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denn-is-njeruh/DjangoMutltipleUsers
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# Generated by Django 3.2.7 on 2021-10-05 04:32 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ('auth', '0012_alter_user_first_name_max_length'), ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_length=128, verbose_name='password')), ('email', models.EmailField(max_length=254, unique=True)), ('name', models.CharField(blank=True, max_length=254, null=True)), ('is_staff', models.BooleanField(default=False)), ('is_superuser', models.BooleanField(default=False)), ('is_active', models.BooleanField(default=True)), ('last_login', models.DateTimeField(blank=True, null=True)), ('date_joined', models.DateTimeField(auto_now_add=True)), ('groups', models.ManyToManyField(blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', related_name='user_set', related_query_name='user', to='auth.Group', verbose_name='groups')), ('user_permissions', models.ManyToManyField(blank=True, help_text='Specific permissions for this user.', related_name='user_set', related_query_name='user', to='auth.Permission', verbose_name='user permissions')), ], options={ 'abstract': False, }, ), ]
[ "dennis.njeru@student.moringaschool.com" ]
dennis.njeru@student.moringaschool.com
8a2150267801d8dbbb8be912f431c32e54340802
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/code/layers.py
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[]
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pearsonlab/gbds
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""" The MIT License (MIT) Copyright (c) 2017 Shariq Iqbal Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import theano import lasagne import theano.tensor as T import numpy as np class DLGMLayer(lasagne.layers.Layer): """ This layer is inspired by the paper "Stochastic Backpropagation and Approximate Inference in Deep Generative Models" incoming (Lasagne Layer): preceding layer in DLGM num_units (int): number of output units in this layer srng (theano RandomState): random number generator rec_nets (dictionary of lasagne NNs): Neural networks that paramaterize the recognition model J (theano symbolic matrix): Input to rec model k (float): regularization term on generative weights """ def __init__(self, incoming, num_units, srng, rec_nets, k, output_layer=False, extra_noise=0.01, param_init=lasagne.init.Normal(0.01), nonlinearity=lasagne.nonlinearities.rectify, **kwargs): super(DLGMLayer, self).__init__(incoming, **kwargs) num_inputs = self.input_shape[1] self.srng = srng self.num_units = num_units self.output_layer = output_layer self.extra_noise = extra_noise # Initialize generative/decoding Parameters self.W = self.add_param(param_init, (num_inputs, num_units), name='W') self.b = self.add_param(param_init, (num_units,), name='b') self.unc_G = self.add_param(param_init, (num_units, num_units), name='unc_G') self.G = (T.diag(T.nnet.softplus(T.diag(self.unc_G))) + T.tril(self.unc_G, k=-1)) self.nonlinearity = nonlinearity # regularization term self.k = k # Load recognition/encoding Parameters self.mu_net = rec_nets['mu_net'] self.u_net = rec_nets['u_net'] self.unc_d_net = rec_nets['unc_d_net'] # add parameters to layer class rec_params = (lasagne.layers.get_all_params(self.mu_net) + lasagne.layers.get_all_params(self.u_net) + lasagne.layers.get_all_params(self.unc_d_net)) for param in rec_params: self.add_param(param, param.shape.eval()) def calculate_xi(self, postJ): """ Calculate xi based on sampled J from posterior """ # get output of rec model self.batch_mu = lasagne.layers.get_output(self.mu_net, inputs=postJ) self.batch_u = lasagne.layers.get_output(self.u_net, inputs=postJ) self.batch_unc_d = lasagne.layers.get_output(self.unc_d_net, inputs=postJ) # add extra dim to batch_u, so it gets treated as column vectors when # iterated over self.batch_u = self.batch_u.reshape( (self.batch_u.shape[0], self.batch_u.shape[1], 1)) def get_cov(u, unc_d): # convert output of rec model to rank-1 covariance matrix # use softplus to get positive constrained d, minimum of -15 # since softplus will turn low numbers into 0, which become NaNs # when inverted d = T.nnet.softplus(T.maximum(unc_d, -15)) D_inv = T.diag(1.0 / d) eta = 1.0 / (u.T.dot(D_inv).dot(u) + 1.0) C = D_inv - eta * D_inv.dot(u).dot(u.T).dot(D_inv) Tr_C = T.nlinalg.trace(C) ld_C = T.log(eta) - T.log(d).sum() # eq 20 in DLGM # coeff = ((1 - T.sqrt(eta)) / (u.T.dot(D_inv).dot(u))) # simplified coefficient below is more stable as u -> 0 # original coefficient from paper is above coeff = eta / (1 + T.sqrt(eta)) R = T.sqrt(D_inv) - coeff * D_inv.dot(u).dot(u.T).dot(T.sqrt(D_inv)) return Tr_C, ld_C, R (self.batch_Tr_C, self.batch_ld_C, self.batch_R), _ = theano.scan( fn=get_cov, outputs_info=None, sequences=[self.batch_u, self.batch_unc_d]) self.batch_xi = (self.batch_mu + T.batched_dot(self.batch_R, self.srng.normal( (self.batch_R.shape[0], self.num_units)))) def get_ELBO(self, length): """ Get ELBO for this layer length (theano symbolic int): length of current batch """ # KL divergence between posterior and N(0,1) prior KL_div = 0.5 * (T.sqrt((self.batch_mu**2).sum(axis=1)).sum() + self.batch_Tr_C.sum() - self.batch_ld_C.sum() - length) weight_reg = ((0.5 / self.k) * T.sqrt((self.W**2).sum()) * T.sqrt((self.G**2).sum())) return -(weight_reg + KL_div) def get_output_for(self, input, add_noise=False, use_rec_model=False, **kwargs): activation = self.nonlinearity(input).dot(self.W) + self.b if use_rec_model: # use sample from rec model xi = self.batch_xi if add_noise: # additional noise xi += self.extra_noise * self.srng.normal(self.batch_xi.shape) else: # pure random input xi = self.srng.normal((input.shape[0], self.num_units)) # we want the mean when training, so don't add noise to # output of last layer when training. if not self.output_layer: activation += T.dot(xi, self.G) elif not add_noise: activation += T.dot(xi, self.G) return activation def get_output_shape_for(self, input_shape): return (input_shape[0], self.num_units) class PKBiasLayer(lasagne.layers.Layer): """ This layer draws different biases (depending on the mode) from a normal distribution, then adds them to the input Default modes are as follows: 0: normal, no biases added 1: saline and DLPFC, bias 0 is added 2: saline and DMPFC, bias 1 is added 3: muscimol and DLPFC, biases 0 and 2 are added 4: muscimol and DMPFC, biases 1 and 3 are added """ def __init__(self, incoming, srng, params, param_init=lasagne.init.Normal(0.01), num_biases=4, **kwargs): super(PKBiasLayer, self).__init__(incoming, **kwargs) num_inputs = self.input_shape[1] self.mode = T.zeros(num_biases) self.srng = srng self.k = np.cast[theano.config.floatX](params['k']) self.m = self.add_param(param_init, (num_biases, num_inputs), name='m') self.log_s = self.add_param(param_init, (num_biases, num_inputs), name='log_s') # standard deviation will always be positive but optimization over # log_s can be unconstrained self.s = T.exp(self.log_s) self.draw_biases() self.draw_on_every_output = True def set_mode(self, mode): self.mode = mode def draw_biases(self): self.biases = self.m + self.srng.normal(self.s.shape) * self.s def get_ELBO(self, nbatches): """ Return the contribution to the ELBO for these biases Normalized by nbatches (number of batches in dataset) """ ELBO = (-T.abs_(self.biases) / self.k - T.log(2 * self.k)).sum() ELBO += T.log(self.s).sum() return ELBO / nbatches def get_output_for(self, input, **kwargs): if self.draw_on_every_output: self.draw_biases() act_biases = self.mode.astype(theano.config.floatX).reshape((1, -1)).dot(self.biases) return input + act_biases class PKRowBiasLayer(lasagne.layers.Layer): """ This layer draws different biases (depending on the mode) from a normal distribution, then adds them to the input. This layer has sparsity at the row level, instead of the individual sparsity of the PKBiasLayer. Default modes are as follows: 0: normal, no biases added 1: saline and DLPFC, bias 0 is added 2: saline and DMPFC, bias 1 is added 3: muscimol and DLPFC, biases 0 and 2 are added 4: muscimol and DMPFC, biases 1 and 3 are added """ def __init__(self, incoming, srng, params, param_init=lasagne.init.Normal(0.01), num_biases=4, **kwargs): super(PKRowBiasLayer, self).__init__(incoming, **kwargs) num_inputs = self.input_shape[1] self.mode = T.zeros(num_biases) self.srng = srng # parameters on prior self.a = np.cast[theano.config.floatX](params['a']) # shape self.b = np.cast[theano.config.floatX](params['b']) # rate # learnable posterior parameters # normal dist over biases self.mu = self.add_param(param_init, (num_biases, num_inputs), name='mu') self.unc_sig = self.add_param(param_init, (num_biases, num_inputs), name='unc_sig') # gamma over rows self.alpha = theano.shared(value=self.a * np.ones((num_biases, 1)), name='alpha', broadcastable=[False, True]) self.beta = theano.shared(value=self.b * np.ones((num_biases, 1)), name='beta', broadcastable=[False, True]) # update for alpha self.alpha += (num_inputs / 2.0) # standard deviation will always be positive but optimization over # unc_sig can be unconstrained self.sigma = T.nnet.softplus(self.unc_sig) self.draw_biases() self.draw_on_every_output = True def set_mode(self, mode): self.mode = mode def draw_biases(self): self.gamma = self.mu + self.srng.normal(self.sigma.shape) * self.sigma def coord_update(self): self.beta = self.b + 0.5 * (self.mu**2 + self.sigma**2).sum(axis=1, keepdims=True) self.beta = T.addbroadcast(self.beta, 1) def get_ELBO(self, nbatches): """ Return the contribution to the ELBO for these biases Normalized by nbatches (number of batches in dataset) """ self.coord_update() # Log Density ELBO = (-0.5 * (self.mu**2 + self.sigma**2) * (self.alpha / self.beta) + 0.5 * (T.psi(self.alpha) - T.log(self.beta)) - 0.5 * T.log(2 * np.pi)).sum() ELBO += ((self.a - 1) * (T.psi(self.alpha) - T.log(self.beta)) - self.b * (self.alpha / self.beta) + self.a * T.log(self.b) - T.gammaln(self.a)).sum() # entropy ELBO += (0.5 * T.log(2 * np.pi) + 0.5 + T.log(self.sigma)).sum() ELBO += (self.alpha - T.log(self.beta) + T.gammaln(self.alpha) + (1 - self.alpha) * T.psi(self.alpha)).sum() return ELBO / nbatches def get_output_for(self, input, **kwargs): if self.draw_on_every_output: self.draw_biases() act_biases = self.mode.astype(theano.config.floatX).reshape((1, -1)).dot(self.gamma) return input + act_biases
[ "shariqiqbal2810@users.noreply.github.com" ]
shariqiqbal2810@users.noreply.github.com
3a58a95ff9ca04c8a9228ff5e3822cfa35a2e6dc
3ccc43f582471af88c90d52bcba0142186d9829e
/src/sorter.py
3cfc650ed0c98ddf50f57f4e7b863c29b968c8e6
[]
no_license
sd2017/typer
bc6dded8acfff5c773b854686a2f81c478db5da3
e0e1e1604598f8d5be492b6b646c02421e809e1c
refs/heads/master
2021-05-03T12:19:44.672193
2016-10-17T00:51:50
2016-10-17T00:51:50
70,138,175
0
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import linecache import strategy import strategy_eng import logger import logging class Sorter: def __init__(self,loggeri,filename,dicti,strategy): self.logger=loggeri self.filename=filename self.dicta=dicti self.line="the most noticeable members of the Reform Club, though he seemed" self.strategy=strategy self.linecache=linecache self.linenum=1 def line_read(self): self.line=self.linecache.getline(self.filename,self.linenum) self.linenum=self.linenum+1 def line_to_dictionary(self): words = self.line.split(self.strategy.seperator) for word in words: word_aligned=self.strategy.align(word) word_index= self.strategy.index(word_aligned) #self.logger.log(logging.ERROR, "{}".format( word_aligned)) # TODO self.logger.log(logging.DEBUG, "{}:{}".format( word_index,word_aligned)) if (None != word_index): self.dicta.setdefault(word_index, set()).add(word_aligned) def sort(self,num): for i in range(0,num): self.line_read() self.line_to_dictionary() def info(self): self.logger.log(logging.INFO, self.dicta) self.logger.log(logging.INFO, self.dicta.keys()) if __name__=="__main__": sorter=Sorter(logger.Loggerf(),"../data/words_80day10.txt",{},strategy_eng.StrategyEng(logger.Logger())) sorter.line_to_dictionary() sorter.info()
[ "sd2017@walla.co.il" ]
sd2017@walla.co.il
bc8fbb48a26fbbb57765c7ee73f93db6fb9cad11
a05fdeb2958b16640fd98120a1898610b9a88467
/ResNet_tf2/source/network_models/resnet50.py
da9bf7270713d57796d2af4c889a4cc3feadc453
[]
no_license
kawayoshiHirota/endscope_diagnosis
15bd6197512736a207010db2c4adb864d03e4735
02006f4db309bfb301707ddb0f67ad391d9fa885
refs/heads/main
2023-03-08T15:04:19.595681
2021-02-24T05:01:40
2021-02-24T05:01:40
338,940,631
0
0
null
null
null
null
UTF-8
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# -*- coding: utf-8 -*- import os import warnings from tensorflow.keras import models from tensorflow.keras import backend from tensorflow.keras import layers import tensorflow.keras.utils as keras_utils def identity_block(input_tensor, kernel_size, filters, stage, block): filters1, filters2, filters3 = filters if backend.image_data_format() == 'channels_last': bn_axis = 3 else: bn_axis = 1 conv_name_base = 'res' + str(stage) + block + '_branch' bn_name_base = 'bn' + str(stage) + block + '_branch' x = layers.Conv2D(filters1, (1, 1), kernel_initializer='he_normal', name=conv_name_base + '2a')(input_tensor) x = layers.BatchNormalization(axis=bn_axis, name=bn_name_base + '2a')(x) x = layers.Activation('relu')(x) x = layers.Conv2D(filters2, kernel_size, padding='same', kernel_initializer='he_normal', name=conv_name_base + '2b')(x) x = layers.BatchNormalization(axis=bn_axis, name=bn_name_base + '2b')(x) x = layers.Activation('relu')(x) x = layers.Conv2D(filters3, (1, 1), kernel_initializer='he_normal', name=conv_name_base + '2c')(x) x = layers.BatchNormalization(axis=bn_axis, name=bn_name_base + '2c')(x) x = layers.add([x, input_tensor]) x = layers.Activation('relu')(x) return x def conv_block(input_tensor, kernel_size, filters, stage, block, strides=(2, 2)): filters1, filters2, filters3 = filters if backend.image_data_format() == 'channels_last': bn_axis = 3 else: bn_axis = 1 conv_name_base = 'res' + str(stage) + block + '_branch' bn_name_base = 'bn' + str(stage) + block + '_branch' x = layers.Conv2D(filters1, (1, 1), strides=strides, kernel_initializer='he_normal', name=conv_name_base + '2a')(input_tensor) x = layers.BatchNormalization(axis=bn_axis, name=bn_name_base + '2a')(x) x = layers.Activation('relu')(x) x = layers.Conv2D(filters2, kernel_size, padding='same', kernel_initializer='he_normal', name=conv_name_base + '2b')(x) x = layers.BatchNormalization(axis=bn_axis, name=bn_name_base + '2b')(x) x = layers.Activation('relu')(x) x = layers.Conv2D(filters3, (1, 1), kernel_initializer='he_normal', name=conv_name_base + '2c')(x) x = layers.BatchNormalization(axis=bn_axis, name=bn_name_base + '2c')(x) shortcut = layers.Conv2D(filters3, (1, 1), strides=strides, kernel_initializer='he_normal', name=conv_name_base + '1')(input_tensor) shortcut = layers.BatchNormalization( axis=bn_axis, name=bn_name_base + '1')(shortcut) x = layers.add([x, shortcut]) x = layers.Activation('relu')(x) return x def ResNet50(input_tensor=None, input_shape=None, pooling=None, classes=3, **kwargs): if input_tensor is None: img_input = layers.Input(shape=input_shape) else: if not backend.is_keras_tensor(input_tensor): img_input = layers.Input(tensor=input_tensor, shape=input_shape) else: img_input = input_tensor if backend.image_data_format() == 'channels_last': bn_axis = 3 else: bn_axis = 1 x = layers.ZeroPadding2D(padding=(3, 3), name='conv1_pad')(img_input) x = layers.Conv2D(64, (7, 7), strides=(2, 2), padding='valid', kernel_initializer='he_normal', name='conv1')(x) x = layers.BatchNormalization(axis=bn_axis, name='bn_conv1')(x) x = layers.Activation('relu')(x) x = layers.ZeroPadding2D(padding=(1, 1), name='pool1_pad')(x) x = layers.MaxPooling2D((3, 3), strides=(2, 2))(x) x = conv_block(x, 3, [64, 64, 256], stage=2, block='a', strides=(1, 1)) x = identity_block(x, 3, [64, 64, 256], stage=2, block='b') x = identity_block(x, 3, [64, 64, 256], stage=2, block='c') x = conv_block(x, 3, [128, 128, 512], stage=3, block='a') x = identity_block(x, 3, [128, 128, 512], stage=3, block='b') x = identity_block(x, 3, [128, 128, 512], stage=3, block='c') x = identity_block(x, 3, [128, 128, 512], stage=3, block='d') x = conv_block(x, 3, [256, 256, 1024], stage=4, block='a') x = identity_block(x, 3, [256, 256, 1024], stage=4, block='b') x = identity_block(x, 3, [256, 256, 1024], stage=4, block='c') x = identity_block(x, 3, [256, 256, 1024], stage=4, block='d') x = identity_block(x, 3, [256, 256, 1024], stage=4, block='e') x = identity_block(x, 3, [256, 256, 1024], stage=4, block='f') x = conv_block(x, 3, [512, 512, 2048], stage=5, block='a') x = identity_block(x, 3, [512, 512, 2048], stage=5, block='b') x = identity_block(x, 3, [512, 512, 2048], stage=5, block='c') x = layers.GlobalAveragePooling2D(name='avg_pool')(x) x = layers.Dense(classes, activation='softmax', name='fc1000')(x) # Ensure that the model takes into account # any potential predecessors of `input_tensor`. if input_tensor is not None: inputs = keras_utils.get_source_inputs(input_tensor) else: inputs = img_input # Create model. model = models.Model(inputs, x, name='resnet50') return model
[ "shohei@hirota-mbp.local" ]
shohei@hirota-mbp.local
7860766fce7868311fe335a79413268f3035d2e4
20670e0ee8673317d90e22f9c99a230c5c810877
/interview/urls.py
ddccc499cdf4513f32930b56b7519b17c5b9912e
[]
no_license
SameerRokade/video-interview-platform
a98871d831508c18e7a314ecc12c00861d3ecc8f
c4d832fd1163daea787fbfa9f0a95d3fdf3f1cba
refs/heads/master
2023-06-17T06:06:17.078647
2021-07-14T22:49:29
2021-07-14T22:49:29
386,064,507
1
0
null
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null
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from django.urls import path from . import views urlpatterns = [ path('', views.index, name='index'), path('record/', views.record, name='record'), path('ajaxHandler/<int:num_question>/', views.getQuestionAjaxHandler, name='ajaxHandler'), path('create-interview/', views.createInterview, name='create-interview'), path('finish-interview/', views.interview_is_finished, name='finish-interview'), path('success-interview/', views.success_interview, name='success-interview'), ]
[ "sameerrokade5@gmail.com" ]
sameerrokade5@gmail.com
cde14b6cc471a81ced9162a70e2bbfd34f16cf3e
2be837d9b230753853cc5bb1ef8339196462f4be
/manage.py
a11d0815cdd16e20353ceae1ed6608d63558369d
[]
no_license
DensonNgumo/deenze-music
0b2747c8698f317bb5bdb1d73db1c44094a6eddc
3ae3d1ad600f718a25b0e0599d555dcc344b58ae
refs/heads/master
2021-01-02T22:40:55.627175
2017-08-07T17:20:09
2017-08-07T17:20:09
99,366,526
0
0
null
null
null
null
UTF-8
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false
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804
py
#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "deenze.settings") try: from django.core.management import execute_from_command_line except ImportError: # The above import may fail for some other reason. Ensure that the # issue is really that Django is missing to avoid masking other # exceptions on Python 2. try: import django except ImportError: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) raise execute_from_command_line(sys.argv)
[ "ngumohd@gmail.com" ]
ngumohd@gmail.com
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#-*- coding:utf-8 -*- from tornado.options import define, options import tornado.options import setting import turbo.register import turbo.app #uncomment this to init state manager: store #import store turbo.register.register_app(setting.SERVER_NAME, setting.TURBO_APP_SETTING, setting.WEB_APPLICATION_SETTING, __file__, globals()) define("port", default=8888, type=int) if __name__ == '__main__': tornado.options.parse_command_line() turbo.app.start(options.port)
[ "zhyq0826@gmail.com" ]
zhyq0826@gmail.com
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/news/urls.py
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[]
no_license
sabyrbekov/newsblog
7f9d84877f8ff6739e2f1b0c9b3b10b285b1568b
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"""news URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.1/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path from django.urls import include urlpatterns = [ path('admin/', admin.site.urls), path('', include('blogs.urls')), path('', include('users.urls')), path('accounts/', include('django.contrib.auth.urls')), ]
[ "aza10k@mail.ru" ]
aza10k@mail.ru
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2020-09-16T06:49:36.345278
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# coding: utf8 # Author: Wing Yung Chan (~wy) # Date: 2017 import math x = math.factorial(100) s = str(x) acc = 0 for i in s: a = int(i) acc = acc + a print(acc)
[ "wingyungchan@gmail.com" ]
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/packages/python/plotly/plotly/validators/pointcloud/hoverlabel/font/_color.py
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hugovk/plotly.py
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2022-05-10T12:17:38.797994
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import _plotly_utils.basevalidators class ColorValidator(_plotly_utils.basevalidators.ColorValidator): def __init__( self, plotly_name="color", parent_name="pointcloud.hoverlabel.font", **kwargs ): super(ColorValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, array_ok=kwargs.pop("array_ok", True), edit_type=kwargs.pop("edit_type", "none"), **kwargs )
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hugovk.noreply@github.com
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[]
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itsolutionscorp/AutoStyle-Clustering
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refs/heads/master
2020-12-11T07:27:19.291038
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def distance(strand1, strand2): if len(strand1) != len(strand2): raise Exception('length mismatch', len(strand1), len(strand2)) hd = 0 for i in xrange(len(strand1)): if strand1[i] != strand2[i]: hd += 1 return hd
[ "rrc@berkeley.edu" ]
rrc@berkeley.edu
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/dependencies/punica/cli/tool_cmd.py
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[]
no_license
OnyxPayDev/SmartContractDemo
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refs/heads/master
2020-08-15T12:05:58.858948
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- import click from punica.tool.tool import Tool from .main import main @main.group('tool', invoke_without_command=True) @click.pass_context def tool_cmd(ctx): """ Data format conversion tool """ if ctx.invoked_subcommand is None: print('Usage: punica tool [OPTIONS] COMMAND [ARGS]...') print('') print(' ', 'Data format conversion tool.') print() print('Options:') print(' ', '-h, --help Show this message and exit.') print() print('Commands:') print(' ', 'decryptprivatekey decrypt privatekey') print(' ', 'transform transform data') else: pass @tool_cmd.command('transform') @click.option('--addresstohex', nargs=1, type=str, default='', help='transform address to hex.') @click.option('--stringtohex', nargs=1, type=str, default='', help='transform string to hex.') @click.option('--hexreverse', nargs=1, type=str, default='', help='hex string reverse.') @click.option('--inttohex', nargs=1, type=int, default=0, help='transform int to hex.') def transform_cmd(addresstohex, stringtohex, hexreverse, inttohex): """ transform data """ if addresstohex != '': Tool.address_to_hex(addresstohex) elif stringtohex != '': Tool.str_to_hex(stringtohex) elif hexreverse != '': Tool.hex_reverse(hexreverse) elif inttohex != 0: Tool.num_to_hex(inttohex) else: print('Usage: punica tool transform [OPTIONS]') print('') print(' ', 'transform data.') print() print('Options:') print(' ', '--addresstohex TEXT transform address to hex.') print(' ', '--stringtohex TEXT transform string to hex.') print(' ', '--hexreverse TEXT hex string reverse.') print(' ', '--numtohex TEXT transform num to hex.') print(' ', '-h, --help Show this message and exit.') print() @tool_cmd.command('decryptprivatekey') @click.option('--key', nargs=1, type=str, default='', help='encrypted private key.') @click.option('--address', nargs=1, type=str, default='', help='address.') @click.option('--salt', nargs=1, type=str, default='', help='salt.') @click.option('--n', nargs=1, type=int, default=16384, help='n.') @click.option('--password', nargs=1, type=str, default='', help='password.') def decryptprivatekey_cmd(key, address, salt, n, password): """ decrypt privatekey """ if key == '' and address == '' and salt == '' or n == 0 and password == '': print('Usage: punica tool decryptprivatekey [OPTIONS]') print('') print(' ', 'decrypt privatekey') print() print('Options:') print(' ', '--key TEXT encrypted private key.') print(' ', '--address TEXT address.') print(' ', '--salt TEXT salt.') print(' ', '--n TEXT n.') print(' ', '--password TEXT password.') print(' ', '-h, --help Show this message and exit.') print() return if key == '': print('Error:') print('key should not be \'\'') return if address == '': print('Error:') print('address should not be \'\'') return if salt == '': print('Error:') print('salt should not be \'\'') return if password == '': print('Error:') print('password should not be \'\'') return Tool.decrypt_private_key(key, address, salt, n, password)
[ "5020980+DancingAxolotl@users.noreply.github.com" ]
5020980+DancingAxolotl@users.noreply.github.com
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/mininet/wifi/util.py
00b9511e070c1f3f235e10d02d277a5b7d286e1e
[ "LicenseRef-scancode-x11-stanford" ]
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MatthiasEckhart/mininet-wifi
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refs/heads/master
2020-03-16T00:52:39.895729
2018-05-11T09:17:26
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"Utility functions for Mininet-WiFi" from mininet.util import retry def moveIntfNoRetry(intf, dstNode, printError=False): """Move interface to node, without retrying. intf: string, interface dstNode: destination Node printError: if true, print error""" from mininet.wifi.node import Station, Car, AP if (isinstance(dstNode, Station) or isinstance(dstNode, Car) or isinstance(dstNode, AP) and 'eth' not in str(intf)): if isinstance(dstNode, Station) or isinstance(dstNode, Car): return True else: return True def moveIntf(intf, dstNode, printError=True, retries=3, delaySecs=0.001): """Move interface to node, retrying on failure. intf: string, interface dstNode: destination Node printError: if true, print error""" from mininet.wifi.node import AP if not isinstance(dstNode, AP): retry(retries, delaySecs, moveIntfNoRetry, intf, dstNode, printError=printError)
[ "ramonreisfontes@gmail.com" ]
ramonreisfontes@gmail.com
7bacefcd596348b1f5cbe3fa92de6644588f16e7
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/messaging/migrations/0012_auto_20200916_0702.py
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[]
no_license
shantanu-tomar/teamit
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refs/heads/master
2022-12-21T07:12:49.485986
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# Generated by Django 3.0.8 on 2020-09-16 07:02 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('messaging', '0011_auto_20200916_0603'), ] operations = [ migrations.AlterField( model_name='message', name='recepient', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='recepient', to=settings.AUTH_USER_MODEL), ), migrations.AlterField( model_name='message', name='sender', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='sender', to=settings.AUTH_USER_MODEL), ), ]
[ "shantanu.tomar94@gmail.com" ]
shantanu.tomar94@gmail.com
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[]
no_license
tboudreaux/SummerSTScICode
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refs/heads/master
2021-01-20T18:07:44.723496
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from gPhoton.gAperture import gAperture def main(): gAperture(band="NUV", skypos=[132.907667,24.697419], stepsz=30., csvfile="/data2/fleming/GPHOTON_OUTPU/LIGHTCURVES/sdBs/sdB_PG_0848+249 /sdB_PG_0848+249_lc.csv", maxgap=1000., overwrite=True, radius=0.00555556, annulus=[0.005972227,0.0103888972], verbose=3) if __name__ == "__main__": main()
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thomas@boudreauxmail.com
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/todo/models.py
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[]
no_license
Sahouaneyassine/ToDo
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refs/heads/main
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from django.db import models from django.contrib.auth.models import User # Create your models here. class Todo(models.Model): title=models.CharField(max_length=100) memo=models.TextField(blank=True) created=models.DateTimeField(auto_now_add=True) datecompleted=models.DateTimeField(null=True,blank=True) important=models.BooleanField(default=False) user=models.ForeignKey(User,on_delete=models.CASCADE)
[ "sahouaneyassine1999@gmail.com" ]
sahouaneyassine1999@gmail.com
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/75.findPeak.py
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[]
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Aissen-Li/lintcode
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refs/heads/master
2020-11-28T16:43:21.760691
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class Solution: """ @param A: An integers array. @return: return any of peek positions. """ def findPeak(self, A): if A[1] > A[2]: return 1 if A[len(A) - 2] > A[len(A) - 3]: return len(A) - 2 start, end = 0, len(A) - 1 while start + 1 < end: mid = (start + end) // 2 if A[mid] > A[mid + 1] and A[mid] > A[mid - 1]: return mid if A[mid] < A[mid + 1]: start = mid + 1 else: end = mid - 1 return start if A[start] >= A[end] else end
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Huynhngocthanh/shinzerorin
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2023-04-17T22:18:04.552717
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import os,random import string t = input('Nhập tên thư mục: ') #Em muốn tạo thư mục trực tiếp trên python path = 'C:\\Users\\MyPC\\Documents\\' os.chdir(path) os.mkdir(t) file_name = input("Nhập tên file dữ liệu: ") #Em muốn tạo tên file trực tiếp trên python n = int(input("Nhập tổng số lượng file với dung lượng 1MB-1024MB: ")) #vì 1MB=>1024KB nên số lượng file nằm từ khoảng 2->1048 files i = 1 for i in range(n): path1 = path + t os.chdir(path1) i = str(i) f = open(file_name + i + '.txt','w+') f.seek(1024*1000-1) f.write(random.choice(string.ascii_lowercase)) if f.seek(0): os.remove(f) #Lọc file 0KB
[ "noreply@github.com" ]
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/python/cowbells/data/tqplot.py
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brettviren/cowbells
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#!/usr/bin/env python ''' Make some plots from the TQ tree. ''' import ROOT import math def liberate(tobj): ROOT.SetOwnership(tobj,0) return tobj def draw_stats(pad, h, fitnum =111): h.Draw() pad.Modified() pad.Update() stats = h.FindObject("stats") if stats: stats.SetOptStat(1110) stats.SetOptFit(fitnum) return class Plots(object): expected_led_time = "abs(tmin[%(chn)d]-1530) < 30" def __init__(self, tree, canvas = None, pdffile = 'tqplot.pdf'): self.tree = tree self.pdffile = pdffile if not canvas: canvas = ROOT.TCanvas("tqtree","tqtree debug", 0,0, 1000, 700) self.canvas = canvas def cprint(self,extra=''): self.canvas.Print('%s%s'%(self.pdffile,extra), 'pdf') def do_twoXtwo(self, what, chn=0): self.canvas.Clear() self.canvas.Divide(2,2) for count, what in enumerate(what): pad = self.canvas.cd(count+1) pad.SetLogy(True) self.tree.Draw("%s[%d]"%(what,chn)) return def do_minmax(self, chn=0): self.do_twoXtwo(['qmin','qmax','tmin','tmax'], chn) def do_stats(self, chn=0): self.do_twoXtwo(['avg','mean','rms','sigma'], chn) def do_sumn(self, chn=0): self.do_twoXtwo(['n3','n4','sum3','sum4'], chn) def do_34(self, chn=0, maxq=400, opt="", logy=True, fit=(25,100)): self.canvas.Clear() self.canvas.Divide(2,2) todraw = "n%(nsig)d[%(chn)d]*mean[%(chn)d] -sum%(nsig)d[%(chn)d]" for count,nsig in enumerate([3,4]): pad = self.canvas.cd(count+1) pad.SetLogy(logy) self.tree.Draw(todraw%locals(),"",opt) for count,nsig in enumerate([3,4]): pad = self.canvas.cd(count+3) pad.SetLogy(logy) h = liberate(ROOT.TH1F("spe%d"%nsig,'sum(ADC) >%d sigma above ped'%nsig,maxq,0,maxq)) self.tree.Draw(todraw%locals()+">>spe%d"%nsig,"",opt) if fit: h.Fit("gaus","","", *fit) h.Draw() pad.Modified() pad.Update() stats = h.FindObject("stats") if stats: stats.SetOptStat(1110) stats.SetOptFit(111) continue return def do_34_50(self, chn=0, opt="", logy=True): self.do_34(chn=chn, maxq=50, opt=opt, logy=logy,fit=None) def do_34vEntry(self, chn=0): self.canvas.Clear() self.canvas.Divide(2,2) measure = "n%(nsig)d[%(chn)d]*mean[%(chn)d]-sum%(nsig)d[%(chn)d]" for count,nsig in enumerate([3,4]): pad = self.canvas.cd(count+1) m = measure % locals() m += ':Entry$' c = "" print m self.tree.Draw(m,c,'colz') for count,nsig in enumerate([3,4]): pad = self.canvas.cd(count+3) m = measure % locals() c = "%s > 0 && %s < 400" % (m,m) m += ':Entry$' print m print c self.tree.Draw(m,c,'colz') return def do_fit(self, chn=0): self.canvas.Clear() self.canvas.Divide(2,2) toplot = "mean[%(chn)d] sigma[%(chn)d] mean[%(chn)d]:Entry$ sigma[%(chn)d]:Entry$" toplot = toplot % locals() for count,what in enumerate(toplot.split()): pad = self.canvas.cd(count+1) opt = "" if 'Entry$' in what: opt = "COLZ" self.tree.Draw(what,"",opt) continue return def _fit_pe(self, chn=0, cuts=None, spe=(60,110), dpe=(115,220), tpe=(225,350), qmeas = 'qpeak'): ''' Fit single/double PE peak of qpeak. ''' if cuts is None: cuts = self.expected_led_time nbins, minq, maxq = 500, 0, 500 cuts = cuts%locals() what = "%(qmeas)s[%(chn)d]"%locals() h = liberate(ROOT.TH1F('hqpeak', "%s {%s}" % (qmeas, cuts,), nbins, minq, maxq)) self.tree.Draw('%s >> hqpeak'%what, cuts) pe1 = liberate(h.Clone()) pe1.Fit("gaus","L","",*spe) fit1 = pe1.GetFunction("gaus") fit1.SetRange(minq,maxq) fit1.SetLineColor(2) pe2 = liberate(h.Clone()) pe2.Add(fit1, -1) pe2.Fit("gaus","L","",*dpe) fit2 = pe2.GetFunction("gaus") fit2.SetRange(spe[0],maxq) fit2.SetLineColor(4) pe3 = liberate(h.Clone()) pe3.Add(fit2, -1) pe3.Fit("gaus","L","",*tpe) fit3 = pe3.GetFunction("gaus") #fit3.SetRange(dpe[0],maxq) fit3.SetLineColor(6) pe123 = liberate(h.Clone()) dfit = liberate(ROOT.TF1("dfit","gaus(0)+gaus(3)+gaus(6)",10,tpe[1])) for ind in range(3): dfit.SetParameter(ind, fit1.GetParameter(ind)) dfit.SetParameter(ind+3,fit2.GetParameter(ind)) dfit.SetParameter(ind+6,fit3.GetParameter(ind)) pe123.Fit(dfit,"L","",10,maxq) dfit = pe123.GetFunction("dfit") dfit.SetRange(10,maxq) dfit.SetLineColor(7) self.canvas.Clear() self.canvas.Divide(2,2) pad = self.canvas.cd(1) draw_stats(pad, pe1) pad = self.canvas.cd(2) draw_stats(pad, pe2) pad = self.canvas.cd(3) draw_stats(pad, pe3) pad = self.canvas.cd(4) draw_stats(pad, pe123, 111111111) a1 = fit1.Integral(minq,maxq) if not a1: print 'No fit 1' return a2 = fit2.Integral(minq,maxq) c1 = fit1.GetParameter(0) c2 = fit2.GetParameter(0) mu1 = fit1.GetParameter(1) mu2 = fit2.GetParameter(1) mupe = 2.0*a2/a1 print 'Mean <PE> of source = 2*%.1f/%.1f = %.3f' %(a2,a1,mupe) mu2mu1_frac = 0 if mu1: mu2mu1_frac = mu2/mu1 print 'Ratio of PE2/PE1: %.1f/%.1f = %.3f (~2?)' % (mu2,mu1,mu2/mu1) if mupe > 0: print 'Prob 0PE: %.3f' % (math.exp(-1*mupe),) return def do_pe_fits(self, chn=0, cuts = None): for qmeas in ['qpeak','qpeaks3','qpeaks4','qpeaks5','qwin']: self._fit_pe(chn=chn,qmeas=qmeas,cuts=cuts) self.cprint() continue return def do_interspersed_led_cuts(self): # Cuts to select LEDs interspersed with cosmic muon triggers self.canvas.Clear() self.canvas.Divide(2,2) pad = self.canvas.cd(1) pad.SetLogy(True) self.tree.Draw("mean[2]-qmin[2]","mean[2]-qmin[2]<1000") pad = self.canvas.cd(2) pad.SetLogy(True) self.tree.Draw("qnpeaks[0]","mean[2]-qmin[2]<100") pad = self.canvas.cd(3) pad.SetLogy(True) self.tree.Draw("tmin[0]","mean[2]-qmin[2]<100 && qnpeaks[0] == 1") pad = self.canvas.cd(4) pad.SetLogy(False) self.tree.Draw("qpeak[0]") def all(self, chn = 0): self.cprint('[') for what in [ 'minmax','stats','fit','sumn', '34','34_50', '34vEntry', ]: meth = getattr(self, 'do_%s' % what) meth(chn) self.cprint() self.do_interspersed_led_cuts() self.cprint() self.do_pe_fits(chn) self.cprint(']') if __name__ == '__main__': import sys fp = ROOT.TFile.Open(sys.argv[1]) tree = fp.Get("tq") try: pdf = sys.argv[2] except IndexError: pdf = None p = Plots(tree, pdffile=pdf) p.all()
[ "bv@bnl.gov" ]
bv@bnl.gov
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/src/scripts/addDocument.py
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[ "BSD-2-Clause" ]
permissive
kstaken/Syncato
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860822e08b08b88b749961a1d61be902ce3b8ea3
refs/heads/master
2020-04-05T22:48:28.727982
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#!/usr/bin/env python # # See the file LICENSE for redistribution information. # # Copyright (c) 2003 Kimbro Staken. All rights reserved. # # Adds a new document to the database import libxml2 import sys sys.path.append('lib') import WeblogUtil if (len(sys.argv) != 6): print "Usage: addDocument.py host baseURL username password content" sys.exit() host = sys.argv[1] base = sys.argv[2] username = sys.argv[3] password = sys.argv[4] document = sys.argv[5] content = open(document).read() result = WeblogUtil.runRequest(host, username, password, "POST", base, content) if (result.status == 201): print "Document URL: " + result.getheader("Location") else: print str(result.status) + " " + result.reason
[ "kstaken@kstaken.com" ]
kstaken@kstaken.com
da20b663295dc181cdefdec4059f904a810546e2
f86a8b55b6e983e694a453300b2b9a58806f73a0
/src/embeddings.py
eeca4ddc3a4e7fd6719d4c030664cdcd1d780a17
[ "MIT" ]
permissive
ArturPrzybysz/ReutersRNNClassifier
d56479fab4ef61d02a7705734007941c1a2e46a4
fba90eccdb73832c4f8057ed43aa23e025f944d3
refs/heads/master
2020-05-07T10:22:44.572242
2019-04-15T12:13:58
2019-04-15T12:13:58
180,415,713
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import csv import numpy as np import pandas as pd from ReutersRNNClassifier.src.config import MAX_NUM_WORDS def embeddings(glove_model_path: str): words = pd.read_csv(glove_model_path, sep=" ", index_col=0, header=None, quoting=csv.QUOTE_NONE) vocab_len = MAX_NUM_WORDS + 1 emb_dim = words.iloc[0].shape[0] emb_matrix = np.zeros((vocab_len, emb_dim)) for i in np.arange(vocab_len - 1): emb_matrix[i, :] = words.iloc[i] print('Found %s word vectors.' % len(emb_matrix)) return emb_matrix, words
[ "prz.artur@gmail.com" ]
prz.artur@gmail.com
eb93998c886f3467fdcd99b8c83ff8a9276b0aa1
74a1145f20945311d6223d92a5affac688a97622
/Attraction/enums/DangerLevel.py
ffd0de398f91ddc10b8c89cba3e9e222469707f4
[]
no_license
OrestSrasiv2001/Lab11
844073e91f7c351d50d9091d6f2c4ec2c53a8d21
78a68ab0f1b8a9361c4ac35be2c30d0abdc2b5b3
refs/heads/master
2020-06-01T03:00:46.705667
2019-06-06T16:03:27
2019-06-06T16:03:27
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py
from enum import Enum class DangerLevel(Enum): LOW = 0 MIDDLE = 1, HIGH = 2, MAXIMUM = 3
[ "stasiv.orest@gmail.com" ]
stasiv.orest@gmail.com
94b494245f7b4c4498e64b18adc55b39bbe3f559
592e01558a8dafca01b143c2f063a196edc0ea77
/05-django/02-required/Ninja_Gold_project/manage.py
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[]
no_license
Python-November-2018/nshredz
899ccb975cbb6779771f0e3555f82235a16556a6
ad840b570546dc036eb135c5edb1a9de58e8b1f8
refs/heads/master
2020-04-03T22:34:31.629095
2018-12-18T21:01:58
2018-12-18T21:01:58
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#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "Ninja_Gold_project.settings") try: from django.core.management import execute_from_command_line except ImportError: # The above import may fail for some other reason. Ensure that the # issue is really that Django is missing to avoid masking other # exceptions on Python 2. try: import django except ImportError: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) raise execute_from_command_line(sys.argv)
[ "44245934+nick77-s@users.noreply.github.com" ]
44245934+nick77-s@users.noreply.github.com
6bbd854d7aa3af2c54a8a772e46e58e79118d2ad
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/EasyLogistics/settings/base.py
2a053944d4bff7b58b7a5b273fefb97cedeeb81b
[]
no_license
gauravgs06/EasyLogistics
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509734971f11f2a222c4230ee61ae7fba3efdb6a
refs/heads/master
2022-02-02T10:54:26.480448
2019-07-21T09:01:34
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py
""" Django settings for EasyLogistics project. Generated by 'django-admin startproject' using Django 2.2.3. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ from .secrets import SECRET_KEY # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', ] 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 = 'EasyLogistics.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'EasyLogistics.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/'
[ "gauravsharmags06@gmail.com" ]
gauravsharmags06@gmail.com
cd7a6e39bddcd867989015fc0c40cc09c18bc796
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/cvxbenchmarks/lib/data/epsilon/epopt/problems/hinge_l2.py
41b8b42fd08be15cf32527c0526e7dc334f6548e
[]
no_license
nishi951/cvxbenchmarks
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refs/heads/master
2021-01-11T07:23:32.260811
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"""Standard SVM, i.e.. hinge loss w/ l2 regularization.""" from epopt.problems import problem_util import cvxpy as cp import epopt as ep import numpy as np import scipy.sparse as sp def create(**kwargs): A, b = problem_util.create_classification(**kwargs) lam = 1 x = cp.Variable(A.shape[1]) f = ep.hinge_loss(x, A, b) + lam*cp.sum_squares(x) return cp.Problem(cp.Minimize(f))
[ "nishimuramarky@yahoo.com" ]
nishimuramarky@yahoo.com
87a1365fd6a9f6ccca02348485d3a70abebd022f
34a26b713021f15d94d416b9728bac50d283ed5f
/interno_pymedigital-9.0/sale_order_invoice_amount/models/sale_order.py
7dc71e3de0680f62a283f98ad86d6675e8ad4e35
[]
no_license
Brahim820/odoo-1
7641b2a0ef411fb3b82f806a11e88b9880875a46
d8ee18a7dc467ff250113a0a3df3fcf1e876b321
refs/heads/master
2020-04-07T10:58:09.517097
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null
null
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UTF-8
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py
# -*- encoding: utf-8 -*- from openerp import api, fields, models, _ from openerp.tools import float_is_zero from openerp.exceptions import UserError class SaleOrder(models.Model): _inherit = 'sale.order' @api.multi def action_invoice_create_from_amount(self, grouped=False, amount=0): if amount == 0: raise UserError(_('The amount to invoice should be greater than cero.')) for order in self: group_key = order.id if grouped else (order.partner_invoice_id.id, order.currency_id.id) inv_obj = self.env['account.invoice'] invoices = {} for line in order.order_line.sorted(key=lambda l: l.qty_to_invoice): if group_key not in invoices: inv_data = order._prepare_invoice() invoice = inv_obj.create(inv_data) invoices[group_key] = invoice elif group_key in invoices: vals = {} if order.name not in invoices[group_key].origin.split(', '): vals['origin'] = invoices[group_key].origin + ', ' + order.name if order.client_order_ref and order.client_order_ref not in invoices[group_key].name.split(', '): vals['name'] = invoices[group_key].name + ', ' + order.client_order_ref invoices[group_key].write(vals) discount = 1 - (line.discount or 0.0 / 100.0) if line.price_unit > 0 and discount < 100: paid_qty = amount / (line.price_unit * discount) else: paid_qty = line.product_uom_qty to_invoice = 0 if line.qty_to_invoice > 0: if paid_qty >= line.qty_to_invoice: to_invoice = line.qty_to_invoice else: to_invoice = paid_qty name = line.name + ' desde ' + str(round(line.qty_invoiced, 2)) + ' a ' + str( round(line.qty_invoiced + to_invoice, 2)) + ' de ' + str(round(line.product_uom_qty, 2)) line.invoice_line_create_from_amount(invoices[group_key].id, to_invoice, name) amount -= to_invoice * line.price_unit if amount > 0: discount = 1 - (line.discount or 0.0 / 100.0) lines = order.order_line.filtered(lambda l: l.product_uom_qty - l.qty_invoiced > 0) for line in lines.sorted( key=lambda l: (l.product_uom_qty - l.qty_invoiced) * l.price_unit): if line.price_unit > 0 and discount < 100: paid_qty = amount / (line.price_unit * discount) else: paid_qty = line.product_uom_qty residual_qty = line.product_uom_qty - line.qty_invoiced to_invoice = 0 if residual_qty > 0: if round(paid_qty, 5) > round(residual_qty, 5): to_invoice = residual_qty else: to_invoice = paid_qty name = ' Pago anticipado: ' + line.name + ' desde ' + str(round(line.qty_invoiced, 2)) + ' a ' + str( round(line.qty_invoiced + to_invoice, 2)) + ' de ' + str(round(line.product_uom_qty, 2)) line.invoice_line_create_from_amount(invoices[group_key].id, to_invoice, name) amount -= to_invoice * line.price_unit if not invoices: raise UserError(_('There is no invoicable line.')) for invoice in invoices.values(): if not invoice.invoice_line_ids: raise UserError(_('There is no invoicable line.')) # If invoice is negative, do a refund invoice instead if invoice.amount_untaxed < 0: invoice.type = 'out_refund' for line in invoice.invoice_line_ids: line.quantity = -line.quantity # Use additional field helper function (for account extensions) for line in invoice.invoice_line_ids: line._set_additional_fields(invoice) # Necessary to force computation of taxes. In account_invoice, they are triggered # by onchanges, which are not triggered when doing a create. invoice.compute_taxes() #TODO: agregar este cálculo a la función principal # para evitar problemas con las funciones que hacen super # como en el módulo l10n_ec_sri_sale resx = [inv.id for inv in invoices.values()] invx = self.env['account.invoice'].browse(resx) for i in invx: i.compute_sri_invoice_amounts() return [inv.id for inv in invoices.values()] class SaleOrderLine(models.Model): _inherit = 'sale.order.line' @api.multi def invoice_line_create_from_amount(self, invoice_id, qty, name): """ Create an invoice line. The quantity to invoice can be positive (invoice) or negative (refund). :param name: char :param invoice_id: integer :param qty: float quantity to invoice """ precision = self.env['decimal.precision'].precision_get('Product Unit of Measure') for line in self: if not float_is_zero(qty, precision_digits=precision): vals = line._prepare_invoice_line(qty=qty) vals.update({'name': name, 'invoice_id': invoice_id, 'sale_line_ids': [(6, 0, [line.id])]}) self.env['account.invoice.line'].create(vals)
[ "ceduardodch@gmail.com" ]
ceduardodch@gmail.com
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/72.py
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[]
no_license
Kavinkumaran/pri-codekata
9645087019d4b972770d41af47f2fcf235b79464
1ffc2b228ed6b15829f4c28bba8aee0ecab53fa9
refs/heads/master
2020-06-19T04:33:34.604445
2019-07-10T18:43:16
2019-07-10T18:43:16
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s=input() p=set(s) if(p=={"1","0"}): print("yes") else: print("no")
[ "noreply@github.com" ]
Kavinkumaran.noreply@github.com
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[]
no_license
satwik77/Simple_LoginApp
2fe8973e86b128b3a4b71149606149389416c6b4
af8c4a08ef909985127fb6267a8701bbeb7ae288
refs/heads/master
2021-01-10T04:04:01.857690
2016-04-14T14:51:13
2016-04-14T14:51:13
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null
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#!flask/bin/python from login_app import login_app login_app.run(debug=True)
[ "satwik55@gmail.com" ]
satwik55@gmail.com
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/recommendation_engine/content_retrieval_v4.py
7249f90634668352da79545511716e17fd0fe13c
[]
no_license
gitw3ll/content_recommendation_engine
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import numpy as np import sqlite3 import dask.dataframe as dd from collections import deque class ContentRetrieval: def __init__(self): self.event_type_strength = { 'VIEW': 1.0, 'LIKE': 2.0, 'BOOKMARK': 3.0, 'COMMENT CREATED': 4.0, 'FOLLOW': 5.0, } self.articles_df = None self.interactions_df = None self.score_data = None self.content_data = None def load_preprocess(self, database_directory): """ """ conn = sqlite3.connect(database_directory) self.articles_df = dd.read_sql_table('content_data', conn) self.interactions_df = dd.read_sql_table('user_data', conn) df = self.articles_df.merge(self.interactions_df, on='content_id') df['eventStrength'] = df['event_type'].apply(lambda x: self.event_type_strength[x]) df = df.drop_duplicates() df = df.groupby(['person_id', 'content_id', 'title']).sum().reset_index() df['title'] = df['title'].astype('category') df['person_id'] = df['person_id'].astype('category') df['content_id'] = df['content_id'].astype('category') df['personId'] = df['person_id'].cat.codes df['contentId'] = df['content_id'].cat.codes self.content_data = df #Load user wellness score data self.scores_data = dd.read_sql_table('scores_data', conn) def retrieve_content(self, user_id, wellness_metric, similar_users=3, content_per_user=5): """ """ user_content = list(self.content_data.loc[self.content_data['personId'] == user_id]['title']) user_content = deque([user_content]) user_score = self.scores_data.at[user_id, wellness_metric] closest_emotional = self.scores_data.iloc[(self.scores_data[wellness_metric] - user_score).abs().argsort()[:similar_users]] closest_ids_list = list(closest_emotional['personId']) similar_content = deque([]) for num in closest_ids_list: similar_content.append(list(self.content_data.loc[self.content_data['personId'] == num]['title'][:content_per_user])) for content in user_content: if content in similar_content: similar_content.remove(content) similar_content = np.concatenate(similar_content, axis=0).tolist() return similar_content
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/russian/posts_crawler.py
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import scrapy import pdb from tqdm import tqdm PAGES = 1000 class PikabuSpider(scrapy.Spider): name = 'pikabu' start_urls = ['https://pikabu.ru/new?page={}'.format(i) for i in range(PAGES)] def parse(self, response): for post in response.css('.stories-feed__container > .story'): yield { 'url': post.css('a.story__title-link ::attr(href)').get(), 'title': post.css('a.story__title-link ::text').get(), 'tags': post.css('a.tags__tag ::text').extract(), }
[ "belchikov1996@gmail.com" ]
belchikov1996@gmail.com
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/24.py
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''' 24. Swap Nodes in Pairs Given a linked list, swap every two adjacent nodes and return its head. For example, Given 1->2->3->4, you should return the list as 2->1->4->3. Your algorithm should use only constant space. You may not modify the values in the list, only nodes itself can be changed. ''' from ListNode import * from pprint import pprint # Definition for singly-linked list. # class ListNode(object): # def __init__(self, x): # self.val = x # self.next = None class Solution(object): def swapPairs(self, head): """ :type head: ListNode :rtype: ListNode """ # To go from pre -> a -> b -> b.next to pre -> b -> a -> b.next, # we need to change those three references. Instead of thinking about # in what order I change them, I just change all three at once. pre = self pre.next = head # <<<< equals self.next = head # next attribute is likely not in Solution but setted manually while pre.next and pre.next.next: a = pre.next b = a.next pre.next, b.next, a.next = b, a, b.next pre = a return self.next def test(): a = [1, 2, 3, 4, 5, 6] head = List_to_Link(a).head sl = Solution() b = sl.swapPairs(head) Link_to_List(b).print_list() if __name__ == "__main__": test()
[ "licheng@utexas.edu" ]
licheng@utexas.edu
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/td/credentials.py
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import json import urllib import pathlib import webbrowser from typing import Union from datetime import datetime from urllib.parse import parse_qs from urllib.parse import urlparse import requests class TdCredentials(): """ ### Overview ---- TD Ameritrade uses an oAuth protocol to authenticate it's users. The `TdCredential` object helps the user manage the credentials to ensure the are properly authenticated. """ def __init__( self, client_id: str, redirect_uri: str, credential_dict: dict = None, credential_file: Union[str, pathlib.Path] = None ) -> None: """Initializes the `TdCredential` object.""" self._access_token = '' self._refresh_token = '' self._scope = [] self._token_type = '' self._expires_in = 0 self._refresh_token_expires_in = 0 self._is_expired = True self._client_id = client_id self._redirect_uri = redirect_uri self._refresh_token_expiration_time = 0 self._access_token_expiration_time = 0 self.resource_url = 'https://api.tdameritrade.com/' self.version = 'v1/' self.token_endpoint = 'oauth2/token' self.authorization_url = 'https://auth.tdameritrade.com/auth?' self.authorization_code = "" self._loaded_from_file = False self._file_path = "" if credential_file: if isinstance(credential_file, pathlib.Path): credential_file = credential_file.resolve() self._loaded_from_file = True self._file_path = credential_file self.from_credential_file(file_path=credential_file) elif credential_dict: self.from_credential_dict(token_dict=credential_dict) else: self.from_workflow() @property def redirect_uri(self) -> str: """Returns the user's redirect URI. ### Returns ---- str The User's redirect URI. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.redirect_uri """ return self._redirect_uri @property def client_id(self) -> str: """Returns the Client ID. ### Returns ---- str The users Client Id. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.client_id """ return self._client_id @property def access_token(self) -> str: """Returns the Access token. ### Returns ---- str A valid Access Token. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.access_token """ return self._access_token @property def refresh_token(self) -> str: """Returns the Refresh token. ### Returns ---- str A valid Refresh Token. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.refresh_token """ return self._refresh_token @property def refresh_token_expiration_time(self) -> datetime: """Returns when the Refresh Token will expire. ### Returns ---- datetime The date and time of the refresh token expiration. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.refresh_token_expiration_time """ return self._refresh_token_expiration_time @property def is_refresh_token_expired(self) -> bool: """Specifies whether the current Refresh Token is expired or not. ### Returns ---- bool `True` if the Refresh Token is expired, `False` otherwise. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.is_refresh_token_expired """ exp_time = self.refresh_token_expiration_time.timestamp() - 20 now = datetime.now().timestamp() return bool(exp_time < now) def from_token_dict(self, token_dict: dict) -> None: """Converts a token dicitonary to a `TdCredential` object. ### Parameters ---- token_dict : dict A dictionary containing all the original token details. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.from_dict( token_dict={ 'access_token': '', 'refresh_token': ', 'scope': '', 'expires_in': 0, 'refresh_token_expires_in': 0, 'token_type': '' } ) """ self._access_token = token_dict.get('access_token', '') self._refresh_token = token_dict.get('refresh_token', '') self._scope = token_dict.get('scope', []) self._token_type = token_dict.get('token_type', '') self._expires_in = token_dict.get('expires_in', 0) self._refresh_token_expires_in = token_dict.get( 'refresh_token_expires_in', 0 ) self._refresh_token_expiration_time = token_dict.get( 'refresh_token_expiration_time', 0 ) self._access_token_expiration_time = token_dict.get( 'access_token_expiration_time', 0 ) # Calculate the Refresh Token expiration time. if isinstance(self._refresh_token_expiration_time, str): self._refresh_token_expiration_time = datetime.fromisoformat( self._refresh_token_expiration_time ) elif isinstance(self._refresh_token_expiration_time, float): self._refresh_token_expiration_time = datetime.fromtimestamp( self._refresh_token_expiration_time ) else: self._calculate_refresh_token_expiration( expiration_secs=self._refresh_token_expires_in ) # Calculate the Access Token Expiration Time. if isinstance(self._access_token_expiration_time, str): self._access_token_expiration_time = datetime.fromisoformat( self._access_token_expiration_time ) elif isinstance(self._access_token_expiration_time, float): self._access_token_expiration_time = datetime.fromtimestamp( self._access_token_expiration_time ) else: self._calculate_access_token_expiration( expiration_secs=self._expires_in, ) self.validate_token() def to_token_dict(self) -> dict: """Converts the TdCredential object to a dictionary object. ### Returns ---- dict A dictionary containing all the original token details. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.to_dict() """ token_dict = { 'access_token': self._access_token, 'refresh_token': self._refresh_token, 'scope': self._scope, 'expires_in': self._expires_in, 'refresh_token_expires_in': self._refresh_token_expires_in, 'token_type': self._token_type, 'refresh_token_expiration_time': self.refresh_token_expiration_time.isoformat(), 'access_token_expiration_time': self.access_token_expiration_time.isoformat(), } return token_dict def _calculate_refresh_token_expiration(self, expiration_secs: int) -> None: """Calculates the number of seconds until the refresh token expires. ### Parameters ---- expiration_secs : int The number of seconds until expiration. """ expiration_time = datetime.now().timestamp() + expiration_secs self._refresh_token_expiration_time = datetime.fromtimestamp( expiration_time ) def _calculate_access_token_expiration(self, expiration_secs: int) -> None: """Calculates the number of seconds until the access token expires. ### Parameters ---- expiration_secs : int The number of seconds until expiration. """ expiration_time = datetime.now().timestamp() + expiration_secs self._access_token_expiration_time = datetime.fromtimestamp( expiration_time ) @property def access_token_expiration_time(self) -> datetime: """Returns when the Access Token will expire. ### Returns ---- datetime The date and time of the access token expiration. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.access_token_expiration_time """ return self._access_token_expiration_time @property def is_access_token_expired(self) -> bool: """Specifies whether the current Access Token is expired or not. ### Returns ---- bool `True` if the Access Token is expired, `False` otherwise. ### Usage ---- >>> td_credential = TdCredentials() >>> td_credential.is_access_token_expired """ exp_time = self.access_token_expiration_time.timestamp() - 20 now = datetime.now().timestamp() return bool(exp_time < now) def from_workflow(self) -> None: """Grabs an Access toke and refresh token using the oAuth workflow. ### Usage ---- >>> td_credentials = TdCredentials( client_id=client_id, redirect_uri=redirect_uri, credential_file='config/td_credentials.jsonc' ) >>> td_credentials.from_workflow() """ self.grab_authorization_code() token_dict = self.exchange_code_for_token(return_refresh_token=True) self.from_token_dict(token_dict=token_dict) def from_credential_file(self, file_path: str) -> None: """Loads the credentials for a JSON file that is formatted in the correct fashion. ### Parameters file_path : str The location of the credentials file. """ with open(file=file_path, mode='r', encoding='utf-8') as token_file: token_dict = json.load(fp=token_file) self.from_token_dict(token_dict=token_dict) def to_credential_file(self, file_path: Union[str, pathlib.Path]) -> None: """Takes the token dictionary and saves it to a JSON file. ### Parameters ---- file_path : Union[str, pathlib.Path] The file path to the credentials file. ### Usage ---- >>> td_credentials.to_token_file( file_path='config/td_credentials.json' ) """ if isinstance(file_path, pathlib.Path): file_path = file_path.resolve() with open(file=file_path, mode='w+', encoding='utf-8') as token_file: json.dump(obj=self.to_token_dict(), fp=token_file, indent=2) def from_credential_dict(self, token_dict: dict) -> None: """Loads the credentials from a token dictionary. ### Parameters ---- token_dict : dict The token dictionary with the required authentication tokens. ### Usage ---- ### Example 1 ---- You don't necessairly need the `refresh_token_expiration_time` or the `access_token_expiration_time` because they can be calculated using the `access_token` key and `refresh_token`. >>> td_credentials.from_credential_dict( token_dict={ "access_token": "YOUR_ACCESS_TOKEN", "refresh_token": "YOUR_REFRESH_TOKEN" "scope": "PlaceTrades AccountAccess MoveMoney", "expires_in": 1800, "refresh_token_expires_in": 7776000, "token_type": "Bearer", "refresh_token_expiration_time": "2021-07-08T17:38:07.973982", "access_token_expiration_time": "2021-04-09T18:08:07.973982" } ) ### Example 2 ---- You don't necessairly need the `refresh_token_expiration_time` or the `access_token_expiration_time` because they can be calculated using the `access_token` key and `refresh_token`. >>> # This just is another way of sending it through. >>> td_credentials.from_credential_dict( token_dict={ "access_token": "YOUR_ACCESS_TOKEN", "refresh_token": "YOUR_REFRESH_TOKEN" "scope": "PlaceTrades AccountAccess MoveMoney", "expires_in": 1800, "refresh_token_expires_in": 7776000, "token_type": "Bearer" } ) """ self.from_token_dict(token_dict=token_dict) self.validate_token() def grab_authorization_code(self) -> None: """Generates the URL to grab the authorization code.""" data = { "response_type": "code", "redirect_uri": self.redirect_uri, "client_id": self.client_id + "@AMER.OAUTHAP" } # url encode the data. params = urllib.parse.urlencode(data) # build the full URL for the authentication endpoint. url = self.authorization_url + params webbrowser.open(url=url) code_url = input("Please Paste the Authorization Code Here: ") query = urlparse(url=code_url) parse_code = parse_qs(qs=query.query) self.authorization_code = parse_code['code'][0] def exchange_code_for_token(self, return_refresh_token: bool) -> dict: """Access token handler for AuthCode Workflow. ### Overview ---- This takes the authorization code parsed from the auth endpoint to call the token endpoint and obtain an access token. ### Parameters ---- return_refresh_token: bool If set to `True`, will request a refresh token in the request. Otherwise, will only request an access token along. ### Returns ---- dict : The token dictionary with the content. """ # Define the parameters of our access token post. data = { 'grant_type': 'authorization_code', 'client_id': self.client_id + '@AMER.OAUTHAP', 'code': self.authorization_code, 'redirect_uri': self.redirect_uri } if return_refresh_token: data['access_type'] = 'offline' # Make the request. response = requests.post( url="https://api.tdameritrade.com/v1/oauth2/token", headers={ 'Content-Type': 'application/x-www-form-urlencoded' }, data=data ) if response.ok: return response.json() raise requests.HTTPError() def grab_access_token(self) -> dict: """Refreshes the current access token. This takes a valid refresh token and refreshes an expired access token. This is different from exchanging a code for an access token. ### Returns ---- dict: The dictionary contain all the token info. """ # build the parameters of our request data = { 'client_id': self.client_id, 'grant_type': 'refresh_token', 'access_type': 'offline', 'refresh_token': self.refresh_token } # Make the request. response = requests.post( url="https://api.tdameritrade.com/v1/oauth2/token", headers={ 'Content-Type': 'application/x-www-form-urlencoded' }, data=data ) if response.ok: return response.json() raise requests.HTTPError() def validate_token(self) -> None: """Validates the access token and refresh token. ### Overview ---- A TD Ameritrade Access token is only valid for 30 minutes, and a TD Ameritrade Refresh token is only valid for 90 days. When an access token expires, a new one is retrieved using the refresh token. If the refresh token is expired the oAuth workflow starts again. """ if self.is_refresh_token_expired: print("Refresh Token Expired, initiating oAuth workflow...") self.from_workflow() if self.is_access_token_expired: print("Access Token Expired, refreshing access token...") token_dict = self.grab_access_token() self.from_token_dict(token_dict=token_dict) if self._loaded_from_file: self.to_credential_file(file_path=self._file_path)
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''' Contains utility functions providing an extension to Python's datetime. ''' import datetime import pytz __author__ = "Finn Frankis" __copyright__ = "Copyright 2019, Crypticko" DESIRED_DATE_FORMAT = "%Y-%m-%d" DESIRED_TIME_ZONE = pytz.timezone("US/Pacific") ''' Converts a timestamp (represented as a string) in one date format into another date format. Returns the newly formatted date as a string. A list of acceptable date format characters can be found at the following link. https://docs.python.org/2/library/datetime.html#strftime-and-strptime-behavior ''' def convertTimestamp(timestamp, initialFormat, desiredFormat): return datetime.datetime.strptime(timestamp, initialFormat).strftime(desiredFormat) ''' A generator function (inclusive on both endpoints) to iterate through every date or datetime in a given range. ''' def dateRange(startDate, endDate): for i in range(int((endDate - startDate).days) + 1): yield startDate + datetime.timedelta(i) ''' Retrieves the current time and date in Pacific time. ''' def getCurrentDateTime(): return datetime.datetime.now(DESIRED_TIME_ZONE)
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"""djangoproject URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.0/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.conf import settings from django.conf.urls.static import static from django.urls import path from .djangoapp import views from .download import views as downloadview urlpatterns = [ path('admin/', admin.site.urls), path('',views.index,name="index"), path('userReg/', views.userReg, name="userReg"), path('facultyReg/', views.facultyReg, name="facultyReg"), path('userlogin/', views.userlogin, name="userlogin"), path('facultylogin/', views.facultylogin, name="facultylogin"), path('adminlogin/', views.adminlogin, name="adminlogin"), path('about/', views.about, name="about"), path('userregistration/', views.usersignup, name="usersignup"), path('facultyregistration/', views.facultysignup, name="facultysignup"), path('admincredential/', views.admincredentialauth, name="admincredentialauth"), path('userdetails/',views.userdetails,name="userdetails"), path('adminhome/',views.adminhome,name="adminhome"), path('userhome/',views.userhome,name="userhome"), path('facultyhome/',views.facultyhome,name="facultyhome"), path('facultydetails/',views.facultydetails,name="facultydetails"), path('logout/',views.logout,name="logout"), path('admincredential/',views.usercredentialauth,name="usercredentialauth"), path('add_courses/',views.add_course,name="add_course"), path('add_course_materials/',views.add_course_materials,name="add_course_materials"), path('select_course/',views.select_course,name="select_course"), path('select_course_materials/',views.select_course_materials,name="select_course_materials"), path('ask_question/',views.ask_question,name="ask_question"), path('view_reply/',views.view_reply,name="view_reply"), path('view_question/',views.view_question,name="view_question"), path('responsing/',views.responsing,name="responsing"), path('usercredential/', views.usercredentialauth, name="usercredentialauth"), path('userlogout/',views.userlogout,name="userlogout"), path('facultycredential/', views.facultycredentialauth, name="facultycredentialauth"), path('facultylogout/',views.facultylogout,name="facultylogout"), path('add_values/',views.add_values,name="add_values"), path('assign_course/',views.assign_course,name="assign_course"), path('course_value/',views.course_value,name="course_value"), path('view_course/',views.view_course,name="view_course"), path('ask_question/',views.ask_question,name="ask_question"), path('save_doubts/',views.save_doubts,name="save_doubts"), path('view_assigned_courses/', views.view_assigned_courses, name="view_assigned_courses"), path('view_users_doubts/', views.view_users_doubts, name="view_users_doubts"), path('reply/', views.reply, name="reply"), path('save_reply/', views.save_reply, name="save_reply"), path('all_reply/', views.all_reply, name="all_reply"), path('view_solution/', views.view_solution, name="view_solution"), path('add_materials/', views.add_materials, name="add_materials"), path('generateKey/', views.generateKey, name="generateKey"), path('material_save/', views.material_save, name="material_save"), path('add_email/', views.add_email, name="add_email"), path('send_mail/', views.send_mail, name="send_mail"), path('read_keys/', views.read_keys, name="read_keys"), path('login/', downloadview.login, name="login"), path('downloadresoure/',downloadview.authenticate_and_download,name="authenticate_and_download"), ] if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
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# -*- coding: utf-8 -*- """Package that includes classes for data models.""" from .attribute_network import AttributeNetwork # noqa: F401 from .filtered_network import FilteredNetwork # noqa: F401 from .gene import Gene # noqa: F401 from .labeled_network import LabeledNetwork # noqa: F401 from .network import Network # noqa: F401
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/python_program/q1769_Minimum_Number_of_Operations_to_Move_All_Balls_to_Each_Box.py
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from typing import List from collections import Counter,defaultdict from math import * from functools import reduce import numpy as np from heapq import * class Solution: def minOperations(self, boxes: str) -> List[int]: num1sAhead = 0 num1sBehind = 0 initialDiff = 0 res = [] for num in boxes: if num == "1": num1sAhead += 1 for i, num in enumerate(boxes): if num == "1": initialDiff += i for i, num in enumerate(boxes): if i == 0: res.append(initialDiff) if num == "1": num1sAhead -= 1 num1sBehind += 1 else: res.append(res[i-1] - num1sAhead + num1sBehind) if num == "1": num1sAhead -= 1 num1sBehind += 1 return res def minOperations_2(self, boxes: str) -> List[int]: n = len(boxes) list_1 = np.array(list(map(lambda x:int(x),boxes)))[:,None] list_2 = np.array(range(n)) result = np.abs((list_2[:,None]-list_2[None,:])*list_1).sum(axis = 0) return list(result) def minOperations_1(self, boxes: str) -> List[int]: n = len(boxes) return_list = [0]*n for i in range(n): count_move = 0 for j,e in enumerate(boxes): count_move+=abs((j-i)*int(e)) return_list[i] = count_move return return_list sol = Solution() # input boxes = "110" # output output = sol.minOperations(boxes) # answer answer = [1,1,3] print(output, answer, answer == output) # input boxes = "001011" # output output = sol.minOperations(boxes) # answer answer = [11,8,5,4,3,4] print(output, answer, answer == output) # input boxes = 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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] print(output, answer, answer == output)
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import unittest import re from flask import url_for from app import create_app,db from app.models import User,Role class FlaskClientTestCase(unittest.TestCase): def setUp(self): self.app = create_app('testing') self.app_context = self.app.app_context() self.app_context.push() db.create_all() Role.insert_roles() self.client = self.app.test_client(use_cookies=True) def tearDown(self): db.session.remove() db.drop_all() self.app_context.pop() def test_home_page(self): response = self.client.get(url_for('main.index')) self.assertTrue('Stranger' in response.get_data(as_text=True)) def test_register_and_login(self): #模拟注册新账户 response = self.client.post(url_for('auth.register'),data={ 'email':'john@example.com', 'username':'john', 'password':'cat', 'password2':'cat' }) self.assertTrue(response.status_code == 302) #使用新注册的账户登入 response = self.client.post(url_for('auth.login'),data={ 'email':'john@example.com', 'password':'cat'}, follow_redirects=True) data = response.get_data(as_text=True) self.assertTrue(re.search('Hello,john!', data)) self.assertTrue('You have not confirmed your account yet' in data) #发送确认令牌 user=User.query.filter_by(email='john@example.com').first() token = user.generate_confirmation_token() response = self.client.get(url_for('auth.confirm',token=token),follow_redirects=True) data=response.get_data(as_text=True) self.assertTrue('You have confirmed your account' in data) #退出 response = self.client.get(url_for('auth.logout'), follow_redirects=True) data = response.get_data(as_text=True) self.assertTrue('You have been logged out' in data)
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# Copyright 2011 OpenStack, 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. """The rescue mode extension.""" import webob from webob import exc from nova.api.openstack import common from nova.api.openstack import extensions as exts from nova.api.openstack import wsgi from nova import compute from nova import exception from nova import flags from nova import log as logging from nova import utils FLAGS = flags.FLAGS LOG = logging.getLogger(__name__) authorize = exts.extension_authorizer('compute', 'rescue') class RescueController(wsgi.Controller): def __init__(self, *args, **kwargs): super(RescueController, self).__init__(*args, **kwargs) self.compute_api = compute.API() def _get_instance(self, context, instance_id): try: return self.compute_api.get(context, instance_id) except exception.InstanceNotFound: msg = _("Server not found") raise exc.HTTPNotFound(msg) @wsgi.action('rescue') @exts.wrap_errors def _rescue(self, req, id, body): """Rescue an instance.""" context = req.environ["nova.context"] authorize(context) if body['rescue'] and 'adminPass' in body['rescue']: password = body['rescue']['adminPass'] else: password = utils.generate_password(FLAGS.password_length) instance = self._get_instance(context, id) try: self.compute_api.rescue(context, instance, rescue_password=password) except exception.InstanceInvalidState as state_error: common.raise_http_conflict_for_instance_invalid_state(state_error, 'rescue') return {'adminPass': password} @wsgi.action('unrescue') @exts.wrap_errors def _unrescue(self, req, id, body): """Unrescue an instance.""" context = req.environ["nova.context"] authorize(context) instance = self._get_instance(context, id) try: self.compute_api.unrescue(context, instance) except exception.InstanceInvalidState as state_error: common.raise_http_conflict_for_instance_invalid_state(state_error, 'unrescue') return webob.Response(status_int=202) class Rescue(exts.ExtensionDescriptor): """Instance rescue mode""" name = "Rescue" alias = "os-rescue" namespace = "http://docs.openstack.org/compute/ext/rescue/api/v1.1" updated = "2011-08-18T00:00:00+00:00" def get_controller_extensions(self): controller = RescueController() extension = exts.ControllerExtension(self, 'servers', controller) return [extension]
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#eachcourse has pre reqs and need to figure out how to take them #we can store all the data as a graph and the edges go to the next class #if there is a cycle you cant make the schedule because if a pre req for class 1 is class 2 and other way around that will have a cycle #first option is to use dfs for checking a cycle we can do a depth limited seach deleting a node once we know it doesnt have a cycle and making time complexity O(n) class Solution: def Cycle(self, graph, course, visited, visitedlist): if course in visitedlist: return visitedlist[course] if course in visited: return True if course not in graph: return False visited.add(course) ret = False for neighbor in graph[course]: if self.Cycle(graph, neighbor, visited, visitedlist): ret = True break visited.remove(course) visitedlist[course] = ret return ret def classes(self, amountCourses, preReqs): graph = {} for preReq in preReqs: if preReq[0] in graph: graph[preReq[0]].append(preReq[1]) else: graph[preReq[0]] = [preReq[1]] for course in range(amountCourses): if self.Cycle(graph, course, set(), {}): return False return True print(Solution().classes(2, [[1, 0]])) print(Solution().classes(2, [[1, 0], [0, 1]]))
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from facebook_business.adobjects.abstractcrudobject import AbstractCrudObject as AbstractCrudObject from facebook_business.adobjects.abstractobject import AbstractObject as AbstractObject from facebook_business.adobjects.objectparser import ObjectParser as ObjectParser from facebook_business.api import FacebookRequest as FacebookRequest from facebook_business.typechecker import TypeChecker as TypeChecker from typing import Any, Optional class HotelRoom(AbstractCrudObject): def __init__(self, fbid: Optional[Any] = ..., parent_id: Optional[Any] = ..., api: Optional[Any] = ...) -> None: ... class Field(AbstractObject.Field): applinks: str = ... base_price: str = ... currency: str = ... description: str = ... id: str = ... images: str = ... margin_level: str = ... name: str = ... room_id: str = ... sale_price: str = ... url: str = ... def api_delete(self, fields: Optional[Any] = ..., params: Optional[Any] = ..., batch: Optional[Any] = ..., success: Optional[Any] = ..., failure: Optional[Any] = ..., pending: bool = ...): ... def api_get(self, fields: Optional[Any] = ..., params: Optional[Any] = ..., batch: Optional[Any] = ..., success: Optional[Any] = ..., failure: Optional[Any] = ..., pending: bool = ...): ... def api_update(self, fields: Optional[Any] = ..., params: Optional[Any] = ..., batch: Optional[Any] = ..., success: Optional[Any] = ..., failure: Optional[Any] = ..., pending: bool = ...): ... def get_pricing_variables(self, fields: Optional[Any] = ..., params: Optional[Any] = ..., batch: Optional[Any] = ..., success: Optional[Any] = ..., failure: Optional[Any] = ..., pending: bool = ...): ...
[ "nandanmarkrao@gmail.com" ]
nandanmarkrao@gmail.com
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/ABSSetup.py
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Mamietti/ABS
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''' This is the list of default addons which we consider the absolute basics ''' default_addons_list = [ 'English (South African) Language Pack', 'English (GB) Language Pack', 'Application Update Service Helper', 'Pocket', 'Web Compat', 'Site Deployment Checker', 'Default', 'Ubuntu Modifications', 'Multi-process staged rollout', 'Disable Prefetch', 'Disable TLS Certificate Transparency' ] ''' These are the addons we want the user to have if they're not going with the basics ''' safety_addons_list = [ 'AdBlocker Ultimate' ]
[ "mauri.miettinen13@gmail.com" ]
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/Session4/Exercises/starter/Question1.py
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import csv # with open("colours_20_simple.csv",mode="r") as csv_file: # csv_reader = csv.reader(csv_file) # #print(csv_reader) # headers = next(csv_reader) # for line in headers: # print(f"{line[0]} {line[1]} {line[2]}") with open("colours_20_simple.csv",mode="r") as csv_file: csv_reader = csv.reader(csv_file) #print(csv_reader) for i,line in enumerate(csv_reader): if i != 0: print(f"{line[0]} {line[1]} {line[2]}")
[ "georgiedignan@gmail.com" ]
georgiedignan@gmail.com
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royrob21/my-first-blog
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from django.conf import settings from django.db import models from django.utils import timezone class Post(models.Model): author = models.ForeignKey(settings.AUTH_USER_MODEL, on_delete=models.CASCADE) title = models.CharField(max_length=200) text = models.TextField() created_date = models.DateTimeField(default=timezone.now) published_date = models.DateTimeField(blank=True, null=True) def publish(self): self.published_date = timezone.now() self.save() def __str__(self): return self.title
[ "roberto.roba@virgilio.it" ]
roberto.roba@virgilio.it
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woowei0102/code2pro
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class Account: def __init__(self, name): self.name = name self._balance = 0 def deposit(self, amount): self._balance = self._balance + amount print('{}存了NT${:,.0f}元.'.format(self.name,self._balance)) def withdraw(self, amount): if amount < self._balance: self._balance = self._balance - amount print('{}提了NT${:,.0f}元.'.format(self.name,self._balance)) else: print('{}的存款不足.'.format(self.name)) def show(self): print('{}餘額NT${:,.0f}元.'.format(self.name,self._balance)) userA = Account("Jack") userA.withdraw(1000) userA.deposit(5000) userA.withdraw(1000) userA.show()
[ "54971984+woowei0102@users.noreply.github.com" ]
54971984+woowei0102@users.noreply.github.com
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/models/layers/layer_normalization.py
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SJ-moon/Transformer
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2023-08-15T02:23:34.556503
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import torch from torch import nn as nn class LayerNorm(nn.Module): def __init__(self, d_model, eps=1e-12): super(LayerNorm,self).__init__() self.gamma = nn.Parameter(torch.ones(d_model)) ## Parameter 와 nn.tensor의 차이점: parameter는 paramter()로 검색이 가능 self.beta = nn.Parameter(torch.zeros(d_model)) self.eps = eps def forward(self, x): mean = x.mean(-1, keepdim = True) std = x.std(-1, keepdim = True) out = (x-mean)/(std + self.eps) out = self.gamma * out + self.beta return out
[ "seungjunee@DESKTOP-NBNJANH.localdomain" ]
seungjunee@DESKTOP-NBNJANH.localdomain
d6de7da64fe8278c4dcc7e25bc1fdf741e82efa8
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/Section-04/create_tables.py
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[]
no_license
tyday/solid-guacamole
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refs/heads/master
2020-05-05T09:01:56.946260
2019-04-14T17:49:13
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import sqlite3 connection = sqlite3.connect('data.db') cursor = connection.cursor() create_table = "CREATE TABLE IF NOT EXISTS users (id INTEGER PRIMARY KEY, username text, password text)" cursor.execute(create_table) create_table = "CREATE TABLE IF NOT EXISTS items (name text, price real)" cursor.execute(create_table) cursor.execute("INSERT INTO items VALUES ('test', 10.99)") connection.commit() connection.close()
[ "tyrday@gmail.com" ]
tyrday@gmail.com
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/venv/bin/flask
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iamaayush98/ChatterBotAPI
4732cdf8e78c1c0d12f4fa8695db0e28ff1f4c61
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refs/heads/master
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#!/home/fake_batman_/PycharmProjects/ChatterBotAPI/venv/bin/python # -*- coding: utf-8 -*- import re import sys from flask.cli import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())
[ "harshitmah98@gmail.com" ]
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ec8bf2a34021126680723c6e854594b55fffde82
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/bindings/pydeck/examples/path_layer.py
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[ "MIT", "Apache-2.0" ]
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visgl/deck.gl
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2023-09-01T00:08:12.457341
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""" PathLayer ========= Locations of the Bay Area Rapid Transit lines. """ import pandas as pd import pydeck as pdk DATA_URL = "https://raw.githubusercontent.com/visgl/deck.gl-data/master/website/bart-lines.json" df = pd.read_json(DATA_URL) def hex_to_rgb(h): h = h.lstrip("#") return tuple(int(h[i : i + 2], 16) for i in (0, 2, 4)) df["color"] = df["color"].apply(hex_to_rgb) view_state = pdk.ViewState(latitude=37.782556, longitude=-122.3484867, zoom=10) layer = pdk.Layer( type="PathLayer", data=df, pickable=True, get_color="color", width_scale=20, width_min_pixels=2, get_path="path", get_width=5, ) r = pdk.Deck(layers=[layer], initial_view_state=view_state, tooltip={"text": "{name}"}) r.to_html("path_layer.html")
[ "noreply@github.com" ]
visgl.noreply@github.com
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EmilioMartinez22/Tienda-Django
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from django.apps import AppConfig class ShopConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'SHOP'
[ "83561976+Kevin-Busy@users.noreply.github.com" ]
83561976+Kevin-Busy@users.noreply.github.com
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24601/pulumi-google-native
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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities from . import outputs __all__ = [ 'GetDomainIamPolicyResult', 'AwaitableGetDomainIamPolicyResult', 'get_domain_iam_policy', 'get_domain_iam_policy_output', ] @pulumi.output_type class GetDomainIamPolicyResult: def __init__(__self__, bindings=None, etag=None, version=None): if bindings and not isinstance(bindings, list): raise TypeError("Expected argument 'bindings' to be a list") pulumi.set(__self__, "bindings", bindings) if etag and not isinstance(etag, str): raise TypeError("Expected argument 'etag' to be a str") pulumi.set(__self__, "etag", etag) if version and not isinstance(version, int): raise TypeError("Expected argument 'version' to be a int") pulumi.set(__self__, "version", version) @property @pulumi.getter def bindings(self) -> Sequence['outputs.BindingResponse']: """ Associates a list of `members` to a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one member. """ return pulumi.get(self, "bindings") @property @pulumi.getter def etag(self) -> str: """ `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. """ return pulumi.get(self, "etag") @property @pulumi.getter def version(self) -> int: """ Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies). """ return pulumi.get(self, "version") class AwaitableGetDomainIamPolicyResult(GetDomainIamPolicyResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetDomainIamPolicyResult( bindings=self.bindings, etag=self.etag, version=self.version) def get_domain_iam_policy(domain_id: Optional[str] = None, options_requested_policy_version: Optional[str] = None, project: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDomainIamPolicyResult: """ Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set. """ __args__ = dict() __args__['domainId'] = domain_id __args__['optionsRequestedPolicyVersion'] = options_requested_policy_version __args__['project'] = project if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('google-native:managedidentities/v1beta1:getDomainIamPolicy', __args__, opts=opts, typ=GetDomainIamPolicyResult).value return AwaitableGetDomainIamPolicyResult( bindings=__ret__.bindings, etag=__ret__.etag, version=__ret__.version) @_utilities.lift_output_func(get_domain_iam_policy) def get_domain_iam_policy_output(domain_id: Optional[pulumi.Input[str]] = None, options_requested_policy_version: Optional[pulumi.Input[Optional[str]]] = None, project: Optional[pulumi.Input[Optional[str]]] = None, opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetDomainIamPolicyResult]: """ Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set. """ ...
[ "noreply@github.com" ]
24601.noreply@github.com
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/check_postgres.py
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[]
no_license
goncalomatos-ic/vector-api
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refs/heads/master
2023-01-10T05:57:55.005675
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import time # Wait for postgres to be up and running # # Improvement: try to connect to postgres # # Note: pinging the container is not enough because # it doesn't ensure that postgres is running time.sleep(10)
[ "goncalo.matos@indiecampers.com" ]
goncalo.matos@indiecampers.com
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import time import webbrowser class Movie: def __init__(self, title, stars, director, trailer_url, votes): self.title = title self.stars = stars self.director = director self.trailer_url = trailer_url self.votes = votes def print_specifications(self): print('\nMOVIE: {}'.format(self.title)) time.sleep(2) print('STARS: {}'.format(self.stars)) time.sleep(2) print('DIRECTOR: {}'.format(self.director)) time.sleep(2) def show_trailer(self): print('\nLoading {} trailer...'.format(self.title)) webbrowser.open_new(self.trailer_url) time.sleep(10) def print_votes(self): print('\n{}'.format(self.title)) time.sleep(2) print("{} votes".format(self.votes)) time.sleep(2)
[ "cmaiacd@gmail.com" ]
cmaiacd@gmail.com
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/schol_library/migrations/0059_auto_20190922_1729.py
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[]
no_license
mustavfaa/back-end
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# Generated by Django 2.2 on 2019-09-22 11:29 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('schol_library', '0058_auto_20190922_1144'), ] operations = [ migrations.AddField( model_name='requestedition', name='checkid', field=models.BooleanField(blank=True, default=False, verbose_name='статус'), ), migrations.AlterField( model_name='checkidrequestedition', name='date_time', field=models.DateTimeField(blank=True, default=datetime.datetime(2019, 9, 22, 17, 29, 19, 729564), null=True, verbose_name='время просмотра'), ), migrations.AlterField( model_name='requestedition', name='date_time', field=models.DateTimeField(blank=True, default=datetime.datetime(2019, 9, 22, 17, 29, 19, 728450), verbose_name='время заявки'), ), ]
[ "72229762+mustavfaa@users.noreply.github.com" ]
72229762+mustavfaa@users.noreply.github.com
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/PYTHON-MUNDO 2/CONVERSAO_TO_BIN_HEX_OCT.py
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[]
no_license
patrickmalg/aulas-python
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refs/heads/master
2020-04-23T02:59:49.879284
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num = int(input("Digite um número inteiro: ")) print("""Escolha uma das bases para conversão: [1] BINÁRIO [2] OCTAL [3] HEXADECIMAL""") opçao = int(input("Opção: ")) if opçao == 1: print("{} convertido para BINÁRIO é igual a {}".format(num, bin(num)[2:])) elif opçao == 2: print("{} convertido para OCTAL é igual a {}".format(num, oct(num)[2:])) elif opçao == 3: print("{} convertido para HEXADECIMAL é igual a {}".format(num, hex(num)[2:])) else: print("Opção inválida. Tente novamente.")
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patrickmoreira2001@hotmail.com
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/book/settings.py
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oneway-fullstack/book-management
a40a9fc5debe54d3c5304334568fa0b47e5b167e
4985ae067bc873b2ca113b2d8978e8a17083a945
refs/heads/main
2023-04-14T05:22:20.110122
2021-04-21T12:02:10
2021-04-21T12:02:10
360,101,616
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""" Django settings for book project. Generated by 'django-admin startproject' using Django 3.2. For more information on this file, see https://docs.djangoproject.com/en/3.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.2/ref/settings/ """ import os from corsheaders.defaults import default_headers from pathlib import Path # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent FRONTEND_DIR = os.path.join(BASE_DIR, 'frontend') TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'django-insecure-*&t+$n+_kj^7*#^z#xu0zri!yr!d3@k^@d^vnf2rg+ko!ooxhg' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [ "*" ] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'webpack_loader', 'rest_framework', 'rest_framework.authtoken', 'djoser', 'corsheaders', 'api', ] REST_FRAMEWORK = { 'DEFAULT_AUTHENTICATION_CLASSES': ( 'rest_framework.authentication.TokenAuthentication', 'rest_framework.authentication.SessionAuthentication', ), } MIDDLEWARE = [ 'corsheaders.middleware.CorsMiddleware', '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 = 'book.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [BASE_DIR / 'templates'] , 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'book.wsgi.application' # Database # https://docs.djangoproject.com/en/3.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': BASE_DIR / 'db.sqlite3', } } # Password validation # https://docs.djangoproject.com/en/3.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.2/howto/static-files/ STATICFILES_DIRS = [os.path.join(BASE_DIR, "site_static")] STATIC_ROOT = os.path.join(BASE_DIR, "static") STATIC_URL = '/static/' MEDIA_ROOT = os.path.join(BASE_DIR, "media") MEDIA_URL = "/media/" APPEND_SLASH = False # Default primary key field type # https://docs.djangoproject.com/en/3.2/ref/settings/#default-auto-field DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField' WEBPACK_LOADER = { 'DEFAULT': { 'CACHE': DEBUG, 'BUNDLE_DIR_NAME': '/bundles/', # must end with slash 'STATS_FILE': os.path.join(FRONTEND_DIR, 'webpack-stats.json'), } } CORS_ALLOW_ALL_ORIGINS=True CORS_ORIGIN_WHITELIST = [ 'http://localhost:8000', 'http://127.0.0.1:8000', 'http://127.0.0.1:8080', ] CORS_ALLOW_HEADERS = list(default_headers) + [ 'x-token', ]
[ "guang.jin@chatterize.com" ]
guang.jin@chatterize.com
3c801ed688a7770f9e2393cb09ac8a8de8a49b2a
0c83baa22afa84347cc319e0cab214ff779e3254
/01_fyyur/starter_code/app.py
8777009175793e3adf6fc9d0e2bd6243990dc656
[]
no_license
rahulaVT/FullStackNanoDegree
52c8380bf6e6f050955f1bc1e3797bfc6ffba132
2b7b6042f8c804637efcba85554abd6518b96eed
refs/heads/master
2022-07-02T19:23:46.698131
2020-05-18T01:26:43
2020-05-18T01:26:43
261,893,486
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#----------------------------------------------------------------------------# # Imports #----------------------------------------------------------------------------# import json import dateutil.parser import babel from flask import Flask, render_template, request, Response, flash, redirect, url_for, jsonify from flask_moment import Moment from flask_sqlalchemy import SQLAlchemy import logging,re from logging import Formatter, FileHandler from flask_wtf import Form from forms import * from flask_migrate import Migrate from operator import itemgetter #----------------------------------------------------------------------------# # App Config. #----------------------------------------------------------------------------# app = Flask(__name__) moment = Moment(app) app.config.from_object('config') db = SQLAlchemy(app) migrate = Migrate(app, db) # TODO: connect to a local postgresql database #----------------------------------------------------------------------------# # Models. #----------------------------------------------------------------------------# class Genre(db.Model): id = db.Column(db.Integer, primary_key = True) name = db.Column(db.String) venue_genre = db.Table('venue_genre', db.Column('genre_id',db.Integer, db.ForeignKey(Genre.id),primary_key=True), db.Column('venue_id',db.Integer, db.ForeignKey("Venue.id"),primary_key=True)) class Venue(db.Model): __tablename__ = 'Venue' id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String) city = db.Column(db.String(120)) state = db.Column(db.String(120)) address = db.Column(db.String(120)) phone = db.Column(db.String(120)) image_link = db.Column(db.String(500)) facebook_link = db.Column(db.String(120)) genres = db.relationship('Genre', secondary = venue_genre, backref = db.backref('venues',lazy=True)) website = db.Column(db.String(120)) seeking_talent = db.Column(db.Boolean, default=False) seeking_description = db.Column(db.String(120)) shows = db.relationship('Show', backref='venue', lazy=True) # Can reference show.venue (as well as venue.shows) def __repr__(self): # return "f'<Venue {self.id} {self.name}>'" return "venue" # TODO: implement any missing fields, as a database migration using Flask-Migrate class Artist(db.Model): __tablename__ = 'Artist' id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String) city = db.Column(db.String(120)) state = db.Column(db.String(120)) phone = db.Column(db.String(120)) genres = db.Column(db.String(120)) image_link = db.Column(db.String(500)) facebook_link = db.Column(db.String(120)) class Show(db.Model): __tablename__ = 'Show' id = db.Column(db.Integer, primary_key=True) start_time = db.Column(db.DateTime, nullable=False, default=datetime.utcnow) # Start time required field artist_id = db.Column(db.Integer, db.ForeignKey('Artist.id'), nullable=False) # Foreign key is the tablename.pk venue_id = db.Column(db.Integer, db.ForeignKey('Venue.id'), nullable=False) def __repr__(self): return '<Show'+ str(self.id)+ str(self.start_time)+ 'artist_id='+str(artist_id) +'venue_id='+str(venue_id)+'>' # return "show" # TODO Implement Show and Artist models, and complete all model relationships and properties, as a database migration. #----------------------------------------------------------------------------# # Filters. #----------------------------------------------------------------------------# def format_datetime(value, format='medium'): date = dateutil.parser.parse(value) if format == 'full': format="EEEE MMMM, d, y 'at' h:mma" elif format == 'medium': format="EE MM, dd, y h:mma" return babel.dates.format_datetime(date, format) app.jinja_env.filters['datetime'] = format_datetime #----------------------------------------------------------------------------# # Controllers. #----------------------------------------------------------------------------# @app.route('/') def index(): return render_template('pages/home.html') # Venues # ---------------------------------------------------------------- @app.route('/venues') def venues(): # TODO: replace with real venues data. # num_shows should be aggregated based on number of upcoming shows per venue. # data=[{ # "city": "San Francisco", # "state": "CA", # "venues": [{ # "id": 1, # "name": "The Musical Hop", # "num_upcoming_shows": 0, # }, { # "id": 3, # "name": "Park Square Live Music & Coffee", # "num_upcoming_shows": 1, # }] # }, { # "city": "New York", # "state": "NY", # "venues": [{ # "id": 2, # "name": "The Dueling Pianos Bar", # "num_upcoming_shows": 0, # }] # }] venues = Venue.query.all() data = [] cities_states = set() for venue in venues: cities_states.add( (venue.city, venue.state) ) # Add tuple # Turn the set into an ordered list cities_states = list(cities_states) cities_states.sort(key=itemgetter(1,0)) now = datetime.now() for loc in cities_states: # For this location, see if there are any venues there, and add if so venues_list = [] for venue in venues: if (venue.city == loc[0]) and (venue.state == loc[1]): # If we've got a venue to add, check how many upcoming shows it has venue_shows = Show.query.filter_by(venue_id=venue.id).all() num_upcoming = 0 for show in venue_shows: if show.start_time > now: num_upcoming += 1 venues_list.append({ "id": venue.id, "name": venue.name, "num_upcoming_shows": num_upcoming }) # After all venues are added to the list for a given location, add it to the data dictionary data.append({ "city": loc[0], "state": loc[1], "venues": venues_list }) return render_template('pages/venues.html', areas=data); @app.route('/venues/search', methods=['POST']) def search_venues(): # TODO: implement search on artists with partial string search. Ensure it is case-insensitive. # seach for Hop should return "The Musical Hop". # search for "Music" should return "The Musical Hop" and "Park Square Live Music & Coffee" search_term = request.form.get('search_term', '').strip() # Use filter, not filter_by when doing LIKE search (i=insensitive to case) venues = Venue.query.filter(Venue.name.ilike('%' + search_term + '%')).all() print(venues) venue_list = [] now = datetime.now() for venue in venues: venue_shows = Show.query.filter_by(venue_id=venue.id).all() num_upcoming = 0 for show in venue_shows: if show.start_time > now: num_upcoming += 1 venue_list.append({ "id": venue.id, "name": venue.name, "num_upcoming_shows": num_upcoming }) response = { "count": len(venues), "data": venue_list } # response={ # "count": 1, # "data": [{ # "id": 2, # "name": "The Dueling Pianos Bar", # "num_upcoming_shows": 0, # }] # } return render_template('pages/search_venues.html', results=response, search_term=search_term) @app.route('/venues/<int:venue_id>') def show_venue(venue_id): # shows the venue page with the given venue_id # TODO: replace with real venue data from the venues table, using venue_id # data1={ # "id": 1, # "name": "The Musical Hop", # "genres": ["Jazz", "Reggae", "Swing", "Classical", "Folk"], # "address": "1015 Folsom Street", # "city": "San Francisco", # "state": "CA", # "phone": "123-123-1234", # "website": "https://www.themusicalhop.com", # "facebook_link": "https://www.facebook.com/TheMusicalHop", # "seeking_talent": True, # "seeking_description": "We are on the lookout for a local artist to play every two weeks. Please call us.", # "image_link": "https://images.unsplash.com/photo-1543900694-133f37abaaa5?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=400&q=60", # "past_shows": [{ # "artist_id": 4, # "artist_name": "Guns N Petals", # "artist_image_link": "https://images.unsplash.com/photo-1549213783-8284d0336c4f?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=300&q=80", # "start_time": "2019-05-21T21:30:00.000Z" # }], # "upcoming_shows": [], # "past_shows_count": 1, # "upcoming_shows_count": 0, # } # data2={ # "id": 2, # "name": "The Dueling Pianos Bar", # "genres": ["Classical", "R&B", "Hip-Hop"], # "address": "335 Delancey Street", # "city": "New York", # "state": "NY", # "phone": "914-003-1132", # "website": "https://www.theduelingpianos.com", # "facebook_link": "https://www.facebook.com/theduelingpianos", # "seeking_talent": False, # "image_link": "https://images.unsplash.com/photo-1497032205916-ac775f0649ae?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=750&q=80", # "past_shows": [], # "upcoming_shows": [], # "past_shows_count": 0, # "upcoming_shows_count": 0, # } # data3={ # "id": 3, # "name": "Park Square Live Music & Coffee", # "genres": ["Rock n Roll", "Jazz", "Classical", "Folk"], # "address": "34 Whiskey Moore Ave", # "city": "San Francisco", # "state": "CA", # "phone": "415-000-1234", # "website": "https://www.parksquarelivemusicandcoffee.com", # "facebook_link": "https://www.facebook.com/ParkSquareLiveMusicAndCoffee", # "seeking_talent": False, # "image_link": "https://images.unsplash.com/photo-1485686531765-ba63b07845a7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=747&q=80", # "past_shows": [{ # "artist_id": 5, # "artist_name": "Matt Quevedo", # "artist_image_link": "https://images.unsplash.com/photo-1495223153807-b916f75de8c5?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=334&q=80", # "start_time": "2019-06-15T23:00:00.000Z" # }], # "upcoming_shows": [{ # "artist_id": 6, # "artist_name": "The Wild Sax Band", # "artist_image_link": "https://images.unsplash.com/photo-1558369981-f9ca78462e61?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=794&q=80", # "start_time": "2035-04-01T20:00:00.000Z" # }, { # "artist_id": 6, # "artist_name": "The Wild Sax Band", # "artist_image_link": "https://images.unsplash.com/photo-1558369981-f9ca78462e61?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=794&q=80", # "start_time": "2035-04-08T20:00:00.000Z" # }, { # "artist_id": 6, # "artist_name": "The Wild Sax Band", # "artist_image_link": "https://images.unsplash.com/photo-1558369981-f9ca78462e61?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=794&q=80", # "start_time": "2035-04-15T20:00:00.000Z" # }], # "past_shows_count": 1, # "upcoming_shows_count": 1, # } venue = Venue.query.get(venue_id) if not venue: # Didn't return one, user must've hand-typed a link into the browser that doesn't exist # Redirect home return redirect(url_for('index')) else: genres = [ genre.name for genre in venue.genres ] past_shows = [] past_shows_count = 0 upcoming_shows = [] upcoming_shows_count = 0 now = datetime.now() for show in venue.shows: if show.start_time > now: upcoming_shows_count += 1 upcoming_shows.append({ "artist_id": show.artist_id, "artist_name": show.artist.name, "artist_image_link": show.artist.image_link, "start_time": format_datetime(str(show.start_time)) }) if show.start_time < now: past_shows_count += 1 past_shows.append({ "artist_id": show.artist_id, "artist_name": show.artist.name, "artist_image_link": show.artist.image_link, "start_time": format_datetime(str(show.start_time)) }) data = { "id": venue_id, "name": venue.name, "genres": genres, "address": venue.address, "city": venue.city, "state": venue.state, # Put the dashes back into phone number "phone": (venue.phone[:3] + '-' + venue.phone[3:6] + '-' + venue.phone[6:]), "website": venue.website, "facebook_link": venue.facebook_link, "seeking_talent": venue.seeking_talent, "seeking_description": venue.seeking_description, "image_link": venue.image_link, "past_shows": past_shows, "past_shows_count": past_shows_count, "upcoming_shows": upcoming_shows, "upcoming_shows_count": upcoming_shows_count } # data = list(filter(lambda d: d['id'] == venue_id, [data1, data2, data3]))[0] return render_template('pages/show_venue.html', venue=data) # Create Venue # ---------------------------------------------------------------- @app.route('/venues/create', methods=['GET']) def create_venue_form(): form = VenueForm() return render_template('forms/new_venue.html', form=form) @app.route('/venues/create', methods=['POST']) def create_venue_submission(): # TODO: insert form data as a new Venue record in the db, instead # TODO: modify data to be the data object returned from db insertion form = VenueForm() name = form.name.data.strip() city = form.city.data.strip() state = form.state.data address = form.address.data.strip() phone = form.phone.data phone = re.sub('\D', '', phone) genres = form.genres.data # ['Alternative', 'Classical', 'Country'] seeking_talent = True if form.seeking_talent.data == 'Yes' else False seeking_description = form.seeking_description.data.strip() image_link = form.image_link.data.strip() website = form.website.data.strip() facebook_link = form.facebook_link.data.strip() if not form.validate(): flash( form.errors ) return redirect(url_for('create_venue_submission')) else: error = False body = {} try: venue = Venue(name=name, city=city, state=state, address=address, phone=phone, \ seeking_talent=seeking_talent, seeking_description=seeking_description, image_link=image_link, \ website=website, facebook_link=facebook_link) for genre in genres: # fetch_genre = session.query(Genre).filter_by(name=genre).one_or_none() # Throws an exception if more than one returned, returns None if none fetch_genre = Genre.query.filter_by(name=genre).one_or_none() # Throws an exception if more than one returned, returns None if none if fetch_genre: # if found a genre, append it to the list venue.genres.append(fetch_genre) else: # fetch_genre was None. It's not created yet, so create it new_genre = Genre(name=genre) db.session.add(new_genre) venue.genres.append(new_genre) # Create a new Genre item and append it db.session.add(venue) db.session.commit() except: error = True db.session.rollback() print(sys.exc_info()) finally: db.session.close() if not error: flash('Venue ' + name + ' was successfully listed!') # on successful db insert, flash success # TODO: on unsuccessful db insert, flash an error instead. # e.g., flash('An error occurred. Venue ' + data.name + ' could not be listed.') # see: http://flask.pocoo.org/docs/1.0/patterns/flashing/ return render_template('pages/home.html') @app.route('/venues/<venue_id>', methods=['DELETE']) def delete_venue(venue_id): venue = Venue.query.get(venue_id) if not venue: # User somehow faked this call, redirect home return redirect(url_for('index')) else: error_on_delete = False # Need to hang on to venue name since will be lost after delete venue_name = venue.name try: db.session.delete(venue) db.session.commit() except: error_on_delete = True db.session.rollback() finally: db.session.close() if error_on_delete: flash('An error occurred deleting venue ' + venue_name) print("Error in delete_venue()") abort(500) else: flash('Successfully removed venue '+venue_name) print(url_for('venues')) return jsonify({ 'deleted': True, 'url': url_for('venues') }) # Artists # ---------------------------------------------------------------- @app.route('/artists') def artists(): # TODO: replace with real data returned from querying the database data=[{ "id": 4, "name": "Guns N Petals", }, { "id": 5, "name": "Matt Quevedo", }, { "id": 6, "name": "The Wild Sax Band", }] return render_template('pages/artists.html', artists=data) @app.route('/artists/search', methods=['POST']) def search_artists(): # TODO: implement search on artists with partial string search. Ensure it is case-insensitive. # seach for "A" should return "Guns N Petals", "Matt Quevado", and "The Wild Sax Band". # search for "band" should return "The Wild Sax Band". response={ "count": 1, "data": [{ "id": 4, "name": "Guns N Petals", "num_upcoming_shows": 0, }] } return render_template('pages/search_artists.html', results=response, search_term=request.form.get('search_term', '')) @app.route('/artists/<int:artist_id>') def show_artist(artist_id): # shows the venue page with the given venue_id # TODO: replace with real venue data from the venues table, using venue_id data1={ "id": 4, "name": "Guns N Petals", "genres": ["Rock n Roll"], "city": "San Francisco", "state": "CA", "phone": "326-123-5000", "website": "https://www.gunsnpetalsband.com", "facebook_link": "https://www.facebook.com/GunsNPetals", "seeking_venue": True, "seeking_description": "Looking for shows to perform at in the San Francisco Bay Area!", "image_link": "https://images.unsplash.com/photo-1549213783-8284d0336c4f?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=300&q=80", "past_shows": [{ "venue_id": 1, "venue_name": "The Musical Hop", "venue_image_link": "https://images.unsplash.com/photo-1543900694-133f37abaaa5?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=400&q=60", "start_time": "2019-05-21T21:30:00.000Z" }], "upcoming_shows": [], "past_shows_count": 1, "upcoming_shows_count": 0, } data2={ "id": 5, "name": "Matt Quevedo", "genres": ["Jazz"], "city": "New York", "state": "NY", "phone": "300-400-5000", "facebook_link": "https://www.facebook.com/mattquevedo923251523", "seeking_venue": False, "image_link": "https://images.unsplash.com/photo-1495223153807-b916f75de8c5?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=334&q=80", "past_shows": [{ "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "venue_image_link": "https://images.unsplash.com/photo-1485686531765-ba63b07845a7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=747&q=80", "start_time": "2019-06-15T23:00:00.000Z" }], "upcoming_shows": [], "past_shows_count": 1, "upcoming_shows_count": 0, } data3={ "id": 6, "name": "The Wild Sax Band", "genres": ["Jazz", "Classical"], "city": "San Francisco", "state": "CA", "phone": "432-325-5432", "seeking_venue": False, "image_link": "https://images.unsplash.com/photo-1558369981-f9ca78462e61?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=794&q=80", "past_shows": [], "upcoming_shows": [{ "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "venue_image_link": "https://images.unsplash.com/photo-1485686531765-ba63b07845a7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=747&q=80", "start_time": "2035-04-01T20:00:00.000Z" }, { "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "venue_image_link": "https://images.unsplash.com/photo-1485686531765-ba63b07845a7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=747&q=80", "start_time": "2035-04-08T20:00:00.000Z" }, { "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "venue_image_link": "https://images.unsplash.com/photo-1485686531765-ba63b07845a7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=747&q=80", "start_time": "2035-04-15T20:00:00.000Z" }], "past_shows_count": 0, "upcoming_shows_count": 3, } data = list(filter(lambda d: d['id'] == artist_id, [data1, data2, data3]))[0] return render_template('pages/show_artist.html', artist=data) # Update # ---------------------------------------------------------------- @app.route('/artists/<int:artist_id>/edit', methods=['GET']) def edit_artist(artist_id): form = ArtistForm() artist={ "id": 4, "name": "Guns N Petals", "genres": ["Rock n Roll"], "city": "San Francisco", "state": "CA", "phone": "326-123-5000", "website": "https://www.gunsnpetalsband.com", "facebook_link": "https://www.facebook.com/GunsNPetals", "seeking_venue": True, "seeking_description": "Looking for shows to perform at in the San Francisco Bay Area!", "image_link": "https://images.unsplash.com/photo-1549213783-8284d0336c4f?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=300&q=80" } # TODO: populate form with fields from artist with ID <artist_id> return render_template('forms/edit_artist.html', form=form, artist=artist) @app.route('/artists/<int:artist_id>/edit', methods=['POST']) def edit_artist_submission(artist_id): # TODO: take values from the form submitted, and update existing # artist record with ID <artist_id> using the new attributes return redirect(url_for('show_artist', artist_id=artist_id)) @app.route('/venues/<int:venue_id>/edit', methods=['GET']) def edit_venue(venue_id): venue = Venue.query.get(venue_id) if venue: form = VenueForm(obj=venue) else: return redirect(url_for('index')) genres = [ genre.name for genre in venue.genres ] venue = { "id": venue_id, "name": venue.name, "genres": genres, "address": venue.address, "city": venue.city, "state": venue.state, "phone": venue.phone, "website": venue.website, "facebook_link": venue.facebook_link, "seeking_talent": venue.seeking_talent, "seeking_description": venue.seeking_description, "image_link": venue.image_link } # venue={ # "id": 1, # "name": "The Musical Hop", # "genres": ["Jazz", "Reggae", "Swing", "Classical", "Folk"], # "address": "1015 Folsom Street", # "city": "San Francisco", # "state": "CA", # "phone": "123-123-1234", # "website": "https://www.themusicalhop.com", # "facebook_link": "https://www.facebook.com/TheMusicalHop", # "seeking_talent": True, # "seeking_description": "We are on the lookout for a local artist to play every two weeks. Please call us.", # "image_link": "https://images.unsplash.com/photo-1543900694-133f37abaaa5?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=400&q=60" # } return render_template('forms/edit_venue.html', form=form, venue=venue) @app.route('/venues/<int:venue_id>/edit', methods=['POST']) def edit_venue_submission(venue_id): form = VenueForm() name = form.name.data.strip() city = form.city.data.strip() state = form.state.data address = form.address.data.strip() phone = form.phone.data phone = re.sub('\D', '', phone) genres = form.genres.data print(form.seeking_talent.data) seeking_talent = True if form.seeking_talent.data == 'Yes' else False seeking_description = form.seeking_description.data.strip() image_link = form.image_link.data.strip() website = form.website.data.strip() facebook_link = form.facebook_link.data.strip() # Redirect back to form if errors in form validation if not form.validate(): flash( form.errors ) return redirect(url_for('edit_venue_submission', venue_id=venue_id)) else: error_in_edit = False try: # get the original venue object venue = Venue.query.get(venue_id) # Update fields venue.name = name venue.city = city venue.state = state venue.address = address venue.phone = phone venue.seeking_talent = seeking_talent venue.seeking_description = seeking_description venue.image_link = image_link venue.website = website venue.facebook_link = facebook_link venue.genres = [] for genre in genres: fetch_genre = Genre.query.filter_by(name=genre).one_or_none() if fetch_genre: # if found a genre, append it to the list venue.genres.append(fetch_genre) else: # fetch_genre was None. It's not created yet, so create it new_genre = Genre(name=genre) db.session.add(new_genre) venue.genres.append(new_genre) # Attempt to save everything db.session.commit() except Exception as e: error_in_edit = True db.session.rollback() finally: db.session.close() if not error_in_edit: # on successful db update, flash success flash('Venue ' + request.form['name'] + ' was successfully updated!') return redirect(url_for('show_venue', venue_id=venue_id)) else: flash('An error occurred. Venue ' + name + ' could not be updated.') print("Error in edit_venue_submission()") abort(500) # return redirect(url_for('show_venue', venue_id=venue_id)) # Create Artist # ---------------------------------------------------------------- @app.route('/artists/create', methods=['GET']) def create_artist_form(): form = ArtistForm() return render_template('forms/new_artist.html', form=form) @app.route('/artists/create', methods=['POST']) def create_artist_submission(): # called upon submitting the new artist listing form # TODO: insert form data as a new Venue record in the db, instead # TODO: modify data to be the data object returned from db insertion # on successful db insert, flash success flash('Artist ' + request.form['name'] + ' was successfully listed!') # TODO: on unsuccessful db insert, flash an error instead. # e.g., flash('An error occurred. Artist ' + data.name + ' could not be listed.') return render_template('pages/home.html') # Shows # ---------------------------------------------------------------- @app.route('/shows') def shows(): # displays list of shows at /shows # TODO: replace with real venues data. # num_shows should be aggregated based on number of upcoming shows per venue. data=[{ "venue_id": 1, "venue_name": "The Musical Hop", "artist_id": 4, "artist_name": "Guns N Petals", "artist_image_link": "https://images.unsplash.com/photo-1549213783-8284d0336c4f?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=300&q=80", "start_time": "2019-05-21T21:30:00.000Z" }, { "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "artist_id": 5, "artist_name": "Matt Quevedo", "artist_image_link": "https://images.unsplash.com/photo-1495223153807-b916f75de8c5?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=334&q=80", "start_time": "2019-06-15T23:00:00.000Z" }, { "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "artist_id": 6, "artist_name": "The Wild Sax Band", "artist_image_link": "https://images.unsplash.com/photo-1558369981-f9ca78462e61?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=794&q=80", "start_time": "2035-04-01T20:00:00.000Z" }, { "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "artist_id": 6, "artist_name": "The Wild Sax Band", "artist_image_link": "https://images.unsplash.com/photo-1558369981-f9ca78462e61?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=794&q=80", "start_time": "2035-04-08T20:00:00.000Z" }, { "venue_id": 3, "venue_name": "Park Square Live Music & Coffee", "artist_id": 6, "artist_name": "The Wild Sax Band", "artist_image_link": "https://images.unsplash.com/photo-1558369981-f9ca78462e61?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=794&q=80", "start_time": "2035-04-15T20:00:00.000Z" }] return render_template('pages/shows.html', shows=data) @app.route('/shows/create') def create_shows(): # renders form. do not touch. form = ShowForm() return render_template('forms/new_show.html', form=form) @app.route('/shows/create', methods=['POST']) def create_show_submission(): # called to create new shows in the db, upon submitting new show listing form # TODO: insert form data as a new Show record in the db, instead # on successful db insert, flash success flash('Show was successfully listed!') # TODO: on unsuccessful db insert, flash an error instead. # e.g., flash('An error occurred. Show could not be listed.') # see: http://flask.pocoo.org/docs/1.0/patterns/flashing/ return render_template('pages/home.html') @app.errorhandler(404) def not_found_error(error): return render_template('errors/404.html'), 404 @app.errorhandler(500) def server_error(error): return render_template('errors/500.html'), 500 if not app.debug: file_handler = FileHandler('error.log') file_handler.setFormatter( Formatter('%(asctime)s %(levelname)s: %(message)s [in %(pathname)s:%(lineno)d]') ) app.logger.setLevel(logging.INFO) file_handler.setLevel(logging.INFO) app.logger.addHandler(file_handler) app.logger.info('errors') #----------------------------------------------------------------------------# # Launch. #----------------------------------------------------------------------------# # Default port: if __name__ == '__main__': app.run() # Or specify port manually: ''' if __name__ == '__main__': port = int(os.environ.get('PORT', 5000)) app.run(host='0.0.0.0', port=port) '''
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"""Service access rights models """ from pydantic import BaseModel, Field from pydantic.types import PositiveInt GroupId = PositiveInt class ServiceGroupAccessRights(BaseModel): execute_access: bool = Field( default=False, description="defines whether the group can execute the service", ) write_access: bool = Field( default=False, description="defines whether the group can modify the service" ) class ServiceAccessRights(BaseModel): access_rights: dict[GroupId, ServiceGroupAccessRights] | None = Field( None, alias="accessRights", description="service access rights per group id", )
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# Dynamic Programming implementation of LCS problem def lcs(X , Y): # find the length of the strings m = len(X) n = len(Y) # declaring the array for storing the dp values L = [[None]*(n+1) for i in xrange(m+1)] """Following steps build L[m+1][n+1] in bottom up fashion Note: L[i][j] contains length of LCS of X[0..i-1] and Y[0..j-1]""" for i in range(m+1): for j in range(n+1): if i == 0 or j == 0 : L[i][j] = 0 elif X[i-1] == Y[j-1]: L[i][j] = L[i-1][j-1]+1 else: L[i][j] = max(L[i-1][j] , L[i][j-1]) # L[m][n] contains the length of LCS of X[0..n-1] & Y[0..m-1] return L[m][n] #end of function lcs # Driver program to test the above function X = "AGGTAB" Y = "GXTXAYB" print "Length of LCS is ", lcs(X, Y) # This code is contributed by Nikhil Kumar Singh(nickzuck_007)
[ "ayushranjancr7@gmail.comgit config --global user.name Ayushgit config --global user.email ayushranjancr7@gmail.com" ]
ayushranjancr7@gmail.comgit config --global user.name Ayushgit config --global user.email ayushranjancr7@gmail.com
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N = int(input()) if N % 2 == 0: print(N // 2) else: print(N //2 + 1)
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#!/usr/bin/env python #-*- coding:utf-8 -*- ''' Created on 14:03 2017/11/4 @author: acer ''' from basic import Basic import urllib2 import poster.encode from poster.streaminghttp import register_openers class Media(object): def __init__(self): register_openers() #上传图片 def uplaod(self, accessToken, filePath, mediaType): openFile = open(filePath, "rb") param = {'media': openFile} postData, postHeaders = poster.encode.multipart_encode(param) postUrl = "https://api.weixin.qq.com/cgi-bin/media/upload?access_token=%s&type=%s" % (accessToken, mediaType) request = urllib2.Request(postUrl, postData, postHeaders) urlResp = urllib2.urlopen(request) print urlResp.read() if __name__ == '__main__': myMedia = Media() accessToken = Basic().get_access_token() filePath = "D:/Pythonwork/weixin/weixitest/test.jpg" #请安实际填写 mediaType = "image" myMedia.uplaod(accessToken, filePath, mediaType)
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/ORMproject1/testApp/migrations/0002_proxyemployee_proxyemployee2.py
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# Generated by Django 3.0.5 on 2020-04-30 05:40 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('testApp', '0001_initial'), ] operations = [ migrations.CreateModel( name='ProxyEmployee', fields=[ ], options={ 'proxy': True, 'indexes': [], 'constraints': [], }, bases=('testApp.employee',), ), migrations.CreateModel( name='ProxyEmployee2', fields=[ ], options={ 'proxy': True, 'indexes': [], 'constraints': [], }, bases=('testApp.employee',), ), ]
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/Ecommerce-site1/site1/store/migrations/0002_productmdl_image.py
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# Generated by Django 3.0.7 on 2020-08-21 07:56 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('store', '0001_initial'), ] operations = [ migrations.AddField( model_name='productmdl', name='image', field=models.ImageField(blank=True, null=True, upload_to=''), ), ]
[ "sudarshannkarki@gmail.com" ]
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/openapi_client/models/overpayment.py
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# coding: utf-8 """ Accounting API No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501 The version of the OpenAPI document: 2.0.0 Contact: api@xero.com Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six class Overpayment(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { 'type': 'str', 'contact': 'Contact', 'date': 'date', 'status': 'str', 'line_amount_types': 'LineAmountTypes', 'line_items': 'list[LineItem]', 'sub_total': 'float', 'total_tax': 'float', 'total': 'float', 'updated_date_utc': 'datetime', 'currency_code': 'CurrencyCode', 'overpayment_id': 'str', 'currency_rate': 'float', 'remaining_credit': 'float', 'allocations': 'list[Allocation]', 'payments': 'list[Payment]', 'has_attachments': 'bool', 'attachments': 'list[Attachment]' } attribute_map = { 'type': 'Type', 'contact': 'Contact', 'date': 'Date', 'status': 'Status', 'line_amount_types': 'LineAmountTypes', 'line_items': 'LineItems', 'sub_total': 'SubTotal', 'total_tax': 'TotalTax', 'total': 'Total', 'updated_date_utc': 'UpdatedDateUTC', 'currency_code': 'CurrencyCode', 'overpayment_id': 'OverpaymentID', 'currency_rate': 'CurrencyRate', 'remaining_credit': 'RemainingCredit', 'allocations': 'Allocations', 'payments': 'Payments', 'has_attachments': 'HasAttachments', 'attachments': 'Attachments' } def __init__(self, type=None, contact=None, date=None, status=None, line_amount_types=None, line_items=None, sub_total=None, total_tax=None, total=None, updated_date_utc=None, currency_code=None, overpayment_id=None, currency_rate=None, remaining_credit=None, allocations=None, payments=None, has_attachments=None, attachments=None): # noqa: E501 """Overpayment - a model defined in OpenAPI""" # noqa: E501 self._type = None self._contact = None self._date = None self._status = None self._line_amount_types = None self._line_items = None self._sub_total = None self._total_tax = None self._total = None self._updated_date_utc = None self._currency_code = None self._overpayment_id = None self._currency_rate = None self._remaining_credit = None self._allocations = None self._payments = None self._has_attachments = None self._attachments = None self.discriminator = None if type is not None: self.type = type if contact is not None: self.contact = contact if date is not None: self.date = date if status is not None: self.status = status if line_amount_types is not None: self.line_amount_types = line_amount_types if line_items is not None: self.line_items = line_items if sub_total is not None: self.sub_total = sub_total if total_tax is not None: self.total_tax = total_tax if total is not None: self.total = total if updated_date_utc is not None: self.updated_date_utc = updated_date_utc if currency_code is not None: self.currency_code = currency_code if overpayment_id is not None: self.overpayment_id = overpayment_id if currency_rate is not None: self.currency_rate = currency_rate if remaining_credit is not None: self.remaining_credit = remaining_credit if allocations is not None: self.allocations = allocations if payments is not None: self.payments = payments if has_attachments is not None: self.has_attachments = has_attachments if attachments is not None: self.attachments = attachments @property def type(self): """Gets the type of this Overpayment. # noqa: E501 See Overpayment Types # noqa: E501 :return: The type of this Overpayment. # noqa: E501 :rtype: str """ return self._type @type.setter def type(self, type): """Sets the type of this Overpayment. See Overpayment Types # noqa: E501 :param type: The type of this Overpayment. # noqa: E501 :type: str """ allowed_values = ["RECEIVE-OVERPAYMENT", "SPEND-OVERPAYMENT"] # noqa: E501 if type not in allowed_values: raise ValueError( "Invalid value for `type` ({0}), must be one of {1}" # noqa: E501 .format(type, allowed_values) ) self._type = type @property def contact(self): """Gets the contact of this Overpayment. # noqa: E501 :return: The contact of this Overpayment. # noqa: E501 :rtype: Contact """ return self._contact @contact.setter def contact(self, contact): """Sets the contact of this Overpayment. :param contact: The contact of this Overpayment. # noqa: E501 :type: Contact """ self._contact = contact @property def date(self): """Gets the date of this Overpayment. # noqa: E501 The date the overpayment is created YYYY-MM-DD # noqa: E501 :return: The date of this Overpayment. # noqa: E501 :rtype: date """ return self._date @date.setter def date(self, date): """Sets the date of this Overpayment. The date the overpayment is created YYYY-MM-DD # noqa: E501 :param date: The date of this Overpayment. # noqa: E501 :type: date """ self._date = date @property def status(self): """Gets the status of this Overpayment. # noqa: E501 See Overpayment Status Codes # noqa: E501 :return: The status of this Overpayment. # noqa: E501 :rtype: str """ return self._status @status.setter def status(self, status): """Sets the status of this Overpayment. See Overpayment Status Codes # noqa: E501 :param status: The status of this Overpayment. # noqa: E501 :type: str """ allowed_values = ["AUTHORISED", "PAID", "VOIDED"] # noqa: E501 if status not in allowed_values: raise ValueError( "Invalid value for `status` ({0}), must be one of {1}" # noqa: E501 .format(status, allowed_values) ) self._status = status @property def line_amount_types(self): """Gets the line_amount_types of this Overpayment. # noqa: E501 :return: The line_amount_types of this Overpayment. # noqa: E501 :rtype: LineAmountTypes """ return self._line_amount_types @line_amount_types.setter def line_amount_types(self, line_amount_types): """Sets the line_amount_types of this Overpayment. :param line_amount_types: The line_amount_types of this Overpayment. # noqa: E501 :type: LineAmountTypes """ self._line_amount_types = line_amount_types @property def line_items(self): """Gets the line_items of this Overpayment. # noqa: E501 See Overpayment Line Items # noqa: E501 :return: The line_items of this Overpayment. # noqa: E501 :rtype: list[LineItem] """ return self._line_items @line_items.setter def line_items(self, line_items): """Sets the line_items of this Overpayment. See Overpayment Line Items # noqa: E501 :param line_items: The line_items of this Overpayment. # noqa: E501 :type: list[LineItem] """ self._line_items = line_items @property def sub_total(self): """Gets the sub_total of this Overpayment. # noqa: E501 The subtotal of the overpayment excluding taxes # noqa: E501 :return: The sub_total of this Overpayment. # noqa: E501 :rtype: float """ return self._sub_total @sub_total.setter def sub_total(self, sub_total): """Sets the sub_total of this Overpayment. The subtotal of the overpayment excluding taxes # noqa: E501 :param sub_total: The sub_total of this Overpayment. # noqa: E501 :type: float """ self._sub_total = sub_total @property def total_tax(self): """Gets the total_tax of this Overpayment. # noqa: E501 The total tax on the overpayment # noqa: E501 :return: The total_tax of this Overpayment. # noqa: E501 :rtype: float """ return self._total_tax @total_tax.setter def total_tax(self, total_tax): """Sets the total_tax of this Overpayment. The total tax on the overpayment # noqa: E501 :param total_tax: The total_tax of this Overpayment. # noqa: E501 :type: float """ self._total_tax = total_tax @property def total(self): """Gets the total of this Overpayment. # noqa: E501 The total of the overpayment (subtotal + total tax) # noqa: E501 :return: The total of this Overpayment. # noqa: E501 :rtype: float """ return self._total @total.setter def total(self, total): """Sets the total of this Overpayment. The total of the overpayment (subtotal + total tax) # noqa: E501 :param total: The total of this Overpayment. # noqa: E501 :type: float """ self._total = total @property def updated_date_utc(self): """Gets the updated_date_utc of this Overpayment. # noqa: E501 UTC timestamp of last update to the overpayment # noqa: E501 :return: The updated_date_utc of this Overpayment. # noqa: E501 :rtype: datetime """ return self._updated_date_utc @updated_date_utc.setter def updated_date_utc(self, updated_date_utc): """Sets the updated_date_utc of this Overpayment. UTC timestamp of last update to the overpayment # noqa: E501 :param updated_date_utc: The updated_date_utc of this Overpayment. # noqa: E501 :type: datetime """ self._updated_date_utc = updated_date_utc @property def currency_code(self): """Gets the currency_code of this Overpayment. # noqa: E501 :return: The currency_code of this Overpayment. # noqa: E501 :rtype: CurrencyCode """ return self._currency_code @currency_code.setter def currency_code(self, currency_code): """Sets the currency_code of this Overpayment. :param currency_code: The currency_code of this Overpayment. # noqa: E501 :type: CurrencyCode """ self._currency_code = currency_code @property def overpayment_id(self): """Gets the overpayment_id of this Overpayment. # noqa: E501 Xero generated unique identifier # noqa: E501 :return: The overpayment_id of this Overpayment. # noqa: E501 :rtype: str """ return self._overpayment_id @overpayment_id.setter def overpayment_id(self, overpayment_id): """Sets the overpayment_id of this Overpayment. Xero generated unique identifier # noqa: E501 :param overpayment_id: The overpayment_id of this Overpayment. # noqa: E501 :type: str """ self._overpayment_id = overpayment_id @property def currency_rate(self): """Gets the currency_rate of this Overpayment. # noqa: E501 The currency rate for a multicurrency overpayment. If no rate is specified, the XE.com day rate is used # noqa: E501 :return: The currency_rate of this Overpayment. # noqa: E501 :rtype: float """ return self._currency_rate @currency_rate.setter def currency_rate(self, currency_rate): """Sets the currency_rate of this Overpayment. The currency rate for a multicurrency overpayment. If no rate is specified, the XE.com day rate is used # noqa: E501 :param currency_rate: The currency_rate of this Overpayment. # noqa: E501 :type: float """ self._currency_rate = currency_rate @property def remaining_credit(self): """Gets the remaining_credit of this Overpayment. # noqa: E501 The remaining credit balance on the overpayment # noqa: E501 :return: The remaining_credit of this Overpayment. # noqa: E501 :rtype: float """ return self._remaining_credit @remaining_credit.setter def remaining_credit(self, remaining_credit): """Sets the remaining_credit of this Overpayment. The remaining credit balance on the overpayment # noqa: E501 :param remaining_credit: The remaining_credit of this Overpayment. # noqa: E501 :type: float """ self._remaining_credit = remaining_credit @property def allocations(self): """Gets the allocations of this Overpayment. # noqa: E501 See Allocations # noqa: E501 :return: The allocations of this Overpayment. # noqa: E501 :rtype: list[Allocation] """ return self._allocations @allocations.setter def allocations(self, allocations): """Sets the allocations of this Overpayment. See Allocations # noqa: E501 :param allocations: The allocations of this Overpayment. # noqa: E501 :type: list[Allocation] """ self._allocations = allocations @property def payments(self): """Gets the payments of this Overpayment. # noqa: E501 See Payments # noqa: E501 :return: The payments of this Overpayment. # noqa: E501 :rtype: list[Payment] """ return self._payments @payments.setter def payments(self, payments): """Sets the payments of this Overpayment. See Payments # noqa: E501 :param payments: The payments of this Overpayment. # noqa: E501 :type: list[Payment] """ self._payments = payments @property def has_attachments(self): """Gets the has_attachments of this Overpayment. # noqa: E501 boolean to indicate if a overpayment has an attachment # noqa: E501 :return: The has_attachments of this Overpayment. # noqa: E501 :rtype: bool """ return self._has_attachments @has_attachments.setter def has_attachments(self, has_attachments): """Sets the has_attachments of this Overpayment. boolean to indicate if a overpayment has an attachment # noqa: E501 :param has_attachments: The has_attachments of this Overpayment. # noqa: E501 :type: bool """ self._has_attachments = has_attachments @property def attachments(self): """Gets the attachments of this Overpayment. # noqa: E501 See Attachments # noqa: E501 :return: The attachments of this Overpayment. # noqa: E501 :rtype: list[Attachment] """ return self._attachments @attachments.setter def attachments(self, attachments): """Sets the attachments of this Overpayment. See Attachments # noqa: E501 :param attachments: The attachments of this Overpayment. # noqa: E501 :type: list[Attachment] """ self._attachments = attachments def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_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 pprint.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, Overpayment): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other
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import arcade def diagnose_name_gender_attraction_health(fish_list, info_list): # Funtions som skriver ut fiskarnas status # Informationen ligger lagrad i "info_list" if len(info_list) < len(fish_list): list_length = len(info_list) else: list_length = len(fish_list) for i in range(list_length): x = fish_list[i].center_x y = fish_list[i].center_y arcade.draw_text(str(info_list[i][0]) + " " + str(info_list[i][1]), x, y + 24, arcade.color.BLACK, 18) arcade.draw_text(str(info_list[i][2]), x, y, arcade.color.BLACK, 18) arcade.draw_text(str(info_list[i][3]), x, y, arcade.color.BLACK, 18, anchor_x="left", anchor_y="top")
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#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import numpy as np from ax.models.random.alebo_initializer import ALEBOInitializer from ax.utils.common.testutils import TestCase class ALEBOSobolTest(TestCase): def testALEBOSobolModel(self): B = np.array([[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]) Q = np.linalg.pinv(B) @ B # Test setting attributes m = ALEBOInitializer(B=B) self.assertTrue(np.allclose(Q, m.Q)) # Test gen Z, w = m.gen(5, bounds=[(-1.0, 1.0)] * 3) self.assertEqual(Z.shape, (5, 3)) self.assertTrue(Z.min() >= -1.0) self.assertTrue(Z.max() <= 1.0) # Verify that it is in the subspace self.assertTrue(np.allclose(Q @ Z.transpose(), Z.transpose())) m = ALEBOInitializer(B=B, nsamp=1) with self.assertRaises(ValueError): m.gen(2, bounds=[(-1.0, 1.0)] * 3)
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from typing import List class TreeNode: def __init__(self, x): self.val = x self.left = None self.right = None class Solution: def buildTree(self, preorder: List[int], inorder: List[int]) -> TreeNode: if not preorder: return None root = TreeNode(preorder[0]) mid = inorder.index(preorder[0]) root.left = self.buildTree(preorder[1:mid+1], inorder[:mid]) root.right = self.buildTree(preorder[mid+1:], inorder[mid+1:]) return root if __name__ == "__main__": s = Solution() result = s.buildTree([3, 9, 20, 15, 7], [9, 3, 15, 20, 7]) print(result)
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#!/usr/bin/python # Spam RGB test pattern over UDP import socket import fcntl import struct import time UDP_PORT = 5453 colors = ( (255,0,0), (0,255,0), (0,0,255), (255,255,255) ) # from: # https://www.quora.com/Which-Python-library-allows-us-to-specify-network-interface-to-connect-to-the-Internet def get_ip_address(ifname): s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) return socket.inet_ntoa(fcntl.ioctl( s.fileno(), 0x8915, struct.pack('256s', ifname[:15]) )[20:24]) def sendColor(color): MESSAGE = "" MESSAGE += chr(0x50) #Magic MESSAGE += chr(0x4c) MESSAGE += chr(0x53) MESSAGE += chr(0x54) MESSAGE += chr(0x00) # blend time MESSAGE += chr(0x00) MESSAGE += chr(0x00) MESSAGE += chr(0x00) for pixel in range(0,8*8): MESSAGE += chr(color[0]) MESSAGE += chr(color[1]) MESSAGE += chr(color[2]) s.sendto(MESSAGE, ('<broadcast>', UDP_PORT)) s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) s.bind((get_ip_address("wlan0"), 0)) s.setsockopt(socket.SOL_SOCKET, socket.SO_BROADCAST, 1) while True: for color in colors: sendColor(color) time.sleep(1)
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""" 1. Написать функцию host_ping(), в которой с помощью утилиты ping будет проверяться доступность сетевых узлов. Аргументом функции является список, в котором каждый сетевой узел должен быть представлен именем хоста или ip-адресом. В функции необходимо перебирать ip-адреса и проверять их доступность с выводом соответствующего сообщения («Узел доступен», «Узел недоступен»). При этом ip-адрес сетевого узла должен создаваться с помощью функции ip_address(). """ from ipaddress import ip_address from subprocess import Popen, PIPE host_list = ['127.0.0.1', 'google.com', 'google.ru', 'ya.ru', '192.0.2.1'] def host_ping(my_list, timeout=1000, requests=1): """ Функция пингует IP :param my_list: список IP :param timeout: параметр для команды IP - сколько ждать ответа :param requests: параметр для команды IP - сколько запросов слать :return: возвращает словарик массивами у каких адресов прошел пинг, а у каких - нет """ res = {'Пинг проходит': '', 'Пинг не проходит': ''} print('Начинаем проверочку: ') for host in my_list: try: network = ip_address(host) except ValueError: # print(f'{host} - не IP!') # если нужен вывод IP это или нет network = host my_ping = Popen(f'ping {network} -w {timeout} -n {requests}', shell=False, stdout=PIPE, stderr=PIPE) my_wait = my_ping.wait() if my_wait == 0: print(f'{host} - Хост доступен!') res['Пинг проходит'] += f'{str(network)}\n' else: print(f'{host} - Хост недоступен!') res['Пинг не проходит'] += f'{str(network)}\n' return res if __name__ == '__main__': host_ping(host_list)
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import os from selenium import webdriver from selenium.webdriver.chrome.options import Options from selenium.webdriver.common.by import By from selenium_wework_main.page.add_member import AddMember class Main: def __init__(self): # options = Options() # options.debugger_address = '127.0.0.1:9222' # self._driver = webdriver.Chrome(options=options) browser = os.getenv('browser') if browser == 'chrome': self._driver = webdriver.Chrome() self._driver.get('https://work.weixin.qq.com/wework_admin/frame') def goto_add_member(self): # click add member self._driver.find_element(By.CSS_SELECTOR,'.index_service_cnt_itemWrap:nth-child(1)').click() return AddMember(self._driver)
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from keras.models import Sequential from keras.layers import Conv2D from keras.layers import MaxPooling2D from keras.layers import Dense from keras.layers import Flatten from keras.layers import Dropout from keras.layers import BatchNormalization filters = 32#滤镜个数 filter_size = 3#滤镜大小 pooling_size = 3 conv_layers = 2 dense_units = 256 dense_layers = 2 use_drop = True my1stCNN = Sequential() if (conv_layers == 1): my1stCNN.add(Conv2D(filters, (filter_size,filter_size), activation = 'relu', input_shape = (30,46,3))) else: my1stCNN.add(Conv2D(filters, (filter_size,filter_size), activation = 'relu', input_shape = (30,46,3))) for i in range(conv_layers -1): my1stCNN.add(Conv2D(64, (filter_size,filter_size), activation = 'relu')) my1stCNN.add(MaxPooling2D(pool_size = (pooling_size,pooling_size))) my1stCNN.add(Dropout(0.35)) my1stCNN.add(Flatten()) for i in range(dense_layers): my1stCNN.add(Dense(units = dense_units, activation = 'relu')) if (use_drop): my1stCNN.add(Dropout(0.5)) my1stCNN.add(Dense(units= 10,activation='softmax')) print(my1stCNN.summary()) # optimizer, regularization my1stCNN.compile(optimizer = 'adam', loss = 'categorical_crossentropy', metrics = ['accuracy']) # training from keras.preprocessing.image import ImageDataGenerator train_datagen = ImageDataGenerator(rescale = 1./255) test_datagen = ImageDataGenerator(rescale = 1./255) train_set = train_datagen.flow_from_directory('/Users/like/Downloads/data_set/train_set', target_size = (30,46), batch_size = 5, class_mode = 'categorical') test_set = test_datagen.flow_from_directory('/Users/like/Downloads/data_set/test_set', target_size = (30,46), batch_size = 5, class_mode = 'categorical') my1stCNN.fit_generator(train_set, nb_epoch = 20, steps_per_epoch = 400, validation_data = test_set, nb_val_samples = 300, use_multiprocessing = True, workers = 4) ##save architecture #json_string = my1stCNN.to_json() #open('my_model_architecture3.json','w').write(json_string) ##save weights #my1stCNN.save_weights('my_model_weights3.h5')
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/apps/operation/migrations/0001_initial.py
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ChenHangKeep/Django-Education
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# -*- coding: utf-8 -*- # Generated by Django 1.11 on 2018-11-19 19:16 from __future__ import unicode_literals import datetime from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='CourseComments', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('comments', models.CharField(max_length=200, verbose_name='评论')), ('add_time', models.DateTimeField(default=datetime.datetime.now, verbose_name='添加时间')), ], options={ 'verbose_name': '课程评论', 'verbose_name_plural': '课程评论', }, ), migrations.CreateModel( name='UserAsk', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=20, verbose_name='姓名')), ('mobile', models.CharField(max_length=11, verbose_name='手机')), ('course_name', models.CharField(max_length=50, verbose_name='课程名')), ('add_time', models.DateTimeField(default=datetime.datetime.now, verbose_name='添加时间')), ], options={ 'verbose_name': '用户咨询', 'verbose_name_plural': '用户咨询', }, ), migrations.CreateModel( name='UserCourse', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('add_time', models.DateTimeField(default=datetime.datetime.now, verbose_name='添加时间')), ], options={ 'verbose_name': '用户课程', 'verbose_name_plural': '用户课程', }, ), migrations.CreateModel( name='UserFavorite', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('fav_id', models.IntegerField(default=0, verbose_name='数据id')), ('fav_type', models.IntegerField(choices=[(1, '课程'), (2, '课程机构'), (3, '讲师')], default=1, verbose_name='收藏类型')), ('add_time', models.DateTimeField(default=datetime.datetime.now, verbose_name='添加时间')), ], options={ 'verbose_name': '用户收藏', 'verbose_name_plural': '用户收藏', }, ), migrations.CreateModel( name='UserMessage', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('user', models.IntegerField(default=0, verbose_name='接收用户')), ('message', models.CharField(max_length=500, verbose_name='消息内容')), ('has_read', models.BooleanField(default=False, verbose_name='是否已读')), ('add_time', models.DateTimeField(default=datetime.datetime.now, verbose_name='添加时间')), ], options={ 'verbose_name': '用户消息', 'verbose_name_plural': '用户消息', }, ), ]
[ "596560557@qq.com" ]
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/graphValidTree.py
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''' Given n nodes labeled from 0 to n - 1 and a list of undirected edges (each edge is a pair of nodes), write a function to check whether these edges make up a valid tree. For example: Given n = 5 and edges = [[0, 1], [0, 2], [0, 3], [1, 4]], return true. Given n = 5 and edges = [[0, 1], [1, 2], [2, 3], [1, 3], [1, 4]], return false. Hint: Given n = 5 and edges = [[0, 1], [1, 2], [3, 4]], what should your return? Is this case a valid tree? According to the definition of tree on Wikipedia: "a tree is an undirected graph in which any two vertices are connected by exactly one path. In other words, any connected graph without simple cycles is a tree." Note: you can assume that no duplicate edges will appear in edges. Since all edges are undirected, [0, 1] is the same as [1, 0] and thus will not appear together in edges. ''' class Solution(object): def makeMap(self, n, edges, linkMap): for i in xrange(n): linkMap[i] = [] for n1, n2 in edges: linkMap[n1] += [n2] linkMap[n2] += [n1] def isValidTravel(self, parent, node, linkMap, visited): visited[node] = True for nei in linkMap[node]: if nei == parent: continue elif not nei in visited: res = self.isValidTravel(node, nei, linkMap, visited) if not res: return res else: return False return True def validTree(self, n, edges): linkMap, visited = {}, {} self.makeMap(n, edges, linkMap) res = self.isValidTravel(None, 0, linkMap, visited) return len(visited.keys()) == n and res # for node in xrange(n): # if not node in visited: # res = self.isValidTravel(None, node, linkMap, visited) # if res == False: # return res # return True sol = Solution() n, edges = 5, [[0, 1], [0, 2], [0, 3], [1, 4]] print sol.validTree(n, edges) n, edges = 5, [[0, 1], [1, 2], [2, 3], [1, 3], [1, 4]] print sol.validTree(n, edges) n, edges = 5, [[0, 1], [1, 2], [3, 4]] print sol.validTree(n, edges)
[ "ys486@cornell.edu" ]
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/Classification/Decision Tree Classification/Python/decision_tree_classification.py
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chh14025/ClassAssignments
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2022-08-02T06:45:57.707092
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Apr 27 16:05:22 2020 @author: s.p. """ import numpy as np import pandas as pd import matplotlib.pyplot as plt %matplotlib inline dataset = pd.read_csv('Social_Network_Ads.csv') x = dataset.iloc[:, 2:4].values y = dataset.iloc[:, 4:].values from sklearn.model_selection import train_test_split x_train, x_test, y_train, y_test = train_test_split(x,y,test_size = 0.25, random_state = 0) #No Feature Scailing needed for Decision Tree, but will make high res chart generate quicker from sklearn.preprocessing import StandardScaler sc_x = StandardScaler() x_train = sc_x.fit_transform(x_train) x_test = sc_x.transform(x_test) from sklearn.tree import DecisionTreeClassifier classifier = DecisionTreeClassifier(criterion = 'entropy', random_state = 0) classifier.fit(x_train, y_train) y_pred = classifier.predict(x_test) #Confusion Matrix from sklearn.metrics import confusion_matrix cm = confusion_matrix(y_test, y_pred) cm from matplotlib.colors import ListedColormap x_set, y_set = x_train, y_train x1, x2 = np.meshgrid(np.arange(start = x_set[:, 0].min() -1, stop = x_set[:,0].max() +1,step = 0.01), np.arange(start = x_set[:, 1].min() -1, stop = x_set[:,1].max() +1,step = 0.01)) plt.contourf(x1, x2, classifier.predict(np.array([x1.ravel(),x2.ravel()]).T).reshape(x1.shape)) plt.xlim(x1.min(), x1.max()) plt.ylim(x2.min(), x2.max()) for i, j in enumerate(np.unique(y_set)): plt.scatter(x_set[y_set == j, 0], x_set[y_set == j, 1], c = ListedColormap(('red', 'green'))(i), label = j) plt.title('Decision Tree Classification (Training set)') plt.xlabel('Age') plt.ylabel('Estimated Salary') plt.legend() plt.show()
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/models/image_segmentation/tensorflow/maskrcnn/inference/fp32/coco.py
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# # -*- coding: utf-8 -*- # # Copyright (c) 2019 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. # # SPDX-License-Identifier: EPL-2.0 # """ Mask R-CNN Configurations and data loading code for MS COCO. Copyright (c) 2017 Matterport, Inc. Licensed under the MIT License (see LICENSE for details) Written by Waleed Abdulla ------------------------------------------------------------ Usage: import the module (see Jupyter notebooks for examples), or run from the command line as such: # Train a new model starting from pre-trained COCO weights python3 coco.py train --dataset=/path/to/coco/ --model=coco # Train a new model starting from ImageNet weights python3 coco.py train --dataset=/path/to/coco/ --model=imagenet # Continue training a model that you had trained earlier python3 coco.py train --dataset=/path/to/coco/ --model=/path/to/weights.h5 # Continue training the last model you trained python3 coco.py train --dataset=/path/to/coco/ --model=last # Run COCO evaluatoin on the last model you trained python3 coco.py evaluate --dataset=/path/to/coco/ --model=last """ import os import time import numpy as np import subprocess from pdb import set_trace as bp # Download and install the Python COCO tools from https://github.com/waleedka/coco # That's a fork from the original https://github.com/pdollar/coco with a bug # fix for Python 3. # I submitted a pull request https://github.com/cocodataset/cocoapi/pull/50 # If the PR is merged then use the original repo. # Note: Edit PythonAPI/Makefile and replace "python" with "python3". from pycocotools.coco import COCO from pycocotools.cocoeval import COCOeval from pycocotools import mask as maskUtils import zipfile import urllib.request import shutil from config import Config import utils import model as modellib # Path to trained weights file COCO_MODEL_PATH = os.path.join(os.environ["MOUNT_EXTERNAL_MODELS_SOURCE"], "mask_rcnn_coco.h5") # Directory to save logs and model checkpoints, if not provided # through the command line argument --logs DEFAULT_LOGS_DIR = os.path.join(os.environ["MOUNT_BENCHMARK"], "common/tensorflow/logs") DEFAULT_DATASET_YEAR = "2014" ############################################################ # Configurations ############################################################ class CocoConfig(Config): """Configuration for training on MS COCO. Derives from the base Config class and overrides values specific to the COCO dataset. """ # Give the configuration a recognizable name NAME = "coco" # We use a GPU with 12GB memory, which can fit two images. # Adjust down if you use a smaller GPU. IMAGES_PER_GPU = 2 # Uncomment to train on 8 GPUs (default is 1) # GPU_COUNT = 8 # Number of classes (including background) NUM_CLASSES = 1 + 80 # COCO has 80 classes ############################################################ # Dataset ############################################################ class CocoDataset(utils.Dataset): def load_coco(self, dataset_dir, subset, year=DEFAULT_DATASET_YEAR, class_ids=None, class_map=None, return_coco=False, auto_download=False): """Load a subset of the COCO dataset. dataset_dir: The root directory of the COCO dataset. subset: What to load (train, val, minival, valminusminival) year: What dataset year to load (2014, 2017) as a string, not an integer class_ids: If provided, only loads images that have the given classes. class_map: TODO: Not implemented yet. Supports maping classes from different datasets to the same class ID. return_coco: If True, returns the COCO object. auto_download: Automatically download and unzip MS-COCO images and annotations """ if auto_download is True: self.auto_download(dataset_dir, subset, year) coco = COCO("{}/annotations/instances_{}{}.json".format(dataset_dir, subset, year)) if subset == "minival" or subset == "valminusminival": subset = "val" image_dir = "{}/{}{}".format(dataset_dir, subset, year) # Load all classes or a subset? if not class_ids: # All classes class_ids = sorted(coco.getCatIds()) # All images or a subset? if class_ids: image_ids = [] for id in class_ids: image_ids.extend(list(coco.getImgIds(catIds=[id]))) # Remove duplicates image_ids = list(set(image_ids)) else: # All images image_ids = list(coco.imgs.keys()) # Add classes for i in class_ids: self.add_class("coco", i, coco.loadCats(i)[0]["name"]) # Add images for i in image_ids: self.add_image( "coco", image_id=i, path=os.path.join(image_dir, coco.imgs[i]['file_name']), width=coco.imgs[i]["width"], height=coco.imgs[i]["height"], annotations=coco.loadAnns(coco.getAnnIds( imgIds=[i], catIds=class_ids, iscrowd=None))) if return_coco: return coco def auto_download(self, dataDir, dataType, dataYear): """Download the COCO dataset/annotations if requested. dataDir: The root directory of the COCO dataset. dataType: What to load (train, val, minival, valminusminival) dataYear: What dataset year to load (2014, 2017) as a string, not an integer Note: For 2014, use "train", "val", "minival", or "valminusminival" For 2017, only "train" and "val" annotations are available """ # Setup paths and file names if dataType == "minival" or dataType == "valminusminival": imgDir = "{}/{}{}".format(dataDir, "val", dataYear) imgZipFile = "{}/{}{}.zip".format(dataDir, "val", dataYear) imgURL = "http://images.cocodataset.org/zips/{}{}.zip".format("val", dataYear) else: imgDir = "{}/{}{}".format(dataDir, dataType, dataYear) imgZipFile = "{}/{}{}.zip".format(dataDir, dataType, dataYear) imgURL = "http://images.cocodataset.org/zips/{}{}.zip".format(dataType, dataYear) # print("Image paths:"); print(imgDir); print(imgZipFile); print(imgURL) # Create main folder if it doesn't exist yet if not os.path.exists(dataDir): os.makedirs(dataDir) # Download images if not available locally if not os.path.exists(imgDir): os.makedirs(imgDir) print("Downloading images to " + imgZipFile + " ...") with urllib.request.urlopen(imgURL) as resp, open(imgZipFile, 'wb') as out: shutil.copyfileobj(resp, out) print("... done downloading.") print("Unzipping " + imgZipFile) with zipfile.ZipFile(imgZipFile, "r") as zip_ref: zip_ref.extractall(dataDir) print("... done unzipping") print("Will use images in " + imgDir) # Setup annotations data paths annDir = "{}/annotations".format(dataDir) if dataType == "minival": annZipFile = "{}/instances_minival2014.json.zip".format(dataDir) annFile = "{}/instances_minival2014.json".format(annDir) annURL = "https://dl.dropboxusercontent.com/s/o43o90bna78omob/instances_minival2014.json.zip?dl=0" unZipDir = annDir elif dataType == "valminusminival": annZipFile = "{}/instances_valminusminival2014.json.zip".format(dataDir) annFile = "{}/instances_valminusminival2014.json".format(annDir) annURL = "https://dl.dropboxusercontent.com/s/s3tw5zcg7395368/instances_valminusminival2014.json.zip?dl=0" unZipDir = annDir else: annZipFile = "{}/annotations_trainval{}.zip".format(dataDir, dataYear) annFile = "{}/instances_{}{}.json".format(annDir, dataType, dataYear) annURL = "http://images.cocodataset.org/annotations/annotations_trainval{}.zip".format(dataYear) unZipDir = dataDir # print("Annotations paths:"); print(annDir); print(annFile); print(annZipFile); print(annURL) # Download annotations if not available locally if not os.path.exists(annDir): os.makedirs(annDir) if not os.path.exists(annFile): if not os.path.exists(annZipFile): print("Downloading zipped annotations to " + annZipFile + " ...") with urllib.request.urlopen(annURL) as resp, open(annZipFile, 'wb') as out: shutil.copyfileobj(resp, out) print("... done downloading.") print("Unzipping " + annZipFile) with zipfile.ZipFile(annZipFile, "r") as zip_ref: zip_ref.extractall(unZipDir) print("... done unzipping") print("Will use annotations in " + annFile) def load_mask(self, image_id): """Load instance masks for the given image. Different datasets use different ways to store masks. This function converts the different mask format to one format in the form of a bitmap [height, width, instances]. Returns: masks: A bool array of shape [height, width, instance count] with one mask per instance. class_ids: a 1D array of class IDs of the instance masks. """ # If not a COCO image, delegate to parent class. image_info = self.image_info[image_id] if image_info["source"] != "coco": return super(CocoDataset, self).load_mask(image_id) instance_masks = [] class_ids = [] annotations = self.image_info[image_id]["annotations"] # Build mask of shape [height, width, instance_count] and list # of class IDs that correspond to each channel of the mask. for annotation in annotations: class_id = self.map_source_class_id( "coco.{}".format(annotation['category_id'])) if class_id: m = self.annToMask(annotation, image_info["height"], image_info["width"]) # Some objects are so small that they're less than 1 pixel area # and end up rounded out. Skip those objects. if m.max() < 1: continue # Is it a crowd? If so, use a negative class ID. if annotation['iscrowd']: # Use negative class ID for crowds class_id *= -1 # For crowd masks, annToMask() sometimes returns a mask # smaller than the given dimensions. If so, resize it. if m.shape[0] != image_info["height"] or m.shape[1] != image_info["width"]: m = np.ones([image_info["height"], image_info["width"]], dtype=bool) instance_masks.append(m) class_ids.append(class_id) # Pack instance masks into an array if class_ids: mask = np.stack(instance_masks, axis=2) class_ids = np.array(class_ids, dtype=np.int32) return mask, class_ids else: # Call super class to return an empty mask return super(CocoDataset, self).load_mask(image_id) def image_reference(self, image_id): """Return a link to the image in the COCO Website.""" info = self.image_info[image_id] if info["source"] == "coco": return "http://cocodataset.org/#explore?id={}".format(info["id"]) else: super(CocoDataset, self).image_reference(image_id) # The following two functions are from pycocotools with a few changes. def annToRLE(self, ann, height, width): """ Convert annotation which can be polygons, uncompressed RLE to RLE. :return: binary mask (numpy 2D array) """ segm = ann['segmentation'] if isinstance(segm, list): # polygon -- a single object might consist of multiple parts # we merge all parts into one mask rle code rles = maskUtils.frPyObjects(segm, height, width) rle = maskUtils.merge(rles) elif isinstance(segm['counts'], list): # uncompressed RLE rle = maskUtils.frPyObjects(segm, height, width) else: # rle rle = ann['segmentation'] return rle def annToMask(self, ann, height, width): """ Convert annotation which can be polygons, uncompressed RLE, or RLE to binary mask. :return: binary mask (numpy 2D array) """ rle = self.annToRLE(ann, height, width) m = maskUtils.decode(rle) return m ############################################################ # COCO Evaluation ############################################################ def build_coco_results(dataset, image_ids, rois, class_ids, scores, masks): """Arrange resutls to match COCO specs in http://cocodataset.org/#format """ # If no results, return an empty list if rois is None: return [] results = [] for image_id in image_ids: # Loop through detections for i in range(rois.shape[0]): class_id = class_ids[i] score = scores[i] bbox = np.around(rois[i], 1) mask = masks[:, :, i] result = { "image_id": image_id, "category_id": dataset.get_source_class_id(class_id, "coco"), "bbox": [bbox[1], bbox[0], bbox[3] - bbox[1], bbox[2] - bbox[0]], "score": score, "segmentation": maskUtils.encode(np.asfortranarray(mask)) } results.append(result) return results def evaluate_coco(model, dataset, coco, eval_type="bbox", limit=0, warmup=0, image_ids=None): """Runs official COCO evaluation. dataset: A Dataset object with valiadtion data eval_type: "bbox" or "segm" for bounding box or segmentation evaluation limit: if not 0, it's the number of images to use for evaluation """ # Pick COCO images from the dataset image_ids = image_ids or dataset.image_ids limit = int(limit/config.BATCH_SIZE)*config.BATCH_SIZE; # Limit to a subset if limit: image_ids = image_ids[:limit] # Get corresponding COCO image IDs. coco_image_ids = [dataset.image_info[id]["id"] for id in image_ids] t_prediction = 0 t_start = time.time() results = [] for i, image_id in enumerate(image_ids): # Load image # image = dataset.load_image(image_id) if (i%config.BATCH_SIZE!=0): continue; image_list=[]; for j in range(0,config.BATCH_SIZE): print("i image_id",i+j, image_id+j) image = dataset.load_image(image_id+j) image_list.append(image) # Run detection t = time.time() r = model.detect(image_list, verbose=0)[0] t1 = time.time() - t #t_prediction += (time.time() - t) if (i/config.BATCH_SIZE>=warmup): t_prediction += t1 print("pred time:",i,t1) # Convert results to COCO format image_results = build_coco_results(dataset, coco_image_ids[i:i + 1], r["rois"], r["class_ids"], r["scores"], r["masks"]) results.extend(image_results) # Load results. This modifies results with additional attributes. coco_results = coco.loadRes(results) # Evaluate cocoEval = COCOeval(coco, coco_results, eval_type) cocoEval.params.imgIds = coco_image_ids cocoEval.evaluate() cocoEval.accumulate() cocoEval.summarize() print("Batch size: %d" % (config.BATCH_SIZE)) print("Time spent per BATCH: %.4f ms" % (t_prediction / (len(image_ids)/config.BATCH_SIZE-warmup) * 1000)) print("Total samples/sec: %.4f samples/s" % ((len(image_ids)/config.BATCH_SIZE-warmup) * config.BATCH_SIZE / t_prediction)) print("Total time: ", time.time() - t_start) ############################################################ # Training ############################################################ if __name__ == '__main__': import argparse # Parse command line arguments parser = argparse.ArgumentParser( description='Train Mask R-CNN on MS COCO.') parser.add_argument("command", metavar="<command>", help="'train' or 'evaluate' on MS COCO") parser.add_argument("--trainbs", required=False, default=2, metavar="<train batchsize>", help="Batchsize to train (default=2)") parser.add_argument("--infbs", required=False, default=1, metavar="<inference batchsize>", help="Batchsize to inference (default=1)") parser.add_argument("--num_intra_threads", required=False, default=56, metavar="<num intra threads>", help="Num intra threads (default=56)") parser.add_argument("--num_inter_threads", required=False, default=1, metavar="<num inter threads>", help="Num inter threads (default=1)") parser.add_argument('--dataset', required=True, metavar="/path/to/coco/", help='Directory of the MS-COCO dataset') parser.add_argument('--year', required=False, default=DEFAULT_DATASET_YEAR, metavar="<year>", help='Year of the MS-COCO dataset (2014 or 2017) (default=2014)') parser.add_argument('--model', required=True, metavar="/path/to/weights.h5", help="Path to weights .h5 file or 'coco'") parser.add_argument('--cp', required=False, default=DEFAULT_LOGS_DIR, metavar="/path/to/logs/", help='Logs and checkpoints directory (default=logs/)') parser.add_argument('--nb', required=False, default=50, metavar="<image count>", help='Images to use for evaluation (default=500)') parser.add_argument('--nw', required=False, default=5, metavar="<image count>", help='Images to use for evaluation warmup (default=10)') parser.add_argument('--download', required=False, default=False, metavar="<True|False>", help='Automatically download and unzip MS-COCO files (default=False)', type=bool) args = parser.parse_args() print("Command: ", args.command) print("Model: ", args.model) print("Dataset: ", args.dataset) print("Year: ", args.year) print("Logs: ", args.cp) print("Auto Download: ", args.download) # For pycocotools updates ppath = subprocess.Popen(["python3", "-m", "site", "--user-site"], stdout=subprocess.PIPE).communicate()[0].decode("utf-8") ppath = ppath[:-1] + "/pycocotools/coco.py" ret = subprocess.Popen(["sed", "-i", "s/unicode/bytes/", ppath], stdout=subprocess.PIPE).communicate()[0] # Configurations if args.command == "train": class TrainConfig(CocoConfig): GPU_COUNT = 1 IMAGES_PER_GPU = int(args.trainbs) STEPS_PER_EPOCH = int(args.nb) config = TrainConfig() else: class InferenceConfig(CocoConfig): # Set batch size to 1 since we'll be running inference on # one image at a time. Batch size = GPU_COUNT * IMAGES_PER_GPU GPU_COUNT = 1 IMAGES_PER_GPU = int(args.infbs) DETECTION_MIN_CONFIDENCE = 0 config = InferenceConfig() config.NUM_INTRA = int(args.num_intra_threads) config.NUM_INTER = int(args.num_inter_threads) config.display() # Create model if args.command == "train": model = modellib.MaskRCNN(mode="training", config=config, model_dir=args.cp) else: model = modellib.MaskRCNN(mode="inference", config=config, model_dir=args.cp) # Select weights file to load if args.model.lower() == "coco": model_path = COCO_MODEL_PATH elif args.model.lower() == "last": # Find last trained weights model_path = model.find_last()[1] elif args.model.lower() == "imagenet": # Start from ImageNet trained weights model_path = model.get_imagenet_weights() else: model_path = args.model # Load weights print("Loading weights ", model_path) model.load_weights(model_path, by_name=True) # Train or evaluate if args.command == "train": # Training dataset. Use the training set and 35K from the # validation set, as as in the Mask RCNN paper. dataset_train = CocoDataset() dataset_train.load_coco(args.dataset, "train", year=args.year, auto_download=args.download) dataset_train.load_coco(args.dataset, "valminusminival", year=args.year, auto_download=args.download) dataset_train.prepare() # Validation dataset dataset_val = CocoDataset() dataset_val.load_coco(args.dataset, "minival", year=args.year, auto_download=args.download) dataset_val.prepare() # *** This training schedule is an example. Update to your needs *** # Training - Stage 1 print("Training network heads") model.train(dataset_train, dataset_val, learning_rate=config.LEARNING_RATE, epochs=1, #40, layers='heads', warmup=int(args.nw)) # Training - Stage 2 # Finetune layers from ResNet stage 4 and up print("Fine tune Resnet stage 4 and up") model.train(dataset_train, dataset_val, learning_rate=config.LEARNING_RATE, epochs=2, #120, layers='4+', warmup=int(args.nw)) # Training - Stage 3 # Fine tune all layers print("Fine tune all layers") model.train(dataset_train, dataset_val, learning_rate=config.LEARNING_RATE / 10, epochs=3, #160, layers='all', warmup=int(args.nw)) elif args.command == "evaluate": # Validation dataset dataset_val = CocoDataset() coco = dataset_val.load_coco(args.dataset, "minival", year=args.year, return_coco=True, auto_download=args.download) dataset_val.prepare() print("Running COCO evaluation on {} images.".format(args.nb)) evaluate_coco(model, dataset_val, coco, "bbox", limit=int(args.nb), warmup=int(args.nw)) else: print("'{}' is not recognized. " "Use 'train' or 'evaluate'".format(args.command))
[ "archaeus@hekaplex.com" ]
archaeus@hekaplex.com
88231ca16773294f42e2cf6d51ba1b8dc86895a1
25b81256057c9a2de014ab511e04703dc617f050
/etl/census/census_features.py
19b6e85b6775b9ed6933def9b874cd9390f5bb66
[ "MIT" ]
permissive
conorhenley/cincinnati
7b9b2fc6d13e49ad5e95a557cd79b28bd17f0565
5ca86a8a31099365188969493e0dd369b4faefc0
refs/heads/master
2021-01-13T06:50:18.403686
2016-05-26T20:21:12
2016-05-26T20:21:12
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# coding: utf-8 # In[1]: from sqlalchemy import create_engine import pandas as pd from lib_cinci.config import main as config user = config['db']['user'] password = config['db']['password'] host = config['db']['host'] database = config['db']['database'] engine = create_engine('postgresql://{user}:{password}@{host}:5432/{database}'.format(user=user, password=password, host=host, database=database)) # In[3]: pop_housing_sql = """SELECT census.*, groups.area FROM shape_files.census_pop_housing as census JOIN shape_files.census_blocks_groups as groups on census.tract = groups.tract and census.block_group = groups.blkgrp;""" # In[4]: pop_housing_raw = pd.read_sql_query(pop_housing_sql, con=engine) # # Raw census data # In[5]: pop_housing_raw.head() # # Calculating census features # list of feature description and calculation can be found in folder docs/data_dictionaries # # features are claculated for each pair of census tract and block # In[5]: features = pd.DataFrame({ 'tract' : pop_housing_raw.tract, 'block_group' : pop_housing_raw.block_group, 'housing_density': pop_housing_raw.H0030001/pop_housing_raw.area, 'rate_occupied_units': pop_housing_raw.H0030002/pop_housing_raw.H0030001, 'rate_vacant_units': pop_housing_raw.H0030003/pop_housing_raw.H0030001, 'rate_mortgage_or_loan' : pop_housing_raw.H0040002/pop_housing_raw.H0030001, 'rate_renter_occupied' : pop_housing_raw.H0040004/pop_housing_raw.H0030001, 'rate_for_rent' : pop_housing_raw.H0050002/pop_housing_raw.H0030001, 'rate_white_householder' : pop_housing_raw.H0060002/pop_housing_raw.P0180001, 'rate_black_householder' : pop_housing_raw.H0060003/pop_housing_raw.P0180001, 'rate_native_householder' : (pop_housing_raw.H0060004+pop_housing_raw.H0060006)/pop_housing_raw.P0180001, 'rate_asian_householder' : pop_housing_raw.H0060005/pop_housing_raw.P0180001, 'rate_other_race_householder' : pop_housing_raw.H0060007/pop_housing_raw.P0180001, 'rate_pop_occupied_units' : pop_housing_raw.H0100001/pop_housing_raw.P0010001, 'rate_1_per_household' : pop_housing_raw.H0130002/pop_housing_raw.P0180001, 'rate_2_per_household' : pop_housing_raw.H0130003/pop_housing_raw.P0180001, 'rate_3_per_household' : pop_housing_raw.H0130004/pop_housing_raw.P0180001, 'rate_4_per_household' : pop_housing_raw.H0130005/pop_housing_raw.P0180001, 'rate_5_per_household' : pop_housing_raw.H0130006/pop_housing_raw.P0180001, 'rate_6_per_household' : pop_housing_raw.H0130007/pop_housing_raw.P0180001, 'rate_7_plus_per_household' : pop_housing_raw.H0130008/pop_housing_raw.P0180001, 'rate_owner_occupied' : pop_housing_raw.H0140002/pop_housing_raw.H0030001, 'rate_owner_occupied_white' : pop_housing_raw.H0140003/pop_housing_raw.H0140002, 'rate_owner_occupied_black' : pop_housing_raw.H0140004/pop_housing_raw.H0140002, 'rate_owner_occupied_native' : (pop_housing_raw.H0140005+pop_housing_raw.H0140007)/pop_housing_raw.H0140002, 'rate_owner_occupied_asian' : pop_housing_raw.H0140006/pop_housing_raw.H0140002, 'rate_owner_occupied_other_race' : pop_housing_raw.H0140008/pop_housing_raw.H0140002, 'rate_renter_occupied_white' : pop_housing_raw.H0140011/pop_housing_raw.H0040004, 'rate_renter_occupied_black' : pop_housing_raw.H0140012/pop_housing_raw.H0040004, 'rate_renter_occupied_native' : (pop_housing_raw.H0140013+pop_housing_raw.H0140015)/pop_housing_raw.H0040004, 'rate_renter_occupied_asian' : pop_housing_raw.H0140014/pop_housing_raw.H0040004, 'rate_renter_occupied_other' : pop_housing_raw.H0140016/pop_housing_raw.H0040004, 'rate_owner_occupied_hispanic' : pop_housing_raw.H0150004/pop_housing_raw.H0140002, #'rate_renter_occupied_hispanic' : pop_housing_raw.H0150005/pop_housing_raw.H0040004, 'rate_owner_occupied_w_children' : pop_housing_raw.H0190003/pop_housing_raw.H0140002, 'rate_owner_occupied_no_children' : pop_housing_raw.H0190004/pop_housing_raw.H0140002, 'rate_renter_occupied_no_children' : 1-(pop_housing_raw.H0190006/pop_housing_raw.H0040004), 'rate_renter_occupied_w_children' : pop_housing_raw.H0190006/pop_housing_raw.H0040004, 'population_density' : pop_housing_raw.P0010001/pop_housing_raw.area, 'rate_white_pop' : pop_housing_raw.P0030002/pop_housing_raw.P0010001, 'rate_black_pop' : pop_housing_raw.P0030003/pop_housing_raw.P0010001, 'rate_native_pop' : (pop_housing_raw.P0030006+pop_housing_raw.P0030004)/pop_housing_raw.P0010001, 'rate_asian_pop' : pop_housing_raw.P0030005/pop_housing_raw.P0010001, 'rate_other_race_pop' : pop_housing_raw.P0030007/pop_housing_raw.P0010001, 'rate_pop_over_18' : pop_housing_raw.P0110001/pop_housing_raw.P0010001, 'rate_male_under_18' : (pop_housing_raw.P0120003+pop_housing_raw.P0120004+pop_housing_raw.P0120005+pop_housing_raw.P0120006)/pop_housing_raw.P0010001, 'rate_male_18_35' : pop_housing_raw[['P0120007','P0120008','P0120009','P0120010','P0120011','P0120012']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_male_35_50' : pop_housing_raw[['P0120013','P0120014','P0120015']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_male_50_75' : pop_housing_raw[['P0120016', 'P0120017', 'P0120018', 'P0120019', 'P0120020', 'P0120021', 'P0120022']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_male_over_75' : pop_housing_raw[['P0120023','P0120024','P0120025']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_female_under_18' : pop_housing_raw[['P0120027','P0120028','P0120029','P0120030']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_female_18_35' : pop_housing_raw[['P0120031', 'P0120032', 'P0120033', 'P0120034', 'P0120035', 'P0120036']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_female_35_50' : pop_housing_raw[['P0120037', 'P0120038', 'P0120039']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_female_50_75' : pop_housing_raw[['P0120040', 'P0120041', 'P0120042', 'P0120043', 'P0120044', 'P0120045', 'P0120046']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_male_over_75' : pop_housing_raw[['P0120047','P0120048','P0120049']].sum(axis=1)/pop_housing_raw.P0010001, 'rate_households' : pop_housing_raw.P0180001/pop_housing_raw.H0030001}) # In[7]: features # In[10]: features.to_sql('census_features', engine, schema='shape_files', if_exists='replace', index=False)
[ "edu.blancas@gmail.com" ]
edu.blancas@gmail.com
bd8e762db4466a9af6f76b507af09e77b0f9bb95
6d913a2fe43717d73e7e9122b9fbad973315a7b3
/blog/migrations/0001_initial.py
d70c9f11c5d6a50f4e2c5140b5fbecdf084309ed
[]
no_license
k3nn1x/my-first-blog
b8cb4fb9e53a49d9f8bd4a12abe167363bb0000a
0868c29983ff5575caf298fa4a8c52aa2aeb925f
refs/heads/master
2016-09-14T07:05:26.295328
2016-06-13T12:05:51
2016-06-13T12:05:51
59,143,364
0
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null
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py
# -*- coding: utf-8 -*- # Generated by Django 1.9.6 on 2016-05-18 15:31 from __future__ import unicode_literals from django.conf import settings from django.db import migrations, models import django.db.models.deletion import django.utils.timezone class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='Post', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=200)), ('text', models.TextField()), ('created_date', models.DateTimeField(default=django.utils.timezone.now)), ('published_date', models.DateTimeField(blank=True, null=True)), ('author', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]
[ "kennypedrique@gmail.com" ]
kennypedrique@gmail.com
a0da45bec4db182816084ee19fbf9ac37ec705d9
d93bd218582a25e7f87ef068ded78a39750a9c0d
/chapter_13/thirteenOne_settings.py
c8f7c6b4f888e009c23564a140fc2caf71f00f77
[]
no_license
kelvDp/CC_python_cc_projects
e080ff681b81694a25e2d1474d0a224126f42cd4
7c49f8f05afa58c99979bf490f7bc4ff85a87167
refs/heads/master
2022-12-13T07:36:20.532977
2020-07-28T08:27:52
2020-07-28T08:27:52
281,634,023
0
0
null
null
null
null
UTF-8
Python
false
false
206
py
class Settings: """Class to manage settings""" def __init__(self): """Inits settings""" self.screen_width = 1000 self.screen_height = 600 self.speed = 1.1
[ "noreply@github.com" ]
kelvDp.noreply@github.com
6c4a7e879ce82bb106ec665d968edc363888052d
24798e941b1dc52f39d45fcafe9e7707d161e74e
/src/config.py
12ade15a10614a5b15742fc861012dd58032178c
[]
no_license
IanMadlenya/pugg
a2aa1d12510090026fd806656da4447b262a4419
806642e1b37d8657db4f41a4a81bdfe878a28bba
refs/heads/master
2021-01-25T09:14:33.671412
2013-03-30T01:48:25
2013-03-30T01:48:25
null
0
0
null
null
null
null
UTF-8
Python
false
false
129
py
global MONGO_SERVER global PUGG_DB try: MONGO_SERVER except NameError: MONGO_SERVER="127.0.0.1" PUGG_DB="pugg_production"
[ "natematias@gmail.com" ]
natematias@gmail.com
d410f466a0f98bdf23b7fc68a30269a04ef74fca
a276798900d6f99d0dc79b8e4e66c23973ede4a9
/blog/urls.py
a96decec9876c70c542bf8f64bd4f22291847321
[]
no_license
Mgarchuk/MyBlog
ad73a06e008f80644b33fba795eb601dead21754
a2890a347ab4b56f1e703053840c1cdd1dddb5ba
refs/heads/main
2023-03-07T07:03:32.991927
2021-02-24T22:14:07
2021-02-24T22:14:07
342,049,298
0
0
null
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UTF-8
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py
from django.conf.urls import url from django.urls import path from django.views.generic import ListView from blog.models import Post from . import views from django.conf import settings from django.conf.urls.static import static urlpatterns = [ url(r'^$', views.main_page, name='main_page'), path('post/<int:pk>/', views.post_detail, name='post_detail'), path('posts/', ListView.as_view(queryset=Post.objects.all().order_by("-published_date"), template_name='blog/post_list.html')), path('edit_post/', views.edit_post, name='post_edit'), path('entry/', views.MyProjectLoginView.as_view(), name='entry_page'), path('register/', views.RegisterUserView, name='register_page'), path('create_post/', views.create_post, name='create_post'), path('update_post/<int:pk>', views.update_post, name='update_post'), path('delete_post/<int:pk>', views.delete_post, name='delete_post'), path('create_photo/', views.create_photo, name='create_photo'), path('logout/', views.MyProjectLogout.as_view(), name='logout'), path('photo_list/', views.photo_list, name='photo_list'), url(r'^activate/(?P<uidb64>[0-9A-Za-z_\-]+)/(?P<token>[0-9A-Za-z]{1,13}-[0-9A-Za-z]{1,20})/$', views.activate_account, name='activate'), ] if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
[ "mgarchuk6@gmail.com" ]
mgarchuk6@gmail.com
b561022b7fd0c683ba9c07ba5381c7a55b8b49cd
bc599c9a404940fae21ed6b57edb7bb9dc04e71c
/test/base_test/graphics/baseScatter.py
2bd2cb944a44d6477901a3cff545da2ae9d41870
[]
no_license
jcarlosglx/SparkReport
c9b37a1419f113ea13341e6641ceb17056aeb7d0
9d6b044f037e8dfe583bcf76c51dd792ac1cc34a
refs/heads/master
2023-08-11T16:04:28.393856
2021-09-21T23:06:08
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from test.base_test.base_http.baseGetTest import BaseGetGeneralTest from test.base_test.base_dimension.baseGraphicTwoDimensionTest import \ BaseGraphicTwoDimensionTest from typing import List, Type from flask import Flask from flask_sqlalchemy import SQLAlchemy class BaseGetScatterTest(BaseGetGeneralTest, BaseGraphicTwoDimensionTest): Graphics: List[str] = ["Scatter"] def test_get_scatter(self, get_app: Flask, get_db: Type[SQLAlchemy]): self.reload_json() response = get_app.test_client().get( f"{self.url_get}{self.endpoint_get}", json=self.JSON ) self.save_response_file(response) code_response = str(response.status_code) assert code_response == self.expect_status_get, self.print_error(code_response)
[ "j.carlosglxg@gmail.com" ]
j.carlosglxg@gmail.com
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jbn/brittle_wit_core
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import pytest from brittle_wit_core.oauth import (extract_access_token, extract_request_token, obtain_access_token, obtain_request_token, redirect_url, AppCredentials) def test_extract_request_token_bad_status(): assert extract_request_token(999, "") == (None, None) def test_extract_request_token_good_status_bad_resp(): assert extract_request_token(200, "") == (None, None) def test_extract_request_token_good_status_good_resp(): params = "oauth_token=a,oauth_token_secret=b,oauth_callback_confirmed=true" resp_body = "&".join(params.split(",")) assert extract_request_token(200, resp_body) == ('a', 'b') def test_redirect_url(): base_uri = "https://api.twitter.com/oauth/authenticate" expected = base_uri + "?oauth_token=hello%2Fworld" assert redirect_url("hello/world") == expected def test_extract_access_token_bad_status(): assert extract_access_token(999, "") is None def test_extract_access_token_bad_resp(): assert extract_access_token(200, "") is None def test_extract_access_token_good_status_good_resp(): d = {'oauth_token': 'token', 'oauth_token_secret': 'secret', 'screen_name': 'techcrunch', 'user_id': 42, 'x_auth_expires': '0'} resp_body = "&".join(["{}={}".format(k, v) for k, v in d.items()]) assert extract_access_token(200, resp_body) == d @pytest.fixture def app_cred(): # See: https://dev.twitter.com/web/sign-in/implementing return AppCredentials("cChZNFj6T5R0TigYB9yd1w", "L8qq9PZyRg6ieKGEKhZolGC0vJWLw8iEJ88DRdyOg") def test_obtain_request_token(app_cred): callback_url = "http://localhost/sign-in-with-twitter/" overrides = {'oauth_timestamp': "1318467427", 'oauth_callback': callback_url, 'oauth_nonce': "ea9ec8429b68d6b77cd5600adbbb0456"} _, headers = obtain_request_token(app_cred, callback_url, **overrides) expected_substr = 'oauth_signature="F1Li3tvehgcraF8DMJ7OyxO4w9Y%3D"' assert expected_substr in headers['Authorization'] def test_obtain_access_token(app_cred): assert app_cred.key == "cChZNFj6T5R0TigYB9yd1w" tok = "NPcudxy0yU5T3tBzho7iCotZ3cnetKwcTIRlX0iwRl0" verifier = "uw7NjWHT6OJ1MpJOXsHfNxoAhPKpgI8BlYDhxEjIBY" overrides = {'oauth_timestamp': "1318467427", 'oauth_nonce': "a9900fe68e2573b27a37f10fbad6a755"} _, headers = obtain_access_token(app_cred, tok, verifier, **overrides) expected_substr = 'oauth_signature="eLn5QjdCqHdlBEvOogMeGuRxW4k%3D"' assert expected_substr in headers['Authorization']
[ "jbn@abreka.com" ]
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/usr/share/pyshared/Bio/SeqUtils/IsoelectricPoint.py
[ "prateekgupta.3991@gmail.com" ]
prateekgupta.3991@gmail.com
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/Edurights/Edurights/settings.py
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""" Django settings for Edurights project. Generated by 'django-admin startproject' using Django 3.1.6. For more information on this file, see https://docs.djangoproject.com/en/3.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.1/ref/settings/ """ from pathlib import Path import os # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = '@4v2x+_(1i5q*1ksy2ox@a142mh1f6^2k76%5_#e-&+m44ky8z' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'UI' ] 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 = 'Edurights.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR,'templates')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'Edurights.wsgi.application' # Database # https://docs.djangoproject.com/en/3.1/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': BASE_DIR / 'db.sqlite3', } } # Password validation # https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.1/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.1/howto/static-files/ STATIC_URL = '/static/' PROJECT_DIR = os.path.dirname(os.path.abspath(__file__)) STATIC_ROOT = os.path.join(PROJECT_DIR, 'static') STATICFILES_DIRS = [ BASE_DIR / "static", '/home/ansh/Desktop/EduRights/Edurights/static/', #the absolute path to your static fil ] MEDIA_URL = '/media/'
[ "anshshrivastava1705@gmail.com" ]
anshshrivastava1705@gmail.com
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tinyzimmer/kopf
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import aiohttp.web import pytest from kopf.clients.discovery import discover, is_namespaced, is_status_subresource from kopf.structs.resources import Resource async def test_discovery_of_existing_resource( resp_mocker, aresponses, hostname): res1info = {'name': 'someresources', 'namespaced': True} result = {'resources': [res1info]} list_mock = resp_mocker(return_value=aiohttp.web.json_response(result)) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) resource = Resource('some-group.org', 'someversion', 'someresources') info = await discover(resource=resource) assert info == res1info async def test_discovery_of_unexisting_resource( resp_mocker, aresponses, hostname): result = {'resources': []} list_mock = resp_mocker(return_value=aiohttp.web.json_response(result)) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) resource = Resource('some-group.org', 'someversion', 'someresources') info = await discover(resource=resource) assert info is None @pytest.mark.parametrize('status', [403, 404]) async def test_discovery_of_unexisting_group_or_version( resp_mocker, aresponses, hostname, status): list_mock = resp_mocker(return_value=aresponses.Response(status=status, reason="boo!")) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) resource = Resource('some-group.org', 'someversion', 'someresources') info = await discover(resource=resource) assert info is None async def test_discovery_is_cached_per_session( resp_mocker, aresponses, hostname): res1info = {'name': 'someresources1', 'namespaced': True} res2info = {'name': 'someresources2', 'namespaced': True} result = {'resources': [res1info]} list_mock = resp_mocker(return_value=aiohttp.web.json_response(result)) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) result = {'resources': [res2info]} list_mock = resp_mocker(return_value=aiohttp.web.json_response(result)) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) resource = Resource('some-group.org', 'someversion', 'someresources1') info = await discover(resource=resource) assert info == res1info resource = Resource('some-group.org', 'someversion', 'someresources2') info = await discover(resource=resource) assert info is None # cached as absent on the 1st call. resource = Resource('some-group.org', 'someversion', 'someresources1') info = await discover(resource=resource) assert info == res1info @pytest.mark.parametrize('namespaced', [True, False]) async def test_is_namespaced( resp_mocker, aresponses, hostname, namespaced): res1info = {'name': 'someresources', 'namespaced': namespaced} result = {'resources': [res1info]} list_mock = resp_mocker(return_value=aiohttp.web.json_response(result)) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) resource = Resource('some-group.org', 'someversion', 'someresources') result = await is_namespaced(resource=resource) assert result == namespaced @pytest.mark.parametrize('namespaced', [True, False]) async def test_is_status_subresource_when_not_a_subresource( resp_mocker, aresponses, hostname, namespaced): res1info = {'name': 'someresources', 'namespaced': namespaced} result = {'resources': [res1info]} list_mock = resp_mocker(return_value=aiohttp.web.json_response(result)) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) resource = Resource('some-group.org', 'someversion', 'someresources') result = await is_status_subresource(resource=resource) assert result is False # an extra type-check @pytest.mark.parametrize('namespaced', [True, False]) async def test_is_status_subresource_when_is_a_subresource( resp_mocker, aresponses, hostname, namespaced): res1info = {'name': 'someresources', 'namespaced': namespaced} res1status = {'name': 'someresources/status', 'namespaced': namespaced} result = {'resources': [res1info, res1status]} list_mock = resp_mocker(return_value=aiohttp.web.json_response(result)) aresponses.add(hostname, '/apis/some-group.org/someversion', 'get', list_mock) resource = Resource('some-group.org', 'someversion', 'someresources') result = await is_status_subresource(resource=resource) assert result is True # an extra type-check
[ "nolar@nolar.info" ]
nolar@nolar.info
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abdulwahid24/socialnetwork
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# Generated by Django 2.0.8 on 2019-01-05 18:48 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('authentication', '0002_profile'), ] operations = [ migrations.RemoveField( model_name='user', name='first_name', ), migrations.RemoveField( model_name='user', name='last_name', ), ]
[ "abdulwahid24@gmail.com" ]
abdulwahid24@gmail.com
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imzeali/dueros_mind_reader
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#!/usr/bin/env python2 # -*- encoding=utf-8 -*- # description: # author:jack # create_time: 2018/5/28 """ desc:pass """ from dueros.directive.AudioPlayer.Control.Button import Button class NextButton(Button): def __init__(self): super(NextButton, self).__init__('NEXT') pass if __name__ == '__main__': pass
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/trydjango1-11/src/Scripts/django-admin.py
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#!c:\users\toshiba\desktop\dev\trydjango1-11\src\scripts\python.exe from django.core import management if __name__ == "__main__": management.execute_from_command_line()
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from typing import List from neomodel_constraints.constraint import ConstraintSet, TypeMapperAbstract from .data import Neo4jConstraintQueryRecord def convert_constraints_with_type_mapper( raw: List[Neo4jConstraintQueryRecord], type_mapper: TypeMapperAbstract ) -> ConstraintSet: constraints = set() for record in raw: constraint_type = type_mapper.map(record.type_) constraint = constraint_type.from_raw(record.dict()) constraints.add(constraint) return ConstraintSet(constraints)
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def print_pattern(n): i=0 print("Output :") while(i<n): j=0 k=1 while(j<n): print(k,end=" ") k+=1 j+=1 print("") i+=1 print("Input :",end=" ") x=int(input()) print_pattern(x)
[ "shrihari.dhanorkar@spit.ac.in" ]
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# corpus2sentences.py # reads corpus and builds dictionary {doc-index:[doc-sentences],...} # filters unnecessary and error-causing period expressions such as: # i.e, e.g, A. Taylor (A.) # returns dictionary docs to filter_sentences.py import os import re #closure vars for action() - free vars in action() dbasepath = '../corpus/' #location of corpus file(s) for diagnostics vbasepath = './corpus/' #location of corpus file(s) for vae run corpusname = 'corpus0' #default corpus0 docs = {} #dictionary of documents from corpus def corpus(corpusnm = 'corpus0'): #identify corpusname as closure var, not local global corpusname print('\ncorpus2sentences.corpus(): setting corpusname to ' + corpusnm) corpusname = corpusnm def filter(regex, replace, s_pf, diagnostics=False): #filter each text - eliminate i.e, e.g., A. Taylor s = re.sub(regex, replace, s_pf) #filter by regex result = re.subn(regex, replace, s_pf) #filter by regex if diagnostics: print('filtering detected ' + str(result[1]) + ' anomaly(ies)!!\n') if s != s_pf: print(s_pf + '\n\nreplaced by:\n\n' + s) return s def action(diagnostics=False): #relative location of corpus relative to main file # !!!! change to original !!!! # if diagnostics == True: # basepath = dbasepath + corpusname +'/' #relative to /encoder # else: # basepath = vbasepath + corpusname + '/' #relative to vae.py basepath = vbasepath + corpusname + '/' #relative to vae.py print('\n+++++++++++ corpus2sentences +++++++++++++++++++++') print('corpus2sentences: basepath = ' + basepath) index = 0 #document ordinal identifier - key of dict docs for root, dirs, filenames in os.walk(basepath): for fn in filenames: if fn.endswith(".txt"): with open(basepath+fn, "r") as f: s = '' #string representation of file f for line in f: if not line.startswith('$'): s += line.replace("\n"," ").lstrip() #filter each doc - eliminate i.e, e.g., A. Taylor print('\nfiltering text ' + fn ) rs = '\s([a-z,A-Z]\.)+,*' regex = re.compile(rs) s_pf = s s = filter(regex, '', s_pf, diagnostics) #split the file-string on '***' to form docs a = s.split('***') if diagnostics: print(str(len(a)) + ' documents') for doc in a: doc_sentences = [] #sentences associated with docs[doc] sentences = doc.split('.') #sections of split doc string if diagnostics: print('\n\ndoc ' + str(index)) print(str(len(sentences)-1) + ' sentences:') for sentence in sentences: sentence = sentence.strip() if(len(sentence) >0): #skip empty sentences exp last if diagnostics: print(sentence +'\n') doc_sentences.append(sentence) #add non-empty sent. docs[index] = doc_sentences #sentence-list val for key index index += 1 if diagnostics == True: print('\n\n********************************************') for index in docs: print('%%%%%%%%%') print('docs ' + str(index) + ' is ' + str(docs[index])) else: print('number of paragraphs extracted = ' + str(len(docs.values()))) for k,v in docs.items(): print('paragraph ' + str(k) + ' has ' + str(len(v)) + ' sentences') return(docs) if __name__ == "__main__": print("corpus2sentences module running in diagnostics mode as __main__") #action(True) action(False) #quick check of non-diagnostics output in diagnoistics mode else: print("corpus2sentences module imported")
[ "mark_rudolph@yahoo.com" ]
mark_rudolph@yahoo.com
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""" Django settings for ServiceTeam project. Generated by 'django-admin startproject' using Django 2.0.2. For more information on this file, see https://docs.djangoproject.com/en/2.0/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.0/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) STATIC_DIR = os.path.join(BASE_DIR, 'static') TEMPLATES_DIR = os.path.join(BASE_DIR, 'templates') MEDIA_DIR = os.path.join(BASE_DIR, 'media') # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.0/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'd5irg-7yl9k7w#j^l!a7s)gw4odm^j@&smf=l7ri@q6f=kr_tr' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = ['dimakoserviceteam.pythonanywhere.com'] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'accounts', 'clock_card', 'time_sheets' ] 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 = 'ServiceTeam.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [TEMPLATES_DIR,], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'ServiceTeam.wsgi.application' # Database # https://docs.djangoproject.com/en/2.0/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.0/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'Africa/Johannesburg' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.0/howto/static-files/ STATIC_URL = '/static/' STATICFILES_DIRS = [ STATIC_DIR, ] MEDIA_ROOT = MEDIA_DIR MEDIA_URL = '/media/' LOGIN_REDIRECT_URL = '/accounts/users' LOGOUT_REDIRECT_URL = '/'
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import math print(math.pi) print(math.e) #lam tron 2 chu so sau dau phay print(round(math.e, 2)) #in ra so lam tron xuong cua 1.9 print(math.floor(1.9)) #in ra so lam tron len cua 2.1 print(math.ceil(2.1)) #lay gia tri nguyen cat bo phan thap phan sau dau phay cua so thuc print(math.trunc(-1.9)) #in ra giai thua cua 5 print(math.factorial(5)) #in ra uoc chung lon nhat cua hai so nguyen print(math.gcd(12, 18))
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import threading lock = threading.Lock() class Singleton(type): _instances = {} def __call__(cls, *args, **kwargs): """ This check, (first check) is for avoid unnecessary locking, once instance is set in _instances in dict """ if cls not in cls._instances: # CheckPoint 1 with lock: """ This check, (second check) if needed for overriding _instances dict update: Scenario: multiple threads came to CheckPoint 1 at almost near same time. Now one thread got the lock, came inside critical section and updates _instances dict with newly created instance and then releases the lock. Now second thread got the lock, Now think.... if this second check is not there, this second thread will create new instance and update the dict (which we really dont want) """ if cls not in cls._instances: cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs) return cls._instances[cls] class SingletonClass(metaclass=Singleton): pass def testThread(num): print("Object value",SingletonClass()) if __name__ == '__main__': for i in range(5): t = threading.Thread(target=testThread, args=[i]) t.start()
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""" Copyright 2019 Goldman Sachs. 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. """ from dataclasses import dataclass, asdict, fields from typing import Dict, List from gs_quant.analytics.core.processor import BaseProcessor DEFAULT_WIDTH = 100 class RenderType: DEFAULT = 'default' HEATMAP = 'heatmap' BOXPLOT = 'boxplot' SCALE = 'scale' @dataclass class ColumnFormat: renderType: RenderType = RenderType.DEFAULT precision: int = 2 humanReadable: bool = True tooltip: str = None displayValues: bool = True @classmethod def from_dict(cls, dict_): class_fields = {f.name for f in fields(cls)} return ColumnFormat(**{k: v for k, v in dict_.items() if k in class_fields}) class DataColumn: """Base class for grid column""" def __init__(self, name: str, processor: BaseProcessor = None, *, format_: ColumnFormat = ColumnFormat(), width: int = DEFAULT_WIDTH): """ DataColumn :param name: Name of the column :param processor: Processor to apply to the column for calculation :param format_: Formatting information for the column result :param width: Size of the column in pixels when presented on the UI """ self.name = name self.processor = processor self.format_ = format_ self.width = width def as_dict(self): format_ = asdict(self.format_) if format_['tooltip'] is None: del format_['tooltip'] column = { 'name': self.name, 'format': format_, 'width': self.width } processor = self.processor if processor: column['processorName'] = processor.__class__.__name__ column.update(**processor.as_dict()) return column @classmethod def from_dict(cls, obj: Dict, reference_list: List): processor = BaseProcessor.from_dict(obj, reference_list) return DataColumn(name=obj['name'], processor=processor, format_=ColumnFormat.from_dict(obj.get('format', {})), width=obj.get('width', DEFAULT_WIDTH))
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# Generated by Django 3.1.2 on 2020-10-12 20:48 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('tasks', '0001_initial'), ] operations = [ migrations.AddField( model_name='task', name='user', field=models.ForeignKey(default=1, on_delete=django.db.models.deletion.CASCADE, to='auth.user'), preserve_default=False, ), migrations.AlterField( model_name='task', name='done', field=models.CharField(choices=[('doing', 'Doing'), ('done', 'Done')], max_length=5), ), ]
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import datetime class Migration(migrations.Migration): dependencies = [ ('vis', '0007_auto_20150523_0005'), ] operations = [ migrations.AddField( model_name='visits', name='meta', field=models.TextField(default=b'empty'), preserve_default=True, ), migrations.AlterField( model_name='visits', name='last_visited', field=models.DateTimeField(default=datetime.datetime(2015, 5, 23, 11, 23, 7, 587000)), preserve_default=True, ), ]
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/src/python/pants/backend/experimental/terraform/lint/tfsec/register.py
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# Copyright 2023 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). from pants.backend.terraform.lint.tfsec.rules import rules as tfsec_rules def rules(): return tfsec_rules()
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cau-algorithm-study/Python-Data-Structure
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# -*- coding:utf-8 -*- ''' 남태평양에 있는 어느 나라에 11개의 섬이 다음과 같이 다리로 연결되어 있다. 이 나라의 관광청에서는 관광객들이 11개의 섬들을 모두 방문할 수 있는, 순서가 다른 3개의 관광코스를 만들었다. 각 코스의 관광은 섬 H에서 시작한다. 관광청에서는 각 관광 코스의 방문 순서를 다음과 같은 규칙에 따라 만들었다. H / \ F S / \ / \ U E Z K / / \ N A Y \ T ''' # A 코스 : 섬에 도착하면 항상 도착한 섬을 먼저 관광하고, 그 다음엔 왼쪽 섬으로 관광을 진행한다. # 왼쪽 방향의 모든 섬들을 방문한 후에는 오른쪽 섬으로 관광을 진행한다. def A_course(n): # A 코스 if n != None: print(n.name, '->', end=' ') # 섬 N 방문 A_course(n.left) A_course(n.right) # B 코스 : 섬에 도착하면 도착한 섬의 관광을 미루고, 먼저 왼쪽 섬으로 관광을 진행하고 왼쪽 방향의 모든 # 섬들을 방문한 후에 돌아와서 섬을 관광한다. 그 다음엔 오른쪽 섬으로 관광한다. def B_course(n): if n != None: B_course(n.left) print(n.name, '->', end=' ') B_course(n.right) # C 코스 : 섬에 도착하면 도착한 섬의 관광을 미루고, 먼저 왼쪽 섬으로 관광을 진행하고 왼쪽 방향의 모든 섬들을 # 관광한 후에 돌아와서 오른쪽 섬으로 관광을 진행한다. 오른쪽 방향의 모든 섬들을 관광한 후에 돌아와서, # 관광을 미루었던 섬을 관광한다. def C_course(n): if n != None: C_course(n.left) C_course(n.right) print(n.name, '->', end=' ') class Node: def __init__(self, name, left=None, right=None): self.name = name self.left = left self.right = right def map(): n1 = Node('H') n2 = Node('F') n3 = Node('S') n4 = Node('U') n5 = Node('E') n6 = Node('Z') n7 = Node('K') n8 = Node('N') n9 = Node('A') n10 = Node('Y') n11 = Node('T') n1.left = n2 n1.right = n3 n2.left = n4 n2.right = n5 n3.left = n6 n3.right = n7 n4.left = n8 n5.left = n9 n7.right = n10 n9.right = n11 return n1 # 시작섬 리턴 start = map() print('A-코스:\t') A_course(start) print("") print('B-코스:\t') B_course(start) print("") print('C-코스:\t') C_course(start)
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import variables.colors as c from libs.clear import * def exit(signal, frame): clear() print(c.bcolors.OKGREEN+"Bye!"+c.bcolors.ENDC) sys.exit(0)
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# -*- coding: utf-8 -*- """ ============ Parsing demo ============ This example shows some of the functionality of ``read_tab``. """ # Author: Eric Larson <larson.eric.d@gmail.com> # # License: BSD (3-clause) import ast from expyfun.io import read_tab print(__doc__) data = read_tab('sample.tab') # from simple_experiment print('Number of trials: %s' % len(data)) keys = list(data[0].keys()) print('Data keys: %s\n' % keys) for di, d in enumerate(data): if d['trial_id'][0][0] == 'multi-tone': print('Trial %s multi-tone' % (di + 1)) targs = ast.literal_eval(d['multi-tone trial'][0][0]) presses = [int(k[0]) for k in d['keypress']] print(' Targs: %s\n Press: %s' % (targs, presses))
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