Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import unittest import paddle from paddle import fluid from paddle.distributed import fleet from paddle.distributed.fleet.base import role_maker paddle.enable_static() class TestFleetLambMetaOptimizer(unittest.TestCase): def setUp(self): os.environ["PADDLE_TRAINER_ID"] = "1" os.environ[ "PADDLE_TRAINER_ENDPOINTS" ] = "127.0.0.1:36001,127.0.0.1:36002" def net(self, main_prog, startup_prog): with fluid.program_guard(main_prog, startup_prog): with fluid.unique_name.guard(): input_x = paddle.static.data( name="x", shape=[-1, 32], dtype='float32' ) input_y = paddle.static.data( name="y", shape=[-1, 1], dtype='int64' ) fc_1 = paddle.static.nn.fc( x=input_x, size=64, activation='tanh' ) fc_2 = paddle.static.nn.fc(x=fc_1, size=256, activation='tanh') prediction = paddle.static.nn.fc( x=[fc_2], size=2, activation='softmax' ) cost = paddle.nn.functional.cross_entropy( input=prediction, label=input_y, reduction='none', use_softmax=False, ) avg_cost = paddle.mean(x=cost) strategy = paddle.distributed.fleet.DistributedStrategy() strategy.lamb = True strategy.lamb_configs = { 'lamb_weight_decay': 0.01, 'exclude_from_weight_decay': [], } return avg_cost, strategy def test_lamb_optimizer(self): role = role_maker.PaddleCloudRoleMaker(is_collective=True) fleet.init(role) startup_prog = fluid.Program() train_prog = fluid.Program() avg_cost, strategy = self.net(train_prog, startup_prog) optimizer = paddle.fluid.optimizer.Adam(learning_rate=0.01) optimizer = fleet.distributed_optimizer(optimizer, strategy=strategy) optimizer.minimize(avg_cost) ops = [op.type for op in avg_cost.block.ops] self.assertIn('lamb', ops) def test_lamb_not_apply_with_momentum(self): role = role_maker.PaddleCloudRoleMaker(is_collective=True) fleet.init(role) startup_prog = fluid.Program() train_prog = fluid.Program() avg_cost, strategy = self.net(train_prog, startup_prog) optimizer = paddle.fluid.optimizer.Momentum( learning_rate=0.1, momentum=0.9 ) optimizer = fleet.distributed_optimizer(optimizer, strategy=strategy) optimizer.minimize(avg_cost) ops = [op.type for op in avg_cost.block.ops] self.assertNotIn('lamb', ops) def test_lamb_exclude_fn(self): role = role_maker.PaddleCloudRoleMaker(is_collective=True) fleet.init(role) startup_prog = fluid.Program() train_prog = fluid.Program() avg_cost, strategy = self.net(train_prog, startup_prog) optimizer = paddle.fluid.optimizer.Adam(learning_rate=0.01) strategy.lamb_configs = { 'lamb_weight_decay': 0.01, 'exclude_from_weight_decay': ['.b_0'], } optimizer = fleet.distributed_optimizer(optimizer, strategy=strategy) optimizer.minimize(avg_cost) ops_without_wd = [ op for op in avg_cost.block.ops if op.type == 'lamb' and op.attr('op_role_var')[0].endswith('.b_0') ] for op in ops_without_wd: self.assertEqual(op.attr('weight_decay'), 0) def test_lamb_apply_with_amp(self): role = role_maker.PaddleCloudRoleMaker(is_collective=True) fleet.init(role) input_x = paddle.static.data(name="x", shape=[-1, 32], dtype='float32') input_y = paddle.static.data(name="y", shape=[-1, 1], dtype='int64') fc_1 = paddle.static.nn.fc(x=input_x, size=64, activation='tanh') fc_2 = paddle.static.nn.fc(x=fc_1, size=64, activation='tanh') prediction = paddle.static.nn.fc(x=[fc_2], size=2, activation='softmax') cost = paddle.nn.functional.cross_entropy( input=prediction, label=input_y, reduction='none', use_softmax=False ) avg_cost = paddle.mean(x=cost) strategy = paddle.distributed.fleet.DistributedStrategy() strategy.amp = True strategy.amp_configs = { "init_loss_scaling": 32768, "decr_every_n_nan_or_inf": 2, "incr_every_n_steps": 1000, "incr_ratio": 2.0, "use_dynamic_loss_scaling": True, "decr_ratio": 0.5, "custom_white_list": ['softmax'], "custom_black_list": ['tanh'], } strategy.lamb = True strategy.lamb_configs = { 'lamb_weight_decay': 0.01, 'exclude_from_weight_decay': [], } optimizer = paddle.fluid.optimizer.Adam(learning_rate=0.01) optimizer = fleet.distributed_optimizer(optimizer, strategy=strategy) optimizer.minimize(avg_cost) ops = [op.type for op in avg_cost.block.ops] self.assertIn('lamb', ops) self.assertIn('cast', ops) self.assertIn('check_finite_and_unscale', ops) if __name__ == "__main__": unittest.main()

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import bisect class Solution: # @param {integer[][]} matrix # @param {integer} target # @return {boolean} def searchMatrix(self, matrix, target): row = bisect.bisect_left([r[0] for r in matrix], target) if row == len(matrix): row = row - 1 else: if matrix[row][0] == target: return True else: row = row - 1 col = bisect.bisect_left(matrix[row], target) if col == len(matrix[0]): return False else: return matrix[row][col] == target

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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from azure.identity import DefaultAzureCredential from azure.mgmt.avs import AVSClient """ # PREREQUISITES pip install azure-identity pip install azure-mgmt-avs # USAGE python workload_networks_list_virtual_machines.py Before run the sample, please set the values of the client ID, tenant ID and client secret of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET. For more info about how to get the value, please see: https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal """ def main(): client = AVSClient( credential=DefaultAzureCredential(), subscription_id="00000000-0000-0000-0000-000000000000", ) response = client.workload_networks.list_virtual_machines( resource_group_name="group1", private_cloud_name="cloud1", ) for item in response: print(item) # x-ms-original-file: specification/vmware/resource-manager/Microsoft.AVS/stable/2022-05-01/examples/WorkloadNetworks_ListVirtualMachines.json if __name__ == "__main__": main()

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from typing import List import ghidra.app.util.recognizer import java.lang class DmgRecognizer(object, ghidra.app.util.recognizer.Recognizer): def __init__(self): ... def equals(self, __a0: object) -> bool: ... def getClass(self) -> java.lang.Class: ... def getPriority(self) -> int: ... def hashCode(self) -> int: ... def notify(self) -> None: ... def notifyAll(self) -> None: ... def numberOfBytesRequired(self) -> int: ... def recognize(self, __a0: List[int]) -> unicode: ... def toString(self) -> unicode: ... @overload def wait(self) -> None: ... @overload def wait(self, __a0: long) -> None: ... @overload def wait(self, __a0: long, __a1: int) -> None: ... @property def priority(self) -> int: ...

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# Author: kk.Fang(fkfkbill@gmail.com) import re from .utils import judge_if_ddl def execute_rule(sql, db_model=None, **kwargs): if not judge_if_ddl(sql): return False if re.search('revoke\s+', sql, re.I): return True return False

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""" dev2 api schema 'dev2.baidu.com' api schema # noqa: E501 Generated by: https://openapi-generator.tech """ import sys import unittest import baiduads from baiduads.advancedsegmentbind.model.add_segment_bind_response_wrapper_body import AddSegmentBindResponseWrapperBody from baiduads.common.model.api_response_header import ApiResponseHeader globals()['AddSegmentBindResponseWrapperBody'] = AddSegmentBindResponseWrapperBody globals()['ApiResponseHeader'] = ApiResponseHeader from baiduads.advancedsegmentbind.model.add_segment_bind_response_wrapper import AddSegmentBindResponseWrapper class TestAddSegmentBindResponseWrapper(unittest.TestCase): """AddSegmentBindResponseWrapper unit test stubs""" def setUp(self): pass def tearDown(self): pass def testAddSegmentBindResponseWrapper(self): """Test AddSegmentBindResponseWrapper""" # FIXME: construct object with mandatory attributes with example values # model = AddSegmentBindResponseWrapper() # noqa: E501 pass if __name__ == '__main__': unittest.main()

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# _*_ encoding=utf-8 _*__*_ encoding=utf-8 _*_ # 元组 class A: _name = "A" @classmethod def printName(self): print(self._name) class B: _name = "B" class StartA(A, B): pass class StartB(B, A): pass print(StartA._name) print(StartB._name) StartA.printName() StartB.printName() print(A.__dict__) class B: _name = "B" class BSon(B): pass print(B.__dict__) print(BSon.__dict__) print(BSon.__weakref__ is B.__weakref__)

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# coding: utf-8 # Aluno: Misael Augusto # Matrícula: 117110525 # Problema: Já sei tocar essa música def sei_tocar_musica(musica, acordes): n = 0 for i in range(len(musica)): for j in range(len(acordes)): if musica[i] == acordes[j]: n += 1 break if n == len(musica): return True else: return False

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from rest_framework import serializers from .models import ( Note, Organization, UnitOfMeasure ) class NoteSerializer(serializers.ModelSerializer): class Meta: model = Note fields = "__all__" class OrganizationSerializer(serializers.ModelSerializer): class Meta: model = Organization fields = "__all__" class UnitOfMeasureSerializer(serializers.ModelSerializer): class Meta: model = UnitOfMeasure fields = ['symbol', 'verbose_name', 'scale_factor', 'unit_type'] class UnitOfMeasureSerializer(serializers.ModelSerializer): class Meta: model = UnitOfMeasure fields = [ 'symbol', 'verbose_name', 'scale_factor', 'unit_type' ] class UnitOfMeasureListSerializer(serializers.ModelSerializer): unit_type = serializers.SerializerMethodField() class Meta: model = UnitOfMeasure fields = [ 'symbol', 'verbose_name', 'scale_factor', 'unit_type' ] def get_unit_type(self, obj): return obj.get_unit_type_display()

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# [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://arxiv.org/abs/1409.1556) # dependency file: https://github.com/MorvanZhou/Computer-Vision/requirements.txt from tensorflow import keras from tensorflow.keras import layers from utils import load_mnist, save_model_structure, save_model_weights # get data (x_train, y_train), (x_test, y_test) = load_mnist() # define model # like LeNet with more layers and activations model = keras.Sequential([ layers.Conv2D(filters=8, kernel_size=3, strides=1, padding="same", input_shape=(28, 28, 1)), # [n, 28, 28, 8] layers.Conv2D(filters=8, kernel_size=3, strides=1, padding="same", input_shape=(28, 28, 1)), # [n, 28, 28, 8] layers.ReLU(), layers.MaxPool2D(pool_size=2, strides=2), # [n, 14, 14, 8] layers.Conv2D(16, 3, 1, "same"), # [n, 14, 14, 16] layers.Conv2D(16, 3, 1, "same"), # [n, 14, 14, 16] layers.ReLU(), layers.MaxPool2D(2, 2), # [n, 7, 7, 16] layers.Flatten(), # [n, 7*7*16] layers.Dense(32), # [n, 32] layers.ReLU(), layers.Dense(10) # [n, 32] ], name="VGG") # show model model.summary() save_model_structure(model) # define loss and optimizer loss = keras.losses.SparseCategoricalCrossentropy(from_logits=True) opt = keras.optimizers.Adam(0.001) accuracy = keras.metrics.SparseCategoricalAccuracy() model.compile(optimizer=opt, loss=loss, metrics=[accuracy]) # training and validation model.fit(x=x_train, y=y_train, batch_size=32, epochs=3, validation_data=(x_test, y_test)) # save model save_model_weights(model)

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# Generated by Django 2.2.9 on 2020-07-30 07:18 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('article', '0003_comment'), ] operations = [ migrations.AlterField( model_name='comment', name='article', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='comments', to='article.Article'), ), ]

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""" Create a function that takes a string and returns `True` or `False`, depending on whether the characters are in order or not. ### Examples is_in_order("abc") ➞ True is_in_order("edabit") ➞ False is_in_order("123") ➞ True is_in_order("xyzz") ➞ True ### Notes You don't have to handle empty strings. """ def is_in_order(txt): x = sorted(txt) x = "".join(x) print(x) return x == txt

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# Copyright (c) 2020. Adam Arthur Faizal from sys import copyright print("====== TEKNIK LOOPING ======\n") hewan = ["Kucing", "Kelinci", "Sapi", "Ular", "Burung"] print("Daftar hewan :", hewan) buah = ["Mangga", "Stroberi", "Pepaya", "Melon"] print("Daftar buah :", buah) # Enumerate print("--- Enumerate ---") for nomer, nama in enumerate(hewan): print(nomer + 1, ":", nama) # Zip print("--- Zip ---") for namahewan, namabuah in zip(hewan, buah): print(namahewan, ":", namabuah) # Jika diterapkan pada set dan dictionary # Set barang = {"TV", "Lemari", "Meja", "Kursi", "Kipas Angin"} print("Daftar barang :", barang) for namabarang in sorted(barang): print(namabarang) # Dictionary playlist = {"Linkin Park": "In The End", "Avenged Sevenfold": "So Far Away", "Maroon 5": "Payphone", "Slipknot": "Snuff", "Asking Alexandria": "Moving On"} for band, lagu in enumerate(playlist.items()): print(band, "-", lagu) # Lain-lain print("--- Lain-lain ---") for i in reversed(range(1, 10, 1)): print(i) print('\n') print(copyright) # by Mbah Putih Mulyosugito

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import sys input = sys.stdin.readline def main(): H, W, K = map(int, input().split()) cake = [[0]*W for _ in range(H)] sb = [] for y in range(H): s = input().strip() for x, c in enumerate(s): if c == "#": sb.append((y, x)) for i, (y, x) in enumerate(sb): cake[y][x] = i + 1 for i, s in enumerate(sb): i += 1 y = s[0] x0 = x1 = s[1] for x in range(s[1]-1, -1, -1): if cake[y][x] != 0: break cake[y][x] = i x0 = x for x in range(s[1]+1, W): if cake[y][x] != 0: break cake[y][x] = i x1 = x for y in range(s[0]-1, -1, -1): if cake[y][x0:x1+1].count(0) != x1-x0+1: break for x in range(x0, x1+1): cake[y][x] = i for y in range(s[0]+1, H): if cake[y][x0:x1+1].count(0) != x1-x0+1: break for x in range(x0, x1+1): cake[y][x] = i for c in cake: print(*c) if __name__ == '__main__': main()

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from ..exceptions import InvalidEmail from .partial import partial @partial def mail_validation(backend, details, is_new=False, *args, **kwargs): requires_validation = backend.REQUIRES_EMAIL_VALIDATION or \ backend.setting('FORCE_EMAIL_VALIDATION', False) send_validation = details.get('email') and \ (is_new or backend.setting('PASSWORDLESS', False)) if requires_validation and send_validation: data = backend.strategy.request_data() if 'verification_code' in data: backend.strategy.session_pop('email_validation_address') if not backend.strategy.validate_email(details['email'], data['verification_code']): raise InvalidEmail(backend) else: current_partial = kwargs.get('current_partial') backend.strategy.send_email_validation(backend, details['email'], current_partial.token) backend.strategy.session_set('email_validation_address', details['email']) return backend.strategy.redirect( backend.strategy.setting('EMAIL_VALIDATION_URL') )

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362169885@qq.com

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/tcga_encoder/analyses/old/tsne_from_z_space.py

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2021-01-13T04:50:42.643743

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from tcga_encoder.utils.helpers import * from tcga_encoder.data.data import * from tcga_encoder.definitions.tcga import * #from tcga_encoder.definitions.nn import * from tcga_encoder.definitions.locations import * #from tcga_encoder.algorithms import * import seaborn as sns from sklearn.manifold import TSNE, locally_linear_embedding def main( data_location, results_location ): data_path = os.path.join( HOME_DIR ,data_location ) #, "data.h5" ) results_path = os.path.join( HOME_DIR, results_location ) data_filename = os.path.join( data_path, "data.h5") fill_filename = os.path.join( results_path, "full_vae_fill.h5" ) tsne_dir = os.path.join( results_path, "tsne" ) check_and_mkdir(tsne_dir) print "HOME_DIR: ", HOME_DIR print "data_filename: ", data_filename print "fill_filename: ", fill_filename print "LOADING stores" data_store = pd.HDFStore( data_filename, "r" ) fill_store = pd.HDFStore( fill_filename, "r" ) Z_train = fill_store["/Z/TRAIN/Z/mu"] Z_val = fill_store["/Z/VAL/Z/mu"] tissue = data_store["/CLINICAL/TISSUE"] barcodes_train = Z_train.index.values tissue_train = data_store["/CLINICAL/TISSUE"].loc[barcodes_train] tissues = tissue_train.columns tissue_idx = np.argmax( tissue_train.values, 1 ) #pdb.set_trace() #class sklearn.manifold.TSNE(n_components=2, perplexity=30.0, early_exaggeration=4.0, learning_rate=1000.0, n_iter=1000, n_iter_without_progress=30, min_grad_norm=1e-07, metric='euclidean', init='random', verbose=0, random_state=None, method='barnes_hut', angle=0.5) print "Running TSNE" Z_normed = Z_train.values# - Z_train.values.mean(0) #Z_normed = Z_normed - Z_train.values.std(0) Z_normed = Z_normed[:,:100] perplexity=30 nbr = 2000 np.random.seed(1) I = np.random.permutation( len(Z_normed ))[:nbr] tsne = TSNE(n_components=3,verbose=1, learning_rate=1000, perplexity=perplexity, method='exact') #embedded,dummy = locally_linear_embedding(Z_normed[I,:], n_neighbors=10, n_components=4) n_components =5 w = np.random.randn( Z_normed.shape[1],n_components) embedded = np.dot( Z_normed[I,:], w ) #pdb.set_trace() np.savetxt( tsne_dir + "/z.csv", Z_normed[I,:], fmt='%.3f',delimiter=',') labels = [tissues[idx] for idx in tissue_idx[I]] np.savetxt( tsne_dir + "/labels.csv", labels, fmt='%s',delimiter=',') embedded = tsne.fit_transform( embedded ) print "DONE!" # z_2d = bh_sne(Z_n,perplexity=30) colors = "bgrkycmbgrkycmbgrkycmbgrkycmbgrkycmbgrkycmbgrkycmbgrkycmbgrkycm" markers = "ooooooosssssssvvvvvvvppppppphhhhhhhDDDDDDDooooooosssssssvvvvvvvppppppphhhhhhhDDDDDDD" pp.figure( figsize=(12,12)) for t_idx in range( len(tissues) ): ids = tissue_idx[I] == t_idx #'o', mec="r", mew="2",ms=30,fillstyle="none" if len(ids) >=10: pp.plot( embedded[ids,:][:10,0], embedded[ids,:][:10,1], markers[t_idx], mec=colors[t_idx], mew="2", ms=10, fillstyle="none", alpha=0.5 ) #pp.show() pp.savefig( tsne_dir + "/tsne_perplexity_%d.png"%(perplexity), format='png', dpi=300 ) #pdb.set_trace() if __name__ == "__main__": data_location = sys.argv[1] results_location = sys.argv[2] main( data_location, results_location )

[ "tmeeds@gmail.com" ]

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/kubernetes/client/models/v1alpha1_cluster_role_binding.py

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# coding: utf-8 """ Kubernetes No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) OpenAPI spec version: v1.6.5 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from pprint import pformat from six import iteritems import re class V1alpha1ClusterRoleBinding(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ def __init__(self, api_version=None, kind=None, metadata=None, role_ref=None, subjects=None): """ V1alpha1ClusterRoleBinding - a model defined in Swagger :param dict swaggerTypes: The key is attribute name and the value is attribute type. :param dict attributeMap: The key is attribute name and the value is json key in definition. """ self.swagger_types = { 'api_version': 'str', 'kind': 'str', 'metadata': 'V1ObjectMeta', 'role_ref': 'V1alpha1RoleRef', 'subjects': 'list[V1alpha1Subject]' } self.attribute_map = { 'api_version': 'apiVersion', 'kind': 'kind', 'metadata': 'metadata', 'role_ref': 'roleRef', 'subjects': 'subjects' } self._api_version = api_version self._kind = kind self._metadata = metadata self._role_ref = role_ref self._subjects = subjects @property def api_version(self): """ Gets the api_version of this V1alpha1ClusterRoleBinding. APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: http://releases.k8s.io/HEAD/docs/devel/api-conventions.md#resources :return: The api_version of this V1alpha1ClusterRoleBinding. :rtype: str """ return self._api_version @api_version.setter def api_version(self, api_version): """ Sets the api_version of this V1alpha1ClusterRoleBinding. APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: http://releases.k8s.io/HEAD/docs/devel/api-conventions.md#resources :param api_version: The api_version of this V1alpha1ClusterRoleBinding. :type: str """ self._api_version = api_version @property def kind(self): """ Gets the kind of this V1alpha1ClusterRoleBinding. Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: http://releases.k8s.io/HEAD/docs/devel/api-conventions.md#types-kinds :return: The kind of this V1alpha1ClusterRoleBinding. :rtype: str """ return self._kind @kind.setter def kind(self, kind): """ Sets the kind of this V1alpha1ClusterRoleBinding. Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: http://releases.k8s.io/HEAD/docs/devel/api-conventions.md#types-kinds :param kind: The kind of this V1alpha1ClusterRoleBinding. :type: str """ self._kind = kind @property def metadata(self): """ Gets the metadata of this V1alpha1ClusterRoleBinding. Standard object's metadata. :return: The metadata of this V1alpha1ClusterRoleBinding. :rtype: V1ObjectMeta """ return self._metadata @metadata.setter def metadata(self, metadata): """ Sets the metadata of this V1alpha1ClusterRoleBinding. Standard object's metadata. :param metadata: The metadata of this V1alpha1ClusterRoleBinding. :type: V1ObjectMeta """ self._metadata = metadata @property def role_ref(self): """ Gets the role_ref of this V1alpha1ClusterRoleBinding. RoleRef can only reference a ClusterRole in the global namespace. If the RoleRef cannot be resolved, the Authorizer must return an error. :return: The role_ref of this V1alpha1ClusterRoleBinding. :rtype: V1alpha1RoleRef """ return self._role_ref @role_ref.setter def role_ref(self, role_ref): """ Sets the role_ref of this V1alpha1ClusterRoleBinding. RoleRef can only reference a ClusterRole in the global namespace. If the RoleRef cannot be resolved, the Authorizer must return an error. :param role_ref: The role_ref of this V1alpha1ClusterRoleBinding. :type: V1alpha1RoleRef """ if role_ref is None: raise ValueError("Invalid value for `role_ref`, must not be `None`") self._role_ref = role_ref @property def subjects(self): """ Gets the subjects of this V1alpha1ClusterRoleBinding. Subjects holds references to the objects the role applies to. :return: The subjects of this V1alpha1ClusterRoleBinding. :rtype: list[V1alpha1Subject] """ return self._subjects @subjects.setter def subjects(self, subjects): """ Sets the subjects of this V1alpha1ClusterRoleBinding. Subjects holds references to the objects the role applies to. :param subjects: The subjects of this V1alpha1ClusterRoleBinding. :type: list[V1alpha1Subject] """ if subjects is None: raise ValueError("Invalid value for `subjects`, must not be `None`") self._subjects = subjects def to_dict(self): """ Returns the model properties as a dict """ result = {} for attr, _ in iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """ Returns the string representation of the model """ return pformat(self.to_dict()) def __repr__(self): """ For `print` and `pprint` """ return self.to_str() def __eq__(self, other): """ Returns true if both objects are equal """ if not isinstance(other, V1alpha1ClusterRoleBinding): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """ Returns true if both objects are not equal """ return not self == other

[ "mehdy@google.com" ]

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# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding model 'SparkScript' db.create_table('spark_sparkscript', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('data', self.gf('django.db.models.fields.TextField')(default='{"name": "", "parameters": [], "script": "", "hadoopProperties": [], "type": "python", "properties": [], "resources": [], "job_id": null}')), )) db.send_create_signal('spark', ['SparkScript']) def backwards(self, orm): # Deleting model 'SparkScript' db.delete_table('spark_sparkscript') models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'desktop.document': { 'Meta': {'object_name': 'Document'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'description': ('django.db.models.fields.TextField', [], {'default': "''"}), 'extra': ('django.db.models.fields.TextField', [], {'default': "''"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'last_modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'db_index': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.TextField', [], {'default': "''"}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'doc_owner'", 'to': "orm['auth.User']"}), 'tags': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['desktop.DocumentTag']", 'db_index': 'True', 'symmetrical': 'False'}), 'version': ('django.db.models.fields.SmallIntegerField', [], {'default': '1'}) }, 'desktop.documenttag': { 'Meta': {'object_name': 'DocumentTag'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']"}), 'tag': ('django.db.models.fields.SlugField', [], {'max_length': '50'}) }, 'spark.sparkscript': { 'Meta': {'object_name': 'SparkScript'}, 'data': ('django.db.models.fields.TextField', [], {'default': '\'{"name": "", "parameters": [], "script": "", "hadoopProperties": [], "type": "python", "properties": [], "resources": [], "job_id": null}\''}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}) } } complete_apps = ['spark']

[ "romain@cloudera.com" ]

romain@cloudera.com

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refs/heads/master

2021-11-19T18:45:09.157744

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# Copyright 2021 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for tfx.dsl.context_manager.""" import threading from typing import Dict, Any import tensorflow as tf from tfx.dsl.components.base import base_node from tfx.dsl.context_managers import context_manager class _FakeNode(base_node.BaseNode): @property def inputs(self) -> Dict[str, Any]: return {} @property def outputs(self) -> Dict[str, Any]: return {} @property def exec_properties(self) -> Dict[str, Any]: return {} class _FakeContext(context_manager.DslContext): pass class _FakeContextManager(context_manager.DslContextManager): def create_context(self) -> _FakeContext: return _FakeContext() def enter(self, context: _FakeContext) -> _FakeContext: return context class ContextManagerTest(tf.test.TestCase): def reset_registry(self) -> context_manager._DslContextRegistry: result = context_manager._registry = context_manager._DslContextRegistry() return result def testContext_ContextIdAttrFactory(self): # ID is in format <classname>:<num> where <num> is incremental # regardless of the depth of the contexts. self.reset_registry() with _FakeContextManager() as c1: self.assertEqual(c1.id, '_FakeContext:1') with _FakeContextManager() as c2: self.assertEqual(c2.id, '_FakeContext:2') with _FakeContextManager() as c3: self.assertEqual(c3.id, '_FakeContext:3') with _FakeContextManager() as c4: self.assertEqual(c4.id, '_FakeContext:4') # ID count is reset after registry reset. self.reset_registry() with _FakeContextManager() as c5: self.assertEqual(c5.id, '_FakeContext:1') def testContext_ParentAttrFactory(self): registry = self.reset_registry() bg = registry.background_context with _FakeContextManager() as c1: self.assertIs(c1.parent, bg) with _FakeContextManager() as c2: self.assertIs(c2.parent, c1) with _FakeContextManager() as c3: self.assertEqual(c3.parent, c2) with _FakeContextManager() as c4: self.assertIs(c4.parent, c1) def testContext_Ancestors(self): registry = self.reset_registry() bg = registry.background_context self.assertEqual(list(bg.ancestors), []) with _FakeContextManager() as c1: self.assertEqual(list(c1.ancestors), [bg]) with _FakeContextManager() as c2: self.assertEqual(list(c2.ancestors), [bg, c1]) with _FakeContextManager() as c3: self.assertEqual(list(c3.ancestors), [bg, c1, c2]) with _FakeContextManager() as c4: self.assertEqual(list(c4.ancestors), [bg, c1]) def testRegistry_AllContexts(self): registry = self.reset_registry() bg = registry.background_context self.assertEqual(registry.all_contexts, [bg]) with _FakeContextManager() as c1: self.assertEqual(registry.all_contexts, [bg, c1]) with _FakeContextManager() as c2: self.assertEqual(registry.all_contexts, [bg, c1, c2]) with _FakeContextManager() as c3: self.assertEqual(registry.all_contexts, [bg, c1, c2, c3]) with _FakeContextManager() as c4: self.assertEqual(registry.all_contexts, [bg, c1, c2, c3, c4]) def testRegistry_ActiveContexts(self): registry = self.reset_registry() bg = registry.background_context self.assertEqual(registry.active_contexts, [bg]) with _FakeContextManager() as c1: self.assertEqual(registry.active_contexts, [bg, c1]) with _FakeContextManager() as c2: self.assertEqual(registry.active_contexts, [bg, c1, c2]) with _FakeContextManager() as c3: self.assertEqual(registry.active_contexts, [bg, c1, c2, c3]) with _FakeContextManager() as c4: self.assertEqual(registry.active_contexts, [bg, c1, c4]) def testRegistry_NodeAndContextAssociations(self): registry = self.reset_registry() bg = registry.background_context n0 = _FakeNode() with _FakeContextManager() as c1: n1 = _FakeNode() with _FakeContextManager() as c2: n2 = _FakeNode() with _FakeContextManager() as c3: n3 = _FakeNode() with _FakeContextManager() as c4: n4 = _FakeNode() # Associated nodes for each context self.assertEqual(registry.get_nodes(bg), [n0, n1, n2, n3, n4]) self.assertEqual(registry.get_nodes(c1), [n1, n2, n3, n4]) self.assertEqual(registry.get_nodes(c2), [n2, n3]) self.assertEqual(registry.get_nodes(c3), [n3]) self.assertEqual(registry.get_nodes(c4), [n4]) # Convenient property for calling registry.get_nodes() self.assertEqual(bg.nodes, [n0, n1, n2, n3, n4]) self.assertEqual(c1.nodes, [n1, n2, n3, n4]) self.assertEqual(c2.nodes, [n2, n3]) self.assertEqual(c3.nodes, [n3]) self.assertEqual(c4.nodes, [n4]) # Associated contexts for each node self.assertEqual(registry.get_contexts(n0), [bg]) self.assertEqual(registry.get_contexts(n1), [bg, c1]) self.assertEqual(registry.get_contexts(n2), [bg, c1, c2]) self.assertEqual(registry.get_contexts(n3), [bg, c1, c2, c3]) self.assertEqual(registry.get_contexts(n4), [bg, c1, c4]) def testContextManager_EnterMultipleTimes(self): cm = _FakeContextManager() with cm as c1: pass with cm as c2: self.assertNotEqual(c1, c2) with cm as c3: self.assertNotEqual(c2, c3) def testContextManager_EnterReturnValue(self): class UltimateContextManager(_FakeContextManager): def enter(self, context: _FakeContext) -> int: return 42 with UltimateContextManager() as captured: self.assertEqual(captured, 42) def testRegistry_MultiThreads(self): num_threads = 2 b = threading.Barrier(num_threads) def test(): with _FakeContextManager() as c1: self.assertEqual(c1.id, '_FakeContext:1') b.wait() with _FakeContextManager() as c2: self.assertEqual(c2.id, '_FakeContext:2') self.assertEqual(c2.parent, c1) threads = [threading.Thread(target=test) for i in range(num_threads)] for thread in threads: thread.start() for thread in threads: thread.join() # Expects no unhandled exceptions. def testGetNodes(self): self.reset_registry() n0 = _FakeNode() with _FakeContextManager() as c1: n1 = _FakeNode() with _FakeContextManager() as c2: n2 = _FakeNode() with _FakeContextManager() as c3: n3 = _FakeNode() with _FakeContextManager() as c4: n4 = _FakeNode() with self.subTest('With argument'): self.assertEqual(context_manager.get_nodes(c1), [n1, n2, n3, n4]) self.assertEqual(context_manager.get_nodes(c2), [n2, n3]) self.assertEqual(context_manager.get_nodes(c3), [n3]) self.assertEqual(context_manager.get_nodes(c4), [n4]) with self.subTest('Without argument'): # get_nodes() without argument queries nodes for background context, # which works as a node registry self.assertEqual(context_manager.get_nodes(), [n0, n1, n2, n3, n4]) if __name__ == '__main__': tf.test.main()

[ "tensorflow-extended-nonhuman@googlegroups.com" ]

tensorflow-extended-nonhuman@googlegroups.com

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/codewars/Python/6 kyu/EqualSidesOfAnArray/find_even_index_test.py

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[]

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Adasumizox/ProgrammingChallenges

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from find_even_index import find_even_index import unittest from random import randint class TestFindEvenIndex(unittest.TestCase): def test(self): self.assertEqual(find_even_index([1,2,3,4,3,2,1]), 3, 'Basic test') self.assertEqual(find_even_index([1,100,50,-51,1,1]), 1, 'Basic test') self.assertEqual(find_even_index([1,2,3,4,5,6]), -1, 'Basic test') self.assertEqual(find_even_index([20,10,30,10,10,15,35]), 3, 'Basic test') self.assertEqual(find_even_index([20,10,-80,10,10,15,35]), 0, 'Basic test') self.assertEqual(find_even_index([10,-80,10,10,15,35,20]), 6, 'Basic test') self.assertEqual(find_even_index(range(1,100)),-1, 'Basic test') self.assertEqual(find_even_index([0,0,0,0,0]), 0, 'Basic test') self.assertEqual(find_even_index([-1,-2,-3,-4,-3,-2,-1]), 3, 'Basic test') self.assertEqual(find_even_index(range(-100,-1)), -1, 'Basic test') def test_rand(self): find_even_sol=lambda arr, l=0, r="null", i=0: (lambda r: -1 if i>=len(arr) else i if r==l else find_even_sol(arr, l+arr[i], r-(0 if i+1>=len(arr) else arr[i+1]), i+1))(r if r!="null" else sum(arr[1:])) contract=lambda arr: (lambda pos: arr[:pos]+[sum(arr[pos:])])(randint(0,len(arr)-1)) for _ in range(40): left=[randint(-20, 20) for qu in range(randint(10,20))] right=left[:] if randint(0,1): left[randint(0,len(left)-1)]+=randint(-20,20) left=sorted(contract(left), key=lambda a: randint(1,1000)) right=sorted(contract(right), key=lambda a: randint(1,1000)) arr=([]+left[:]+[randint(-20,20)]+right[:])[:] self.assertEqual(find_even_index(arr[:]), find_even_sol(arr), "It should work for random inputs too") if __name__ == '__main__': unittest.main()

[ "darkdan099@gmail.com" ]

darkdan099@gmail.com

645e0aebaab4b939d2f1eaa75c24879619c3c55e

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/buildbuild/api/tests/test_api_team_list_search.py

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wikibootup/buildbuild

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from django.test import TestCase from django.test.client import Client from teams.models import Team class TestAPITeamListSearch(TestCase): def setUp(self): self.test_string = "test_string" self.team_with_test_string = Team.objects.create_team( name="team_name_with_" + self.test_string, # prefix 'test_' is excluded in this test case # because of model validation ( max_length=30 on Team.name ) ) self.team_without_test_string = Team.objects.create_team( name="team_name_without_", # + self.test_string, ) self.client = Client() self.response = self.client.get("/api/teams/?search=" + self.test_string) def test_api_team_list_search_should_return_valid_result(self): self.assertContains(self.response, self.team_with_test_string.name) self.assertNotContains(self.response, self.team_without_test_string.name)

[ "dobestan@gmail.com" ]

dobestan@gmail.com

8542295dc0339d09a52885dcaa9e153216812568

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/mtraits/strait.py

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[]

no_license

micheles/papers

a5e7f2fa0cf305cd3f8face7c7ecc0db70ce7cc7

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refs/heads/master

2023-06-07T16:46:46.306040

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__version__ = '0.5.3' __all__ = ['__version__', 'include', 'MetaTOS'] import inspect import types import warnings class OverridingError(NameError): pass class OverridingWarning(Warning): pass class Super(object): # this is needed to fix a shortcoming of unbound super objects, # i.e. this is how the unbound version of super should work def __init__(self, thisclass): self.__thisclass__ = thisclass def __get__(self, obj, objcls): return super(self.__thisclass__, obj or objcls) def oldstyle(*bases): "Return True if there are no bases or all bases are old-style" return not bases or set(map(type, bases)) == set([types.ClassType]) class Namespace(dict): "A named dictionary containing the attribute of a class and its ancestors" @classmethod def from_cls(klass, cls): if oldstyle(cls): mro = inspect.getmro(cls) else: mro = cls.__mro__[:-1] # all except object dic = merge(subc.__dict__ for subc in reversed(mro)) return klass(cls.__name__, dic) def __init__(self, name, attrs): self.__name__ = name self.update(attrs) def merge(dicts): """Merge a sequence of dictionaries. In case of name clashes, the last dict in the sequence wins.""" dic = {} for d in dicts: dic.update(d) return dic class MetaTOS(type): "The metaclass of the Trait Object System" def __new__(mcl, name, bases, dic): if len(bases) > 1: raise TypeError( 'Multiple inheritance of bases %s is forbidden for TOS classes' % str(bases)) elif oldstyle(*bases): # converts into new-style bases += (object,) cls = mcl.__super.__new__(mcl, name, bases, dic) setattr(cls, '_%s__super' % name, Super(cls)) return cls MetaTOS._MetaTOS__super = Super(MetaTOS) def find_common_names(namespaces): "Perform n*(n-1)/2 namespace overlapping checks on a set of n namespaces" n = len(namespaces) if n <= 1: return names = map(set, namespaces) for i in range(0, n): for j in range(i+1, n): ci, cj = namespaces[i], namespaces[j] common = names[i] & names[j] if common: yield common, ci, cj def check_overridden(namespaces, exclude=frozenset(), raise_='error'): "Raise an OverridingError for common names not in the exclude set" for common, n1, n2 in find_common_names(namespaces): overridden = ', '.join(common - exclude) if overridden: msg = '%s overrides names in %s: {%s}' % ( n1.__name__, n2.__name__, overridden) if raise_ == 'error': raise OverridingError(msg) elif raise_ == 'warning': warnings.warn(msg, OverridingWarning, stacklevel=2) known_metas = set([MetaTOS]) def get_right_meta(metatos, bases): # there is only one base because of the single-inheritance constraint try: base = bases[0] except IndexError: base = object meta = type(base) if meta in (types.ClassType, type): # is a builtin meta return metatos elif any(issubclass(meta, m) for m in known_metas): return meta # meta is independent from all known_metas, make a new one with # __new__ method coming from MetaTOS newmeta = type( '_TOS' + meta.__name__, (meta,), dict(__new__=metatos.__new__)) setattr(newmeta, '_%s__super' % metatos.__name__, Super(newmeta)) known_metas.add(newmeta) return newmeta exclude_attrs = set('__doc__ __module__ __dict__ __weakref__'.split()) def new(metatos, name, bases, attrs, traits): # traits as in Squeak take the precedence over the base class # but they are overridden by attributes in the class namespaces = map(Namespace.from_cls, traits) check_overridden(namespaces, exclude=set(attrs) | exclude_attrs) meta = get_right_meta(metatos, bases) cls = meta(name, bases, merge(namespaces + [Namespace(name, attrs)])) cls.__traits__ = traits for t in traits: setattr(cls, '_%s__super' % t.__name__, Super(cls)) return cls def include(*traits, **kw): "Returns a class factory" metatos = kw.get('MetaTOS', MetaTOS) # other kw free for future extensions def makecls(name, bases, dic): return new(metatos, name, bases, dic, traits) makecls.__name__ = 'include_%s' % '_'.join(m.__name__ for m in traits) return makecls

[ "michele.simionato@gmail.com" ]

michele.simionato@gmail.com

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/8. String to Integer (atoi).py

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[]

no_license

dundunmao/LeetCode2019

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refs/heads/master

2020-09-16T16:46:50.482697

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class Solution: # @return an integer def myAtoi(self, str): str = str.strip() #去掉所有空格 if len(str) == 0: return 0 tmp = "" result = 0 i = 0 sign = 1 if str[0] == "-": #处理正负号 sign = -1 i = 1 if str[0] == "+": #处理正负号 i = 1 MAX_INT = 2147483647 MIN_INT = -2147483648 for i in range(i, len(str)): #把digit的取出来，遇到非digit的break if str[i].isdigit(): tmp += str[i] else: break if len(tmp) > 0: #计算长度 result = sign * int(tmp) if result > MAX_INT > 0: #处理溢出情况 return MAX_INT elif result < MIN_INT < 0: return MIN_INT else: return result # class Solution(object): # def myAtoi(self, str): # """ # :type str: str # :rtype: int # """ # if str == '' or str is None: # return 0 # str.strip() # i = 0 # while str[0] == '-' or str[0] == '+' or str[i] == '0' or not str[i].isdigit(): # if str[0] == '-' or str[0] == '+' or str[i] == '0': # i += 1 # if i > len(str)-1: # break # if i < len(str) and not str[i].isdigit(): # return 0 # # le = 0 # j = i # nums = 0 # while j < len(str): # if str[j].isdigit(): # le += 1 # j += 1 # else: # break # # for k in range(i, i + le): # nums += int(str[k]) * 10 ** (le - 1) # # print nums # le -= 1 # # if str[0] == '-': # return -nums # else: # return nums if __name__ == "__main__": # s = "12" s = "-3.14159" x = Solution() print(x.myAtoi(s))

[ "dundunmao@gmail.com" ]

dundunmao@gmail.com

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/python/array/1403_minimum_subsequence_in_non_increasing_order.py

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linshaoyong/leetcode

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class Solution(object): def minSubsequence(self, nums): """ :type nums: List[int] :rtype: List[int] """ half = sum(nums) // 2 snums = sorted(nums, reverse=True) s, k = 0, 0 for i, n in enumerate(snums): s += n k = i if s > half: break return snums[:k + 1] def test_min_subsequence(): s = Solution() assert [10, 9] == s.minSubsequence([4, 3, 10, 9, 8]) assert [7, 7, 6] == s.minSubsequence([4, 4, 7, 6, 7]) assert [6] == s.minSubsequence([6])

[ "linshaoyong@gmail.com" ]

linshaoyong@gmail.com

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/homework/utils/utils_hw4.py

8ad12f3734ea88def8ee88e8468fd773013a1718

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no_license

yqdch/MLDS-Note

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refs/heads/master

2021-09-22T01:20:03.243647

2018-09-04T15:32:14

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from torchvision import transforms transform = transforms.Compose([transforms.ToPILImage(mode='RGB'), transforms.Grayscale(1), transforms.Resize((84, 84)), transforms.ToTensor()]) # process the image.. def pre_process(x): return transform(x)

[ "tinyshine@yeah.net" ]

tinyshine@yeah.net

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/daemon/test.py

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mattvenn/energy-wristband

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refs/heads/master

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2017-03-23T10:31:52

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import unittest import time from diff import diff_energy import os sens=50 max_energy=3000 max_time=30 class Test_Diff(unittest.TestCase): def setUp(self): import logging logging.basicConfig(level=logging.INFO) self.d = diff_energy(logging, max_energy=max_energy, sens=sens, max_time=max_time) def test_convert(self): self.assertEqual(self.d.energy_to_div(max_energy),4) self.assertEqual(self.d.energy_to_div(max_energy/5),1) def test_convert_limits(self): self.assertEqual(self.d.energy_to_div(-2*max_energy),1) self.assertEqual(self.d.energy_to_div(2*max_energy),4) def test_no_history(self): self.assertEqual(self.d.get_last_valid(1),1) def test_time_too_long(self): now = time.time() self.d.hist = {"t": now - max_time - 1, "e": 100} self.assertEqual(self.d.get_last_valid(1),1) def test_large_change_up(self): now = time.time() self.d.hist = {"t": now - max_time / 2, "e": 100} self.assertEqual(self.d.get_last_valid(1500),100) def test_large_change_down(self): now = time.time() self.d.hist = {"t": now - max_time / 2, "e": 2000} self.assertEqual(self.d.get_last_valid(100),2000) def test_ignore_large_slow_change(self): e = 200 self.assertEqual(self.d.get_last_valid(e),e) time.sleep(1.0) e += sens self.assertEqual(self.d.get_last_valid(e),e) time.sleep(1.0) e += sens self.assertEqual(self.d.get_last_valid(e),e) time.sleep(1.0) e += sens self.assertEqual(self.d.get_last_valid(e),e) time.sleep(1.0) e += sens self.assertEqual(self.d.get_last_valid(e),e) def test_ignore_small_change(self): e = 200 self.assertEqual(self.d.get_last_valid(e),e) time.sleep(0.5) e += sens / 4 self.assertEqual(self.d.get_last_valid(e),e) time.sleep(0.5) e += sens / 4 self.assertEqual(self.d.get_last_valid(e),e) time.sleep(0.5) e += sens / 4 self.assertEqual(self.d.get_last_valid(e),e) def test_small_change_over_boundary(self): boundary = self.d.energy_per_div now = time.time() self.d.hist = {"t": now - 10, "e": boundary - 10} time.sleep(1) self.assertEqual(self.d.get_last_valid(boundary + 10),boundary + 10) def test_no_repetition(self): self.assertEqual(self.d.get_last_valid(200),200) time.sleep(1) self.assertEqual(self.d.get_last_valid(250),250) time.sleep(1) self.assertEqual(self.d.get_last_valid(3000),250) time.sleep(1) self.assertEqual(self.d.get_last_valid(2800),3000) if __name__ == '__main__': unittest.main()

[ "matt@mattvenn.net" ]

matt@mattvenn.net

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/pattern10.py

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[]

no_license

Neeraj-kaushik/coding_ninja

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2022-11-07T19:43:05.869574

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n=int(input()) i=1 while i<=n: p=1 j=n while j>=i: print(p,end="") j=j-1 p=p+1 print() i=i+1

[ "nkthecoder@gmail.com" ]

nkthecoder@gmail.com

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SECRET_KEY = "secret" DATABASES = {"default": {"ENGINE": "django.db.backends.sqlite3", "NAME": ":memory:"}} INSTALLED_APPS = ( "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sessions", "django.contrib.messages", "django.contrib.staticfiles", "helusers.apps.HelusersConfig", "helusers.apps.HelusersAdminConfig", "helsinki_gdpr", "tests", ) MIDDLEWARE = [ "django.middleware.security.SecurityMiddleware", "django.contrib.sessions.middleware.SessionMiddleware", "django.middleware.common.CommonMiddleware", "django.middleware.csrf.CsrfViewMiddleware", "django.contrib.auth.middleware.AuthenticationMiddleware", "django.contrib.messages.middleware.MessageMiddleware", "django.middleware.clickjacking.XFrameOptionsMiddleware", ] ROOT_URLCONF = "tests.urls" AUTH_USER_MODEL = "tests.User" GDPR_API_MODEL = "tests.Profile" GDPR_API_QUERY_SCOPE = "testprefix.gdprquery" GDPR_API_DELETE_SCOPE = "testprefix.gdprdelete" DEBUG = True USE_TZ = True OIDC_API_TOKEN_AUTH = { "AUDIENCE": "test_audience", "ISSUER": "https://test_issuer_1", "REQUIRE_API_SCOPE_FOR_AUTHENTICATION": False, "API_AUTHORIZATION_FIELD": "", "API_SCOPE_PREFIX": "", }

[ "juha.louhiranta@anders.fi" ]

juha.louhiranta@anders.fi

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/flask/flask_fundamentals/Dojo_Survey/server.py

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[]

no_license

IanAranha/Python2021

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d9769b8b387b77753b77f6efe3a9a270a1f158d3

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2021-04-10T22:27:10

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from flask import Flask, render_template, redirect, request app = Flask(__name__) @app.route("/") def index(): return render_template("index.html") @app.route("/users", methods={"POST"}) def results(): return render_template("result.html") @app.route("/back", methods=["post"]) def back(): return redirect("/") @app.route("/danger") def danger(): print('A user tried to visit /danger. We have redirected the user to /') return redirect("/") if __name__ == "__main__": app.run(debug=True)

[ "ianorama@gmail.com" ]

ianorama@gmail.com

9dd52a5dbaf126ed8780d8d3fabfc6508c0af245

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/visualization/grill/pusher_reward_type_ablation.py

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[ "MIT" ]

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Asap7772/rail-rl-franka-eval

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refs/heads/master

2022-11-15T07:08:33.416025

2020-07-12T22:05:32

279,155,722

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1,142

py

import matplotlib from visualization.grill.config import ( output_dir, ashvin_base_dir, format_func, configure_matplotlib, ) import matplotlib.pyplot as plt from railrl.visualization import plot_util as plot configure_matplotlib(matplotlib) f = plot.filter_by_flat_params( {'replay_kwargs.fraction_goals_are_env_goals': 0.5}) exps = plot.load_exps([ ashvin_base_dir + 's3doodad/share/steven/pushing-multipushing/pusher-reward-variants'], f, suppress_output=True) plot.tag_exps(exps, "name", "dsae") plot.comparison(exps, ["Final puck_distance Mean", "Final hand_distance Mean"], figsize=(6, 4), vary=["vae_wrapped_env_kwargs.reward_params.type"], default_vary={"reward_params.type": "unknown"}, smooth=plot.padded_ma_filter(10), xlim=(0, 250000), ylim=(0.15, 0.22), method_order=None) plt.gca().xaxis.set_major_formatter(plt.FuncFormatter(format_func)) plt.xlabel("Timesteps") plt.ylabel("") plt.title("Visual Pusher") plt.legend([]) plt.tight_layout() plt.savefig(output_dir + "pusher_reward_type_ablation.pdf")

[ "asap7772@berkeley.edu" ]

asap7772@berkeley.edu

164292f20f8de66cf509569b2cdaffd15af4baee

b9a6440766ac6d09cbe5bcb0dd9ec035e79b68de

/0x0F-python-object_relational_mapping/1-filter_states.py

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[]

no_license

zulsb/holbertonschool-higher_level_programming

aa684ce2bad9f583dd54224e7cb1d60d2189b229

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refs/heads/master

2021-06-25T15:16:48.849508

2021-05-23T00:07:13

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#!/usr/bin/python3 """ Script that lists states with a name starting with N (upper N) from the database hbtn_0e_0_usa. """ import MySQLdb from sys import argv if __name__ == "__main__": """Connect to database.""" conec_db = MySQLdb.connect( host="localhost", port=3306, user=argv[1], passwd=argv[2], db=argv[3]) """Create cursor to exec queries using SQL.""" cursor = conec_db.cursor() cursor.execute("""SELECT * FROM states WHERE name LIKE BINARY 'N%' ORDER BY id ASC""") for row in cursor.fetchall(): print(row) cursor.close() conec_db.close()

[ "zulsb2093@gmail.com" ]

zulsb2093@gmail.com

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/blog/admin.py

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[]

no_license

Gentility01/my-project

aaab030abad105094aa1c0206995a95a756448be

9cd0805ffc7a02b811f6481ad79bda8e4b14a786

refs/heads/master

2023-06-17T13:39:01.353408

2021-07-07T01:20:59

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from django.contrib import admin from .models import Post,Like,Comment # Register your models here. admin.site.register(Post) admin.site.register(Like) admin.site.register(Comment) # admin.site.register(Post_pictures)

[ "mastergentility5@gmail.com" ]

mastergentility5@gmail.com

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/lib/surface/looker/instances/export.py

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permissive

google-cloud-sdk-unofficial/google-cloud-sdk

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refs/heads/master

2023-08-31T05:40:41.317697

2023-08-23T18:23:16

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2022-10-29T20:49:13

2021-02-02T05:47:30

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# -*- coding: utf-8 -*- # # Copyright 2023 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Export a Looker instance.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals from googlecloudsdk.api_lib.looker import instances from googlecloudsdk.calliope import base from googlecloudsdk.command_lib.looker import flags from googlecloudsdk.core import log @base.ReleaseTracks(base.ReleaseTrack.ALPHA, base.ReleaseTrack.GA) class Export(base.Command): """Export a Looker instance. This command can fail for the following reasons: * The instance specified does not exist. * The active account does not have permission to access the given instance. * The Google Cloud Storage bucket does not exist. """ detailed_help = {'EXAMPLES': """\ To export an instance with the name `my-looker-instance` in the default region, run: $ {command} my-looker-instance --target-gcs-uri='gs://bucketName/folderName' --kms-key='projects/my-project/locations/us-central1/keyRings/my-key-ring/cryptoKeys/my-key' Note that the kms-key flag should be the full name of the kms key. """} @staticmethod def Args(parser): """Register flags for this command.""" flags.AddExportInstanceArgs(parser) def Run(self, args): instance_ref = args.CONCEPTS.instance.Parse() op = instances.ExportInstance(instance_ref, args, self.ReleaseTrack()) log.status.Print( 'Export request issued for: [{}]\n' 'Check operation [{}] for status.'.format(args.instance, op.name) ) return op

[ "cloudsdk.mirror@gmail.com" ]

cloudsdk.mirror@gmail.com

e6d17a0f40ceb577e98f6ae04e3eae4ea842f9db

be51250bcf59e1b47ed417c45e203c50aa233aae

/dojo-python-flask-mysql/pr1/servererr.py

fb918ee40f7bd663d312ead3bde46ed6a7560cc1

[]

no_license

shoredata/dojo-python

4f064c76632bf94a385bb9f552562eb5640398b2

e7b7a542fa086088252ce92257f37c4b5eedd0c4

refs/heads/master

2020-05-02T22:07:31.547469

2019-03-28T17:44:06

178,242,426

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from flask import Flask # import the function connectToMySQL from the file mysqlconnection.py from mysqlconnerr import connectToMySQL app = Flask(__name__) # invoke the connectToMySQL function and pass it the name of the database we're using # connectToMySQL returns an instance of MySQLConnection, which we will store in the variable 'mysql' mysql = connectToMySQL('mydb') # now, we may invoke the query_db method query = "SELECT * FROM users;" sqldata = mysql.query_db(query) # print("all the users", sqldata) print("mysql>>> mydb::users::"+query) for i in sqldata: print(i) # for k in i: # print(i,k,i[k]) if __name__ == "__main__": app.run(debug=True)

[ "31630233+shoredata@users.noreply.github.com" ]

31630233+shoredata@users.noreply.github.com

d623fe68c6326fee1aba92885d989524184c5f2d

87d5b21265c381104de8f45aa67842a4adc880eb

/486. Predict the Winner.py

447e9a702208ffb5145c18af27a90a00db128a70

[]

no_license

MYMSSENDOG/leetcodes

ac047fe0d951e0946740cb75103fc94aae967166

8a52a417a903a0742034161471a084bc1e494d68

refs/heads/master

2020-09-23T16:55:08.579319

2020-09-03T19:44:26

225,543,895

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class Solution: def PredictTheWinner(self, nums): n = len(nums) dp = [[0] * (n+1) for _ in range(n+1)] for i in range(n-1,-1,-1): for j in range(i+1): l = j r = i-j dp[l][r] = max(nums[l] - dp[l+1][r], nums[-r-1] - dp[l][r + 1]) return dp[0][0] >= 0 sol = Solution() nums = [1,5,233,7] print(sol.PredictTheWinner(nums))

[ "fhqmtkfkd@naver.com" ]

fhqmtkfkd@naver.com

46d2e6cb4678a7bb86f2a93e3287a37554d642b4

0466559817d3a1be9409da2c83db99c4db3bacfe

/hubcheck/pageobjects/widgets/tags_view_form.py

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[ "MIT" ]

permissive

ken2190/hubcheck

955cf9b75a1ee77e28256dfd3a780cfbc17de961

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refs/heads/master

2023-03-20T15:17:12.949715

2015-09-29T16:11:18

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0

null

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py

from hubcheck.pageobjects.basepagewidget import BasePageWidget import re class TagsViewForm(BasePageWidget): def __init__(self, owner, locatordict={}): super(TagsViewForm,self).__init__(owner,locatordict) # load hub's classes TagsViewForm_Locators = self.load_class('TagsViewForm_Locators') TagSearchBox = self.load_class('TagSearchBox') SortOrderOptions = self.load_class('SortOrderOptions') SearchResults = self.load_class('SearchResults') TagsViewResultsRow = self.load_class('TagsViewResultsRow') ListPageNav = self.load_class('ListPageNav') # update this object's locator self.locators.update(TagsViewForm_Locators.locators) # update the locators with those from the owner self.update_locators_from_owner() # setup page object's components self.searchbox = TagSearchBox(self, { 'base' : 'searchbox', 'tags' : 'tags', 'tagsac' : 'tagsac', 'tagsacchoices' : 'tagsacchoices', 'tagsactoken' : 'tagsactoken', 'tagsacdelete' : 'tagsacdelete', 'submit' : 'submit', }) self.sortoptions = SortOrderOptions(self, { 'base' : 'sortoptions', 'date' : 'sortbydate', 'title' : 'sortbytitle', }) self.footer = ListPageNav(self,{'base':'footer'}) self.search_results = SearchResults(self, { 'base' : 'searchresults', 'counts' : 'sr_counts', 'row' : 'sr_row', 'substrow' : 'sr_substrow', }, TagsViewResultsRow, { 'src_title' : 'title', 'src_text' : 'text', 'src_href' : 'href', }) # update the component's locators with this objects overrides self._updateLocators() def search_for(self,terms): return self.searchbox.search_for(terms) def goto_page_number(self,pagenumber): return self.footer.goto_page_number(pagenumber) def goto_page_relative(self,relation): return self.footer.goto_page_relative(relation) def get_caption_counts(self): return self.search_results.header_counts() def get_pagination_counts(self): return self.footer.get_pagination_counts() def get_current_page_number(self): return self.footer.get_current_page_number() def get_link_page_numbers(self): return self.footer.get_link_page_numbers() def search_result_rows(self): return iter(self.search_results) class TagsViewForm_Locators_Base(object): """locators for TagsViewForm object""" locators = { 'base' : "css=#main form", 'searchbox' : "css=.data-entry", 'tags' : "css=#actags", 'tagsac' : "css=#token-input-actags", 'tagsacchoices' : "css=.token-input-dropdown-act", 'tagsactoken' : "css=.token-input-token-act", 'tagsacdelete' : "css=.token-input-delete-token-act", 'submit' : "css=.entry-search-submit", 'sortoptions' : "css=.entries-menu", 'sortbytitle' : "css=.entries-menu a[title='Sort by title']", 'sortbydate' : "css=.entries-menu a[title='Sort by newest to oldest']", 'footer' : "css=.list-footer", # 'searchresults' : "css=#search .results", 'searchresults' : "css=.container-block", 'sr_substrow' : "css=#search .results li:nth-of-type({row_num})", 'sr_row' : "css=#search .results li", 'sr_counts' : "css=#rel-search span", 'src_title' : "css=#search .results li:nth-of-type({row_num}) .title", 'src_text' : "css=#search .results li:nth-of-type({row_num}) p:nth-of-type(2)", 'src_href' : "css=#search .results li:nth-of-type({row_num}) .href", }

[ "telldsk@gmail.com" ]

telldsk@gmail.com

ef45fa15c61956b4c8f11b18890b9b8cf99f1ac7

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/xai/brain/wordbase/verbs/_tremble.py

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[ "MIT" ]

permissive

cash2one/xai

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refs/heads/master

2021-01-19T12:33:54.964379

2017-01-28T02:00:50

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#calss header class _TREMBLE(): def __init__(self,): self.name = "TREMBLE" self.definitions = [u'to shake slightly, usually because you are cold, frightened, or very emotional: '] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'verbs' def run(self, obj1 = [], obj2 = []): return self.jsondata

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

f22f021684ba14c9aea722e7b575fa83cc9e8627

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/python/test_builder_of_things.py

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[]

no_license

desertSniper87/codewars

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03f918e818a1c5a8b68ff23e24ad09698c32346b

refs/heads/master

2021-05-05T04:41:20.424603

2021-04-24T16:31:52

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import unittest from builder_of_things import * class TestClass(unittest.TestCase): def testName(self): jane = Thing('Jane') self.assertEqual(jane.name, 'Jane') self.assertEqual(jane.is_a_woman, True) self.assertEqual(jane.is_a_man, False) def testArms(self): jane = Thing('Jane') self.assertEqual(isinstance(jane.arms, tuple), True) self.assertEqual(len(jane.arms), 2) self.assertEqual(all(isinstance(v, Thing) for v in jane.arms), True) self.assertEqual(all(v.name=="arm" for v in jane.arms), True) self.assertEqual(all(v.is_arm for v in jane.arms), True) self.assertEqual(len(jane.arms), 2) self.assertEqual(all(isinstance(v, Thing) for v in jane.arms), True) def testHead(self): jane = Thing('Jane') self.assertEqual(isinstance(jane.head, Thing), True) self.assertEqual(jane.head.name, "head") def testEyes(self): jane = Thing('Jane') self.assertEqual(len(jane.head.eyes), 2) self.assertEqual(all(isinstance(v, Thing) for v in jane.head.eyes), True) self.assertEqual(all(v.name=='eye' for v in jane.head.eyes), True) def testFingers(self): jane = Thing('Jane') self.assertEqual(all(len(v.fingers)==5 for v in jane.arms), True) def testParent(self): jane = Thing('Jane') self.assertEqual(jane.parent_of, "joe") def testEyeColor(self): jane = Thing('Jane') self.assertEqual(all(v.color=='blue' for v in jane.head.eyes), True) def testEyeShape(self): jane = Thing('Jane') self.assertEqual(all(v.color=='blue' for v in jane.eyes), True) self.assertEqual(all(v.shape=='round' for v in jane.eyes), True) def testEyesColor(self): jane = Thing('Jane') self.assertEqual(all(v.color=='green' for v in jane.eyes), True) self.assertEqual(all(v.pupil.color=='black' for v in jane.eyes), True) # def testSpeech(self): # jane = Thing('Jane') # def fnc(phrase): # return "%s says: %s" % (name, phrase) # jane.can.speak(fnc) # self.assertEqual(jane.speak('hi'), "Jane says: hi") # def testSpeech2(self): # jane = Thing('Jane') # fnc = lambda phrase: "%s says: %s" % (name, phrase) # jane.can.speak(fnc, 'spoke') # jane.speak('hi') # self.assertEqual(jane.spoke, ["Jane says: hi"]) # jane.speak('goodbye') # self.assertEqual(jane.spoke, ["Jane says: hi", "Jane says: goodbye"]) def main(): unittest.main() if __name__ == '__main__': main()

[ "torshobuet@gmail.com" ]

torshobuet@gmail.com

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/Chapter-05/pandas_handlemissingdata.py

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lovejing0306/PythonforDataAnalysis

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be8d4862acc7538b52379cec36047b1c5bd48b3e

refs/heads/master

2021-06-09T20:40:04.157547

2016-11-20T02:23:07

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# coding=utf-8 from pandas import DataFrame, Series import pandas as pd import numpy as np # 测试 if __name__ == '__main__': string_data = Series(['aardvark', 'artichoke', np.nan, 'avocado']) print(string_data) print(string_data.isnull()) string_data[0] = None # python内置的None值也会被当作NaN来处理 print(string_data.isnull()) print(string_data.notnull()) ## 滤除缺失数据 # Series data = Series([1, np.nan, 3.5, np.nan, 7]) print(data) print(data.dropna()) print(data[data.notnull()]) # 通过布尔索引达到相同的效果 # DataFrame data = DataFrame([[1., 6.5, 3.], [1., np.nan, np.nan], [np.nan, np.nan, np.nan, np.nan], [np.nan, 6.5, 3.]]) print(data) print(data.dropna()) # 默认丢弃含有NaN的行 print(data.dropna(how='all')) # 丢弃全部都是NaN的行 data[4] = np.nan print(data) print(data.dropna(axis=1)) # 丢弃列 print(data.dropna(axis=1, how='all')) df = DataFrame(np.random.randn(7,3)) df.ix[:4, 1] = np.nan df.ix[:2, 2] = np.nan print(df) print(df.dropna()) print(df.dropna(thresh=3)) ## 填充缺失数据 print(df.fillna(0)) print(df.fillna({1:0.5, 2:-1})) # 通过字典实现对不同列不同值的填充 dfInplace = df.fillna(0, inplace=True) print(dfInplace) # fillna默认返回新对象，但也可以对现有对象进行就地修改 print(df) df = DataFrame(np.random.randn(6,3)) print(df) df.ix[2:, 1] = np.nan df.ix[3:, 2] = np.nan print(df) print(df.fillna(method='ffill')) print(df.fillna(method='ffill', limit=2)) data = Series([1., np.nan, 3.5, np.nan, 7]) print(data.fillna(data.mean()))

[ "lovejing0306@gmail.com" ]

lovejing0306@gmail.com

c8ef1d94e1d70ae6da235286cc8081214dd6866f

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[]

no_license

u-blavins/secret_sasquatch_society

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refs/heads/master

2020-08-14T00:39:52.948272

2020-01-22T13:54:58

215,058,646

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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- # Generated file, DO NOT EDIT # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------------------------- from msrest.serialization import Model class ReleaseDefinitionGate(Model): """ReleaseDefinitionGate. :param tasks: :type tasks: list of :class:`WorkflowTask <release.v4_1.models.WorkflowTask>` """ _attribute_map = { 'tasks': {'key': 'tasks', 'type': '[WorkflowTask]'} } def __init__(self, tasks=None): super(ReleaseDefinitionGate, self).__init__() self.tasks = tasks

[ "usama.blavins1@gmail.com" ]

usama.blavins1@gmail.com

ac54da57e3eea33615811d6513ec2872ea1f784b

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/01, 특강_210705_0706/02, source/CookData(2021.01.15)/Code14-01.py

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[]

no_license

goareum93/Algorithm

f0ab0ee7926f89802d851c2a80f98cba08116f6c

ec68f2526b1ea2904891b929a7bbc74139a6402e

refs/heads/master

2023-07-01T07:17:16.987779

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## 함수 선언 부분 ## def knapsack(): print('## 메모이제이션 배열 ##') array = [[0 for _ in range(maxWeight+1)] for _ in range(rowCount+1)] # 빈 배열을 만들고 모두 0으로 for row in range(1, rowCount+1) : # 1~4개 (4회) print(row, '개 -->', end = ' ') for col in range(1, maxWeight+1) : # 1colg ~ 7colg if weight[row] > col : # 물건의 무게가 열보다 크면 == 물건이 가방에 안 들어가면 array[row][col] = array[row-1][col] else : # 물건의 부피가 s보다 작거나 같으면 value1 = money[row] + array[row-1][col-weight[row]] # 각 그림의 1-1 value2 = array[row-1][col] # 각 그림의 1-2 array[row][col] = max(value1, value2) print('%2d' % array[row][col], end = ' ') print() return array[rowCount][maxWeight] ## 전역 변수 선언 부분 ## maxWeight = 7 # 배낭 최대 무게 rowCount = 4 # 보석 숫자 weight = [0, 6, 4,3, 5] # 보석 무게 (0, 금괴, 수정, 루비, 진주) money = [0,13, 8, 6, 12] # 보석 가격 (0, 금괴, 수정, 루비, 진주) ## 메인 코드 부분 ## maxValue = knapsack() print() print('배낭에 담을 수 있는 보석의 최대 가격 -->', maxValue, '억원')

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goareum7@gmail.com

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2022-11-06T01:48:06.925790

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import collections import os import requests from shutil import copyfile import castero from castero.net import Net class DataFile: """Extendable class for objects with filesystem data. Used when handling files with data that can reasonably be stored in a dictionary. Particularly used in the Config class and the Feeds class. Extended by classes which are based on a data file. """ PACKAGE = os.path.dirname(__file__) HOME = os.path.expanduser('~') XDG_CONFIG_HOME = os.getenv('XDG_CONFIG_HOME', os.path.join(HOME, '.config')) XDG_DATA_HOME = os.getenv('XDG_DATA_HOME', os.path.join(HOME, '.local', 'share')) CONFIG_DIR = os.path.join(XDG_CONFIG_HOME, castero.__title__) DATA_DIR = os.path.join(XDG_DATA_HOME, castero.__title__) DEFAULT_DOWNLOADED_DIR = os.path.join(DATA_DIR, "downloaded") def __init__(self, path, default_path) -> None: """ Args: path: the path to the data file default_path: the path to the default data file """ assert os.path.exists(default_path) self.data = collections.OrderedDict() self._path = path self._default_path = default_path # if path doesn't exit, create it based on default_path if not os.path.exists(self._path): DataFile.ensure_path(self._path) copyfile(self._default_path, self._path) def __iter__(self) -> iter: """Iterator for the keys of self.data In order to iterate over data values, you should use something like: for key in file_instance: value = file_instance[key] """ return self.data.__iter__() def __len__(self) -> int: return len(self.data) def __getitem__(self, item): if item in self.data: return self.data[item] def __setitem__(self, key, value): self.data[key] = value def __delitem__(self, key): self.data.pop(key, None) @staticmethod def ensure_path(filename): """Ensure that the path to the filename exists, creating it if needed. """ path = os.path.dirname(filename) if not os.path.exists(path): os.makedirs(path) @staticmethod def download_to_file(url, file, name, download_queue, display=None): """Downloads a URL to a local file. Args: url: the source url file: the destination path name: the user-friendly name of the content download_queue: the download_queue overseeing this download display: (optional) the display to write status updates to """ chunk_size = 1024 chuck_size_label = "KB" try: response = Net.Get(url, stream=True) except requests.exceptions.RequestException as e: if display is not None: display.change_status("RequestException: %s" % str(e)) download_queue.next() return else: handle = open(file, "wb") downloaded = 0 for chunk in response.iter_content(chunk_size=chunk_size): if display is not None: status_str = "Downloading \"%s\": %d%s" % ( name, downloaded / chunk_size, chuck_size_label ) if download_queue.length > 1: status_str += " (+%d downloads in queue)" % \ (download_queue.length - 1) display.change_status(status_str) if chunk: handle.write(chunk) downloaded += len(chunk) if display is not None: display.change_status("Episode successfully downloaded.") display.menus_valid = False download_queue.next() def load(self) -> None: """Loads the data file. Should be implemented by classes which extend this class. """ pass def write(self) -> None: """Writes to the data file. Should be implemented by classes which extend this class. """ pass

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jake@faltro.com

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/image_task_kg/make_KG.py

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monisha-jega/mmd

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2022-07-20T17:01:39.043859

2020-05-16T23:31:35

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from __future__ import print_function import json, os, pickle from parameters import * def convert_json(the_json): new_json = {} for key, val in the_json.items(): new_json[key.lower()] = val return new_json def is_int(s): try: int(s) return True except ValueError: return False domain_features = [ ['price'], #['style'], ['type'], ['fit'], #['brand'], ['gender'], #['neck'], ['material', 'fabric'], #['length'], #['sleeves'], #['model_worn'], ['currency'], ['color'] ] num_features = len(domain_features) feature_existence_count = [0 for i in range(num_features)] root_dir = "../../raw_catalog/" dirlist = [root_dir + name for name in ['public_jsons', 'public_jsons (2)', 'public_jsons (3)', 'public_jsons (4)']] count = 0 KG = {} for diri in dirlist[:]: print(len(os.listdir(diri))) for json_file in os.listdir(diri): #print("ok") the_json = convert_json(json.load(open(diri +"/" + json_file))) feature_vec = ["" for i in range(num_features)] for l in range(num_features): feature_names = domain_features[l] for feature_name in feature_names: if feature_name in the_json: if the_json[feature_name] == "" or (l == 0 and (not is_int(the_json[feature_name]) or int(the_json[feature_name]) == 0)): pass else: feature_vec[l] = the_json[feature_name] feature_existence_count[l] += 1 KG[the_json["image_filename"]] = feature_vec for orientation, links in the_json['image_filename_all'].items(): for link in links: KG[link] = feature_vec count += 1 if count%20000 == 0: print(count, end="") print(" ") print() print(feature_existence_count) json.dump(KG, open(data_dump_dir+"image_kg.json", "wb")) pickle.dump(KG, open(data_dump_dir+"image_kg.pkl", "wb"))

[ "monishaj@Monishas-MacBook-Pro.local" ]

monishaj@Monishas-MacBook-Pro.local

da7b653eafb429de4d61b697f9d80f9c7895357e

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/nickles_and_dimes.py

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[]

no_license

Th3Lourde/Mathematical_Modeling

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refs/heads/master

2020-04-24T01:23:26.447512

2019-04-08T02:38:56

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''' 11 coins 70 cents nickles and dimes ''' total = 70 coin_key = [] n = 5 d = 10 # Start with one dime and all nickles # Hypothesis: 3 dimes, 8 nickles # Done # Equation: 5x+10y = 70 # Equation: x + y = 11 # . # . # .

[ "th3sylvia.lourde@gmail.com" ]

th3sylvia.lourde@gmail.com

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/3.advanced_features/1.advanced_features.py

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[]

no_license

fzingithub/LearnPythonFromLiao

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refs/heads/master

2020-03-29T19:37:32.831341

2018-09-27T10:39:11

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# -*- coding: utf-8 -*- """ Created on Sun Jan 21 18:43:50 2018 @author: FZ """ #make a list 1...99 L = list(range(1,100,2)) print (L) #高级特性，1行代码能实现的功能，决不写5行代码。请始终牢记，代码越少，开发效率越高。

[ "1194585271@qq.com" ]

1194585271@qq.com

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/medium/833_find_and_replace_in_string.py

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[]

no_license

esddse/leetcode

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2021-06-08T19:15:14.346584

2020-01-09T01:41:23

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class Solution: def findReplaceString(self, S: str, indexes: List[int], sources: List[str], targets: List[str]) -> str: replacements = sorted(zip(indexes, sources, targets), key=lambda item:item[0]) length = len(S) start = 0 new_S = "" for idx, source, target in replacements: if idx >= length: break new_S += S[start:idx] sl = len(source) if S[idx:idx+sl] == source: new_S += target start = idx+sl else: start = idx new_S += S[start:] return new_S

[ "tjz427@sina.cn" ]

tjz427@sina.cn

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/ex073/venv/Scripts/easy_install-3.7-script.py

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ArthurAlesi/Python-Exercicios-CursoEmVideo

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2022-12-31T13:21:30.001538

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#!C:\Users\User\Documents\github-MeusRepositórios\Python-Exercicios-CursoEmVideo\ex073\venv\Scripts\python.exe -x # EASY-INSTALL-ENTRY-SCRIPT: 'setuptools==40.8.0','console_scripts','easy_install-3.7' __requires__ = 'setuptools==40.8.0' import re import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit( load_entry_point('setuptools==40.8.0', 'console_scripts', 'easy_install-3.7')() )

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/python/src/nnabla/backward_function/bc_add2.py

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2020-12-03T05:11:24.724125

2019-09-04T06:39:41

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# Copyright (c) 2017 Sony Corporation. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np import nnabla as nn import nnabla.functions as F from .backward_function import BackwardFunction class BcAdd2Backward(BackwardFunction): def name(self): return 'BcAdd2Backward' def _create_forward_inputs_and_outputs(self, inputs, outputs): # Inputs on the forward graph inputs_fwd = [] for i in range(self._num_inputs_fwd): need_grad = self.forward_func.inputs[i].need_grad v = nn.Variable(inputs[i].shape, need_grad=need_grad) v.data = inputs[i].data v.grad = outputs[i].data inputs_fwd += [v] # Outputs on the forward graph outputs_fwd = [] for i in range(self._num_outputs_fwd): inp = inputs[self._num_inputs_fwd + i] v = nn.Variable(inp.shape) v.grad = inp.data outputs_fwd += [v] return inputs_fwd, outputs_fwd def backward_impl(self, inputs, outputs, prop_down, accum): # inputs: [inputs_fwd_graph] + [inputs_bwd_graph] or # [inputs_fwd_graph] + [outputs_fwd_graph] + [inputs_bwd_graph] raise NotImplementedError( "The backward method of BcAdd2Backward class is not implemented.")

[ "Kazuki.Yoshiyama@sony.com" ]

Kazuki.Yoshiyama@sony.com

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/Python/problem0082.py

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1050669722/LeetCode-Answers

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2023-03-08T01:25:19.720931

2021-02-22T00:34:43

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# Definition for singly-linked list. class ListNode: def __init__(self, x): self.val = x self.next = None class Solution: def deleteDuplicates(self, head: ListNode) -> ListNode: if not (head and head.next): return head d = {} tmp = head while tmp: if tmp.val in d: d[tmp.val] += 1 else: d[tmp.val] = 1 tmp = head head = ListNode(None) head.next = tmp pre, cur = head, head.next while cur: if d[cur.val] == 1: cur = cur.next pre = pre.next else: for _ in range(d[cur.val]): cur = cur.next pre.next = cur return head.next

[ "1050669722@qq.com" ]

1050669722@qq.com

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/src/spaceone/inventory/connector/aws_secrets_manager_connector/schema/service_type.py

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2022-12-12T03:12:10.744727

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from spaceone.inventory.libs.schema.dynamic_field import TextDyField, DateTimeDyField, SearchField from spaceone.inventory.libs.schema.resource import CloudServiceTypeResource, CloudServiceTypeResponse, \ CloudServiceTypeMeta cst_secret = CloudServiceTypeResource() cst_secret.name = 'Secret' cst_secret.provider = 'aws' cst_secret.group = 'SecretsManager' cst_secret.labels = ['Security'] cst_secret.tags = { 'spaceone:icon': 'https://spaceone-custom-assets.s3.ap-northeast-2.amazonaws.com/console-assets/icons/cloud-services/aws/AWS-Secrets-Manager.svg', 'spaceone:is_major': 'true', } cst_secret._metadata = CloudServiceTypeMeta.set_meta( fields=[ TextDyField.data_source('Name', 'data.name'), TextDyField.data_source('Description', 'data.description'), DateTimeDyField.data_source('Last Retrieved', 'data.last_accessed_date'), ], search=[ SearchField.set(name='Name', key='data.name'), SearchField.set(name='ARN', key='data.arn'), SearchField.set(name='Last Changed Time', key='data.last_changed_date', data_type='datetime'), SearchField.set(name='Last Accessed Time', key='data.last_accessed_date', data_type='datetime'), SearchField.set(name='Rotation Enabled', key='data.rotation_enabled', data_type='boolean'), SearchField.set(name='Region', key='data.region_name'), SearchField.set(name='AWS Account ID', key='data.account_id'), ] ) CLOUD_SERVICE_TYPES = [ CloudServiceTypeResponse({'resource': cst_secret}), ]

[ "bluese@megazone.com" ]

bluese@megazone.com

c51f6f32ab60667f3221123353d8004395f8d50b

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/example06-06-01.py

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[]

no_license

Minari766/study_python

c4243df47f23e8fda5bcdf16b65f3b3af97f888c

b1e48e750126f377a15f8be8b3c2547687416ec4

refs/heads/master

2022-12-15T10:29:05.306690

2020-09-03T13:05:21

null

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null

UTF-8

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# coding:utf-8 import tkinter as tk import tkinter.messagebox as tmsg import random #ボタンがクリックされたときの処理 def ButtonClick(): b = editbox1.get() #テキスト入力欄に入力された文字列を取得。変数.getメソッドを使用 #Lesson 5-4のプログラム。4桁の数字かどうかを判定 #4桁の数字かどうかを判断する isok = False if len(b)!= 4: tmsg.showerror("エラー","4桁の数字を入れてください") else: kazuok = True for i in range(4): if (b[i] < "0") or (b[i] > "9"): tmsg.showerror("エラー", "数字ではありません") kazuok = False break if kazuok: isok = True if isok: #4桁の数字だった場合。ヒットを判定 hit = 0 for i in range(4): if a[i] == int(b[i]): hit = hit +1 #ブローを判定 blow = 0 for j in range(4): for i in range(4): if (int(b[j]) == a[i]) and (a[i] != int(b[i])) and (a[j] != int(b[j])): blow = blow + 1 break #ヒットが4なら正解となり、終了 if hit == 4: tmsg.showinfo("正解！", "おめでとうございます！") #終了 root.destroy() else: #ヒット数とブロー数を表示。 rirekibox.insert(tk.END, b + " /H:" + str(hit) + " B:" + str(blow) + "\n")#ウィンドウ向けに新たに調整した部分 #メインのプログラム #予めランダムな4つの数字を設定 a = [random.randint(0, 9), random.randint(0, 9), random.randint(0, 9), random.randint(0, 9)] #ウィンドウを作る root = tk.Tk() root.geometry("600x400") root.title("数当てゲーム") #ウィンドウを作る #履歴表示のテキストボックスを作る rirekibox = tk.Text(root, font = ("Meiryo UI", 14)) rirekibox.place(x=400, y=0, width=200, height=400) #ラベルを作る label1 = tk.Label(root, text="数を入力してください", font=("Meiryo UI", 14)) #文章を入れる label1.place(x = 20, y = 20) #変数の入力欄を動かす #テキストボックス（プレイヤーの入力欄）を作る editbox1 = tk.Entry(width =4, font = ("Meiryo UI", 28)) #テキスト入力欄を作る editbox1.place(x = 160, y = 20) #ボタンを作る button1 = tk.Button(root, text = "チェック", font = ("Meiryo UI", 14), command = ButtonClick) button1.place(x = 240, y = 20) #ウィンドウを表示する root.mainloop() #ウィンドウを表示する

[ "mina3.ryu0728@gmail.com" ]

mina3.ryu0728@gmail.com

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/solutions_python/Problem_116/1400.py

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no_license

dr-dos-ok/Code_Jam_Webscraper

c06fd59870842664cd79c41eb460a09553e1c80a

26a35bf114a3aa30fc4c677ef069d95f41665cc0

refs/heads/master

2020-04-06T08:17:40.938460

2018-10-14T10:12:47

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'''Qualification Round Problem A. Speaking in Tongues''' import sys SIZE = 4 def checkLine( line ): o = 0 x = 0 for cell in line: if cell == 'O': o += 1 elif cell == 'X': x += 1 elif cell == '.': return None if o == 0: return 'X won' elif x == 0: return 'O won' else: return None def checkResult( board ): # horizontal for line in board: result = checkLine( line ) if result is not None: return result # vertical for i in range( SIZE ): line = ( row[ i ] for row in board ) result = checkLine( line ) if result is not None: return result # diagonal line = ( row[ i ] for i, row in enumerate( board ) ) result = checkLine( line ) if result is not None: return result line = ( row[ SIZE - i - 1 ] for i, row in enumerate( board ) ) result = checkLine( line ) if result is not None: return result # completion-check for line in board: if line.find( '.' ) >= 0: return 'Game has not completed' return 'Draw' def main( input ): count = int( input.readline() ) for index in range( 1, count + 1 ): board = [] for rowIndex in range( SIZE ): line = input.readline().strip() board.append( line ) input.readline() result = checkResult( board ) print( 'Case #{}: {}'.format( index, result ) ) main( sys.stdin )

[ "miliar1732@gmail.com" ]

miliar1732@gmail.com

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/problem/p_1346_check_if_N_and_its_double_exist/solutions.py

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[]

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Lee-W/leetcode

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from typing import List class Solution: def checkIfExist(self, arr: List[int]) -> bool: for m_i, m in [(num_i, num) for num_i, num in enumerate(arr) if not num % 2]: for n_i, num in enumerate(arr): if m_i == n_i: continue if num * 2 == m: return True return False

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# This module is called from 3R Automation Component. import os import sys # pdftotree is available as part of the virtual environment for 3R Python processing import pdftotree import json from pprint import pprint import pdfminer import ocr_extract as imgpdf from utils.ocr.handle_image import * # pdf_doc = json.loads(sys.argv[1])['doc_name'] # html_path = json.loads(sys.argv[1])['html_path'] # Use the following for testing pdf_doc = '/home/dsie/Developer/sandbox/3ray/3rml/kbc_process/documents/pdf/Sri_khyati_CV.pdf' html_path = '/home/dsie/Developer/sandbox/3ray/3rml/kbc_process/documents/html/Sri_khyati_CV.html' def create_hocr(pdf_doc='', html_path='', model_path='./model/model.pkl'): return pdftotree.parse(pdf_doc, html_path=html_path, model_type=None, model_path=model_path, visualize=False) create_hocr_output = None try: create_hocr_output = create_hocr(pdf_doc=pdf_doc, html_path=html_path) except pdfminer.pdfparser.PDFSyntaxError as pdfException: create_hocr_output = pdfException # Use the following for testing non PDF files # print(f'{os.path.basename(pdf_doc).split(".")[0]+".pdf"}') # print(f'{os.path.abspath(pdf_doc).split(".")[0]+".pdf"}') # try: # # imgpdf.convert_image_to_pdf(pdf_doc, os.path(pdf_doc)+os.path.basename(pdf_doc).split('.')[0]+'.pdf') # imgpdf.convert_image_to_pdf(pdf_doc, os.path.dirname(pdf_doc), os.path.abspath(pdf_doc).split(".")[0]+".pdf") # except Exception as exc: # print(exc) # Output of "print" statement is passed to the calling program proc_status = "OK" if create_hocr_output == None else "Not a PDF document. Please provide a PDF file for processing." json_out = {"pdf_doc": pdf_doc, "process_status": proc_status} print(json_out)

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#!f:\proshop_django-master\venv\scripts\python.exe # Author: # Contact: grubert@users.sf.net # Copyright: This module has been placed in the public domain. """ man.py ====== This module provides a simple command line interface that uses the man page writer to output from ReStructuredText source. """ import locale try: locale.setlocale(locale.LC_ALL, '') except: pass from docutils.core import publish_cmdline, default_description from docutils.writers import manpage description = ("Generates plain unix manual documents. " + default_description) publish_cmdline(writer=manpage.Writer(), description=description)

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# coding=UTF-8 # ********************************************************************** # Copyright (c) 2013-2016 Cisco Systems, Inc. All rights reserved # written by zen warriors, do not modify! # ********************************************************************** from cobra.mit.meta import ClassMeta from cobra.mit.meta import StatsClassMeta from cobra.mit.meta import CounterMeta from cobra.mit.meta import PropMeta from cobra.mit.meta import Category from cobra.mit.meta import SourceRelationMeta from cobra.mit.meta import NamedSourceRelationMeta from cobra.mit.meta import TargetRelationMeta from cobra.mit.meta import DeploymentPathMeta, DeploymentCategory from cobra.model.category import MoCategory, PropCategory, CounterCategory from cobra.mit.mo import Mo # ################################################## class Adj(Mo): """ The connectivity to an external network. """ meta = ClassMeta("cobra.model.hvs.Adj") meta.moClassName = "hvsAdj" meta.rnFormat = "adj-[%(nbrKey)s]" meta.category = MoCategory.REGULAR meta.label = "Adjacency" meta.writeAccessMask = 0x5 meta.readAccessMask = 0x5 meta.isDomainable = False meta.isReadOnly = True meta.isConfigurable = False meta.isDeletable = False meta.isContextRoot = False meta.childClasses.add("cobra.model.fault.Inst") meta.childClasses.add("cobra.model.fault.Counts") meta.childClasses.add("cobra.model.health.Inst") meta.childClasses.add("cobra.model.hvs.RtNicAdj") meta.childClasses.add("cobra.model.hvs.RsLsNode") meta.childNamesAndRnPrefix.append(("cobra.model.hvs.RtNicAdj", "rtcompNicAdj-")) meta.childNamesAndRnPrefix.append(("cobra.model.hvs.RsLsNode", "rsLsNode")) meta.childNamesAndRnPrefix.append(("cobra.model.fault.Counts", "fltCnts")) meta.childNamesAndRnPrefix.append(("cobra.model.fault.Inst", "fault-")) meta.childNamesAndRnPrefix.append(("cobra.model.health.Inst", "health")) meta.parentClasses.add("cobra.model.comp.Hv") meta.rnPrefixes = [ ('adj-', True), ] prop = PropMeta("str", "addr", "addr", 234, PropCategory.REGULAR) prop.label = "Neighbor Address" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("addr", prop) prop = PropMeta("str", "childAction", "childAction", 4, PropCategory.CHILD_ACTION) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop._addConstant("deleteAll", "deleteall", 16384) prop._addConstant("deleteNonPresent", "deletenonpresent", 8192) prop._addConstant("ignore", "ignore", 4096) meta.props.add("childAction", prop) prop = PropMeta("str", "configIssues", "configIssues", 238, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "none" prop._addConstant("missing-mgmtip", "management-address-is-not-configured-on-loosenode-(unmanaged-switch)", 1) prop._addConstant("none", "none", 0) meta.props.add("configIssues", prop) prop = PropMeta("str", "dn", "dn", 1, PropCategory.DN) prop.label = "None" prop.isDn = True prop.isImplicit = True prop.isAdmin = True prop.isCreateOnly = True meta.props.add("dn", prop) prop = PropMeta("str", "ifId", "ifId", 236, PropCategory.REGULAR) prop.label = "Interface Id" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("ifId", prop) prop = PropMeta("str", "ifName", "ifName", 235, PropCategory.REGULAR) prop.label = "Neighbor Interface" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("ifName", prop) prop = PropMeta("str", "lcOwn", "lcOwn", 9, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "local" prop._addConstant("implicit", "implicit", 4) prop._addConstant("local", "local", 0) prop._addConstant("policy", "policy", 1) prop._addConstant("replica", "replica", 2) prop._addConstant("resolveOnBehalf", "resolvedonbehalf", 3) meta.props.add("lcOwn", prop) prop = PropMeta("str", "modTs", "modTs", 7, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "never" prop._addConstant("never", "never", 0) meta.props.add("modTs", prop) prop = PropMeta("str", "monPolDn", "monPolDn", 13777, PropCategory.REGULAR) prop.label = "Monitoring policy attached to this observable object" prop.isImplicit = True prop.isAdmin = True meta.props.add("monPolDn", prop) prop = PropMeta("str", "name", "name", 229, PropCategory.REGULAR) prop.label = "Name" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 16)] prop.regex = ['[a-zA-Z0-9_.:-]+'] meta.props.add("name", prop) prop = PropMeta("str", "nbrDesc", "nbrDesc", 232, PropCategory.REGULAR) prop.label = "Neighbor Description" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("nbrDesc", prop) prop = PropMeta("str", "nbrId", "nbrId", 231, PropCategory.REGULAR) prop.label = "Neighbor Identifier" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("nbrId", prop) prop = PropMeta("str", "nbrKey", "nbrKey", 233, PropCategory.REGULAR) prop.label = "Neighbor Key" prop.isConfig = True prop.isAdmin = True prop.isCreateOnly = True prop.isNaming = True prop.range = [(1, 512)] meta.props.add("nbrKey", prop) prop = PropMeta("str", "nbrName", "nbrName", 230, PropCategory.REGULAR) prop.label = "Name" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 16)] prop.regex = ['[a-zA-Z0-9_.:-]+'] meta.props.add("nbrName", prop) prop = PropMeta("str", "nbrType", "nbrType", 237, PropCategory.REGULAR) prop.label = "Neighbor Type, Leaf or Loosenode" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 1 prop.defaultValueStr = "leaf" prop._addConstant("leaf", "leaf", 1) prop._addConstant("loosenode", "loosenode", 2) meta.props.add("nbrType", prop) prop = PropMeta("str", "proto", "proto", 228, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "none" prop._addConstant("CDP", "cdp", 2) prop._addConstant("LLDP", "lldp", 1) prop._addConstant("none", "none", 0) meta.props.add("proto", prop) prop = PropMeta("str", "rn", "rn", 2, PropCategory.RN) prop.label = "None" prop.isRn = True prop.isImplicit = True prop.isAdmin = True prop.isCreateOnly = True meta.props.add("rn", prop) prop = PropMeta("str", "status", "status", 3, PropCategory.STATUS) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop._addConstant("created", "created", 2) prop._addConstant("deleted", "deleted", 8) prop._addConstant("modified", "modified", 4) meta.props.add("status", prop) meta.namingProps.append(getattr(meta.props, "nbrKey")) getattr(meta.props, "nbrKey").needDelimiter = True def __init__(self, parentMoOrDn, nbrKey, markDirty=True, **creationProps): namingVals = [nbrKey] Mo.__init__(self, parentMoOrDn, markDirty, *namingVals, **creationProps) # End of package file # ##################################################

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import tensorflow as tf from scipy import stats def Drop( X, keep_rate ): keep_mask = stats.bernoulli( keep_rate).rvs( X.shape ) Y = X*keep_mask + (1-keep_mask)*0 return Y def DropColumns( X, cols2drop ): Y = X.copy() Y[:,cols2drop] = 0 return Y class Regularizer(object): def __init__( self, lam_value ): self.lam = lam_value def Apply( self, w ): raise NotImplemented, "Must derive class" class L2Regularizer(Regularizer): def Apply( self, w ): return self.lam*tf.reduce_sum( tf.square(w) ) class L1Regularizer(Regularizer): def Apply( self, w ): return self.lam*tf.reduce_sum( tf.abs(w) ) class LqRegularizer(Regularizer): def __init__( self, lam_value, q ): self.lam = lam_value self.q = q self.eps = 1e-6 def Apply( self, w ): return self.lam*tf.reduce_sum( tf.pow( tf.abs(w), self.q ) + self.eps ) class SortedL1RegularizerAxis2(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): return self.lam*tf.reduce_sum( tf.abs(w[:,:,1:]-w[:,:,:-1]) + self.eps ) class SortedL1RegularizerAxis1(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): return self.lam*tf.reduce_sum( tf.abs(w[:,1:,:]-w[:,:-1,:]) + self.eps ) class SortedL1RegularizerAxis0(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): return self.lam*tf.reduce_sum( tf.abs(w[1:,:,:]-w[:-1,:,:]) + self.eps ) class SortedAbsL1RegularizerAxis2(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): aw = tf.abs(w) return self.lam*tf.reduce_sum( tf.abs(aw[:,:,1:]-aw[:,:,:-1]) + self.eps ) class SortedAbsL1RegularizerAxis1(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): aw = tf.abs(w) return self.lam*tf.reduce_sum( tf.abs(aw[:,1:,:]-aw[:,:-1,:]) + self.eps ) class SortedAbsL1RegularizerAxis0(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): aw = tf.abs(w) return self.lam*tf.reduce_sum( tf.abs(aw[1:,:,:]-aw[:-1,:,:]) + self.eps ) # ------------------ class SortedL2RegularizerAxis2(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): return self.lam*tf.reduce_sum( tf.square(w[:,:,1:]-w[:,:,:-1]) + self.eps ) class SortedL2RegularizerAxis1(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): return self.lam*tf.reduce_sum( tf.square(w[:,1:,:]-w[:,:-1,:]) + self.eps ) class SortedL2RegularizerAxis0(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): return self.lam*tf.reduce_sum( tf.square(w[1:,:,:]-w[:-1,:,:]) + self.eps ) class SortedAbsL2RegularizerAxis2(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): aw = tf.abs(w) return self.lam*tf.reduce_sum( tf.square(aw[:,:,1:]-aw[:,:,:-1]) + self.eps ) class SortedAbsL2RegularizerAxis1(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): aw = tf.abs(w) return self.lam*tf.reduce_sum( tf.square(aw[:,1:,:]-aw[:,:-1,:]) + self.eps ) class SortedAbsL2RegularizerAxis0(Regularizer): def __init__( self, lam_value ): self.lam = lam_value #self.q = q self.eps = 1e-6 def Apply( self, w ): aw = tf.abs(w) return self.lam*tf.reduce_sum( tf.square(aw[1:,:,:]-aw[:-1,:,:]) + self.eps )

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# -*- coding: utf-8 -*- # Generated by Django 1.9.7 on 2016-11-07 16:26 from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('wetLab', '0016_auto_20161107_1556'), ] operations = [ migrations.RenameField( model_name='treatmentrnai', old_name='treatmentRnai_target_sequence', new_name='treatmentRnai_targetNucleotide_seq', ), ]

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# -*- coding: utf-8 -*- # Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import abc import typing import pkg_resources import google.auth # type: ignore from google.api_core import gapic_v1 # type: ignore from google.api_core import retry as retries # type: ignore from google.auth import credentials as ga_credentials # type: ignore from google.ads.googleads.v7.resources.types import detail_placement_view from google.ads.googleads.v7.services.types import detail_placement_view_service try: DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( gapic_version=pkg_resources.get_distribution( 'google-ads', ).version, ) except pkg_resources.DistributionNotFound: DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo() class DetailPlacementViewServiceTransport(metaclass=abc.ABCMeta): """Abstract transport class for DetailPlacementViewService.""" AUTH_SCOPES = ( 'https://www.googleapis.com/auth/adwords', ) def __init__( self, *, host: str = 'googleads.googleapis.com', credentials: ga_credentials.Credentials = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, ) -> None: """Instantiate the transport. Args: host (Optional[str]): The hostname to connect to. credentials (Optional[google.auth.credentials.Credentials]): The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment. client_info (google.api_core.gapic_v1.client_info.ClientInfo): The client info used to send a user-agent string along with API requests. If ``None``, then default info will be used. Generally, you only need to set this if you're developing your own client library. """ # Save the hostname. Default to port 443 (HTTPS) if none is specified. if ':' not in host: host += ':443' self._host = host # If no credentials are provided, then determine the appropriate # defaults. if credentials is None: credentials, _ = google.auth.default(scopes=self.AUTH_SCOPES) # Save the credentials. self._credentials = credentials # Lifted into its own function so it can be stubbed out during tests. self._prep_wrapped_messages(client_info) def _prep_wrapped_messages(self, client_info): # Precomputed wrapped methods self._wrapped_methods = { self.get_detail_placement_view: gapic_v1.method.wrap_method( self.get_detail_placement_view, default_timeout=None, client_info=client_info, ), } @property def get_detail_placement_view(self) -> typing.Callable[ [detail_placement_view_service.GetDetailPlacementViewRequest], detail_placement_view.DetailPlacementView]: raise NotImplementedError __all__ = ( 'DetailPlacementViewServiceTransport', )

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import argparse import sys import logging import os import gzip sys.path.insert(0, '/home/shengq2/program/ngsperl/lib/RNAediting') from WordRoleUtils import WordRole roles = {} roles["Turnee_word"] = [ WordRole("TurneeA", "AACCAT", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeB", "AACGTC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeC", "AACTCA", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeD", "AAGACT", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeE", "ACTATT", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeH", "ATATGA", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeI", "CAATAT", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeJ", "CCTCGG", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeK", "CGCTTC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeN", "GCAGAA", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeP", "GCGTCC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeQ", "GGAGTC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeT", "GTTGCC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeU", "TACCGG", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeV", "TCAGCC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeW", "TTCGGC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), WordRole("TurneeX", "TTGACC", 6, "GCTGGACCGGTATGTAGCA", 0.9, 25, "RTRCGTRRTCCTRTTGAGCATAGCCGGTTCAATTCGCGGACTAAGGCCATCATGAA", ['A', 'G']), ] logger = logging.getLogger('findWord') logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)-8s - %(message)s') wordCounts = {} discardCounts = {} rootFolder = "/scratch/VANGARD/20180305_turnee_rnaediting/" fileName = rootFolder + "1364-TM-1_S1_R1_001.fastq.gz" gzipped = fileName.endswith(".gz") if gzipped: f = gzip.open(fileName, 'rt') else: f = open(fileName, 'r') def findWord(sequence, roles, wordCounts): for userName, userRoles in roles.iteritems(): if not userName in wordCounts: wordCounts[userName] = {} userCounts = wordCounts[userName] if not userName in discardCounts: discardCounts[userName] = {} userDiscardCounts = discardCounts[userName] for role in userRoles: curWord = role.getWord(sequence) if curWord.discarded: if role.SampleName in userDiscardCounts: userDiscardCounts[role.SampleName] = userDiscardCounts[role.SampleName] + 1 else: userDiscardCounts[role.SampleName] = 1 return(None) if len(curWord.word) > 0: if not role.SampleName in userCounts: userCounts[role.SampleName] = {} sampleCounts = userCounts[role.SampleName] if not curWord.word in sampleCounts: sampleCounts[curWord.word] = 1 else: sampleCounts[curWord.word] = sampleCounts[curWord.word] + 1 return(role) return(None) fastqMap = {} try: count = 0 while True: header = f.readline() if '' == header: break if not header.startswith("@"): continue sequence = f.readline().strip() line3 = f.readline() line4 = f.readline() role = findWord(sequence, roles, wordCounts) if role != None: if not role.SampleName in fastqMap: fastqFile = rootFolder + role.SampleName + ".fastq.gz" fastqMap[role.SampleName] = gzip.open(fastqFile, "wt") sw = fastqMap[role.SampleName] sw.write("%s\n" % header.strip()) sw.write("%s\n" % sequence) sw.write("%s\n" % line3.strip()) sw.write("%s\n" % line4.strip()) count = count+1 if count % 100000 == 0: logger.info("%d reads processed" % count) #if count % 20000 == 0: # break finally: f.close() logger.info("total %d reads processed" % count) for sw in fastqMap.values(): sw.close() for userName, userCounts in wordCounts.iteritems(): samples = sorted(userCounts.iterkeys()) totalCounts = {sample:sum(userCounts[sample].values()) for sample in samples} words = sorted(set( val for dic in userCounts.values() for val in dic.keys())) with open(rootFolder + userName + ".count.txt", "w") as swCount: with open(rootFolder + userName + ".perc.txt", "w") as swPerc: header = "Word\t%s\n" % "\t".join(samples) swCount.write(header) swPerc.write(header) for word in words: swCount.write(word) swPerc.write(word) for sample in samples: sampleCounts = userCounts[sample] if word in sampleCounts: swCount.write("\t%d" % sampleCounts[word]) swPerc.write("\t%.4f" % (sampleCounts[word] * 1.0 / totalCounts[sample])) else: swCount.write("\t0") swPerc.write("\t0") swCount.write("\n") swPerc.write("\n") swCount.write("TotalWord\t%s\n" % "\t".join([str(totalCounts[sample]) for sample in samples])) swCount.write("DiscardRead\t%s\n" % "\t".join([str(discardCounts[userName][sample]) for sample in samples])) gPerc = {} for sample in samples: gPerc[sample] = {} sampleCounts = userCounts[sample] for word in sampleCounts: maxChrInd = len(word) wCount = sampleCounts[word] for chrInx in range(0, len(word)) : if chrInx in gPerc[sample]: chrMap = gPerc[sample][chrInx] else: chrMap = {'G':0, 'R':0} gPerc[sample][chrInx] = chrMap if word[chrInx] == 'G': chrMap['G'] = chrMap['G'] + wCount else: chrMap['R'] = chrMap['R'] + wCount with open(rootFolder + userName + ".G.txt", "w") as swG: swG.write("Word\t%s\n" % "\t".join(samples)) for chrInd in range(0, maxChrInd): word = 'R' * chrInd + 'G' + 'R' *(maxChrInd - chrInd - 1) swG.write(word) for sample in samples: chrMap = gPerc[sample][chrInd] perc = chrMap['G'] * 1.0 / (chrMap['G'] + chrMap['R']) swG.write('\t%.4f' % perc) swG.write('\n') logger.info("done")

[ "shengqh@gmail.com" ]

shengqh@gmail.com

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/Facturacion/urls.py

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matheo97/ERP

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from django.conf.urls import url, include from .views import * urlpatterns = [ url(r'^generar_cotizacion/$', generarCotizacion.as_view(), name="generar_cotizacion"), url(r'^generar_factura/$', generarFactura.as_view(), name="generar_factura"), url(r'^editar_factura/(?P<id_factura>\w+)$', editarFactura.as_view(), name="editar_factura"), url(r'^generar_factura_cotizacion/(?P<id_cotizacion>\d+)$', generarFacturadeCotizacion.as_view(), name="generar_factura_cotizacion"), url(r'^generar_remision/$', generarRemision.as_view(), name="generar_remision"), url(r'^generar_cotizacion/eliminar_presentacion_carrito$', eliminarPresentacionCarrito.as_view(), name="eliminar_presentacion_carrito"), url(r'^generar_factura/eliminar_presentacion_carrito$', eliminarPresentacionCarrito.as_view(), name="eliminar_presentacion_carrito"), url(r'^listar_facturacion/(?P<id_cliente>.+)$', listarFacturacion.as_view(), name="listar_facturacion"), url(r'^listar_facturas/(?P<id_cliente>.+)$', listar_facturas, name="listar_facturas"), url(r'^listar_cotizaciones/(?P<id_cliente>.+)$', listar_cotizaciones, name="listar_cotizaciones"), url(r'^listar_remisiones/(?P<id_cliente>.+)$', listar_remisiones, name="listar_remisiones"), url(r'^generar_cotizacion_pdf/(?P<id_cotizacion>\d+)$', generarCotizacionPDF.as_view(), name="generarCotizacion_pdf"), url(r'^generar_factura_pdf/(?P<id_factura>\w+)$', generarFacturaPDF.as_view(), name="generarFactura_pdf"), url(r'^generar_factura/validar_consecutivo/', validar_consecutivo, name="validar_consecutivo"), url(r'^generar_factura_cotizacion/validar_consecutivo/', validar_consecutivo, name="generar_factura_cotizacion_1"), url(r'^generar_remision_pdf/(?P<id_remision>\d+)$', generarRemisionPDF.as_view(), name="generarRemision_pdf"), url(r'^ver_factura/(?P<id_factura>\d+)$', verFactura.as_view(), name="ver_factura"), url(r'^limpiar_carrito/(?P<documento>\w+)$', limpiar_carrito, name="limpiar_carrito"), url(r'^eliminar_factura/$', eliminar_factura.as_view(), name="eliminar_factura"), ]

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refs/heads/master

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#calss header class _FOCUSING(): def __init__(self,): self.name = "FOCUSING" self.definitions = focus self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['focus']

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ravi4all/PythonDecMorning

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Python 3.6.2 (v3.6.2:5fd33b5, Jul 8 2017, 04:57:36) [MSC v.1900 64 bit (AMD64)] on win32 Type "copyright", "credits" or "license()" for more information. >>> a = 2 >>> a = "*" >>> print(a*5) ***** >>> for i in range(1,6): print('*' * ((i*2)-1))) SyntaxError: invalid syntax >>> for i in range(1,6): print('*' * ((i*2)-1)) * *** ***** ******* ********* >>> for i in range(1,6): print('*' * i) * ** *** **** ***** >>> for i in range(1,6): print(' ' * (6-i) + '*' * (2*i + 1)) *** ***** ******* ********* *********** >>> for i in range(1,6): print(' ' * (6-i) + '*' * (2*i - 1)) * *** ***** ******* ********* >>> for i in reversed(range(1,6)): print(' ' * (6-i) + '*' * (2*i - 1)) ********* ******* ***** *** * >>>

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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import sys import os import shutil import lmdb import unittest import tempfile from caffe2.proto import caffe2_pb2 from caffe2.python import workspace, cnn import numpy as np class VideoInputOpTest(unittest.TestCase): def create_a_list(self, output_file, line, n): # create a list that repeat a line n times # used for creating a list file for simple test input with open(output_file, 'w') as file: for _i in range(n): file.write(line) def create_video_db(self, list_file, output_file, use_list=False): # Write to lmdb database... LMDB_MAP_SIZE = 1 << 40 # MODIFY env = lmdb.open(output_file, map_size=LMDB_MAP_SIZE) total_size = 0 file_name = [] start_frame = [] label = [] index = 0 with env.begin(write=True) as txn: with open(list_file, 'r') as data: for line in data: p = line.split() file_name = p[0] start_frame = int(p[1]) label = int(p[2]) if not use_list: with open(file_name, mode='rb') as file: video_data = file.read() else: video_data = file_name tensor_protos = caffe2_pb2.TensorProtos() video_tensor = tensor_protos.protos.add() video_tensor.data_type = 4 # string data video_tensor.string_data.append(video_data) label_tensor = tensor_protos.protos.add() label_tensor.data_type = 2 label_tensor.int32_data.append(label) start_frame_tensor = tensor_protos.protos.add() start_frame_tensor.data_type = 2 start_frame_tensor.int32_data.append(start_frame) txn.put( '{}'.format(index).encode('ascii'), tensor_protos.SerializeToString() ) index = index + 1 total_size = total_size + len(video_data) + sys.getsizeof(int) return total_size def test_read_from_db(self): random_label = np.random.randint(0, 100) VIDEO = "/mnt/vol/gfsdataswarm-oregon/users/trandu/sample.avi" temp_list = tempfile.NamedTemporaryFile(delete=False).name line_str = '{} 0 {}\n'.format(VIDEO, random_label) self.create_a_list( temp_list, line_str, 16) video_db_dir = tempfile.mkdtemp() self.create_video_db(temp_list, video_db_dir) model = cnn.CNNModelHelper(name="Video Loader from LMDB") reader = model.CreateDB( "sample", db=video_db_dir, db_type="lmdb") model.VideoInput( reader, ["data", "label"], name="data", batch_size=10, width=171, height=128, crop=112, length=8, sampling_rate=2, mirror=1, use_local_file=0, temporal_jitter=1) workspace.RunNetOnce(model.param_init_net) workspace.RunNetOnce(model.net) data = workspace.FetchBlob("data") label = workspace.FetchBlob("label") np.testing.assert_equal(label, random_label) np.testing.assert_equal(data.shape, [10, 3, 8, 112, 112]) os.remove(temp_list) shutil.rmtree(video_db_dir) if __name__ == "__main__": unittest.main()

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amitks815/pycode

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import re list1=[] with open ("file.txt") as f : #content=f.readlines() for line in f.readlines(): list1.append(line) print(list1) pattern=(r'[A-za-z0-9.]+@[A-za-z0-9]+.[A-za-z]+') for val in list1: matches=re.search(pattern,val) if matches: print(matches.group(0))

[ "42370714+amitks815@users.noreply.github.com" ]

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/forH4G/h4gFittingTools/MyCMSStyle.py

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bmarzocc/Scripts

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refs/heads/master

2023-03-22T13:40:43.987502

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from ROOT import * def SetAxisTextSizes(obj, yoff=0, ysize=1, xoff=0, xsize=1): obj.GetYaxis().SetTitleOffset(1.1+yoff) obj.GetYaxis().SetTitleSize(0.0425*ysize) obj.GetYaxis().SetLabelSize(0.04*ysize) obj.GetXaxis().SetTitleOffset(1.1+xoff) obj.GetXaxis().SetTitleSize(0.0425*xsize) obj.GetXaxis().SetLabelSize(0.04*xsize) try: obj.GetZaxis().SetTitleOffset(1.1) obj.GetZaxis().SetTitleSize(0.0425) obj.GetZaxis().SetLabelSize(0.04) except AttributeError: a=1 def SetGeneralStyle(): gStyle.SetFrameLineWidth(2) def SetPadStyle(obj): obj.SetTicky() obj.SetTickx() def DrawCMSLabels(obj, lumi=''): pad = obj.cd() l = pad.GetLeftMargin() t = pad.GetTopMargin() r = pad.GetRightMargin() b = pad.GetBottomMargin() lat = TLatex() lat.SetTextSize(0.045) lat.SetTextAlign(11) lat.SetTextFont(42) cmsTag = "#bf{CMS}" lumiTag = lumi+' fb^{-1} (13 TeV)' if lumi == '': cmsTag = "#bf{CMS} #it{Simulation}" lumiTag = '(13 TeV)' lat.DrawLatexNDC(l+0.01, 1-t+0.02, cmsTag) lat.SetTextAlign(31) lat.DrawLatexNDC(1-r-0.001, 1-t+0.02, lumiTag)

[ "wamorkar.t@husky.neu.edu" ]

wamorkar.t@husky.neu.edu

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/model-optimizer/extensions/front/tf/InterpolateTransposes.py

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anton-potapov/openvino

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refs/heads/master

2023-04-27T16:34:50.724901

2020-06-10T11:13:08

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""" Copyright (C) 2018-2020 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import numpy as np from mo.front.common.partial_infer.utils import int64_array from mo.front.tf.replacement import FrontReplacementFromConfigFileGeneral from mo.graph.graph import Graph, Node from mo.middle.pattern_match import find_pattern_matches, inverse_dict class InterpolateTranspose(FrontReplacementFromConfigFileGeneral): """ Delete useless transposes around ResizeNearestNeighbor op. In TF this op is working in NHWC layout, Resample in OpenVINO working in NCHW layout. If all graph has NCHW layout we should delete transposes around Resample: (NCHW->NHWC) -> Resample -> (NHWC -> NCHW) to run this op in NCHW without changes of layout. """ enabled = True replacement_id = 'InterpolateTranspose' graph_condition = [lambda graph: graph.graph['layout'] == 'NCHW'] pattern_nodes = [ ('interpolate', {'kind': 'op', 'op': 'Interpolate'}), ('transpose_1', {'kind': 'op', 'op': 'Transpose'}), ('transpose_1_order', {'kind': 'op', 'op': 'Const', 'value': lambda x: x is not None and np.array_equal(x, int64_array([0, 2, 3, 1]))}), ('transpose_2', {'kind': 'op', 'op': 'Transpose'}), ('transpose_2_order', {'kind': 'op', 'op': 'Const', 'value': lambda x: x is not None and np.array_equal(x, int64_array([0, 3, 1, 2]))}), ] pattern_edges = [ ('transpose_1', 'interpolate', {'in': 0, 'out': 0}), ('transpose_1_order', 'transpose_1', {'in': 1, 'out': 0}), ('interpolate', 'transpose_2', {'in': 0, 'out': 0}), ('transpose_2_order', 'transpose_2', {'in': 1, 'out': 0}), ] def transform_graph(self, graph: Graph, replacement_descriptions: dict): matches = find_pattern_matches(graph, self.pattern_nodes, self.pattern_edges) for match in list(matches): inverse_match = inverse_dict(match) interpolate = Node(graph, inverse_match['interpolate']) transpose_1 = Node(graph, inverse_match['transpose_1']) transpose_2 = Node(graph, inverse_match['transpose_2']) # because we remove Transpose layers the ResizeNearestNeighbor should be updated for NCHW layout interpolate.axes = int64_array([2, 3]) transpose_1.in_port(0).get_connection().set_destination(interpolate.in_port(0)) transpose_2.out_port(0).get_connection().set_source(interpolate.out_port(0)) graph.remove_nodes_from([transpose_1.id, transpose_2.id])

[ "alexey.suhov@intel.com" ]

alexey.suhov@intel.com

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[]

no_license

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refs/heads/master

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# to get new file map a place to a position on map import pandas as pd import numpy as np from PIL import Image import matplotlib.pyplot as plt nflis_path="../MCM_NFLIS_Data.xlsx" nflis_df=pd.read_excel(nflis_path,sheet_name="Data") zipcode_path='../zipcode.csv' zipcode_df=pd.read_csv(zipcode_path) zipcode_df=zipcode_df.rename(columns={'city':'county','state':'state','latitude':'latitude',\ 'longitude':'longitude'}) #further process nflis nflis_df=nflis_df.rename(columns={'COUNTY':'county','State':'state','FIPS_County':'fips_county',\ 'FIPS_State':'fips_state','TotalDrugReportsCounty':'county_report'}) tmp_year=2017 nflis_df=nflis_df.loc[nflis_df['YYYY']==tmp_year] nflis_df=nflis_df[['county','state','county_report']] nflis_df=nflis_df.groupby(['county','state']).mean().reset_index() #convert to upper zipcode_county=zipcode_df['county'] zipcode_county=zipcode_county.str.upper() zipcode_df['county']=zipcode_county # print(zipcode_df) map_df=pd.merge(nflis_df,zipcode_df,how='left',on=['county','state']) map_df=map_df.drop_duplicates(subset=['county','state'],keep='first') map_df=map_df.dropna(axis=0,how='any') map_df=map_df[['county','state','latitude','longitude','county_report']] # map_df.to_csv('county2position.csv') longitude_list=map_df['longitude'].tolist() longitude_list=np.array(longitude_list) # print(longitude_list) max_longitude=longitude_list.max() min_longitude=longitude_list.min() horizon_start=0 horizon_end=99 k_longitude=(horizon_end-horizon_start)/(max_longitude-min_longitude) b_longitude=horizon_start-k_longitude*min_longitude # print(k_longitude) latitude_list=map_df['latitude'].tolist() latitude_list=np.array(latitude_list) # print(longitude_list) max_latitude=latitude_list.max() min_latitude=latitude_list.min() vertical_start=0 vertical_end=99 k_latitude=(vertical_end-vertical_start)/(max_latitude-min_latitude) b_latitude=vertical_start-k_latitude*min_latitude img_arr=np.zeros((100,100)) for row in map_df.iterrows(): row=row[1] tmp_longitude=row['longitude'] tmp_latitude=row['latitude'] tmp_county_report=row['county_report'] tmp_horizon=k_longitude*tmp_longitude+b_longitude tmp_vertical=k_latitude*tmp_latitude+b_latitude tmp_vertical=int(tmp_vertical+0.1) tmp_horizon=int(tmp_horizon+0.1) img_arr[tmp_horizon][tmp_vertical]=tmp_county_report img = Image.fromarray(img_arr) img=img.convert('L') img.show() img.save(str(tmp_year)+'_img.jpg') # print(map_df)

[ "weixinluwx@foxmail.com" ]

weixinluwx@foxmail.com

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/xlsxwriter/test/comparison/test_chart_size02.py

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[ "BSD-2-Clause-Views" ]

permissive

projectsmahendra/XlsxWriter

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refs/heads/master

2023-07-21T19:40:41.103336

2023-07-08T16:54:37

353,636,960

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NOASSERTION

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2021-04-01T08:57:20

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py

############################################################################### # # Tests for XlsxWriter. # # Copyright (c), 2013-2021, John McNamara, jmcnamara@cpan.org # from ..excel_comparison_test import ExcelComparisonTest from ...workbook import Workbook class TestCompareXLSXFiles(ExcelComparisonTest): """ Test file created by XlsxWriter against a file created by Excel. """ def setUp(self): self.set_filename('chart_size01.xlsx') def test_create_file(self): """Test XlsxWriter chartarea properties.""" workbook = Workbook(self.got_filename) worksheet = workbook.add_worksheet() chart = workbook.add_chart({'type': 'column'}) chart.axis_ids = [61355904, 61365248] data = [ [1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [3, 6, 9, 12, 15], ] worksheet.write_column('A1', data[0]) worksheet.write_column('B1', data[1]) worksheet.write_column('C1', data[2]) chart.add_series({'values': '=Sheet1!$A$1:$A$5'}) chart.add_series({'values': '=Sheet1!$B$1:$B$5'}) chart.add_series({'values': '=Sheet1!$C$1:$C$5'}) chart.set_size({'x_scale': 1.066666666, 'y_scale': 1.11111111}) worksheet.insert_chart('E9', chart) workbook.close() self.assertExcelEqual()

[ "jmcnamara@cpan.org" ]

jmcnamara@cpan.org

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/tests/test_npc_cli/test_describe/test_describe_systems_cmd.py

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[ "MIT" ]

permissive

aurule/npc

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refs/heads/develop

2023-09-02T02:46:47.900892

2023-08-30T17:31:00

47,045,977

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2

MIT

2023-08-18T20:49:12

2015-11-29T01:40:18

Python

UTF-8

Python

false

590

py

from click.testing import CliRunner from tests.fixtures import tmp_campaign from npc_cli import cli def test_shows_system_name(tmp_path): runner = CliRunner() with runner.isolated_filesystem(temp_dir=tmp_path): result = runner.invoke(cli, ['describe', 'systems']) assert "New World of Darkness" in result.output def test_shows_current_campaign_system(tmp_campaign): runner = CliRunner() with runner.isolated_filesystem(temp_dir=tmp_campaign.root): result = runner.invoke(cli, ['describe', 'systems']) assert "Currently using" in result.output

[ "paige.andrews@modolabs.com" ]

paige.andrews@modolabs.com

bbb794515424fcae3a62640604b057d36412e869

2e74cff6c9639f3903ccde662e79359d0724285e

/2019_late/20190920/swea_5188_최소합.py

73b522689d9b934a03bfafa00236176b182caa0d

[]

no_license

dodonmountain/algorithm

e29988071f651e51ba65e3926302f94a3d4074a5

ce33e0d74220839aed4b17a47fa0069458a4324e

refs/heads/master

2022-11-05T05:14:01.527015

2022-11-01T04:29:37

200,008,533

0

null

UTF-8

Python

false

986

py

import sys sys.stdin = open('5188.txt') dx, dy = (1,0), (0,1) def dfs(h,c): global tmp if h == (N-1,N-1): if c < tmp: tmp = c return for i in range(2): nx, ny = h[0], h[1] if 0 <= h[0] + dx[i] < N: nx = h[0] + dx[i] if 0 <= h[1] + dy[i] < N: ny = h[1] + dy[i] if not visit[nx][ny]: if c+board[nx][ny] <= tmp: visit[nx][ny] = 1 dfs((nx,ny),c+board[nx][ny]) visit[nx][ny] = 0 for t_case in range(int(input())): N = int(input()) board,pp,ll = [],0,0 for _ in range(N): board.append(list(map(int, input().split()))) for i in range(1, N): pp += board[i][N-1];ll += board[i][0] if sum(board[0])+ pp > sum(board[N-1]) + ll: tmp = sum(board[N-1]) + ll tmp = sum(board[0]) + pp visit = [[0] * N for _ in range(N)] dfs((0,0),board[0][0]) print('#{} {}'.format(t_case+1, tmp))

[ "lkh151515@gmail.com" ]

lkh151515@gmail.com

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/aliyun/api/rest/Ram20140214AddUserRequest.py

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snowyxx/aliyun-python-demo

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refs/heads/master

2021-01-10T03:37:31.657793

2016-01-21T02:03:14

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py

''' Created by auto_sdk on 2015.01.27 ''' from aliyun.api.base import RestApi class Ram20140214AddUserRequest(RestApi): def __init__(self,domain='ram.aliyuncs.com',port=80): RestApi.__init__(self,domain, port) self.AccountSpace = None self.Comments = None self.UserName = None def getapiname(self): return 'ram.aliyuncs.com.AddUser.2014-02-14'

[ "snowyxx@126.com" ]

snowyxx@126.com

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/home/migrations/0005_remove_page_is_footer_1.py

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[]

no_license

Fabricourt/school

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refs/heads/main

2023-01-01T15:48:43.760288

2020-10-26T11:15:32

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py

# Generated by Django 3.1.2 on 2020-10-17 13:07 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('home', '0004_auto_20201017_1552'), ] operations = [ migrations.RemoveField( model_name='page', name='is_footer_1', ), ]

[ "mfalme2030@gmail.com" ]

mfalme2030@gmail.com

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/p847h/shorest_path_length.py

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l33tdaima/l33tdaima

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refs/heads/main

2023-07-20T21:52:26.330301

2023-07-19T02:30:22

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MIT

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2017-08-06T19:44:29

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py

from cmath import exp from curses.ascii import SO class Solution: def shortestPathLength(self, graph: list[list[int]]) -> int: memo, final, steps = set(), (1 << len(graph)) - 1, 0 queue = [(i, 1 << i) for i in range(len(graph))] while True: new = [] for node, state in queue: if state == final: return steps for v in graph[node]: if (v, state | 1 << v) not in memo: new.append((v, state | 1 << v)) memo.add((v, state | 1 << v)) queue = new steps += 1 # TESTS for graph, expected in [ ([[1, 2, 3], [0], [0], [0]], 4), ([[1], [0, 2, 4], [1, 3, 4], [2], [1, 2]], 4), ]: sol = Solution() actual = sol.shortestPathLength(graph) print("Shortest path to visit all nodes in", graph, "->", actual) assert actual == expected

[ "l33tdaima@github.com" ]

l33tdaima@github.com

62f9354ab6fcf808aef2ae3afc2deb20f08226ab

89d5dbd7672d9e03e7ca5277a9fd942b2444db86

/Advance python/08_global_local_variable.py

c69f04343d0079f2abeadbbb65295b89401249d5

[]

no_license

rameshparajuli-github/python-programming

6ff218d4d1cdde73a578e4f2f3ba6241310d6408

5d2638a24e8b50614f2c15f04eb1f00dba0f6175

refs/heads/master

2023-06-17T18:40:47.797595

2021-07-16T14:02:52

386,656,247

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0

null

UTF-8

Python

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py

a=54 # Global Variable def func1(): global a # This line change Global variable print(f"This statement:{a}") a=9 # Local Variable # yadi teo mathi ko global a use nagareko vaya yo line ma 54 naii print hunthyo print(f"This statement:{a}") func1() print(f"This statement:{a}")

[ "susmitscore619@gmail.com" ]

susmitscore619@gmail.com

3a40a65282330a85aeb70fd636c76af7cc562d0b

a7a29bc1643e14ae74f95d0b6695de32b6d6cfb5

/0x0B-python-input_output/1-number_of_lines.py

148a4fadbe23197c0272795e3bbb6c927d9f17e7

[]

no_license

ToqYang/holbertonschool-higher_level_programming

95752a663307534e16d57a73cc4a8b0170f86614

862f88652619711eb0d1c7f821467b15d3f9b7cf

refs/heads/master

2020-07-23T01:41:19.574505

2020-02-14T04:46:35

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1

0

null

UTF-8

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false

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py

#!/usr/bin/python3 """ Read a file """ def number_of_lines(filename=""): """ Received the filename for it can does a syscall for read the file Return: Counter of the lines""" count = 0 with open(filename, mode="r", encoding="utf-8") as fil: for line in fil: count += 1 return count

[ "santitoya-2001@outlook.com" ]

santitoya-2001@outlook.com

caf49e720e7a11db13c00411024b3f18209fde61

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/Lib/site-packages/phonenumbers/shortdata/region_PW.py

2b53f97da4c5bba6ee25876c99a74d7e9f7544e6

[]

no_license

GlovesMaker/Sklepinternetowy

4459f8651d2280e4840cfb293de28f9413df68af

d05372e96f7238c9459caf4f7a890a5a6f2bb2c3

refs/heads/master

2022-12-22T02:43:33.628016

2018-09-11T18:20:37

167,855,928

0

1

null

2022-12-08T05:55:04

2019-01-27T20:36:42

Python

UTF-8

Python

false

548

py

"""Auto-generated file, do not edit by hand. PW metadata""" from ..phonemetadata import NumberFormat, PhoneNumberDesc, PhoneMetadata PHONE_METADATA_PW = PhoneMetadata(id='PW', country_code=None, international_prefix=None, general_desc=PhoneNumberDesc(national_number_pattern='9\\d\\d', possible_length=(3,)), emergency=PhoneNumberDesc(national_number_pattern='911', example_number='911', possible_length=(3,)), short_code=PhoneNumberDesc(national_number_pattern='911', example_number='911', possible_length=(3,)), short_data=True)

[ "buchar123@gmail.com" ]

buchar123@gmail.com

9a4ba82eb6c3c0b5c1df859b72e504c966f1763a

74482894c61156c13902044b4d39917df8ed9551

/test/test_tokens_forwarding_fail_data_item.py

ce8cc93181cac7dc8210c609b3d54fa4af76f3a7

[ "MIT" ]

permissive

xan187/Crypto_APIs_2.0_SDK_Python

bb8898556ba014cc7a4dd31b10e24bec23b74a19

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refs/heads/main

2023-06-22T15:45:08.273635

2021-07-21T03:41:05

387,982,780

1

0

NOASSERTION

2021-07-21T03:35:29

null

UTF-8

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false

1,274

py

""" CryptoAPIs Crypto APIs 2.0 is a complex and innovative infrastructure layer that radically simplifies the development of any Blockchain and Crypto related applications. Organized around REST, Crypto APIs 2.0 can assist both novice Bitcoin/Ethereum enthusiasts and crypto experts with the development of their blockchain applications. Crypto APIs 2.0 provides unified endpoints and data, raw data, automatic tokens and coins forwardings, callback functionalities, and much more. # noqa: E501 The version of the OpenAPI document: 2.0.0 Contact: developers@cryptoapis.io Generated by: https://openapi-generator.tech """ import sys import unittest import cryptoapis from cryptoapis.model.tokens_forwarding_fail_data_item import TokensForwardingFailDataItem class TestTokensForwardingFailDataItem(unittest.TestCase): """TokensForwardingFailDataItem unit test stubs""" def setUp(self): pass def tearDown(self): pass def testTokensForwardingFailDataItem(self): """Test TokensForwardingFailDataItem""" # FIXME: construct object with mandatory attributes with example values # model = TokensForwardingFailDataItem() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "kristiyan.ivanov@menasoftware.com" ]

kristiyan.ivanov@menasoftware.com

ad96a6a7aee94d1afcd1bceb24d8af138afdff98

a3d6556180e74af7b555f8d47d3fea55b94bcbda

/third_party/fuchsia-gn-sdk/src/gn_run_binary.py

b39f49b5c30357b323b41f6911d8d6f0b7c05077

[ "GPL-1.0-or-later", "MIT", "LGPL-2.0-or-later", "Apache-2.0", "LicenseRef-scancode-unknown-license-reference", "BSD-2-Clause", "BSD-3-Clause" ]

permissive

chromium/chromium

aaa9eda10115b50b0616d2f1aed5ef35d1d779d6

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refs/heads/main

2023-08-24T00:35:12.585945

2023-08-23T22:01:11

120,360,765

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7,102

BSD-3-Clause

2023-09-10T23:44:27

2018-02-05T20:55:32

null

UTF-8

Python

false

720

py

#!/usr/bin/env python3.8 # Copyright 2019 The Fuchsia Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Helper script for GN to run an arbitrary binary. Run with: python3.8 gn_run_binary.py <binary_name> [args ...] """ import os import subprocess import sys # This script is designed to run binaries produced by the current build. We # may prefix it with "./" to avoid picking up system versions that might # also be on the path. path = sys.argv[1] if not os.path.isabs(path): path = './' + path # The rest of the arguments are passed directly to the executable. args = [path] + sys.argv[2:] sys.exit(subprocess.call(args))

[ "chromium-scoped@luci-project-accounts.iam.gserviceaccount.com" ]

chromium-scoped@luci-project-accounts.iam.gserviceaccount.com

9bd8e8da9f5987759171e2b03d02241ddba91fc8

a96bbc3da8557e68cb01db671b930fec9f46c0c2

/blog/migrations/0005_comment.py

2c007c09ada8afc58aec82f33ab624bfc2cadb43

[]

no_license

winterash2/django_first_blog

dd3de9f01f8e2b2df21fba9cd3d636c6fbd94fd1

06f059570ae5851db97b5c7f9b9d043da033c023

refs/heads/master

2022-11-26T18:44:47.316248

2020-08-10T09:10:16

286,345,428

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1

null

UTF-8

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py

# Generated by Django 3.0.9 on 2020-08-07 02:01 from django.db import migrations, models import django.db.models.deletion import django.utils.timezone class Migration(migrations.Migration): dependencies = [ ('blog', '0004_auto_20200806_1540'), ] operations = [ migrations.CreateModel( name='Comment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('author', models.CharField(max_length=200)), ('text', models.TextField()), ('created_date', models.DateTimeField(default=django.utils.timezone.now)), ('approved_comment', models.BooleanField(default=False)), ('post', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='comments', to='blog.Post')), ], ), ]

[ "winterash2@naver.com" ]

winterash2@naver.com

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/system/python_stubs/-745935208/PySide2/QtGui/QTextBlockUserData.py

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[]

no_license

sidbmw/PyCharm-Settings

a71bc594c83829a1522e215155686381b8ac5c6e

083f9fe945ee5358346e5d86b17130d521d1b954

refs/heads/master

2020-04-05T14:24:03.216082

2018-12-28T02:29:29

156,927,399

0

null

UTF-8

Python

false

595

py

# encoding: utf-8 # module PySide2.QtGui # from C:\Users\siddh\AppData\Local\Programs\Python\Python37\lib\site-packages\PySide2\QtGui.pyd # by generator 1.146 # no doc # imports import PySide2.QtCore as __PySide2_QtCore import Shiboken as __Shiboken class QTextBlockUserData(__Shiboken.Object): # no doc def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass

[ "siddharthnatamai@gmail.com" ]

siddharthnatamai@gmail.com

3772b803daea556dbaca21372e0a9c473332e531

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/sCH5gcyoRqq3Gfzyi_12.py

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[]

no_license

daniel-reich/turbo-robot

feda6c0523bb83ab8954b6d06302bfec5b16ebdf

a7a25c63097674c0a81675eed7e6b763785f1c41

refs/heads/main

2023-03-26T01:55:14.210264

2021-03-23T16:08:01

350,773,815

0

null

UTF-8

Python

false

474

py

""" Create a function which validates whether a given number exists, and could represent a real life quantity. Inputs will be given as a string. ### Examples valid_str_number("3.2") ➞ True valid_str_number("324") ➞ True valid_str_number("54..4") ➞ False valid_str_number("number") ➞ False ### Notes Accept numbers such as `.5` and `0003`. """ import re def valid_str_number(s): return bool(re.fullmatch('\d*\.?\d*', s))

[ "daniel.reich@danielreichs-MacBook-Pro.local" ]

daniel.reich@danielreichs-MacBook-Pro.local

fb33dce1897d5dc122db0542d61b43b2317c257a

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/468.py

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[]

no_license

zenmeder/leetcode

51a0fa4dc6a82aca4c67b5f4e0ee8916d26f976a

0fddcc61923d760faa5fc60311861cbe89a54ba9

refs/heads/master

2020-12-02T18:16:10.825121

2018-10-30T11:47:53

96,505,735

0

null

UTF-8

Python

false

776

py

#!/usr/local/bin/ python3 # -*- coding:utf-8 -*- # __author__ = "zenmeder" class Solution(object): def validIPAddress(self, IP): """ :type IP: str :rtype: str """ if self.isIPV4(IP): return "IPv4" elif self.isIPV6(IP): return "IPv6" else: return "Neither" def isIPV4(self, IP): ip = IP.split('.') if len(ip) != 4: return False for num in ip: if '0' <= num <= '255' and (num[0] != '0' or num == '0') and len(num) <= 3: continue else: return False return True def isIPV6(self, IP): ip = IP.split(':') if len(ip) != 8: return False for num in ip: print(num) if '0' <= num.upper() <= 'FFFF' and len(num) <= 4: continue else: return False return True print(Solution().validIPAddress("192.0.0.1"))

[ "zenmeder@gmail.com" ]

zenmeder@gmail.com

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/kinl.py

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jyothiesai/guvij

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fdcd29f5548c12095f259ff2f74024317787b110

refs/heads/master

2020-04-16T01:42:44.848569

2019-08-07T13:24:44

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#jyothi n,k=raw_input().split(' ') n,k=int(n),int(k) l=[int(x) for x in raw_input().split(' ')] if k in l: print('yes') else: print('no')

[ "noreply@github.com" ]

jyothiesai.noreply@github.com

6801ecc4ad1ea58b5cafd1fd372f067ab59d8863

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/New LeetCode Problems/remove_outermost_parens.py

669927e0a71b7d1f372ff3cddc03ce00f0133f34

[]

no_license

matthewharrilal/CS-Questions-GRIND

cac1cb562e5dad79ee4e224895d034f9c71d9ed3

7196c5e8df495d43ee91f218d6253c8a88a7d59d

refs/heads/master

2020-04-16T01:30:53.289837

2019-07-24T04:34:21

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# https://leetcode.com/problems/remove-outermost-parentheses/ # def removeOuterParentheses(self, S): # """ # :type S: str # :rtype: str # """

[ "matthewharrilal@gmail.com" ]

matthewharrilal@gmail.com

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/PYTHON/EJERCICIOS/TEMA 5/COMPIS/017_G8-Carla Guillén Pingarrón_638450_assignsubmission_file_/S5_G8.py

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[]

no_license

enanibus/biopython

3a58efbcc92f1ce60285a115c620de9295b7d281

613d334a5c0502059930d9381a9464ef533cca1c

refs/heads/master

2021-01-12T17:27:39.516793

2017-01-02T18:30:09

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##Group 8: Álvaro Alfayate, Andrea de la Fuente, Carla Guillén y Jorge Nuevo. def ReadFasta(FileName): ##Definimos una función que lea el archivo FASTA elegidoy extraiga la información requerida MyFile=open(FileName,'r') ReadSeq='' #Una variable vacia que va a almacenar el Fasta leído for Line in MyFile: ##Unimos todas las líneas del fasta. if '>' in Line: ##Si es la primera línea definimos esta condición #No hacemos un strip para poder separar la primera línea de la secuencia por un \n ReadSeq=ReadSeq+Line #Añadimos la primera línea con el \n else: Line=Line.strip().upper() #Con la secuencia si hacemos strip, para unir toda la secuencia junta. ReadSeq=ReadSeq+Line MySeq_RE=r'([NX]M_\d+\.\d).+\n([AGCT]+)' #Definimos la expresión regular que nos extrae por un lado el accession number y por otro la secuencia. MySeq_Comp=re.compile(MySeq_RE) SeqInfo=MySeq_Comp.search(ReadSeq).groups() #Buscamos nuestra expresión regular en la secuencia leída y sacamos los grupos. return (SeqInfo) ##SeqInfo es una lista donde el primer elemento es el accesion number y el segundo la secuencia de DNA MyFile.close() def CreateDictionary(DicFile): ##Definimos una función que crea diccionarios a partir del archivo que le pasemos. MyFile=open(DicFile,'r') MyDic_RE=r'([ATGC]{3})\t([^BJUXZ])\t([A-Z][a-z]{2})' ##Definimos una expresión variable que saca por un lado el codon, por otro los aminoácidos (en ambos códigos) MyDic_Comp=re.compile(MyDic_RE) Data2='' GENCODE={} for Line in MyFile: ##Recorremos todas las líneas del archivo y las unimos en Data 2 Data2=Data2+Line.strip() MyRes2=MyDic_Comp.findall(Data2) ##Busca en Data2 todos los elementos que cumplen la secuencia consenso y los almacena en MyRes2 como una lista de listas (2D) x=0 for n in range(0,len(MyRes2)):##Durante la longitud de la lista MyRes2 va a ejecutar este bloque de código. GENCODE[MyRes2[x][0]]=MyRes2[x][1:] #Forma un diccionario recorriendo todas las líneas del archivo (que corresponden a la primera dimensión de la lista) x+=1 #Avanzamos una posición en la primera dimensión --> A la siguiente línea del archivo de código genético return (GENCODE) MyFile.close() def ComplementaryGenerator(SeqName): #Creamos una función que nos devuelve la hebra complementaria de la secuencia de la primera función SeqReverse=SeqName[::-1] ##Se invierte la secuencia, de forma que se va a leer la secuencia + en dirección 3'-5' SeqComplementary='' ##Se genera la variable donde se almacenará la secuencia complementaria GenCode={'A':'T','C':'G','G':'C','T':'A'} ##Diccionario con los nucleótidos complementarios for Nucleotide in SeqReverse: ##Vamos itinerando por cada nucleótido de la secuencia ##Se van añadiendo los nucleótidos complementarios 1 a 1 en nuestra variable, generando la secuencia complementaria en dirección 5'-3'. SeqComplementary=SeqComplementary+GenCode[Nucleotide] return(SeqComplementary) ##Ahora SeqComplementary será la variable resultado de correr esta función. def TranslateDNA(DNASeq,COMPSEQ,DicFile,ExportName): MyFile=open(ExportName+'.txt','w') Counter='+' #Declaramos Seq como +. Es un contador de en qué secuencia estamos for Seq in (DNASeq,COMPSEQ): if Counter=='+': ##Al empezar estamos en la secuencia + print('\t\t\t\t\t\t\t\t\t\tPLUS STRAND\n') MyFile.write('\t\t\t\t\t\t\t\t\t\tPLUS STRAND\n') if Counter=='-': #Para que escriba Minus Strand en este caso MyFile.write('\n\t\t\t\t\t\t\t\t\t\tMINUS STRAND\n\n') print('\n\t\t\t\t\t\t\t\t\t\tMINUS STRAND\n\n') for CodingFrame in range(0,3): #Bucle para leer en las tres pautas de lectura ProtSeq='' MyFile.write('\n\t\t\t\t\t\t\t\t\t\t Frame '+str(CodingFrame+1)+'\n\n')#Escribe el Frame en el que está (Sumando +1 pues el rango empieza en 0) print('\n\t\t\t\t\t\t\t\t\t\t Frame '+str(CodingFrame+1)+'\n\n') while True: if CodingFrame>(((len(Seq)/3)-1)*3): ##Esta condición permite correr el código hasta que se alcanza el final de la secuencia. break SubSeq=Seq[CodingFrame]+Seq[CodingFrame+1]+Seq[CodingFrame+2] ##Formamos el codón y lo asignamos a SubSeq. ProtSeq=ProtSeq+DicFile[SubSeq][0] ##Traducimos el codón actual a código de una letra y lo añadimos a la secuencia traducida que ya estuviera. CodingFrame+=3 #Movemos 3 nucleótidos para leer el siguiente codón print(ProtSeq) MyFile.write(ProtSeq+'\n') #Escribimos la secuencia Counter='-' #Cuando terminamos el bloque con SeqName, para la empezar con la reversa Seq será - MyFile.close() def Body(): DNAList=ReadFasta(sys.argv[1]) #Lista que contiene el DNA y el Accession number GenCode=CreateDictionary('GeneticCode_standard.csv') CompSeq=ComplementaryGenerator(DNAList[1]) #CompSeq contiene ahora la secuencia complementaria correspondente de llamar la función ComplementaryGenerator Protein=TranslateDNA(DNAList[1],CompSeq,GenCode,DNAList[0]) ##DNAList[1] contiene la secuencia de DNA extraida y DNAList[0] el Accession Number if __name__=='__main__': import sys import re if len(sys.argv)<2: print('Please, introduce as an argument the file you want to translate.') #Si no nos introduce el argumento con la secuencia, se lo pide. if not('.fasta') in sys.argv[1]: #Si introducimos como argumento un archivo que no es fasta te indica que introduzcas un fasta print('You have to introduce a fasta sequence') else: Body()

[ "juanenriqueztraba@gmail.com" ]

juanenriqueztraba@gmail.com

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/leetcode/241. Different Ways to Add Parentheses/Python3/diff_ways.py

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bryand1/solutions

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2021-07-09T08:39:45.301754

2019-03-01T16:31:36

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from operator import add, sub, mul op = {'+': add, '-': sub, '*': mul} class Solution: def diffWaysToCompute(self, expr): """ :type input: str :rtype: List[int] """ arr = self.parse(expr) return self.diffWaysToComputeRec(arr, 0, len(arr)) def diffWaysToComputeRec(self, arr, lo, hi): if hi - lo == 1: return [arr[lo]] res = [] for i in range(lo + 1, hi, 2): op = arr[i] lhs = self.diffWaysToComputeRec(arr, lo, i) rhs = self.diffWaysToComputeRec(arr, i + 1, hi) for a in lhs: for b in rhs: res.append(op(a, b)) return res def parse(self, expr): res = [] n = 0 for char in expr: if char.isdigit(): n = 10 * n + int(char) else: res.append(n) n = 0 res.append(op[char]) res.append(n) return res

[ "bryand1@gmail.com" ]

bryand1@gmail.com

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/addons/purchase/models/stock_config_settings.py

f07bb2fa1319b3603ec86c3a653f03c531b9923b

[]

no_license

gahan-corporation/wyatt

3a6add8f8f815bd26643e1e7c81aea024945130d

77e56da362bec56f13bf0abc9f8cf13e98461111

refs/heads/master

2021-09-03T18:56:15.726392

2018-01-08T02:54:47

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# -*- coding: utf-8 -*- # Part of Odoo. See LICENSE file for full copyright and licensing details. from gerp import api, fields, models class ResConfigSettings(models.TransientModel): _inherit = 'res.config.settings' po_lead = fields.Float(related='company_id.po_lead') use_po_lead = fields.Boolean( string="Security Lead Time for Purchase", oldname='default_new_po_lead', help="Margin of error for vendor lead times. When the system generates Purchase Orders for reordering products,they will be scheduled that many days earlier to cope with unexpected vendor delays.") @api.onchange('use_po_lead') def _onchange_use_po_lead(self): if not self.use_po_lead: self.po_lead = 0.0 def get_values(self): res = super(ResConfigSettings, self).get_values() res.update( use_po_lead=self.env['ir.config_parameter'].sudo().get_param('purchase.use_po_lead') ) return res def set_values(self): super(ResConfigSettings, self).set_values() self.env['ir.config_parameter'].sudo().set_param('purchase.use_po_lead', self.use_po_lead)

[ "duchess@gahan-corporation.com" ]

duchess@gahan-corporation.com

a710d37abf1d105c4e455d43f64b6efdd6cb4977

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/saigon/rat/RuckusAutoTest/scripts/zd/ats_ZD_Combo_SNMP_V2_Continue_Walking.py

566d4e7bb980151a16a79e016fed8da87f2030ed

[]

no_license

jichunwei/MyGitHub-1

ae0c1461fe0a337ef459da7c0d24d4cf8d4a4791

f826fc89a030c6c4e08052d2d43af0b1b4b410e3

refs/heads/master

2021-01-21T10:19:22.900905

2016-08-20T03:34:52

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''' Continue walking via SNMP V2 Continue walking nodes many times, can get information correctly. 1. Continue walking system objects 50 times via SNMP V2, compare the information from SNMP and CLI. expect result: All steps should result properly. How to: 1) Get system information via ZD CLI 2) Continue walking system object 50 times, parsing the system result. 3) Compare the result for each walking are same 4) Compare the result from SNMP and CLI are same Created on 2011-4-14 @author: cherry.cheng@ruckuswireless.com ''' import sys import libZD_TestSuite as testsuite from RuckusAutoTest.common import lib_KwList as kwlist def define_test_cfg(tcfg): test_cfgs = [] test_name = 'CB_Scaling_ZD_CLI_Process_Check' common_name = 'apmgr and stamgr daemon pid mark' param_cfg = dict() test_cfgs.append((param_cfg, test_name, common_name, 0, False)) test_name = 'CB_ZD_CLI_Set_SNMP_Agent' common_name = 'Disable SNMP Agent Version 2' test_cfgs.append(({'snmp_agent_cfg': {'version': 2, 'enabled': False}}, test_name, common_name, 0, False)) test_name = 'CB_ZD_CLI_Set_SNMP_Agent' common_name = 'Disable SNMP Agent Version 3' test_cfgs.append(({'snmp_agent_cfg': {'version': 3, 'enabled': False}}, test_name, common_name, 0, False)) test_name = 'CB_ZD_CLI_Set_SNMP_Agent' common_name = 'Enable SNMP Agent Version 2' test_cfgs.append(({'snmp_agent_cfg':tcfg['set_snmp_agent_cfg']}, test_name, common_name, 0, False)) test_case_name = '[Continue Walking]' test_name = 'CB_ZD_CLI_Get_Sys_Basic_Info' common_name = '%sGet System Info via ZD CLI' % (test_case_name,) test_cfgs.append(( {}, test_name, common_name, 1, False)) test_name = 'CB_ZD_SNMP_Contine_Walking_Sys_Basic_Info' common_name = '%sVerify continue walking to get system basic info' % (test_case_name,) test_cfgs.append(( {'snmp_agent_cfg': tcfg['set_snmp_agent_cfg'], 'snmp_cfg': tcfg['snmp_cfg'], 'times': tcfg['times']}, test_name, common_name, 2, False)) test_name = 'CB_ZD_SNMP_Verify_Sys_Basic_Info_SNMPGet_CLIGet' common_name = '%sVerify System Info between SNMP Get and CLI Get' % (test_case_name,) test_cfgs.append(( {}, test_name, common_name, 2, False)) test_name = 'CB_Scaling_ZD_CLI_Process_Check' common_name = 'apmgr and stamgr daemon pid checking.' param_cfg = dict() test_cfgs.append((param_cfg, test_name, common_name, 0, False)) return test_cfgs def define_test_parameters(tbcfg): set_snmp_agent_cfg = {'version': 2, 'enabled': True, 'ro_community': 'public', 'rw_community': 'private', 'contact': 'support@ruckuswireless.com', 'location': 'shenzhen',} snmp_cfg = {#'ip_addr': tbcfg['ZD']['ip_addr'], 'timeout': 20, 'retries': 3,} tcfg = {'snmp_cfg': snmp_cfg, 'set_snmp_agent_cfg': set_snmp_agent_cfg, 'times': 50, } return tcfg def create_test_suite(**kwargs): tb = testsuite.getTestbed2(**kwargs) tbcfg = testsuite.getTestbedConfig(tb) if str(tb.tbtype) == "ZD_Stations_IPV6": zd_ip_version = tbcfg['ip_cfg']['zd_ip_cfg']['ip_version'] ap_ip_version = tbcfg['ip_cfg']['ap_ip_cfg']['ip_version'] ts_name = 'ZD SNMP V2 ZD %s AP %s - Continue Walking' % (zd_ip_version, ap_ip_version) else: ts_name = 'ZD SNMP V2 - Continue Walking' tcfg = define_test_parameters(tbcfg) ts = testsuite.get_testsuite(ts_name, 'Verify Continue Walking', combotest=True) test_cfgs = define_test_cfg(tcfg) test_order = 1 test_added = 0 for test_params, testname, common_name, exc_level, is_cleanup in test_cfgs: if testsuite.addTestCase(ts, testname, common_name, test_params, test_order, exc_level, is_cleanup) > 0: test_added += 1 test_order += 1 print "Add test case with test name: %s\n\t\common name: %s" % (testname, common_name) print "\n-- Summary: added %d test cases into test suite '%s'" % (test_added, ts.name) if __name__ == "__main__": _dict = kwlist.as_dict(sys.argv[1:]) create_test_suite(**_dict)

[ "tan@xx.com" ]

tan@xx.com

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/ShowAndSearch/__init__.py

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[ "Apache-2.0" ]

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2022-12-22T06:28:36.601500

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''' lanhuage: python Descripttion: version: beta Author: xiaoshuyui Date: 2020-09-15 13:53:11 LastEditors: xiaoshuyui LastEditTime: 2020-09-22 11:20:14 ''' __version__ = '0.0.0' __appname__ = 'show and search'

[ "528490652@qq.com" ]

528490652@qq.com

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/0x0F-python-object_relational_mapping/7-model_state_fetch_all.py

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[]

no_license

Caroll1889/holbertonschool-higher_level_programming

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f3c222c101e05bf5876951fc7a2566f3ce0ff7e6

refs/heads/master

2020-07-22T22:51:35.948398

2020-02-14T16:35:29

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#!/usr/bin/python3 """ """ from sys import argv from model_state import Base, State from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker import sqlalchemy if __name__ == "__main__": en = create_engine('mysql+mysqldb://{}:{}@localhost/{}'.format(argv[1], argv[2], argv[3])) Base.metadata.create_all(en) Session = sessionmaker(bind=en) session = Session() for states in session.query(State).order_by(State.id): print("{}: {}".format(states.id, states.name)) session.close()

[ "diahancaroll@hotmail.com" ]

diahancaroll@hotmail.com

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2023-02-20T12:05:14.980685

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import os import json from jedi._compatibility import FileNotFoundError, NotADirectoryError from jedi.api.environment import SameEnvironment, \ get_cached_default_environment from jedi.api.exceptions import WrongVersion from jedi._compatibility import force_unicode from jedi.evaluate.sys_path import discover_buildout_paths from jedi.evaluate.cache import evaluator_as_method_param_cache from jedi.common.utils import traverse_parents _CONFIG_FOLDER = '.jedi' _CONTAINS_POTENTIAL_PROJECT = 'setup.py', '.git', '.hg', 'requirements.txt', 'MANIFEST.in' _SERIALIZER_VERSION = 1 def _remove_duplicates_from_path(path): used = set() for p in path: if p in used: continue used.add(p) yield p def _force_unicode_list(lst): return list(map(force_unicode, lst)) class Project(object): # TODO serialize environment _serializer_ignore_attributes = ('_environment',) _environment = None @staticmethod def _get_json_path(base_path): return os.path.join(base_path, _CONFIG_FOLDER, 'project.json') @classmethod def load(cls, path): """ :param path: The path of the directory you want to use as a project. """ with open(cls._get_json_path(path)) as f: version, data = json.load(f) if version == 1: self = cls.__new__() self.__dict__.update(data) return self else: raise WrongVersion( "The Jedi version of this project seems newer than what we can handle." ) def __init__(self, path, **kwargs): """ :param path: The base path for this project. :param sys_path: list of str. You can override the sys path if you want. By default the ``sys.path.`` is generated from the environment (virtualenvs, etc). :param smart_sys_path: If this is enabled (default), adds paths from local directories. Otherwise you will have to rely on your packages being properly configured on the ``sys.path``. """ def py2_comp(path, environment=None, sys_path=None, smart_sys_path=True, _django=False): self._path = path if isinstance(environment, SameEnvironment): self._environment = environment self._sys_path = sys_path self._smart_sys_path = smart_sys_path self._django = _django py2_comp(path, **kwargs) def _get_base_sys_path(self, environment=None): if self._sys_path is not None: return self._sys_path # The sys path has not been set explicitly. if environment is None: environment = self.get_environment() sys_path = list(environment.get_sys_path()) try: sys_path.remove('') except ValueError: pass return sys_path @evaluator_as_method_param_cache() def _get_sys_path(self, evaluator, environment=None): """ Keep this method private for all users of jedi. However internally this one is used like a public method. """ suffixed = [] prefixed = [] sys_path = list(self._get_base_sys_path(environment)) if self._smart_sys_path: prefixed.append(self._path) if evaluator.script_path is not None: suffixed += discover_buildout_paths(evaluator, evaluator.script_path) traversed = list(traverse_parents(evaluator.script_path)) # AFAIK some libraries have imports like `foo.foo.bar`, which # leads to the conclusion to by default prefer longer paths # rather than shorter ones by default. suffixed += reversed(traversed) if self._django: prefixed.append(self._path) path = prefixed + sys_path + suffixed return list(_force_unicode_list(_remove_duplicates_from_path(path))) def save(self): data = dict(self.__dict__) for attribute in self._serializer_ignore_attributes: data.pop(attribute, None) with open(self._get_json_path(self._path), 'wb') as f: return json.dump((_SERIALIZER_VERSION, data), f) def get_environment(self): if self._environment is None: return get_cached_default_environment() return self._environment def __repr__(self): return '<%s: %s>' % (self.__class__.__name__, self._path) def _is_potential_project(path): for name in _CONTAINS_POTENTIAL_PROJECT: if os.path.exists(os.path.join(path, name)): return True return False def _is_django_path(directory): """ Detects the path of the very well known Django library (if used) """ try: with open(os.path.join(directory, 'manage.py'), 'rb') as f: return b"DJANGO_SETTINGS_MODULE" in f.read() except (FileNotFoundError, NotADirectoryError): return False return False def get_default_project(path=None): if path is None: path = os.getcwd() check = os.path.realpath(path) probable_path = None first_no_init_file = None for dir in traverse_parents(check, include_current=True): try: return Project.load(dir) except (FileNotFoundError, NotADirectoryError): pass if first_no_init_file is None: if os.path.exists(os.path.join(dir, '__init__.py')): # In the case that a __init__.py exists, it's in 99% just a # Python package and the project sits at least one level above. continue else: first_no_init_file = dir if _is_django_path(dir): return Project(dir, _django=True) if probable_path is None and _is_potential_project(dir): probable_path = dir if probable_path is not None: # TODO search for setup.py etc return Project(probable_path) if first_no_init_file is not None: return Project(first_no_init_file) curdir = path if os.path.isdir(path) else os.path.dirname(path) return Project(curdir)

[ "nicolas.holzschuch@inria.fr" ]

nicolas.holzschuch@inria.fr

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b5313b8442b26e4a54172e55eb84d501ee4cae12

/run.py

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[ "MIT" ]

permissive

summeraz/ljmc

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refs/heads/master

2020-03-20T06:10:31.396309

2018-06-13T22:49:39

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from __future__ import division import pyximport; pyximport.install() from forcefield import * from mc import * from system import * from utils import * ### Define Lennard-Jones Parameters ### sigma = 1.0 epsilon = 1.0 cutoff = 2.5 ### Define System Parameters ### n_particles = 125 number_density = 0.5 ### Define Monte Carlo Parameters ### temperature = 1.2 # Temperature of the simulation dx = 0.1 # Initial maximum displacement target = 0.5 # Target acceptance probabality n_relax = 2500 # Number of timesteps to relax from initial configuration n_mc = 25000 # Total number of MC steps ############################################################################# ####### # RUN # ####### # Create the force field forcefield = ForceField(sigma=sigma, epsilon=epsilon, cutoff=cutoff) # Create the system system = System(n_particles, number_density, forcefield) # Initialize the neighborlist system.build_nlist(skin=0.5) # Create Monte Carlo instance mc = MonteCarlo(system=system, dx=dx, temperature=temperature, target=target) # Relax the system and optimize `dx` mc.relax(n_relax, adjust_freq=50) # Monte Carlo production run mc.run(traj_filename='traj.xyz', steps=n_mc, freq=100)

[ "andrew.z.summers@gmail.com" ]

andrew.z.summers@gmail.com

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/scrapers/megafilmeshd21_net.py

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[]

no_license

theclonedude/Scraping_BeautifulSoup_phantomjs

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# coding=utf-8 from sandcrawler.scraper import ScraperBase, SimpleScraperBase class Megafilmeshd21Net(SimpleScraperBase): BASE_URL = 'http://megafilmeshd21.net' OTHER_URLS = ['http://maxfilmesonline.net'] SCRAPER_TYPES = [ ScraperBase.SCRAPER_TYPE_OSP, ] LANGUAGE = 'por' MEDIA_TYPES = [ ScraperBase.MEDIA_TYPE_FILM, ScraperBase.MEDIA_TYPE_TV, ] URL_TYPES = [ScraperBase.URL_TYPE_SEARCH, ScraperBase.URL_TYPE_LISTING, ] def _fetch_search_url(self, search_term, media_type): return '{base_url}?&s={search_term}'.format(base_url=self.BASE_URL, search_term=search_term) def _fetch_no_results_text(self): return None def _fetch_next_button(self, soup): next_button = soup.select_one('a.nextpostslink') if next_button: return next_button.href return None def _parse_search_result_page(self, soup): found=0 for result in soup.select('a.thumb'): self.submit_search_result( link_url=result.href, link_title=result.text, image=self.util.find_image_src_or_none(result, 'img'), ) found=1 if not found: return self.submit_search_no_results() def _parse_parse_page(self, soup): index_page_title = self.util.get_page_title(soup) series_season = series_episode = None title = soup.select_one('h1') if title and title.text: series_season, series_episode = self.util.extract_season_episode(title.text) for link in soup.select('nav.lista-players a.btn-player'): self.submit_parse_result( index_page_title=index_page_title, link_url=link['data-href'], link_title=link.text, series_season=series_season, series_episode=series_episode, )

[ "stryokka@gmail.com" ]

stryokka@gmail.com

c24872cd28d1af12915e4db50558f458d2ddbe15

9af204535dfc39d5c9a2dc4e2daf538cb2454caf

/src/tasks/shapes/parameters.py

e9f86a6d13a821edc1beebb17b97b1a42a49e26f

[]

no_license

kevinyu/reimagined-robot

c94f51e1b025dc3636a40b06cf8d914238596f9e

970e451a70b43d1cd7ac7f8f3700ea8e9eb88aa3

refs/heads/master

2021-01-20T15:57:41.095221

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2017-05-24T01:40:51

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import os import numpy as np import theano import theano.tensor as T import config from utils import float_x from utils.complex import ComplexTuple from shapes.properties import properties from shapes.objects import shapes if os.path.exists(os.path.join(config.SAVE_DIR, "S0.npy")): S0_array = np.load(os.path.join(config.SAVE_DIR, "S0.npy")) S0 = ComplexTuple( theano.shared(float_x(S0_array[0])), theano.shared(float_x(S0_array[1])) ) else: S0 = ComplexTuple( theano.shared(float_x(np.zeros(config.DIM))), theano.shared(float_x(np.zeros(config.DIM))) ) # D_table is a dict mapping categories to dictionaries of hypervectors D_table = {} filename = os.path.join(config.SAVE_DIR, "D_Shapes.npy") if os.path.exists(filename): darray = np.load(filename) D_table["Shapes"] = ComplexTuple( theano.shared(float_x(darray[0])), theano.shared(float_x(darray[1])) ) else: D_table["Shapes"] = ComplexTuple( theano.shared(float_x(0.01 * np.random.uniform(-1, 1, size=(config.DIM, len(shapes))))), theano.shared(float_x(0.01 * np.random.uniform(-1, 1, size=(config.DIM, len(shapes))))) ) for prop in properties: filename = os.path.join(config.SAVE_DIR, "D_{}.npy".format(prop.__name__)) if os.path.exists(filename): darray = np.load(filename) D_table[prop.__name__] = ComplexTuple( theano.shared(float_x(darray[0])), theano.shared(float_x(darray[1])) ) else: D_table[prop.__name__] = ComplexTuple( theano.shared(float_x(0.01 * np.random.uniform(-1, 1, size=(config.DIM, len(prop.params))))), theano.shared(float_x(0.01 * np.random.uniform(-1, 1, size=(config.DIM, len(prop.params))))) ) # Generate all bound combinations of available objects with properties _D_combined = D_table["Shapes"] for i, prop in enumerate(properties): # each iteration increases the dimensionality of D_combined by one # the last dimension corresponds to the ith property i += 1 _D_combined = ( _D_combined.dimshuffle([0] + range(1, i+1) + ["x"]) * D_table[prop.__name__].dimshuffle(*[[0] + (["x"] * i) + [1]]) ) D = _D_combined.flatten(2) # Concatenate a single vector representing background to D bg_filename = os.path.join(config.SAVE_DIR, "D_bg.npy") if os.path.exists(bg_filename): darray = np.load(bg_filename) bg_vector = ComplexTuple( theano.shared(float_x(darray[0])), theano.shared(float_x(darray[1])) ) else: bg_vector = ComplexTuple( theano.shared(float_x(0.01 * np.random.uniform(-1, 1, size=(config.DIM, 1)))), theano.shared(float_x(0.01 * np.random.uniform(-1, 1, size=(config.DIM, 1)))) ) D = ComplexTuple( T.concatenate([D.real, bg_vector.real], axis=1), T.concatenate([D.imag, bg_vector.imag], axis=1) ) learn_params = [bg_vector.real, bg_vector.imag] for D_prop in D_table.values(): learn_params += [D_prop.real, D_prop.imag] learn_params = [S0.real, S0.imag] + learn_params def save_params(): s0_filename = os.path.join(config.SAVE_DIR, "S0") np.save(s0_filename, np.array(list(S0.get_value()))) D_filename = os.path.join(config.SAVE_DIR, "D_Shapes") np.save(D_filename, np.array(list(D_table["Shapes"].get_value()))) for prop in properties: D_filename = os.path.join(config.SAVE_DIR, "D_{}".format(prop.__name__)) np.save(D_filename, np.array(list(D_table[prop.__name__].get_value()))) np.save(os.path.join(config.SAVE_DIR, "D_bg"), np.array(list(bg_vector.get_value())))

[ "thekevinyu@gmail.com" ]

thekevinyu@gmail.com

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/output/models/ms_data/identity_constraint/id_l051_xsd/__init__.py

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permissive

tefra/xsdata-w3c-tests

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from output.models.ms_data.identity_constraint.id_l051_xsd.id_l051 import ( Root, Uid, ) __all__ = [ "Root", "Uid", ]

[ "tsoulloftas@gmail.com" ]

tsoulloftas@gmail.com

3f96a324be5d36b890aa2e0eb8f0d22f9106d7b3

03195206540b44d74f86801c5e58b2b731c863bf

/pi/mission_control/debile/pousse_feu.py

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[]

no_license

clement91190/eurobot

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refs/heads/master

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from mission_control.mission import Mission, SuccessOut, FailOut from utils.coord import Coord from mae_generator.mae import MAE, InitState, debugger def get_mission(com_state_factory): #raise NotImplementedError(" mission non codee") return Mission(" pousse_feu ", Coord(-800, 600, 180), MAEPousseFeu(com_state_factory)) class MAEPousseFeu(MAE): def __init__(self, com_state_factory): MAE.__init__(self) self.sf = com_state_factory #states init = InitState() #tape = self.sf.get_pmi_tape() avance_triangle1 = self.sf.get_bf_fw(Coord(200)) out = SuccessOut() out2 = FailOut() #transitions init.add_instant_transition(avance_triangle1) avance_triangle1.add_afini_transition(out) avance_triangle1.add_bloc_transition(out) avance_triangle1.add_advd_transition(out) self.state_list = [ init, avance_triangle1, out, out2 ] self.reinit_state() if __name__ == "__main__": from com_state_factory import ComStateFactory from communication import PipoCommunication com = PipoCommunication() mae = MAEPousseFeu(ComStateFactory(com)) com.set_global_mae(mae) #mae = MAEGlobal() debugger(mae)

[ "clem.jambou@gmail.com" ]

clem.jambou@gmail.com

c08a65cd4eaa895be6579ac952edbbb1cfd00cc9

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/all_data/exercism_data/python/kindergarten-garden/d338583c2ba84654b20ddcf61ff29827.py

c739d565e7f3e97d21da436f3a80d769200473d7

[]

no_license

itsolutionscorp/AutoStyle-Clustering

54bde86fe6dbad35b568b38cfcb14c5ffaab51b0

be0e2f635a7558f56c61bc0b36c6146b01d1e6e6

refs/heads/master

2020-12-11T07:27:19.291038

2016-03-16T03:18:00

2016-03-16T03:18:42

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2016-05-23T05:40:56

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from collections import defaultdict, deque from typing import Dict, Iterable, List PLANTS = { 'R': 'Radishes', 'C': 'Clover', 'G': 'Grass', 'V': 'Violets', } STUDENTS = ( 'Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Fred', 'Ginny', 'Harriet', 'Ileana', 'Joseph', 'Kincaid', 'Larry' ) class Garden: def __init__(self, garden: str, students: Iterable[str]=STUDENTS, grouping: int=2) -> None: self.students = defaultdict(List[str]) # type: Dict[str, List[str]] if isinstance(students, list): students.sort() for group in garden.split(): group_queue = deque(group) for student in students: for x in range(grouping): self.students[student].append(PLANTS[group_queue.popleft()]) if not group_queue: break def plants(self, student: str) -> List[str]: return self.students.get(student)

[ "rrc@berkeley.edu" ]

rrc@berkeley.edu

c31badd4543416eb333ff1a8f62aac8c166188c5

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/l2hmc-qcd/train.py

d9568bd70244bddda72a9c96ba1f88273e2b46d6

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permissive

FigTop/l2hmc-qcd

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refs/heads/master

2023-04-21T21:20:43.724346

2021-05-22T19:28:21

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""" train.py Train 2D U(1) model using eager execution in tensorflow. """ # noqa: E402, F401 # pylint:disable=wrong-import-position,invalid-name, unused-import, # pylint: disable=ungrouped-imports from __future__ import absolute_import, division, print_function import os import json import contextlib import logging import tensorflow as tf from config import BIN_DIR import utils try: import horovod import horovod.tensorflow as hvd try: RANK = hvd.rank() except ValueError: hvd.init() RANK = hvd.rank() HAS_HOROVOD = True logging.info(f'using horovod version: {horovod.__version__}') logging.info(f'using horovod from: {horovod.__file__}') GPUS = tf.config.experimental.list_physical_devices('GPU') for gpu in GPUS: tf.config.experimental.set_memory_growth(gpu, True) if GPUS: gpu = GPUS[hvd.local_rank()] tf.config.experimental.set_visible_devices(gpu, 'GPU') except (ImportError, ModuleNotFoundError): HAS_HOROVOD = False from utils.file_io import console import utils.file_io as io from utils.attr_dict import AttrDict from utils.parse_configs import parse_configs from dynamics.gauge_dynamics import build_dynamics from utils.training_utils import train, train_hmc from utils.inference_utils import run, run_hmc, run_inference_from_log_dir # os.environ['TF_CPP_MIN_VLOG_LEVEL'] = '3' # os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' logger = logging.getLogger(__name__) logging_datefmt = '%Y-%m-%d %H:%M:%S' logging_level = logging.WARNING logging_format = ( '%(asctime)s %(levelname)s:%(process)s:%(thread)s:%(name)s:%(message)s' ) logging.info(f'using tensorflow version: {tf.__version__}') logging.info(f'using tensorflow from: {tf.__file__}') @contextlib.contextmanager def experimental_options(options): """Run inside contextmanager with special options.""" old_opts = tf.config.optimizer.get_experimental_options() tf.config.optimizer.set_experimental_options(options) try: yield finally: tf.config.optimizer.set_experimental_options(old_opts) def restore_flags(flags, train_dir): """Update `FLAGS` using restored flags from `log_dir`.""" rf_file = os.path.join(train_dir, 'FLAGS.z') if os.path.isfile(rf_file): try: restored = io.loadz(rf_file) restored = AttrDict(restored) io.log(f'Restoring FLAGS from: {rf_file}...') flags.update(restored) except (FileNotFoundError, EOFError): pass return flags def main(configs, num_chains=None, run_steps=None): """Main method for training.""" hmc_steps = configs.get('hmc_steps', 0) # tf.keras.backend.set_floatx('float32') log_file = os.path.join(os.getcwd(), 'log_dirs.txt') x = None log_dir = configs.get('log_dir', None) beta_init = configs.get('beta_init', None) beta_final = configs.get('beta_final', None) if log_dir is not None: # we want to restore from latest checkpoint configs.restore = True run_steps = configs.get('run_steps', None) train_steps = configs.get('train_steps', None) restored = restore_flags(configs, os.path.join(configs.log_dir, 'training')) for key, val in configs.items(): if key in restored: if val != restored[key]: io.log(f'Restored {key}: {restored[key]}') io.log(f'Using {key}: {val}') configs.update({ 'train_steps': train_steps, 'run_steps': run_steps, }) if beta_init != configs.get('beta_init', None): configs.beta_init = beta_init if beta_final != configs.get('beta_final', None): configs.beta_final = beta_final else: # New training session train_steps = configs.get('train_steps', None) run_steps = configs.get('run_steps', None) timestamps = AttrDict({ 'month': io.get_timestamp('%Y_%m'), 'time': io.get_timestamp('%Y-%M-%d-%H%M%S'), 'hour': io.get_timestamp('%Y-%m-%d-%H'), 'minute': io.get_timestamp('%Y-%m-%d-%H%M'), 'second': io.get_timestamp('%Y-%m-%d-%H%M%S'), }) configs.log_dir = io.make_log_dir(configs, 'GaugeModel', log_file, timestamps=timestamps) io.write(f'{configs.log_dir}', log_file, 'a') configs.restore = False if hmc_steps > 0: # x, _, eps = train_hmc(args) x, dynamics_hmc, _, hflags = train_hmc(configs, num_chains=num_chains) # dirs_hmc = hflags.get('dirs', None) # args.dynamics_config['eps'] = dynamics_hmc.eps.numpy() _ = run(dynamics_hmc, hflags, save_x=False) if num_chains is None: num_chains = configs.get('num_chains', 15) x, dynamics, train_data, configs = train(configs, x=x, make_plots=True, num_chains=num_chains) if run_steps is None: run_steps = configs.get('run_steps', 50000) # ==== # Run inference on trained model if run_steps > 0: # run_steps = args.get('run_steps', 125000) log_dir = configs.log_dir beta = configs.get('beta_final') if configs.get('small_batch', False): batch_size = 256 old_shape = configs['dynamics_config']['x_shape'] new_shape = (batch_size, *old_shape[1:]) configs['dynamics_config']['x_shape'] = new_shape dynamics = build_dynamics(configs, log_dir=log_dir) x = x[:batch_size] results = run(dynamics, configs, x, beta=beta, make_plots=True, therm_frac=0.1, num_chains=num_chains, save_x=False) try: run_data = results.run_data run_dir = run_data.dirs['run_dir'] dataset = run_data.save_dataset(run_dir, therm_frac=0.) except: # TODO: Properly catch exception (if thrown) pass # _ = run_inference_from_log_dir(log_dir=log_dir, # run_steps=run_steps, # beta=beta, # num_chains=num_chains, # batch_size=batch_size, # therm_frac=0.2, # make_plots=True, # train_steps=0, # x=xbatch) # Run with random start # _ = run(dynamics, args) # # Run HMC # args.hmc = True # args.dynamics_config['eps'] = 0.15 # hmc_dir = os.path.join(args.log_dir, 'inference_hmc') # _ = run_hmc(args=args, hmc_dir=hmc_dir) if __name__ == '__main__': timestamp = io.get_timestamp('%Y-%m-%d-%H%M') # debug_events_writer = tf.debugging.experimental.enable_dump_debug_info( # debug_dir, circular_buffer_size=-1, # tensor_debug_mode="FULL_HEALTH", # ) CONFIGS = parse_configs() CONFIGS = AttrDict(CONFIGS.__dict__) if CONFIGS.get('debug', False): logging_level = logging.DEBUG os.environ['TF_CPP_MIN_VLOG_LEVEL'] = '0' os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0' else: logging_level = logging.WARNING console.log(f'CONFIGS: {dict(**CONFIGS)}') # io.print_dict(CONFIGS) main(CONFIGS) # if RANK == 0: # console.save_text(os.path.join(os.getcwd(), 'train.log'), styles=False) # # debug_events_writer.FlushExecutionFiles() # debug_events_writer.FlushNonExecutionFiles()

[ "saforem2@gmail.com" ]

saforem2@gmail.com

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/190820/working_order.py

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[]

no_license

baambox5/algorithm

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refs/heads/master

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import sys sys.stdin = open('working_order.txt', 'r') # for test_case in range(1, 11): # V, E = tuple(map(int, input().split())) # G = [[] for _ in range(V + 1)] # condition = [0] * (V + 1) # visit = [0] * (V + 1) # arr = list(map(int, input().split())) # stack_list = [] # for i in range(len(arr)): # if i % 2: # condition[arr[i]] += 1 # else: # G[arr[i]].append(arr[i + 1]) # print('#{}'.format(test_case), end=' ') # for i in range(1, V + 1): # if not condition[i] and not visit[i]: # stack_list.append(i) # visit[i] = 1 # print('{}'.format(i), end=' ') # for j in G[i]: # condition[j] -= 1 # while stack_list: # for w in G[i]: # if not condition[w] and not visit[w]: # visit[w] = 1 # stack_list.append(i) # print('{}'.format(w), end=' ') # i = w # for j in G[w]: # condition[j] -= 1 # break # else: # i = stack_list.pop() # print() def dfs(v): visit[v] = 1 print('{}'.format(v), end=' ') for w in G[v]: condition[w] -= 1 if not condition[w] and not visit[w]: dfs(w) for test_case in range(1, 11): V, E = tuple(map(int, input().split())) G = [[] for _ in range(V + 1)] condition = [0] * (V + 1) visit = [0] * (V + 1) arr = list(map(int, input().split())) for i in range(len(arr)): if i % 2: condition[arr[i]] += 1 else: G[arr[i]].append(arr[i + 1]) print('#{}'.format(test_case), end=' ') for i in range(1, V + 1): if not condition[i] and not visit[i]: dfs(i) print()

[ "baamboxo@gmail.com" ]

baamboxo@gmail.com