoring values on the diagonal, and NaNs will written to the diagonal in the output. Diagonal values are ignored because they are the locations where the mask ``m`` produced False. :: AAPL MSFT MCD BK 2017-03-13 NaN -1.000 0.000 1.000 2017-03-14 -0.500 NaN 1.500 -1.000 2017-03-15 -0.166 0.833 NaN -0.666 2017-03-16 0.166 1.166 -1.333 NaN ``f.demean(groupby=c)`` will subtract the group-mean of AAPL/MSFT and MCD/BK from their respective entries. The AAPL/MSFT are grouped together because both assets always produce 1 in the output of the classifier ``c``. Similarly, MCD/BK are grouped together because they always produce 2. :: AAPL MSFT MCD BK 2017-03-13 -0.500 0.500 -0.500 0.500 2017-03-14 -0.500 0.500 1.250 -1.250 2017-03-15 -0.500 0.500 1.250 -1.250 2017-03-16 -0.500 0.500 -0.500 0.500 ``f.demean(mask=m, groupby=c)`` will also subtract the group-mean of AAPL/MSFT and MCD/BK, but means will be calculated ignoring values on the diagonal , and NaNs will be written to the diagonal in the output. :: AAPL MSFT MCD BK 2017-03-13 NaN 0.000 -0.500 0.500 2017-03-14 0.000 NaN 1.250 -1.250 2017-03-15 -0.500 0.500 NaN 0.000 2017-03-16 -0.500 0.500 0.000 NaN Notes ----- Mean is sensitive to the magnitudes of outliers. When working with factor that can potentially produce large outliers, it is often useful to use the ``mask`` parameter to discard values at the extremes of the distribution:: >>> base = MyFactor(...) # doctest: +SKIP >>> normalized = base.demean( ... mask=base.percentile_between(1, 99), ... ) # doctest: +SKIP ``demean()`` is only supported on Factors of dtype float64. See Also -------- :meth:`pandas.DataFrame.groupby`
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python
train
google/prettytensor
prettytensor/layers.py
https://github.com/google/prettytensor/blob/75daa0b11252590f548da5647addc0ea610c4c45/prettytensor/layers.py#L84-L116
def he_init(n_inputs, n_outputs, activation_fn, uniform=True): """Sets the parameter initialization using the method described. This method is designed to keep the scale of the gradients roughly the same in all layers with ReLU activations. He et al. (2015): Delving deep into rectifiers: surpassing human-level performance on imageNet classification. International Conference on Computer Vision. For activations other than ReLU and ReLU6, this method uses Xavier initialization as in xavier_init(). Args: n_inputs: The number of input nodes into each output. n_outputs: The number of output nodes for each input. activation_fn: Activation function used in this layer. uniform: If uniform distribution will be used for Xavier initialization. Normal distribution will be used if False. Returns: An initializer. """ def in_relu_family(activation_fn): if isinstance(activation_fn, collections.Sequence): activation_fn = activation_fn[0] return activation_fn in (tf.nn.relu, tf.nn.relu6) if in_relu_family(activation_fn): stddev = math.sqrt(2.0 / n_inputs) # TODO(): Evaluates truncated_normal_initializer. return tf.random_normal_initializer(stddev=stddev) else: return xavier_init(n_inputs, n_outputs, uniform)
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Sets the parameter initialization using the method described. This method is designed to keep the scale of the gradients roughly the same in all layers with ReLU activations. He et al. (2015): Delving deep into rectifiers: surpassing human-level performance on imageNet classification. International Conference on Computer Vision. For activations other than ReLU and ReLU6, this method uses Xavier initialization as in xavier_init(). Args: n_inputs: The number of input nodes into each output. n_outputs: The number of output nodes for each input. activation_fn: Activation function used in this layer. uniform: If uniform distribution will be used for Xavier initialization. Normal distribution will be used if False. Returns: An initializer.
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python
train
Miserlou/Zappa
zappa/core.py
https://github.com/Miserlou/Zappa/blob/3ccf7490a8d8b8fa74a61ee39bf44234f3567739/zappa/core.py#L2633-L2771
def schedule_events(self, lambda_arn, lambda_name, events, default=True): """ Given a Lambda ARN, name and a list of events, schedule this as CloudWatch Events. 'events' is a list of dictionaries, where the dict must contains the string of a 'function' and the string of the event 'expression', and an optional 'name' and 'description'. Expressions can be in rate or cron format: http://docs.aws.amazon.com/lambda/latest/dg/tutorial-scheduled-events-schedule-expressions.html """ # The stream sources - DynamoDB, Kinesis and SQS - are working differently than the other services (pull vs push) # and do not require event permissions. They do require additional permissions on the Lambda roles though. # http://docs.aws.amazon.com/lambda/latest/dg/lambda-api-permissions-ref.html pull_services = ['dynamodb', 'kinesis', 'sqs'] # XXX: Not available in Lambda yet. # We probably want to execute the latest code. # if default: # lambda_arn = lambda_arn + ":$LATEST" self.unschedule_events(lambda_name=lambda_name, lambda_arn=lambda_arn, events=events, excluded_source_services=pull_services) for event in events: function = event['function'] expression = event.get('expression', None) # single expression expressions = event.get('expressions', None) # multiple expression kwargs = event.get('kwargs', {}) # optional dict of keyword arguments for the event event_source = event.get('event_source', None) description = event.get('description', function) # - If 'cron' or 'rate' in expression, use ScheduleExpression # - Else, use EventPattern # - ex https://github.com/awslabs/aws-lambda-ddns-function if not self.credentials_arn: self.get_credentials_arn() if expression: expressions = [expression] # same code for single and multiple expression if expressions: for index, expression in enumerate(expressions): name = self.get_scheduled_event_name(event, function, lambda_name, index) # if it's possible that we truncated name, generate a unique, shortened name # https://github.com/Miserlou/Zappa/issues/970 if len(name) >= 64: rule_name = self.get_hashed_rule_name(event, function, lambda_name) else: rule_name = name rule_response = self.events_client.put_rule( Name=rule_name, ScheduleExpression=expression, State='ENABLED', Description=description, RoleArn=self.credentials_arn ) if 'RuleArn' in rule_response: logger.debug('Rule created. ARN {}'.format(rule_response['RuleArn'])) # Specific permissions are necessary for any trigger to work. self.create_event_permission(lambda_name, 'events.amazonaws.com', rule_response['RuleArn']) # Overwriting the input, supply the original values and add kwargs input_template = '{"time": <time>, ' \ '"detail-type": <detail-type>, ' \ '"source": <source>,' \ '"account": <account>, ' \ '"region": <region>,' \ '"detail": <detail>, ' \ '"version": <version>,' \ '"resources": <resources>,' \ '"id": <id>,' \ '"kwargs": %s' \ '}' % json.dumps(kwargs) # Create the CloudWatch event ARN for this function. # https://github.com/Miserlou/Zappa/issues/359 target_response = self.events_client.put_targets( Rule=rule_name, Targets=[ { 'Id': 'Id' + ''.join(random.choice(string.digits) for _ in range(12)), 'Arn': lambda_arn, 'InputTransformer': { 'InputPathsMap': { 'time': '$.time', 'detail-type': '$.detail-type', 'source': '$.source', 'account': '$.account', 'region': '$.region', 'detail': '$.detail', 'version': '$.version', 'resources': '$.resources', 'id': '$.id' }, 'InputTemplate': input_template } } ] ) if target_response['ResponseMetadata']['HTTPStatusCode'] == 200: print("Scheduled {} with expression {}!".format(rule_name, expression)) else: print("Problem scheduling {} with expression {}.".format(rule_name, expression)) elif event_source: service = self.service_from_arn(event_source['arn']) if service not in pull_services: svc = ','.join(event['event_source']['events']) self.create_event_permission( lambda_name, service + '.amazonaws.com', event['event_source']['arn'] ) else: svc = service rule_response = add_event_source( event_source, lambda_arn, function, self.boto_session ) if rule_response == 'successful': print("Created {} event schedule for {}!".format(svc, function)) elif rule_response == 'failed': print("Problem creating {} event schedule for {}!".format(svc, function)) elif rule_response == 'exists': print("{} event schedule for {} already exists - Nothing to do here.".format(svc, function)) elif rule_response == 'dryrun': print("Dryrun for creating {} event schedule for {}!!".format(svc, function)) else: print("Could not create event {} - Please define either an expression or an event source".format(name))
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Given a Lambda ARN, name and a list of events, schedule this as CloudWatch Events. 'events' is a list of dictionaries, where the dict must contains the string of a 'function' and the string of the event 'expression', and an optional 'name' and 'description'. Expressions can be in rate or cron format: http://docs.aws.amazon.com/lambda/latest/dg/tutorial-scheduled-events-schedule-expressions.html
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python
train
sanger-pathogens/Fastaq
pyfastaq/intervals.py
https://github.com/sanger-pathogens/Fastaq/blob/2c775c846d2491678a9637daa320592e02c26c72/pyfastaq/intervals.py#L60-L65
def intersection(self, i): '''If intervals intersect, returns their intersection, otherwise returns None''' if self.intersects(i): return Interval(max(self.start, i.start), min(self.end, i.end)) else: return None
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If intervals intersect, returns their intersection, otherwise returns None
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python
valid
IRC-SPHERE/HyperStream
hyperstream/utils/time_utils.py
https://github.com/IRC-SPHERE/HyperStream/blob/98478f4d31ed938f4aa7c958ed0d4c3ffcb2e780/hyperstream/utils/time_utils.py#L90-L98
def reconstruct_interval(experiment_id): """ Reverse the construct_experiment_id operation :param experiment_id: The experiment id :return: time interval """ start, end = map(lambda x: udatetime.utcfromtimestamp(x / 1000.0), map(float, experiment_id.split("-"))) from ..time_interval import TimeInterval return TimeInterval(start, end)
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Reverse the construct_experiment_id operation :param experiment_id: The experiment id :return: time interval
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python
train
SavinaRoja/OpenAccess_EPUB
src/openaccess_epub/utils/__init__.py
https://github.com/SavinaRoja/OpenAccess_EPUB/blob/6b77ba30b7394fd003920e7a7957bca963a90656/src/openaccess_epub/utils/__init__.py#L167-L176
def get_absolute_path(some_path): """ This function will return an appropriate absolute path for the path it is given. If the input is absolute, it will return unmodified; if the input is relative, it will be rendered as relative to the current working directory. """ if os.path.isabs(some_path): return some_path else: return evaluate_relative_path(os.getcwd(), some_path)
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This function will return an appropriate absolute path for the path it is given. If the input is absolute, it will return unmodified; if the input is relative, it will be rendered as relative to the current working directory.
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python
train
treycucco/bidon
bidon/util/__init__.py
https://github.com/treycucco/bidon/blob/d9f24596841d0e69e8ac70a1d1a1deecea95e340/bidon/util/__init__.py#L67-L75
def json_default(obj): """Convert an object to JSON, via the defaults set with register_json_default. :obj: the object to convert """ for default in _JSON_DEFAULTS: if default[0](obj): return default[1](obj) raise TypeError(repr(obj) + " is not JSON serializable")
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Convert an object to JSON, via the defaults set with register_json_default. :obj: the object to convert
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python
train
alvarogzp/telegram-bot-framework
bot/multithreading/worker/pool/workers/limited_lifespan.py
https://github.com/alvarogzp/telegram-bot-framework/blob/7b597a415c1901901c677976cb13100fc3083107/bot/multithreading/worker/pool/workers/limited_lifespan.py#L21-L34
def _get_and_execute(self): """ :return: True if it should continue running, False if it should end its execution. """ try: work = self.queue.get(timeout=self.max_seconds_idle) except queue.Empty: # max_seconds_idle has been exhausted, exiting self.end_notify() return False else: self._work(work) self.queue.task_done() return True
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:return: True if it should continue running, False if it should end its execution.
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python
train
peerplays-network/python-peerplays
peerplaysapi/websocket.py
https://github.com/peerplays-network/python-peerplays/blob/188f04238e7e21d5f73e9b01099eea44289ef6b7/peerplaysapi/websocket.py#L216-L263
def on_message(self, ws, reply, *args): """ This method is called by the websocket connection on every message that is received. If we receive a ``notice``, we hand over post-processing and signalling of events to ``process_notice``. """ log.debug("Received message: %s" % str(reply)) data = {} try: data = json.loads(reply, strict=False) except ValueError: raise ValueError("API node returned invalid format. Expected JSON!") if data.get("method") == "notice": id = data["params"][0] if id >= len(self.__events__): log.critical("Received an id that is out of range\n\n" + str(data)) return # This is a "general" object change notification if id == self.__events__.index("on_object"): # Let's see if a specific object has changed for notice in data["params"][1]: try: if "id" in notice: self.process_notice(notice) else: for obj in notice: if "id" in obj: self.process_notice(obj) except Exception as e: log.critical( "Error in process_notice: {}\n\n{}".format( str(e), traceback.format_exc ) ) else: try: callbackname = self.__events__[id] log.info("Patching through to call %s" % callbackname) [getattr(self.events, callbackname)(x) for x in data["params"][1]] except Exception as e: log.critical( "Error in {}: {}\n\n{}".format( callbackname, str(e), traceback.format_exc() ) )
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This method is called by the websocket connection on every message that is received. If we receive a ``notice``, we hand over post-processing and signalling of events to ``process_notice``.
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python
train
chaoss/grimoirelab-elk
grimoire_elk/enriched/git.py
https://github.com/chaoss/grimoirelab-elk/blob/64e08b324b36d9f6909bf705145d6451c8d34e65/grimoire_elk/enriched/git.py#L809-L842
def remove_commits(self, items, index, attribute, origin): """Delete documents that correspond to commits deleted in the Git repository :param items: target items to be deleted :param index: target index :param attribute: name of the term attribute to search items :param origin: name of the origin from where the items must be deleted """ es_query = ''' { "query": { "bool": { "must": { "term": { "origin": "%s" } }, "filter": { "terms": { "%s": [%s] } } } } } ''' % (origin, attribute, ",".join(['"%s"' % i for i in items])) r = self.requests.post(index + "/_delete_by_query?refresh", data=es_query, headers=HEADER_JSON, verify=False) try: r.raise_for_status() except requests.exceptions.HTTPError as ex: logger.error("Error updating deleted commits for %s.", self.elastic.anonymize_url(index)) logger.error(r.text) return
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Delete documents that correspond to commits deleted in the Git repository :param items: target items to be deleted :param index: target index :param attribute: name of the term attribute to search items :param origin: name of the origin from where the items must be deleted
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python
train
praekelt/django-analytics
analytics/geckoboard_views.py
https://github.com/praekelt/django-analytics/blob/29c22d03374ccc0ec451650e2c2886d324f6e5c6/analytics/geckoboard_views.py#L199-L215
def geckoboard_funnel(request, frequency=settings.STATISTIC_FREQUENCY_DAILY): """ Returns a funnel chart for the metrics specified in the GET variables. """ # get all the parameters for this function params = get_gecko_params(request, cumulative=True) metrics = Metric.objects.filter(uid__in=params['uids']) items = [(metric.latest_count(frequency=params['frequency'], count=not params['cumulative'], cumulative=params['cumulative']), metric.title) for metric in metrics] return { 'items' : items, 'type' : params['type'], 'percentage': params['percentage'], 'sort' : params['sort'], }
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Returns a funnel chart for the metrics specified in the GET variables.
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python
test
graphql-python/graphql-core-next
graphql/validation/validate.py
https://github.com/graphql-python/graphql-core-next/blob/073dce3f002f897d40f9348ffd8f107815160540/graphql/validation/validate.py#L15-L54
def validate( schema: GraphQLSchema, document_ast: DocumentNode, rules: Sequence[RuleType] = None, type_info: TypeInfo = None, ) -> List[GraphQLError]: """Implements the "Validation" section of the spec. Validation runs synchronously, returning a list of encountered errors, or an empty list if no errors were encountered and the document is valid. A list of specific validation rules may be provided. If not provided, the default list of rules defined by the GraphQL specification will be used. Each validation rule is a ValidationRule object which is a visitor object that holds a ValidationContext (see the language/visitor API). Visitor methods are expected to return GraphQLErrors, or lists of GraphQLErrors when invalid. Optionally a custom TypeInfo instance may be provided. If not provided, one will be created from the provided schema. """ if not document_ast or not isinstance(document_ast, DocumentNode): raise TypeError("You must provide a document node.") # If the schema used for validation is invalid, throw an error. assert_valid_schema(schema) if type_info is None: type_info = TypeInfo(schema) elif not isinstance(type_info, TypeInfo): raise TypeError(f"Not a TypeInfo object: {inspect(type_info)}") if rules is None: rules = specified_rules elif not isinstance(rules, (list, tuple)): raise TypeError("Rules must be passed as a list/tuple.") context = ValidationContext(schema, document_ast, type_info) # This uses a specialized visitor which runs multiple visitors in parallel, # while maintaining the visitor skip and break API. visitors = [rule(context) for rule in rules] # Visit the whole document with each instance of all provided rules. visit(document_ast, TypeInfoVisitor(type_info, ParallelVisitor(visitors))) return context.errors
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python
train
rigetti/pyquil
pyquil/api/_quantum_computer.py
https://github.com/rigetti/pyquil/blob/ec98e453084b0037d69d8c3245f6822a5422593d/pyquil/api/_quantum_computer.py#L122-L132
def get_isa(self, oneq_type: str = 'Xhalves', twoq_type: str = 'CZ') -> ISA: """ Return a target ISA for this QuantumComputer's device. See :py:func:`AbstractDevice.get_isa` for more. :param oneq_type: The family of one-qubit gates to target :param twoq_type: The family of two-qubit gates to target """ return self.device.get_isa(oneq_type=oneq_type, twoq_type=twoq_type)
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Return a target ISA for this QuantumComputer's device. See :py:func:`AbstractDevice.get_isa` for more. :param oneq_type: The family of one-qubit gates to target :param twoq_type: The family of two-qubit gates to target
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python
train
bitesofcode/projexui
projexui/widgets/xmultitagedit.py
https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/widgets/xmultitagedit.py#L622-L633
def setEditable(self, state): """ Sets whether or not the user can edit the items in the list by typing. :param state | <bool> """ self._editable = state if state: self.setEditTriggers(self.AllEditTriggers) else: self.setEditTriggers(self.NoEditTriggers)
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Sets whether or not the user can edit the items in the list by typing. :param state | <bool>
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python
train
assamite/creamas
creamas/vote.py
https://github.com/assamite/creamas/blob/54dc3e31c97a3f938e58272f8ab80b6bcafeff58/creamas/vote.py#L335-L366
def validate_candidates(self): """Validate current candidates. This method validates the current candidate list in all the agents in the environment (or underlying slave environments) and replaces the current :attr:`candidates` with the list of validated candidates. The artifact candidates must be hashable and have a :meth:`__eq__` implemented for validation to work on multi-environments and distributed environments. """ async def slave_task(addr, candidates): r_manager = await self.env.connect(addr) return await r_manager.validate_candidates(candidates) self._log(logging.DEBUG, "Validating {} candidates" .format(len(self.candidates))) candidates = self.candidates if self._single_env: self._candidates = self.env.validate_candidates(candidates) else: mgrs = self.get_managers() tasks = create_tasks(slave_task, mgrs, candidates, flatten=False) rets = run(tasks) valid_candidates = set(self.candidates) for r in rets: valid_candidates = valid_candidates.intersection(set(r)) self._candidates = list(valid_candidates) self._log(logging.DEBUG, "{} candidates after validation" .format(len(self.candidates)))
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Validate current candidates. This method validates the current candidate list in all the agents in the environment (or underlying slave environments) and replaces the current :attr:`candidates` with the list of validated candidates. The artifact candidates must be hashable and have a :meth:`__eq__` implemented for validation to work on multi-environments and distributed environments.
[ "Validate", "current", "candidates", "." ]
python
train
sprockets/sprockets.mixins.metrics
sprockets/mixins/metrics/statsd.py
https://github.com/sprockets/sprockets.mixins.metrics/blob/0b17d5f0c09a2be9db779e17e6789d3d5ff9a0d0/sprockets/mixins/metrics/statsd.py#L135-L140
async def _tcp_on_closed(self): """Invoked when the socket is closed.""" LOGGER.warning('Not connected to statsd, connecting in %s seconds', self._tcp_reconnect_sleep) await asyncio.sleep(self._tcp_reconnect_sleep) self._sock = self._tcp_socket()
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Invoked when the socket is closed.
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python
train
LEMS/pylems
lems/sim/build.py
https://github.com/LEMS/pylems/blob/4eeb719d2f23650fe16c38626663b69b5c83818b/lems/sim/build.py#L816-L844
def build_on_event(self, runnable, regime, on_event): """ Build OnEvent event handler code. @param on_event: OnEvent event handler object @type on_event: lems.model.dynamics.OnEvent @return: Generated OnEvent code @rtype: list(string) """ on_event_code = [] if self.debug: on_event_code += ['print("Maybe handling something for %s ("+str(id(self))+")")'%(runnable.id), 'print("EICs ("+str(id(self))+"): "+str(self.event_in_counters))'] on_event_code += ['count = self.event_in_counters[\'{0}\']'.\ format(on_event.port), 'while count > 0:', ' print(" Handling event")' if self.debug else '', ' count -= 1'] for action in on_event.actions: code = self.build_action(runnable, regime, action) for line in code: on_event_code += [' ' + line] on_event_code += ['self.event_in_counters[\'{0}\'] = 0'.\ format(on_event.port),] return on_event_code
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Build OnEvent event handler code. @param on_event: OnEvent event handler object @type on_event: lems.model.dynamics.OnEvent @return: Generated OnEvent code @rtype: list(string)
[ "Build", "OnEvent", "event", "handler", "code", "." ]
python
train
spookylukey/django-paypal
paypal/pro/creditcard.py
https://github.com/spookylukey/django-paypal/blob/b07d0a3ad91b5c5fe7bb27be3e5d70aabcdef76f/paypal/pro/creditcard.py#L61-L66
def get_type(self): """Return the type if it matches one of the cards.""" for card, pattern in CARDS.items(): if pattern.match(self.number): return card return None
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Return the type if it matches one of the cards.
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python
train
iotile/coretools
iotilebuild/iotile/build/config/scons-local-3.0.1/SCons/Tool/docbook/__init__.py
https://github.com/iotile/coretools/blob/2d794f5f1346b841b0dcd16c9d284e9bf2f3c6ec/iotilebuild/iotile/build/config/scons-local-3.0.1/SCons/Tool/docbook/__init__.py#L198-L213
def _detect(env): """ Detect all the command line tools that we might need for creating the requested output formats. """ global prefer_xsltproc if env.get('DOCBOOK_PREFER_XSLTPROC',''): prefer_xsltproc = True if ((not has_libxml2 and not has_lxml) or (prefer_xsltproc)): # Try to find the XSLT processors __detect_cl_tool(env, 'DOCBOOK_XSLTPROC', xsltproc_com, xsltproc_com_priority) __detect_cl_tool(env, 'DOCBOOK_XMLLINT', xmllint_com) __detect_cl_tool(env, 'DOCBOOK_FOP', fop_com, ['fop','xep','jw'])
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Detect all the command line tools that we might need for creating the requested output formats.
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python
train
marcinmiklitz/pywindow
pywindow/trajectory.py
https://github.com/marcinmiklitz/pywindow/blob/e5264812157224f22a691741ca2e0aefdc9bd2eb/pywindow/trajectory.py#L68-L95
def make_supercell(system, matrix, supercell=[1, 1, 1]): """ Return a supercell. This functions takes the input unitcell and creates a supercell of it that is returned as a new :class:`pywindow.molecular.MolecularSystem`. Parameters ---------- system : :attr:`pywindow.molecular.MolecularSystem.system` The unit cell for creation of the supercell matrix : :class:`numpy.array` The unit cell parameters in form of a lattice. supercell : :class:`list`, optional A list that specifies the size of the supercell in the a, b and c direction. (default=[1, 1, 1]) Returns ------- :class:`pywindow.molecular.MolecularSystem` Returns the created supercell as a new :class:`MolecularSystem`. """ user_supercell = [[1, supercell[0]], [1, supercell[1]], [1, supercell[1]]] system = create_supercell(system, matrix, supercell=user_supercell) return MolecularSystem.load_system(system)
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Return a supercell. This functions takes the input unitcell and creates a supercell of it that is returned as a new :class:`pywindow.molecular.MolecularSystem`. Parameters ---------- system : :attr:`pywindow.molecular.MolecularSystem.system` The unit cell for creation of the supercell matrix : :class:`numpy.array` The unit cell parameters in form of a lattice. supercell : :class:`list`, optional A list that specifies the size of the supercell in the a, b and c direction. (default=[1, 1, 1]) Returns ------- :class:`pywindow.molecular.MolecularSystem` Returns the created supercell as a new :class:`MolecularSystem`.
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python
train
offu/WeRoBot
werobot/pay.py
https://github.com/offu/WeRoBot/blob/fd42109105b03f9acf45ebd9dcabb9d5cff98f3c/werobot/pay.py#L60-L86
def create_js_pay_params(self, **package): """ 签名 js 需要的参数 详情请参考 支付开发文档 :: wxclient.create_js_pay_params( body=标题, out_trade_no=本地订单号, total_fee=价格单位分, notify_url=通知url, spbill_create_ip=建议为支付人ip, ) :param package: 需要签名的的参数 :return: 支付需要的对象 """ pay_param, sign, sign_type = self._pay_sign_dict( package=self.create_js_pay_package(**package) ) pay_param['paySign'] = sign pay_param['signType'] = sign_type # 腾讯这个还得转成大写 JS 才认 for key in ['appId', 'timeStamp', 'nonceStr']: pay_param[key] = str(pay_param.pop(key.lower())) return pay_param
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签名 js 需要的参数 详情请参考 支付开发文档 :: wxclient.create_js_pay_params( body=标题, out_trade_no=本地订单号, total_fee=价格单位分, notify_url=通知url, spbill_create_ip=建议为支付人ip, ) :param package: 需要签名的的参数 :return: 支付需要的对象
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python
train
klahnakoski/pyLibrary
jx_elasticsearch/es52/painless.py
https://github.com/klahnakoski/pyLibrary/blob/fa2dcbc48fda8d26999baef400e9a98149e0b982/jx_elasticsearch/es52/painless.py#L118-L130
def box(script): """ :param es_script: :return: TEXT EXPRESSION WITH NON OBJECTS BOXED """ if script.type is BOOLEAN: return "Boolean.valueOf(" + text_type(script.expr) + ")" elif script.type is INTEGER: return "Integer.valueOf(" + text_type(script.expr) + ")" elif script.type is NUMBER: return "Double.valueOf(" + text_type(script.expr) + ")" else: return script.expr
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:param es_script: :return: TEXT EXPRESSION WITH NON OBJECTS BOXED
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python
train
troeger/opensubmit
web/opensubmit/cmdline.py
https://github.com/troeger/opensubmit/blob/384a95b7c6fa41e3f949a129d25dafd9a1c54859/web/opensubmit/cmdline.py#L97-L108
def django_admin(args): ''' Run something like it would be done through Django's manage.py. ''' from django.core.management import execute_from_command_line from django.core.exceptions import ImproperlyConfigured os.environ.setdefault("DJANGO_SETTINGS_MODULE", "opensubmit.settings") try: execute_from_command_line([sys.argv[0]] + args) except ImproperlyConfigured as e: print(str(e)) exit(-1)
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Run something like it would be done through Django's manage.py.
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python
train
wecatch/app-turbo
turbo/app.py
https://github.com/wecatch/app-turbo/blob/75faf97371a9a138c53f92168d0a486636cb8a9c/turbo/app.py#L307-L314
def wo_resp(self, resp): """ can override for other style """ if self._data is not None: resp['res'] = self.to_str(self._data) return self.wo_json(resp)
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can override for other style
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python
train
andychase/reparse
reparse/expression.py
https://github.com/andychase/reparse/blob/5f46cdd0fc4e239c0ddeca4b542e48a5ae95c508/reparse/expression.py#L47-L55
def findall(self, string): """ Parse string, returning all outputs as parsed by functions """ output = [] for match in self.pattern.findall(string): if hasattr(match, 'strip'): match = [match] self._list_add(output, self.run(match)) return output
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Parse string, returning all outputs as parsed by functions
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python
train
oceanprotocol/oceandb-bigchaindb-driver
oceandb_bigchaindb_driver/plugin.py
https://github.com/oceanprotocol/oceandb-bigchaindb-driver/blob/82315bcc9f7ba8b01beb08014bdeb541546c6671/oceandb_bigchaindb_driver/plugin.py#L204-L238
def _delete(self, tx_id): """Delete a transaction. Read documentation about CRAB model in https://blog.bigchaindb.com/crab-create-retrieve-append-burn-b9f6d111f460. :param tx_id: transaction id :return: """ txs = self.driver.instance.transactions.get(asset_id=self.get_asset_id(tx_id)) unspent = txs[-1] output_index = 0 output = unspent['outputs'][output_index] transfer_input = { 'fulfillment': output['condition']['details'], 'fulfills': { 'output_index': output_index, 'transaction_id': unspent['id'] }, 'owners_before': output['public_keys'] } prepared_transfer_tx = self.driver.instance.transactions.prepare( operation='TRANSFER', asset=unspent['asset'] if 'id' in unspent['asset'] else {'id': unspent['id']}, inputs=transfer_input, recipients=self.BURN_ADDRESS, metadata={ 'namespace': 'burned', } ) signed_tx = self.driver.instance.transactions.fulfill( prepared_transfer_tx, private_keys=self.user.private_key, ) self.driver.instance.transactions.send_commit(signed_tx)
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Delete a transaction. Read documentation about CRAB model in https://blog.bigchaindb.com/crab-create-retrieve-append-burn-b9f6d111f460. :param tx_id: transaction id :return:
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python
train
pandas-dev/pandas
pandas/core/strings.py
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/strings.py#L1240-L1313
def str_pad(arr, width, side='left', fillchar=' '): """ Pad strings in the Series/Index up to width. Parameters ---------- width : int Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`. side : {'left', 'right', 'both'}, default 'left' Side from which to fill resulting string. fillchar : str, default ' ' Additional character for filling, default is whitespace. Returns ------- Series or Index of object Returns Series or Index with minimum number of char in object. See Also -------- Series.str.rjust : Fills the left side of strings with an arbitrary character. Equivalent to ``Series.str.pad(side='left')``. Series.str.ljust : Fills the right side of strings with an arbitrary character. Equivalent to ``Series.str.pad(side='right')``. Series.str.center : Fills boths sides of strings with an arbitrary character. Equivalent to ``Series.str.pad(side='both')``. Series.str.zfill : Pad strings in the Series/Index by prepending '0' character. Equivalent to ``Series.str.pad(side='left', fillchar='0')``. Examples -------- >>> s = pd.Series(["caribou", "tiger"]) >>> s 0 caribou 1 tiger dtype: object >>> s.str.pad(width=10) 0 caribou 1 tiger dtype: object >>> s.str.pad(width=10, side='right', fillchar='-') 0 caribou--- 1 tiger----- dtype: object >>> s.str.pad(width=10, side='both', fillchar='-') 0 -caribou-- 1 --tiger--- dtype: object """ if not isinstance(fillchar, str): msg = 'fillchar must be a character, not {0}' raise TypeError(msg.format(type(fillchar).__name__)) if len(fillchar) != 1: raise TypeError('fillchar must be a character, not str') if not is_integer(width): msg = 'width must be of integer type, not {0}' raise TypeError(msg.format(type(width).__name__)) if side == 'left': f = lambda x: x.rjust(width, fillchar) elif side == 'right': f = lambda x: x.ljust(width, fillchar) elif side == 'both': f = lambda x: x.center(width, fillchar) else: # pragma: no cover raise ValueError('Invalid side') return _na_map(f, arr)
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Pad strings in the Series/Index up to width. Parameters ---------- width : int Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`. side : {'left', 'right', 'both'}, default 'left' Side from which to fill resulting string. fillchar : str, default ' ' Additional character for filling, default is whitespace. Returns ------- Series or Index of object Returns Series or Index with minimum number of char in object. See Also -------- Series.str.rjust : Fills the left side of strings with an arbitrary character. Equivalent to ``Series.str.pad(side='left')``. Series.str.ljust : Fills the right side of strings with an arbitrary character. Equivalent to ``Series.str.pad(side='right')``. Series.str.center : Fills boths sides of strings with an arbitrary character. Equivalent to ``Series.str.pad(side='both')``. Series.str.zfill : Pad strings in the Series/Index by prepending '0' character. Equivalent to ``Series.str.pad(side='left', fillchar='0')``. Examples -------- >>> s = pd.Series(["caribou", "tiger"]) >>> s 0 caribou 1 tiger dtype: object >>> s.str.pad(width=10) 0 caribou 1 tiger dtype: object >>> s.str.pad(width=10, side='right', fillchar='-') 0 caribou--- 1 tiger----- dtype: object >>> s.str.pad(width=10, side='both', fillchar='-') 0 -caribou-- 1 --tiger--- dtype: object
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python
train
marshmallow-code/marshmallow-jsonapi
marshmallow_jsonapi/utils.py
https://github.com/marshmallow-code/marshmallow-jsonapi/blob/7183c9bb5cdeace4143e6678bab48d433ac439a1/marshmallow_jsonapi/utils.py#L38-L56
def resolve_params(obj, params, default=missing): """Given a dictionary of keyword arguments, return the same dictionary except with values enclosed in `< >` resolved to attributes on `obj`. """ param_values = {} for name, attr_tpl in iteritems(params): attr_name = tpl(str(attr_tpl)) if attr_name: attribute_value = get_value(obj, attr_name, default=default) if attribute_value is not missing: param_values[name] = attribute_value else: raise AttributeError( '{attr_name!r} is not a valid ' 'attribute of {obj!r}'.format(attr_name=attr_name, obj=obj), ) else: param_values[name] = attr_tpl return param_values
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Given a dictionary of keyword arguments, return the same dictionary except with values enclosed in `< >` resolved to attributes on `obj`.
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python
train
twilio/twilio-python
twilio/rest/pricing/v1/__init__.py
https://github.com/twilio/twilio-python/blob/c867895f55dcc29f522e6e8b8868d0d18483132f/twilio/rest/pricing/v1/__init__.py#L31-L37
def messaging(self): """ :rtype: twilio.rest.pricing.v1.messaging.MessagingList """ if self._messaging is None: self._messaging = MessagingList(self) return self._messaging
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:rtype: twilio.rest.pricing.v1.messaging.MessagingList
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python
train
commonsense/metanl
metanl/token_utils.py
https://github.com/commonsense/metanl/blob/4b9ae8353489cc409bebd7e1fe10ab5b527b078e/metanl/token_utils.py#L28-L44
def untokenize(words): """ Untokenizing a text undoes the tokenizing operation, restoring punctuation and spaces to the places that people expect them to be. Ideally, `untokenize(tokenize(text))` should be identical to `text`, except for line breaks. """ text = ' '.join(words) step1 = text.replace("`` ", '"').replace(" ''", '"').replace('. . .', '...') step2 = step1.replace(" ( ", " (").replace(" ) ", ") ") step3 = re.sub(r' ([.,:;?!%]+)([ \'"`])', r"\1\2", step2) step4 = re.sub(r' ([.,:;?!%]+)$', r"\1", step3) step5 = step4.replace(" '", "'").replace(" n't", "n't").replace( "can not", "cannot") step6 = step5.replace(" ` ", " '") return step6.strip()
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Untokenizing a text undoes the tokenizing operation, restoring punctuation and spaces to the places that people expect them to be. Ideally, `untokenize(tokenize(text))` should be identical to `text`, except for line breaks.
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python
train
CellProfiler/centrosome
centrosome/cpmorphology.py
https://github.com/CellProfiler/centrosome/blob/7bd9350a2d4ae1b215b81eabcecfe560bbb1f32a/centrosome/cpmorphology.py#L3260-L3276
def hbreak(image, mask=None, iterations=1): '''Remove horizontal breaks 1 1 1 1 1 1 0 1 0 -> 0 0 0 (this case only) 1 1 1 1 1 1 ''' global hbreak_table if mask is None: masked_image = image else: masked_image = image.astype(bool).copy() masked_image[~mask] = False result = table_lookup(masked_image, hbreak_table, False) if not mask is None: result[~mask] = image[~mask] return result
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Remove horizontal breaks 1 1 1 1 1 1 0 1 0 -> 0 0 0 (this case only) 1 1 1 1 1 1
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python
train
LuminosoInsight/python-ftfy
ftfy/formatting.py
https://github.com/LuminosoInsight/python-ftfy/blob/476acc6ad270bffe07f97d4f7cf2139acdc69633/ftfy/formatting.py#L67-L98
def display_ljust(text, width, fillchar=' '): """ Return `text` left-justified in a Unicode string whose display width, in a monospaced terminal, should be at least `width` character cells. The rest of the string will be padded with `fillchar`, which must be a width-1 character. "Left" here means toward the beginning of the string, which may actually appear on the right in an RTL context. This is similar to the use of the word "left" in "left parenthesis". >>> lines = ['Table flip', '(╯°□°)╯︵ ┻━┻', 'ちゃぶ台返し'] >>> for line in lines: ... print(display_ljust(line, 20, '▒')) Table flip▒▒▒▒▒▒▒▒▒▒ (╯°□°)╯︵ ┻━┻▒▒▒▒▒▒▒ ちゃぶ台返し▒▒▒▒▒▒▒▒ This example, and the similar ones that follow, should come out justified correctly when viewed in a monospaced terminal. It will probably not look correct if you're viewing this code or documentation in a Web browser. """ if character_width(fillchar) != 1: raise ValueError("The padding character must have display width 1") text_width = monospaced_width(text) if text_width == -1: # There's a control character here, so just don't add padding return text padding = max(0, width - text_width) return text + fillchar * padding
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Return `text` left-justified in a Unicode string whose display width, in a monospaced terminal, should be at least `width` character cells. The rest of the string will be padded with `fillchar`, which must be a width-1 character. "Left" here means toward the beginning of the string, which may actually appear on the right in an RTL context. This is similar to the use of the word "left" in "left parenthesis". >>> lines = ['Table flip', '(╯°□°)╯︵ ┻━┻', 'ちゃぶ台返し'] >>> for line in lines: ... print(display_ljust(line, 20, '▒')) Table flip▒▒▒▒▒▒▒▒▒▒ (╯°□°)╯︵ ┻━┻▒▒▒▒▒▒▒ ちゃぶ台返し▒▒▒▒▒▒▒▒ This example, and the similar ones that follow, should come out justified correctly when viewed in a monospaced terminal. It will probably not look correct if you're viewing this code or documentation in a Web browser.
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python
train
limodou/uliweb
uliweb/orm/__init__.py
https://github.com/limodou/uliweb/blob/34472f25e4bc0b954a35346672f94e84ef18b076/uliweb/orm/__init__.py#L2728-L2739
def distinct(self, field=None): """ If field is None, then it means that it'll create: select distinct * and if field is not None, for example: 'name', it'll create: select distinc(name), """ if field is None: self.funcs.append(('distinct', (), {})) else: self.distinct_field = field return self
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If field is None, then it means that it'll create: select distinct * and if field is not None, for example: 'name', it'll create: select distinc(name),
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python
train
ceph/ceph-deploy
ceph_deploy/hosts/remotes.py
https://github.com/ceph/ceph-deploy/blob/86943fcc454cd4c99a86e3493e9e93a59c661fef/ceph_deploy/hosts/remotes.py#L178-L189
def write_keyring(path, key, uid=-1, gid=-1): """ create a keyring file """ # Note that we *require* to avoid deletion of the temp file # otherwise we risk not being able to copy the contents from # one file system to the other, hence the `delete=False` tmp_file = tempfile.NamedTemporaryFile('wb', delete=False) tmp_file.write(key) tmp_file.close() keyring_dir = os.path.dirname(path) if not path_exists(keyring_dir): makedir(keyring_dir, uid, gid) shutil.move(tmp_file.name, path)
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create a keyring file
[ "create", "a", "keyring", "file" ]
python
train
HewlettPackard/python-hpOneView
hpOneView/resources/networking/logical_interconnects.py
https://github.com/HewlettPackard/python-hpOneView/blob/3c6219723ef25e6e0c83d44a89007f89bc325b89/hpOneView/resources/networking/logical_interconnects.py#L449-L464
def update_qos_aggregated_configuration(self, qos_configuration, timeout=-1): """ Updates the QoS aggregated configuration for the logical interconnect. Args: qos_configuration: QOS configuration. timeout: Timeout in seconds. Wait for task completion by default. The timeout does not abort the operation in OneView, just stops waiting for its completion. Returns: dict: Logical Interconnect. """ uri = "{}{}".format(self.data["uri"], self.QOS_AGGREGATED_CONFIGURATION) return self._helper.update(qos_configuration, uri=uri, timeout=timeout)
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Updates the QoS aggregated configuration for the logical interconnect. Args: qos_configuration: QOS configuration. timeout: Timeout in seconds. Wait for task completion by default. The timeout does not abort the operation in OneView, just stops waiting for its completion. Returns: dict: Logical Interconnect.
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python
train
stitchfix/pyxley
pyxley/charts/mg/barchart.py
https://github.com/stitchfix/pyxley/blob/2dab00022d977d986169cd8a629b3a2f91be893f/pyxley/charts/mg/barchart.py#L58-L70
def to_json(df, x, y): """Format output for json response.""" values = [] for i, row in df.iterrows(): values.append({ "x": row[x], "y": row[y] }) if df.empty: return {"result": [{"x": 0, "y": 0}], "date": False} return {"result": values, "date": False}
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Format output for json response.
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python
train
treycucco/bidon
bidon/db/access/model_access.py
https://github.com/treycucco/bidon/blob/d9f24596841d0e69e8ac70a1d1a1deecea95e340/bidon/db/access/model_access.py#L208-L212
def get_model_id_constraints(model): """Returns constraints to target a specific model.""" pkname = model.primary_key_name pkey = model.primary_key return get_id_constraints(pkname, pkey)
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Returns constraints to target a specific model.
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python
train
RedKrieg/pysparklines
sparkline/sparkline.py
https://github.com/RedKrieg/pysparklines/blob/7efdc98f841a0003e138a93c4e27cd71a64e7062/sparkline/sparkline.py#L41-L55
def guess_series(input_string): u"""Tries to convert <input_string> into a list of floats. Example: >>> guess_series("0.5 1.2 3.5 7.3 8 12.5, 13.2," ... "15.0, 14.2, 11.8, 6.1, 1.9") [0.5, 1.2, 3.5, 7.3, 8.0, 12.5, 13.2, 15.0, 14.2, 11.8, 6.1, 1.9] """ float_finder = re.compile("([-+]?[0-9]*\.?[0-9]+(?:[eE][-+]?[0-9]+)?)") return ([ i for i in [ _convert_to_float(j) for j in float_finder.findall(input_string) # Remove entires we couldn't convert to a sensible value. ] if i is not None and not math.isnan(i) and not math.isinf(i) ])
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u"""Tries to convert <input_string> into a list of floats. Example: >>> guess_series("0.5 1.2 3.5 7.3 8 12.5, 13.2," ... "15.0, 14.2, 11.8, 6.1, 1.9") [0.5, 1.2, 3.5, 7.3, 8.0, 12.5, 13.2, 15.0, 14.2, 11.8, 6.1, 1.9]
[ "u", "Tries", "to", "convert", "<input_string", ">", "into", "a", "list", "of", "floats", "." ]
python
train
NetEaseGame/ATX
atx/drivers/ios_webdriveragent.py
https://github.com/NetEaseGame/ATX/blob/f4415c57b45cb0730e08899cbc92a2af1c047ffb/atx/drivers/ios_webdriveragent.py#L165-L175
def _take_screenshot(self): """Take a screenshot, also called by Mixin Args: - filename(string): file name to save Returns: PIL Image object """ raw_png = self._wda.screenshot() img = Image.open(BytesIO(raw_png)) return img
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Take a screenshot, also called by Mixin Args: - filename(string): file name to save Returns: PIL Image object
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python
train
StackStorm/pybind
pybind/nos/v6_0_2f/rbridge_id/snmp_server/__init__.py
https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/nos/v6_0_2f/rbridge_id/snmp_server/__init__.py#L100-L121
def _set_engineID(self, v, load=False): """ Setter method for engineID, mapped from YANG variable /rbridge_id/snmp_server/engineID (container) If this variable is read-only (config: false) in the source YANG file, then _set_engineID is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_engineID() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=engineID.engineID, is_container='container', presence=False, yang_name="engineID", rest_name="engineID", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u"Holds local Agents's Engine ID. Reboot is required to make changes to be effective in snmp", u'callpoint': u'snmplocalengineid', u'cli-incomplete-no': None}}, namespace='urn:brocade.com:mgmt:brocade-snmp', defining_module='brocade-snmp', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """engineID must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=engineID.engineID, is_container='container', presence=False, yang_name="engineID", rest_name="engineID", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u"Holds local Agents's Engine ID. Reboot is required to make changes to be effective in snmp", u'callpoint': u'snmplocalengineid', u'cli-incomplete-no': None}}, namespace='urn:brocade.com:mgmt:brocade-snmp', defining_module='brocade-snmp', yang_type='container', is_config=True)""", }) self.__engineID = t if hasattr(self, '_set'): self._set()
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python
train
KelSolaar/Umbra
umbra/managers/actions_manager.py
https://github.com/KelSolaar/Umbra/blob/66f45f08d9d723787f1191989f8b0dda84b412ce/umbra/managers/actions_manager.py#L374-L392
def get_category(self, name, vivify=False): """ Returns requested category. :param name: Category to retrieve. :type name: unicode :param vivify: Vivify missing parents in the chain to the requested category. :type vivify: bool :return: Category. :rtype: dict """ category = self.__get_category(self.__categories, name, vivify) if isinstance(category, dict): LOGGER.debug("> Category '{0}': '{1}'.".format(name, category)) return category else: raise umbra.exceptions.CategoryExistsError("{0} | '{1}' category doesn't exists!".format (self.__class__.__name__, name))
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Returns requested category. :param name: Category to retrieve. :type name: unicode :param vivify: Vivify missing parents in the chain to the requested category. :type vivify: bool :return: Category. :rtype: dict
[ "Returns", "requested", "category", "." ]
python
train
saltstack/salt
salt/modules/aptly.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/aptly.py#L462-L485
def list_mirrors(config_path=_DEFAULT_CONFIG_PATH): ''' Get a list of all the mirrored remote repositories. :param str config_path: The path to the configuration file for the aptly instance. :return: A list of the mirror names. :rtype: list CLI Example: .. code-block:: bash salt '*' aptly.list_mirrors ''' _validate_config(config_path) cmd = ['mirror', 'list', '-config={}'.format(config_path), '-raw=true'] cmd_ret = _cmd_run(cmd) ret = [line.strip() for line in cmd_ret.splitlines()] log.debug('Found mirrors: %s', len(ret)) return ret
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Get a list of all the mirrored remote repositories. :param str config_path: The path to the configuration file for the aptly instance. :return: A list of the mirror names. :rtype: list CLI Example: .. code-block:: bash salt '*' aptly.list_mirrors
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python
train
angr/angr
angr/analyses/ddg.py
https://github.com/angr/angr/blob/4e2f97d56af5419ee73bdb30482c8dd8ff5f3e40/angr/analyses/ddg.py#L1581-L1605
def find_killers(self, var_def, simplified_graph=True): """ Find all killers to the specified variable definition. :param ProgramVariable var_def: The variable definition. :param bool simplified_graph: True if we want to search in the simplified graph, False otherwise. :return: A collection of all killers to the specified variable definition. :rtype: list """ if simplified_graph: graph = self.simplified_data_graph else: graph = self.data_graph if var_def not in graph: return [] killers = [] out_edges = graph.out_edges(var_def, data=True) for _, dst, data in out_edges: if 'type' in data and data['type'] == 'kill': killers.append(dst) return killers
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Find all killers to the specified variable definition. :param ProgramVariable var_def: The variable definition. :param bool simplified_graph: True if we want to search in the simplified graph, False otherwise. :return: A collection of all killers to the specified variable definition. :rtype: list
[ "Find", "all", "killers", "to", "the", "specified", "variable", "definition", "." ]
python
train
Nic30/hwt
hwt/pyUtils/fileHelpers.py
https://github.com/Nic30/hwt/blob/8cbb399e326da3b22c233b98188a9d08dec057e6/hwt/pyUtils/fileHelpers.py#L5-L26
def find_files(directory, pattern, recursive=True): """ Find files by pattern in directory """ if not os.path.isdir(directory): if os.path.exists(directory): raise IOError(directory + ' is not directory') else: raise IOError(directory + " does not exists") if recursive: for root, _, files in os.walk(directory): for basename in files: if fnmatch.fnmatch(basename, pattern): filename = os.path.join(root, basename) yield filename else: root = directory for basename in os.listdir(root): if fnmatch.fnmatch(basename, pattern): filename = os.path.join(root, basename) if os.path.isfile(filename): yield filename
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Find files by pattern in directory
[ "Find", "files", "by", "pattern", "in", "directory" ]
python
test
revarbat/pymuv
pymuv/lvalue.py
https://github.com/revarbat/pymuv/blob/cefa2f2d35fc32054b9595da5f3393f6cceee5e0/pymuv/lvalue.py#L300-L339
def del_expr(self, ctx): """ Returns the MUF needed to delete a given lvalue. (ie: array item) Returned MUF will set a bare variable to 0, and will remove the given indexed item for an indexed array or dictionary. """ if self.readonly: raise MuvError( "Cannot assign value to constant '%s'." % self.varname, position=self.position ) varname = ctx.lookup_variable(self.varname) if varname is None: raise MuvError( "Undeclared identifier '%s'." % self.varname, position=self.position ) if len(self.indexing) == 0: return "0 {var} !".format(var=varname) if len(self.indexing) == 1: if ctx.target in ['fb7']: return "{var} @ {idx} array_delitem".format( var=varname, idx=self.indexing[0].generate_code(ctx), ) else: return "{var} @ {idx} array_delitem dup {var} !".format( var=varname, idx=self.indexing[0].generate_code(ctx), ) if ctx.target in ['fb7']: return "{var} @ {{ {idx} }}list array_nested_del".format( var=varname, idx=" ".join(x.generate_code(ctx) for x in self.indexing), ) else: return "{var} @ {{ {idx} }}list array_nested_del dup {var} !".format( var=varname, idx=" ".join(x.generate_code(ctx) for x in self.indexing), )
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Returns the MUF needed to delete a given lvalue. (ie: array item) Returned MUF will set a bare variable to 0, and will remove the given indexed item for an indexed array or dictionary.
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python
train
cokelaer/spectrum
src/spectrum/toeplitz.py
https://github.com/cokelaer/spectrum/blob/bad6c32e3f10e185098748f67bb421b378b06afe/src/spectrum/toeplitz.py#L21-L81
def TOEPLITZ(T0, TC, TR, Z): """solve the general toeplitz linear equations Solve TX=Z :param T0: zero lag value :param TC: r1 to rN :param TR: r1 to rN returns X requires 3M^2+M operations instead of M^3 with gaussian elimination .. warning:: not used right now """ assert len(TC)>0 assert len(TC)==len(TR) M = len(TC) X = numpy.zeros(M+1,dtype=complex) A = numpy.zeros(M,dtype=complex) B = numpy.zeros(M,dtype=complex) P = T0 if P == 0: raise ValueError("P must be different from zero") if P == 0: raise ValueError("P must be different from zero") X[0] = Z[0]/T0 for k in range(0, M): save1 = TC[k] save2 = TR[k] beta = X[0]*TC[k] if k == 0: temp1 = -save1 / P temp2 = -save2 / P else: for j in range(0, k): save1 = save1 + A[j] * TC[k-j-1] save2 = save2 + B[j] * TR[k-j-1] beta = beta + X[j+1] * TC[k-j-1] temp1 = -save1 / P temp2 = -save2/P P = P * (1. - (temp1*temp2)) if P <= 0: raise ValueError("singular matrix") A[k] = temp1 B[k] = temp2 alpha = (Z[k+1]-beta)/P if k == 0: X[k+1] = alpha for j in range(0,k+1): X[j] = X[j] + alpha * B[k-j] continue for j in range(0, k): kj = k-j-1 save1 = A[j] A[j] = save1 + temp1 * B[kj] B[kj] = B[kj] + temp2*save1 X[k+1] = alpha for j in range(0,k+1): X[j] = X[j] + alpha*B[k-j] return X
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solve the general toeplitz linear equations Solve TX=Z :param T0: zero lag value :param TC: r1 to rN :param TR: r1 to rN returns X requires 3M^2+M operations instead of M^3 with gaussian elimination .. warning:: not used right now
[ "solve", "the", "general", "toeplitz", "linear", "equations" ]
python
valid
bcbio/bcbio-nextgen
bcbio/rnaseq/gtf.py
https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/rnaseq/gtf.py#L263-L282
def _biotype_lookup_fn(gtf): """ return a function that will look up the biotype of a feature this checks for either gene_biotype or biotype being set or for the source column to have biotype information """ db = get_gtf_db(gtf) sources = set([feature.source for feature in db.all_features()]) gene_biotypes = set([feature.attributes.get("gene_biotype", [None])[0] for feature in db.all_features()]) biotypes = set([feature.attributes.get("biotype", [None])[0] for feature in db.all_features()]) if "protein_coding" in sources: return lambda feature: feature.source elif "protein_coding" in biotypes: return lambda feature: feature.attributes.get("biotype", [None])[0] elif "protein_coding" in gene_biotypes: return lambda feature: feature.attributes.get("gene_biotype", [None])[0] else: return None
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return a function that will look up the biotype of a feature this checks for either gene_biotype or biotype being set or for the source column to have biotype information
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python
train
10gen/mongo-orchestration
mongo_orchestration/servers.py
https://github.com/10gen/mongo-orchestration/blob/81fd2224205922ea2178b08190b53a33aec47261/mongo_orchestration/servers.py#L283-L313
def info(self): """return info about server as dict object""" proc_info = {"name": self.name, "params": self.cfg, "alive": self.is_alive, "optfile": self.config_path} if self.is_alive: proc_info['pid'] = self.proc.pid logger.debug("proc_info: {proc_info}".format(**locals())) mongodb_uri = '' server_info = {} status_info = {} if self.hostname and self.cfg.get('port', None): try: c = self.connection server_info = c.server_info() logger.debug("server_info: {server_info}".format(**locals())) mongodb_uri = 'mongodb://' + self.hostname status_info = {"primary": c.is_primary, "mongos": c.is_mongos} logger.debug("status_info: {status_info}".format(**locals())) except (pymongo.errors.AutoReconnect, pymongo.errors.OperationFailure, pymongo.errors.ConnectionFailure): server_info = {} status_info = {} result = {"mongodb_uri": mongodb_uri, "statuses": status_info, "serverInfo": server_info, "procInfo": proc_info, "orchestration": 'servers'} if self.login: result['mongodb_auth_uri'] = self.mongodb_auth_uri(self.hostname) logger.debug("return {result}".format(result=result)) return result
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return info about server as dict object
[ "return", "info", "about", "server", "as", "dict", "object" ]
python
train
Microsoft/malmo
MalmoEnv/malmoenv/bootstrap.py
https://github.com/Microsoft/malmo/blob/4139cd6f3e52f6e893a931a1d4b70d35f8e70e5a/MalmoEnv/malmoenv/bootstrap.py#L68-L88
def launch_minecraft(port, installdir="MalmoPlatform", replaceable=False): """Launch Minecraft listening for malmoenv connections. Args: port: the TCP port to listen on. installdir: the install dir name. Defaults to MalmoPlatform. Must be same as given (or defaulted) in download call if used. replaceable: whether or not to automatically restart Minecraft (default is false). """ launch_script = './launchClient.sh' if os.name == 'nt': launch_script = 'launchClient.bat' cwd = os.getcwd() os.chdir(installdir) os.chdir("Minecraft") try: cmd = [launch_script, '-port', str(port), '-env'] if replaceable: cmd.append('-replaceable') subprocess.check_call(cmd) finally: os.chdir(cwd)
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Launch Minecraft listening for malmoenv connections. Args: port: the TCP port to listen on. installdir: the install dir name. Defaults to MalmoPlatform. Must be same as given (or defaulted) in download call if used. replaceable: whether or not to automatically restart Minecraft (default is false).
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python
train
JdeRobot/base
src/drivers/MAVLinkServer/MAVProxy/pymavlink/dialects/v10/matrixpilot.py
https://github.com/JdeRobot/base/blob/303b18992785b2fe802212f2d758a60873007f1f/src/drivers/MAVLinkServer/MAVProxy/pymavlink/dialects/v10/matrixpilot.py#L12729-L12739
def gps_rtcm_data_send(self, flags, len, data, force_mavlink1=False): ''' WORK IN PROGRESS! RTCM message for injecting into the onboard GPS (used for DGPS) flags : LSB: 1 means message is fragmented (uint8_t) len : data length (uint8_t) data : RTCM message (may be fragmented) (uint8_t) ''' return self.send(self.gps_rtcm_data_encode(flags, len, data), force_mavlink1=force_mavlink1)
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WORK IN PROGRESS! RTCM message for injecting into the onboard GPS (used for DGPS) flags : LSB: 1 means message is fragmented (uint8_t) len : data length (uint8_t) data : RTCM message (may be fragmented) (uint8_t)
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python
train
datajoint/datajoint-python
datajoint/connection.py
https://github.com/datajoint/datajoint-python/blob/4f29bb154a7ed2b8b64b4d3a9c8be4c16b39621c/datajoint/connection.py#L20-L44
def conn(host=None, user=None, password=None, init_fun=None, reset=False): """ Returns a persistent connection object to be shared by multiple modules. If the connection is not yet established or reset=True, a new connection is set up. If connection information is not provided, it is taken from config which takes the information from dj_local_conf.json. If the password is not specified in that file datajoint prompts for the password. :param host: hostname :param user: mysql user :param password: mysql password :param init_fun: initialization function :param reset: whether the connection should be reset or not """ if not hasattr(conn, 'connection') or reset: host = host if host is not None else config['database.host'] user = user if user is not None else config['database.user'] password = password if password is not None else config['database.password'] if user is None: # pragma: no cover user = input("Please enter DataJoint username: ") if password is None: # pragma: no cover password = getpass(prompt="Please enter DataJoint password: ") init_fun = init_fun if init_fun is not None else config['connection.init_function'] conn.connection = Connection(host, user, password, init_fun) return conn.connection
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python
train
mbedmicro/pyOCD
pyocd/probe/pydapaccess/dap_access_cmsis_dap.py
https://github.com/mbedmicro/pyOCD/blob/41a174718a9739f3cbe785c2ba21cb7fd1310c6f/pyocd/probe/pydapaccess/dap_access_cmsis_dap.py#L452-L465
def get_connected_devices(): """ Return an array of all mbed boards connected """ all_daplinks = [] all_interfaces = _get_interfaces() for interface in all_interfaces: try: new_daplink = DAPAccessCMSISDAP(None, interface=interface) all_daplinks.append(new_daplink) except DAPAccessIntf.TransferError: logger = logging.getLogger(__name__) logger.error('Failed to get unique id', exc_info=session.Session.get_current().log_tracebacks) return all_daplinks
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Return an array of all mbed boards connected
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python
train
pgjones/quart
quart/ctx.py
https://github.com/pgjones/quart/blob/7cb2d3bd98e8746025764f2b933abc12041fa175/quart/ctx.py#L368-L373
def pop(self, name: str, default: Any=_sentinel) -> Any: """Pop, get and remove the named attribute of this instance.""" if default is _sentinel: return self.__dict__.pop(name) else: return self.__dict__.pop(name, default)
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Pop, get and remove the named attribute of this instance.
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python
train
CalebBell/thermo
thermo/chemical.py
https://github.com/CalebBell/thermo/blob/3857ed023a3e64fd3039a32d53576c24990ef1c3/thermo/chemical.py#L1604-L1625
def Cps(self): r'''Solid-phase heat capacity of the chemical at its current temperature, in units of [J/kg/K]. For calculation of this property at other temperatures, or specifying manually the method used to calculate it, and more - see the object oriented interface :obj:`thermo.heat_capacity.HeatCapacitySolid`; each Chemical instance creates one to actually perform the calculations. Note that that interface provides output in molar units. Examples -------- >>> Chemical('palladium', T=400).Cps 241.63563239992484 >>> Pd = Chemical('palladium', T=400) >>> Cpsms = [Pd.HeatCapacitySolid.T_dependent_property(T) for T in np.linspace(300,500, 5)] >>> [property_molar_to_mass(Cps, Pd.MW) for Cps in Cpsms] [234.40150347679008, 238.01856793835751, 241.63563239992484, 245.25269686149224, 248.86976132305958] ''' Cpsm = self.HeatCapacitySolid(self.T) if Cpsm: return property_molar_to_mass(Cpsm, self.MW) return None
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r'''Solid-phase heat capacity of the chemical at its current temperature, in units of [J/kg/K]. For calculation of this property at other temperatures, or specifying manually the method used to calculate it, and more - see the object oriented interface :obj:`thermo.heat_capacity.HeatCapacitySolid`; each Chemical instance creates one to actually perform the calculations. Note that that interface provides output in molar units. Examples -------- >>> Chemical('palladium', T=400).Cps 241.63563239992484 >>> Pd = Chemical('palladium', T=400) >>> Cpsms = [Pd.HeatCapacitySolid.T_dependent_property(T) for T in np.linspace(300,500, 5)] >>> [property_molar_to_mass(Cps, Pd.MW) for Cps in Cpsms] [234.40150347679008, 238.01856793835751, 241.63563239992484, 245.25269686149224, 248.86976132305958]
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python
valid
openstack/proliantutils
proliantutils/ilo/ris.py
https://github.com/openstack/proliantutils/blob/86ef3b47b4eca97c221577e3570b0240d6a25f22/proliantutils/ilo/ris.py#L752-L764
def reset_secure_boot_keys(self): """Reset secure boot keys to manufacturing defaults. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server. """ if self._is_boot_mode_uefi(): self._change_secure_boot_settings('ResetToDefaultKeys', True) else: msg = ('System is not in UEFI boot mode. "SecureBoot" related ' 'resources cannot be changed.') raise exception.IloCommandNotSupportedInBiosError(msg)
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Reset secure boot keys to manufacturing defaults. :raises: IloError, on an error from iLO. :raises: IloCommandNotSupportedError, if the command is not supported on the server.
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python
train
stevepeak/inquiry
inquiry/helpers.py
https://github.com/stevepeak/inquiry/blob/f6ea435c302560ba19985b5d4ce2c97e2f321508/inquiry/helpers.py#L18-L33
def _merge_fix(d): """Fixes keys that start with "&" and "-" d = { "&steve": 10, "-gary": 4 } result = { "steve": 10, "gary": 4 } """ if type(d) is dict: for key in d.keys(): if key[0] in ('&', '-'): d[key[1:]] = _merge_fix(d.pop(key)) return d
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Fixes keys that start with "&" and "-" d = { "&steve": 10, "-gary": 4 } result = { "steve": 10, "gary": 4 }
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python
train
bitesofcode/projexui
projexui/widgets/xoverlaywizard.py
https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/widgets/xoverlaywizard.py#L558-L618
def next(self): """ Goes to the previous page for this wizard. """ curr_page = self.currentPage() if not curr_page: return elif not curr_page.validatePage(): return pageId = curr_page.nextId() try: next_page = self._pages[pageId] except KeyError: return self._currentId = pageId self._navigation.append(pageId) y = curr_page.y() next_page.move(self.width(), y) # animate the last page in anim_in = QtCore.QPropertyAnimation(self) anim_in.setTargetObject(curr_page) anim_in.setPropertyName('pos') anim_in.setStartValue(curr_page.pos()) anim_in.setEndValue(QtCore.QPoint(-curr_page.width(), y)) anim_in.setDuration(self.animationSpeed()) anim_in.setEasingCurve(QtCore.QEasingCurve.Linear) # animate the current page out anim_out = QtCore.QPropertyAnimation(self) anim_out.setTargetObject(next_page) anim_out.setPropertyName('pos') anim_out.setStartValue(next_page.pos()) anim_out.setEndValue(curr_page.pos()) anim_out.setDuration(self.animationSpeed()) anim_out.setEasingCurve(QtCore.QEasingCurve.Linear) # create the anim group anim_grp = QtCore.QParallelAnimationGroup(self) anim_grp.addAnimation(anim_in) anim_grp.addAnimation(anim_out) anim_grp.finished.connect(curr_page.hide) anim_grp.finished.connect(anim_grp.deleteLater) next_page.show() # update the button states self._buttons[self.WizardButton.BackButton].setVisible(True) self._buttons[self.WizardButton.NextButton].setVisible(self.canGoForward()) self._buttons[self.WizardButton.RetryButton].setVisible(self.canRetry()) self._buttons[self.WizardButton.CommitButton].setVisible(next_page.isCommitPage()) self._buttons[self.WizardButton.FinishButton].setVisible(next_page.isFinalPage()) self.adjustSize() # initialize the new page self.currentIdChanged.emit(pageId) next_page.initializePage() anim_grp.start()
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Goes to the previous page for this wizard.
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python
train
HDI-Project/ballet
ballet/util/io.py
https://github.com/HDI-Project/ballet/blob/6f4d4b87b8234cb6bb38b9e9484a58ef8fe8fdb2/ballet/util/io.py#L20-L33
def write_tabular(obj, filepath): """Write tabular object in HDF5 or pickle format Args: obj (array or DataFrame): tabular object to write filepath (path-like): path to write to; must end in '.h5' or '.pkl' """ _, fn, ext = splitext2(filepath) if ext == '.h5': _write_tabular_h5(obj, filepath) elif ext == '.pkl': _write_tabular_pickle(obj, filepath) else: raise NotImplementedError
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Write tabular object in HDF5 or pickle format Args: obj (array or DataFrame): tabular object to write filepath (path-like): path to write to; must end in '.h5' or '.pkl'
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python
train
QuantEcon/QuantEcon.py
quantecon/markov/ddp.py
https://github.com/QuantEcon/QuantEcon.py/blob/26a66c552f2a73967d7efb6e1f4b4c4985a12643/quantecon/markov/ddp.py#L455-L485
def to_sa_pair_form(self, sparse=True): """ Convert this instance of `DiscreteDP` to SA-pair form Parameters ---------- sparse : bool, optional(default=True) Should the `Q` matrix be stored as a sparse matrix? If true the CSR format is used Returns ------- ddp_sa : DiscreteDP The correspnoding DiscreteDP instance in SA-pair form Notes ----- If this instance is already in SA-pair form then it is returned un-modified """ if self._sa_pair: return self else: s_ind, a_ind = np.where(self.R > - np.inf) RL = self.R[s_ind, a_ind] if sparse: QL = sp.csr_matrix(self.Q[s_ind, a_ind]) else: QL = self.Q[s_ind, a_ind] return DiscreteDP(RL, QL, self.beta, s_ind, a_ind)
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Convert this instance of `DiscreteDP` to SA-pair form Parameters ---------- sparse : bool, optional(default=True) Should the `Q` matrix be stored as a sparse matrix? If true the CSR format is used Returns ------- ddp_sa : DiscreteDP The correspnoding DiscreteDP instance in SA-pair form Notes ----- If this instance is already in SA-pair form then it is returned un-modified
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python
train
uralbash/pyramid_pages
pyramid_pages/resources.py
https://github.com/uralbash/pyramid_pages/blob/545b1ecb2e5dee5742135ba2a689b9635dd4efa1/pyramid_pages/resources.py#L156-L166
def models_of_config(config): """ Return list of models from all resources in config. """ resources = resources_of_config(config) models = [] for resource in resources: if not hasattr(resource, '__table__') and hasattr(resource, 'model'): models.append(resource.model) else: models.append(resource) return models
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Return list of models from all resources in config.
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python
train
rigetti/pyquil
pyquil/paulis.py
https://github.com/rigetti/pyquil/blob/ec98e453084b0037d69d8c3245f6822a5422593d/pyquil/paulis.py#L159-L173
def copy(self): """ Properly creates a new PauliTerm, with a completely new dictionary of operators """ new_term = PauliTerm("I", 0, 1.0) # create new object # manually copy all attributes over for key in self.__dict__.keys(): val = self.__dict__[key] if isinstance(val, (dict, list, set)): # mutable types new_term.__dict__[key] = copy.copy(val) else: # immutable types new_term.__dict__[key] = val return new_term
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Properly creates a new PauliTerm, with a completely new dictionary of operators
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python
train
googleapis/oauth2client
oauth2client/contrib/appengine.py
https://github.com/googleapis/oauth2client/blob/50d20532a748f18e53f7d24ccbe6647132c979a9/oauth2client/contrib/appengine.py#L892-L910
def oauth2decorator_from_clientsecrets(filename, scope, message=None, cache=None): """Creates an OAuth2Decorator populated from a clientsecrets file. Args: filename: string, File name of client secrets. scope: string or list of strings, scope(s) of the credentials being requested. message: string, A friendly string to display to the user if the clientsecrets file is missing or invalid. The message may contain HTML and will be presented on the web interface for any method that uses the decorator. cache: An optional cache service client that implements get() and set() methods. See clientsecrets.loadfile() for details. Returns: An OAuth2Decorator """ return OAuth2DecoratorFromClientSecrets(filename, scope, message=message, cache=cache)
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Creates an OAuth2Decorator populated from a clientsecrets file. Args: filename: string, File name of client secrets. scope: string or list of strings, scope(s) of the credentials being requested. message: string, A friendly string to display to the user if the clientsecrets file is missing or invalid. The message may contain HTML and will be presented on the web interface for any method that uses the decorator. cache: An optional cache service client that implements get() and set() methods. See clientsecrets.loadfile() for details. Returns: An OAuth2Decorator
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python
valid
mikedh/trimesh
trimesh/primitives.py
https://github.com/mikedh/trimesh/blob/25e059bf6d4caa74f62ffd58ce4f61a90ee4e518/trimesh/primitives.py#L624-L636
def volume(self): """ The volume of the primitive extrusion. Calculated from polygon and height to avoid mesh creation. Returns ---------- volume: float, volume of 3D extrusion """ volume = abs(self.primitive.polygon.area * self.primitive.height) return volume
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The volume of the primitive extrusion. Calculated from polygon and height to avoid mesh creation. Returns ---------- volume: float, volume of 3D extrusion
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python
train
OSSOS/MOP
src/jjk/preproc/findTriplets.py
https://github.com/OSSOS/MOP/blob/94f91d32ad5ec081d5a1ebd67604a838003465af/src/jjk/preproc/findTriplets.py#L257-L312
def setDiscoveryTriples(win,table="discovery"): """Provide user with a list of triples that could be discovery triples""" win.help("Getting a list of pointings with triples from the CFEPS db") pointings=getPointingsWithTriples() win.help("Select the "+table+" triple form the list...") import time for pointing in pointings: header="%10s %10s %8s %10s %8s" % (pointing[1],'mjdate','Elongation','Filter', 'IQ') triples=getTriples(pointing=pointing[0]) choices=[] triplist=[] no_type=0 previous_list=[] for triple in triples: #win.help(str(triple)) tripinfo=getTripInfo(triple[0]) if not tripinfo[table]==None: previous_list.append(triple[0]) #if not abs(180-tripinfo['elongation'])< 20: # continue triplist.append(triple) if str(tripinfo['iq'])=='None': tripinfo['iq']=-1.0 obs_type=' ' if tripinfo['discovery']: obs_type='D' elif tripinfo['checkup']: obs_type='C' elif tripinfo['recovery']: obs_type='R' if obs_type==' ': no_type+=1 line=(obs_type,tripinfo['mjdate'], tripinfo['elongation'], tripinfo['filter'], tripinfo['iq'], tripinfo['block'] ) choices.append('%10s %10s %8.2f %10s %8.2f %8s' % line) if len(choices)==0 or no_type==0: continue #if len(previous_list)==1: # continue win.help("Choose a "+table+" triple (space) [no choice means skip] then press enter\n (q) to exit") choice=win.list(header,choices) if choice==None: win.help("Loading next triple") break ### Record which triplet is a discovery triplet if len(choice)!=1: win.help("Loading next triple\n") continue discovery_triple=triplist[choice[0]] for triple in previous_list: sql="DELETE FROM "+table+" WHERE triple=%s " cfeps.execute(sql,triple) sql="INSERT INTO "+table+" ( triple ) VALUES ( %s ) " cfeps.execute(sql,discovery_triple)
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Provide user with a list of triples that could be discovery triples
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python
train
spacetelescope/drizzlepac
drizzlepac/buildwcs.py
https://github.com/spacetelescope/drizzlepac/blob/15bec3c929a6a869d9e71b9398ced43ede0620f1/drizzlepac/buildwcs.py#L75-L219
def build(outname, wcsname, refimage, undistort=False, applycoeffs=False, coeffsfile=None, **wcspars): """ Core functionality to create a WCS instance from a reference image WCS, user supplied parameters or user adjusted reference WCS. The distortion information can either be read in as part of the reference image WCS or given in 'coeffsfile'. Parameters ---------- outname : string filename of output WCS wcsname : string WCSNAME ID for generated WCS refimage : string filename of image with source WCS used as basis for output WCS undistort : bool Create an undistorted WCS? applycoeffs : bool Apply coefficients from refimage to generate undistorted WCS? coeffsfile : string If specified, read distortion coeffs from separate file """ # Insure that the User WCS parameters have values for all the parameters, # even if that value is 'None' user_wcs_pars = convert_user_pars(wcspars) userwcs = wcspars['userwcs'] """ Use cases to document the logic required to interpret the parameters WCS generation based on refimage/userwcs parameters ------------------------------------------------------------- refimage == None, userwcs == False: *NO WCS specified* => print a WARNING message and return without doing anything refimage == None, userwcs == True: => Create WCS without a distortion model entirely from user parameters* refimage != None, userwcs == False: => No user WCS parameters specified => Simply use refimage WCS as specified refimage != None, userwcs == True: => Update refimage WCS with user specified values* Apply distortion and generate final headerlet using processed WCS ----------------------------------------------------------------- refimage == None, userwcs == True: *Output WCS generated entirely from user supplied parameters* Case 1: applycoeffs == False, undistort == True/False (ignored) => no distortion model to interpret => generate undistorted headerlet with no distortion model Case 2: applycoeffs == True/False, undistort == True => ignore any user specified distortion model => generate undistorted headerlet with no distortion model Case 3: applycoeffs == True, undistort == False => WCS from scratch combined with distortion model from another image => generate headerlet with distortion model refimage != None, userwcs == True/False: *Output WCS generated from reference image possibly modified by user parameters* Case 4: applycoeffs == False, undistort == True => If refimage has distortion, remove it => generate undistorted headerlet with no distortion model Case 5: applycoeffs == False, undistort == False => Leave refimage distortion model (if any) unmodified => generate a headerlet using same distortion model (if any) as refimage Case 6: applycoeffs == True, undistort == False => Update refimage with distortion model with user-specified model => generate a headerlet with a distortion model Case 7: applycoeffs == True, undistort == True => ignore user specified distortion model and undistort WCS => generate a headerlet without a distortion model """ ### Build WCS from refimage and/or user pars if util.is_blank(refimage) and not userwcs: print('WARNING: No WCS specified... No WCS created!') return customwcs = None if util.is_blank(refimage) and userwcs: # create HSTWCS object from user parameters complete_wcs = True for key in user_wcs_pars: if util.is_blank(user_wcs_pars[key]): complete_wcs = False break if complete_wcs: customwcs = wcs_functions.build_hstwcs(user_wcs_pars['crval1'],user_wcs_pars['crval2'], user_wcs_pars['crpix1'],user_wcs_pars['crpix2'], user_wcs_pars['naxis1'],user_wcs_pars['naxis2'], user_wcs_pars['pscale'],user_wcs_pars['orientat']) else: print('WARNING: Not enough WCS information provided by user!') raise ValueError if not util.is_blank(refimage): refwcs = stwcs.wcsutil.HSTWCS(refimage) else: refwcs = customwcs ### Apply distortion model (if any) to update WCS if applycoeffs and not util.is_blank(coeffsfile): if not util.is_blank(refimage): replace_model(refwcs, coeffsfile) else: if not undistort: add_model(refwcs,coeffsfile) # Only working with custom WCS from user, no distortion # so apply model to WCS, including modifying the CD matrix apply_model(refwcs) ### Create undistorted WCS, if requested if undistort: outwcs = undistortWCS(refwcs) else: outwcs = refwcs if userwcs: # replace (some/all?) WCS values from refimage with user WCS values # by running 'updatewcs' functions on input WCS outwcs = mergewcs(outwcs,customwcs,user_wcs_pars) ### Create the final headerlet and write it out, if specified if not util.is_blank(refimage): template = refimage elif not util.is_blank(coeffsfile): template = coeffsfile else: template = None # create default WCSNAME if None was given wcsname = create_WCSname(wcsname) print('Creating final headerlet with name ',wcsname,' using template ',template) outhdr = generate_headerlet(outwcs,template,wcsname,outname=outname) # synchronize this new WCS with the rest of the chips in the image for ext in outhdr: if 'extname' in ext.header and ext.header['extname'] == 'SIPWCS': ext_wcs = wcsutil.HSTWCS(ext) stwcs.updatewcs.makewcs.MakeWCS.updateWCS(ext_wcs,outwcs) return outwcs
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Core functionality to create a WCS instance from a reference image WCS, user supplied parameters or user adjusted reference WCS. The distortion information can either be read in as part of the reference image WCS or given in 'coeffsfile'. Parameters ---------- outname : string filename of output WCS wcsname : string WCSNAME ID for generated WCS refimage : string filename of image with source WCS used as basis for output WCS undistort : bool Create an undistorted WCS? applycoeffs : bool Apply coefficients from refimage to generate undistorted WCS? coeffsfile : string If specified, read distortion coeffs from separate file
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python
train
GoogleCloudPlatform/appengine-mapreduce
python/src/mapreduce/handlers.py
https://github.com/GoogleCloudPlatform/appengine-mapreduce/blob/2045eb3605b6ecb40c83d11dd5442a89fe5c5dd6/python/src/mapreduce/handlers.py#L1008-L1023
def _processing_limit(self, spec): """Get the limit on the number of map calls allowed by this slice. Args: spec: a Mapreduce spec. Returns: The limit as a positive int if specified by user. -1 otherwise. """ processing_rate = float(spec.mapper.params.get("processing_rate", 0)) slice_processing_limit = -1 if processing_rate > 0: slice_processing_limit = int(math.ceil( parameters.config._SLICE_DURATION_SEC*processing_rate/ int(spec.mapper.shard_count))) return slice_processing_limit
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Get the limit on the number of map calls allowed by this slice. Args: spec: a Mapreduce spec. Returns: The limit as a positive int if specified by user. -1 otherwise.
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python
train
chemlab/chemlab
chemlab/io/handlers/gamess.py
https://github.com/chemlab/chemlab/blob/c8730966316d101e24f39ac3b96b51282aba0abe/chemlab/io/handlers/gamess.py#L107-L139
def _parse_tddft(self): """Parse the output resulted from a tddft calculation. """ text = self.text energies = sections("SUMMARY OF TDDFT RESULTS", "DONE WITH TD-DFT EXCITATION ENERGIES", text) lines = energies[0].splitlines() regex = re.compile(""" \s+(\d+) # State Number \s+([ ^]+) # State sym \s+([+-]?\d+\.\d+) # Tot Energy \s+([+-]?\d+\.\d+) # Exc Energy (\s+([+-]?\d+\.\d+) # \s+([+-]?\d+\.\d+) # Dipole moment \s+([+-]?\d+\.\d+) # \s+([+-]?\d+\.\d+))? # Oscillator strength """, flags=re.VERBOSE) states = [] for line in lines: match = regex.match(line) if match: # Check for strange behaviour of symmetry if not re.match("\w+",match.group(4)): raise ValueError("Strange symmetry string: %s"%match.group(4)) osc_strength = float(match.group(9)) if match.group(9) else 0.000 states.append({"num": int(match.group(1)), "sym": match.group(4), "strength": osc_strength}) return {"states": states}
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Parse the output resulted from a tddft calculation.
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python
train
theonion/djes
djes/utils/query.py
https://github.com/theonion/djes/blob/8f7347382c74172e82e959e3dfbc12b18fbb523f/djes/utils/query.py#L4-L29
def batched_queryset(queryset, chunksize=1000): ''''' Iterate over a Django Queryset ordered by the primary key This method loads a maximum of chunksize (default: 1000) rows in it's memory at the same time while django normally would load all rows in it's memory. Using the iterator() method only causes it to not preload all the classes. Note that the implementation of the iterator does not support ordered query sets. Source: https://djangosnippets.org/snippets/1949/ ''' try: last_pk = queryset.order_by('-pk')[0].pk except IndexError: # Support empty querysets return queryset = queryset.order_by('pk') pk = 0 while pk < last_pk: for row in queryset.filter(pk__gt=pk)[:chunksize]: pk = row.pk yield row gc.collect()
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Iterate over a Django Queryset ordered by the primary key This method loads a maximum of chunksize (default: 1000) rows in it's memory at the same time while django normally would load all rows in it's memory. Using the iterator() method only causes it to not preload all the classes. Note that the implementation of the iterator does not support ordered query sets. Source: https://djangosnippets.org/snippets/1949/
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python
train
pypa/pipenv
pipenv/vendor/pathlib2/__init__.py
https://github.com/pypa/pipenv/blob/cae8d76c210b9777e90aab76e9c4b0e53bb19cde/pipenv/vendor/pathlib2/__init__.py#L1544-L1554
def exists(self): """ Whether this path exists. """ try: self.stat() except OSError as e: if e.errno not in (ENOENT, ENOTDIR): raise return False return True
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Whether this path exists.
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python
train
theislab/scanpy
scanpy/utils.py
https://github.com/theislab/scanpy/blob/9e4e5ee02e04cf618872d9b098e24f0542e8b227/scanpy/utils.py#L591-L608
def moving_average(a, n): """Moving average over one-dimensional array. Parameters ---------- a : np.ndarray One-dimensional array. n : int Number of entries to average over. n=2 means averaging over the currrent the previous entry. Returns ------- An array view storing the moving average. """ ret = np.cumsum(a, dtype=float) ret[n:] = ret[n:] - ret[:-n] return ret[n - 1:] / n
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Moving average over one-dimensional array. Parameters ---------- a : np.ndarray One-dimensional array. n : int Number of entries to average over. n=2 means averaging over the currrent the previous entry. Returns ------- An array view storing the moving average.
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python
train
Dispersive-Hydrodynamics-Lab/PACE
PACE/PACE.py
https://github.com/Dispersive-Hydrodynamics-Lab/PACE/blob/4ce27d5fc9b02cc2ce55f6fea7fc8d6015317e1f/PACE/PACE.py#L191-L203
def plot_traindata(self, name: str='dataplot') -> None: """ Plots traindata.... choo choo... """ traindata = self.get_traindata() plt.figure(figsize=(16, 16)) plt.scatter(traindata[:, 1], traindata[:, 2], c=traindata[:, 5], marker='o', label='Datastore Points') plt.xlabel(r'$\log_{10}$ Noise') plt.ylabel(r'$\log_{10}$ Curvature') plt.legend(loc=2, fontsize='xx-large') plt.savefig('./img/{}.png'.format(name))
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Plots traindata.... choo choo...
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python
train
tanghaibao/goatools
goatools/go_enrichment.py
https://github.com/tanghaibao/goatools/blob/407682e573a108864a79031f8ca19ee3bf377626/goatools/go_enrichment.py#L482-L486
def prt_tsv(self, prt, goea_results, **kws): """Write tab-separated table data""" prt_flds = kws.get('prt_flds', self.get_prtflds_default(goea_results)) tsv_data = MgrNtGOEAs(goea_results).get_goea_nts_prt(prt_flds, **kws) RPT.prt_tsv(prt, tsv_data, **kws)
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Write tab-separated table data
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python
train
project-rig/rig
rig/routing_table/ordered_covering.py
https://github.com/project-rig/rig/blob/3a3e053d3214899b6d68758685835de0afd5542b/rig/routing_table/ordered_covering.py#L553-L598
def _refine_upcheck(merge, min_goodness): """Remove from the merge any entries which would be covered by entries between their current position and the merge insertion position. For example, the third entry of:: 0011 -> N 0100 -> N 1000 -> N X000 -> NE Cannot be merged with the first two entries because that would generate the new entry ``XXXX`` which would move ``1000`` below the entry with the key-mask pair of ``X000``, which would cover it. Returns ------- :py:class:`~.Merge` New merge with entries possibly removed. If the goodness of the merge ever drops below `min_goodness` then an empty merge will be returned. bool If the merge has been changed at all. """ # Remove any entries which would be covered by entries above the merge # position. changed = False for i in sorted(merge.entries, reverse=True): # Get all the entries that are between the entry we're looking at the # insertion index of the proposed merged index. If this entry would be # covered up by any of them then we remove it from the merge. entry = merge.routing_table[i] key, mask = entry.key, entry.mask if any(intersect(key, mask, other.key, other.mask) for other in merge.routing_table[i+1:merge.insertion_index]): # The entry would be partially or wholly covered by another entry, # remove it from the merge and return a new merge. merge = _Merge(merge.routing_table, merge.entries - {i}) changed = True # Check if the merge is sufficiently good if merge.goodness <= min_goodness: merge = _Merge(merge.routing_table) # Replace with empty merge break # Return the final merge return merge, changed
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Remove from the merge any entries which would be covered by entries between their current position and the merge insertion position. For example, the third entry of:: 0011 -> N 0100 -> N 1000 -> N X000 -> NE Cannot be merged with the first two entries because that would generate the new entry ``XXXX`` which would move ``1000`` below the entry with the key-mask pair of ``X000``, which would cover it. Returns ------- :py:class:`~.Merge` New merge with entries possibly removed. If the goodness of the merge ever drops below `min_goodness` then an empty merge will be returned. bool If the merge has been changed at all.
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python
train
tnkteja/myhelp
virtualEnvironment/lib/python2.7/site-packages/pip/utils/__init__.py
https://github.com/tnkteja/myhelp/blob/fb3a4809d448ad14d5b2e6ddf2e7e89ad52b71cb/virtualEnvironment/lib/python2.7/site-packages/pip/utils/__init__.py#L102-L126
def find_command(cmd, paths=None, pathext=None): """Searches the PATH for the given command and returns its path""" if paths is None: paths = os.environ.get('PATH', '').split(os.pathsep) if isinstance(paths, six.string_types): paths = [paths] # check if there are funny path extensions for executables, e.g. Windows if pathext is None: pathext = get_pathext() pathext = [ext for ext in pathext.lower().split(os.pathsep) if len(ext)] # don't use extensions if the command ends with one of them if os.path.splitext(cmd)[1].lower() in pathext: pathext = [''] # check if we find the command on PATH for path in paths: # try without extension first cmd_path = os.path.join(path, cmd) for ext in pathext: # then including the extension cmd_path_ext = cmd_path + ext if os.path.isfile(cmd_path_ext): return cmd_path_ext if os.path.isfile(cmd_path): return cmd_path raise BadCommand('Cannot find command %r' % cmd)
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Searches the PATH for the given command and returns its path
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python
test
amcat/nlpipe
nlpipe/backend.py
https://github.com/amcat/nlpipe/blob/e9dcf0214d5dc6ba3900b8d7359909e1e33f1ce7/nlpipe/backend.py#L58-L66
def get_input_ids(query, limit=None): """Get the ids of existing input documents that match a query""" docs = scan(_es, index=esconfig.ES_INPUT_INDEX, doc_type=esconfig.ES_INPUT_DOCTYPE, query=query, size=(limit or 1000), fields="") for i, a in enumerate(docs): if limit and i >= limit: return yield a['_id']
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Get the ids of existing input documents that match a query
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python
train
tonyseek/html5lib-truncation
html5lib_truncation/utils.py
https://github.com/tonyseek/html5lib-truncation/blob/b5551e345e583d04dbdf6b97dc2a43a266eec8d6/html5lib_truncation/utils.py#L4-L29
def truncate_sentence(text, max_chars, break_words=False, padding=0): """Truncates a sentence. :param max_chars: The maximum characters of truncated sentence. :param break_words: If you wish to truncate given sentence strictly even if it breaks a word, set it to ``True``. It defaults to ``False`` which means truncating given sentence shorter but never breaking words. :param padding: The padding size for truncating. It is usually used to keep spaces for some ending characters such as ``"..."``. :return: The truncated sentence. """ if break_words: return text[:-abs(max_chars - len(text)) - padding] words = [] for word in text.split(): predicted_len = ( sum(map(len, words)) + # length of words len(word) + # length of next word len(words) - 1 + # length of spaces padding) if predicted_len >= max_chars: break words.append(word) return ' '.join(words)
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Truncates a sentence. :param max_chars: The maximum characters of truncated sentence. :param break_words: If you wish to truncate given sentence strictly even if it breaks a word, set it to ``True``. It defaults to ``False`` which means truncating given sentence shorter but never breaking words. :param padding: The padding size for truncating. It is usually used to keep spaces for some ending characters such as ``"..."``. :return: The truncated sentence.
[ "Truncates", "a", "sentence", "." ]
python
train
LonamiWebs/Telethon
telethon_examples/interactive_telegram_client.py
https://github.com/LonamiWebs/Telethon/blob/1ead9757d366b58c1e0567cddb0196e20f1a445f/telethon_examples/interactive_telegram_client.py#L26-L31
def print_title(title): """Helper function to print titles to the console more nicely""" sprint('\n') sprint('=={}=='.format('=' * len(title))) sprint('= {} ='.format(title)) sprint('=={}=='.format('=' * len(title)))
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Helper function to print titles to the console more nicely
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python
train
tensorflow/mesh
mesh_tensorflow/ops.py
https://github.com/tensorflow/mesh/blob/3921196e5e43302e820da0a87329f25d7e2a3016/mesh_tensorflow/ops.py#L4431-L4453
def pretty_print_counters(counters): """print counters hierarchically. Each counter is a pair of a string and a number. The string can have slashes, meaning that the number also counts towards each prefix. e.g. "parameters/trainable" counts towards both "parameters" and "parameters/trainable". Args: counters: a list of (string, number) pairs Returns: a string """ totals = collections.defaultdict(int) for (name, val) in counters: prefixes = [name[:i] for i in xrange(len(name)) if name[i] == "/"] + [name] for p in prefixes: totals[p] += val parts = [] for name, val in sorted(six.iteritems(totals)): parts.append(" " * name.count("/") + "%s: %.3g" % (name, val)) return "\n".join(parts)
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print counters hierarchically. Each counter is a pair of a string and a number. The string can have slashes, meaning that the number also counts towards each prefix. e.g. "parameters/trainable" counts towards both "parameters" and "parameters/trainable". Args: counters: a list of (string, number) pairs Returns: a string
[ "print", "counters", "hierarchically", "." ]
python
train
dantezhu/melon
melon/melon.py
https://github.com/dantezhu/melon/blob/44d859fa85fbfb2d77479e01eade925a0d26e4f7/melon/melon.py#L113-L126
def make_proc_name(self, subtitle): """ 获取进程名称 :param subtitle: :return: """ proc_name = '[%s:%s %s] %s' % ( constants.NAME, subtitle, self.name, ' '.join([sys.executable] + sys.argv) ) return proc_name
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获取进程名称 :param subtitle: :return:
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python
train
tensorflow/tensorboard
tensorboard/backend/event_processing/directory_watcher.py
https://github.com/tensorflow/tensorboard/blob/8e5f497b48e40f2a774f85416b8a35ac0693c35e/tensorboard/backend/event_processing/directory_watcher.py#L172-L192
def _SetPath(self, path): """Sets the current path to watch for new events. This also records the size of the old path, if any. If the size can't be found, an error is logged. Args: path: The full path of the file to watch. """ old_path = self._path if old_path and not io_wrapper.IsCloudPath(old_path): try: # We're done with the path, so store its size. size = tf.io.gfile.stat(old_path).length logger.debug('Setting latest size of %s to %d', old_path, size) self._finalized_sizes[old_path] = size except tf.errors.OpError as e: logger.error('Unable to get size of %s: %s', old_path, e) self._path = path self._loader = self._loader_factory(path)
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Sets the current path to watch for new events. This also records the size of the old path, if any. If the size can't be found, an error is logged. Args: path: The full path of the file to watch.
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python
train
xflr6/graphviz
graphviz/backend.py
https://github.com/xflr6/graphviz/blob/7376095ef1e47abad7e0b0361b6c9720b706e7a0/graphviz/backend.py#L139-L161
def run(cmd, input=None, capture_output=False, check=False, quiet=False, **kwargs): """Run the command described by cmd and return its (stdout, stderr) tuple.""" if input is not None: kwargs['stdin'] = subprocess.PIPE if capture_output: kwargs['stdout'] = kwargs['stderr'] = subprocess.PIPE try: proc = subprocess.Popen(cmd, startupinfo=get_startupinfo(), **kwargs) except OSError as e: if e.errno == errno.ENOENT: raise ExecutableNotFound(cmd) else: raise out, err = proc.communicate(input) if not quiet and err: stderr_write_bytes(err, flush=True) if check and proc.returncode: raise CalledProcessError(proc.returncode, cmd, output=out, stderr=err) return out, err
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Run the command described by cmd and return its (stdout, stderr) tuple.
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python
train
tkf/rash
rash/database.py
https://github.com/tkf/rash/blob/585da418ec37dd138f1a4277718b6f507e9536a2/rash/database.py#L129-L160
def connection(self, commit=False): """ Context manager to keep around DB connection. :rtype: sqlite3.Connection SOMEDAY: Get rid of this function. Keeping connection around as an argument to the method using this context manager is probably better as it is more explicit. Also, holding "global state" as instance attribute is bad for supporting threaded search, which is required for more fluent percol integration. """ if commit: self._need_commit = True if self._db: yield self._db else: try: with self._get_db() as db: self._db = db db.create_function("REGEXP", 2, sql_regexp_func) db.create_function("PROGRAM_NAME", 1, sql_program_name_func) db.create_function("PATHDIST", 2, sql_pathdist_func) yield self._db if self._need_commit: db.commit() finally: self._db = None self._need_commit = False
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Context manager to keep around DB connection. :rtype: sqlite3.Connection SOMEDAY: Get rid of this function. Keeping connection around as an argument to the method using this context manager is probably better as it is more explicit. Also, holding "global state" as instance attribute is bad for supporting threaded search, which is required for more fluent percol integration.
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python
train
flowersteam/explauto
explauto/sensorimotor_model/inverse/cma.py
https://github.com/flowersteam/explauto/blob/cf0f81ecb9f6412f7276a95bd27359000e1e26b6/explauto/sensorimotor_model/inverse/cma.py#L1137-L1167
def repair(self, x, copy_if_changed=True, copy_always=False): """sets out-of-bounds components of ``x`` on the bounds. """ # TODO (old data): CPU(N,lam,iter=20,200,100): 3.3s of 8s for two bounds, 1.8s of 6.5s for one bound # remark: np.max([bounds[0], x]) is about 40 times slower than max((bounds[0], x)) copy = copy_if_changed if copy_always: x = array(x, copy=True) bounds = self.bounds if bounds not in (None, [None, None], (None, None)): # solely for effiency x = array(x, copy=True) if copy and not copy_always else x if bounds[0] is not None: if isscalar(bounds[0]): for i in rglen(x): x[i] = max((bounds[0], x[i])) else: for i in rglen(x): j = min([i, len(bounds[0]) - 1]) if bounds[0][j] is not None: x[i] = max((bounds[0][j], x[i])) if bounds[1] is not None: if isscalar(bounds[1]): for i in rglen(x): x[i] = min((bounds[1], x[i])) else: for i in rglen(x): j = min((i, len(bounds[1]) - 1)) if bounds[1][j] is not None: x[i] = min((bounds[1][j], x[i])) return x
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sets out-of-bounds components of ``x`` on the bounds.
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python
train
a1ezzz/wasp-general
wasp_general/network/primitives.py
https://github.com/a1ezzz/wasp-general/blob/1029839d33eb663f8dec76c1c46754d53c1de4a9/wasp_general/network/primitives.py#L584-L597
def parse_socket_info(cls, info): """ Parse string that is formed like '[address]<:port>' and return corresponding :class:`.WIPV4ScketInfo` object :param info: string to parse :return: WIPV4ScketInfo """ info = info.split(':') if len(info) > 2: raise ValueError('Incorrect socket info specified') address = info[0].strip() port = int(info[1].strip()) if len(info) == 2 else None return WIPV4SocketInfo(address=address, port=port)
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Parse string that is formed like '[address]<:port>' and return corresponding :class:`.WIPV4ScketInfo` object :param info: string to parse :return: WIPV4ScketInfo
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python
train
chrisrink10/basilisp
src/basilisp/lang/compiler/generator.py
https://github.com/chrisrink10/basilisp/blob/3d82670ee218ec64eb066289c82766d14d18cc92/src/basilisp/lang/compiler/generator.py#L1928-L1937
def _maybe_class_to_py_ast(_: GeneratorContext, node: MaybeClass) -> GeneratedPyAST: """Generate a Python AST node for accessing a potential Python module variable name.""" assert node.op == NodeOp.MAYBE_CLASS return GeneratedPyAST( node=ast.Name( id=Maybe(_MODULE_ALIASES.get(node.class_)).or_else_get(node.class_), ctx=ast.Load(), ) )
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Generate a Python AST node for accessing a potential Python module variable name.
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python
test
mbakker7/timml
timml/linesink.py
https://github.com/mbakker7/timml/blob/91e99ad573cb8a9ad8ac1fa041c3ca44520c2390/timml/linesink.py#L715-L736
def potinf(self, x, y, aq=None): ''' linesink 0, order 0, layer[0] order 0, layer[1] ... order 1, layer[0] order 1, layer[1] ... linesink 1, order 0, layer[0] order 0, layer[1] ... order 1, layer[0] order 1, layer[1] ... ''' if aq is None: aq = self.model.aq.find_aquifer_data(x, y) rv = np.zeros((self.nls, self.lslist[0].nparam, aq.naq)) if aq in self.aq: for i, ls in enumerate(self.lslist): rv[i] = ls.potinf(x, y, aq) rv.shape = (self.nparam, aq.naq) return rv
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python
train
Spinmob/spinmob
_data.py
https://github.com/Spinmob/spinmob/blob/f037f5df07f194bcd4a01f4d9916e57b9e8fb45a/_data.py#L948-L1018
def is_same_as(self, other_databox, headers=True, columns=True, header_order=True, column_order=True, ckeys=True): """ Tests that the important (i.e. savable) information in this databox is the same as that of the other_databox. Parameters ---------- other_databox Databox with which to compare. headers=True Make sure all header elements match. columns=True Make sure every element of every column matches. header_order=True Whether the order of the header elements must match. column_order=True Whether the order of the columns must match. This is only a sensible concern if ckeys=True. ckeys=True Whether the actual ckeys matter, or just the ordered columns of data. Note the == symbol runs this function with everything True. """ d = other_databox if not hasattr(other_databox, '_is_spinmob_databox'): return False # Proceed by testing things one at a time, returning false if one fails if headers: # Same number of elements if not len(self.hkeys) == len(d.hkeys): return False # Elements if header_order and not self.hkeys == d.hkeys: return False # Each value for k in self.hkeys: # Make sure the key exists if not k in d.hkeys: return False # Make sure it's the same. if not self.h(k) == d.h(k): return False if columns: # Same number of columns if not len(self.ckeys) == len(d.ckeys): return False # If we're checking columns by ckeys if ckeys: # Columns if column_order and not self.ckeys == d.ckeys: return False # Each value of each array for k in self.ckeys: # Make sure the key exists if not k in d.ckeys: return False # Check the values if not (_n.array(self[k]) == _n.array(d[k])).all(): return False # Otherwise we're ignoring ckeys else: for n in range(len(self.ckeys)): if not (_n.array(self[n]) == _n.array(d[n])).all(): return False # Passes all tests return True
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Tests that the important (i.e. savable) information in this databox is the same as that of the other_databox. Parameters ---------- other_databox Databox with which to compare. headers=True Make sure all header elements match. columns=True Make sure every element of every column matches. header_order=True Whether the order of the header elements must match. column_order=True Whether the order of the columns must match. This is only a sensible concern if ckeys=True. ckeys=True Whether the actual ckeys matter, or just the ordered columns of data. Note the == symbol runs this function with everything True.
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python
train
saltstack/salt
salt/config/__init__.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/config/__init__.py#L4224-L4251
def apply_spm_config(overrides, defaults): ''' Returns the spm configurations dict. .. versionadded:: 2015.8.1 ''' opts = defaults.copy() _adjust_log_file_override(overrides, defaults['log_file']) if overrides: opts.update(overrides) # Prepend root_dir to other paths prepend_root_dirs = [ 'formula_path', 'pillar_path', 'reactor_path', 'spm_cache_dir', 'spm_build_dir' ] # These can be set to syslog, so, not actual paths on the system for config_key in ('spm_logfile',): log_setting = opts.get(config_key, '') if log_setting is None: continue if urlparse(log_setting).scheme == '': prepend_root_dirs.append(config_key) prepend_root_dir(opts, prepend_root_dirs) return opts
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Returns the spm configurations dict. .. versionadded:: 2015.8.1
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python
train
guaix-ucm/pyemir
emirdrp/processing/wavecal/slitlet2d.py
https://github.com/guaix-ucm/pyemir/blob/fef6bbabcb13f80123cafd1800a0f508a3c21702/emirdrp/processing/wavecal/slitlet2d.py#L406-L431
def ximshow_unrectified(self, slitlet2d): """Display unrectified image with spectrails and frontiers. Parameters ---------- slitlet2d : numpy array Array containing the unrectified slitlet image. """ title = "Slitlet#" + str(self.islitlet) ax = ximshow(slitlet2d, title=title, first_pixel=(self.bb_nc1_orig, self.bb_ns1_orig), show=False) xdum = np.linspace(1, EMIR_NAXIS1, num=EMIR_NAXIS1) ylower = self.list_spectrails[0](xdum) ax.plot(xdum, ylower, 'b-') ymiddle = self.list_spectrails[1](xdum) ax.plot(xdum, ymiddle, 'b--') yupper = self.list_spectrails[2](xdum) ax.plot(xdum, yupper, 'b-') ylower_frontier = self.list_frontiers[0](xdum) ax.plot(xdum, ylower_frontier, 'b:') yupper_frontier = self.list_frontiers[1](xdum) ax.plot(xdum, yupper_frontier, 'b:') pause_debugplot(debugplot=self.debugplot, pltshow=True)
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Display unrectified image with spectrails and frontiers. Parameters ---------- slitlet2d : numpy array Array containing the unrectified slitlet image.
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python
train
AtteqCom/zsl
src/zsl/interface/task_queue.py
https://github.com/AtteqCom/zsl/blob/ab51a96da1780ff642912396d4b85bdcb72560c1/src/zsl/interface/task_queue.py#L28-L52
def execute_job(job, app=Injected, task_router=Injected): # type: (Job, Zsl, TaskRouter) -> dict """Execute a job. :param job: job to execute :type job: Job :param app: service application instance, injected :type app: ServiceApplication :param task_router: task router instance, injected :type task_router: TaskRouter :return: task result :rtype: dict """ app.logger.info("Job fetched, preparing the task '{0}'.".format(job.path)) task, task_callable = task_router.route(job.path) jc = JobContext(job, task, task_callable) app.logger.info("Executing task.") result = jc.task_callable(jc.task_data) app.logger.info("Task {0} executed successfully.".format(job.path)) return {'task_name': job.path, 'data': result}
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Execute a job. :param job: job to execute :type job: Job :param app: service application instance, injected :type app: ServiceApplication :param task_router: task router instance, injected :type task_router: TaskRouter :return: task result :rtype: dict
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python
train
jquast/wcwidth
bin/wcwidth-libc-comparator.py
https://github.com/jquast/wcwidth/blob/78800b68911880ef4ef95ae83886154710441871/bin/wcwidth-libc-comparator.py#L44-L63
def report_ucs_msg(ucs, wcwidth_libc, wcwidth_local): """ Return string report of combining character differences. :param ucs: unicode point. :type ucs: unicode :param wcwidth_libc: libc-wcwidth's reported character length. :type comb_py: int :param wcwidth_local: wcwidth's reported character length. :type comb_wc: int :rtype: unicode """ ucp = (ucs.encode('unicode_escape')[2:] .decode('ascii') .upper() .lstrip('0')) url = "http://codepoints.net/U+{}".format(ucp) name = unicodedata.name(ucs) return (u"libc,ours={},{} [--o{}o--] name={} val={} {}" " ".format(wcwidth_libc, wcwidth_local, ucs, name, ord(ucs), url))
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Return string report of combining character differences. :param ucs: unicode point. :type ucs: unicode :param wcwidth_libc: libc-wcwidth's reported character length. :type comb_py: int :param wcwidth_local: wcwidth's reported character length. :type comb_wc: int :rtype: unicode
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python
train
jgillick/LendingClub
lendingclub/session.py
https://github.com/jgillick/LendingClub/blob/4495f99fd869810f39c00e02b0f4112c6b210384/lendingclub/session.py#L73-L85
def __continue_session(self): """ Check if the time since the last HTTP request is under the session timeout limit. If it's been too long since the last request attempt to authenticate again. """ now = time.time() diff = abs(now - self.last_request_time) timeout_sec = self.session_timeout * 60 # convert minutes to seconds if diff >= timeout_sec: self.__log('Session timed out, attempting to authenticate') self.authenticate()
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Check if the time since the last HTTP request is under the session timeout limit. If it's been too long since the last request attempt to authenticate again.
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python
train
dariusbakunas/rawdisk
rawdisk/util/rawstruct.py
https://github.com/dariusbakunas/rawdisk/blob/1dc9d0b377fe5da3c406ccec4abc238c54167403/rawdisk/util/rawstruct.py#L195-L204
def get_string(self, offset, length): """Returns string (length bytes) Args: offset (int): sring offset in byte array length (int): string length """ return struct.unpack(str(length) + "s", self.data[ offset:offset + length ])[0]
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Returns string (length bytes) Args: offset (int): sring offset in byte array length (int): string length
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python
train
NASA-AMMOS/AIT-Core
ait/core/server/client.py
https://github.com/NASA-AMMOS/AIT-Core/blob/9d85bd9c738e7a6a6fbdff672bea708238b02a3a/ait/core/server/client.py#L34-L39
def publish(self, msg): """ Publishes input message with client name as topic. """ self.pub.send("{} {}".format(self.name, msg)) log.debug('Published message from {}'.format(self))
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Publishes input message with client name as topic.
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python
train
fracpete/python-weka-wrapper3
python/weka/core/classes.py
https://github.com/fracpete/python-weka-wrapper3/blob/d850ab1bdb25fbd5a8d86e99f34a397975425838/python/weka/core/classes.py#L843-L852
def component_type(self): """ Returns the classname of the elements. :return: the class of the elements :rtype: str """ cls = javabridge.call(self.jobject, "getClass", "()Ljava/lang/Class;") comptype = javabridge.call(cls, "getComponentType", "()Ljava/lang/Class;") return javabridge.call(comptype, "getName", "()Ljava/lang/String;")
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Returns the classname of the elements. :return: the class of the elements :rtype: str
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python
train
lago-project/lago
lago/plugins/vm.py
https://github.com/lago-project/lago/blob/5b8970f7687e063e4619066d5b8093ca997678c9/lago/plugins/vm.py#L476-L492
def export_disks( self, standalone=True, dst_dir=None, compress=False, collect_only=False, with_threads=True, *args, **kwargs ): """ Thin method that just uses the provider """ return self.provider.export_disks( standalone, dst_dir, compress, collect_only, with_threads, *args, **kwargs )
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Thin method that just uses the provider
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python
train
pyviz/holoviews
holoviews/core/dimension.py
https://github.com/pyviz/holoviews/blob/ae0dd2f3de448b0ca5e9065aabd6ef8d84c7e655/holoviews/core/dimension.py#L1370-L1385
def _deduplicate_items(cls, items): "Deduplicates assigned paths by incrementing numbering" counter = Counter([path[:i] for path, _ in items for i in range(1, len(path)+1)]) if sum(counter.values()) == len(counter): return items new_items = [] counts = defaultdict(lambda: 0) for i, (path, item) in enumerate(items): if counter[path] > 1: path = path + (util.int_to_roman(counts[path]+1),) elif counts[path]: path = path[:-1] + (util.int_to_roman(counts[path]+1),) new_items.append((path, item)) counts[path] += 1 return new_items
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Deduplicates assigned paths by incrementing numbering
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python
train