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

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class Solution: def permuteUnique(self, nums): """ :type nums: List[int] :rtype: List[List[int]] """ res = [] if len(nums) == 0: return [] distinct_nums = set(nums) rest = {} for i in nums: if i in rest: rest[i] += 1 else: rest[i] = 1 print(rest) def deeper(path): if len(path) == len(nums): res.append(path) for i in distinct_nums: if rest[i] > 0: rest[i] -= 1 deeper(path + [i]) rest[i] += 1 deeper([]) return res s = Solution() res = s.permuteUnique([1,1,2]) print(res)

[ "836807627@qq.com" ]

836807627@qq.com

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from calk import pow, multi, summa from calk.pow import pow as r y = multi.multi(3, 5) x = summa.summa(5, 7) z = r(3, 5) print(x, y, z) print(dir(pow))

[ "coxatiy@gmail.com" ]

coxatiy@gmail.com

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/beginLearn/googleclass/class3/test.py

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RoderickAdriance/PythonDemo

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2020-04-06T17:36:46.000133

2018-11-15T07:07:03

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from __future__ import print_function import math from sklearn import metrics from IPython import display from matplotlib import cm from matplotlib import gridspec from matplotlib import pyplot as plt import numpy as np import pandas as pd import tensorflow as tf from tensorflow.python.data import Dataset tf.logging.set_verbosity(tf.logging.ERROR) pd.options.display.max_rows = 10 pd.options.display.float_format = '{:.1f}'.format california_housing_dataframe = pd.read_csv("data.csv") # 数据随机化处理 california_housing_dataframe = california_housing_dataframe.reindex( np.random.permutation(california_housing_dataframe.index)) california_housing_dataframe["median_house_value"] /= 1000.0 def my_input_fn(features, targets, batchsize=1, shuffle=True, num_epochs=None): features = {key: np.array(value) for key, value in dict(features).items()} ds = Dataset.from_tensor_slices((features, targets)) ds = ds.batch(batchsize).repeat(num_epochs) if shuffle: ds = ds.shuffle(10000) features, label = ds.make_one_shot_iterator().get_next() return features, label features,label = my_input_fn(california_housing_dataframe[["total_rooms"]], california_housing_dataframe[["median_house_value"]], batchsize=1)

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1371553306@qq.com

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rdemaria/pjlsa

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import java.lang import java.security import java.util import typing class AclEntry(java.lang.Cloneable): def addPermission(self, permission: 'Permission') -> bool: ... def checkPermission(self, permission: 'Permission') -> bool: ... def clone(self) -> typing.Any: ... def getPrincipal(self) -> java.security.Principal: ... def isNegative(self) -> bool: ... def permissions(self) -> java.util.Enumeration['Permission']: ... def removePermission(self, permission: 'Permission') -> bool: ... def setNegativePermissions(self) -> None: ... def setPrincipal(self, principal: java.security.Principal) -> bool: ... def toString(self) -> str: ... class AclNotFoundException(java.lang.Exception): def __init__(self): ... class Group(java.security.Principal): def addMember(self, principal: java.security.Principal) -> bool: ... def equals(self, object: typing.Any) -> bool: ... def hashCode(self) -> int: ... def isMember(self, principal: java.security.Principal) -> bool: ... def members(self) -> java.util.Enumeration[java.security.Principal]: ... def removeMember(self, principal: java.security.Principal) -> bool: ... def toString(self) -> str: ... class LastOwnerException(java.lang.Exception): def __init__(self): ... class NotOwnerException(java.lang.Exception): def __init__(self): ... class Owner: def addOwner(self, principal: java.security.Principal, principal2: java.security.Principal) -> bool: ... def deleteOwner(self, principal: java.security.Principal, principal2: java.security.Principal) -> bool: ... def isOwner(self, principal: java.security.Principal) -> bool: ... class Permission: def equals(self, object: typing.Any) -> bool: ... def toString(self) -> str: ... class Acl(Owner): def addEntry(self, principal: java.security.Principal, aclEntry: AclEntry) -> bool: ... def checkPermission(self, principal: java.security.Principal, permission: Permission) -> bool: ... def entries(self) -> java.util.Enumeration[AclEntry]: ... def getName(self) -> str: ... def getPermissions(self, principal: java.security.Principal) -> java.util.Enumeration[Permission]: ... def removeEntry(self, principal: java.security.Principal, aclEntry: AclEntry) -> bool: ... def setName(self, principal: java.security.Principal, string: str) -> None: ... def toString(self) -> str: ... class __module_protocol__(typing.Protocol): # A module protocol which reflects the result of ``jp.JPackage("java.security.acl")``. Acl: typing.Type[Acl] AclEntry: typing.Type[AclEntry] AclNotFoundException: typing.Type[AclNotFoundException] Group: typing.Type[Group] LastOwnerException: typing.Type[LastOwnerException] NotOwnerException: typing.Type[NotOwnerException] Owner: typing.Type[Owner] Permission: typing.Type[Permission]

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michi.hostettler@cern.ch

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# Distributed under MIT License # Copyright (c) 2021 Remi BERTHOLET from server.httpserver import HttpServer from htmltemplate import Br,ButtonCmd,Option,SwitchCmd,Tag,SliderCmd,ComboCmd,Paragraph from webpage.mainpage import * from tools import useful # Called when the button pressed @HttpServer.addRoute(b'/sample/button') async def buttonPressed(request, response, args): print("Button clicked") await response.sendOk() # Called when the slider state changed @HttpServer.addRoute(b'/sample/slider') async def sliderChanged(request, response, args): print("Slider change to %d"%int(request.params[b"value"])) await response.sendOk() # Called when the combo state changed @HttpServer.addRoute(b'/sample/combo') async def comboChanged(request, response, args): print("Number %s selected"%useful.tostrings(request.params[b"value"])) await response.sendOk() # Called when the switch state changed @HttpServer.addRoute(b'/sample/switch') async def switchChanged(request, response, args): print("Switch change to %s"%useful.tostrings(request.params[b"value"])) await response.sendOk() # Test simple page with button @HttpServer.addRoute(b'/sample', menu=b"Sample", item=b"Sample") async def samplePage(request, response, args): page = mainFrame(request, response, args, b"Sample", Tag(b''' Example to interact with esp32 via an html page (see the content of file sample.py) '''), ButtonCmd(text=b"Click on button", path=b"/sample/button"), Br(),Br(), SliderCmd(min=b"10", max=b"30", step=b"2", value=b"12", text=b"Move slider", path=b"/sample/slider"), Br(), ComboCmd(\ [ Option(value=b"One" , text=b"One"), Option(value=b"Two" , text=b"Two", selected=True), Option(value=b"Three" , text=b"Three"), ], path=b"/sample/combo", text=b"Select number"), Br(),Br(), SwitchCmd(text=b"Change this switch", checked=True, path=b"/sample/switch"), Br(), Br(), Paragraph(b"To eliminate this page delete the sample.py file")) await response.sendPage(page)

[ "remi_bertholet@yahoo.fr" ]

remi_bertholet@yahoo.fr

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2023-03-15T04:29:16.039753

2020-12-30T19:35:54

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# coding=utf-8 # *** WARNING: this file was generated by crd2pulumi. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** SNAKE_TO_CAMEL_CASE_TABLE = { "access_group_def": "accessGroupDef", "access_group_id": "accessGroupID", "access_group_name": "accessGroupName", "access_group_namespace": "accessGroupNamespace", "api_version": "apiVersion", "custom_role_name": "customRoleName", "custom_role_namespace": "customRoleNamespace", "custom_roles_d_name": "customRolesDName", "custom_roles_def": "customRolesDef", "defined_roles": "definedRoles", "display_name": "displayName", "group_id": "GroupID", "policy_id": "policyID", "resource_group": "resourceGroup", "resource_id": "resourceID", "resource_key": "resourceKey", "resource_name": "resourceName", "resource_value": "resourceValue", "role_crn": "roleCRN", "role_id": "roleID", "role_name": "roleName", "service_class": "serviceClass", "service_i_ds": "serviceIDs", "service_id": "serviceID", "user_email": "userEmail", "user_emails": "userEmails", } CAMEL_TO_SNAKE_CASE_TABLE = { "accessGroupDef": "access_group_def", "accessGroupID": "access_group_id", "accessGroupName": "access_group_name", "accessGroupNamespace": "access_group_namespace", "apiVersion": "api_version", "customRoleName": "custom_role_name", "customRoleNamespace": "custom_role_namespace", "customRolesDName": "custom_roles_d_name", "customRolesDef": "custom_roles_def", "definedRoles": "defined_roles", "displayName": "display_name", "GroupID": "group_id", "policyID": "policy_id", "resourceGroup": "resource_group", "resourceID": "resource_id", "resourceKey": "resource_key", "resourceName": "resource_name", "resourceValue": "resource_value", "roleCRN": "role_crn", "roleID": "role_id", "roleName": "role_name", "serviceClass": "service_class", "serviceIDs": "service_i_ds", "serviceID": "service_id", "userEmail": "user_email", "userEmails": "user_emails", }

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/solutions_python/Problem_135/203.py

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import sys in_ = sys.stdin T = int(in_.readline()) for t in xrange(T): r1 = int(in_.readline()) a1 = [map(int, in_.readline().split(' ')) for i in xrange(4)] r2 = int(in_.readline()) a2 = [map(int, in_.readline().split(' ')) for i in xrange(4)] res = set(a1[r1 - 1]).intersection(a2[r2 - 1]) prefix = 'Case #%d:' % (t + 1) if len(res) == 1: print prefix, list(res)[0] elif len(res) > 1: print prefix, 'Bad magician!' else: print prefix, 'Volunteer cheated!'

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/LeetCode/!0232. Implement Queue using Stacks.py

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AshkenSC/Programming-Practice

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''' 0232. Implement Queue using Stacks 请你仅使用两个栈实现先入先出队列。队列应当支持一般队列的支持的所有操作（push、pop、peek、empty）。 ''' class MyQueue: def __init__(self): """ Initialize your data structure here. """ self.stk = [] self.temp = [] self.current_queue = 0 def push(self, x: int) -> None: """ Push element x to the back of queue. 1) 压入stk """ self.stk.append(x) def pop(self) -> int: """ Removes the element from in front of queue and returns that element. 1）stk所有元素压入temp 2）出栈一次 3）temp中剩余元素压回stk，temp清空 """ while len(self.stk) > 0: self.temp.append(self.stk.pop()) top = self.temp.pop() while len(self.temp) > 0: cur = self.temp.pop() self.stk.append(cur) return top def peek(self) -> int: """ Get the front element. 1）stk所有元素压入temp 2）top一次 3）temp元素放回stk 4）temp清空 """ while len(self.stk) > 0: self.temp.append(self.stk.pop()) top = self.temp[-1] while len(self.temp) > 0: self.stk.append(self.temp.pop()) return top def empty(self) -> bool: """ Returns whether the queue is empty. 1）检查len(stk) """ return len(self.stk) < 1

[ "393940378@qq.com" ]

393940378@qq.com

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def arrayMaxConsecutiveSum(a, k): res = [sum(a[0:k])] for i in range(1, len(a)-k+1): res.append(res[i-1]-a[i-1]+a[i+k-1]) return(max(res)) inputArray = [1, 3, 2, 4] k = 3 # , the output should be print(arrayMaxConsecutiveSum(inputArray, k)) # = 9. # All possible sums of 2 consecutive elements are: # 2 + 3 = 5 # 3 + 5 = 8 # 5 + 1 = 6 # 1 + 6 = 7. # Thus, the answer is 8.

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import pygame class Ship(): def __init__(self, ai_settings, screen): """Initialize the ship, and set its starting position.""" self.screen = screen self.ai_settings = ai_settings # Load the ship image, and get its rect. self.image = pygame.image.load('images/ship.bmp') self.rect = self.image.get_rect() self.screen_rect = screen.get_rect() # Start each new ship at the bottom center of the screen. self.rect.centerx = self.screen_rect.centerx self.rect.bottom = self.screen_rect.bottom # Store a decimal value for the ship's center. self.center = float(self.rect.centerx) # Movement flags. self.moving_right = False self.moving_left = False def update(self): """Update the ship's position, based on movement flags.""" # Update the ship's center value, not the rect. if self.moving_right and self.rect.right < self.screen_rect.right: self.center += self.ai_settings.ship_speed_factor if self.moving_left and self.rect.left > 0: self.center -= self.ai_settings.ship_speed_factor # Update rect object from self.center. self.rect.centerx = self.center def blitme(self): """Draw the ship at its current location.""" self.screen.blit(self.image, self.rect)

[ "bryan.guner@gmail.com" ]

bryan.guner@gmail.com

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2021-07-09T18:34:09.462100

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"""From built-in optimizer classes. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import six import copy from six.moves import zip from tensorflow.keras import backend as K from tensorflow.keras.utils.generic_utils import serialize_keras_object from tensorflow.keras.utils.generic_utils import deserialize_keras_object from tensorflow.keras.legacy import interfaces from tensorflow.keras.optimizers import Optimizer class AdamW(Optimizer): """AdamW optimizer. Default parameters follow those provided in the original paper. # Arguments lr: float >= 0. Learning rate. beta_1: float, 0 < beta < 1. Generally close to 1. beta_2: float, 0 < beta < 1. Generally close to 1. epsilon: float >= 0. Fuzz factor. If `None`, defaults to `K.epsilon()`. decay: float >= 0. Learning rate decay over each update. weight_decay: float >= 0. Weight decay (L2 penalty) (default: 0.025). batch_size: integer >= 1. Batch size used during training. samples_per_epoch: integer >= 1. Number of samples (training points) per epoch. epochs: integer >= 1. Total number of epochs for training. # References - [Adam - A Method for Stochastic Optimization](http://arxiv.org/abs/1412.6980v8) - [Fixing Weight Decay Regularization in Adam](https://arxiv.org/abs/1711.05101) """ def __init__(self, lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0., weight_decay=0.025, batch_size=1, samples_per_epoch=1, epochs=1, **kwargs): super(AdamW, self).__init__(**kwargs) with K.name_scope(self.__class__.__name__): self.iterations = K.variable(0, dtype='int64', name='iterations') self.lr = K.variable(lr, name='lr') self.beta_1 = K.variable(beta_1, name='beta_1') self.beta_2 = K.variable(beta_2, name='beta_2') self.decay = K.variable(decay, name='decay') self.weight_decay = K.variable(weight_decay, name='weight_decay') self.batch_size = K.variable(batch_size, name='batch_size') self.samples_per_epoch = K.variable(samples_per_epoch, name='samples_per_epoch') self.epochs = K.variable(epochs, name='epochs') if epsilon is None: epsilon = K.epsilon() self.epsilon = epsilon self.initial_decay = decay @interfaces.legacy_get_updates_support def get_updates(self, loss, params): grads = self.get_gradients(loss, params) self.updates = [K.update_add(self.iterations, 1)] lr = self.lr if self.initial_decay > 0: lr = lr * (1. / (1. + self.decay * K.cast(self.iterations, K.dtype(self.decay)))) t = K.cast(self.iterations, K.floatx()) + 1 '''Bias corrections according to the Adam paper ''' lr_t = lr * (K.sqrt(1. - K.pow(self.beta_2, t)) / (1. - K.pow(self.beta_1, t))) ms = [K.zeros(K.int_shape(p), dtype=K.dtype(p)) for p in params] vs = [K.zeros(K.int_shape(p), dtype=K.dtype(p)) for p in params] self.weights = [self.iterations] + ms + vs for p, g, m, v in zip(params, grads, ms, vs): m_t = (self.beta_1 * m) + (1. - self.beta_1) * g v_t = (self.beta_2 * v) + (1. - self.beta_2) * K.square(g) '''Schedule multiplier eta_t = 1 for simple AdamW According to the AdamW paper, eta_t can be fixed, decay, or also be used for warm restarts (AdamWR to come). ''' eta_t = 1. p_t = p - eta_t*(lr_t * m_t / (K.sqrt(v_t) + self.epsilon)) if self.weight_decay != 0: '''Normalized weight decay according to the AdamW paper ''' w_d = self.weight_decay*K.sqrt(self.batch_size/(self.samples_per_epoch*self.epochs)) p_t = p_t - eta_t*(w_d*p) self.updates.append(K.update(m, m_t)) self.updates.append(K.update(v, v_t)) new_p = p_t # Apply constraints. if getattr(p, 'constraint', None) is not None: new_p = p.constraint(new_p) self.updates.append(K.update(p, new_p)) return self.updates def get_config(self): config = {'lr': float(K.get_value(self.lr)), 'beta_1': float(K.get_value(self.beta_1)), 'beta_2': float(K.get_value(self.beta_2)), 'decay': float(K.get_value(self.decay)), 'weight_decay': float(K.get_value(self.weight_decay)), 'batch_size': int(K.get_value(self.batch_size)), 'samples_per_epoch': int(K.get_value(self.samples_per_epoch)), 'epochs': int(K.get_value(self.epochs)), 'epsilon': self.epsilon} base_config = super(AdamW, self).get_config() return dict(list(base_config.items()) + list(config.items()))

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[]

no_license

michaelJwilson/SV-QA

8f486422eb71b3fbd0d395904fd654ba432bd777

dd6095d570442852bb28ac9da0f18be7b83cddce

refs/heads/master

2020-07-29T16:04:55.759155

2019-12-20T14:37:23

209,872,086

0

null

UTF-8

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py

import os import sys import glob import fitsio import matplotlib import pylab as pl import pandas as pd import numpy as np import astropy.io.fits as fits import matplotlib.pyplot as plt import numpy.lib.recfunctions as rfn import healpy as hp from mpl_toolkits.axes_grid1 import make_axes_locatable from fast_scatter import fast_scatter from matplotlib import rc from astropy.table import Table, vstack from desitarget.targets import encode_targetid from desitarget.geomask import is_in_box from desitarget.targetmask import desi_mask from mpl_toolkits.axes_grid1 import make_axes_locatable from mpl_toolkits.axes_grid1.inset_locator import inset_axes from scipy.stats import pearsonr rc('font', **{'family':'serif', 'serif':['Times']}) rc('text', usetex=True) ## nside = np.int(sys.argv[1]) parea = hp.nside2pixarea(nside, degrees = True) def read_elgs(nrandom=20000, _all=False): cols = ['NOBS_G', 'NOBS_R', 'NOBS_Z', 'PSFDEPTH_G', 'PSFDEPTH_R', 'PSFDEPTH_Z', 'GALDEPTH_G', 'GALDEPTH_R', 'GALDEPTH_Z', 'PSFSIZE_G', 'PSFSIZE_R', 'PSFSIZE_Z', 'PSFDEPTH_W1', 'PSFDEPTH_W2', 'MASKBITS'] if _all: nrandom = -1 randoms = fitsio.FITS('/project/projectdirs/desi/target/catalogs/dr8/0.31.0/randomsall/randoms-inside-dr8-0.31.0-all.fits') else: randoms = fitsio.FITS('/project/projectdirs/desi/target/catalogs/dr8/0.31.0/randoms/randoms-inside-dr8-0.31.0-2.fits') ## randoms = randoms[1][cols + ['RA', 'DEC']][:nrandom] return randoms, cols if __name__ == '__main__': nside = 512 _all = True save = False ## randoms, cols = read_elgs(nrandom=5000, _all=_all) isin = np.ones(len(randoms), dtype=np.float) for bit in [1, 5, 6, 7, 11, 12, 13]: isin = isin * (1.0 - np.clip(np.bitwise_and(randoms['MASKBITS'], np.ones_like(randoms['MASKBITS']) * 2 ** bit), a_min=0.0, a_max=1.0)) ## isin = isin * np.array([(x & 2 ** bit) == 0 for x in randoms['MASKBITS']]).astype(np.int) isin = isin.astype(np.bool) remaining = randoms[isin] print('Input: {}; Remaining: {} ({})'.format(len(randoms), len(remaining), np.count_nonzero(isin))) ## randoms = Table(data=randoms, names=['RA', 'DEC'] + cols) ## randoms.pprint() ''' binary = np.load('/global/cscratch1/sd/mjwilson/BGS/SV-ASSIGN/healmaps/elg_tdensity_{}.npy'.format(nside)) rhpind = binary[:,0] rhpra = binary[:,1] rhpdec = binary[:,2] rtdensity = binary[:,3] ''' ## npix = hp.pixelfunc.nside2npix(nside) indices = np.arange(npix) result = np.zeros_like(indices) denom = np.zeros_like(indices) ## hppix = hp.ang2pix(nside, (90. - remaining['DEC']) * np.pi / 180., remaining['RA'] * np.pi / 180., nest=False) hpind, cnts = np.unique(hppix, return_counts=True) for i, ind in enumerate(hpind): result[ind] += cnts[i] hppix = hp.ang2pix(nside, (90. - randoms['DEC']) * np.pi / 180., randoms['RA'] * np.pi / 180., nest=False) hpind, cnts = np.unique(hppix, return_counts=True) for i, ind in enumerate(hpind): denom[ind] += cnts[i] mask = np.array(denom > 0.0).astype(np.int) result = mask * result / denom occupied = result[result > 0.0] print('\n\nDeviation level: {:.3} per cent.'.format(100. * np.std(occupied))) ## theta, phi = hp.pix2ang(nside, range(npix), nest=False) hpra, hpdec = 180. / np.pi * phi, 90. -180. / np.pi * theta if save: np.save(os.environ['CSCRATCH'] + '/BGS/SV-ASSIGN/elgs/pix_area.npy', np.c_[np.arange(npix), hpra, hpdec, result]) print('\n\nDone.\n\n') if not _all: fig, axarr = plt.subplots(nrows=1, ncols=1, figsize=(10, 10)) plt.subplots_adjust(left = 0.05, right = 0.95, hspace=0.4, wspace=0.2, top = 0.955, bottom = 0.025) hpra[hpra > 300.] -= 360. hpra += 60. fast_scatter(axarr, hpra, hpdec, mask, -0.1, 1.1, 50, cmap='BuPu', printit=False) axarr.set_xlim(365., -5.) pl.savefig('pix_area_test.png')

[ "mjwilson@lbl.gov" ]

mjwilson@lbl.gov

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/moodledata/vpl_data/90/usersdata/197/60329/submittedfiles/matriz2.py

85af8758f0a532d442df4077a2a04b076b7f95fe

[]

no_license

rafaelperazzo/programacao-web

95643423a35c44613b0f64bed05bd34780fe2436

170dd5440afb9ee68a973f3de13a99aa4c735d79

refs/heads/master

2021-01-12T14:06:25.773146

2017-12-22T16:05:45

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# -*- coding: utf-8 -*- import numpy AS np n=int(input('Digite o numero de linhas e colunas:')) a=np.zeros((n,n)) for i in range (0, a.shape[0] def somas iguais(a):

[ "rafael.mota@ufca.edu.br" ]

rafael.mota@ufca.edu.br

5dc345bc932009a8b62c1f5f0ee1a5f1c621fe79

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/protocol/split_mutations.py

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[]

no_license

Ningshiqi/protocol

07e0e95c57d74e0ea2bbbfd7d49f9dc42c5dc37e

8a906a79a2835a61d252cafc2452b407230c4409

refs/heads/master

2021-01-20T07:27:38.880511

2016-06-22T18:39:15

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from random_split import RandomSplit import pandas as pd import sys import argparse import os def mymkdir(dir_path): try: os.mkdir(dir_path) except OSError: pass def parse_arguments(): d = ('Generate splits of the data while respecting the proportion ' 'of each tumor type in the split.') parser = argparse.ArgumentParser(description=d) help_str = 'Mutations in correct format' parser.add_argument('-i', '--input', type=str, required=True, help=help_str) help_str = 'Number of times to perform random split of data' parser.add_argument('-n', '--number', type=int, default=1, help=help_str) help_str = ('Column name containing the sample ID. Default: automatically' ' checks whether "Tumor_Sample_Barcode" or "Tumor_Sample" is a column.') parser.add_argument('-s', '--sample-col', type=str, default=None, help=help_str) help_str = 'Output directory for mutations split into two files' parser.add_argument('-o', '--output', type=str, required=True, help=help_str) args = parser.parse_args() return vars(args) def main(opts): # try to make directory mymkdir(opts['output']) # read in data df = pd.read_csv(opts['mutations'], sep='\t') # figure out the sample column if opts['sample_col'] is not None: samp_col = opts['sample_col'] if 'Tumor_Sample_Barcode' in df.columns: samp_col = 'Tumor_Sample_Barcode' elif 'Tumor_Sample' in df.columns: samp_col = 'Tumor_Sample' else: logger.warning('Please specify the column name for the sample ID (--sample-col)') sys.exit(1) # setup random splitting object SAMPLE_RATE = .5 # half splits dfg = RandomSplit(df.copy(), col_name=samp_col, sub_sample=SAMPLE_RATE, num_iter=opts['number']) # make random splits for i, (left_df, right_df) in enumerate(dfg.dataframe_generator()): output_dir = os.path.join(opts['output'], 'Iteration_{0}'.format(i)) mymkdir(output_dir) # make sure data is sorted by genes, so no problem with entropy script # assuming sorted order left_df.sort(columns=['Gene'], inplace=True) right_df.sort(columns=['Gene'], inplace=True) lout_path = os.path.join(output_dir, 'first.txt') left_df.to_csv(lout_path, sep='\t', index=False) rout_path = os.path.join(output_dir, 'second.txt') right_df.to_csv(rout_path, sep='\t', index=False) if __name__ == '__main__': opts = parse_arguments() main(opts)

[ "collintokheim@gmail.com" ]

collintokheim@gmail.com

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/Python_codes/p02629/s238693041.py

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[]

no_license

Aasthaengg/IBMdataset

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f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

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import sys , math from bisect import bisect N=int(input()) alp="abcdefghijklmnopqrstuvwxyz" R=[] i=1 tot = 0 while tot < 1000000000000001: tar = 26**i tot+=tar R.append(tot+1) i+=1 keta = bisect(R , N)+1 if keta == 1: print(alp[N-1]) sys.exit() ans = "" M = N - R[keta - 1] for i in range(keta): j = keta - i - 1 ind = M // (26**j) M -= ind * (26**j) ans+=alp[ind] print(ans)

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

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/ironbox/evaluation_models/classify_fcnet.py

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[]

no_license

evanthebouncy/class_and_style

5f165f75e3850919e90a05a72533209429efed04

d434e2414526bece7d6757f4c9c1ccb94263769f

refs/heads/master

2020-03-29T18:09:36.417411

2019-02-04T22:10:33

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UTF-8

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import numpy as np import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torch.autograd import Variable # ===================== FC NN CLASSIFIER ===================== def to_torch(x, dtype, req = False): tor_type = torch.cuda.LongTensor if dtype == "int" else torch.cuda.FloatTensor x = Variable(torch.from_numpy(x).type(tor_type), requires_grad = req) return x # A simple fully connected neural nework representing a function that maps # A input_dim input to k classes class FCNet(nn.Module): # require input dimension, k_classes outputs # input-layer, input_dim // 2 hidden layer, k_class output layer def __init__(self, input_dim, k_classes): super(FCNet, self).__init__() self.name = "FCNet" self.fc = nn.Linear(input_dim, input_dim // 2) self.pred = nn.Linear(input_dim // 2, k_classes) self.opt = torch.optim.Adam(self.parameters(), lr=0.001) def predict(self, x): x = F.relu(self.fc(x)) x = F.log_softmax(self.pred(x), dim=1) return x # train until saturation # assume train_corpus is a data_holder that supports a 'get_sample(n_batch)' # function which return some samples def learn(self, train_corpus): losses = [] while True: # terminate if no improvement if len(losses) > 2100: if losses[-1] < 1e-3: break near_data_loss = np.mean(losses[-1000:]) far_data_loss = np.mean(losses[-2000:-1000]) # if average loss of last 1k iteration is greater than 99% of the # last last 1k iterations, stop too if near_data_loss > 0.99 * far_data_loss: break # randomly sample a batch of data X_batch, Y_batch = train_corpus.get_sample(40) # convert to proper torch forms X_batch = to_torch(X_batch, "float") Y_batch = to_torch(Y_batch, "int") # optimize self.opt.zero_grad() output = self.predict(X_batch) loss = F.nll_loss(output, Y_batch) losses.append( loss.data.cpu().numpy() ) loss.backward() self.opt.step() # evaluate the model on the test_corpus, here test_corpus is assumed to be simply # a pair of X, Y def evaluate(self, test_corpus): X, Y = test_corpus X = to_torch(X, "float") label_pred = np.argmax(self.predict(X).data.cpu().numpy(), axis=1) return np.sum(label_pred != Y) / len(Y) if __name__ == '__main__': fcnet = FCNet(100, 4) print ("hi")

[ "evanthebouncy@gmail.com" ]

evanthebouncy@gmail.com

b761885bc3e88a2116f44fd2680442026270b9cd

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/memegen/memegen/routes/examples.py

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permissive

flavienbwk/memegen

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refs/heads/master

2020-11-25T03:38:56.626649

2019-12-16T23:59:24

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2019-12-16T22:09:07

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from flask import Blueprint, render_template, current_app, make_response from ._utils import samples blueprint = Blueprint('examples-page', __name__) @blueprint.route("/examples") def get(): sample_images = list(samples()) html = render_template( "examples.html", sample_images=sample_images, config=current_app.config, ) response = make_response(html) response.headers['Cache-Control'] = f'max-age={60*60*24*7}' return response

[ "jacebrowning@gmail.com" ]

jacebrowning@gmail.com

d003a7c6ff75f74dbe0eb5bd94675975cd7a687c

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/matplotlib/多序列堆积条状图.py

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[]

no_license

thj120000/python

eb7daddefef6b9a1039e8ef58c3af88e05ffb794

a52aad1e57b100064db3e1e3a2af3c02eded4bf7

refs/heads/master

2020-04-24T19:29:48.741308

2019-03-03T11:11:12

172,213,828

2

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#!@Author : Sanwat #!@File : .py import numpy as np import pandas as pd import matplotlib.pyplot as plt ''' bar()类型，可以将pandas 的dataframe he series用图表表示出来 ''' plt.figure(1) series1= np.array([3,4,5,3]) series2= np.array([1,2,2,5]) series3= np.array([2,3,3,4]) index= np.arange(4) plt.axis([0,4,0,15]) plt.bar(index,series1,color='r') plt.bar(index,series2,color='g',bottom=series1) plt.bar(index,series3,color='b',bottom=series1+series2) plt.xticks(index-0.4,['Jan15','Feb15','Mar15','Apr15']) plt.show() plt.figure(2) plt.axis([0,15,0,4]) plt.barh(index,series1,color='g') plt.barh(index,series2,color='r',left=series1) plt.barh(index,series3,color='b',left=series1+series2) plt.yticks(index-0.4,['Jan','Feb','Mar','Apr']) plt.show() ''' 下面我们用不同的颜色来区分多个序列。 ''' plt.figure(3) plt.axis([0,15,0,4]) plt.title('A Multiseries Horizontal Bar Chart',fontsize=20,color='r') plt.barh(index,series1,color='w',hatch='xx')#hatch关键字指定线条的类型 plt.barh(index,series2,color='w',hatch= '///',left=series1) plt.barh(index,series3,color='w',hatch='\\\\\\',left=series1+series2) plt.yticks(index-0.4,['Jan','Feb','Mar','Apr']) plt.show()

[ "2464237217@qq.com" ]

2464237217@qq.com

c2a45a4d33438fa9313023600490c3ba37f977e5

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/src/python/WMComponent/DBS3Buffer/Oracle/DBSBufferFiles/SetLocationByLFN.py

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[]

no_license

cinquo/WMCore

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122f9332f2e944154dd0df68b6b3f2875427b032

refs/heads/master

2021-01-09T06:28:58.947626

2013-06-05T08:31:53

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#!/usr/bin/env python """ _SetLocationByLFN_ Oracle implementation of DBSBuffer.SetLocationByLFN """ from WMComponent.DBS3Buffer.MySQL.DBSBufferFiles.SetLocationByLFN import SetLocationByLFN as MySQLSetLocationByLFN class SetLocationByLFN(MySQLSetLocationByLFN): """ Set the location of files using lfn as the key """ sql = """INSERT INTO dbsbuffer_file_location (filename, location) SELECT df.id, dl.id FROM dbsbuffer_file df, dbsbuffer_location dl WHERE df.lfn = :lfn AND dl.se_name = :sename """

[ "sfoulkes@4525493e-7705-40b1-a816-d608a930855b" ]

sfoulkes@4525493e-7705-40b1-a816-d608a930855b

15c3b44a518019dd9db25700f49622a3c9501ea3

488ae9723f148082e949448eed2fdcb4c111e784

/bill-calculator.py

61c9064f33cd5cda10414550cac73be05a057b70

[]

no_license

priyanka-advani/hba_functions_exercise

91b55ab221557d6358a6364bc8d26bb9644b12fc

d4a1d6cbfc90cc3fbee8157ba2e8707d36ef8484

refs/heads/master

2021-01-20T02:39:11.656709

2017-04-26T04:20:16

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""" This is Part 4 of the Hackbright Prep functions exercise """ def calculate_tip(bill_amt, tip_percentage): """Given the bill amount and tip percentage, calculates the tip.""" # ENTER YOUR CODE HERE tip_amt = bill_amt * tip_percentage return tip_amt def calculate_total(bill_amt, tip_amt): """Given the tip amount and the bill amount, calculates the total bill.""" # ENTER YOUR CODE HERE total = bill_amt + tip_amt return total def split_bill(total, number_of_people): """Given the bill total and the number of people, calculates the total per person.""" # ENTER YOUR CODE HERE total_per_person = total / number_of_people return total_per_person def total_per_person(): """Gets user input for bill amount, tip %, and # of people. Returns total per person. This function should: 1. Get user input for the bill amount, tip percentage, and # of people 2. Calculate the tip amount and save it to a variable. 3. Using the tip amount calculated above, find the total bill amount. 4. Using the total found above, calculate the total per person. """ # ENTER YOUR CODE HERE bill_amt = int(raw_input("Enter bill amount: ")) tip_percentage = float(raw_input("Enter tip percentage: ")) number_of_people = int(raw_input("Enter number of people: ")) tip_amt = calculate_tip(bill_amt, tip_percentage) total = calculate_total(bill_amt, tip_amt) per_person = split_bill(total, number_of_people) return per_person ############################################################################## # Don't touch the code below, this will allow us to run the total_per_person function when we # run our python file in the terminal using `python bill-calculator.py` if __name__ == "__main__": print total_per_person()

[ "no-reply@hackbrightacademy.com" ]

no-reply@hackbrightacademy.com

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/apps/users/forms.py

bfaf6e3a5f29e314158102103fa93e41451581f5

[]

no_license

shishengjia/Django_By_Example_Bookmarks

6ce125b2f15348b6b2fec26c4ff8694f000194e6

377d7ce31ea66e5e55032fcf47d84a1afd9acdbe

refs/heads/master

2021-01-19T14:16:52.566325

2017-04-27T12:23:41

88,141,126

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from django import forms from .models import UserProfile class LoginForm(forms.Form): username = forms.CharField(error_messages={'required': '请填写您的姓名'}) password = forms.CharField(min_length=6, error_messages={'required': '请填写您的密码', 'min_length': '密码不能少于6位'}) class RegisterForm(forms.ModelForm): username = forms.CharField() password = forms.CharField(label='Password', widget=forms.PasswordInput) class Meta: model = UserProfile fields = ('username', )

[ "shishengjia1@live.com" ]

shishengjia1@live.com

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/huaweicloud-sdk-ocr/huaweicloudsdkocr/v1/model/recognize_thailand_idcard_request.py

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huaweicloud/huaweicloud-sdk-python-v3

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refs/heads/master

2023-09-01T19:29:43.013318

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2023-06-22T14:50:48

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# coding: utf-8 import six from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization class RecognizeThailandIdcardRequest: """ 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. """ sensitive_list = [] openapi_types = { 'enterprise_project_id': 'str', 'body': 'ThailandIdcardRequestBody' } attribute_map = { 'enterprise_project_id': 'Enterprise-Project-Id', 'body': 'body' } def __init__(self, enterprise_project_id=None, body=None): """RecognizeThailandIdcardRequest The model defined in huaweicloud sdk :param enterprise_project_id: 企业项目ID。OCR支持通过企业项目管理（EPS）对不同用户组和用户的资源使用，进行分账。获取方法：进入“[企业项目管理](https://console-intl.huaweicloud.com/eps/?region=ap-southeast-2#/projects/list)”页面，单击企业项目名称，在企业项目详情页获取Enterprise-Project-Id（企业项目ID）。企业项目创建步骤请参见用户指南。 > 说明：创建企业项目后，在传参时，有以下三类场景。 - 携带正确的ID，正常使用OCR服务，账单归到企业ID对应的企业项目中。 - 携带错误的ID，正常使用OCR服务，账单的企业项目会被分类为“未归集”。 - 不携带ID，正常使用OCR服务，账单的企业项目会被分类为“未归集”。 :type enterprise_project_id: str :param body: Body of the RecognizeThailandIdcardRequest :type body: :class:`huaweicloudsdkocr.v1.ThailandIdcardRequestBody` """ self._enterprise_project_id = None self._body = None self.discriminator = None if enterprise_project_id is not None: self.enterprise_project_id = enterprise_project_id if body is not None: self.body = body @property def enterprise_project_id(self): """Gets the enterprise_project_id of this RecognizeThailandIdcardRequest. 企业项目ID。OCR支持通过企业项目管理（EPS）对不同用户组和用户的资源使用，进行分账。获取方法：进入“[企业项目管理](https://console-intl.huaweicloud.com/eps/?region=ap-southeast-2#/projects/list)”页面，单击企业项目名称，在企业项目详情页获取Enterprise-Project-Id（企业项目ID）。企业项目创建步骤请参见用户指南。 > 说明：创建企业项目后，在传参时，有以下三类场景。 - 携带正确的ID，正常使用OCR服务，账单归到企业ID对应的企业项目中。 - 携带错误的ID，正常使用OCR服务，账单的企业项目会被分类为“未归集”。 - 不携带ID，正常使用OCR服务，账单的企业项目会被分类为“未归集”。 :return: The enterprise_project_id of this RecognizeThailandIdcardRequest. :rtype: str """ return self._enterprise_project_id @enterprise_project_id.setter def enterprise_project_id(self, enterprise_project_id): """Sets the enterprise_project_id of this RecognizeThailandIdcardRequest. 企业项目ID。OCR支持通过企业项目管理（EPS）对不同用户组和用户的资源使用，进行分账。获取方法：进入“[企业项目管理](https://console-intl.huaweicloud.com/eps/?region=ap-southeast-2#/projects/list)”页面，单击企业项目名称，在企业项目详情页获取Enterprise-Project-Id（企业项目ID）。企业项目创建步骤请参见用户指南。 > 说明：创建企业项目后，在传参时，有以下三类场景。 - 携带正确的ID，正常使用OCR服务，账单归到企业ID对应的企业项目中。 - 携带错误的ID，正常使用OCR服务，账单的企业项目会被分类为“未归集”。 - 不携带ID，正常使用OCR服务，账单的企业项目会被分类为“未归集”。 :param enterprise_project_id: The enterprise_project_id of this RecognizeThailandIdcardRequest. :type enterprise_project_id: str """ self._enterprise_project_id = enterprise_project_id @property def body(self): """Gets the body of this RecognizeThailandIdcardRequest. :return: The body of this RecognizeThailandIdcardRequest. :rtype: :class:`huaweicloudsdkocr.v1.ThailandIdcardRequestBody` """ return self._body @body.setter def body(self, body): """Sets the body of this RecognizeThailandIdcardRequest. :param body: The body of this RecognizeThailandIdcardRequest. :type body: :class:`huaweicloudsdkocr.v1.ThailandIdcardRequestBody` """ self._body = body 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: if attr in self.sensitive_list: result[attr] = "****" else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" import simplejson as json if six.PY2: import sys reload(sys) sys.setdefaultencoding("utf-8") return json.dumps(sanitize_for_serialization(self), ensure_ascii=False) def __repr__(self): """For `print`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, RecognizeThailandIdcardRequest): 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 tkinter as tk def submit(): print("Submit pressed") list.append(ent.get()) print(list) lab.config(text = "Changed") #This function will parse a string and #add a new element to the list for all #values #creates an empty list list = [] root = tk.Tk() lab = tk.Label(root, text = "Input Food") lab.pack() ent = tk.Entry(root) ent.pack() btn = tk.Button(root, text = "Submit", command = submit) btn.pack() root.mainloop()

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from math import cos, log10, isnan from I3Tray import I3Units from icecube import icetray, dataclasses from icecube.production_histograms.histograms.histogram import Histogram from icecube.production_histograms.histogram_modules.histogram_module import HistogramModule class CORSIKAWeightModule(HistogramModule): def __init__(self): HistogramModule.__init__(self) self.frame_key = "CorsikaWeightMap" self.append(Histogram(, , , "FluxSum")) self.append(Histogram(, , , "Weight")) def DAQ(self, frame): if self.frame_key not in frame : return weight_dict = frame[self.frame_key] if "FluxSum" in weight_dict: self.histograms["FluxSum"].fill(weight_dict["FluxSum"]) if "Weight" in weight_dict: self.histograms["Weight"].fill(weight_dict["Weight"])

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import tetris class Main: def __init__(self, screen): self.screen = screen def run(self, elapse): return self.tetris.update(elapse) def start(self, kind): if kind == 6: self.tetris = tetris.Tetris(self.screen) else: self.tetris = eval( "tetris.Tetris" + str(kind) + "(self.screen)")

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.contrib.auth.models import AbstractBaseUser, PermissionsMixin from django.db import models from .managers import UserManager class User(AbstractBaseUser, PermissionsMixin): created_on = models.DateTimeField( auto_now_add=True, null=True, ) modified_on = models.DateTimeField( auto_now=True, null=True, ) deactivated = models.DateTimeField( blank=True, null=True, verbose_name='Deactivated', help_text='Designates whether this user should be treated as deactivated', ) first_name = models.CharField( max_length=30, blank=True, null=True, verbose_name='First Name', ) last_name = models.CharField( max_length=30, blank=True, null=True, verbose_name='Last Name', ) middle_name = models.CharField( max_length=30, blank=True, null=True, verbose_name='Middle Name', ) email = models.EmailField( unique=True, max_length=50, verbose_name='Email', ) phone = models.CharField( max_length=30, blank=True, null=True, verbose_name='Phone Number', ) is_staff = models.BooleanField( default=False, verbose_name='Is Staff', help_text='Designates whether the user can log into Django admin site', ) password_reset_token = models.CharField( max_length=50, blank=True, null=True, verbose_name='Password Reset Token', ) invitation_token = models.CharField( max_length=50, blank=True, null=True, verbose_name='Invitation Token' ) USERNAME_FIELD = 'email' objects = UserManager() class Meta: get_latest_by = 'date_joined' def __str__(self): return self.email

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from SortStrategy import SortStrategy class ShellSortStrategy(SortStrategy): """docstring for ShellSortStrategy""" def sort(self, my_list = []): return "Lista ordenada con Shell Sort!"

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# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/105_models.RNN.ipynb (unless otherwise specified). __all__ = ['RNN', 'LSTM', 'GRU'] # Cell from ..imports import * from .layers import * # Cell class _RNN_Base(Module): def __init__(self, c_in, c_out, hidden_size=100, n_layers=1, bias=True, rnn_dropout=0, bidirectional=False, fc_dropout=0.): self.rnn = self._cell(c_in, hidden_size, num_layers=n_layers, bias=bias, batch_first=True, dropout=rnn_dropout, bidirectional=bidirectional) self.dropout = nn.Dropout(fc_dropout) if fc_dropout else noop self.fc = nn.Linear(hidden_size * (1 + bidirectional), c_out) def forward(self, x): x = x.transpose(2,1) # [batch_size x n_vars x seq_len] --> [batch_size x seq_len x n_vars] output, _ = self.rnn(x) # output from all sequence steps: [batch_size x seq_len x hidden_size * (1 + bidirectional)] output = output[:, -1] # output from last sequence step : [batch_size x hidden_size * (1 + bidirectional)] output = self.fc(self.dropout(output)) return output class RNN(_RNN_Base): _cell = nn.RNN class LSTM(_RNN_Base): _cell = nn.LSTM class GRU(_RNN_Base): _cell = nn.GRU

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations def add_legacy_name(apps, schema_editor): ContentType = apps.get_model('contenttypes', 'ContentType') for ct in ContentType.objects.all(): try: ct.name = apps.get_model(ct.app_label, ct.model)._meta.object_name except: ct.name = ct.model ct.save() class Migration(migrations.Migration): dependencies = [ ('contenttypes', '0001_initial'), ] operations = [ migrations.AlterModelOptions( name='contenttype', options={'verbose_name': 'content type', 'verbose_name_plural': 'content types'}, ), migrations.AlterField( model_name='contenttype', name='name', field=models.CharField(max_length=100, null=True), ), migrations.RunPython( migrations.RunPython.noop, add_legacy_name, ), migrations.RemoveField( model_name='contenttype', name='name', ), ]

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# try to import Panda3D, but delay exceptions until the class is actually used try: from panda3d.core import NodePath, TextNode import panda3d except ImportError: panda3d = None #coloredtextbox class: this will be converted to a canvas drone using "build_canvasdrone" class coloredtextbox(object): #obligatory argument list for __init__: canvasdrone, object, identifier, parameters def __init__(self, canvasdrone, ctb, identifier, parameters): if panda3d is None: raise ImportError("Cannot locate Panda3D") from dragonfly.canvas import box2d if identifier is None: identifier = "" self.node = None box = box2d(ctb.posx, ctb.posy, ctb.sizex, ctb.sizey, ctb.sizemode) self.pnode = canvasdrone._get_parent_nodepath(identifier, box) self._show(ctb, identifier) #obligatory method "update". Argument list: object, identifier, parameters def update(self, ctb, identifier, parameters): self._show(ctb, identifier) #obligatory method "remove" def remove(self): if self.pnode is not None: self.pnode.removeNode() self.pnode = None def _show(self, ctb, identifier): if self.node is not None: self.node.removeNode() tnode = TextNode(identifier) tnode.setText(ctb.text) r, g, b, a = ctb.textcolor tnode.setTextColor(r, g, b, a) r, g, b, a = ctb.boxcolor tnode.setCardColor(r, g, b, a) tnode.setCardAsMargin(0, 0, 0, 0) tnode.setCardDecal(True) node = NodePath(tnode) self._scale(tnode, node) node.reparentTo(self.pnode) self.node = node def _scale(self, tnode, node): top, bottom = tnode.getTop(), tnode.getBottom() l, r = tnode.getLeft(), tnode.getRight() w, h = r - l, top - bottom scalex = 0 if w > 0: scalex = 1.0 / w scaley = 0 if h > 0: scaley = 1.0 / h node.setScale(scalex, 1, -scaley) dimx = w * scalex midx = (l * scalex + r * scalex) / 2.0 dimy = h * scaley midy = (top * scaley + bottom * scaley) / 2.0 node.setPos(-midx + 0.5, 0, midy - 0.5) import bee from dragonfly.canvas import canvasdrone from dragonfly.pandahive import build_canvasdrone coloredtextbox_panda = build_canvasdrone( wrappedclass=coloredtextbox, classname="coloredtextbox_panda", drawshow="show", drawshowtype=("object", "coloredtextbox"), baseclass=canvasdrone )

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# # Copyright 2018 Analytics Zoo Authors. # # 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 zoo.tfpark.text.estimator import * def make_bert_classifier_model_fn(optimizer): def _bert_classifier_model_fn(features, labels, mode, params): """ Model function for BERTClassifier. :param features: Dict of feature tensors. Must include the key "input_ids". :param labels: Label tensor for training. :param mode: 'train', 'eval' or 'infer'. :param params: Must include the key "num_classes". :return: tf.estimator.EstimatorSpec. """ import tensorflow as tf from zoo.tfpark import ZooOptimizer output_layer = bert_model(features, labels, mode, params).get_pooled_output() hidden_size = output_layer.shape[-1].value output_weights = tf.get_variable( "output_weights", [params["num_classes"], hidden_size], initializer=tf.truncated_normal_initializer(stddev=0.02)) output_bias = tf.get_variable( "output_bias", [params["num_classes"]], initializer=tf.zeros_initializer()) with tf.variable_scope("loss"): if mode == tf.estimator.ModeKeys.TRAIN: output_layer = tf.nn.dropout(output_layer, keep_prob=0.9) logits = tf.matmul(output_layer, output_weights, transpose_b=True) logits = tf.nn.bias_add(logits, output_bias) probabilities = tf.nn.softmax(logits, axis=-1) if mode == tf.estimator.ModeKeys.PREDICT: return tf.estimator.EstimatorSpec(mode=mode, predictions=probabilities) else: log_probs = tf.nn.log_softmax(logits, axis=-1) one_hot_labels = tf.one_hot(labels, depth=params["num_classes"], dtype=tf.float32) per_example_loss = -tf.reduce_sum(one_hot_labels * log_probs, axis=-1) loss = tf.reduce_mean(per_example_loss) if mode == tf.estimator.ModeKeys.EVAL: return tf.estimator.EstimatorSpec(mode=mode, predictions=probabilities, loss=loss) else: train_op = ZooOptimizer(optimizer).minimize(loss) return tf.estimator.EstimatorSpec(mode=mode, train_op=train_op, loss=loss) return _bert_classifier_model_fn class BERTClassifier(BERTBaseEstimator): """ A pre-built TFEstimator that takes the hidden state of the first token of BERT to do classification. :param num_classes: Positive int. The number of classes to be classified. :param bert_config_file: The path to the json file for BERT configurations. :param init_checkpoint: The path to the initial checkpoint of the pre-trained BERT model if any. Default is None. :param use_one_hot_embeddings: Boolean. Whether to use one-hot for word embeddings. Default is False. :param optimizer: The optimizer used to train the estimator. It should be an instance of tf.train.Optimizer. Default is None if no training is involved. :param model_dir: The output directory for model checkpoints to be written if any. Default is None. """ def __init__(self, num_classes, bert_config_file, init_checkpoint=None, use_one_hot_embeddings=False, optimizer=None, model_dir=None): super(BERTClassifier, self).__init__( model_fn=make_bert_classifier_model_fn(optimizer), bert_config_file=bert_config_file, init_checkpoint=init_checkpoint, use_one_hot_embeddings=use_one_hot_embeddings, model_dir=model_dir, num_classes=num_classes)

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import os import permeability as prm import matplotlib.pyplot as plt import pickle as pickle from os import system import pdb import numpy as np import mdtraj as mdt #data_dir = '/Users/rmhartkamp/Dropbox/PostDoc_2_Vanderbilt/Simulation/Permeability/DSPC_C12OH_3_1' #data_dir = '/raid6/homes/ahy3nz/Trajectories/Data/11_DSPC_C18OH/DSPC-50_alc18-50_5-4a' data_dir = os.getcwd() n_sweeps = 26 #n_sweeps = 30 preamble = "folder" prm.analyze_sweeps(data_dir, timestep=1.0, verbosity=2, directory_prefix='sweep', n_sweeps=n_sweeps, correlation_length=300) #prm.analyze_sweeps(data_dir, timestep=1000.0, verbosity=2, directory_prefix='sweep', n_sweeps=n_sweeps) #forcetime = prm.force_timeseries(data_dir, timestep=2.0, n_windows=40, start_window=15, directory_prefix='sweep') #prm.plot_timeseries(forcetime['time'], forcetime['forces']) output = prm.analyze_force_acf_data(data_dir, 305.0, timestep=1, verbosity=2, directory_prefix='sweep',n_sweeps=n_sweeps, kB=1.987e-3) pickle.dump(output, open('{}/output.p'.format(preamble), 'wb')) #output = pickle.load(open('output.p', 'rb')) #pdb.set_trace() #system('rm *.pdf *.png') prm.plot_forces(output['z'], output['forces'], fig_filename='{}/forces.pdf'.format(preamble),sweep_alpha=0.2) prm.plot_free_energy_z(output['z'], output['dG'], fig_filename='{}/delta_G.pdf'.format(preamble)) prm.plot_force_acfs_time(output['time'], output['facf_windows'], fig_filename="{}/force_acf.png".format(preamble), normalize=True) prm.plot_int_acfs_time(output['time'], output['int_facf_windows'], fig_filename="{}/int-acf.png".format(preamble)) prm.plot_symmetrized_free_energy(output['z'], output['dG_sym'], output['dG_sym_err'],savefig=True, fig_filename="{}/delG-sym.pdf".format(preamble)) prm.plot_sym_diffusion_coefficient_z(output['z'], output['d_z_sym'], output['d_z_sym_err'],savefig=True, fig_filename="{}/d-sym_z.pdf".format(preamble)) prm.plot_resistance_z(output['z'], output['R_z'], output['R_z_err'], savefig=True, fig_filename="{}/R_z.pdf".format(preamble)) prm.plot_sym_exp_free_energy(output['z'], output['dG_sym'], output['dG_sym_err'], output['d_z_sym'], output['d_z_sym_err'], output['R_z'], output['R_z_err'], 305, fig_filename="{}/expdelG-sym.pdf".format(preamble)) print('Permeability (cm/sec): {} ({})'.format(output['permeability'], output['perm_err'])) #prm.plot_forces(output['z'], output['forces'], fig_filename='forces.pdf',sweep_alpha=0.2) #prm.plot_free_energy_z(output['z'], output['dG'], fig_filename='delta_G.pdf') #prm.plot_force_acfs_time(output['time'], output['facf_windows'], normalize=True) #prm.plot_int_acfs_time(output['time'], output['int_facf_windows']) #prm.plot_symmetrized_free_energy(output['z'], output['dG_sym'], # output['dG_sym_err'],savefig=True) #prm.plot_sym_diffusion_coefficient_z(output['z'], output['d_z_sym'], # output['d_z_sym_err'],savefig=True) #prm.plot_resistance_z(output['z'], output['R_z'], output['R_z_err'], savefig=True) #prm.plot_sym_exp_free_energy(output['z'], output['dG_sym'], output['dG_sym_err'], output['d_z_sym'], # output['d_z_sym_err'], output['R_z'], output['R_z_err'], 305) #print('Permeability (cm/sec): {} ({})'.format(output['permeability'], output['perm_err'])) ##system('open -a preview *.pdf *.png')

[ "alexander.h.yang@vanderbilt.edu" ]

alexander.h.yang@vanderbilt.edu

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/python/beckjun/백준_2169_로봇 조종하기_백트래킹.py

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from collections import deque n, m = map(int, input().split()) mat = [list(map(int, input().split())) for _ in range(n)] di = (0,0,1) dj = (1,-1,0) dp = [[[-1000000001] * 3 for _ in range(m)] for _ in range(n)] q = deque([(mat[0][0], 0, 0, 0)]) dp[0][0][0] = max(dp[0][0][0], mat[0][0]) c = 0 while q: cnt, x, y, pre_d = q.popleft() for k in range(3): c += 1 newX, newY = x+di[k], y+dj[k] if pre_d^1 == k: continue if not (0 <= newX<n and 0<= newY<m): continue if dp[newX][newY][k] < cnt + mat[newX][newY]: dp[newX][newY][k] = cnt + mat[newX][newY] q.append((cnt + mat[newX][newY], newX, newY, k)) print(max(dp[n-1][m-1]),c)

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/tools/code_coverage/package/tool/parser/llvm_coverage_segment.py

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from typing import List, NamedTuple, Optional, Tuple class LlvmCoverageSegment(NamedTuple): line: int col: int segment_count: int has_count: int is_region_entry: int is_gap_entry: Optional[int] @property def has_coverage(self) -> bool: return self.segment_count > 0 @property def is_executable(self) -> bool: return self.has_count > 0 def get_coverage( self, prev_segment: "LlvmCoverageSegment" ) -> Tuple[List[int], List[int]]: # Code adapted from testpilot.testinfra.runners.gtestcoveragerunner.py if not prev_segment.is_executable: return [], [] # this segment ends at the line if col == 1 # (so segment effectively ends on the line) and # line+1 if col is > 1 (so it touches at least some part of last line). end_of_segment = self.line if self.col == 1 else self.line + 1 lines_range = list(range(prev_segment.line, end_of_segment)) return (lines_range, []) if prev_segment.has_coverage else ([], lines_range) def parse_segments(raw_segments: List[List[int]]) -> List[LlvmCoverageSegment]: """ Creates LlvmCoverageSegment from a list of lists in llvm export json. each segment is represented by 5-element array. """ ret: List[LlvmCoverageSegment] = [] for raw_segment in raw_segments: assert ( len(raw_segment) == 5 or len(raw_segment) == 6 ), "list is not compatible with llvmcom export:" " Expected to have 5 or 6 elements" if len(raw_segment) == 5: ret.append( LlvmCoverageSegment( raw_segment[0], raw_segment[1], raw_segment[2], raw_segment[3], raw_segment[4], None, ) ) else: ret.append(LlvmCoverageSegment(*raw_segment)) return ret

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/x12/4042/149004042.py

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dougvanhorn/bots-grammars

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from bots.botsconfig import * from records004042 import recorddefs syntax = { 'version' : '00403', #version of ISA to send 'functionalgroup' : 'NT', } structure = [ {ID: 'ST', MIN: 1, MAX: 1, LEVEL: [ {ID: 'BGN', MIN: 1, MAX: 1}, {ID: 'DTM', MIN: 1, MAX: 99999}, {ID: 'TDS', MIN: 0, MAX: 1}, {ID: 'REF', MIN: 0, MAX: 99999}, {ID: 'MSG', MIN: 0, MAX: 99999}, {ID: 'N1', MIN: 1, MAX: 99999, LEVEL: [ {ID: 'N2', MIN: 0, MAX: 2}, {ID: 'IN2', MIN: 0, MAX: 10}, {ID: 'N3', MIN: 0, MAX: 2}, {ID: 'N4', MIN: 0, MAX: 1}, {ID: 'PER', MIN: 0, MAX: 2}, ]}, {ID: 'TFS', MIN: 0, MAX: 99999, LEVEL: [ {ID: 'REF', MIN: 0, MAX: 99999}, {ID: 'DTM', MIN: 0, MAX: 99999}, {ID: 'TIA', MIN: 0, MAX: 99999}, {ID: 'N1', MIN: 0, MAX: 99999, LEVEL: [ {ID: 'N2', MIN: 0, MAX: 2}, {ID: 'IN2', MIN: 0, MAX: 10}, {ID: 'N3', MIN: 0, MAX: 2}, {ID: 'N4', MIN: 0, MAX: 1}, ]}, {ID: 'FGS', MIN: 0, MAX: 99999, LEVEL: [ {ID: 'REF', MIN: 0, MAX: 99999}, {ID: 'DTM', MIN: 0, MAX: 99999}, {ID: 'TIA', MIN: 0, MAX: 99999}, {ID: 'MSG', MIN: 0, MAX: 99999}, {ID: 'PCT', MIN: 0, MAX: 99999}, {ID: 'AMT', MIN: 0, MAX: 99999, LEVEL: [ {ID: 'DTM', MIN: 0, MAX: 99999}, ]}, {ID: 'N1', MIN: 0, MAX: 99999, LEVEL: [ {ID: 'N2', MIN: 0, MAX: 2}, {ID: 'IN2', MIN: 0, MAX: 10}, {ID: 'N3', MIN: 0, MAX: 2}, {ID: 'N4', MIN: 0, MAX: 1}, ]}, ]}, ]}, {ID: 'SE', MIN: 1, MAX: 1}, ]} ]

[ "jason.capriotti@gmail.com" ]

jason.capriotti@gmail.com

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/Chapter 12/nest_egg_mcs_1st_5yrs.py

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afettouhi/ImpracticalPythonProjects-py38

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refs/heads/master

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""" Retirement nest egg calculator using Monte Carlo simulation. """ import sys import random import matplotlib.pyplot as plt def read_to_list(file_name): """ Open a file of data in percent, convert to decimal & return a list. """ with open(file_name) as in_file: lines = [float(line.strip()) for line in in_file] decimal = [round(line / 100, 5) for line in lines] return decimal def default_input(prompt, default=None): """ Allow use of default values in input """ prompt = '{} [{}]: '.format(prompt, default) response = input(prompt) if not response and default: return default else: return response # load data files with original data in percent form print("\nNote: Input data should be in percent, not decimal!\n") try: bonds = read_to_list('../data/10-yr_TBond_returns_1926-2013_pct.txt') stocks = read_to_list('../data/SP500_returns_1926-2013_pct.txt') blend_40_50_10 = read_to_list('../data/S-B-C_blend_1926-2013_pct.txt') blend_50_50 = read_to_list('../data/S-B_blend_1926-2013_pct.txt') infl_rate = read_to_list('../data/annual_infl_rate_1926-2013_pct.txt') except IOError as e: print("{}. \nTerminating program.".format(e), file=sys.stderr) sys.exit(1) # get user input; use dictionary for investment-type arguments investment_type_args = {'bonds': bonds, 'stocks': stocks, 'sb_blend': blend_50_50, 'sbc_blend': blend_40_50_10} # print input legend for user print(" stocks = SP500") print(" bonds = 10-yr Treasury Bond") print(" sb_blend = 50% SP500/50% TBond") print("sbc_blend = 40% SP500/50% TBond/10% Cash\n") print("Press ENTER to take default value shown in [brackets]. \n") # get user input invest_type = default_input("Enter investment type: (stocks, bonds, sb_blend," \ " sbc_blend): \n", 'bonds').lower() while invest_type not in investment_type_args: invest_type = input("Invalid investment. Enter investment type " \ "as listed in prompt: ") start_value = default_input("Input starting value of investments: \n", \ '2000000') while not start_value.isdigit(): start_value = input("Invalid input! Input integer only: ") withdrawal_1 = default_input("Input annual pre-tax withdrawal for " \ "first 5 yrs(today's $): \n", '100000') while not withdrawal_1.isdigit(): withdrawal_1 = input("Invalid input! Input integer only: ") withdrawal_2 = default_input("Input annual pre-tax withdrawal for " \ "remainder (today's $): \n", '80000') while not withdrawal_2.isdigit(): withdrawal_2 = input("Invalid input! Input integer only: ") min_years = default_input("Input minimum years in retirement: \n", '18') while not min_years.isdigit(): min_years = input("Invalid input! Input integer only: ") most_likely_years = default_input("Input most-likely years in retirement: \n", '25') while not most_likely_years.isdigit(): most_likely_years = input("Invalid input! Input integer only: ") max_years = default_input("Input maximum years in retirement: \n", '40') while not max_years.isdigit(): max_years = input("Invalid input! Input integer only: ") num_cases = default_input("Input number of cases to run: \n", '50000') while not num_cases.isdigit(): num_cases = input("Invalid input! Input integer only: ") # check for other erroneous input if not int(min_years) < int(most_likely_years) < int(max_years) \ or int(max_years) > 99: print("\nProblem with input years.", file=sys.stderr) print("Requires Min < ML < Max & Max <= 99.", file=sys.stderr) sys.exit(1) def montecarlo(returns): """ Run MCS & return investment value at death & and # of times bankrupt. """ case_count = 0 bankrupt_count = 0 outcome = [] while case_count < int(num_cases): investments = int(start_value) start_year = random.randrange(0, len(returns)) duration = int(random.triangular(int(min_years), int(max_years), int(most_likely_years))) end_year = start_year + duration lifespan = [i for i in range(start_year, end_year)] bankrupt = 'no' # build temporary lists for each case lifespan_returns = [] lifespan_infl = [] for i in lifespan: lifespan_returns.append(returns[i % len(returns)]) lifespan_infl.append(infl_rate[i % len(infl_rate)]) # loop through each year of retirement for each case run for index, i in enumerate(lifespan_returns): infl = lifespan_infl[index] # don't adjust for inflation the first year if index == 0: withdraw_infl_adj_1 = int(withdrawal_1) withdraw_infl_adj_2 = int(withdrawal_2) else: withdraw_infl_adj_1 = int(withdraw_infl_adj_1 * (1 + infl)) withdraw_infl_adj_2 = int(withdraw_infl_adj_2 * (1 + infl)) if index < 5: withdraw_infl_adj = withdraw_infl_adj_1 else: withdraw_infl_adj = withdraw_infl_adj_2 investments -= withdraw_infl_adj investments = int(investments * (1 + i)) if investments <= 0: bankrupt = 'yes' break if bankrupt == 'yes': outcome.append(0) bankrupt_count += 1 else: outcome.append(investments) case_count += 1 return outcome, bankrupt_count def bankrupt_prob(outcome, bankrupt_count): """ Calculate & return chance of running out of money & print statistics. """ total = len(outcome) odds = round(100 * bankrupt_count / total, 1) print("\nInvestment type: {}".format(invest_type)) print("Starting value: ${:,}".format(int(start_value))) print("Annual withdrawal first 5 yrs: ${:,}".format(int(withdrawal_1))) print("Annual withdrawal after 5 yrs: ${:,}".format(int(withdrawal_2))) print("Years in retirement (min-ml-max): {}-{}-{}" .format(min_years, most_likely_years, max_years)) print("Number of runs: {:,}\n".format(len(outcome))) print("Odds of running out of money: {}%\n".format(odds)) print("Average outcome: ${:,}".format(int(sum(outcome) / total))) print("Minimum outcome: ${:,}".format(min(i for i in outcome))) print("Maximum outcome: ${:,}".format(max(i for i in outcome))) return odds def main(): """ Run the program and draw bar chart of results. """ outcome, bankrupt_count = montecarlo(investment_type_args[invest_type]) odds = bankrupt_prob(outcome, bankrupt_count) # generate matplotlib bar chart plotdata = outcome[:3000] # only plot first 3000 runs plt.figure('Outcome by Case (showing first {} runs)'.format(len(plotdata)), figsize=(16, 5)) # size is width, height in inches index = [i + 1 for i in range(len(plotdata))] plt.bar(index, plotdata, color='black') plt.xlabel('Simulated Lives', fontsize=18) plt.ylabel('$ Remaining', fontsize=18) plt.ticklabel_format(style='plain', axis='y') ax = plt.gca() ax.get_yaxis().set_major_formatter(plt.FuncFormatter(lambda x, loc: "{:,}" .format(int(x)))) plt.title('Probability of running out of money = {}%'.format(odds), fontsize=20, color='red') plt.show() # run program if __name__ == '__main__': main()

[ "A.Fettouhi@gmail.com" ]

A.Fettouhi@gmail.com

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/test/view_helpers/test_Maps_Views.py

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dariovillalon/OSBot-browser

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from unittest import TestCase from osbot_aws.apis.Lambda import Lambda from pbx_gs_python_utils.utils.Dev import Dev from osbot_browser.browser.Browser_Lamdba_Helper import Browser_Lamdba_Helper from osbot_browser.view_helpers.Maps_Views import Maps_Views from gw_bot.Deploy import Deploy class Test_Maps_Views(TestCase): def setUp(self): Deploy().setup() # set local ossbot environment self.maps_views = Maps_Views() self.png_data = None self.result = None def tearDown(self): if self.result: Dev.pprint(self.result) if self.png_data: Browser_Lamdba_Helper().save_png_data(self.png_data) def test_default(self): self.result = self.maps_views.default(headless=False)#,channel='DJ8UA0RFT') def test_exec_js(self): channel = 'DJ8UA0RFT' channel = None params = ["maps.add_component('aaa 123' , 2, 1)"] self.result = self.maps_views.exec_js(headless=False ,channel=channel, params=params) def test_via_lambda_execution(self): self.test_update_lambda() view = 'default' code = '' aws_lambda = Lambda('osbot_browser.lambdas.lambda_browser') payload = {"params": ["maps", view, code], 'data': { 'channel' : 'DJ8UA0RFT'}} self.result = aws_lambda.invoke(payload) def test_via_lambda_execution__version(self): self.test_update_lambda() aws_lambda = Lambda('osbot_browser.lambdas.lambda_browser') payload = {"params": ["maps", "version"],'data': {}} self.result = aws_lambda.invoke(payload) def test_update_lambda_browser(self): Deploy().setup().deploy_lambda__browser() def test_update_lambda_oss_bot(self): Deploy().setup().deploy_lambda__gw_bot()

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dinis.cruz@owasp.org

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/mysql_proto/plugins/plugin.py

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permissive

alvinzane/PyMP

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# coding=utf-8 class Plugin(object): def init(self, context): raise NotImplementedError() def read_handshake(self, context): raise NotImplementedError() def send_handshake(self, context): raise NotImplementedError() def read_auth(self, context): raise NotImplementedError() def send_auth(self, context): raise NotImplementedError() def read_auth_result(self, context): raise NotImplementedError() def send_auth_result(self, context): raise NotImplementedError() def read_query(self, context): raise NotImplementedError() def send_query(self, context): raise NotImplementedError() def read_query_result(self, context): raise NotImplementedError() def send_query_result(self, context): raise NotImplementedError() def cleanup(self, context): raise NotImplementedError() def shutdown(self, context): raise NotImplementedError()

[ "kormoc@gmail.com" ]

kormoc@gmail.com

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/Tree/Construct_Binary_Tree_from_Preorder_and_Postorder_Traversal.py

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[]

no_license

prashant97sikarwar/leetcode

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#Problem Link :- https://leetcode.com/problems/construct-binary-tree-from-preorder-and-postorder-traversal/ """Return any binary tree that matches the given preorder and postorder traversals. Values in the traversals pre and post are distinct positive integers.""" # Definition for a binary tree node. class TreeNode: def __init__(self, val=0, left=None, right=None): self.val = val self.left = left self.right = right class Solution: def constructFromPrePost(self, pre,post): if not pre: return root = TreeNode(pre[0]) if len(pre) == 1: return root L = post.index(pre[1]) + 1 root.left = self.constructFromPrePost(pre[1:L+1],post[:L]) root.right = self.constructFromPrePost(pre[L+1:],post[L:-1]) return root

[ "prashant97sikarwar@gmail.com" ]

prashant97sikarwar@gmail.com

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2021-03-02T15:13:22

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"""Useful for sequence tagging tasks like POS or NER.""" from quati import opts from quati.dataset.fields.affixes import AffixesField from quati.dataset.fields.caps import CapsField def build(options): prefixes_field = AffixesField() suffixes_field = AffixesField() caps_field = CapsField() fields_tuples = [] if options.use_prefixes: fields_tuples.append(('prefixes', prefixes_field)) if options.use_suffixes: fields_tuples.append(('suffixes', suffixes_field)) if options.use_caps: fields_tuples.append(('caps', caps_field)) return fields_tuples def load(path): options = opts.load(path) return build(options) class Caps: all_upper = 'UPPER' # acronyms all_lower = 'LOWER' # normal words first_upper = 'FIRST' # names, titles non_alpha = 'NON_ALPHA' # dates, hours, punctuations other = 'OTHER' # any other def extract_prefixes(words, min_length, max_length): return extract_affixes(words, min_length, max_length, affix_type='prefix') def extract_suffixes(words, min_length, max_length): return extract_affixes(words, min_length, max_length, affix_type='suffix') def extract_affixes(words, min_length, max_length, affix_type='prefix'): total_length = max_length - min_length + 1 pad_token = '<pad-{}>'.format(affix_type) def fill_with_pad(v): for _ in range(total_length - len(v)): v.append(pad_token) new_words = [] for sentence in words: tokens = sentence.split() affixes_tokens = [] for token in tokens: affixes = [] if len(token) >= min_length: i, j = min_length, min(max_length, len(token)) for k in range(i, j + 1): affix = token[:k] if affix_type == 'prefix' else token[-k:] affixes.append(affix) fill_with_pad(affixes) affixes_tokens.extend(affixes) new_words.append(' '.join(affixes_tokens)) return new_words def extract_caps(words): new_words = [] for sentence in words: tokens = sentence.split() caps_tokens = [] for token in tokens: if not token.isalpha(): caps_tokens.append(Caps.non_alpha) elif token.isupper(): caps_tokens.append(Caps.all_upper) elif token.islower(): caps_tokens.append(Caps.all_lower) elif token[0].isupper() and token[1:].islower(): caps_tokens.append(Caps.first_upper) else: caps_tokens.append(Caps.other) new_words.append(caps_tokens) return new_words

[ "marcosvtreviso@gmail.com" ]

marcosvtreviso@gmail.com

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/Python_codes/p03673/s956353086.py

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[]

no_license

Aasthaengg/IBMdataset

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refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

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n = int(input()) a = list(map(int,input().rstrip().split(" "))) b1 = [] b2 = [] ans = [] if n % 2 == 0: for i in range(n): if i % 2 == 0: b1.append(a[i]) else: b2.append(a[i]) b2.reverse() ans = b2 + b1 print(" ".join(str(i) for i in ans)) else: for i in range(n): if i % 2 == 0: b1.append(a[i]) else: b2.append(a[i]) b1.reverse() ans = b1 + b2 print(" ".join(str(i) for i in ans))

[ "66529651+Aastha2104@users.noreply.github.com" ]

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/resolwe/flow/migrations/0015_refactor_relations_1.py

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mzagmajster/resolwe

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refs/heads/master

2022-02-20T05:23:41.953200

2019-08-27T16:36:25

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# -*- coding: utf-8 -*- # Generated by Django 1.11.14 on 2018-08-06 02:13 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('flow', '0014_track_resources'), ] operations = [ migrations.RenameModel( old_name='PositionInRelation', new_name='RelationPartition', ), migrations.RenameField( model_name='relation', old_name='label', new_name='category', ), migrations.AlterField( model_name='relation', name='category', field=models.CharField(default='', max_length=100), preserve_default=False, ), migrations.AddField( model_name='relation', name='unit', field=models.CharField(blank=True, choices=[('s', 'Second'), ('min', 'Minute'), ('hr', 'Hour'), ('d', 'Day'), ('wk', 'Week')], max_length=3, null=True), ), migrations.AlterField( model_name='relation', name='collection', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='flow.Collection'), ), migrations.AlterUniqueTogether( name='relation', unique_together=set([('collection', 'category')]), ), migrations.AddField( model_name='relationpartition', name='label', field=models.CharField(blank=True, db_index=True, max_length=30, null=True), ), migrations.AlterUniqueTogether( name='relationpartition', unique_together=set([('entity', 'relation')]), ), ]

[ "domen@blenkus.com" ]

domen@blenkus.com

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/test/functional/feature_filelock.py

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permissive

devcoin/core

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refs/heads/master

2023-05-25T03:42:03.998451

2023-05-24T07:59:22

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#!/usr/bin/env python3 # Copyright (c) 2018-2020 The Bitcoin Core and Devcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. """Check that it's not possible to start a second devcoind instance using the same datadir or wallet.""" import os import random import string from test_framework.test_framework import DevcoinTestFramework from test_framework.test_node import ErrorMatch class FilelockTest(DevcoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 2 def setup_network(self): self.add_nodes(self.num_nodes, extra_args=None) self.nodes[0].start() self.nodes[0].wait_for_rpc_connection() def run_test(self): datadir = os.path.join(self.nodes[0].datadir, self.chain) self.log.info("Using datadir {}".format(datadir)) self.log.info("Check that we can't start a second devcoind instance using the same datadir") expected_msg = "Error: Cannot obtain a lock on data directory {0}. {1} is probably already running.".format(datadir, self.config['environment']['PACKAGE_NAME']) self.nodes[1].assert_start_raises_init_error(extra_args=['-datadir={}'.format(self.nodes[0].datadir), '-noserver'], expected_msg=expected_msg) if self.is_wallet_compiled(): def check_wallet_filelock(descriptors): wallet_name = ''.join([random.choice(string.ascii_lowercase) for _ in range(6)]) self.nodes[0].createwallet(wallet_name=wallet_name, descriptors=descriptors) wallet_dir = os.path.join(datadir, 'wallets') self.log.info("Check that we can't start a second devcoind instance using the same wallet") if descriptors: expected_msg = "Error: SQLiteDatabase: Unable to obtain an exclusive lock on the database, is it being used by another devcoind?" else: expected_msg = "Error: Error initializing wallet database environment" self.nodes[1].assert_start_raises_init_error(extra_args=['-walletdir={}'.format(wallet_dir), '-wallet=' + wallet_name, '-noserver'], expected_msg=expected_msg, match=ErrorMatch.PARTIAL_REGEX) if self.is_bdb_compiled(): check_wallet_filelock(False) if self.is_sqlite_compiled(): check_wallet_filelock(True) if __name__ == '__main__': FilelockTest().main()

[ "fernando@develcuy.com" ]

fernando@develcuy.com

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/pullenti/ner/booklink/internal/EpNerBooklinkInternalResourceHelper.py

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[]

no_license

MihaJjDa/APCLtask

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refs/heads/master

2020-04-16T17:15:10.846647

2020-02-24T16:06:43

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# Copyright (c) 2013, Pullenti. All rights reserved. Non-Commercial Freeware. # This class is generated using the converter UniSharping (www.unisharping.ru) from Pullenti C#.NET project (www.pullenti.ru). # See www.pullenti.ru/downloadpage.aspx. import io from pullenti.unisharp.Utils import Utils class EpNerBooklinkInternalResourceHelper: """ Это для поддержки получения встроенных ресурсов """ @staticmethod def getBytes(name : str) -> bytearray: """ Получить встроенный ресурс Args: name(str): имя, на который оканчивается ресурс """ # ignored: assembly = EpNerBooklinkInternalResourceHelper. names = Utils.getResourcesNames('pullenti.ner.booklink.properties', '.png') for n in names: if (Utils.endsWithString(n, name, True)): try: inf = Utils.getResourceInfo('pullenti.ner.booklink.properties', n) if (inf is None): continue with Utils.getResourceStream('pullenti.ner.booklink.properties', n) as stream: buf = Utils.newArrayOfBytes(Utils.getLengthIO(stream), 0) Utils.readIO(stream, buf, 0, len(buf)) return buf except Exception as ex: pass return None @staticmethod def getString(name : str) -> str: arr = EpNerBooklinkInternalResourceHelper.getBytes(name) if (arr is None): return None if ((len(arr) > 3 and arr[0] == (0xEF) and arr[1] == (0xBB)) and arr[2] == (0xBF)): return arr[3:3+len(arr) - 3].decode("UTF-8", 'ignore') else: return arr.decode("UTF-8", 'ignore')

[ "danila.puchkin@mail.ru" ]

danila.puchkin@mail.ru

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/sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_feature_set/feature_set_specification_schema.py

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openapi-env-test/azure-sdk-for-python

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MIT

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# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- # pylint: disable=unused-argument,no-self-use from marshmallow import fields, post_load from azure.ai.ml._schema.core.schema import PatchedSchemaMeta class FeatureSetSpecificationSchema(metaclass=PatchedSchemaMeta): path = fields.Str(required=True, allow_none=False) @post_load def make(self, data, **kwargs): from azure.ai.ml.entities._feature_set.feature_set_specification import FeatureSetSpecification return FeatureSetSpecification(**data)

[ "noreply@github.com" ]

openapi-env-test.noreply@github.com

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/vycontrol/config/models.py

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Akmon47/vycontrol

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refs/heads/master

2023-03-29T16:42:03.361002

2021-04-05T07:38:52

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from django.db import models from django.contrib.auth.models import Group class Instance(models.Model): hostname = models.CharField(max_length=120, primary_key=True) alias = models.CharField(max_length=30) port = models.IntegerField() key = models.CharField(max_length=100) https = models.BooleanField() main = models.BooleanField(default=False) group = models.ForeignKey(Group, null=True, on_delete=models.SET_NULL) Group.add_to_class('active', models.BooleanField(default=True))

[ "roberto.berto@gmail.com" ]

roberto.berto@gmail.com

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/wrf_management/modules/compress_cli.py

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[]

no_license

daliagachc/wrf_management

dd88cf5d6279457f4e2b414acfa0d0cbaaad3873

4ee88c668ed0252e68713aa756b74344ecada615

refs/heads/master

2021-06-13T09:39:08.477315

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# project name: wrf_management # created by diego aliaga daliaga_at_chacaltaya.edu.bo # todo still under construction import sys import wrf_management.modules.CompressOut as CO import os zip_path = os.path.join(os.path.dirname(sys.argv[1]),'compresser_log_xxx') input_dic = dict( source_path = sys.argv[1], zip_path = zip_path, db_path = os.path.join(zip_path,f'zip{CO.get_unique_id()}.sqlite'), lock_last_date = False, source_path_is_file = True, compress_level_target = 4 ) if __name__=="__main__": co = CO.Compresser(**input_dic) co.get_and_zip_next_row(move=True)

[ "diego.aliaga@helsinki.fi" ]

diego.aliaga@helsinki.fi

dc44b2f609558f860a5b9afec10dfdf9fedc3d50

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/ScrapeNASAPicDayWebsite/.history/scraper_20190701160044.py

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[]

no_license

web3-qa/intermediatePython

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refs/heads/master

2023-02-08T14:18:54.288227

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import urllib.request import urllib.parse import urljoin from bs4 import BeautifulSoup baseURL = "http://apod.nasa.gov/apod/archivepix.html" content = urllib.request.urlopen(baseURL).read() BeautifulSoup(content, "lxml").findAll("a")

[ "dcolmer@statestreet.com" ]

dcolmer@statestreet.com

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/xacro/geometry_tutorials/turtle_tf2/nodes/dynamic_tf2_broadcaster.py

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[]

no_license

jincheng-ai/ros-melodic-python3-opencv4

b0f4d3860ab7ae3d683ade8aa03e74341eff7fcf

47c74188560c2274b8304647722d0c9763299a4b

refs/heads/main

2023-05-28T17:37:34.345164

2021-06-17T09:59:25

377,856,153

5

0

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#!/usr/bin/env python # Software License Agreement (BSD License) # # Copyright (c) 2008, Willow Garage, Inc. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following # disclaimer in the documentation and/or other materials provided # with the distribution. # * Neither the name of the Willow Garage nor the names of its # contributors may be used to endorse or promote products derived # from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS # FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE # COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, # INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, # BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT # LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN # ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. import rospy import tf2_ros import geometry_msgs.msg import math if __name__ == '__ STATIC main__': rospy.init_node('my_tf2_broadcaster') br = tf2_ros.TransformBroadcaster() t = geometry_msgs.msg.TransformStamped() t.header.frame_id = "turtle1" t.child_frame_id = "carrot1" t.transform.translation.x = 0.0 t.transform.translation.y = 2.0 t.transform.translation.z = 0.0 t.transform.rotation.x = 0.0 t.transform.rotation.y = 0.0 t.transform.rotation.z = 0.0 t.transform.rotation.w = 1.0 rate = rospy.Rate(10.0) while not rospy.is_shutdown(): t.header.stamp = rospy.Time.now() br.sendTransform(t) rate.sleep() if __name__ == '__main__': rospy.init_node('my_tf2_broadcaster') br = tf2_ros.TransformBroadcaster() t = geometry_msgs.msg.TransformStamped() t.header.frame_id = "turtle1" t.child_frame_id = "carrot1" rate = rospy.Rate(10.0) while not rospy.is_shutdown(): x = rospy.Time.now().to_sec() * math.pi t.header.stamp = rospy.Time.now() t.transform.translation.x = 10 * math.sin(x) t.transform.translation.y = 10 * math.cos(x) t.transform.translation.z = 0.0 t.transform.rotation.x = 0.0 t.transform.rotation.y = 0.0 t.transform.rotation.z = 0.0 t.transform.rotation.w = 1.0 br.sendTransform(t) rate.sleep()

[ "shuyuanhao@cetiti.com" ]

shuyuanhao@cetiti.com

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/CoreSource/speechRec.py

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[ "Apache-2.0", "LicenseRef-scancode-unknown-license-reference" ]

permissive

Happy-Egg/redesigned-happiness

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refs/heads/master

2022-12-28T02:40:21.713456

2020-03-03T09:04:30

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2022-12-08T06:19:04

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py

# coding=<encoding name> from aip import AipSpeech # 百度智能云账户参数配置 APP_ID = '17134145' API_KEY = 'yDTW0ljcQd24ZKyaHYRTDleX' SECRET_KEY = 'O6de7NZmhxd6KZILjZj2oHoqITdRoHyg' client = AipSpeech(APP_ID, API_KEY, SECRET_KEY) # 读取文件 def get_file_content(file_path): with open(file_path, 'rb') as fp: return fp.read() # 识别本地文件 def do_tts(file_path, file_format): ret = client.asr(get_file_content(file_path), file_format, 16000, { 'dev_pid': 1537, }) return ret['result'][0].encode('utf-8')

[ "yangyang4910709@163.com" ]

yangyang4910709@163.com

b6dfbdbb85b92e08ea92fb40b6b8d4f6337b17e6

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/sunyata/layer/recurrent/gru.py

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[]

no_license

knighton/sunyata_2017

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refs/heads/master

2021-09-06T13:19:06.341771

2018-02-07T00:28:07

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from ... import backend as Z from ... import init from ..base import LinkBuilder from .base import RecurrentLayer, RecurrentSpec class GRULayer(RecurrentLayer): def __init__(self, forward, last, input_kernel, recurrent_kernel, bias): dim = input_kernel.shape[1] // 3 dtype = input_kernel.dtype.name super().__init__(dim, dtype, forward, last) self.input_kernel = self.add_param(input_kernel) self.recurrent_kernel = self.add_param(recurrent_kernel) self.bias = self.add_param(bias) i = 2 * self.out_dim self.reset_update_input_kernel = self.input_kernel[:, :i] self.reset_update_recurrent_kernel = self.recurrent_kernel[:, :i] self.reset_update_bias = self.bias[:i] self.new_input_kernel = self.input_kernel[:, i:] self.new_recurrent_kernel = self.recurrent_kernel[:, i:] self.new_bias = self.bias[i:] def step(self, x, prev_state, prev_internal_state): gates = Z.sigmoid( Z.matmul(x, self.reset_update_input_kernel) + Z.matmul(prev_state, self.reset_update_recurrent_kernel) + self.reset_update_bias) i = self.out_dim reset_gate = gates[:, :i] update_gate = gates[:, i:2 * i] new_state = Z.tanh( Z.matmul(x, self.new_input_kernel) + Z.matmul(reset_gate * prev_state, self.new_recurrent_kernel) + self.new_bias) state = update_gate * prev_state + (1 - update_gate) * new_state return state, None class GRUSpec(RecurrentSpec): def __init__(self, dim=None, forward=True, last=False, input_kernel_init='glorot_uniform', recurrent_kernel_init='orthogonal', bias_init='zeros'): super().__init__(dim, forward, last) self.input_kernel_init = init.get(input_kernel_init) self.recurrent_kernel_init = init.get(recurrent_kernel_init) self.bias_init = init.get(bias_init) def make_layer(self, in_dim, out_dim, dtype): input_kernel_shape = in_dim, 3 * out_dim input_kernel = self.input_kernel_init( input_kernel_shape, dtype, 'conv_kernel') recurrent_kernel_shape = out_dim, 3 * out_dim recurrent_kernel = self.recurrent_kernel_init( recurrent_kernel_shape, dtype) bias_shape = 3 * out_dim, bias = self.bias_init(bias_shape, dtype) return GRULayer(self.go_forward, self.ret_last, input_kernel, recurrent_kernel, bias) GRU = LinkBuilder(GRUSpec)

[ "iamknighton@gmail.com" ]

iamknighton@gmail.com

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/google-cloud-sdk/.install/.backup/lib/googlecloudsdk/api_lib/compute/networks_utils.py

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KaranToor/MA450

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c98b58aeb0994e011df960163541e9379ae7ea06

refs/heads/master

2021-06-21T06:17:42.585908

2020-12-24T00:36:28

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# Copyright 2015 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Code that's shared between multiple networks subcommands.""" def _GetNetworkMode(network): """Takes a network resource and returns the "mode" of the network.""" if network.get('IPv4Range', None) is not None: return 'legacy' if network.get('autoCreateSubnetworks', False): return 'auto' else: return 'custom' def AddMode(items): for resource in items: resource['x_gcloud_mode'] = _GetNetworkMode(resource) yield resource

[ "toork@uw.edu" ]

toork@uw.edu

aeccd1e46dde4148b0683a43aaf35d79b4119967

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/ue4docker/infrastructure/BuildConfiguration.py

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permissive

hackertron/ue4-docker

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f849ae89f75644c5f34276e8ebe76ef03528029c

refs/heads/master

2020-04-19T22:51:26.502673

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from .PackageUtils import PackageUtils from .WindowsUtils import WindowsUtils import humanfriendly, os, platform, random # Import the `semver` package even when the conflicting `node-semver` package is present semver = PackageUtils.importFile('semver', os.path.join(PackageUtils.getPackageLocation('semver'), 'semver.py')) # The default Unreal Engine git repository DEFAULT_GIT_REPO = 'https://github.com/EpicGames/UnrealEngine.git' # The base images for Linux containers LINUX_BASE_IMAGES = { 'opengl': 'nvidia/opengl:1.0-glvnd-devel-ubuntu18.04', 'cudagl': { '9.2': 'nvidia/cudagl:9.2-devel-ubuntu18.04', '10.0': 'nvidia/cudagl:10.0-devel-ubuntu18.04' } } # The default CUDA version to use when `--cuda` is specified without a value DEFAULT_CUDA_VERSION = '9.2' # The default memory limit (in GB) under Windows DEFAULT_MEMORY_LIMIT = 10.0 class BuildConfiguration(object): def __init__(self, args): ''' Creates a new build configuration based on the supplied arguments object ''' # Determine if we are building a custom version of UE4 rather than an official release if args.release.lower() == 'custom': # Both a custom repository and a custom branch/tag must be specified if args.repo is None or args.branch is None: raise RuntimeError('both a repository and branch/tag must be specified when building a custom version of the Engine') # Use the specified repository and branch/tag self.release = 'custom' self.repository = args.repo self.branch = args.branch else: # Validate the specified version string try: ue4Version = semver.parse(args.release) if ue4Version['major'] != 4 or ue4Version['prerelease'] != None: raise Exception() self.release = semver.format_version(ue4Version['major'], ue4Version['minor'], ue4Version['patch']) except: raise RuntimeError('invalid UE4 release number "{}", full semver format required (e.g. "4.19.0")'.format(args.release)) # Use the default repository and the release tag for the specified version self.repository = DEFAULT_GIT_REPO self.branch = '{}-release'.format(self.release) # Store our common configuration settings self.containerPlatform = 'windows' if platform.system() == 'Windows' and args.linux == False else 'linux' self.dryRun = args.dry_run self.rebuild = args.rebuild self.pullPrerequisites = args.pull_prerequisites self.noEngine = args.no_engine self.noMinimal = args.no_minimal self.noFull = args.no_full self.suffix = args.suffix self.platformArgs = ['--no-cache'] if args.no_cache == True else [] self.baseImage = None self.prereqsTag = None # If we're building Windows containers, generate our Windows-specific configuration settings if self.containerPlatform == 'windows': self._generateWindowsConfig(args) # If we're building Linux containers, generate our Linux-specific configuration settings if self.containerPlatform == 'linux': self._generateLinuxConfig(args) def _generateWindowsConfig(self, args): # Store the path to the directory containing our required Windows DLL files self.defaultDllDir = os.path.join(os.environ['SystemRoot'], 'System32') self.dlldir = args.dlldir if args.dlldir is not None else self.defaultDllDir # Determine base tag for the Windows release of the host system self.hostRelease = WindowsUtils.getWindowsRelease() self.hostBasetag = WindowsUtils.getReleaseBaseTag(self.hostRelease) # Store the tag for the base Windows Server Core image self.basetag = args.basetag if args.basetag is not None else self.hostBasetag self.baseImage = 'microsoft/dotnet-framework:4.7.2-sdk-windowsservercore-' + self.basetag self.prereqsTag = self.basetag # Verify that any user-specified base tag is valid if WindowsUtils.isValidBaseTag(self.basetag) == False: raise RuntimeError('unrecognised Windows Server Core base image tag "{}", supported tags are {}'.format(self.basetag, WindowsUtils.getValidBaseTags())) # Set the memory limit Docker flags if args.m is not None: try: self.memLimit = humanfriendly.parse_size(args.m) / (1000*1000*1000) except: raise RuntimeError('invalid memory limit "{}"'.format(args.m)) else: self.memLimit = DEFAULT_MEMORY_LIMIT if args.random_memory == False else random.uniform(DEFAULT_MEMORY_LIMIT, DEFAULT_MEMORY_LIMIT + 2.0) self.platformArgs.extend(['-m', '{:.2f}GB'.format(self.memLimit)]) # Set the isolation mode Docker flags self.isolation = args.isolation if args.isolation is not None else 'default' if self.isolation != 'default': self.platformArgs.append('-isolation=' + self.isolation) # Set the PDB truncation Docker flags self.keepDebug = args.keep_debug if self.keepDebug == True: self.platformArgs.extend(['--build-arg', 'KEEP_DEBUG=1']) def _generateLinuxConfig(self, args): # Determine if we are building CUDA-enabled container images self.cuda = None if args.cuda is not None: # Verify that the specified CUDA version is valid self.cuda = args.cuda if args.cuda != '' else DEFAULT_CUDA_VERSION if self.cuda not in LINUX_BASE_IMAGES['cudagl']: raise RuntimeError('unsupported CUDA version "{}", supported versions are: {}'.format( self.cuda, ', '.join([v for v in LINUX_BASE_IMAGES['cudagl']]) )) # Use the appropriate base image for the specified CUDA version self.baseImage = LINUX_BASE_IMAGES['cudagl'][self.cuda] self.prereqsTag = 'cudagl{}'.format(self.cuda) else: self.baseImage = LINUX_BASE_IMAGES['opengl'] self.prereqsTag = 'opengl'

[ "adam.rehn@my.jcu.edu.au" ]

adam.rehn@my.jcu.edu.au

c3503b21d2104e0e4b8f3d87ebe23954c6c35551

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/Server.py

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[]

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zhantong/wetwo-server

074facf45695f054855eaff26bd2dc3272a1aba0

7271acc9047da65d647a572160683b043b8163a1

refs/heads/master

2021-08-27T19:41:40.549066

2017-11-28T05:19:50

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from flask import Flask, request, render_template, redirect, jsonify, g import flask_login from WeTwo import WeTwo app = Flask(__name__) app.secret_key = '\xecG>\xc3\xe6\xe5\xbds\xa5\xf1\xae\x81u\x19\xb0`\x88W\xc6\\\xb7\xfeL\xcc' login_manager = flask_login.LoginManager() login_manager.init_app(app) class User(flask_login.UserMixin): pass def get_wetwo(): if not hasattr(g, 'wetwo'): g.wetwo = WeTwo() return g.wetwo @login_manager.user_loader def user_loader(user_id): if not get_wetwo().is_user_id_exists(user_id): return user = User() user.id = user_id return user @app.route('/login', methods=['GET', 'POST']) def login(): if request.method == 'GET': return render_template('login.html') user_name = request.form['name'] password = request.form['password'] if user_name and password and get_wetwo().is_password_correct(user_name=user_name, password=password): user_id = get_wetwo().get_user_id(user_name) user = User() user.id = user_id flask_login.login_user(user) return 'Login Success' return 'Bad Login' @app.route('/api/login', methods=['POST']) def api_login(): user_name = request.form['name'] password = request.form['password'] if user_name and password and get_wetwo().is_password_correct(user_name=user_name, password=password): user_id = get_wetwo().get_user_id(user_name) user = User() user.id = user_id flask_login.login_user(user) return jsonify({'status': True, 'message': '登录成功'}) return jsonify({'status': False, 'message': '登录失败'}) @app.route('/logout') def logout(): flask_login.logout_user() return 'Logged out' @app.route('/api/logout') def api_logout(): flask_login.logout_user() return jsonify({'status': True, 'message': '注销成功'}) @app.route('/') @flask_login.login_required def index(): articles = get_wetwo().get_articles() for article in articles: article['comments'] = get_wetwo().get_comments(article['article_id']) return render_template('index.html', articles=articles) @app.route('/api/getUserInfo') @flask_login.login_required def api_get_user_info(): user_id = flask_login.current_user.id user_name = get_wetwo().get_user_name(user_id) num_unread_notifications = get_wetwo().get_num_unread_comments(user_id) info = { 'id': user_id, 'name': user_name, 'num_unread_notifications': num_unread_notifications } return jsonify(info) @app.route('/api/getAllArticles') @flask_login.login_required def api_get_all_articles(): offset = request.args['offset'] if 'offset' in request.args else 0 limit = request.args['limit'] if 'limit' in request.args else 20 articles = get_wetwo().get_articles(offset=offset, limit=limit) for article in articles: article['comments'] = get_wetwo().get_comments(article['article_id']) return jsonify(articles) @app.route('/api/getArticles') @flask_login.login_required def api_get_articles(): user_id = flask_login.current_user.id articles = get_wetwo().get_articles(user_id) for article in articles: article['comments'] = get_wetwo().get_comments(article['article_id']) return jsonify(articles) @app.route('/api/getArticle') @flask_login.login_required def api_get_article(): article_id = request.args['articleId'] article = get_wetwo().get_article(article_id) article['comments'] = get_wetwo().get_comments(article['article_id']) return jsonify(article) @app.route('/postArticle', methods=['POST']) @flask_login.login_required def post_article(): article = request.form['article'] user_id = flask_login.current_user.id article_id = get_wetwo().post_article(article, user_id) return redirect('/') @app.route('/api/postArticle', methods=['POST']) @flask_login.login_required def api_post_article(): article = request.form['article'] time = request.form['time'] if 'time' in request.form else None user_id = flask_login.current_user.id article_id = get_wetwo().post_article(article, user_id, time) return jsonify({'status': True, 'articleId': article_id}) @app.route('/postComment', methods=['POST']) @flask_login.login_required def post_comment(): article_id = request.form['articleId'] comment = request.form['comment'] parent_comment_id = request.form['parentCommentId'] user_id = flask_login.current_user.id get_wetwo().post_comment(article_id, user_id, comment, parent_comment_id) article = get_wetwo().get_article(article_id) article['comments'] = get_wetwo().get_comments(article_id) return render_template('comment.html', article=article) @app.route('/api/postComment', methods=['POST']) @flask_login.login_required def api_post_comment(): article_id = request.form['articleId'] comment = request.form['comment'] parent_comment_id = request.form['parentCommentId'] time = request.form['time'] if 'time' in request.form else None user_id = flask_login.current_user.id if 'userId' not in request.form else request.form['userId'] comment_id = get_wetwo().post_comment(article_id, user_id, comment, parent_comment_id, time) return jsonify({'status': True, 'commentId': comment_id}) @app.route('/api/getUnreadComments') @flask_login.login_required def api_get_unread_comments(): user_id = flask_login.current_user.id comments = get_wetwo().get_unread_comments(user_id) return jsonify(comments) @app.route('/api/setCommentRead', methods=['POST']) @flask_login.login_required def api_set_comment_read(): comment_id = request.form['commentId'] get_wetwo().set_comment_read(comment_id) return jsonify({'status': True}) @app.route('/protected') @flask_login.login_required def protected(): return 'Logged in as: ' + flask_login.current_user.id @app.teardown_appcontext def teardown_appcontext(error): if hasattr(g, 'wetwo'): del g.wetwo if __name__ == '__main__': app.run(host='0.0.0.0', debug=True)

[ "zhantong1994@163.com" ]

zhantong1994@163.com

2f6b30e1b2d944c0354a536d1c08f9eff2fa2e31

867846ed1df7f560ccc473413a70020155f66ad4

/fixMarkdownHeadings.py

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[]

no_license

abhineet123/PTF

84297bf5aa95320dbc2d34f422f2dd563ff65a58

0c63f7f8251af0d70c329b2cef53694db76c1656

refs/heads/master

2023-08-18T18:34:40.513936

2023-08-09T17:28:51

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import pyperclip from Tkinter import Tk from anytree import Node, RenderTree def findChildren(_headings, root_level, _start_id, _root_node, n_headings): nodes = [] _id = _start_id while _id < n_headings: _heading, line_id = _headings[_id] words = _heading.split(' ') curr_level = words[0].count('#') if curr_level <= root_level: break heading_words = [] for word in words[1:]: if word.startswith('@'): break if word and not word.isspace(): heading_words.append(word) parent_text = '' if _root_node is not None and _root_node.parent is not None: parent_text = _root_node.name if curr_level > 2: # parent_text = str(_root_node) parent_text = '{}/{}'.format(parent_text, _root_node.parent_text) heading_text = '_'.join(heading_words) new_node = Node(heading_text, parent=_root_node, orig_text=_heading, parent_text=parent_text, marker=words[0], line_id=line_id) nodes.append(new_node) child_nodes, ___id = findChildren(_headings, curr_level, _id + 1, new_node, n_headings) nodes += child_nodes _id = ___id return nodes, _id def main(): in_txt = Tk().clipboard_get() lines = in_txt.split('\n') lines = [line for line in lines] start_t = None curr_t = None curr_root = Node("root_node") headings = [(k, i) for i, k in enumerate(lines) if k.startswith('#')] n_headings = len(headings) heading_id = 0 level = 0 nodes, _ = findChildren(headings, 0, 0, curr_root, n_headings) print(RenderTree(curr_root)) # out_txt = in_txt for node in nodes: if node.is_root or node.parent.is_root: continue orig_text = node.orig_text new_text = '{} {} @ {}'.format(node.marker, node.name, node.parent_text) lines[node.line_id] = new_text print('{}: new_text: {}'.format(node, new_text)) # out_txt = out_txt.replace(orig_text + '\n', new_text) out_txt = '\n'.join(lines) # print(out_txt) # with open(out_fname, 'w') as out_fid: # out_fid.write(out_txt) try: pyperclip.copy(out_txt) spam = pyperclip.paste() except pyperclip.PyperclipException as e: print('Copying to clipboard failed: {}'.format(e)) if __name__ == '__main__': main()

[ "asingh1@ualberta.ca" ]

asingh1@ualberta.ca

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/pa65DgwG5HMbtf6iY_17.py

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[]

no_license

daniel-reich/ubiquitous-fiesta

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9af2700dbe59284f5697e612491499841a6c126f

refs/heads/master

2023-04-05T06:40:37.328213

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class player(): def __init__(self, name, age, height, weight): self.name = name self.age = age self.height = height self.weight = weight def get_age(self): return self.name + " is age " + str(self.age) def get_height(self): return self.name + " is " + str(self.height) + "cm" def get_weight(self): return self.name + " weighs " + str(self.weight) + "kg"

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

daniel.reich@danielreichs-MacBook-Pro.local

f92344a7b55176c215b569cd01d99ec9c4fd8ee9

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/stock_scraper/Indicators/RSI.py

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[ "MIT" ]

permissive

webclinic017/Stock-Analysis

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eea8cb5bcb635f12eb15ac13306ef16e2892cd92

refs/heads/master

2022-04-13T00:20:54.287730

2020-03-29T21:05:22

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import sys from os import path sys.path.append( path.dirname( path.dirname( path.abspath(__file__) ) ) ) import pandas as pd class kRSI(): def __init__(self): #do nothing print "In kRSI class" def CalculateRSI(self, avgGain, avgLoss): if avgLoss == 0: return 100 rs = avgGain / abs(avgLoss) rsi = 100 - ( 100 / ( 1 + rs)) return rsi def Calculate(self, dataFrame): ##### ALGORITHM ##### # 100 # RSI = 100 - -------- # 1 + RS # RS = Average Gain / Average Loss # The very first calculations for average gain and average loss are simple 14-period averages. # First Average Gain = Sum of Gains over the past 14 periods / 14. # First Average Loss = Sum of Losses over the past 14 periods / 14 # The second, and subsequent, calculations are based on the prior averages and the current gain loss: # Average Gain = [(previous Average Gain) x 13 + current Gain] / 14. # Average Loss = [(previous Average Loss) x 13 + current Loss] / 14. close = dataFrame['Close'] change = close.diff() change = change.fillna(0) firstAvgGain = 0 firstAvgLoss = 0 rsiSeries = pd.Series() for i in range(14): # Appending first 14 dummy value to RSI series rsiSeries = rsiSeries.append(pd.Series({dataFrame.index[i]: 0})) if change[i]>0: firstAvgGain = firstAvgGain + change[i] else: firstAvgLoss = firstAvgLoss + change[i] firstAvgGain = firstAvgGain/14 firstAvgLoss = firstAvgLoss/14 rsiValue = self.CalculateRSI(firstAvgGain, firstAvgLoss) rsiSeries[13] = rsiValue avgGain = firstAvgGain; avgLoss = firstAvgLoss for i in range(14, close.count()): if change[i]>0: avgGain = ((avgGain * 13) + change[i]) / 14 else: avgLoss = ((avgLoss * 13) + change[i]) / 14 rsiValue = self.CalculateRSI(avgGain, avgLoss) rsiSeries = rsiSeries.append(pd.Series({dataFrame.index[i]: rsiValue})) #print rsiSeries return rsiSeries

[ "singhanurag50@gmail.com" ]

singhanurag50@gmail.com

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/data/p3BR/R1/benchmark/startQiskit_Class245.py

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[ "BSD-3-Clause" ]

permissive

UCLA-SEAL/QDiff

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d968cbc47fe926b7f88b4adf10490f1edd6f8819

refs/heads/main

2023-08-05T04:52:24.961998

2021-09-19T02:56:16

405,159,939

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# qubit number=3 # total number=46 import numpy as np from qiskit import QuantumCircuit, execute, Aer, QuantumRegister, ClassicalRegister, transpile, BasicAer, IBMQ from qiskit.visualization import plot_histogram from typing import * from pprint import pprint from math import log2 from collections import Counter from qiskit.test.mock import FakeVigo, FakeYorktown kernel = 'circuit/bernstein' def bitwise_xor(s: str, t: str) -> str: length = len(s) res = [] for i in range(length): res.append(str(int(s[i]) ^ int(t[i]))) return ''.join(res[::-1]) def bitwise_dot(s: str, t: str) -> str: length = len(s) res = 0 for i in range(length): res += int(s[i]) * int(t[i]) return str(res % 2) def build_oracle(n: int, f: Callable[[str], str]) -> QuantumCircuit: # implement the oracle O_f # NOTE: use multi_control_toffoli_gate ('noancilla' mode) # https://qiskit.org/documentation/_modules/qiskit/aqua/circuits/gates/multi_control_toffoli_gate.html # https://quantumcomputing.stackexchange.com/questions/3943/how-do-you-implement-the-toffoli-gate-using-only-single-qubit-and-cnot-gates # https://quantumcomputing.stackexchange.com/questions/2177/how-can-i-implement-an-n-bit-toffoli-gate controls = QuantumRegister(n, "ofc") target = QuantumRegister(1, "oft") oracle = QuantumCircuit(controls, target, name="Of") for i in range(2 ** n): rep = np.binary_repr(i, n) if f(rep) == "1": for j in range(n): if rep[j] == "0": oracle.x(controls[j]) oracle.mct(controls, target[0], None, mode='noancilla') for j in range(n): if rep[j] == "0": oracle.x(controls[j]) # oracle.barrier() # oracle.draw('mpl', filename=(kernel + '-oracle.png')) return oracle def build_circuit(n: int, f: Callable[[str], str]) -> QuantumCircuit: # implement the Bernstein-Vazirani circuit zero = np.binary_repr(0, n) b = f(zero) # initial n + 1 bits input_qubit = QuantumRegister(n+1, "qc") classicals = ClassicalRegister(n, "qm") prog = QuantumCircuit(input_qubit, classicals) # inverse last one (can be omitted if using O_f^\pm) prog.x(input_qubit[n]) # circuit begin prog.h(input_qubit[1]) # number=1 prog.rx(-0.09738937226128368,input_qubit[2]) # number=2 prog.h(input_qubit[1]) # number=33 prog.cz(input_qubit[2],input_qubit[1]) # number=34 prog.h(input_qubit[1]) # number=35 prog.h(input_qubit[1]) # number=3 # apply H to get superposition for i in range(n): prog.h(input_qubit[i]) prog.h(input_qubit[n]) prog.barrier() # apply oracle O_f oracle = build_oracle(n, f) prog.append( oracle.to_gate(), [input_qubit[i] for i in range(n)] + [input_qubit[n]]) # apply H back (QFT on Z_2^n) for i in range(n): prog.h(input_qubit[i]) prog.barrier() # measure return prog def get_statevector(prog: QuantumCircuit) -> Any: state_backend = Aer.get_backend('statevector_simulator') statevec = execute(prog, state_backend).result() quantum_state = statevec.get_statevector() qubits = round(log2(len(quantum_state))) quantum_state = { "|" + np.binary_repr(i, qubits) + ">": quantum_state[i] for i in range(2 ** qubits) } return quantum_state def evaluate(backend_str: str, prog: QuantumCircuit, shots: int, b: str) -> Any: # Q: which backend should we use? # get state vector quantum_state = get_statevector(prog) # get simulate results # provider = IBMQ.load_account() # backend = provider.get_backend(backend_str) # qobj = compile(prog, backend, shots) # job = backend.run(qobj) # job.result() backend = Aer.get_backend(backend_str) # transpile/schedule -> assemble -> backend.run results = execute(prog, backend, shots=shots).result() counts = results.get_counts() a = Counter(counts).most_common(1)[0][0][::-1] return { "measurements": counts, # "state": statevec, "quantum_state": quantum_state, "a": a, "b": b } def bernstein_test_1(rep: str): """011 . x + 1""" a = "011" b = "1" return bitwise_xor(bitwise_dot(a, rep), b) def bernstein_test_2(rep: str): """000 . x + 0""" a = "000" b = "0" return bitwise_xor(bitwise_dot(a, rep), b) def bernstein_test_3(rep: str): """111 . x + 1""" a = "111" b = "1" return bitwise_xor(bitwise_dot(a, rep), b) if __name__ == "__main__": n = 2 a = "11" b = "1" f = lambda rep: \ bitwise_xor(bitwise_dot(a, rep), b) prog = build_circuit(n, f) sample_shot =4000 writefile = open("../data/startQiskit_Class245.csv", "w") # prog.draw('mpl', filename=(kernel + '.png')) backend = BasicAer.get_backend('statevector_simulator') circuit1 = transpile(prog, FakeYorktown()) circuit1.h(qubit=2) circuit1.x(qubit=3) info = execute(circuit1,backend=backend, shots=sample_shot).result().get_counts() print(info, file=writefile) print("results end", file=writefile) print(circuit1.depth(), file=writefile) print(circuit1, file=writefile) writefile.close()

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import matplotlib.pyplot as plt import numpy as np import itertools def plot_confusion_matrix(cm, classes, normalize=False, title='Confusion matrix', cmap=plt.cm.Blues): """ This function prints and plots the confusion matrix. Normalization can be applied by setting `normalize=True`. """ plt.imshow(cm, interpolation='nearest', cmap=cmap) plt.title(title) plt.colorbar() tick_marks = np.arange(len(classes)) plt.xticks(tick_marks, classes, rotation=45) plt.yticks(tick_marks, classes) if normalize: cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis] thresh = cm.max() / 2. for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])): plt.text(j, i, cm[i, j], horizontalalignment="center", color="white" if cm[i, j] > thresh else "black") plt.tight_layout() plt.ylabel('True label') plt.xlabel('Predicted label')

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from PIL import Image import sys sys.path.append('/path/to/dir') import json import pyocr import pyocr.builders tools = pyocr.get_available_tools() if len(tools) == 0: print("No OCR tool found") sys.exit(1) tool = tools[0] print("Will use tool '%s'" % (tool.get_name())) langs = tool.get_available_languages() print("Available languages: %s" % ", ".join(langs)) builder = pyocr.builders.TextBuilder() builder = pyocr.tesseract.CharBoxBuilder() builder = pyocr.builders.LineBoxBuilder() # tesseract_layout=6 with open('../docs/iiif/amami/manifest.json') as f: df = json.load(f) canvases = df["sequences"][0]["canvases"] members = [] for i in range(len(canvases)): page = str(i+1).zfill(4) canvas = canvases[i] canvas_id = canvas["@id"] image_url = canvas["images"][0]["resource"]["@id"] filename = image_url.split("/")[-1] im_path = "../docs/files/large/"+filename char_boxes = tool.image_to_string( Image.open(im_path), lang='jpn_vert', builder=builder ) # print(char_boxes) im = Image.open(im_path) for j in range(len(char_boxes)): box = char_boxes[j] # box.position は左下を原点とした ((min-x, min-y), (max-x, max-y)) らしい。 # ここでは左上を原点とした x, y, width, height に変換してみる x = box.position[0][0] y = im.height - box.position[1][1] width = box.position[1][0] - x height = im.height - box.position[0][1] - y text = box.content.replace(" ", "") print("\t".join([ text, # 文字 str(x), str(y), str(width), str(height), # 確信度 str(box.confidence), ])) if text == "": continue member_id = canvas_id+"#xywh="+str(x)+","+str(y)+","+str(width)+","+str(height) member = { "label": "Page "+page+"_"+str(j+1), "metadata": [ { "label": "Annotation", "value": [ { "on": member_id, "resource": { "@type": "cnt:ContentAsText", "chars": text, "marker": { "text": text, }, "format": "text/html" }, "motivation": "sc:painting", "@id": "http://codh.rois.ac.jp/char-shape/book/200003803/annotation/"+"Page "+page+"_"+str(j+1), "@type": "oa:Annotation" } ] } ], "@id": member_id, "@type": "sc:Canvas" } members.append(member) break curation = { "@context": [ "http://iiif.io/api/presentation/2/context.json", "http://codh.rois.ac.jp/iiif/curation/1/context.json" ], "@type": "cr:Curation", "@id": "https://mp.ex.nii.ac.jp/api/curation/json/aaa5d585-3cd2-4651-ba98-71769b028e19", "label": "Curating list", "selections": [ { "@id": "https://mp.ex.nii.ac.jp/api/curation/json/aaa5d585-3cd2-4651-ba98-71769b028e19/range1", "@type": "sc:Range", "label": "Manual curation by IIIF Curation Viewer", "members": members, "within": { "@id": "https://raw.githubusercontent.com/nakamura196/amami/master/docs/iiif/amami/manifest.json", "@type": "sc:Manifest", "label": "奄美大島" } } ] } fw = open("../docs/curation/test_line.json", 'w') json.dump(curation, fw, ensure_ascii=False, indent=4, sort_keys=True, separators=(',', ': '))

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from .act import * # noqa from .config import * # noqa from .encoder import * # noqa from .head import * # noqa from .layer import * # noqa from .loader import * # noqa from .loss import * # noqa from .network import * # noqa from .optimizer import * # noqa from .pooling import * # noqa from .stage import * # noqa from .train import * # noqa from .transform import * # noqa

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n = int(input()) boxes = [int(_) for _ in input().split()] dp = [1 for _ in range(n)] # 최장증가수열 문제 # dp[i] : i에서 끝나는 최장증가수열 answer = 1 for i in range(0, n): for j in range(0, i): if boxes[i] > boxes[j] and dp[i] < dp[j]+1: dp[i] = dp[j] + 1 if dp[i] > answer: answer = dp[i] print(answer)

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phaustin/parallel_project

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#http://blog.thumbtack.net/python-coroutines/ def coroutine(f): def wrapper(*arg, **kw): c = f(*arg, **kw) c.send(None) return c return wrapper @coroutine def logger(prefix="", next=None): while True: message = yield print("{0}: {1}".format(prefix, message)) if next: next.send(message) @coroutine def cache_checker(cache, onsuccess=None, onfail=None): while True: request = yield if request in cache and onsuccess: onsuccess.send(cache[request]) elif onfail: onfail.send(request) @coroutine def load_balancer(*workers): while True: for worker in workers: request = yield worker.send(request) @coroutine def worker(cache, response, next=None): while True: request = yield cache[request] = response if next: next.send(response) cache = {} response_logger = logger("Response") cluster = load_balancer( logger("Worker 1", worker(cache, 1, response_logger)), logger("Worker 2", worker(cache, 2, response_logger)), logger("Worker 3", worker(cache, 3, response_logger)), ) cluster = cache_checker(cache, response_logger, cluster) cluster = logger("Request", cluster) if __name__ == "__main__": from random import randint for i in range(20): cluster.send(randint(1, 5))

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Miker69/Landing_telebot

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""" WSGI config for Landing project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'Landing.settings') application = get_wsgi_application()

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hamko/sample

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#!/home/hamko/git/sample/chainerrl/TicTacToe/env/bin/python3 # -*- coding: utf-8 -*- import re import sys from wheel.tool import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())

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from collections import deque class Solution: # @param A : tuple of integers # @param B : integer # @return a list of integers def slidingMaximum(self, a, k): q=deque() for i in range(k): if(len(q)==0 or a[q[-1]]>=a[i]): q.append(i) else: while(len(q)!=0 and a[q[-1]]<a[i]): q.pop() q.append(i) ans=[] ans.append(a[q[0]]) for i in range(k,len(a)): if(len(q)==0 or a[q[-1]]>=a[i]): q.append(i) else: while(len(q)!=0 and a[q[-1]]<a[i]): q.pop() q.append(i) while(len(q)!=0 and q[0]<=i-k): q.popleft() ans.append(a[q[0]]) return ans """ Sliding Window Maximum Problem Description Given an array of integers A. There is a sliding window of size B which is moving from the very left of the array to the very right. You can only see the B numbers in the window. Each time the sliding window moves rightwards by one position. You have to find the maximum for each window. Return an array C, where C[i] is the maximum value in the array from A[i] to A[i+B-1]. Refer to the given example for clarity. NOTE: If B > length of the array, return 1 element with the max of the array. Problem Constraints 1 <= |A|, B <= 106 Input Format The first argument given is the integer array A. The second argument given is the integer B. Output Format Return an array C, where C[i] is the maximum value of from A[i] to A[i+B-1]. Example Input Input 1: A = [1, 3, -1, -3, 5, 3, 6, 7] B = 3 Input 2: A = [1, 2, 3, 4, 2, 7, 1, 3, 6] B = 6 Example Output Output 1: [3, 3, 5, 5, 6, 7] Output 2: [7, 7, 7, 7] Example Explanation Explanation 1: Window position | Max --------------------|------- [1 3 -1] -3 5 3 6 7 | 3 1 [3 -1 -3] 5 3 6 7 | 3 1 3 [-1 -3 5] 3 6 7 | 5 1 3 -1 [-3 5 3] 6 7 | 5 1 3 -1 -3 [5 3 6] 7 | 6 1 3 -1 -3 5 [3 6 7] | 7 Explanation 2: Window position | Max --------------------|------- [1 2 3 4 2 7] 1 3 6 | 7 1 [2 3 4 2 7 1] 3 6 | 7 1 2 [3 4 2 7 1 3] 6 | 7 1 2 3 [4 2 7 1 3 6] | 7 """

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# -*- coding: utf-8 -*- # Part of BrowseInfo. See LICENSE file for full copyright and licensing details. from datetime import datetime, timedelta from odoo import models, api, fields from logging import getLogger _logger = getLogger(__name__) class bono(models.TransientModel): _inherit = "account.wizard.generacion.txtfile" @api.multi def print_bono2(self): VAR = 0 VAR2 = 0 concepto2 = self.concepto.upper() totalpago = 0 if self.bancose == 'activo': # /////////////////////////////Creacion del archivo .txt en carpeta local odoo/////////////////////////////////// file = open("archivo.txt", "w") # /////////7////////calculos y ceacion de datos para el .txt///////////////////////////////////////////////////// self.invoices = self.env['hr.payslip'].search( [('date_to', '<=', self.date_to), ('date_from', '>=', self.date_from)]) _logger.info("\n\n\n {} \n\n\n".format(self.invoices)) date_f = str(self.date_imp) a = date_f[0:4] m = date_f[5:7] d = date_f[8:] #saco el encabezado for invoice in self.invoices: # traigo el numero de cuenta cuenta = invoice.employee_id.account_number_2 if cuenta: filtro = cuenta[0:4] else: filtro = '1234' if filtro == '0171': VAR2 += 1 for n in invoice.line_ids: #varsuma = n.total #varsuma = float("{0:.2f}".format(varsuma)).. totalpago += n.total totalpago = float("{0:.2f}".format(totalpago)) totalpago = str(totalpago) for i in range(0, len(totalpago)): if (totalpago[i] == '.'): cds = totalpago[i + 1:] if len(cds) == 2: ceroextra = '0' imprimir0 = '' else: ceroextra = '' imprimir0 = '0' #escribo en el txt totalpago = totalpago.replace(".", ",") lineas = ['H', ';', VAR2, ';', totalpago, imprimir0, ';', concepto2, ';', self.nlote, ';', d,m,a] for l in lineas: file.write(str(l)) file.write('\n') for invoice in self.invoices: # traigo el numero de cuenta cuenta = invoice.employee_id.account_number_2 if cuenta: filtro = cuenta[0:4] else: filtro = '1234' if filtro == '0171': letra = invoice.employee_id.nationality ncedu = invoice.employee_id.identification_id_2 catcedu = len(ncedu) if catcedu == 7: catce = '00' if catcedu == 8: catce = '0' # catce, es los ceros que se agregan antes de la cedula # ncedu, es el numero de cedula # calculo del monto total de nomina busqueda = self.env['hr.salary.rule.category'].search([('id', '!=', 0)]) if busqueda: for a in busqueda: if a.name == 'Net': ttotal = a.id busqueda2 = self.env['hr.payslip.line'].search([('id', '!=', 0)]) for vip in invoice.line_ids: for vip2 in busqueda2: if vip == vip2: if vip2.category_id.id == ttotal: totalpago = vip2.total totalpago = float("{0:.2f}".format(totalpago)) totalpago = str(totalpago) for i in range(0, len(totalpago)): if (totalpago[i] == '.'): cds = totalpago[i + 1:] if len(cds) == 2: ceroextra = '0' imprimir0 = '' else: ceroextra = '' imprimir0 = '0' totalpago = totalpago.replace(".", ",") VAR += 1 # imprimo en el txt lineas = ['P', ';', letra, catce, ncedu, ';', totalpago, imprimir0, ';', concepto2, ';', VAR, ';', '000' ] for l in lineas: file.write(str(l)) file.write('\n') file.close() nombretxt = 'CargaMasivadepagodeNómina.txt' nameclass = 'account.wizard.generacion.txtfile' return self.imprimir_txt(nombretxt,nameclass)

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from typing import List """ 1. First, create a graph (adjacency list) connecting all emails that are related to the same account 2. Second, keep track of the account name for each unique email 3. Find connected components in the graph: a. Each connected component refers to the same account. b. So, all unique emails in a connected component belong to the same account. Hence, sorting them gives the answer - Use DFS to traverse the graph and find the connected components """ from collections import defaultdict class Solution: def accountsMerge(self, accounts: List[List[str]]) -> List[List[str]]: if not accounts: return [] emailToName = dict() # The adj list will contain all emails connected to each email from all the accounts adj_list = defaultdict(set) visited = set() for account in accounts: name = account[0] for email in account[1:]: first_email = account[1] adj_list[first_email].add(email) adj_list[email].add(first_email) emailToName[email] = name def dfs(email): visited.add(email) stack = [email] components = [email] while len(stack) > 0: email = stack.pop() for neighbor in adj_list[email]: if neighbor in visited: continue # Add the neighbor to the stack stack.append(neighbor) components.append(neighbor) visited.add(neighbor) return components # We need to run DFS from each email and see how many connected components are present result = [] for email in adj_list: if email in visited: continue components = dfs(email) result.append([emailToName[email]] + sorted(components)) return result

[ "ashiz2013@gmail.com" ]

ashiz2013@gmail.com

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67416177cd9e221db0b20332c02dcc7680fcdd0e

/이것이 취업을 위한 코딩 테스트다/Chapter05_DFS_BFS/Q04_S.py

0e89d038a59dde7bce9a39cb6bf567d78488ff5a

[]

no_license

svclaw2000/Algorithm

4fe5e3bf50888b974df4f3d87387a003b5249352

b6d92cf0d18997e9e973d5f731ecb44a7935d93a

refs/heads/main

2023-06-21T21:50:13.089719

2021-07-11T14:18:47

363,825,838

0

null

UTF-8

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py

from collections import deque N, M = map(int, input().split()) maze = [list(map(int, input())) for _ in range(N)] ds = ((-1, 0), (0, 1), (1, 0), (0, -1)) def dfs(x, y): queue = deque() queue.append((x, y)) while queue: x, y = queue.popleft() for dx, dy in ds: nx, ny = x + dx, y + dy if not 0 <= nx < N or not 0 <= ny < M or maze[nx][ny] == 0: # 범위 벗어나거나 괴물이면 무시 continue if maze[nx][ny] == 1: # 최초 방문(거리 1) 시 최단거리 저장 및 다른 곳 탐색 maze[nx][ny] = maze[x][y] + 1 queue.append((nx, ny)) return maze[-1][-1] print(dfs(0, 0))

[ "svclaw2000@gmail.com" ]

svclaw2000@gmail.com

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556db265723b0cc30ad2917442ed6dad92fd9044

/tensorflow/python/profiler/profiler_v2_test.py

42fbeba1e98be36f2c2c401a3db60bfbe1f1b5a8

[ "MIT", "Apache-2.0", "BSD-2-Clause" ]

permissive

graphcore/tensorflow

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085b20a4b6287eff8c0b792425d52422ab8cbab3

refs/heads/r2.6/sdk-release-3.2

2023-07-06T06:23:53.857743

2023-03-14T13:04:04

2023-03-14T13:48:43

162,717,602

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17

Apache-2.0

2023-03-25T01:13:37

2018-12-21T13:30:38

C++

UTF-8

Python

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py

# Copyright 2020 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Tests for tf 2.x profiler.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import socket from tensorflow.python.eager import test from tensorflow.python.framework import constant_op from tensorflow.python.framework import errors from tensorflow.python.framework import test_util from tensorflow.python.platform import gfile from tensorflow.python.profiler import profiler_v2 as profiler from tensorflow.python.profiler import trace class ProfilerTest(test_util.TensorFlowTestCase): def test_profile_exceptions(self): logdir = self.get_temp_dir() profiler.start(logdir) with self.assertRaises(errors.AlreadyExistsError): profiler.start(logdir) profiler.stop() with self.assertRaises(errors.UnavailableError): profiler.stop() # Test with a bad logdir, and it correctly raises exception and deletes # profiler. # pylint: disable=anomalous-backslash-in-string profiler.start('/\/\/:123') # pylint: enable=anomalous-backslash-in-string with self.assertRaises(Exception): profiler.stop() profiler.start(logdir) profiler.stop() def test_save_profile(self): logdir = self.get_temp_dir() profiler.start(logdir) with trace.Trace('three_times_five'): three = constant_op.constant(3) five = constant_op.constant(5) product = three * five self.assertAllEqual(15, product) profiler.stop() file_list = gfile.ListDirectory(logdir) self.assertEqual(len(file_list), 2) for file_name in gfile.ListDirectory(logdir): if gfile.IsDirectory(os.path.join(logdir, file_name)): self.assertEqual(file_name, 'plugins') else: self.assertTrue(file_name.endswith('.profile-empty')) profile_dir = os.path.join(logdir, 'plugins', 'profile') run = gfile.ListDirectory(profile_dir)[0] hostname = socket.gethostname() overview_page = os.path.join(profile_dir, run, hostname + '.overview_page.pb') self.assertTrue(gfile.Exists(overview_page)) input_pipeline = os.path.join(profile_dir, run, hostname + '.input_pipeline.pb') self.assertTrue(gfile.Exists(input_pipeline)) tensorflow_stats = os.path.join(profile_dir, run, hostname + '.tensorflow_stats.pb') self.assertTrue(gfile.Exists(tensorflow_stats)) kernel_stats = os.path.join(profile_dir, run, hostname + '.kernel_stats.pb') self.assertTrue(gfile.Exists(kernel_stats)) trace_file = os.path.join(profile_dir, run, hostname + '.trace.json.gz') self.assertTrue(gfile.Exists(trace_file)) def test_profile_with_options(self): logdir = self.get_temp_dir() options = profiler.ProfilerOptions( host_tracer_level=3, python_tracer_level=1) profiler.start(logdir, options) with trace.Trace('three_times_five'): three = constant_op.constant(3) five = constant_op.constant(5) product = three * five self.assertAllEqual(15, product) profiler.stop() file_list = gfile.ListDirectory(logdir) self.assertEqual(len(file_list), 2) def test_context_manager_with_options(self): logdir = self.get_temp_dir() options = profiler.ProfilerOptions( host_tracer_level=3, python_tracer_level=1) with profiler.Profile(logdir, options): with trace.Trace('three_times_five'): three = constant_op.constant(3) five = constant_op.constant(5) product = three * five self.assertAllEqual(15, product) file_list = gfile.ListDirectory(logdir) self.assertEqual(len(file_list), 2) if __name__ == '__main__': test.main()

[ "gardener@tensorflow.org" ]

gardener@tensorflow.org

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c7cebec6209866b02ee654cffeafe0f2cf0646f1

/implementation/oceangame.py

8c2fcb4e93ffdc7cf0b2c1af8292a4326c4b7a2d

[]

no_license

dondon17/algorithm

5492cf039a96ecf5a944816bdca9b5755e5a2623

da4d6ca1c21c31c6521a62b38855e0b9cf4b0d91

refs/heads/master

2023-05-02T14:54:35.185914

2021-05-30T07:31:40

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n, m = map(int, input().split()) x, y, _dir = map(int, input().split()) check = [[0]*m for _ in range(n)] # 0으로 채워진 n * m 행렬 생성 check[x][y] = 1 # 시작 위치 방문 처리 _map = [] for i in range(n): _map.append(list(map(int, input().split()))) count = 1 turn_time = 0 # 4방이 이미 방문한 곳이거나 바다인 경우를 체크하기 위함 dx = [-1, 0, 1, 0] dy = [0, 1, 0, -1] def turnleft(): global _dir _dir -= 1 if _dir == -1: _dir = 3 while True: turnleft() nx = x + dx[_dir] ny = y + dy[_dir] if check[nx][ny] == 0 and _map[nx][ny] == 0: check[nx][ny] = 1 x, y = nx, ny count += 1 turn_time = 0 continue else: turn_time+=1 if turn_time == 4: nx = x-dx[_dir] ny = y-dy[_dir] if _map[nx][ny] == 0: x, y = nx, ny else: break turn_time = 0 print(count)

[ "qwerqw889@ajou.ac.kr" ]

qwerqw889@ajou.ac.kr

f45b44a0ce075baa3867c855c1d857223d4631c4

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/algorithm/algorithm_week/week3/problem_3.py

1dfac10225edd5d46d7a5f1b0aee2c62ba86901b

[]

no_license

websvey1/TIL

aa86c1b31d3efc177df45503d705b3e58b800f8e

189e797ba44e2fd22a033d1024633f9e0128d5cf

refs/heads/master

2023-01-12T10:23:45.677578

2019-12-09T07:26:59

162,102,142

0

1

null

2022-12-11T16:31:08

2018-12-17T08:57:58

Python

UTF-8

Python

false

498

py

import sys sys.stdin = open("problem_3.txt", "r") T = int(input()) for tc in range(1, T+1): comp = input() total = input() len_comp = len(comp) len_total = len(total) empty_list = [0] * len_comp result = 0 # print(empty_list) for i in range(len_comp): for j in range(len_total): if total[j] == comp[i]: empty_list[i] += 1 result = max(empty_list) print(f'#{tc} {result}') ##################### dict 사용해보기

[ "websvey1@gmail.com" ]

websvey1@gmail.com

d4263f84ee75cfae0c1c0448bd6e638c64abaaec

f68e0b205bd3eb036905c60bd03a8d9c7f3b1d88

/gluon-tutorials-zh-master/chapter_optimization/adagrad-gluon.py

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[ "Apache-2.0" ]

permissive

SleepyBag/TrivialPractice

c31458d0c28afba158cb4090cb7013267ff54bb2

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refs/heads/master

2020-03-22T00:34:37.415074

2018-06-30T14:02:04

139,253,389

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UTF-8

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py

import mxnet as mx from mxnet import gluon, nd from mxnet.gluon import nn import sys sys.path.append('..') import utils # 生成数据集。 num_inputs = 2 num_examples = 1000 true_w = [2, -3.4] true_b = 4.2 features = nd.random.normal(scale=1, shape=(num_examples, num_inputs)) labels = true_w[0] * features[:, 0] + true_w[1] * features[:, 1] + true_b labels += nd.random.normal(scale=0.01, shape=labels.shape) # 线性回归模型。 net = nn.Sequential() net.add(nn.Dense(1)) learning_rate = .01 net.collect_params().initialize(mx.init.Normal(sigma=1), force_reinit=True) trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': learning_rate}) utils.optimize(batch_size=10, trainer=trainer, num_epochs=5, decay_epoch=None, log_interval=10, features=features, labels=labels, net=net) net.collect_params().initialize(mx.init.Normal(sigma=1), force_reinit=True) trainer = gluon.Trainer(net.collect_params(), 'adagrad', {'learning_rate': learning_rate}) utils.optimize(batch_size=10, trainer=trainer, num_epochs=5, decay_epoch=None, log_interval=10, features=features, labels=labels, net=net)

[ "xueqianming200@gmail.com" ]

xueqianming200@gmail.com

86fee19decbe6fbd99256621b5d77459a4c80b51

a6cc157fdd1a15e9d451af653cf3eadbdac60885

/cpp_develop/catkin_ws/src/ros_arduino_bridge/ros_arduino_python/src/ros_arduino_python/calibrate_linear.py

3ab1f901ef9a959a737978f37d4c3bb5cebabeba

[]

no_license

miaoruonan/morn

9b4f0b64241c12140e8adc571579974d9e35a14b

88e353ce480265b0b0b12f22a67ce13dd2ff42f3

refs/heads/master

2021-06-26T05:18:58.321932

2021-01-28T07:21:51

2021-01-28T07:25:16

214,172,876

0

null

UTF-8

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py

#!/usr/bin/env python import rospy from geometry_msgs.msg import Twist, Point from math import copysign, sqrt, pow import tf class CalibrateLinear(): def __init__(self): #give the node a name rospy.init_node('calibrate_linear', anonymous=False) #set rospy to execute a shutdown function when terminating the script rospy.on_shutdown(self.shutdown) #How fast will we check the odometry values? self.rate = 10 r = rospy.Rate(self.rate) #set the distance to travel self.test_distance = 1.5 self.speed = 0.2 self.tolerance = 0.01 self.odom_linear_scale_correction = 1.0 self.start_test = True #Publisher to control the robot's speed self.cmd_vel = rospy.Publisher('/cmd_vel', Twist, queue_size=5) #The base frame is base_footprint for the robot self.base_frame = rospy.get_param('~base_frame', '/base_footprint') #The odom frame is usually just /odom self.odom_frame = rospy.get_param('~odom_frame', '/odom') #initialize the tf listener self.tf_listener = tf.TransformListener() #give tf some time to fill its buffer rospy.sleep(2) #make sure we see the odom and base frames self.tf_listener.waitForTransform(self.odom_frame, self.base_frame, rospy.Time(), rospy.Duration(60.0)) self.position = Point() #get the starting position from the tf transform between the odom and base frames self.position = self.get_position() x_start = self.position.x y_start = self.position.y move_cmd = Twist() while not rospy.is_shutdown(): #Stop the robot by default move_cmd = Twist() if self.start_test: #get the current position from the tf transform between the odom and base frames self.position = self.get_position() #compute the euclidean distance from the target point distance = sqrt(pow((self.position.x - x_start), 2) + pow((self.position.y - y_start), 2)) #correct the estimate distance by the correction factor distance *= self.odom_linear_scale_correction #How close are we? error = distance - self.test_distance #are we close enough? if not self.start_test or abs(error) < self.tolerance: self.start_test = False params = False rospy.loginfo(params) else: #if not, move in the appropriate direction move_cmd.linear.x = copysign(self.speed, -1*error) else: self.position = self.get_position() x_start = self.position.x y_start = self.position.y self.cmd_vel.publish(move_cmd) r.sleep() #stop the robot self.cmd_vel.publish(Twist()) def get_position(self): #get the current transform between the odom and base frames try: (trans, rot) = self.tf_listener.lookupTransform(self.odom_frame, self.base_frame, rospy.Time(0)) except (tf.Exception, tf.ConnectivityException, tf.LookupException): rospy.loginfo("TF exception") return return Point(*trans) def shutdown(self): #Always stop the robot when shutting down the node rospy.loginfo("Stopping the robot") self.cmd_vel.publish(Twist()) rospy.sleep(1) if __name__ == '__main__': try: CalibrateLinear() rospy.spin() except: rospy.loginfo("Calibration terminated.")

[ "15879209474@163.com" ]

15879209474@163.com

7ffae845f088fb2c95c7c37d9f6e0559af611adc

6d9fbe6e6a2abfd8455e92f6dba67a5f02d87f41

/lib/phonenumbers/data/region_AC.py

243d707a8213496a114091c66baa4551350d4629

[]

no_license

JamesBrace/InfluenceUWebLaunch

549d0b48ff3259b139cb891a19cb8b5382ffe2c8

332d25940e4b1b45a7a2a8200f77c8413543b199

refs/heads/master

2021-09-04T04:08:47.594900

2018-01-15T16:49:29

80,778,825

1

null

UTF-8

Python

false

1,094

py

"""Auto-generated file, do not edit by hand. AC metadata""" from ..phonemetadata import NumberFormat, PhoneNumberDesc, PhoneMetadata PHONE_METADATA_AC = PhoneMetadata(id='AC', country_code=247, international_prefix='00', general_desc=PhoneNumberDesc(national_number_pattern='[46]\\d{4}|[01589]\\d{5}', possible_number_pattern='\\d{5,6}', possible_length=(5, 6)), fixed_line=PhoneNumberDesc(national_number_pattern='6[2-467]\\d{3}', possible_number_pattern='\\d{5}', example_number='62889', possible_length=(5,)), mobile=PhoneNumberDesc(national_number_pattern='4\\d{4}', possible_number_pattern='\\d{5}', example_number='40123', possible_length=(5,)), toll_free=PhoneNumberDesc(), premium_rate=PhoneNumberDesc(), shared_cost=PhoneNumberDesc(), personal_number=PhoneNumberDesc(), voip=PhoneNumberDesc(), pager=PhoneNumberDesc(), uan=PhoneNumberDesc(national_number_pattern='[01589]\\d{5}', possible_number_pattern='\\d{6}', example_number='542011', possible_length=(6,)), voicemail=PhoneNumberDesc(), no_international_dialling=PhoneNumberDesc())

[ "james.brace@mail.mcgill.ca" ]

james.brace@mail.mcgill.ca

9f628a3fcb3ba15724f1abcb004ff2ed34f398a2

ad13583673551857615498b9605d9dcab63bb2c3

/output/instances/nistData/atomic/nonNegativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonNegativeInteger-enumeration-3-2.py

b576ac7679de66f6d806e4fa821974abf9447594

[ "MIT" ]

permissive

tefra/xsdata-w3c-tests

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081d0908382a0e0b29c8ee9caca6f1c0e36dd6db

refs/heads/main

2023-08-03T04:25:37.841917

2023-07-29T17:10:13

2023-07-30T12:11:13

239,622,251

2

0

MIT

2023-07-25T14:19:04

2020-02-10T21:59:47

Python

UTF-8

Python

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py

from output.models.nist_data.atomic.non_negative_integer.schema_instance.nistschema_sv_iv_atomic_non_negative_integer_enumeration_3_xsd.nistschema_sv_iv_atomic_non_negative_integer_enumeration_3 import NistschemaSvIvAtomicNonNegativeIntegerEnumeration3 from output.models.nist_data.atomic.non_negative_integer.schema_instance.nistschema_sv_iv_atomic_non_negative_integer_enumeration_3_xsd.nistschema_sv_iv_atomic_non_negative_integer_enumeration_3 import NistschemaSvIvAtomicNonNegativeIntegerEnumeration3Type obj = NistschemaSvIvAtomicNonNegativeIntegerEnumeration3( value=NistschemaSvIvAtomicNonNegativeIntegerEnumeration3Type.VALUE_9176 )

[ "tsoulloftas@gmail.com" ]

tsoulloftas@gmail.com

52164c85a80608ac931cec19edf6440abf757d17

e48a43af1b285f19137cf1c839ea5836312c6793

/toutiao.py

f330e711018b71ad4b9619c8c133b9cad3456107

[]

no_license

willfengis/toutiao

5f933aadebd6a24d5f4a69c162a61efb4dcd68d0

10fc31a46368f9cc08e5889f4a644a2e0ffc7028

refs/heads/master

2021-01-21T10:47:17.788795

2017-08-31T10:09:27

101,987,700

0

null

UTF-8

Python

false

2,909

py

import requests from urllib.parse import urlencode from requests.exceptions import RequestException import json from bs4 import BeautifulSoup import re import pymongo import os from multiprocessing import Pool from hashlib import md5 from com.it.ttconfig import * client = pymongo.MongoClient(MONGO_URL,connect=False) db = client[MONGO_DB] def getHtml(Url): try: Myhtml = requests.get(Url,headers=Myheader) if Myhtml.status_code == 200: return Myhtml.text return "getHtmlerror" except RequestException: return "getHtmlerror" def getStr(Myhtml): Data = json.loads(Myhtml) if Data and "data" in Data.keys(): for url1 in Data.get("data"): yield url1.get("share_url") def getDetail(Url1): try: Myhtml = requests.get(Url1,headers=Myheader) if Myhtml.status_code == 200: return Myhtml.text return "getDetailHtmlerror" except RequestException: print("Url1 error") return "getDetailHtmlerror" def getStr2(Myhtml2,Url1): Bs4html = BeautifulSoup(Myhtml2,"lxml") Mytitle = Bs4html.select("title")[0].get_text() Myrule = re.compile("BASE_DATA.galleryInfo.*?gallery:(.*?),\n\s*?siblingList",re.S) Mystr2 = re.search(Myrule,Myhtml2) if Mystr2: json_str2 = json.loads(Mystr2.group(1)) if json_str2 and "sub_images" in json_str2.keys(): sub_image = json_str2.get("sub_images") image = [x.get("url") for x in sub_image] for imageurlone in image:downLoad(imageurlone) return {"title":Mytitle,"imageurl":image,"Url":Url1} return "url2error" return "url2error" def saveMongo(imageurl): if db[MONGO_TABLE].insert(imageurl): print("url save to mongodb ok") return True return False def downLoad(imageurlone): try: Myhtml = requests.get(imageurlone,headers=Myheader) if Myhtml.status_code == 200: saveImage(Myhtml.content) return "getHtmlerror" except RequestException: print("downloadImagError") return "getHtmlerror" def saveImage(content): path = "{0}/{1}.{2}".format(os.getcwd()+"/image",md5(content).hexdigest(),"jpg") if not os.path.exists(path): with open(path,"wb") as f: f.write(content) f.close() print("downimage successful:"+ path) def main(Offset): Data = {'offset': Offset, 'format': 'json', 'keyword': Find, 'autoload': 'true', 'count': '20', 'cur_tab': '1'} Url = "http://www.toutiao.com/search_content/?" + urlencode(Data) Myhtml = getHtml(Url) for Url1 in getStr(Myhtml): Myhtml2 = getDetail(Url1) imageurl = getStr2(Myhtml2,Url1) if imageurl != "url2error": saveMongo(imageurl) if __name__ == "__main__": page = [i*20 for i in range(0,6)] pool = Pool() pool.map(main,page)

[ "root@localhost.localdomain" ]

root@localhost.localdomain

651465018b3370f246d12c0b45dead9a006898ac

5488617b1b05c436b1f8c8642ea75ca754719f8d

/phenomenological/Single_TOP/select_scripts/script/script_1065.py

07afd7a1b201fed85dd725acf70a9ea4ba7a34d7

[]

no_license

wenxingfang/TW_Top

fdb1ba136be6ace8fdacaade58cb4ca4fcdc3c9e

389e76c904d08a59d9141b9b66ec15d2583f8e9a

refs/heads/master

2021-02-05T06:54:27.908688

2020-02-28T13:24:00

243,754,087

0

1

null

UTF-8

Python

false

231

py

import os import ROOT ROOT.gSystem.Load("/user/wenxing/ST_TW_channel/CMSSW_8_0_25/src/Phynomenological_study/Single_TOP/select_scripts/select_save_parton_C.so") ROOT.gROOT.ProcessLine('select_save_parton("1065")') print 'Done!'

[ "wenxing.fang@cern.ch" ]

wenxing.fang@cern.ch

781541a1f0b86a43ce728e170b53055a99749d93

12123592a54c4f292ed6a8df4bcc0df33e082206

/py2/pgms/sec6/flask/db_create.py

667c9a87acb3e16e1bbb26111a89d32eaae62ba8

[]

no_license

alvinooo/advpython

b44b7322915f832c8dce72fe63ae6ac7c99ef3d4

df95e06fd7ba11b0d2329f4b113863a9c866fbae

refs/heads/master

2021-01-23T01:17:22.487514

2017-05-30T17:51:47

92,860,630

0

null

UTF-8

Python

false

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#!venv/bin/python # db_create.py - create database from migrate.versioning import api from config import SQLALCHEMY_DATABASE_URI from config import SQLALCHEMY_MIGRATE_REPO from app import db import os.path db.create_all() if not os.path.exists(SQLALCHEMY_MIGRATE_REPO): api.create(SQLALCHEMY_MIGRATE_REPO, 'database repository') api.version_control(SQLALCHEMY_DATABASE_URI, SQLALCHEMY_MIGRATE_REPO) else: api.version_control(SQLALCHEMY_DATABASE_URI, SQLALCHEMY_MIGRATE_REPO, api.version(SQLALCHEMY_MIGRATE_REPO))

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alvin.heng@teradata.com

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uiandwe/TIL

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# -*- coding: utf-8 -*- """ Given an array of integers where every integer occurs three times except for one integer, which only occurs once, find and return the non-duplicated integer. For example, given [6, 1, 3, 3, 3, 6, 6], return 1. Given [13, 19, 13, 13], return 19. Do this in O(N) time and O(1) space. """ def getSingle(arr): ones = 0 twos = 0 n = len(arr) for i in range(n): twos = twos | (ones & arr[i]) ones = ones ^ arr[i] common_bit_mask = ~(ones & twos) ones &= common_bit_mask twos &= common_bit_mask return ones if __name__ == '__main__': print(getSingle([13, 1, 13, 13])) print(getSingle([13, 1, 13, 13, 2, 3, 2, 3, 2, 3]))

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uiandwe.noreply@github.com

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/python/voz.py

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# coding: cp860 import speech_recognition as sr r = sr.Recognizer() with sr.Microphone() as s: r.adjust_for_ambient_noise(s) while True: audio = r.listen(s) print("Voce respondeu:", r.recognize_google(audio, language = 'pt'))

[ "vcatafesta@gmail.com" ]

vcatafesta@gmail.com

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/blog.py

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xxnbyy/mytools

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2021-04-29T10:13:07.230358

2016-12-29T13:16:56

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2017-01-03T01:49:32

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############################################################# ### ### _|_|_| _| _| _| _| ### _| _| _| _|_|_| _|_| _| _| _|_|_|_| ### _|_| _|_| _| _| _| _| _| _| _| ### _| _| _| _| _| _| _| _| _| _| ### _|_|_| _| _| _|_|_| _| _| _| _|_| ### _| ### _| ### ### name: blog.py ### function: write blog ### date: 2016-11-02 ### author: quanyechavshuo ### blog: https://3xp10it.cc ############################################################# import time from exp10it import figlet2file figlet2file("3xp10it",0,True) time.sleep(1)

[ "quanyechavshuo@gmail.com" ]

quanyechavshuo@gmail.com

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/python-zict/lilac.py

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[]

no_license

MikeyBaldinger/arch4edu

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c1775bf7fe0ffc87f3c8b4109fb1e8acde12a430

refs/heads/master

2022-12-23T16:40:55.513537

2020-09-28T21:00:59

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#!/usr/bin/env python3 from lilaclib import * maintainers = [{'github': 'petronny', 'email': 'Jingbei Li <i@jingbei.li>'}] update_on = [{'aur': None}, {'alias': 'python'}] build_prefix = 'extra-x86_64' repo_depends = ['python-heapdict'] pre_build = aur_pre_build post_build = aur_post_build if __name__ == '__main__': single_main(build_prefix)

[ "i@jingbei.li" ]

i@jingbei.li

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/src/api/symbols/views/__init__.py

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[]

no_license

fan1018wen/Alpha

26899cc0eb6761bf6bd8089e7d12716c9e7ae01e

c50def8cde58fd4663032b860eb058302cbac6da

refs/heads/master

2021-05-12T12:54:15.747220

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from django.core.paginator import Paginator from django.db.models import Q from rest_framework.views import APIView from common.models import BackstageHTTPResponse from common.utils import log_exception from symbols.filters import SymbolFilter from symbols.models import Symbol from symbols.serializers import SymbolSerializer class SymbolListAPI(APIView): @log_exception def get(self, request, *args, **kwargs): """ 公式可用数据点列表 --- parameters: - name: index description: 页数 type: integer paramType: query required: false - name: number description: 每页条数 type: integer paramType: query required: false - name: table_name description: 表名 type: string paramType: query required: false - name: classification_1 description: 第一维度 type: string paramType: query required: false - name: classification_2 description: 第二维度 type: string paramType: query required: false """ symbols = Symbol.objects.all() symbols = SymbolFilter(request.GET, queryset=symbols).qs paginator = Paginator(symbols, request.GET.get('number', 100)) page = paginator.page(request.GET.get('index', 1)) serializer = SymbolSerializer(page, many=True) return BackstageHTTPResponse( code=BackstageHTTPResponse.API_HTTP_CODE_NORMAL, data=serializer.data, pageinfo=page ).to_response() class TableListAPI(APIView): @log_exception def get(self, request, *args, **kwargs): """ 公式可用表 --- parameters: - name: index description: 页数 type: integer paramType: query required: false - name: number description: 每页条数 type: integer paramType: query required: false """ table_names = list(Symbol.objects.exclude( Q(table_name__isnull=True)|(Q(table_name='')) ).values_list('table_name', flat=True).order_by('table_name').distinct()) return BackstageHTTPResponse( code=BackstageHTTPResponse.API_HTTP_CODE_NORMAL, data=table_names, ).to_response() class SymbolClassificationListAPI(APIView): @log_exception def get(self, request, classification, *args, **kwargs): """ 公式可用区分维度 --- parameters: - name: classification description: 第几个区分维度 type: integer paramType: path required: true """ column_name = 'classification_%s' % classification if column_name not in [i.attname for i in Symbol._meta.fields]: return BackstageHTTPResponse( code=BackstageHTTPResponse.API_HTTP_CODE_NOT_FOUND, message='未找到数据' ).to_response() query_dict_1 = {'%s__isnull' % column_name: True} query_dict_2 = {column_name: ''} column_values = list(Symbol.objects.exclude( Q(**query_dict_1)|(Q(**query_dict_2)) ).values_list(column_name, flat=True).order_by(column_name).distinct()) return BackstageHTTPResponse( code=BackstageHTTPResponse.API_HTTP_CODE_NORMAL, data=column_values, ).to_response()

[ "mengqiang@1b2b.cn" ]

mengqiang@1b2b.cn

9ae6c6e071cb9074c94b0058901696c52d416298

a0eb6744e6f7f509b96d21f0bc8b3f8387f6861c

/notebook/union_find_basic_usage.py

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[ "MIT" ]

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nkmk/python-snippets

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2023-08-03T04:20:05.606293

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from union_find_basic import UnionFindBasic, UnionFindPathCompression, UnionFindByRank, UnionFindBySize, UnionFind ufb = UnionFindBasic(5) print(ufb.parents) # [0, 1, 2, 3, 4] ufb.union(3, 4) print(ufb.parents) ufb.union(2, 3) print(ufb.parents) ufb.union(1, 2) print(ufb.parents) ufb.union(0, 4) print(ufb.parents) # [0, 1, 2, 3, 3] # [0, 1, 2, 2, 3] # [0, 1, 1, 2, 3] # [0, 0, 1, 2, 3] print([ufb.find(i) for i in range(5)]) # [0, 0, 0, 0, 0] ufpc = UnionFindPathCompression(5) print(ufpc.parents) # [0, 1, 2, 3, 4] ufpc.union(3, 4) print(ufpc.parents) ufpc.union(2, 3) print(ufpc.parents) ufpc.union(1, 2) print(ufpc.parents) ufpc.union(0, 4) print(ufpc.parents) # [0, 1, 2, 3, 3] # [0, 1, 2, 2, 3] # [0, 1, 1, 2, 3] # [0, 0, 1, 1, 1] print([ufpc.find(i) for i in range(5)]) # [0, 0, 0, 0, 0] ufbr = UnionFindByRank(5) print(ufbr.parents) # [0, 1, 2, 3, 4] ufbr.union(3, 4) print(ufbr.parents) ufbr.union(2, 3) print(ufbr.parents) ufbr.union(1, 2) print(ufbr.parents) ufbr.union(0, 4) print(ufbr.parents) # [0, 1, 2, 3, 3] # [0, 1, 3, 3, 3] # [0, 3, 3, 3, 3] # [3, 3, 3, 3, 3] ufbs = UnionFindBySize(5) print(ufbs.parents) # [0, 1, 2, 3, 4] ufbs.union(3, 4) print(ufbs.parents) ufbs.union(2, 3) print(ufbs.parents) ufbs.union(1, 2) print(ufbs.parents) ufbs.union(0, 4) print(ufbs.parents) # [0, 1, 2, 3, 3] # [0, 1, 3, 3, 3] # [0, 3, 3, 3, 3] # [3, 3, 3, 3, 3] print(ufbs.size) # [1, 1, 1, 5, 1] print(ufbs.size[ufbs.find(0)]) # 5 uf = UnionFind(5) print(uf.parents) # [-1, -1, -1, -1, -1] uf.union(3, 4) print(uf.parents) uf.union(2, 3) print(uf.parents) uf.union(1, 2) print(uf.parents) uf.union(0, 4) print(uf.parents) # [-1, -1, -1, -2, 3] # [-1, -1, 3, -3, 3] # [-1, 3, 3, -4, 3] # [3, 3, 3, -5, 3]

[ "nkmk.on@gmail.com" ]

nkmk.on@gmail.com

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/topologyTest/GetDDIs_150_250Examples_WithDifferentDomainNames.py

cafde521581bfddd4fd57d7b907fcb2ae3e1149d

[]

no_license

magic2du/contact_matrix

9f8ae868d71e7e5c8088bf22a9407ea3eb073be6

957e2ead76fabc0299e36c1435162edd574f4fd5

refs/heads/master

2021-01-18T21:15:07.341341

2015-09-16T02:14:53

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2014-09-19T16:48:37

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import _mysql from dealFile import * #Get of Domains which has more than 2 interfaces have 16-20 examples db=_mysql.connect(host="localhost",user="root",passwd="zxcv4321",db="DDI") #db.query("""select COUNT(*) from PPI inner join example on (ID = PPI_ID) where domain1="ACT" and domain2="ACT" and topology_1 = 6 and topology_2 = 6""") #db.query("""select * from PPI inner join example on (ID = PPI_ID) where domain1="ACT" and domain2="ACT" """) ddiList=readDDIsFile('listOfFolders15OCT.txt') ddis=[] #Number of Domains which has 2 interfaces have more than 15 examples for ddi in ddiList: [domain1,domain2]=ddi if domain1 == domain2: continue #print i #print domain1 #print domain2 #query='SELECT DISTINCT topology_1,topology_2 from DDItopology WHERE domain1="'+domain1+'" AND domain2="'+domain2+'"' #query='SELECT DISTINCT topology_1,topology_2 from DDItopology WHERE domain1="'+domain1+'" AND domain2="'+domain2+'"' query='SELECT COUNT(DISTINCT topology_1,topology_2) from DDItopology WHERE domain1="'+domain1+'" AND domain2="'+domain2+'"' #print query #query='select domain1,domain2 from DDI1' db.query(query) result=db.store_result() numTopology=result.fetch_row(0) print numTopology[0][0] if numTopology[0][0]<2: break try: query='SELECT COUNT(*) from DDItopology WHERE domain1="'+domain1+'" AND domain2="'+domain2+'"' #print query db.query(query) result=db.store_result() numExample=result.fetch_row(0) print int(numExample[0][0]) if int(numExample[0][0])>150 and int(numExample[0][0])<250: ddis.append(domain1+'_int_'+domain2) except: print 'error' break writeListFile('listOfDDIsHaveOver2InterfacesHave150-250Examples.txt',ddis) #print result.fetch_row() #print r[0][0] readDDIsFile('listOfDDIsHave2InterfacesOver15.txt')

[ "magic2du@gmail.com" ]

magic2du@gmail.com

b5ab5cda1555793b46c2e5542858767a98e8ef6e

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/course_DE/udacity-data-engineering-projects-master/Project 5 - Data Pipelines with Airflow/exercises/dags/3_ex3_subdags/dag.py

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yennanliu/analysis

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refs/heads/master

2021-01-23T21:48:58.572269

2020-10-13T22:47:12

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# Instructions # In this exercise, we’ll place our S3 to RedShift Copy operations into a SubDag. # 1 - Consolidate HasRowsOperator into the SubDag # 2 - Reorder the tasks to take advantage of the SubDag Operators import datetime from airflow import DAG from airflow.operators.postgres_operator import PostgresOperator from airflow.operators.subdag_operator import SubDagOperator from airflow.operators.udacity_plugin import HasRowsOperator from lesson3.exercise3.subdag import get_s3_to_redshift_dag import sql_statements start_date = datetime.datetime.utcnow() dag = DAG( "lesson3.exercise3", start_date=start_date, ) trips_task_id = "trips_subdag" trips_subdag_task = SubDagOperator( subdag=get_s3_to_redshift_dag( "lesson3.exercise3", trips_task_id, "redshift", "aws_credentials", "trips", sql_statements.CREATE_TRIPS_TABLE_SQL, s3_bucket="udac-data-pipelines", s3_key="divvy/unpartitioned/divvy_trips_2018.csv", start_date=start_date, ), task_id=trips_task_id, dag=dag, ) stations_task_id = "stations_subdag" stations_subdag_task = SubDagOperator( subdag=get_s3_to_redshift_dag( "lesson3.exercise3", stations_task_id, "redshift", "aws_credentials", "stations", sql_statements.CREATE_STATIONS_TABLE_SQL, s3_bucket="udac-data-pipelines", s3_key="divvy/unpartitioned/divvy_stations_2017.csv", start_date=start_date, ), task_id=stations_task_id, dag=dag, ) # # TODO: Consolidate check_trips and check_stations into a single check in the subdag # as we did with the create and copy in the demo # check_trips = HasRowsOperator( task_id="check_trips_data", dag=dag, redshift_conn_id="redshift", table="trips" ) check_stations = HasRowsOperator( task_id="check_stations_data", dag=dag, redshift_conn_id="redshift", table="stations" ) location_traffic_task = PostgresOperator( task_id="calculate_location_traffic", dag=dag, postgres_conn_id="redshift", sql=sql_statements.LOCATION_TRAFFIC_SQL ) # # TODO: Reorder the Graph once you have moved the checks # trips_subdag_task >> check_trips stations_subdag_task >> check_stations check_stations >> location_traffic_task check_trips >> location_traffic_task

[ "f339339@gmail.com" ]

f339339@gmail.com

a0fcd76bb531bd1b8db92bfd0f143b1ac789e17f

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/homeads/mails.py

a837ea5fa7f51062eae6d086a491ffecd86079ce

[]

no_license

wd5/localized_classified_ads

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refs/heads/master

2020-12-25T15:30:40.113192

2012-11-01T15:29:02

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#-*- coding: utf-8 -*- from django.contrib.sites.models import Site from utils.mails import AdEmailMultiAlternatives class HomeEmail(AdEmailMultiAlternatives): """ Class used to send multi alternavies email (text + html) for AcheterSansCom and LouerSansCom """ def get_default_context(self): if self.ad: if self.ad.__class__.__name__ == "HomeForSaleAd": self.default_context = {'linkColor': '#20B2AB', 'secondColor': '#FFB82E'} if self.ad.__class__.__name__ == "HomeForRentAd": self.default_context = {'linkColor': '#9D81A1', 'secondColor': 'Pink'} else: domain = Site.objects.get_current().domain if domain == 'achetersanscom.com': self.default_context = {'linkColor': '#20B2AB', 'secondColor': '#FFB82E'} if domain == 'louersanscom.com': self.default_context = {'linkColor': '#9D81A1', 'secondColor': 'Pink'} return self.default_context def get_default_images(self): if self.ad: if self.ad.__class__.__name__ == "HomeForSaleAd": self.default_files = (('img/home.png', 'logo'), ('img/shadow_bottom.jpg', 'shadow')) if self.ad.__class__.__name__ == "HomeForRentAd": self.default_files = (('img/apartment.png', 'logo'), ('img/shadow_bottom.jpg', 'shadow')) else: domain = Site.objects.get_current().domain if domain == 'achetersanscom.com': self.default_files = (('img/home.png', 'logo'), ('img/shadow_bottom.jpg', 'shadow')) if domain == 'louersanscom.com': self.default_files = (('img/apartment.png', 'logo'), ('img/shadow_bottom.jpg', 'shadow')) return self.default_files class UserSignIn(HomeEmail): """ User Sign In """ subject = u"[{{ site.name }}] Validation de votre inscription" template_name = 'emails/user_sign_in/body' class HomeAdCreatedMessageEmail(HomeEmail): """ Home Ad Created Message Email Send when user create a new ad """ subject = u"[{{ site.name }}] Annonce créée" template_name = 'emails/home_ad_created/body' class HomeAdUpdatedMessageEmail(HomeEmail): """ Home Ad Update Message Email Send when user update an ad """ subject = u"[{{ site.name }}] Annonce mise à jour" template_name = 'emails/home_ad_updated/body' class BuyerToVendorMessageEmail(HomeEmail): """ User message email from buyer to vendor for an Ad """ subject = u'[{{ site.name }}] Nouveau message à propos de votre bien' template_name = 'emails/to_vendor_message/body' class VendorToBuyerMessageEmail(HomeEmail): """ User message email from vendor to buyer for an Ad """ subject = u'[{{ site.name }}] Nouveau message à propos de votre recherche' template_name = 'emails/to_buyer_message/body' class NewPotentialBuyerToVendorMessageEmail(HomeEmail): """ Mail sent to vendor when a user has it search coincides with it ad """ subject = u'[{{ site.name }}] Une nouvelle personne pourrait être interessée par votre bien' template_name = 'emails/to_vendor_potential_buyer/body' class NewAdToBuyerMessageEmail(HomeEmail): """ Mail sent to inform a user that a new ad corresponds to it search """ subject = u'[{{ site.name }}] Un nouveau bien correspond à votre recherche' template_name = 'emails/to_buyer_potential_ad/body'

[ "samuel.goldszmidt@gmail.com" ]

samuel.goldszmidt@gmail.com

2d91f87c27aff3220f48df0e44ec5d65370af653

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/Calibration/CalibConfigFiles/MuonCalibration/CalibConfig_DetModel89_RecoStage38.py

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[]

no_license

StevenGreen1/OptimisationStudies

8cca03f57d2cbf81e5fb609f13e2fa4b9c9880f6

c5741e8d2fab4752ceca8b10cc5f2bbc1a7fafa9

refs/heads/master

2021-01-18T21:30:51.418785

2017-02-21T16:27:50

44,306,370

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null

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# Digitisation Constants - ECal CalibrECal = 42.121331495 # Digitisation Constants ILDCaloDigi - HCal CalibrHCalBarrel = 47.5716455642 CalibrHCalEndcap = 53.3873293873 CalibrHCalOther = 29.2886957667 # Digitisation Constants NewLDCCaloDigi - HCal CalibrHCal = -1 # Digitisation Constants - Muon Chamber CalibrMuon = 56.7 # MIP Peak position in directed corrected SimCaloHit energy distributions # used for realistic ECal and HCal digitisation options CalibrECalMIP = 0.0001475 CalibrHCalMIP = 0.0004925 # MIP Peak position in directed corrected CaloHit energy distributions # used for MIP definition in PandoraPFA ECalToMIPCalibration = 153.846 HCalToMIPCalibration = 41.841 MuonToMIPCalibration = 10.3093 # EM and Had Scale Settings ECalToEMGeVCalibration = 1.01529193221 HCalToEMGeVCalibration = 1.12124159762 ECalToHadGeVCalibration = 1.08839104614 HCalToHadGeVCalibration = 1.12124159762 # Pandora Threshold Cuts ECalMIPThresholdPandora = 0.5 HCalMIPThresholdPandora = 0.3 # Hadronic Energy Truncation in HCal PandoraPFA MaxHCalHitHadronicEnergy = 1 # Timing ECal ECalBarrelTimeWindowMax = 1000000 ECalEndcapTimeWindowMax = 1000000 # Timing HCal HCalBarrelTimeWindowMax = 1000000 HCalEndcapTimeWindowMax = 1000000

[ "sg1sg2sg3@hotmail.co.uk" ]

sg1sg2sg3@hotmail.co.uk

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/examples/query_horizon.py

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[ "Apache-2.0" ]

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kingdavid6336/py-stellar-base

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refs/heads/master

2021-12-18T14:20:01.146139

2020-06-21T07:55:59

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from stellar_sdk import Server server = Server(horizon_url="https://horizon-testnet.stellar.org") # get a list of transactions that occurred in ledger 1400 transactions = server.transactions().for_ledger(1400).call() print(transactions) # get a list of transactions submitted by a particular account transactions = server.transactions() \ .for_account(account_id="GASOCNHNNLYFNMDJYQ3XFMI7BYHIOCFW3GJEOWRPEGK2TDPGTG2E5EDW") \ .call() print(transactions)

[ "4catcode@gmail.com" ]

4catcode@gmail.com

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/examples/vector_v3.py

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""" A multi-dimensional ``Vector`` class, take 3 """ from array import array import math import reprlib import numbers class Vector: typecode = 'd' def __init__(self, components): self._components = array(self.typecode, components) def __len__(self): return len(self._components) def __iter__(self): return iter(self._components) def __abs__(self): return math.sqrt(sum(x * x for x in self)) def __eq__(self, other): return (len(self) == len(other) and all(a == b for a, b in zip(self, other))) def __str__(self): return str(tuple(self)) def __repr__(self): components = reprlib.repr(self._components) components = components[components.find('['):-1] return 'Vector({})'.format(components) def __getitem__(self, index): cls = type(self) if isinstance(index, slice): return cls(self._components[index]) elif isinstance(index, numbers.Integral): return self._components[index] else: msg = '{cls.__name__} indices must be integers' raise TypeError(msg.format(cls=cls)) # ... def __mul__(self, scalar): if isinstance(scalar, numbers.Real): return Vector(n * scalar for n in self) else: return NotImplemented

[ "luciano@ramalho.org" ]

luciano@ramalho.org

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/main/rates/management/commands/get_rate_data.py

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Hawk94/coin_tracker

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2021-01-24T08:12:37.041745

2017-08-10T11:01:19

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from django.core.management.base import BaseCommand, CommandError from django.conf import settings from main.rates.models import Rate import requests import datetime import decimal class Command(BaseCommand): help = 'Gets todays BTC price and saves it to the database' def handle(self, *args, **options): base_url = 'https://openexchangerates.org/api/latest.json?app_id={}' request_json = requests.get(base_url.format(settings.OPEN_EXCHANGE_APP_ID)).json()['rates'] eur_rate = 1 / request_json['EUR'] gbp_rate = 1 / request_json['GBP'] date = datetime.date.today() Rate.objects.create(date=date, eur_rate=eur_rate, gbp_rate=gbp_rate) self.stdout.write(self.style.SUCCESS('Successfully created exchange rate records!'))

[ "x99tom.miller@gmail.com" ]

x99tom.miller@gmail.com

123ff2163d0dea2759b84eef2ebe3fab6a5fdbff

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/iHome/web_html.py

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[]

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zengsiquan/ihome

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40926f74d46bc76de4aecd98cfc52302ecf72f1b

refs/heads/master

2020-03-10T00:55:06.484107

2018-04-10T13:22:52

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# -*- coding:utf-8 -*- from flask import Blueprint,current_app,make_response from flask_wtf import csrf html = Blueprint('html',__name__) @html.route('/<re(".*"):file_name>') def get_html(file_name): if not file_name: file_name = 'index.html' if file_name != "favicon.ico": file_name= 'html/'+file_name response = make_response(current_app.send_static_file(file_name)) csrf_token = csrf.generate_csrf() response.set_cookie('csrf_token',csrf_token) # return current_app.send_static_file(file_name) return response

[ "xwp_fullstack@163.com" ]

xwp_fullstack@163.com

718743c7da0e3030a59f7358c4988be1a2d87356

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/Python/Data Structure/Binary Tree/Serilization:Deserialization/Verify Preorder Serialization of a Binary Tree.py

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[]

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XinheLIU/Coding-Interview

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refs/heads/master

2022-09-17T14:30:54.371370

2022-08-19T15:53:35

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class Solution: def isValidSerialization(self, preorder: str) -> bool: stack = [] top = -1 preorder = preorder.split(',') for s in preorder: stack.append(s) top += 1 while self.endsWithTwoHashes(stack,top): h = stack.pop() top -= 1 h = stack.pop() top -= 1 if top < 0: return False h = stack.pop() stack.append('#') #print stack if len(stack) == 1: if stack[0] == '#': return True return False def endsWithTwoHashes(self,stack,top): if top < 1: return False if stack[top]=='#' and stack[top-1]=='#': return True return False

[ "LIUXinhe@outlook.com" ]

LIUXinhe@outlook.com

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/asynchttp/websocket.py

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oohlaf/asynchttp

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2021-01-16T19:47:18.929253

2013-10-10T23:36:13

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"""WebSocket protocol versions 13 and 8.""" __all__ = ['WebSocketParser', 'WebSocketWriter', 'do_handshake', 'Message', 'WebSocketError', 'MSG_TEXT', 'MSG_BINARY', 'MSG_CLOSE', 'MSG_PING', 'MSG_PONG'] import base64 import binascii import collections import hashlib import struct from asynchttp import errors # Frame opcodes defined in the spec. OPCODE_CONTINUATION = 0x0 MSG_TEXT = OPCODE_TEXT = 0x1 MSG_BINARY = OPCODE_BINARY = 0x2 MSG_CLOSE = OPCODE_CLOSE = 0x8 MSG_PING = OPCODE_PING = 0x9 MSG_PONG = OPCODE_PONG = 0xa WS_KEY = b'258EAFA5-E914-47DA-95CA-C5AB0DC85B11' WS_HDRS = ('UPGRADE', 'CONNECTION', 'SEC-WEBSOCKET-VERSION', 'SEC-WEBSOCKET-KEY') Message = collections.namedtuple('Message', ['tp', 'data', 'extra']) class WebSocketError(Exception): """WebSocket protocol parser error.""" def WebSocketParser(out, buf): while True: message = yield from parse_message(buf) out.feed_data(message) if message.tp == MSG_CLOSE: out.feed_eof() break def parse_frame(buf): """Return the next frame from the socket.""" # read header data = yield from buf.read(2) first_byte, second_byte = struct.unpack('!BB', data) fin = (first_byte >> 7) & 1 rsv1 = (first_byte >> 6) & 1 rsv2 = (first_byte >> 5) & 1 rsv3 = (first_byte >> 4) & 1 opcode = first_byte & 0xf # frame-fin = %x0 ; more frames of this message follow # / %x1 ; final frame of this message # frame-rsv1 = %x0 ; 1 bit, MUST be 0 unless negotiated otherwise # frame-rsv2 = %x0 ; 1 bit, MUST be 0 unless negotiated otherwise # frame-rsv3 = %x0 ; 1 bit, MUST be 0 unless negotiated otherwise if rsv1 or rsv2 or rsv3: raise WebSocketError('Received frame with non-zero reserved bits') if opcode > 0x7 and fin == 0: raise WebSocketError('Received fragmented control frame') if fin == 0 and opcode == OPCODE_CONTINUATION: raise WebSocketError( 'Received new fragment frame with non-zero opcode') has_mask = (second_byte >> 7) & 1 length = (second_byte) & 0x7f # Control frames MUST have a payload length of 125 bytes or less if opcode > 0x7 and length > 125: raise WebSocketError( "Control frame payload cannot be larger than 125 bytes") # read payload if length == 126: data = yield from buf.read(2) length = struct.unpack_from('!H', data)[0] elif length > 126: data = yield from buf.read(8) length = struct.unpack_from('!Q', data)[0] if has_mask: mask = yield from buf.read(4) if length: payload = yield from buf.read(length) else: payload = b'' if has_mask: payload = bytes(b ^ mask[i % 4] for i, b in enumerate(payload)) return fin, opcode, payload def parse_message(buf): fin, opcode, payload = yield from parse_frame(buf) if opcode == OPCODE_CLOSE: if len(payload) >= 2: close_code = struct.unpack('!H', payload[:2])[0] close_message = payload[2:] return Message(OPCODE_CLOSE, close_code, close_message) elif payload: raise WebSocketError( 'Invalid close frame: {} {} {!r}'.format(fin, opcode, payload)) return Message(OPCODE_CLOSE, '', '') elif opcode == OPCODE_PING: return Message(OPCODE_PING, '', '') elif opcode == OPCODE_PONG: return Message(OPCODE_PONG, '', '') elif opcode not in (OPCODE_TEXT, OPCODE_BINARY): raise WebSocketError("Unexpected opcode={!r}".format(opcode)) # load text/binary data = [payload] while not fin: fin, _opcode, payload = yield from parse_frame(buf) if _opcode != OPCODE_CONTINUATION: raise WebSocketError( 'The opcode in non-fin frame is expected ' 'to be zero, got {!r}'.format(opcode)) else: data.append(payload) if opcode == OPCODE_TEXT: return Message(OPCODE_TEXT, b''.join(data).decode('utf-8'), '') else: return Message(OPCODE_BINARY, b''.join(data), '') class WebSocketWriter: def __init__(self, transport): self.transport = transport def _send_frame(self, message, opcode): """Send a frame over the websocket with message as its payload.""" header = bytes([0x80 | opcode]) msg_length = len(message) if msg_length < 126: header += bytes([msg_length]) elif msg_length < (1 << 16): header += bytes([126]) + struct.pack('!H', msg_length) else: header += bytes([127]) + struct.pack('!Q', msg_length) self.transport.write(header + message) def pong(self): """Send pong message.""" self._send_frame(b'', OPCODE_PONG) def ping(self): """Send pong message.""" self._send_frame(b'', OPCODE_PING) def send(self, message, binary=False): """Send a frame over the websocket with message as its payload.""" if isinstance(message, str): message = message.encode('utf-8') if binary: self._send_frame(message, OPCODE_BINARY) else: self._send_frame(message, OPCODE_TEXT) def close(self, code=1000, message=b''): """Close the websocket, sending the specified code and message.""" if isinstance(message, str): message = message.encode('utf-8') self._send_frame( struct.pack('!H%ds' % len(message), code, message), opcode=OPCODE_CLOSE) def do_handshake(method, headers, transport): """Prepare WebSocket handshake. It return http response code, response headers, websocket parser, websocket writer. It does not perform any IO.""" # WebSocket accepts only GET if method.upper() != 'GET': raise errors.HttpErrorException(405, headers=(('Allow', 'GET'),)) headers = dict(((hdr, val) for hdr, val in headers if hdr in WS_HDRS)) if 'websocket' != headers.get('UPGRADE', '').lower().strip(): raise errors.BadRequestException( 'No WebSocket UPGRADE hdr: {}\n' 'Can "Upgrade" only to "WebSocket".'.format( headers.get('UPGRADE'))) if 'upgrade' not in headers.get('CONNECTION', '').lower(): raise errors.BadRequestException( 'No CONNECTION upgrade hdr: {}'.format( headers.get('CONNECTION'))) # check supported version version = headers.get('SEC-WEBSOCKET-VERSION') if version not in ('13', '8', '7'): raise errors.BadRequestException( 'Unsupported version: {}'.format(version)) # check client handshake for validity key = headers.get('SEC-WEBSOCKET-KEY') try: if not key or len(base64.b64decode(key)) != 16: raise errors.BadRequestException( 'Handshake error: {!r}'.format(key)) except binascii.Error: raise errors.BadRequestException( 'Handshake error: {!r}'.format(key)) from None # response code, headers, parser, writer return (101, (('UPGRADE', 'websocket'), ('CONNECTION', 'upgrade'), ('TRANSFER-ENCODING', 'chunked'), ('SEC-WEBSOCKET-ACCEPT', base64.b64encode( hashlib.sha1(key.encode() + WS_KEY).digest()).decode())), WebSocketParser, WebSocketWriter(transport))

[ "fafhrd91@gmail.com" ]

fafhrd91@gmail.com

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/imported-from-gmail/2020-05-03-invert-a-binary-tree.py

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[]

no_license

johncornflake/dailyinterview

292615849cea62cb945ecc7039c594b6966a81f3

91bb0edb9e25255e6222279109c15ae9d203970c

refs/heads/master

2022-12-09T21:02:12.204755

2021-06-07T13:09:34

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Hi, here's your problem today. (You've reached the end of the problems for now - in the meanwhile, here is a random question. And visit CoderPro for more practice!) This problem was recently asked by Twitter: You are given the root of a binary tree. Invert the binary tree in place. That is, all left children should become right children, and all right children should become left children. Example: a / \ b c / \ / d e f The inverted version of this tree is as follows: a / \ c b \ / \ f e d Here is the function signature: class Node : def __init__ ( self , value ): self . left = None self . right = None self . value = value def preorder ( self ): print self . value , if self . left : self . left . preorder () if self . right : self . right . preorder () def invert ( node ): # Fill this in. root = Node ( 'a' ) root . left = Node ( 'b' ) root . right = Node ( 'c' ) root . left . left = Node ( 'd' ) root . left . right = Node ( 'e' ) root . right . left = Node ( 'f' ) root . preorder () # a b d e c f print "\n" invert ( root ) root . preorder () # a c f b e d

[ "chadeous@gmail.com" ]

chadeous@gmail.com

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/loginpass/github.py

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authlib/loginpass

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refs/heads/master

2022-06-08T13:08:09.271879

2020-12-08T06:04:39

128,506,236

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2022-05-13T19:30:54

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""" loginpass.github ~~~~~~~~~~~~~~~~ Loginpass Backend of GitHub (https://github.com). Useful Links: - Create App: https://github.com/settings/developers - API documentation: https://developer.github.com/v3/ :copyright: (c) 2018 by Hsiaoming Yang :license: BSD, see LICENSE for more details. """ from authlib.oidc.core import UserInfo class GitHub(object): NAME = 'github' OAUTH_CONFIG = { 'api_base_url': 'https://api.github.com/', 'access_token_url': 'https://github.com/login/oauth/access_token', 'authorize_url': 'https://github.com/login/oauth/authorize', 'client_kwargs': {'scope': 'user:email'}, 'userinfo_endpoint': 'https://api.github.com/user', } def userinfo(self, **kwargs): resp = self.get(self.OAUTH_CONFIG['userinfo_endpoint'], **kwargs) data = resp.json() params = { 'sub': str(data['id']), 'name': data['name'], 'email': data.get('email'), 'preferred_username': data['login'], 'profile': data['html_url'], 'picture': data['avatar_url'], 'website': data.get('blog'), } # The email can be be None despite the scope being 'user:email'. # That is because a user can choose to make his/her email private. # If that is the case we get all the users emails regardless if private or note # and use the one he/she has marked as `primary` if params.get('email') is None: resp = self.get('user/emails', **kwargs) resp.raise_for_status() data = resp.json() params["email"] = next(email['email'] for email in data if email['primary']) return UserInfo(params)

[ "me@lepture.com" ]

me@lepture.com

ee32eb4c5bf0fa3b9827e0a11a8b943fbb9b709d

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/codingtest/findCityBJ18352.py

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[]

no_license

jewerlykim/python_Algorithm

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e83b7e8fc58807ebf05f423d962ad9ce37100ada

refs/heads/main

2023-08-22T10:23:29.764080

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import sys from collections import deque # sys.stdin = open("/Users/jewerlykim/Desktop/python_Algorithm/codingtest/18352.txt", 'r') cityNumber, roadNumber, distance, startCityNumber = map(int, sys.stdin.readline().split()) graph = [[] for _ in range(cityNumber+1)] visited = [False for _ in range(cityNumber+1)] distanceGraph = [0 for _ in range(cityNumber+1)] for _ in range(roadNumber): departure, arrive = map(int, sys.stdin.readline().split()) graph[departure].append(arrive) def bfs(startCityNumber): queue = deque() queue.append(startCityNumber) visited[startCityNumber] = True while queue: city = queue.popleft() for i in graph[city]: if visited[i] == False: queue.append(i) visited[i] = True distanceGraph[i] = distanceGraph[city] + 1 bfs(startCityNumber) exist = False for i, value in enumerate(distanceGraph): if value == distance: print(i) exist = True if not exist: print(-1)

[ "jsjs21good@gmail.com" ]

jsjs21good@gmail.com

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c929632612012a436fdec27771a6a8716cdb24bf

/setup.py

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[]

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imclab/python-ucto

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a07e87f568cdb342b84f7b76e9f466d507567211

refs/heads/master

2021-01-14T10:30:27.892695

2016-03-10T14:49:58

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#!/usr/bin/env python from distutils.core import setup, Extension from Cython.Distutils import build_ext import glob import os import sys from os.path import expanduser HOMEDIR = expanduser("~") VERSION = '0.3.0' includedirs = [HOMEDIR + '/local/include/','/usr/include/', '/usr/include/libxml2','/usr/local/include/' ] libdirs = [HOMEDIR + '/local/lib/','/usr/lib','/usr/local/lib'] if 'VIRTUAL_ENV' in os.environ: includedirs.insert(0,os.environ['VIRTUAL_ENV'] + '/include') libdirs.insert(0,os.environ['VIRTUAL_ENV'] + '/lib') if sys.version < '3': extensions = [ Extension("ucto", [ "libfolia_classes.pxd", "ucto_classes.pxd", "ucto_wrapper2.pyx"], language='c++', include_dirs=includedirs, library_dirs=libdirs, libraries=['ucto','folia'], extra_compile_args=['--std=c++0x'], ) ] else: extensions = [ Extension("ucto", [ "libfolia_classes.pxd", "ucto_classes.pxd", "ucto_wrapper.pyx"], language='c++', include_dirs=includedirs, library_dirs=libdirs, libraries=['ucto','folia'], extra_compile_args=['--std=c++0x'], ) ] setup( name = 'python-ucto', version = VERSION, author = 'Maarten van Gompel', author_email = "proycon@anaproy.nl", description = ("This is a Python binding to the tokenizer Ucto. Tokenisation is one of the first step in almost any Natural Language Processing task, yet it is not always as trivial a task as it appears to be. This binding makes the power of the ucto tokeniser available to Python. Ucto itself is a regular-expression based, extensible, and advanced tokeniser written in C++ (https://languagemachines.github.io/ucto)."), license = "GPL", keywords = "tokenizer tokenization tokeniser tokenisation nlp computational_linguistics ucto", url = "https://github.com/proycon/python-ucto", ext_modules = extensions, cmdclass = {'build_ext': build_ext}, requires=['ucto (>=0.8.4)'], install_requires=['Cython'], classifiers=[ "Development Status :: 4 - Beta", "Topic :: Text Processing :: Linguistic", "Programming Language :: Cython", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Operating System :: POSIX", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", ], )

[ "proycon@anaproy.nl" ]

proycon@anaproy.nl