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import datetime from unittest import TestCase from apps.core.utils import convert_to_snake_case, chain, get_future_date class UtilsTestCase(TestCase): def test_get_future_date(self): now = datetime.datetime.now() future_date_str = get_future_date(60) extra_days = datetime.datetime.strptime(future_date_str, "%a, %d-%b-%Y %H:%M:%S GMT") - now # +- 1 day is acceptable here assert extra_days.days in range(59, 60) def test_convert_to_snake_case(self): test_string = "Some Test String" assert "some_test_string" == convert_to_snake_case(test_string) def test_chain(self): l1 = (1, 2, 3) l2 = [4, 5, 6] assert [*l1, *l2] == list(chain(l1, l2))
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# samples ratios SAMPLES_RATIO_01 = '5:1' SAMPLES_RATIO_02 = "39:1" SAMPLES_RATIO_03 = '50:1' # sampling strategy SS_ADASYN = 'ada_syn' SS_SMOTE = 'smote' SS_TOMEK = 'tomek' SS_ENN = 'smote_enn' SS_ROS = 'ros' SS_NONE = 'none' # base classifiers CLF_SVC = 'SVC' CLF_RF = 'RF' CLF_AB = 'AB' CLF_KNN = 'KNN' CLF_RUSBOOST = 'RUSB'
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import random import numpy as np import math import os import copy class Robot(object): def __init__(self, maze, alpha=0.5, gamma=0.9, epsilon0=0.5): self.maze = maze self.valid_actions = self.maze.valid_actions self.state = None self.action = None # Set Parameters of the Learning Robot self.alpha = alpha self.gamma = gamma self.epsilon0 = epsilon0 self.epsilon = epsilon0 self.t = 0 # sxn self.nS = self.maze.height * self.maze.width self.Qtable = {} self.reset() def reset(self): """ Reset the robot """ self.state = self.sense_state() self.create_Qtable_line(self.state) def set_status(self, learning=False, testing=False): """ Determine whether the robot is learning its q table, or exceuting the testing procedure. """ self.learning = learning self.testing = testing def update_parameter(self, step_times=None): """ Some of the paramters of the q learning robot can be altered, update these parameters when necessary. """ if self.testing: # TODO 1. No random choice when testing self.epsilon = 1.0 else: # TODO 2. Update parameters when learning if step_times != None: if step_times <= self.maze.height*self.maze.width: self.epsilon = 1.0/math.sqrt(self.t) else: self.epsilon = 1.0/math.log(self.t+1000,1000) else: if self.t < 10 * 1000: self.epsilon = 1.0/math.log(self.t+1000,1000) else : self.epsilon = 1.0/math.sqrt(self.t) return self.epsilon def sense_state(self): """ Get the current state of the robot. In this """ # TODO 3. Return robot's current state r, c = self.maze.robot['loc'] return r, c def create_Qtable_line(self, state): """ Create the qtable with the current state """ # TODO 4. Create qtable with current state # Our qtable should be a two level dict, # Qtable[state] ={'u':xx, 'd':xx, ...} # If Qtable[state] already exits, then do # not change it. if state not in self.Qtable: self.Qtable[state] = {a:0.0 for a in self.maze.valid_actions} pass def choose_action(self): """ Return an action according to given rules """ def is_random_exploration(): # TODO 5. Return whether do random choice # hint: generate a random number, and compare # it with epsilon return random.uniform(0,1) < self.epsilon action = None if self.learning: if is_random_exploration(): # TODO 6. Return random choose aciton action = np.random.choice(self.maze.valid_actions) else: # TODO 7. Return action with highest q value action = max(self.Qtable[self.state], key=self.Qtable[self.state].get) elif self.testing: # TODO 7. choose action with highest q value action = max(self.Qtable[self.state], key=self.Qtable[self.state].get) else: # TODO 6. Return random choose aciton action = np.random.choice(self.maze.valid_actions,\ p=get_epsilon_greedy_probs(self.state)) return action def update_Qtable(self, r, action, next_state): """ Update the qtable according to the given rule. """ if self.learning: # TODO 8. When learning, update the q table according # to the given rules QTable_next_state = max(list(self.Qtable[next_state].values())) self.Qtable[self.state][action] = (1 - self.alpha) * self.Qtable[self.state][action] + \ self.alpha * (r + self.gamma * QTable_next_state) def update(self, avg_step_times_last_10=None): """ Describle the procedure what to do when update the robot. Called every time in every epoch in training or testing. Return current action and reward. """ self.t += 1 self.state = self.sense_state() # Get the current state self.create_Qtable_line(self.state) # For the state, create q table line action = self.choose_action() # choose action for this state reward = self.maze.move_robot(action) # move robot for given action next_state = self.sense_state() # get next state self.create_Qtable_line(next_state) # create q table line for next state if self.learning and not self.testing: self.update_Qtable(reward, action, next_state) # update q table self.update_parameter(avg_step_times_last_10) # update parameters return action, reward def Qstate_to_file(self, file_name): f = open(file_name, 'w') for r in range(self.maze.height): for c in range(self.maze.width): if (r,c) in self.Qtable: f.writelines('({},{}): {}\n'.format(r, c, self.Qtable[(r,c)])) else: f.writelines('({},{}): {}\n'.format(r, c, 'NA')) f.close()
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# -*- coding: utf-8 -*- #COMECE AQUI ABAIXO idade = int(input('Digite sua idade')) if idade => 18: print ("maior de idade") else: print ('menor de idade')
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# Generated by Django 2.1 on 2020-02-25 09:37 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('app', '0005_auto_20200225_1615'), ] operations = [ migrations.AddField( model_name='usermanager', name='img', field=models.ImageField(blank=True, default='users/default.jpg', null=True, upload_to='users', verbose_name='用户头像'), ), ]
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# cs212 ; Problem Set 1 ; 2 # CS 212, hw1-2: Jokers Wild # # ----------------- # User Instructions # # Write a function best_wild_hand(hand) that takes as # input a 7-card hand and returns the best 5 card hand. # In this problem, it is possible for a hand to include # jokers. Jokers will be treated as 'wild cards' which # can take any rank or suit of the same color. The # black joker, '?B', can be used as any spade or club # and the red joker, '?R', can be used as any heart # or diamond. # # The itertools library may be helpful. Feel free to # define multiple functions if it helps you solve the # problem. # # ----------------- # Grading Notes # # Muliple correct answers will be accepted in cases # where the best hand is ambiguous (for example, if # you have 4 kings and 3 queens, there are three best # hands: 4 kings along with any of the three queens). import itertools def best_wild_hand(hand): "Try all values for jokers in all 5-card selections." # Your code here def test_best_wild_hand(): assert (sorted(best_wild_hand("6C 7C 8C 9C TC 5C ?B".split())) == ['7C', '8C', '9C', 'JC', 'TC']) assert (sorted(best_wild_hand("TD TC 5H 5C 7C ?R ?B".split())) == ['7C', 'TC', 'TD', 'TH', 'TS']) assert (sorted(best_wild_hand("JD TC TH 7C 7D 7S 7H".split())) == ['7C', '7D', '7H', '7S', 'JD']) return 'test_best_wild_hand passes' # ------------------ # Provided Functions # # You may want to use some of the functions which # you have already defined in the unit to write # your best_hand function. def hand_rank(hand): "Return a value indicating the ranking of a hand." ranks = card_ranks(hand) if straight(ranks) and flush(hand): return (8, max(ranks)) elif kind(4, ranks): return (7, kind(4, ranks), kind(1, ranks)) elif kind(3, ranks) and kind(2, ranks): return (6, kind(3, ranks), kind(2, ranks)) elif flush(hand): return (5, ranks) elif straight(ranks): return (4, max(ranks)) elif kind(3, ranks): return (3, kind(3, ranks), ranks) elif two_pair(ranks): return (2, two_pair(ranks), ranks) elif kind(2, ranks): return (1, kind(2, ranks), ranks) else: return (0, ranks) def card_ranks(hand): "Return a list of the ranks, sorted with higher first." ranks = ['--23456789TJQKA'.index(r) for r, s in hand] ranks.sort(reverse = True) return [5, 4, 3, 2, 1] if (ranks == [14, 5, 4, 3, 2]) else ranks def flush(hand): "Return True if all the cards have the same suit." suits = [s for r,s in hand] return len(set(suits)) == 1 def straight(ranks): """Return True if the ordered ranks form a 5-card straight.""" return (max(ranks)-min(ranks) == 4) and len(set(ranks)) == 5 def kind(n, ranks): """Return the first rank that this hand has exactly n-of-a-kind of. Return None if there is no n-of-a-kind in the hand.""" for r in ranks: if ranks.count(r) == n: return r return None def two_pair(ranks): """If there are two pair here, return the two ranks of the two pairs, else None.""" pair = kind(2, ranks) lowpair = kind(2, list(reversed(ranks))) if pair and lowpair != pair: return (pair, lowpair) else: return None
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import unicodedata from pathlib import Path class Common: def read_model(self, file): path = Path(__file__).parent.joinpath(file) with path.open(encoding="utf-8") as f: lines = unicodedata.normalize("NFC", f.read()).split("\n") return lines
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from __future__ import absolute_import, division, print_function, unicode_literals import fractions import math from six.moves import xrange # http://stackoverflow.com/questions/4798654/modular-multiplicative-inverse-function-in-python # from https://en.wikibooks.org/wiki/Algorithm_Implementation/Mathematics/Extended_Euclidean_algorithm def egcd(a, b): x, y, u, v = 0, 1, 1, 0 while a: q, r = b // a, b % a m, n = x - u*q, y - v*q b, a, x, y, u, v = a, r, u, v, m, n return b, x, y def modinv(a, m): g, x, y = egcd(a, m) if g == 1: return x % m raise Exception('modular inverse does not exist') def largest_invertible(x): """In the ring Mod(x), returns the invertible number nearest to x / 2, and its inverse.""" if x >= 5: for i in xrange(int(x / 2), 1, -1): try: ii = (i if i < (x / 2) else x - i) return ii, modinv(ii, x) except: pass return 1, 1
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# Intro to Computer Science # Build a Search Engine & a Social Network # https://www.udacity.com/course/intro-to-computer-science--cs101 #Lesson 1 Write your first computer program # Sergey Brin's advice on learning to program. # Get started on your first Python program. # How to create and use variables in Python. #Lesson 2 Write programs to do repeating work # Introducing procedures. # Sum procedure with a return statement. # Equality comparisons and more. #Lesson 3 How ot manage data # Nested lists. # A list of strings. # Aliasing and more. #Lesson 4 Responding to queries # Data structures. # Lookup. # Building the Web Index and more. #Lesson 5 How programs run # Measuring speed. # Spin loop. # Index size vs. time and more. #Lesson 6 How to have infinite power # Infinite power. # Counter. # Recursive definitions and more. ##################################################### # Lesson 1 Write your first computer program # This course will introduce you to the fundemental ideas of computing, and teach you to read and write your own programs. We are going to do this in the context of building a web search engine. # Computer science is about how to solve problems by breaking them up into smaller pieces. And then preciely and mechanically describing a sequence of steps to execute in order to solve these pieces. And these steps can be preformed by a computer. # Build a search engine # - Find data (web crawler) Units- 1-3 # - Building an index (respond to search quieries) - Units 4-5 # - Rank pages (to get best result) - Units 6 # Unit 1 Getting started - extracting the first link # Web crawler, start with one page (seed?) follow links, get many pages # A webpage is a text, a link is a special sequence of text print 3 print 2+3 # Bakus Naur Form, derivation: Non-terminal -> replacement # Grace Hopper and Augusta Ada King s = 'audacity' print "U" + s[2:] # Write Python code that assigns to the # variable url a string that is the value # of the first URL that appears in a link # tag in the string page. # Your code should print http://udacity.com # Make sure that if page were changed to # page = '<a href="http://udacity.com">Hello world</a>' # that your code still assigns the same value to the variable 'url', # and therefore still prints the same thing. # page = contents of a web page page =('<div id="top_bin"><div id="top_content" class="width960">' '<div class="udacity float-left"><a href="http://udacity.com">') start_link = page.find('<a href=') print start_link end_link = page.find('"', start_link+9) print end_link url = page[(start_link+9):end_link] print url ############################################### # Exercise by Websten from forums # ############################################### # To minimize errors when writing long texts with # complicated expressions you could replace # the tricky parts with a marker. # Write a program that takes a line of text and # finds the first occurrence of a certain marker # and replaces it with a replacement text. # The resulting line of text should be stored in a variable. # All input data will be given as variables. # # Replace the first occurrence of marker in the line below. # There will be at least one occurrence of the marker in the # line of text. Put the answer in the variable 'replaced'. # Hint: You can find out the length of a string by command # len(string). We might test your code with different markers! # Example 1 marker = "AFK" replacement = "away from keyboard" line = "I will now go to sleep and be AFK until lunch time tomorrow." marker_start = line.find(marker) marker_end = line.find(marker) + len(marker) replaced = line[:marker_start] + replacement + line[marker_end:] print replaced # Example 2 # uncomment this to test with different input marker = "EY" replacement = "Eyjafjallajokull" line = "The eruption of the volcano EY in 2010 disrupted air travel in Europe for 6 days." ### # YOUR CODE BELOW. DO NOT DELETE THIS LINE ### marker_start = line.find(marker) marker_end = line.find(marker) + len(marker) replaced = line[:marker_start] + replacement + line[marker_end:] print replaced # Example 1 output should be: #>>> I will now go to sleep and be away from keyboard until lunch time tomorrow. # Example 2 output should be: #>>> The eruption of the volcano Eyjafjallajokull in 2010 disrupted air travel in Europe for 6 days. ##################################################### # Lesson 2 Write programs to do repeating work # Procedures, like functions in R. Inputs -> Procedure -> Outputs # Control page =('<div id="top_bin"><div id="top_content" class="width960">' '<div class="udacity float-left"><a href="http://udacity.com">') start_link = page.find('<a href=') print start_link end_link = page.find('"', start_link+9) print end_link url = page[(start_link+9):end_link] print url # Procedures ##################################################### # Lesson 3 How ot manage data ##################################################### # Lesson 4 Responding to queries ##################################################### # Lesson 5 How programs run ##################################################### # Lesson 6 How to have infinite power
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bartzleby/mllib
b30973709de7f38688a5ef1031ed31879c820093
56c67027ef903a09bbe1936a986e4043801b8a4e
refs/heads/main
2023-04-22T13:36:36.713401
2021-05-07T15:47:47
2021-05-07T15:47:47
335,476,969
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null
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py
#!/usr/bin/env python3 # # CS5350 # Danny Bartz # March, 2021 # # bank-note meta data in python # dtype = 'float' features = ['variance', 'skewness', 'curtosis', 'entropy'] def labels_to_pmone(labels): '''map labels in {0, 1} to {-1,1} respectively. ''' # TODO: probably a better way.. for l in range(len(labels)): if labels[l]*1 < 0.1: labels[l] = -1 elif labels[l]-1 < 1e-6: labels[l] = 1 else: print('unexpected label!') print("label: ", labels[l]) return return labels
[ "bartzleby@gmail.com" ]
bartzleby@gmail.com
d242fc244edeb09b0c77a69cefb7db4c2ecc9864
b228d361a1256d0d168fc45f973b90ae4afe5737
/deprecated/scratch_B120_B122.py
110283de7ee9b942a8319b964126d99d02e506df
[]
no_license
mjstarke/globe-QA
0c69d3c50a697401ac2e257276d2080c6dfcfbd6
8e8ab5c0db3fe0b96180ed98b8889ef01b148401
refs/heads/master
2022-07-07T14:49:17.150402
2019-08-09T16:02:32
2019-08-09T16:02:32
192,923,326
1
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null
2022-06-21T22:27:49
2019-06-20T13:17:44
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# DEPRECATED: This script is superseded partially by figure_S017. from figure_common import * globe_categories = [None, "none", "few", "isolated", "scattered", "broken", "overcast", "obscured"] globe_labels = ["null", "none", "few", "isolated", "scattered", "broken", "overcast", "obscured"] geos_categories = ["none", "few", "isolated", "scattered", "broken", "overcast"] geos_labels = ["none", "few", "isolated", "scattered", "broken", "overcast"] obs = tools.parse_csv(fp_obs_with_satellite_matches_2018) ######################################################################################################################## cdf_jan = Dataset(fp_GEOS_Jan) obs_jan = tools.filter_by_datetime(obs, earliest=tools.get_cdf_datetime(cdf_jan, 0) - timedelta(minutes=30), latest=tools.get_cdf_datetime(cdf_jan, -1) + timedelta(minutes=30)) for ob in tqdm(obs_jan, desc="Gathering coincident GEOS output"): ob.tcc_geos = cdf_jan["CLDTOT"][tools.find_closest_gridbox(cdf_jan, ob.measured_dt, ob.lat, ob.lon)] ob.tcc_geos_category = tools.bin_cloud_fraction(ob.tcc_geos, True) ######################################################################################################################## absolute_jan = np.zeros((6, 8)) for ob in obs_jan: x = geos_categories.index(ob.tcc_geos_category) y = globe_categories.index(ob.tcc) absolute_jan[x, y] += 1 rowwise_jan = absolute_jan / absolute_jan.sum(axis=0, keepdims=True) columnwise_jan = absolute_jan / absolute_jan.sum(axis=1, keepdims=True) ######################################################################################################################## fig = plt.figure(figsize=(14, 7)) ax1 = fig.add_subplot(131) ax2 = fig.add_subplot(132) ax3 = fig.add_subplot(133) plotters.plot_annotated_heatmap(absolute_jan, geos_labels, globe_labels, text_color_threshold=1000, ax=ax1) ax1.set_xlabel("GEOS total cloud cover") ax1.set_ylabel("GLOBE total cloud cover") plt.tight_layout() plotters.plot_annotated_heatmap(columnwise_jan, geos_labels, ["" for _ in globe_labels], text_color_threshold=0.4, text_formatter="{:.2%}", ax=ax2) ax2.set_xlabel("GEOS total cloud cover") ax2.yaxis.set_ticks_position("none") plt.tight_layout() plotters.plot_annotated_heatmap(rowwise_jan, geos_labels, globe_labels, text_color_threshold=0.4, text_formatter="{:.2%}", ax=ax3) ax3.set_xlabel("GEOS total cloud cover") ax3.yaxis.set_ticks_position("right") plt.tight_layout() ######################################################################################################################## cdf_jul = Dataset(fp_GEOS_Jul) obs_jul = tools.filter_by_datetime(obs, earliest=tools.get_cdf_datetime(cdf_jul, 0) - timedelta(minutes=30), latest=tools.get_cdf_datetime(cdf_jul, -1) + timedelta(minutes=30)) for ob in tqdm(obs_jul, desc="Gathering coincident GEOS output"): ob.tcc_geos = cdf_jul["CLDTOT"][tools.find_closest_gridbox(cdf_jul, ob.measured_dt, ob.lat, ob.lon)] ob.tcc_geos_category = tools.bin_cloud_fraction(ob.tcc_geos, True) ######################################################################################################################## absolute_jul = np.zeros((6, 8)) for ob in obs_jul: x = geos_categories.index(ob.tcc_geos_category) y = globe_categories.index(ob.tcc) absolute_jul[x, y] += 1 rowwise_jul = absolute_jul / absolute_jul.sum(axis=0, keepdims=True) columnwise_jul = absolute_jul / absolute_jul.sum(axis=1, keepdims=True) ######################################################################################################################## fig = plt.figure(figsize=(14, 7)) ax1 = fig.add_subplot(131) ax2 = fig.add_subplot(132) ax3 = fig.add_subplot(133) plotters.plot_annotated_heatmap(absolute_jul, geos_labels, globe_labels, text_color_threshold=800, ax=ax1) ax1.set_xlabel("GEOS total cloud cover") ax1.set_ylabel("GLOBE total cloud cover") plt.tight_layout() plotters.plot_annotated_heatmap(columnwise_jul, geos_labels, ["" for _ in globe_labels], text_color_threshold=0.4, text_formatter="{:.2%}", ax=ax2) ax2.set_xlabel("GEOS total cloud cover") ax2.yaxis.set_ticks_position("none") plt.tight_layout() plotters.plot_annotated_heatmap(rowwise_jul, geos_labels, globe_labels, text_color_threshold=0.4, text_formatter="{:.2%}", ax=ax3) ax3.set_xlabel("GEOS total cloud cover") ax3.yaxis.set_ticks_position("right") plt.tight_layout() ######################################################################################################################## fig = plt.figure(figsize=(14, 7)) ax1 = fig.add_subplot(131) ax2 = fig.add_subplot(132) ax3 = fig.add_subplot(133) plotters.plot_annotated_heatmap(absolute_jul - absolute_jan, geos_labels, globe_labels, text_color_threshold=-600, ax=ax1, cmap="bwr") ax1.set_xlabel("GEOS total cloud cover") ax1.set_ylabel("GLOBE total cloud cover") plt.tight_layout() plotters.plot_annotated_heatmap(columnwise_jul - columnwise_jan, geos_labels, ["" for _ in globe_labels], text_color_threshold=-5, text_formatter="{:.2%}", ax=ax2, cmap="bwr", vmin=-.3, vmax=.3) ax2.set_xlabel("GEOS total cloud cover") ax2.yaxis.set_ticks_position("none") plt.tight_layout() plotters.plot_annotated_heatmap(rowwise_jul - rowwise_jan, geos_labels, globe_labels, text_color_threshold=-0.2, text_formatter="{:.2%}", ax=ax3, cmap="bwr", vmin=-.3, vmax=.3) ax3.set_xlabel("GEOS total cloud cover") ax3.yaxis.set_ticks_position("right") plt.tight_layout()
[ "matthew.j.starke@nasa.gov" ]
matthew.j.starke@nasa.gov
bcbcb90c7cf3f44d39c8b7ada7255ad68f25b3f9
a20be0bd31e0ba46806d605cd4b852008b6a7141
/New Fancy PWM motor/PWM with AND enable/desperation.py
ebc72d5b7795ac273868779d161f1dcc627b768c
[]
no_license
systemetric/hr-brain-2018
7dd367baf1bc348a735ec4ed1e604cabb38813af
5a209e43ae03efd48f28d93571ddc0333fbeac0e
refs/heads/master
2021-09-07T23:41:59.379209
2018-03-03T10:52:42
2018-03-03T10:52:42
null
0
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null
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import time from sr.robot import * robot = Robot() robot.motors[0].m0.power = 50 robot.motors[0].m1.power = -50 time.sleep(1) robot.motors[0].m0.power = 20 robot.motors[0].m1.power = -20
[ "jacklarkin241@gmail.com" ]
jacklarkin241@gmail.com
b8a88b113dc2f9df1412f3ceecd57bcfb7d140af
a87a7a4bce23ee1ade177b8ceb7fe82d4737f837
/month04/django/day04/mysite4/bookstore/models.py
97cfdd1568219b76f704b8ac6182b2d0c72e3761
[]
no_license
ywzq87bzx/code
3d9f9579f842216bb2afbaaf52e9678c25bcfd92
e77cf592b1dd1239daa0f1cba1591e9a03fb550d
refs/heads/main
2023-02-18T10:27:21.132762
2021-01-22T09:58:35
2021-01-22T09:58:35
326,974,212
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from django.db import models # Create your models here. class Book(models.Model): title=models.CharField('书名',max_length=30) price=models.DecimalField('定价',max_digits=5,decimal_places=2) market_price=models.DecimalField('零售价',max_digits=5,decimal_places=2) pub=models.CharField('出版社',max_length=30)
[ "1070727987@qq.com" ]
1070727987@qq.com
5f6883e8c0e6b0a1c622e7cab2a1c38ef0de001a
785c66f17fb44a43582f3af5291f5e46d7d76f6b
/main.py
2ecae00dec131e26e408e380ccb196e9ba8f9f83
[]
no_license
jamcmich/python-ftp-client
b77c200299dfff7468140eba282f4485704dae0b
432adb1bd1a96c5bc28aaa6c8bf9c48354b5a9ea
refs/heads/main
2023-07-31T03:15:44.115569
2021-09-23T21:00:21
2021-09-23T21:00:21
406,514,055
0
0
null
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UTF-8
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# ----- Connecting to an FTP Server ----- # We will connect anonymously to Port 21 - Default FTP Port # Anonymous FTP Connection # Use an anonymous login to the FTP server. from ftplib import FTP try: print("\nAttempting anonymous login...") with FTP("ftp.dlptest.com") as ftp: print(f"\t{ftp.getwelcome()}") # A "with" statement will automatically close the connection when it reaches the end of the code block. except Exception as e: print(f"\tException... {e}") else: print("\tSuccess!") # Authenticated Login # Use an authenticated login to the FTP server using two different methods. # Method #1: Passing in the 'user' and 'passwd' parameters to the 'FTP()' constructor. # Note: I've intentionally passed in the wrong credentials for this example. try: print("\nMethod #1\n\tAttempting authenticated connection with login details...") with FTP(host="ftp.dlptest.com", user="user", passwd="password") as ftp: print(f"\t{ftp.getwelcome()}") except Exception as e: print(f"\tException... {e}") else: print("\tSuccess!") # Method #2: Calling 'connect()' and 'login()'. try: print("\nMethod #2\n\tAttempting authenticated connection with login details...") ftp = FTP() ftp.connect("ftp.dlptest.com") ftp.login("dlpuser", "rNrKYTX9g7z3RgJRmxWuGHbeu") print(f"\t{ftp.getwelcome()}") ftp.close() except Exception as e: print(f"\tException... {e}") else: print("\tSuccess!") # Connection with SSL/TLS Over Default Port 21 from ftplib import FTP_TLS try: print( "\nConnection with SSL/TLS\n\tAttempting authenticated connection with login details..." ) with FTP_TLS("ftp.dlptest.com", "dlpuser", "rNrKYTX9g7z3RgJRmxWuGHbeu") as ftp: print(f"\t{ftp.getwelcome()}") except Exception as e: print(f"\tException... {e}") else: print("\tSuccess!") # ----- Working with Directories ----- # Printing the current working directory. try: print( "\nConnection with SSL/TLS\n\tAttempting authenticated connection with login details..." ) with FTP_TLS("ftp.dlptest.com", "dlpuser", "rNrKYTX9g7z3RgJRmxWuGHbeu") as ftp: print(f"\t{ftp.pwd()}") # Usually the default is / try: ftp.mkd("my_dir") # Make a directory print("\tMade a new directory.") except Exception as e: print(f"\tException... {e}") try: ftp.rmd("my_dir") # Remove a directory print("\tRemoved the directory.") except Exception as e: print(f"\tException... {e}") try: ftp.cwd("other_dir") # Change current working directory print("\tChanged the current working directory.") except Exception as e: print(f"\tException... {e}") try: # Listing directory files # files = [] # ftp.dir(files.append) # Takes a callback for each file # for file in files: # print(f"\tfile") for name in ftp.nlst(): print(f"\t{name}") except Exception as e: print(f"\tException... {e}") except Exception as e: print(f"\tException... {e}") # ----- Working with Files ----- try: print( "\nConnection with SSL/TLS\n\tAttempting authenticated connection with login details..." ) with FTP_TLS("ftp.dlptest.com", "dlpuser", "rNrKYTX9g7z3RgJRmxWuGHbeu") as ftp: print(f"\tAttempting to upload test files.") # Upload a test file. # For text or binary file, always use `rb` print(f"\nUploading text file...") with open("text.txt", "rb") as text_file: ftp.storlines( "STOR text.txt", text_file ) # 'storlines()' should not be used to transfer binary files print(f"\tUploading image file...") with open("cat_image.jpg", "rb") as image_file: ftp.storbinary("STOR cat_image.jpg", image_file) print(f"\tSuccessfully uploaded test files.") print(f"\tGetting a list of new files...") for name in ftp.nlst(): print(f"\t{name}") # Get the size of a file. print(f"\nGetting file size...") try: ftp.sendcmd('TYPE I') # 'TYPE I' denotes an image or binary data print(ftp.size('\tImage size in bytes:' + 'cat_image.jpg')) except Exception as e: print(f"\tError checking image size: {e}") # Rename a file. print(f"\nRenaming file...") try: ftp.rename('cat_image.jpg', 'cat.jpg') # Change 'cat_image.jpg' to 'cat.jpg' print('\tSuccessfully renamed file!') except Exception as e: print(f"\tError renaming file: {e}") # Download a file. print(f"\nDownloading file...") with open("local_text.txt", "w") as local_file: # Open local file for writing response = ftp.retrlines('RETR text.txt', local_file.write) # Check the response code print(f"\tChecking response code...") # https://en.wikipedia.org/wiki/List_of_FTP_server_return_codes if response.startswith('226'): # Transfer complete print('\tTransfer complete.') else: print('\tError transferring. Local file may be incomplete or corrupt.') except Exception as e: print(f"\tException... {e}")
[ "jacobmcmichael@gmail.com" ]
jacobmcmichael@gmail.com
55d29e8a29c50328f21cb3ebad13224f1f616e71
4e7f16f67b52155b21c7eeb023f2f60f5b3d5c0d
/pynexradml/trainer.py
cb658b868954d8f459f71cce5609b8126b5a6dd0
[]
no_license
DailyActie/AI_APP_HYD-py-nexrad-ml
26b3d6202ae90bbe16e5c520d18ac07d2cd49778
bdee8f72cbcf6728deec796e41a70c254b327e75
refs/heads/master
2020-12-12T02:04:26.811108
2012-11-28T02:22:08
2012-11-28T02:22:08
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from __future__ import division import random import numpy as np import ffnn import preprocessor import datastore import cache from config import NexradConfig def printStats(tp, tn, fp, fn, mse): accuracy = (tp + tn) / (tp + tn + fp + fn) precision = 0.0 if (tp + fp) == 0 else tp / (tp + fp) recall = 0.0 if (tp + fn) == 0 else tp / (tp + fn) f1 = 0.0 if (precision + recall) == 0 else 2 * (precision * recall) / (precision + recall) print "---------------------------------" print "Classifier Performance:" print "" print " Confusion Matrix" print " TP | FP " print " +---------------------+" print " |%10d|%10d|" % (tp, fp) print " |%10d|%10d|" % (fn, tn) print " +---------------------+" print " FN | TN " print "" print " - Accuracy = %.3f" % accuracy print " - Precision = %.3f" % precision print " - Recall = %.3f" % recall print " - F1 = %.3f" % f1 print " - MSE = %.3f" % mse print "---------------------------------" if __name__ == "__main__": import argparse, os parser = argparse.ArgumentParser(description='Build and validate classifiers') parser.add_argument('-a', '--arch', help="Network Architecture e.g. 3,2,1 for 3 inputs, 2 hidden nodes and 1 output") parser.add_argument('--cache', action='store_true', help='Cache data to disk to allow for more data than can fit in memory.') parser.add_argument('-d', '--data_dir', help='Directory containing datastore') parser.add_argument('--epochs', type=int, help='Number of epochs for training a neural network') parser.add_argument('-f', '--config_file', default='pynexrad.cfg', help='override default pynexrad.cfg config file') parser.add_argument('--features', nargs='*', help='Features to include (e.g. ref, vel, sw)') parser.add_argument('--filters', nargs='*', help='Filters to include (e.g. min_range_20km, no_bad_ref, su)') parser.add_argument('--norm', nargs='*', help='Normalizers to use (e.g. SymmetricNormalizer(0,1,2))') parser.add_argument('-t', '--training_data', nargs='*', help='Datasets to use for training data (e.g. rd1 rd2)') parser.add_argument('-o', '--output', help='Save classifier to an output file (e.g. nn.ml)') parser.add_argument('-v', '--verbose', action='store_true', help='Show verbose output') args = parser.parse_args() config = NexradConfig(args.config_file, "trainer") dataDir = config.getOverrideOrConfig(args, 'data_dir') ds = datastore.Datastore(dataDir) #Get Data sweeps = [] for dataset in config.getOverrideOrConfigAsList(args, 'training_data'): sweeps += [(dataset, x[0], x[1]) for x in ds.getManifest(dataset)] processor = preprocessor.Preprocessor() for f in config.getOverrideOrConfigAsList(args, 'features'): print "Adding Feature %s to Preprocessor" % f processor.createAndAddFeature(f) for f in config.getOverrideOrConfigAsList(args, 'filters'): print "Adding Filter %s to Preprocessor" % f processor.createAndAddFilter(f) for n in config.getOverrideOrConfigAsList(args, 'norm'): print "Adding Normalizer %s to Preprocessor" % n processor.createAndAddNormalizer(n) useCache = config.getOverrideOrConfigAsBool(args, 'cache') if useCache: cache = cache.Cache(dataDir) instances = cache.createDiskArray("temp_data", len(processor.featureKeys) + 1) else: instances = [] print "Loading Data..." for sweep in sweeps: print "Constructing Data for %s, Class = %s" % (sweep[1], sweep[2]) instance = processor.processData(ds.getData(sweep[0], sweep[1])) instances.append(np.hstack([instance, np.ones((instance.shape[0], 1)) * float(sweep[2])])) if useCache: composite = instances else: composite = np.vstack(instances) print "Normalizing Data..." data = processor.normalizeData(composite) def shuffle(index): global data for x in xrange(0, index): i = (index - 1 - x) j = random.randint(0, i) tmp = np.array(data[i, :]) data[i, :] = data[j, :] data[j, :] = tmp #np.random.shuffle(data) shuffle(len(data)) validationIndex = int(len(data) * 0.9) archConfig = config.getOverrideOrConfig(args, 'arch') if archConfig != None: arch = [int(x) for x in archConfig.split(',')] else: nodes = len(data[0]) - 1 arch = [nodes, nodes // 2, 1] network = ffnn.FeedForwardNeuralNet(layers=arch) def customLearningGen(): if network.shuffle: shuffle(validationIndex) for i in xrange(0,validationIndex): yield(data[i, :-1], data[i, -1]) def customValidationGen(): for i in xrange(validationIndex, len(data)): yield(data[i, :-1], data[i, -1]) network.learningGen = customLearningGen network.validationGen = customValidationGen network.shuffle = True network.momentum = 0.1 network.verbose = config.getOverrideOrConfigAsBool(args, 'verbose') print "Learning Network, Architecture = %s..." % arch network.learn(0.03, config.getOverrideOrConfigAsInt(args, 'epochs')) tp, tn, fp, fn, count = (0, 0, 0, 0, 0) def callback(inputs, target, output): global tp global tn global fp global fn global count if output > 0: output = 1 elif output <= 0: output = -1 target = int(target) if target == 1 and output == 1: tp += 1 elif target == 1 and output != 1: fn += 1 elif target == -1 and output == -1: tn += 1 elif target == -1 and output != -1: fp += 1 count += 1 mse = network.validate(callback) printStats(tp, tn, fp, fn, mse) output = config.getOverrideOrConfig(args, 'output') if output != None: print "Saving Network to %s" % (output + ".net") network.save(output + ".net") print "Saving Preprocessor to %s" % (output + ".proc") processor.save(output + ".proc") if useCache: cache.close()
[ "reggiemead@gmail.com" ]
reggiemead@gmail.com
33791d780f140caa7af658d364f82aa0c8a86f28
aa1972e6978d5f983c48578bdf3b51e311cb4396
/nitro-python-1.0/nssrc/com/citrix/netscaler/nitro/resource/config/cluster/clusternodegroup_streamidentifier_binding.py
e684932798111ad39584954df57a8ca7c17454bc
[ "Python-2.0", "Apache-2.0", "LicenseRef-scancode-unknown-license-reference" ]
permissive
MayankTahil/nitro-ide
3d7ddfd13ff6510d6709bdeaef37c187b9f22f38
50054929214a35a7bb19ed10c4905fffa37c3451
refs/heads/master
2020-12-03T02:27:03.672953
2017-07-05T18:09:09
2017-07-05T18:09:09
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2017-07-05T16:51:29
2017-07-01T01:03:20
HTML
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# # Copyright (c) 2008-2016 Citrix Systems, Inc. # # 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 nssrc.com.citrix.netscaler.nitro.resource.base.base_resource import base_resource from nssrc.com.citrix.netscaler.nitro.resource.base.base_resource import base_response from nssrc.com.citrix.netscaler.nitro.service.options import options from nssrc.com.citrix.netscaler.nitro.exception.nitro_exception import nitro_exception from nssrc.com.citrix.netscaler.nitro.util.nitro_util import nitro_util class clusternodegroup_streamidentifier_binding(base_resource) : """ Binding class showing the streamidentifier that can be bound to clusternodegroup. """ def __init__(self) : self._identifiername = None self._name = None self.___count = 0 @property def name(self) : r"""Name of the nodegroup to which you want to bind a cluster node or an entity.<br/>Minimum length = 1. """ try : return self._name except Exception as e: raise e @name.setter def name(self, name) : r"""Name of the nodegroup to which you want to bind a cluster node or an entity.<br/>Minimum length = 1 """ try : self._name = name except Exception as e: raise e @property def identifiername(self) : r"""stream identifier and rate limit identifier that need to be bound to this nodegroup. """ try : return self._identifiername except Exception as e: raise e @identifiername.setter def identifiername(self, identifiername) : r"""stream identifier and rate limit identifier that need to be bound to this nodegroup. """ try : self._identifiername = identifiername except Exception as e: raise e def _get_nitro_response(self, service, response) : r""" converts nitro response into object and returns the object array in case of get request. """ try : result = service.payload_formatter.string_to_resource(clusternodegroup_streamidentifier_binding_response, response, self.__class__.__name__) if(result.errorcode != 0) : if (result.errorcode == 444) : service.clear_session(self) if result.severity : if (result.severity == "ERROR") : raise nitro_exception(result.errorcode, str(result.message), str(result.severity)) else : raise nitro_exception(result.errorcode, str(result.message), str(result.severity)) return result.clusternodegroup_streamidentifier_binding except Exception as e : raise e def _get_object_name(self) : r""" Returns the value of object identifier argument """ try : if self.name is not None : return str(self.name) return None except Exception as e : raise e @classmethod def add(cls, client, resource) : try : if resource and type(resource) is not list : updateresource = clusternodegroup_streamidentifier_binding() updateresource.name = resource.name updateresource.identifiername = resource.identifiername return updateresource.update_resource(client) else : if resource and len(resource) > 0 : updateresources = [clusternodegroup_streamidentifier_binding() for _ in range(len(resource))] for i in range(len(resource)) : updateresources[i].name = resource[i].name updateresources[i].identifiername = resource[i].identifiername return cls.update_bulk_request(client, updateresources) except Exception as e : raise e @classmethod def delete(cls, client, resource) : try : if resource and type(resource) is not list : deleteresource = clusternodegroup_streamidentifier_binding() deleteresource.name = resource.name deleteresource.identifiername = resource.identifiername return deleteresource.delete_resource(client) else : if resource and len(resource) > 0 : deleteresources = [clusternodegroup_streamidentifier_binding() for _ in range(len(resource))] for i in range(len(resource)) : deleteresources[i].name = resource[i].name deleteresources[i].identifiername = resource[i].identifiername return cls.delete_bulk_request(client, deleteresources) except Exception as e : raise e @classmethod def get(cls, service, name="", option_="") : r""" Use this API to fetch clusternodegroup_streamidentifier_binding resources. """ try : if not name : obj = clusternodegroup_streamidentifier_binding() response = obj.get_resources(service, option_) else : obj = clusternodegroup_streamidentifier_binding() obj.name = name response = obj.get_resources(service) return response except Exception as e: raise e @classmethod def get_filtered(cls, service, name, filter_) : r""" Use this API to fetch filtered set of clusternodegroup_streamidentifier_binding resources. Filter string should be in JSON format.eg: "port:80,servicetype:HTTP". """ try : obj = clusternodegroup_streamidentifier_binding() obj.name = name option_ = options() option_.filter = filter_ response = obj.getfiltered(service, option_) return response except Exception as e: raise e @classmethod def count(cls, service, name) : r""" Use this API to count clusternodegroup_streamidentifier_binding resources configued on NetScaler. """ try : obj = clusternodegroup_streamidentifier_binding() obj.name = name option_ = options() option_.count = True response = obj.get_resources(service, option_) if response : return response[0].__dict__['___count'] return 0 except Exception as e: raise e @classmethod def count_filtered(cls, service, name, filter_) : r""" Use this API to count the filtered set of clusternodegroup_streamidentifier_binding resources. Filter string should be in JSON format.eg: "port:80,servicetype:HTTP". """ try : obj = clusternodegroup_streamidentifier_binding() obj.name = name option_ = options() option_.count = True option_.filter = filter_ response = obj.getfiltered(service, option_) if response : return response[0].__dict__['___count'] return 0 except Exception as e: raise e class clusternodegroup_streamidentifier_binding_response(base_response) : def __init__(self, length=1) : self.clusternodegroup_streamidentifier_binding = [] self.errorcode = 0 self.message = "" self.severity = "" self.sessionid = "" self.clusternodegroup_streamidentifier_binding = [clusternodegroup_streamidentifier_binding() for _ in range(length)]
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def full_name(first, last): print(f'{first} {last}') full_name('Kristine', 'Hudgens') def auth(email, password): if email == 'kristine@hudgens.com' and password == 'secret': print('You are authorized') else: print('You are not authorized') auth('kristine@hudgens.com', 'asdf') def hundred(): for num in range(1, 101): print(num) hundred() def counter(max_value): for num in range(1, max_value): print(num) counter(501)
[ "jedthompson@gmail.com" ]
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jofrankiewicz/AnalizaEMG
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import pandas as pd import seaborn as sns import matplotlib.pyplot as plt import numpy as np from convert import array_from_dat_file def left_or_right(array): srednia = np.mean(array) if srednia > 0: return 'right' elif srednia < 0: return 'left' def top_or_bottom(array, hand): ix = [] for i in range(len(array) - 1): if(array[i] != array[i + 1]): ix.append(i) for i in ix[0:-1]: t1 = np.take(array, range(i, i + 50)) t2 = np.take(array, range(i + 50, i + 100)) if np.mean(t1) > np.mean(t2): if hand == 'right': return 'bottom' elif hand == 'left': return 'top' elif np.mean(t1) < np.mean(t2): if hand == 'right': return 'top' elif hand == 'left': return 'bottom' file = '2017-12-13 00-46-24 EgzoDynamicReversalExercise Position.dat' array = array_from_dat_file(file) which_hand = left_or_right(array) destination = top_or_bottom(array, which_hand)
[ "joannadariafrankiewicz@gmail.com" ]
joannadariafrankiewicz@gmail.com
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/loader_functions/data_loaders.py
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import os import shelve def save_level(player,game_map,dungeon_level): with shelve.open('level{0}{1}'.format(player.name,dungeon_level), 'n') as data_file: data_file['game_map'] = game_map def save_entities(player,entities,dungeon_level): with shelve.open('entities{0}{1}'.format(player.name,dungeon_level), 'n') as data_file: entities.remove(player) data_file['entities'] = entities entities.append(player) def load_level(player,dungeon_level): if not os.path.isfile('level{0}{1}.dat'.format(player.name,dungeon_level)): raise FileNotFoundError with shelve.open('level{0}{1}'.format(player.name, dungeon_level), 'r') as data_file: game_map = data_file['game_map'] return game_map def load_entities(player,dungeon_level): if not os.path.isfile('entities{0}{1}.dat'.format(player.name,dungeon_level)): raise FileNotFoundError with shelve.open('entities{0}{1}'.format(player.name, dungeon_level), 'r') as data_file: entities = data_file['entities'] return entities def save_game(player, entities, game_map, message_log, game_state): with shelve.open('savegame.dat', 'n') as data_file: data_file['player_index'] = entities.index(player) data_file['entities'] = entities data_file['game_map'] = game_map data_file['message_log'] = message_log data_file['game_state'] = game_state def load_game(): if not os.path.isfile('savegame.dat'): raise FileNotFoundError with shelve.open('savegame.dat', 'r') as data_file: player_index = data_file['player_index'] entities = data_file['entities'] game_map = data_file['game_map'] message_log = data_file['message_log'] game_state = data_file['game_state'] player = entities[player_index] return player, entities, game_map, message_log, game_state
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FatBunny13.noreply@github.com
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/mlonmcu/platform/espidf/__init__.py
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permissive
tum-ei-eda/mlonmcu
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# # Copyright (c) 2022 TUM Department of Electrical and Computer Engineering. # # This file is part of MLonMCU. # See https://github.com/tum-ei-eda/mlonmcu.git for further info. # # 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. # """MLonMCU ESP-IDF platform""" # pylint: disable=wildcard-import, redefined-builtin from .espidf import EspIdfPlatform __all__ = ["EspIdfPlatform"]
[ "philipp.van-kempen@tum.de" ]
philipp.van-kempen@tum.de
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/enemy.py
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[]
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import pygame from random import * # 创建随机数模块 class SmallEnemy(pygame.sprite.Sprite): def __init__(self, bg_size): # 构造函数,传入对象和背景大小 pygame.sprite.Sprite.__init__(self) # 调用父类(Sprite)的构造函数 self.image = pygame.image.load("images/enemy1.png").convert_alpha() # 创建图像 # 加载摧毁图片 self.destroy_images = [] self.destroy_images.extend([\ pygame.image.load("images/enemy1_down1.png").convert_alpha(), \ pygame.image.load("images/enemy1_down2.png").convert_alpha(), \ pygame.image.load("images/enemy1_down3.png").convert_alpha(), \ pygame.image.load("images/enemy1_down4.png").convert_alpha() \ ]) self.rect = self.image.get_rect() # 获取具有图像尺寸的矩形对象 self.width, self.height = bg_size[0], bg_size[1] # 矩形的长和宽赋初值 self.speed = 3 # 敌机的速度 self.active = True #表示当前飞机存活或摧毁 self.rect.left, self.rect.top = \ randint(0, self.width - self.rect.width), \ randint(-5 * self.height, 0) # 随机敌机的位置,高度为负数,一开始未显示成在界面中,但是已经生成 self.mask = pygame.mask.from_surface(self.image) # 取对象图片中非透明部分 def move(self): # 敌机移动函数 if self.rect.top < self.height: # 未到底部就一直向下走 self.rect.top += self.speed else : self.reset()# 否则出界,重新初始化 def reset(self): # 敌机重新初始化函数 self.active = True self.rect.left, self.rect.top = \ randint(0, self.width - self.rect.width), \ randint(-5 * self.height, 0) # 随机敌机的位置,高度为负数,一开始未显示成在界面中,但是已经生成 class MidEnemy(pygame.sprite.Sprite): energy = 8 # 中型飞机的血量 def __init__(self, bg_size): # 构造函数,传入对象和背景大小 pygame.sprite.Sprite.__init__(self) # 调用父类(Sprite)的构造函数 self.image = pygame.image.load("images/enemy2.png").convert_alpha() # 创建图像 # 加载被击中时的图片 self.image_hit = pygame.image.load("images/enemy2_hit.png").convert_alpha() # 加载摧毁图片 self.destroy_images = [] self.destroy_images.extend([\ pygame.image.load("images/enemy2_down1.png").convert_alpha(), \ pygame.image.load("images/enemy2_down2.png").convert_alpha(), \ pygame.image.load("images/enemy2_down3.png").convert_alpha(), \ pygame.image.load("images/enemy2_down4.png").convert_alpha() \ ]) self.rect = self.image.get_rect() # 获取具有图像尺寸的矩形对象 self.width, self.height = bg_size[0], bg_size[1] # 矩形的长和宽赋初值 self.speed = 2 # 敌机的速度 self.active = True #表示当前飞机存活或摧毁 self.rect.left, self.rect.top = \ randint(0, self.width - self.rect.width), \ randint(-10 * self.height, -self.height) # 随机敌机的位置,高度为负数,不会一开始就出现中型敌机 self.mask = pygame.mask.from_surface(self.image) # 取对象图片中非透明部分 self.energy = MidEnemy.energy # 初始化血量 self.hit = False #检测是否被击中 def move(self): if self.rect.top < self.height: # 未到底部就一直向下走 self.rect.top += self.speed else : self.reset()# 否则出界,重新初始化 def reset(self): self.active = True self.energy = MidEnemy.energy # 初始化血量 self.rect.left, self.rect.top = \ randint(0, self.width - self.rect.width), \ randint(-10 * self.height, -self.height) # 随机敌机的位置,高度为负数,不会一开始就出现中型敌机 class BigEnemy(pygame.sprite.Sprite): energy = 20 def __init__(self, bg_size): # 构造函数,传入对象和背景大小 pygame.sprite.Sprite.__init__(self) # 调用父类(Sprite)的构造函数 self.image1 = pygame.image.load("images/enemy3_n1.png").convert_alpha() # 创建图像 self.image2 = pygame.image.load("images/enemy3_n2.png").convert_alpha() # 创建图像 # 加载被击中时的图片 self.image_hit = pygame.image.load("images/enemy3_hit.png").convert_alpha() # 加载摧毁图片 self.destroy_images = [] self.destroy_images.extend([\ pygame.image.load("images/enemy3_down1.png").convert_alpha(), \ pygame.image.load("images/enemy3_down2.png").convert_alpha(), \ pygame.image.load("images/enemy3_down3.png").convert_alpha(), \ pygame.image.load("images/enemy3_down4.png").convert_alpha(), \ pygame.image.load("images/enemy3_down5.png").convert_alpha(), \ pygame.image.load("images/enemy3_down6.png").convert_alpha() \ ]) self.rect = self.image1.get_rect() # 获取具有图像尺寸的矩形对象 self.width, self.height = bg_size[0], bg_size[1] # 矩形的长和宽赋初值 self.speed = 1 # 敌机的速度 self.active = True #表示当前飞机存活或摧毁 self.rect.left, self.rect.top = \ randint(0, self.width - self.rect.width), \ randint(-15 * self.height, -5 * self.height) # 随机敌机的位置,高度为负数,不会一开始就出现中型敌机 self.mask = pygame.mask.from_surface(self.image1) # 取对象图片中非透明部分 self.energy = BigEnemy.energy # 初始化血量 self.hit = False #检测是否被击中 def move(self): if self.rect.top < self.height: # 未到底部就一直向下走 self.rect.top += self.speed else : self.reset()# 否则出界,重新初始化 def reset(self): self.active = True self.energy = BigEnemy.energy # 初始化血量 self.rect.left, self.rect.top = \ randint(0, self.width - self.rect.width), \ randint(-15 * self.height, -5 * self.height) # 随机敌机的位置,高度为负数,不会一开始就出现中型敌机
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/dataloader/SecenFlowLoader.py
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import os import torch import torch.utils.data as data import torch import torchvision.transforms as transforms import random from PIL import Image, ImageOps from utils import preprocess from dataloader import listflowfile as lt from utils import readpfm as rp import numpy as np IMG_EXTENSIONS = [ '.jpg', '.JPG', '.jpeg', '.JPEG', '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP', ] def is_image_file(filename): return any(filename.endswith(extension) for extension in IMG_EXTENSIONS) def default_loader(path): return Image.open(path).convert('RGB') def disparity_loader(path): return rp.readPFM(path) class myImageFloder(data.Dataset): def __init__(self, left, right, left_disparity, training, loader=default_loader, dploader= disparity_loader): self.left = left self.right = right self.disp_L = left_disparity self.loader = loader self.dploader = dploader self.training = training def __getitem__(self, index): left = self.left[index] right = self.right[index] disp_L= self.disp_L[index] left_img = self.loader(left) right_img = self.loader(right) dataL, scaleL = self.dploader(disp_L) dataL = np.ascontiguousarray(dataL,dtype=np.float32) if self.training: w, h = left_img.size th, tw = 256, 512 x1 = random.randint(0, w - tw) y1 = random.randint(0, h - th) left_img = left_img.crop((x1, y1, x1 + tw, y1 + th)) right_img = right_img.crop((x1, y1, x1 + tw, y1 + th)) dataL = dataL[y1:y1 + th, x1:x1 + tw] processed = preprocess.get_transform(augment=False) left_img = processed(left_img) right_img = processed(right_img) return left_img, right_img, dataL else: w, h = left_img.size left_img = left_img.crop((w-960, h-544, w, h)) right_img = right_img.crop((w-960, h-544, w, h)) processed = preprocess.get_transform(augment=False) left_img = processed(left_img) right_img = processed(right_img) return left_img, right_img, dataL def __len__(self): return len(self.left)
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/posneg.py
0499fb6e8cb47afd020dad8629d6d9db3f6d9eb6
[]
no_license
Mehareethaa/meha
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refs/heads/master
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n=int(input()) if n>1: print("Positive") elseif n>1: print("Negative") elseif n==0: print("Zero") else: print("Invalid input")
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/SPConvNets/trainer_3dmatch.py
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[ "MIT" ]
permissive
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from importlib import import_module from SPConvNets import FragmentLoader, FragmentTestLoader, PointCloudPairSampler, Dataloader_3dmatch_eval from tqdm import tqdm import torch import vgtk import vgtk.pc as pctk import numpy as np import os import os.path as osp class Trainer(vgtk.Trainer): def __init__(self, opt): super(Trainer, self).__init__(opt) if self.opt.train_loss.equi_alpha > 0: self.summary.register(['Loss', 'InvLoss', 'Pos', 'Neg', 'Acc', \ 'EquiLoss', 'EquiPos', 'EquiNeg', 'EquiAcc' ]) else: self.summary.register(['Loss', 'Pos', 'Neg', 'Acc']) self.epoch_counter = 0 self.iter_counter = 0 def _setup_datasets(self): if self.opt.mode == 'train': dataset = FragmentLoader(self.opt, self.opt.model.search_radius, kptname=self.opt.dataset, \ use_normals=self.opt.model.normals, npt=self.opt.npt) sampler = PointCloudPairSampler(len(dataset)) self.dataset_train = torch.utils.data.DataLoader(dataset, \ batch_size=self.opt.batch_size, \ shuffle=False, \ sampler=sampler, num_workers=self.opt.num_thread) self.dataset_iter = iter(self.dataset_train) if self.opt.mode == 'eval': self.dataset_train = None def _setup_eval_datasets(self, scene): dataset_eval = Dataloader_3dmatch_eval(self.opt, scene) self.dataset_eval = torch.utils.data.DataLoader(dataset_eval, \ batch_size=1, \ shuffle=False, \ num_workers=1) def _setup_model(self): param_outfile = osp.join(self.root_dir, "params.json") module = import_module('SPConvNets.models') self.model = getattr(module, self.opt.model.model).build_model_from(self.opt, param_outfile) # flag for whether the model requires an input fragment (besides patches) self.smooth_model = type(self.model) == import_module('SPConvNets.models').inv_so3net_smooth.InvSO3ConvSmoothModel def _setup_metric(self): self.anchors = self.model.get_anchor().to(self.opt.device) self.metric = vgtk.loss.TripletBatchLoss(self.opt,\ self.anchors, alpha = self.opt.train_loss.equi_alpha) \ # For epoch-based training def epoch_step(self): for it, data in tqdm(enumerate(self.dataset_train)): self._optimize(data) # For iter-based training def step(self): try: data = next(self.dataset_iter) except StopIteration: # New epoch self.epoch_counter += 1 print("[DataLoader]: At Epoch %d!"%self.epoch_counter) self.dataset_iter = iter(self.dataset_train) data = next(self.dataset_iter) self._optimize(data) def _prepare_input(self, data): in_tensor_src = data['src'].to(self.opt.device) in_tensor_tgt = data['tgt'].to(self.opt.device) nchannel = in_tensor_src.shape[-1] in_tensor_src = in_tensor_src.view(-1, self.opt.model.input_num, nchannel) in_tensor_tgt = in_tensor_tgt.view(-1, self.opt.model.input_num, nchannel) if self.smooth_model: fragment_src = data['frag_src'].to(self.opt.device).squeeze() in_tensor_src = (in_tensor_src, fragment_src) fragment_tgt = data['frag_tgt'].to(self.opt.device).squeeze() in_tensor_tgt = (in_tensor_tgt, fragment_tgt) return in_tensor_src, in_tensor_tgt def _optimize(self, data): gt_T = data['T'].to(self.opt.device) in_tensor_src, in_tensor_tgt = self._prepare_input(data) y_src, yw_src = self.model(in_tensor_src) y_tgt, yw_tgt = self.model(in_tensor_tgt) self.optimizer.zero_grad() if self.opt.train_loss.equi_alpha > 0: self.loss, inv_info, equi_info = self.metric(y_src, y_tgt, gt_T, yw_src, yw_tgt) invloss, pos_loss, neg_loss, accuracy = inv_info equiloss, equi_accuracy, equi_pos_loss, equi_neg_loss = equi_info else: self.loss, accuracy, pos_loss, neg_loss = self.metric(y_src, y_tgt, gt_T) self.loss.backward() self.optimizer.step() # Log training stats if self.opt.train_loss.equi_alpha > 0: log_info = { 'Loss': self.loss.item(), 'InvLoss': invloss.item(), 'Pos': pos_loss.item(), 'Neg': neg_loss.item(), 'Acc': 100 * accuracy.item(), 'EquiLoss': equiloss.item(), 'EquiPos': equi_pos_loss.item(), 'EquiNeg': equi_neg_loss.item(), 'EquiAcc': 100 * equi_accuracy.item(), } else: log_info = { 'Loss': self.loss.item(), 'Pos': pos_loss.item(), 'Neg': neg_loss.item(), 'Acc': 100 * accuracy.item(), } self.summary.update(log_info) self.iter_counter += 1 def _print_running_stats(self, step): stats = self.summary.get() self.logger.log('Training', f'{step}: {stats}') # self.summary.reset(['Loss', 'Pos', 'Neg', 'Acc', 'InvAcc']) def test(self): pass def eval(self, select): ''' 3D Match evaluation. Only works for invariant setting ''' from SPConvNets.datasets import evaluation_3dmatch as eval3dmatch # set up where to store the output feature all_results = dict() for scene in select: assert osp.isdir(osp.join(self.opt.dataset_path, scene)) print(f"Working on scene {scene}...") target_folder = osp.join('data/evaluate/3DMatch/', self.opt.experiment_id, scene, f'{self.opt.model.output_num}_dim') self._setup_eval_datasets(scene) self._generate(target_folder) # recalls: [tau, ratio] results = eval3dmatch.evaluate_scene(self.opt.dataset_path, target_folder, scene) all_results[scene] = results self._write_csv(all_results) print("Done!") def _generate(self, target_folder): with torch.no_grad(): self.model.eval() bs = self.opt.batch_size print("\n---------- Evaluating the network! ------------------") from tqdm import tqdm for it, data in enumerate(self.dataset_eval): sid = data['sid'].item() # scene = data['scene'] checknan = lambda tensor: torch.sum(torch.isnan(tensor)) print("\nWorking on fragment id", sid) n_keypoints = data['clouds'].shape[0] # 5000 x N x 3 clouds = data['clouds'].to(self.opt.device).squeeze() npt = clouds.shape[0] if self.smooth_model: frag = data['frag'].to(self.opt.device).squeeze() feature_buffer = [] for bi in tqdm(range(0, npt, bs)): in_tensor_test = clouds[bi : min(npt,bi+bs)] if self.smooth_model: in_tensor_test = (in_tensor_test, frag) feature, _ = self.model(in_tensor_test) feature_np = feature.detach().cpu().numpy() if checknan(feature).item() > 0: feature_np = np.nan_to_num(feature_np) feature_buffer.append(feature_np) # print("Batch counter at %d/%d"%(bi, npt), end='\r') # target_folder = osp.join('data/evaluate/3DMatch/', self.opt.experiment_id, scene, f'{self.opt.model.output_num}_dim') os.makedirs(target_folder, exist_ok=True) feature_out = np.vstack(feature_buffer) out_path = osp.join(target_folder, "feature%d.npy"%sid) print(f"\nSaving features to {out_path}") np.save(out_path, feature_out) def _write_csv(self, results): import csv from SPConvNets.datasets import evaluation_3dmatch as eval3dmatch csvpath = osp.join('data/evaluate/3DMatch/', self.opt.experiment_id, 'recall.csv') with open(csvpath, 'w', newline='') as csvfile: fieldnames = ['Scene'] + ['tau_%.2f'%tau for tau in eval3dmatch.TAU_RANGE] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for scene in results.keys(): recalls = results[scene] row = dict() row['Scene'] = scene for tup in recalls: tau, ratio = tup row['tau_%.2f'%tau] = "%.2f"%ratio writer.writerow(row) ### print out the stats all_recall = [] for scene in results.keys(): tau, ratio = results[scene][0] print("%s recall is %.2f at tau %.2f"%(scene, ratio, tau)) all_recall.append(ratio) avg = np.array(all_recall).mean() print("Average recall is %.2f !" % avg)
[ "chw9308@hotmail.com" ]
chw9308@hotmail.com
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[]
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db2398/set7
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refs/heads/master
2020-06-14T14:33:04.014545
2019-07-03T11:18:53
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py
t=input() sd=set(t) if(sd=={"0","1"}): print("yes") else: print("no")
[ "noreply@github.com" ]
db2398.noreply@github.com
ecfe49b03baa1334ccc75a2b3bdbf0eb1e4e241a
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/_0163_Missing_Ranges.py
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[]
no_license
mingweihe/leetcode
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class Solution(object): def findMissingRanges(self, nums, lower, upper): """ :type nums: List[int] :type lower: int :type upper: int :rtype: List[str] """ res = [] for x in nums: if x == lower: lower += 1 elif lower < x: if lower + 1 == x: res.append(str(lower)) else: res.append('%s->%s' % (lower, x-1)) lower = x + 1 if lower == upper: res.append(str(upper)) elif lower < upper: res.append('%s->%s' % (lower, upper)) return res
[ "10962421@qq.com" ]
10962421@qq.com
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/Python_codes/p02700/s274282920.py
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[]
no_license
Aasthaengg/IBMdataset
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refs/heads/main
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2021-05-13T17:27:22
2021-05-13T17:27:22
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A,B,C,D = (int(x) for x in input().split()) while True: C -= B if C <= 0: print('Yes') break else: A -= D if A <= 0: print('No') break
[ "66529651+Aastha2104@users.noreply.github.com" ]
66529651+Aastha2104@users.noreply.github.com
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/djangoproject2/helloworld_project/settings.py
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[]
no_license
rupeennaik/DjangoLearnings
aac9cbfc937c722eaa600209130ff91d82e9b6b1
c84ca5df2ed3baf0686ba7c6c5f09663b9f4c404
refs/heads/master
2023-05-01T05:57:11.653928
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py
""" Django settings for helloworld_project project. Generated by 'django-admin startproject' using Django 2.2.7. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'zoywqmo46(f4_06ym7%q=^4-=sw$*fczj=z=*-1dv!0s9ohg)b' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = ['*'] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'pages.apps.PagesConfig' # new ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'helloworld_project.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [r"D:\DjangoLearnings\djangoproject2\helloworld_project\templates"], # new 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'helloworld_project.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/'
[ "rupeennaik85@gmail.com" ]
rupeennaik85@gmail.com
52bf7e4630283924775a27166d4d67d3905e5f2f
9496842de3b1e530a25369a3beb360674346dd8e
/ex075.py
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[]
no_license
zuko56/Projetos_Python
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refs/heads/master
2020-05-15T06:03:16.224070
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py
num = (int(input('Digite um número: ')), int(input('Digite outro número: ')), int(input('Digite mais um número: ')), int(input('Digite o último número: '))) print(f'Vc digitou os valores {num}') print(f'O valor 9 apareceu {num.count(9)} vezes') if 3 in num: print(f'O valor 3 apareceu {num.index(3) + 1} posição') else: print('O valor 3 não foi encontrado') print('Os valores pares digitados foram: ', end='') for n in num: if n % 2 == 0: print(n, end=' ')
[ "noreply@github.com" ]
zuko56.noreply@github.com
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/homeworks/hw03/src/widgets.py
5c99146ce06a2685dff092dc9838d7ffb85631c3
[]
no_license
ZaydH/cmps242
6933f7ba2b3609669b898d2afcbea17a4aa85c19
d618d0a7b06998a4b8a43fc41c36e1b3094d6153
refs/heads/master
2022-03-02T11:31:54.598754
2019-09-11T00:36:05
2019-09-11T00:36:05
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0
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UTF-8
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from IPython.display import Javascript, display import ipywidgets import const def run_all(_): # noinspection PyTypeChecker display(Javascript('IPython.notebook.execute_cells_below()')) k_slider = ipywidgets.IntSlider( value=10, min=2, max=20, step=1, disabled=False, continuous_update=False, orientation='horizontal', readout=True, readout_format='d', width=100, ) k_hbox = ipywidgets.HBox([ipywidgets.Label('Number of Folds: '), k_slider]) learning_alg_radio = ipywidgets.RadioButtons( options=[const.ALG_GD, const.ALG_EG, const.ALG_SGD], description="", disabled=False ) learning_alg_radio.value = const.ALG_GD learning_alg_hbox = ipywidgets.HBox([ipywidgets.Label("Select the Learning Algorithm: "), learning_alg_radio]) regularizer_radio = ipywidgets.RadioButtons( options=[const.REGULARIZER_L1_NORM, const.REGULARIZER_L2_NORM], description="", disabled=False ) regularizer_radio.value = const.REGULARIZER_L2_NORM regularizer_hbox = ipywidgets.HBox([ipywidgets.Label("Select the Regularizer: "), regularizer_radio]) error_type_radio = ipywidgets.RadioButtons( options=[const.ERROR_ACCURACY, const.ERROR_RMS], description="", disabled=False ) error_type_radio.value = const.ERROR_ACCURACY error_type_hbox = ipywidgets.HBox([ipywidgets.Label("Select the Validation Error Calculation: "), error_type_radio]) epoch_slider = ipywidgets.IntSlider( value=25, min=1, max=100, step=1, disabled=False, continuous_update=False, orientation='horizontal', readout=True, readout_format='d', width=100, ) epoch_hbox = ipywidgets.HBox([ipywidgets.Label('Max. Number of Epochs: '), epoch_slider]) run_button = ipywidgets.Button( description='Run Learner', disabled=False, button_style='', # 'success', 'info', 'warning', 'danger' or '' tooltip='Run Learning Algorithm with the specified paramters', icon='check' ) run_button.on_click(run_all) learning_rate_slider = ipywidgets.FloatSlider( value=20, min=0.1, max=100, step=0.1, orientation='horizontal', readout=True, readout_format='.2f', ) learning_rate_hbox = ipywidgets.HBox([ipywidgets.Label("Learning Rate ($\eta$): "), learning_rate_slider]) lambdas_range_slider = ipywidgets.IntRangeSlider( value=[-10, 10], min=-10, max=10, step=1, orientation='horizontal', readout=True, readout_format='d', ) lambdas_range_hbox = ipywidgets.HBox([ipywidgets.Label("Range of $\lambda$ in Form $2^{x}$: "), lambdas_range_slider]) update_results_button = ipywidgets.Button( description='Update Results', disabled=False, button_style='', # 'success', 'info', 'warning', 'danger' or '' tooltip='Update the table and graph', icon='check' ) update_results_button.on_click(run_all)
[ "zhammoud@ucsc.edu" ]
zhammoud@ucsc.edu
eec8fe6e2f22fd18ff0f380dd0c780a1162a9cc0
3721d5d0c6f041323db876f1fa167b0f1f7878cf
/polls/views.py
0ec3cc718dc4174aff399eefed5159d22f9563b5
[]
no_license
SemieZX/mysite
e76e7964dbed8728f6efea161a3c3b83b6361964
06e6b1d577b2da1c91e717dea82a2462309e660d
refs/heads/master
2023-06-09T19:45:50.204551
2021-06-29T15:51:04
2021-06-29T15:51:04
381,083,144
0
0
null
null
null
null
UTF-8
Python
false
false
534
py
from django.shortcuts import render from django.http import HttpResponse # Create your views here. def index(request): return HttpResponse("This is paul's poll web") def detail(request, question_id): return HttpResponse("You're looking at question %s." % question_id) def results(request, question_id): response = "You're looking at the results of question %s." return HttpResponse(response % question_id) def vote(request, question_id): return HttpResponse("You're voting on question %s." % question_id)
[ "18846031359@163.com" ]
18846031359@163.com
714954d08ba02518407e7f3e2aed040adb3d741f
53a48e74508e615173493436eb34b7f8f6eefd96
/web_api/project/schema.py
eb8bf79a81e863204db9ed39ca6fcb98781c1675
[]
no_license
williamstrong/ForestArtBackEnd
4f82cb3b663c586238b3f9d6421ece8227f4755a
f2d69547d948e731b1b87b5acd17ae52156614e6
refs/heads/master
2020-03-22T17:10:41.809137
2018-08-23T18:30:57
2018-08-23T18:30:57
140,378,639
0
0
null
null
null
null
UTF-8
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false
false
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py
import graphene import image_api.schema class Query(image_api.schema.Query, graphene.ObjectType): pass schema = graphene.Schema(query=Query)
[ "william.strong@me.com" ]
william.strong@me.com
df297e6f7f59c6368f32e5ccd5de786138cb5f86
71a3616c900f1b2e385b37904c279ed63b09a150
/code/function.py
b96e804efb5d73b6d159c1e4606a9472bab57ce6
[]
no_license
svoss/masters-thesis
21c7fd88e685310c74af8f9dce0357c71f1fe30f
23c86a87aa1ee3376c3b825a5ebc9fe6b3b662f8
refs/heads/master
2021-03-27T20:41:15.310349
2017-09-05T11:26:18
2017-09-05T11:26:18
87,936,350
2
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null
null
null
null
UTF-8
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py
import numpy from chainer import cuda from chainer import function from chainer.utils import type_check class MultiTaskLoss(function.Function): """Padding of an array""" def __init__(self, factors): self.factors = factors self.factors_xp = None def check_type_forward(self, in_types): # Depending on the arguments, pad_width and keywords, the input value # may be inappropriate. In that case, numpy.pad or cupy.pad will raise # errors, so that only check the size and the dtype in this function. type_check.expect(in_types.size() == 1) x_type = in_types[0] type_check.expect(x_type.dtype.kind == 'f') type_check.expect(x_type.shape[0] == len(self.factors)) def forward(self, inputs): xp = cuda.get_array_module(*inputs) if self.factors_xp is None: self.factors_xp = xp.array(self.factors,dtype=inputs[0].dtype) x = inputs[0].dot(self.factors_xp) return xp.array(x,dtype=inputs[0].dtype).reshape(()), def backward(self, inputs, grads): xp = cuda.get_array_module(*inputs) x = inputs[0] gy = grads[0] gx = gy.dot(self.factors_xp).astype(x.dtype, copy=False) return gx, if __name__ == "__main__": import numpy as np MTL = MultiTaskLoss([.33,.33,.33]) L = np.array([[1.,1.,1.],[1.,2.,3.]],dtype=np.float64) X = MTL(L) print X.data X.backward()
[ "svoss@i-sti.nl" ]
svoss@i-sti.nl
6b854b39440765b0f5c80e3c3f73c5fdf6d4f8b8
4d10250b7ce80730414468e5e0060a207253a6d0
/jplephem/test.py
bc8ec152f0e375d2117b0930f489d0e20a305d78
[]
no_license
NatalieP-J/python
c68fdb84a6c9c432b34e57ae4e376f652451578a
c74bcfabde4704939550875bc42fc3e8a5dbc5bf
refs/heads/master
2021-01-23T03:08:06.448979
2013-08-21T04:04:11
2013-08-21T04:04:11
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0
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null
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null
null
UTF-8
Python
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"""Tests for ``jplephem``. See the accompanying ``jpltest`` module for a more intense numerical test suite that can verify that ``jplephem`` delivers, in a large number of cases, the same results as when the ephemerides are run at JPL. This smaller and more feature-oriented suite can be run with:: python -m unittest discover jplephem """ import numpy as np from functools import partial from jplephem import Ephemeris, DateError from unittest import TestCase class Tests(TestCase): def check0(self, x, y, z, dx, dy, dz): eq = partial(self.assertAlmostEqual, delta=1.0) eq(x, 39705023.28) eq(y, 131195345.65) eq(z, 56898495.41) eq(dx, -2524248.19) eq(dy, 619970.11) eq(dz, 268928.26) def check1(self, x, y, z, dx, dy, dz): eq = partial(self.assertAlmostEqual, delta=1.0) eq(x, -144692624.00) eq(y, -32707965.14) eq(z, -14207167.26) eq(dx, 587334.38) eq(dy, -2297419.36) eq(dz, -996628.74) def test_scalar_input(self): import de421 e = Ephemeris(de421) self.check0(*e.compute('earthmoon', 2414994.0)) self.check1(*e.compute('earthmoon', 2415112.5)) def test_array_input(self): import de421 e = Ephemeris(de421) v = e.compute('earthmoon', np.array([2414994.0, 2415112.5])) v = np.array(v) self.check0(*v[:,0]) self.check1(*v[:,1]) def test_ephemeris_end_date(self): import de421 e = Ephemeris(de421) x, y, z = e.position('earthmoon', e.jomega) self.assertAlmostEqual(x, -2.81196460e+07, delta=1.0) self.assertAlmostEqual(y, 1.32000379e+08, delta=1.0) self.assertAlmostEqual(z, 5.72139011e+07, delta=1.0) def test_too_early_date(self): import de421 e = Ephemeris(de421) self.assertRaises(DateError, e.compute, 'earthmoon', e.jalpha - 0.01) def test_too_late_date(self): import de421 e = Ephemeris(de421) self.assertRaises(DateError, e.compute, 'earthmoon', e.jomega + 16.01)
[ "natalie.price.jones@mail.utoronto.ca" ]
natalie.price.jones@mail.utoronto.ca
843082097c900a540cea7686d7ee120b302d66b2
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/Regular Expressions/Regularexpression.py
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[]
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nareshkodimala/Python
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#this re.match() which finds only first matched string otherwise it gives None # import re # st="this is regular expresstion" # result=re.match(r"this",st) # print(result) # # which is gives matched name as it is by using group # import re # st="example of print name only" # result=re.match(r"example",st) # print(result.group(0)) # example of start and end functions in regular expression import re st="example for start position of matching pattern in the string" res=re.match(r"example",st) #this strat fun gives first position of the given pattern string print(res.start()) #this end fun gives first position of the given pattern string print(res.end())
[ "nareshkodimala111@gmail.com" ]
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/faceborder/1.py
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from tensorflow.keras.applications.mobilenet_v2 import preprocess_input from tensorflow.keras.preprocessing.image import img_to_array from tensorflow.keras.models import load_model from imutils.video import VideoStream import numpy as np import argparse import imutils import time import cv2 import os img2 = cv2.imread('/home/pi/Desktop/face_new/faceborder/11.jpg' ) print(img2) img2=cv2.resize(img2, (750, 1200)) img1 = cv2.imread('/home/pi/Desktop/face_new/faceborder/12.jpg' ) img1=cv2.resize(img1, (750, 1200)) #img_rgb = cv2.cvtColor(img2, cv2.COLOR_BGR2RGB) def detect_and_predict_mask(frame, faceNet, maskNet): # grab the dimensions of the frame and then construct a blob # from it (h, w) = frame.shape[:2] blob = cv2.dnn.blobFromImage(frame, 1.0, (300, 300), (104.0, 177.0, 123.0)) # pass the blob through the network and obtain the face detections faceNet.setInput(blob) detections = faceNet.forward() # initialize our list of faces, their corresponding locations, # and the list of predictions from our face mask network faces = [] locs = [] preds = [] # loop over the detections for i in range(0, detections.shape[2]): # extract the confidence (i.e., probability) associated with # the detection confidence = detections[0, 0, i, 2] # filter out weak detections by ensuring the confidence is # greater than the minimum confidence if confidence > args["confidence"]: # compute the (x, y)-coordinates of the bounding box for # the object box = detections[0, 0, i, 3:7] * np.array([w, h, w, h]) (startX, startY, endX, endY) = box.astype("int") # ensure the bounding boxes fall within the dimensions of # the frame (startX, startY) = (max(0, startX), max(0, startY)) (endX, endY) = (min(w - 1, endX), min(h - 1, endY)) # extract the face ROI, convert it from BGR to RGB channel # ordering, resize it to 224x224, and preprocess it #print(startY,endY, startX,endX) face = frame[startY:endY, startX:endX] # print(face) try: face = cv2.cvtColor(face, cv2.COLOR_BGR2RGB) face = cv2.resize(face, (224, 224)) face = img_to_array(face) face = preprocess_input(face) face = np.expand_dims(face, axis=0) # add the face and bounding boxes to their respective # lists faces.append(face) locs.append((startX, startY, endX, endY)) except: pass # only make a predictions if at least one face was detected if len(faces) > 0: # for faster inference we'll make batch predictions on *all* # faces at the same time rather than one-by-one predictions # in the above `for` loop preds = maskNet.predict(faces) # return a 2-tuple of the face locations and their corresponding # locations return (locs, preds) import temp1 # construct the argument parser and parse the arguments ap = argparse.ArgumentParser() ap.add_argument("-f", "--face", type=str, default="face_detector", help="path to face detector model directory") ap.add_argument("-m", "--model", type=str, default="mask_detector.model", help="path to trained face mask detector model") ap.add_argument("-c", "--confidence", type=float, default=0.5, help="minimum probability to filter weak detections") args = vars(ap.parse_args()) # load our serialized face detector model from disk print("[INFO] loading face detector model...") prototxtPath = os.path.sep.join([args["face"], "deploy.prototxt"]) weightsPath = os.path.sep.join([args["face"], "res10_300x300_ssd_iter_140000.caffemodel"]) faceNet = cv2.dnn.readNet(prototxtPath, weightsPath) # load the face mask detector model from disk print("[INFO] loading face mask detector model...") maskNet = load_model(args["model"]) # initialize the video stream and allow the camera sensor to warm up print("[INFO] starting video stream...") #cap = VideoStream(src=0).start() cap = VideoStream(src=0,usePiCamera=1).start() time.sleep(2) while 1: img=cap.read() print=img img=cv2.resize(img, (750, 1200)) img = cv2.flip(img, 1) #blank_img = img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) frame = cv2.addWeighted(src1=img,alpha=1,src2=img2,beta=0.4, gamma = 0) blended1 = cv2.addWeighted(src1=img,alpha=1,src2=img1,beta=0.9, gamma = 0) (locs, preds) = detect_and_predict_mask(blended1, faceNet, maskNet) # loop over the detected face locations and their corresponding # locations for (box, pred) in zip(locs, preds): # unpack the bounding box and predictions (startX, startY, endX, endY) = box (mask, withoutMask) = pred # determine the class label and color we'll use to draw # the bounding box and text label = "Mask" if mask > withoutMask else "No Mask" color = (0, 255, 0) if label == "Mask" else (0, 0, 255) # temperature=temp1.read_temp() # print(temperature) temperature='97.5' # include the probability in the label label = "{}: {:.2f}%".format(label, max(mask, withoutMask) * 100) # display the label and bounding box rectangle on the output # frame cv2.putText(frame, temperature, (50, 50),cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2) cv2.putText(frame, label, (startX, startY - 10),cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2) cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2) # show the output frame cv2.imshow("Frame", frame) cv2.imshow("Frame1", blended1) key = cv2.waitKey(1) & 0xFF
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[]
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AnastasiiaNovikova/stepic
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import sys for line in sys.stdin: (key, values_str) = line.strip().split("\t") values = values_str.split(",") for value in values: print(key, ",", value, "\t", 1, sep="")
[ "mike.plekhanov@gmail.com" ]
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#!/usr/bin/env python # -*- coding: utf-8 -*- from string import split as L from django.contrib import admin from paypal.standard.pdt.models import PayPalPDT # ToDo: How similiar is this to PayPalIPNAdmin? Could we just inherit off one common admin model? class PayPalPDTAdmin(admin.ModelAdmin): date_hierarchy = 'payment_date' fieldsets = ( (None, { "fields": L("flag txn_id txn_type payment_status payment_date transaction_entity reason_code pending_reason mc_gross mc_fee auth_status auth_amount auth_exp auth_id") }), ("Address", { "description": "The address of the Buyer.", 'classes': ('collapse',), "fields": L("address_city address_country address_country_code address_name address_state address_status address_street address_zip") }), ("Buyer", { "description": "The information about the Buyer.", 'classes': ('collapse',), "fields": L("first_name last_name payer_business_name payer_email payer_id payer_status contact_phone residence_country") }), ("Seller", { "description": "The information about the Seller.", 'classes': ('collapse',), "fields": L("business item_name item_number quantity receiver_email receiver_id custom invoice memo") }), ("Subscriber", { "description": "The information about the Subscription.", 'classes': ('collapse',), "fields": L("subscr_id subscr_date subscr_effective") }), ("Recurring", { "description": "Information about recurring Payments.", "classes": ("collapse",), "fields": L("profile_status initial_payment_amount amount_per_cycle outstanding_balance period_type product_name product_type recurring_payment_id receipt_id next_payment_date") }), ("Admin", { "description": "Additional Info.", "classes": ('collapse',), "fields": L("test_ipn ipaddress query flag_code flag_info") }), ) list_display = L("__unicode__ flag invoice custom payment_status created_at") search_fields = L("txn_id recurring_payment_id") admin.site.register(PayPalPDT, PayPalPDTAdmin)
[ "william.lagos@icloud.com" ]
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/src/sms/schemas/send.py
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[]
no_license
athletictools/sms-gateway
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refs/heads/master
2023-05-03T01:22:55.027935
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from typing import List, Optional from pydantic import BaseModel class Message(BaseModel): id: str = None phone_no: str text: str class SendRequest(BaseModel): messages: List[Message]
[ "evtatarintsev@ya.ru" ]
evtatarintsev@ya.ru
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/tools/android/native_lib_memory/parse_smaps.py
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[ "Zlib", "BSD-3-Clause", "LicenseRef-scancode-unknown-license-reference", "LGPL-2.1-only", "LGPL-2.0-or-later", "APSL-2.0", "MIT", "Apache-2.0", "LGPL-2.0-only", "LicenseRef-scancode-unknown" ]
permissive
otcshare/chromium-src
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#!/usr/bin/python # Copyright 2018 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Parses /proc/[pid]/smaps on a device and shows the total amount of swap used. """ from __future__ import print_function import argparse import collections import logging import os import re import sys _SRC_PATH = os.path.join( os.path.dirname(__file__), os.pardir, os.pardir, os.pardir) sys.path.append(os.path.join(_SRC_PATH, 'third_party', 'catapult', 'devil')) from devil.android import device_utils class Mapping(object): """A single entry (mapping) in /proc/[pid]/smaps.""" def __init__(self, start, end, permissions, offset, pathname): """Initializes an instance. Args: start: (str) Start address of the mapping. end: (str) End address of the mapping. permissions: (str) Permission string, e.g. r-wp. offset: (str) Offset into the file or 0 if this is not a file mapping. pathname: (str) Path name, or pseudo-path, e.g. [stack] """ self.start = int(start, 16) self.end = int(end, 16) self.permissions = permissions self.offset = int(offset, 16) self.pathname = pathname.strip() self.fields = collections.OrderedDict() def AddField(self, line): """Adds a field to an entry. Args: line: (str) As it appears in /proc/[pid]/smaps. """ assert ':' in line split_index = line.index(':') k, v = line[:split_index].strip(), line[split_index + 1:].strip() assert k not in self.fields if v.endswith('kB'): v = int(v[:-2]) self.fields[k] = v def ToString(self): """Returns a string representation of a mapping. The returned string is similar (but not identical) to the /proc/[pid]/smaps entry it was generated from. """ lines = [] lines.append('%x-%x %s %x %s' % ( self.start, self.end, self.permissions, self.offset, self.pathname)) for name in self.fields: format_str = None if isinstance(self.fields[name], int): format_str = '%s: %d kB' else: format_str = '%s: %s' lines.append(format_str % (name, self.fields[name])) return '\n'.join(lines) def _ParseProcSmapsLines(lines): SMAPS_ENTRY_START_RE = ( # start-end '^([0-9a-f]{1,16})-([0-9a-f]{1,16}) ' # Permissions '([r\-][w\-][x\-][ps]) ' # Offset '([0-9a-f]{1,16}) ' # Device '([0-9a-f]{2,3}:[0-9a-f]{2,3}) ' # Inode '([0-9]*) ' # Pathname '(.*)') assert re.search(SMAPS_ENTRY_START_RE, '35b1800000-35b1820000 r-xp 00000000 08:02 135522 ' '/usr/lib64/ld-2.15.so') entry_re = re.compile(SMAPS_ENTRY_START_RE) mappings = [] for line in lines: match = entry_re.search(line) if match: (start, end, perms, offset, _, _, pathname) = match.groups() mappings.append(Mapping(start, end, perms, offset, pathname)) else: mappings[-1].AddField(line) return mappings def ParseProcSmaps(device, pid, store_file=False): """Parses /proc/[pid]/smaps on a device, and returns a list of Mapping. Args: device: (device_utils.DeviceUtils) device to parse the file from. pid: (int) PID of the process. store_file: (bool) Whether to also write the file to disk. Returns: [Mapping] all the mappings in /proc/[pid]/smaps. """ command = ['cat', '/proc/%d/smaps' % pid] lines = device.RunShellCommand(command, check_return=True) if store_file: with open('smaps-%d' % pid, 'w') as f: f.write('\n'.join(lines)) return _ParseProcSmapsLines(lines) def _GetPageTableFootprint(device, pid): """Returns the page table footprint for a process in kiB.""" command = ['cat', '/proc/%d/status' % pid] lines = device.RunShellCommand(command, check_return=True) for line in lines: if line.startswith('VmPTE:'): value = int(line[len('VmPTE: '):line.index('kB')]) return value def _SummarizeMapping(mapping, metric): return '%s %s %s: %d kB (Total Size: %d kB)' % ( hex(mapping.start), mapping.pathname, mapping.permissions, metric, (mapping.end - mapping.start) / 1024) def _PrintMappingsMetric(mappings, field_name): """Shows a summary of mappings for a given metric. For the given field, compute its aggregate value over all mappings, and prints the mappings sorted by decreasing metric value. Args: mappings: ([Mapping]) all process mappings. field_name: (str) Mapping field to process. """ total_kb = sum(m.fields[field_name] for m in mappings) print('Total Size (kB) = %d' % total_kb) sorted_by_metric = sorted(mappings, key=lambda m: m.fields[field_name], reverse=True) for mapping in sorted_by_metric: metric = mapping.fields[field_name] if not metric: break print(_SummarizeMapping(mapping, metric)) def _PrintSwapStats(mappings): print('SWAP:') _PrintMappingsMetric(mappings, 'Swap') def _FootprintForAnonymousMapping(mapping): assert mapping.pathname.startswith('[anon:') if (mapping.pathname == '[anon:libc_malloc]' and mapping.fields['Shared_Dirty'] != 0): # libc_malloc mappings can come from the zygote. In this case, the shared # dirty memory is likely dirty in the zygote, don't count it. return mapping.fields['Rss'] else: return mapping.fields['Private_Dirty'] def _PrintEstimatedFootprintStats(mappings, page_table_kb): print('Private Dirty:') _PrintMappingsMetric(mappings, 'Private_Dirty') print('\n\nShared Dirty:') _PrintMappingsMetric(mappings, 'Shared_Dirty') print('\n\nPrivate Clean:') _PrintMappingsMetric(mappings, 'Private_Clean') print('\n\nShared Clean:') _PrintMappingsMetric(mappings, 'Shared_Clean') print('\n\nSwap PSS:') _PrintMappingsMetric(mappings, 'SwapPss') print('\n\nPage table = %d kiB' % page_table_kb) def _ComputeEstimatedFootprint(mappings, page_table_kb): """Returns the estimated footprint in kiB. Args: mappings: ([Mapping]) all process mappings. page_table_kb: (int) Sizeof the page tables in kiB. """ footprint = page_table_kb for mapping in mappings: # Chrome shared memory. # # Even though it is shared memory, it exists because the process exists, so # account for its entirety. if mapping.pathname.startswith('/dev/ashmem/shared_memory'): footprint += mapping.fields['Rss'] elif mapping.pathname.startswith('[anon'): footprint += _FootprintForAnonymousMapping(mapping) # Mappings without a name are most likely Chrome's native memory allocators: # v8, PartitionAlloc, Oilpan. # All of it should be charged to our process. elif mapping.pathname.strip() == '': footprint += mapping.fields['Rss'] # Often inherited from the zygote, only count the private dirty part, # especially as the swap part likely comes from the zygote. elif mapping.pathname.startswith('['): footprint += mapping.fields['Private_Dirty'] # File mappings. Can be a real file, and/or Dalvik/ART. else: footprint += mapping.fields['Private_Dirty'] return footprint def _ShowAllocatorFootprint(mappings, allocator): """Shows the total footprint from a specific allocator. Args: mappings: ([Mapping]) all process mappings. allocator: (str) Allocator name. """ total_footprint = 0 pathname = '[anon:%s]' % allocator for mapping in mappings: if mapping.pathname == pathname: total_footprint += _FootprintForAnonymousMapping(mapping) print('\tFootprint from %s: %d kB' % (allocator, total_footprint)) def _CreateArgumentParser(): parser = argparse.ArgumentParser() parser.add_argument('--pid', help='PID.', required=True, type=int) parser.add_argument('--estimate-footprint', help='Show the estimated memory foootprint', action='store_true') parser.add_argument('--store-smaps', help='Store the smaps file locally', action='store_true') parser.add_argument('--show-allocator-footprint', help='Show the footprint from a given allocator', choices=['v8', 'libc_malloc', 'partition_alloc'], nargs='+') parser.add_argument( '--device', help='Device to use', type=str, default='default') return parser def main(): parser = _CreateArgumentParser() args = parser.parse_args() devices = device_utils.DeviceUtils.HealthyDevices(device_arg=args.device) if not devices: logging.error('No connected devices') return device = devices[0] if not device.HasRoot(): device.EnableRoot() # Enable logging after device handling as devil is noisy at INFO level. logging.basicConfig(level=logging.INFO) mappings = ParseProcSmaps(device, args.pid, args.store_smaps) if args.estimate_footprint: page_table_kb = _GetPageTableFootprint(device, args.pid) _PrintEstimatedFootprintStats(mappings, page_table_kb) footprint = _ComputeEstimatedFootprint(mappings, page_table_kb) print('\n\nEstimated Footprint = %d kiB' % footprint) else: _PrintSwapStats(mappings) if args.show_allocator_footprint: print('\n\nMemory Allocators footprint:') for allocator in args.show_allocator_footprint: _ShowAllocatorFootprint(mappings, allocator) if __name__ == '__main__': main()
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commit-bot@chromium.org
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cs50puyo/check50ap
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SIZE = 7 i = 0 while i < SIZE: j = 0 while j < SIZE: if i >= j: print('T', end='') j += 1 i += 1 print()
[ "luisvf@bandofcoders.com" ]
luisvf@bandofcoders.com
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[]
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KDercksen/adventofcode18
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- from string import ascii_lowercase def react(text): i = 0 while i < len(text) - 1: if abs(ord(text[i]) - ord(text[i + 1])) == 32: del text[i : i + 2] i -= 1 else: i += 1 i = max(i, 0) return len(text) if __name__ == "__main__": with open("input.txt") as f: text = list(f.read().strip()) print( min( [ react([unit for unit in text if unit.lower() != letter]) for letter in ascii_lowercase ] ) )
[ "mail@koendercksen.com" ]
mail@koendercksen.com
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/res/scripts/client/gui/shared/utils/requesters/tokenrequester.py
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webiumsk/WOT-0.9.12-CT
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# 2015.11.10 21:29:45 Střední Evropa (běžný čas) # Embedded file name: scripts/client/gui/shared/utils/requesters/TokenRequester.py import cPickle from functools import partial import BigWorld from adisp import async from constants import REQUEST_COOLDOWN, TOKEN_TYPE from debug_utils import LOG_CURRENT_EXCEPTION from TokenResponse import TokenResponse from ids_generators import SequenceIDGenerator def _getAccountRepository(): import Account return Account.g_accountRepository class TokenRequester(object): __idsGen = SequenceIDGenerator() def __init__(self, tokenType, wrapper = TokenResponse, cache = True): super(TokenRequester, self).__init__() if callable(wrapper): self.__wrapper = wrapper else: raise ValueError, 'Wrapper is invalid: {0}'.format(wrapper) self.__tokenType = tokenType self.__callback = None self.__lastResponse = None self.__requestID = 0 self.__cache = cache self.__timeoutCbID = None return def isInProcess(self): return self.__callback is not None def clear(self): self.__callback = None repository = _getAccountRepository() if repository: repository.onTokenReceived -= self.__onTokenReceived self.__lastResponse = None self.__requestID = 0 self.__clearTimeoutCb() return def getReqCoolDown(self): return getattr(REQUEST_COOLDOWN, TOKEN_TYPE.COOLDOWNS[self.__tokenType], 10.0) @async def request(self, timeout = None, callback = None): requester = getattr(BigWorld.player(), 'requestToken', None) if not requester or not callable(requester): if callback: callback(None) return elif self.__cache and self.__lastResponse and self.__lastResponse.isValid(): if callback: callback(self.__lastResponse) return else: self.__callback = callback self.__requestID = self.__idsGen.next() if timeout: self.__loadTimeout(self.__requestID, self.__tokenType, max(timeout, 0.0)) repository = _getAccountRepository() if repository: repository.onTokenReceived += self.__onTokenReceived requester(self.__requestID, self.__tokenType) return def __onTokenReceived(self, requestID, tokenType, data): if self.__requestID != requestID or tokenType != self.__tokenType: return else: repository = _getAccountRepository() if repository: repository.onTokenReceived -= self.__onTokenReceived try: self.__lastResponse = self.__wrapper(**cPickle.loads(data)) except TypeError: LOG_CURRENT_EXCEPTION() self.__requestID = 0 if self.__callback is not None: self.__callback(self.__lastResponse) self.__callback = None return def __clearTimeoutCb(self): if self.__timeoutCbID is not None: BigWorld.cancelCallback(self.__timeoutCbID) self.__timeoutCbID = None return def __loadTimeout(self, requestID, tokenType, timeout): self.__clearTimeoutCb() self.__timeoutCbID = BigWorld.callback(timeout, partial(self.__onTimeout, requestID, tokenType)) def __onTimeout(self, requestID, tokenType): self.__clearTimeoutCb() self.__onTokenReceived(requestID, tokenType, cPickle.dumps({'error': 'TIMEOUT'}, -1)) # okay decompyling c:\Users\PC\wotsources\files\originals\res\scripts\client\gui\shared\utils\requesters\tokenrequester.pyc # decompiled 1 files: 1 okay, 0 failed, 0 verify failed # 2015.11.10 21:29:46 Střední Evropa (běžný čas)
[ "info@webium.sk" ]
info@webium.sk
b3ba9461e231113f9206accdb8553163b1022ef2
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/AUInference.py
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[]
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JaineBudke/fake_emotion_analysis
519071893dc1cbad6a77135e73955c5568827271
53d5c3dc7adeac280d95eafbb2b39ee9da6466c2
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import numpy as np class AUInference: shape = np.empty(68) neutral_shape = np.empty(68) features = {} neutral_features = {} def __init__(self, shape, features, neutral_shape, neutral_features): self.shape = shape self.features = features self.neutral_shape = neutral_shape self.neutral_features = neutral_features def AU1(self): return ((self.features['ieb_height'] > (self.neutral_features['ieb_height'] + 0.075)) and (self.shape[22][1] >= self.neutral_shape[22][1]) and (self.shape[21][1] >= self.neutral_shape[21][1])) def AU2(self): return ( (self.features['oeb_height'] > (self.neutral_features['oeb_height'] + 0.08)) and (self.shape[19][1] >= self.neutral_shape[19][1]) and (self.shape[24][1] >= self.neutral_shape[24][1]) ) def AU4(self): return ((self.features['ieb_height'] < (self.neutral_features['ieb_height'] - 0.03)) and (self.features['eb_distance'] < (self.neutral_features['eb_distance'] - 0.03))) def AU5(self): return ( (self.features['e_slanting'] >= (self.neutral_features['e_slanting'] - 0.05)) and (self.features['e_openness'] > (self.neutral_features['e_openness'] + 0.055))) def AU6(self): return ((self.features['m_mos'] >= (self.neutral_features['m_mos'] + 0.045)) and (self.features['e_openness'] < (self.neutral_features['e_openness'] - 0.05))) def AU7(self): return (self.features['e_openness'] < (self.neutral_features['e_openness'] - 0.07)) def AU9(self): return ( (self.features['m_width'] < (self.neutral_features['m_width'] - 0.1)) and (self.features['e_openness'] < (self.neutral_features['e_openness'] - 0.05)) and (self.features['ieb_height'] < (self.neutral_features['ieb_height'] - 0.06)) ) def AU10(self): return ((self.features['mul_height'] > (self.neutral_features['mul_height'] + 0.03)) and (self.features['m_width'] <= self.neutral_features['m_width']) and (self.features['m_openness'] > (self.neutral_features['m_openness'] + 0.15))) def AU12(self): return ((self.features['m_mos'] >= (self.neutral_features['m_mos'] + 0.05)) and (self.features['m_width'] > (self.neutral_features['m_width'] + 0.12))) def AU15(self): return (((self.features['m_mos'] + 0.03) <= self.neutral_features['m_mos']) and (self.features['lc_height'] < (self.neutral_features['lc_height'] + 0.055))) def AU16(self): return ((self.features['mll_height'] <= (self.neutral_features['mll_height'] - 0.01)) and (self.features['m_openness'] > (self.neutral_features['m_openness'] + 0.1)) and (self.features['lc_height'] < self.neutral_features['lc_height'])) def AU17(self): return ( (self.features['m_openness'] < self.neutral_features['m_openness']) and ((abs(self.neutral_features['m_openness']) - abs(self.features['m_openness'])) >= 0.08) and (-self.features['mll_height'] < (-self.neutral_features['mll_height'] - 0.08)) ) def AU20(self): return ((self.features['m_width'] > self.neutral_features['m_width']) and ((abs(self.features['m_width']) - abs(self.neutral_features['m_width'])) >= 0.15) and (self.features['m_mos'] < (self.neutral_features['m_mos'] + 0.075)) and (self.features['lc_height'] < self.neutral_features['lc_height'])) def AU23(self): return (self.features['m_openness'] < (self.neutral_features['m_openness'] - 0.1)) def AU24(self): return ((self.features['mul_height'] < self.neutral_features['mul_height']) and (self.features['mll_height'] > self.neutral_features['mll_height'] + 0.075) and (self.features['m_openness'] < (self.neutral_features['m_openness'] - 0.1))) def AU25(self): return (self.features['m_openness'] >= (self.neutral_features['m_openness'] + 0.13)) def AU26(self): return ((self.features['m_openness'] >= (self.neutral_features['m_openness'] + 0.55)) and (self.features['m_openness'] <= (self.neutral_features['m_openness'] + 0.63))) def AU27(self): return (self.features['m_openness'] >= (self.neutral_features['m_openness'] + 0.63)) # get action units (AUs) and set in a dictionary def getAllActionUnits(self): AUs = { "AU1": self.AU1(), "AU2": self.AU2(), "AU4": self.AU4(), "AU5": self.AU5(), "AU6": self.AU6(), "AU7": self.AU7(), "AU9": self.AU9(), "AU10": self.AU10(), "AU12": self.AU12(), "AU15": self.AU15(), "AU16": self.AU16(), "AU17": self.AU17(), "AU20": self.AU20(), "AU23": self.AU23(), "AU24": self.AU24(), "AU25": self.AU25(), "AU26": self.AU26(), "AU27": self.AU27() } return AUs
[ "jainebudke@hotmail.com" ]
jainebudke@hotmail.com
b56a9efa0e36bccedee67abd895b45d54be4114e
a259b8e6fbac1bc4ff26e18e6709829ca1eb1f3d
/a02_TextCNN/word_cnn.py
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[]
no_license
godkillok/daguan
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refs/heads/master
2020-03-25T00:20:35.446593
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from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf import numpy as np import re import os import json # for python 2.x # import sys # reload(sys) # sys.setdefaultencoding("utf-8") flags = tf.app.flags flags.DEFINE_string("model_dir", "./model_dir", "Base directory for the model.") flags.DEFINE_float("dropout_rate", 0.25, "Drop out rate") flags.DEFINE_float("learning_rate", 0.001, "Learning rate") flags.DEFINE_integer("embedding_size", 128, "embedding size") flags.DEFINE_integer("num_filters", 100, "number of filters") flags.DEFINE_integer("num_classes", 14, "number of classes") flags.DEFINE_integer("shuffle_buffer_size", 1000000, "dataset shuffle buffer size") flags.DEFINE_integer("sentence_max_len", 100, "max length of sentences") flags.DEFINE_integer("batch_size", 64, "number of instances in a batch") flags.DEFINE_integer("save_checkpoints_steps", 5000, "Save checkpoints every this many steps") flags.DEFINE_integer("train_steps", 2000, "Number of (global) training steps to perform") flags.DEFINE_integer("train_epoch", 1, "Number of (global) training steps to perform") flags.DEFINE_string("data_dir", "./dbpedia_csv", "Directory containing the dataset") flags.DEFINE_string("filter_sizes", "3,4,5", "Comma-separated list of number of window size in each filter") flags.DEFINE_string("pad_word", "<pad>", "used for pad sentence") FLAGS = flags.FLAGS def parse_line(line, vocab): def get_content(record): fields = record.decode().split(",") if len(fields) < 3: raise ValueError("invalid record %s" % record) text = re.sub(r"[^A-Za-z0-9\'\`]", " ", fields[2]) text = re.sub(r"\s{2,}", " ", text) text = re.sub(r"\`", "\'", text) text = text.strip().lower() tokens = text.split() tokens = [w.strip("'") for w in tokens if len(w.strip("'")) > 0] n = len(tokens) # type: int if n > FLAGS.sentence_max_len: tokens = tokens[:FLAGS.sentence_max_len] if n < FLAGS.sentence_max_len: tokens += [FLAGS.pad_word] * (FLAGS.sentence_max_len - n) return [tokens, np.int32(fields[0])] result = tf.py_func(get_content, [line], [tf.string, tf.int32]) result[0].set_shape([FLAGS.sentence_max_len]) result[1].set_shape([]) # Lookup tokens to return their ids ids = vocab.lookup(result[0]) return {"sentence": ids}, result[1] - 1 def input_fn(path_csv, path_vocab, shuffle_buffer_size, num_oov_buckets): """Create tf.data Instance from csv file Args: path_csv: (string) path containing one example per line vocab: (tf.lookuptable) Returns: dataset: (tf.Dataset) yielding list of ids of tokens and labels for each example """ vocab = tf.contrib.lookup.index_table_from_file(path_vocab, num_oov_buckets=num_oov_buckets) # Load txt file, one example per line dataset = tf.data.TextLineDataset(path_csv) # Convert line into list of tokens, splitting by white space dataset = dataset.map(lambda line: parse_line(line, vocab)) dataset = dataset.repeat(FLAGS.train_epoch) if shuffle_buffer_size > 0: dataset = dataset.shuffle(shuffle_buffer_size) dataset = dataset.batch(FLAGS.batch_size).prefetch(1) print(dataset.output_types) print(dataset.output_shapes) return dataset def my_model(features, labels, mode, params): sentence = features['sentence'] # Get word embeddings for each token in the sentence embeddings = tf.get_variable(name="embeddings", dtype=tf.float32, shape=[params["vocab_size"], FLAGS.embedding_size]) sentence = tf.nn.embedding_lookup(embeddings, sentence) # shape:(batch, sentence_len, embedding_size) # add a channel dim, required by the conv2d and max_pooling2d method sentence = tf.expand_dims(sentence, -1) # shape:(batch, sentence_len/height, embedding_size/width, channels=1) pooled_outputs = [] for filter_size in params["filter_sizes"]: conv = tf.layers.conv2d( sentence, filters=FLAGS.num_filters, kernel_size=[filter_size, FLAGS.embedding_size], strides=(1, 1), padding="VALID", activation=tf.nn.relu) pool = tf.layers.max_pooling2d( conv, pool_size=[FLAGS.sentence_max_len - filter_size + 1, 1], strides=(1, 1), padding="VALID") pooled_outputs.append(pool) h_pool = tf.concat(pooled_outputs, 3) # shape: (batch, 1, len(filter_size) * embedding_size, 1) h_pool_flat = tf.reshape(h_pool, [-1, FLAGS.num_filters * len( params["filter_sizes"])]) # shape: (batch, len(filter_size) * embedding_size) if 'dropout_rate' in params and params['dropout_rate'] > 0.0: h_pool_flat = tf.layers.dropout(h_pool_flat, params['dropout_rate'], training=(mode == tf.estimator.ModeKeys.TRAIN)) logits = tf.layers.dense(h_pool_flat, FLAGS.num_classes, activation=None) optimizer = tf.train.AdagradOptimizer(learning_rate=params['learning_rate']) def _train_op_fn(loss): return optimizer.minimize(loss, global_step=tf.train.get_global_step()) my_head = tf.contrib.estimator.multi_class_head(n_classes=FLAGS.num_classes) return my_head.create_estimator_spec( features=features, mode=mode, labels=labels, logits=logits, train_op_fn=_train_op_fn ) def main(unused_argv): # Load the parameters from the dataset, that gives the size etc. into params json_path = os.path.join(FLAGS.data_dir, 'dataset_params.json') assert os.path.isfile(json_path), "No json file found at {}, run build_vocab.py".format(json_path) # Loads parameters from json file with open(json_path) as f: config = json.load(f) FLAGS.pad_word = config["pad_word"] if config["train_size"] < FLAGS.shuffle_buffer_size: FLAGS.shuffle_buffer_size = config["train_size"] print("shuffle_buffer_size:", FLAGS.shuffle_buffer_size) # Get paths for vocabularies and dataset path_words = os.path.join(FLAGS.data_dir, 'words.txt') assert os.path.isfile(path_words), "No vocab file found at {}, run build_vocab.py first".format(path_words) # words = tf.contrib.lookup.index_table_from_file(path_words, num_oov_buckets=config["num_oov_buckets"]) path_train = os.path.join(FLAGS.data_dir, 'train.csv') path_eval = os.path.join(FLAGS.data_dir, 'test.csv') classifier = tf.estimator.Estimator( model_fn=my_model, params={ 'vocab_size': config["vocab_size"], 'filter_sizes': list(map(int, FLAGS.filter_sizes.split(','))), 'learning_rate': FLAGS.learning_rate, 'dropout_rate': FLAGS.dropout_rate }, config=tf.estimator.RunConfig(model_dir=FLAGS.model_dir, save_checkpoints_steps=FLAGS.save_checkpoints_steps) ) train_spec = tf.estimator.TrainSpec( input_fn=lambda: input_fn(path_train, path_words, FLAGS.shuffle_buffer_size, config["num_oov_buckets"]), max_steps=FLAGS.train_steps ) input_fn_for_eval = lambda: input_fn(path_eval, path_words, 0, config["num_oov_buckets"]) eval_spec = tf.estimator.EvalSpec(input_fn=input_fn_for_eval,steps=600, throttle_secs=30000) print("before train and evaluate") tf.estimator.train_and_evaluate(classifier, train_spec, eval_spec) input_fn_for_pred=lambda: input_fn(path_train, path_words, 0, config["num_oov_buckets"]) print("evalue train set") ge1=classifier.evaluate(input_fn=input_fn_for_pred) print("evalue test set") ge2 = classifier.evaluate(input_fn=input_fn_for_eval) print("after train and evaluate") def pred(unused_argv): path_eval = os.path.join(FLAGS.data_dir, 'test.csv') path_words = os.path.join(FLAGS.data_dir, 'words.txt') input_fn_for_pred = lambda: input_fn(path_eval, path_words, 0, 100) json_path = os.path.join(FLAGS.data_dir, 'dataset_params.json') with open(json_path) as f: config = json.load(f) classifier = tf.estimator.Estimator( model_fn=my_model, params={ 'vocab_size': config["vocab_size"], 'filter_sizes': list(map(int, FLAGS.filter_sizes.split(','))), 'learning_rate': FLAGS.learning_rate, 'dropout_rate': FLAGS.dropout_rate }, config=tf.estimator.RunConfig(model_dir=FLAGS.model_dir, save_checkpoints_steps=FLAGS.save_checkpoints_steps) ) eval_spec = classifier.predict(input_fn=input_fn_for_pred) count = 0 for e in eval_spec: count += 1 print(e.get('classes', '')) print(count) if __name__ == "__main__": tf.logging.set_verbosity(tf.logging.INFO) tf.app.run(main=main)
[ "fujianhaowawa@163.com" ]
fujianhaowawa@163.com
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/Ejercicio3.py
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ayanez16/Tarea-1-Estructura
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#Un vendedor recibe u sueldo base mas un 10% extra por comision de sus ventas. #El vendedor desea saber cuanto dinero obtendra por concepto de comisiones por las tres ventas que realiza en el mes y el total que recibira #en el mes tomando en cuenta su sueldo base y sus comosiones. class Ejercicio3: def run(): S=float(input("Ingrese el salario base: ")) V1=float(input("Ingrese el valor de la primera venta: ")) V2=float(input("Ingrese el valor de la segunda venta: ")) V3=float(input("Ingrese el valor de la tercera venta: ")) T=V1+V2+V3 B=T*0.10 R=S+B print("El total del salario a recibir es: $") print(R,"El sueldo a recibir: $") run()
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mn3711698/ECommerceCrawlers
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#!/usr/bin/env python # -*- coding: utf-8 -*- """ __author__ = 'AJay' __mtime__ = '2019/4/26 0026' """ import asyncio import aiohttp import time #!/usr/bin/env python # -*- coding: utf-8 -*- """ __author__ = 'AJay' __mtime__ = '2019/4/24 0024' """ #-*- coding:utf-8 -*- import time import requests import os import json import re from pyquery import PyQuery as pq import datetime import threading import random from dingding import DingMsg from db import MongoConfig,MongoProduct,MongoKeyword,MongoTime class XianYu(): def __init__(self,logMessage,errMessage): self.page = 1 self.dbconf = MongoConfig() self.dbprod = MongoProduct() self.dbkey = MongoKeyword() self.dmes = DingMsg() self.finsh = False self.paginator_next = False self.data_list = [] # self.base_path = os.path.abspath(os.path.dirname(__file__)) self.logMessage=logMessage self.errMessage=errMessage def range_webhook(self): webhook ='https://oapi.dingtalk.com/robot/send?access_token='+self.dbconf.select_all()[random.randint(0,self.dbconf.count()-1)].get('webhook') return webhook async def parse_html(self, html,keyword): print('开始解析') doc = pq(html) num = doc.find('.cur-num').text() # 注释掉的参数为后续更改需求服务 # print('总数',num) paginator_count = doc.find('.paginator-count').text() # paginator_pre = doc.find('.paginator-pre').text() self.paginator_next = doc.find('.paginator-next').text() # 下一页 now_page = doc.find('.paginator-curr').text() # print('现在在第几页',now_page) # P = '共([0-9]+)页' # all_pagenum = re.findall(P, paginator_count, re.S) # if all_pagenum: # print(int(all_pagenum[0])) itmes = doc('#J_ItemListsContainer .ks-waterfall').items() for item in itmes: data = {} data['keyword'] =keyword data['seller_nick'] = item.find('.seller-nick a').text() # nick data['pic_href'] = 'https:'+str(item.find('.item-pic a').attr('href')) # details_ulr data['title'] = item.find('.item-pic a').attr('title') # title data['img_src'] = 'https:'+str(item.find('.item-pic a img').attr('data-ks-lazyload-custom')) # img data['price'] = item.find('.item-attributes .item-price span em').text() # price data['location'] = item.find('.item-attributes .item-location').text() data['desc'] = item.find('.item-brief-desc').text() data['pub_time'] = item.find('.item-pub-info .item-pub-time').text() data['add_time'] = datetime.datetime.now().strftime('%Y-%m-%d %H:%M-%S') #TODO:10分钟之内的商品采集 try: if int(data.get('pub_time').replace('分钟前','')) > 10: # 大于20分之间隔时间判定为超时 continue except Exception as e: # 默认的时间大于及时了,直接舍弃 continue # 如果数据库找不到对应关键字的链接 就插入数据,并且推送 if not self.dbprod.select({"keyword":keyword,"pic_href":data.get('pic_href')}): self.dbprod.insert(data) self.logMessage.put('['+keyword+']['+data['pub_time']+']['+data['title']+'[') # print(data) # TODO:普通发消息 # def send_message(): # if not getDingMes(webhook_url=self.range_webhook(), data=data,type=1): # send_message() # send_message() # TODO: 链接发消息,不可取 #TODO:markdown发消息 self.markdown_list.append(data) else: print('数据已经存在mpass') print(data) print('#' * 50) async def get(self,url,payload): async with aiohttp.ClientSession() as session: async with session.get(url,params=payload) as resp: print(resp.status) print(resp.url) result = await resp.text() return result async def request(self,keyword_obj): keyword = keyword_obj.get('keyword') minPrice=keyword_obj.get('minPrice') maxPrice=keyword_obj.get('maxPrice') payload = { "st_edtime":1, # 最新发布 "_input_charset": "utf8", "search_type": "item", "q": keyword, "page": self.page, "start": minPrice, # 价格范围 "end": maxPrice, } url = 'https://s.2.taobao.com/list/' print('Waiting for', url) result = await self.get(url,payload) await self.parse_html(result,keyword) def run(self,type): self.markdown_list = [] keywords = self.dbkey.select_all({'start':1}) tasks = [] for key_obj in keywords: tasks.append(asyncio.ensure_future(self.request(key_obj))) print(len(tasks)) if tasks : loop = asyncio.get_event_loop() loop.run_until_complete(asyncio.wait(tasks)) # 发送markdown数据文档,节约资源 def send_message(): if not self.dmes.send_msg(webhook_url=self.range_webhook(), data=self.markdown_list,type=type): send_message() self.errMessage.put('钉钉消息发送失败,发送数据太过于频繁') else: self.errMessage.put('钉钉消息发送,使用类型{}'.format(type)) if self.markdown_list: send_message() def _run(logMessage,errMessage): # 这在tk线程中运行 print('启动') dbtime = MongoTime() while True: time_config = dbtime.select_one({"flag":1}) type =time_config.get('type') padding_time =time_config.get('time') start_time = time.time() xy = XianYu(logMessage,errMessage) xy.run(type) print('异步爬取用时:',time.time() - start_time ) # TODO:配置中的时间 errMessage.put('爬取耗时{}秒'.format(int(time.time() - start_time))) if not padding_time: padding_time = 10 time.sleep(padding_time) if __name__ == '__main__': from multiprocessing import Process,JoinableQueue logMessage = JoinableQueue() errMessage = JoinableQueue() TProcess_crawler = threading.Thread(target=_run,args=(logMessage, errMessage)) # TProcess_crawler.daemon = True TProcess_crawler.start() # TProcess_crawler.join() print('继续运行')
[ "1599121712@qq.com" ]
1599121712@qq.com
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/app/request_session.py
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[]
no_license
corporacionrst/software_RST
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2021-04-26T23:23:27.241893
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from sistema.usuarios.models import Perfil def getPerfil(request): return Perfil.objects.get(usuario=request.user) # def getStore(request): # return Perfil.objects.get(usuario=request.user).tienda def OKadmin(request): if request.user.is_authenticated(): if "ADMIN" in Perfil.objects.get(usuario=request.user).puesto.nombre: return True return False def OKbodega(request): if request.user.is_authenticated(): ppl=Perfil.objects.get(usuario=request.user).puesto.nombre if "BODEGA" in ppl: return True elif "ADMIN" in ppl: return True return False def OKconta(request): if request.user.is_authenticated(): ppl=Perfil.objects.get(usuario=request.user).puesto.nombre if "CONTA" in ppl: return True elif "ADMIN" in ppl: return True return False def OKmultitienda(request): if request.user.is_authenticated(): return Perfil.objects.get(usuario=request.user).multitienda return False def OKcobros(request): if request.user.is_authenticated(): ppl=Perfil.objects.get(usuario=request.user).puesto.nombre if "COBROS" in ppl or "ADMIN" in ppl: return True return False def OKventas(request): if request.user.is_authenticated(): ppl=Perfil.objects.get(usuario=request.user).puesto.nombre if "VENTA" in ppl: return True elif "ADMIN" in ppl: return True return False def OKpeople(request): if request.user.is_authenticated(): return True return False def sumar_DATO(request,numero): val=Perfil.objects.get(usuario=request.user) if numero=="4": v = val.documento4.split("~") val.documento4=v[0]+"~"+v[1]+"~"+str(int(v[2])+1) val.save() return v[0]+"~"+v[1]+"~"+str(int(v[2])+1) def obtenerPlantilla(request): if OKadmin(request): return "admin.html" elif OKconta(request): return "conta.html" elif OKbodega(request): return "bodega.html" elif OKcobros(request): return "cobros.html" else: return "ventas.html"
[ "admin@corporacionrst.com" ]
admin@corporacionrst.com
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/run_seq2seq.py
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[]
no_license
dowobeha/pytorch_examples
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refs/heads/master
2020-07-26T00:05:52.752334
2019-10-04T19:33:44
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from typing import List, Tuple import torch from torch.utils.data import DataLoader from data import PigLatin from seq2seq import EncoderWithEmbedding, DecoderWithAttention, verify_shape def run_model(*, path: str, saved_encoder: str, saved_decoder: str, batch_size: int, device_name: str) -> None: from torch.nn.functional import softmax import numpy encoder: EncoderWithEmbedding = torch.load(saved_encoder) decoder: DecoderWithAttention = torch.load(saved_decoder) print(type(decoder)) device = torch.device(device_name) words: PigLatin = PigLatin(path=path, vocab=decoder.vocab) data: DataLoader = DataLoader(dataset=words, batch_size=batch_size) encoder.eval() decoder.eval() with torch.no_grad(): for batch in data: # type: torch.Tensor examples: torch.Tensor = batch["data"].to(device) labels: torch.LongStorage = batch["labels"].to(device) decoder_previous_output: torch.LongTensor = batch["start-of-sequence"].squeeze(dim=1).to(device) # At the end of the data set, the actual batch size may be smaller than batch_size, and that's OK actual_batch_size: int = min(batch_size, examples.shape[0]) decoder_hidden_state: torch.Tensor = torch.zeros(actual_batch_size, 1, decoder.hidden_size).to(device) verify_shape(tensor=decoder_previous_output, expected=[actual_batch_size]) verify_shape(tensor=examples, expected=[actual_batch_size, words.max_len]) verify_shape(tensor=labels, expected=[actual_batch_size, words.max_len]) encoder_states: torch.Tensor = encoder(batch_size=actual_batch_size, seq_len=words.max_len, input_tensor=examples) decoder_output_list: List[torch.Tensor] = list() for _ in range(words.max_len): decoder_results: Tuple[torch.Tensor, torch.Tensor] = decoder(batch_size=actual_batch_size, input_seq_len=words.max_len, previous_decoder_output=decoder_previous_output, previous_decoder_hidden_state=decoder_hidden_state, encoder_states=encoder_states) decoder_raw_output: torch.Tensor = decoder_results[0] decoder_hidden_state: torch.Tensor = decoder_results[1] verify_shape(tensor=decoder_raw_output, expected=[actual_batch_size, 1, len(decoder.vocab)]) verify_shape(tensor=decoder_hidden_state, expected=[actual_batch_size, 1, decoder.hidden_size]) decoder_previous_output: torch.LongTensor = softmax(decoder_raw_output, dim=2).squeeze(dim=1).topk( k=1).indices.squeeze(dim=1) verify_shape(tensor=decoder_previous_output, expected=[actual_batch_size]) decoder_output_list.append(decoder_previous_output) print(len(decoder_output_list)) predictions: torch.Tensor = torch.stack(tensors=decoder_output_list).permute(1, 0) verify_shape(tensor=predictions, expected=[actual_batch_size, words.max_len]) #print(decoder_output.shape) #sys.exit() # decoder_output: torch.Tensor = decoder(batch_size=actual_batch_size, # input_seq_len=words.max_len, # output_seq_len=words.max_len, # previous_decoder_output=decoder_start_of_sequence, # previous_decoder_hidden_state=decoder_hidden_state, # encoder_states=encoder_states) #verify_shape(tensor=decoder_output, expected=[actual_batch_size, words.max_len, len(decoder.vocab)]) # for index in range(actual_batch_size): # verify_shape(tensor=seq2seq_output[index], expected=[words.max_len, len(seq2seq.vocab)]) #prediction_distributions: torch.Tensor = softmax(input=decoder_output, dim=2) #verify_shape(tensor=prediction_distributions, # expected=[actual_batch_size, words.max_len, len(decoder.vocab)]) #predictions: torch.LongTensor = torch.topk(input=prediction_distributions, k=1).indices.squeeze(dim=2) #verify_shape(tensor=predictions, expected=[actual_batch_size, words.max_len]) for b in range(actual_batch_size): int_tensor: torch.LongTensor = predictions[b] verify_shape(tensor=int_tensor, expected=[words.max_len]) word: str = "".join([decoder.vocab.i2s[i] for i in int_tensor.tolist()]) label: str = "".join([decoder.vocab.i2s[i] for i in labels[b].tolist()]) print(f"{b}\t{words.max_len}\t{word}\t{label}\t{labels[b]}") if __name__ == "__main__": import sys if len(sys.argv) == 4: run_model(path=sys.argv[1], saved_encoder=sys.argv[2], saved_decoder=sys.argv[3], batch_size=10, device_name="cuda:0" if torch.cuda.is_available() else "cpu")
[ "dowobeha@gmail.com" ]
dowobeha@gmail.com
d5a140b811fe5a8c23c9eb3d8e15902576a1fd05
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/Chapter 7/number-analysis-program.py
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[]
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stephenmoye/Python-Programming-Projects
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refs/heads/main
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2020-12-10T05:24:53
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# Number Analysis Program # Design a program that asks the user to enter a series of 20 numbers. The program should store # the numbers in a list then display the following data: # The lowest number in the list # The highest number in the list # The total of the numbers in the list # The average of the numbers in the list numbersList = [] def main(): for month in range(0, 20): print("Enter any number") numbers = int(input()) numbersList.append(numbers) analyze(numbersList) def analyze(numbers): total = 0 for nums in range(0, 20): total = total + numbers[nums] average = total / 20 print("Lowest number:", min(numbers)) print("Highest number:", max(numbers)) print("Total:", total) print("Average:", average) main()
[ "stephenmoye@gmail.com" ]
stephenmoye@gmail.com
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/1_introduction/fraction.py
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[]
no_license
prestidigitation/algo_and_data_struc
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refs/heads/master
2021-01-10T04:38:36.071922
2016-10-25T19:10:51
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def gcd(m, n): while m % n != 0: old_m = m old_n = n m = old_n n = old_m % old_n return n class Fraction: def __init__(self, top, bottom): self.num = top self.den = bottom common = gcd(self.num, self.den) self.num = top // common self.den = bottom // common def __str__(self): return str(self.num) + "/" + str(self.den) def show(self): print(self.num, "/", self.den) def __add__(self, other_fraction): new_num = self.num * other_fraction.den + \ self.den * other_fraction.num new_den = self.den * other_fraction.den return Fraction(new_num, new_den) def __sub__(self, other_fraction): new_num = self.num * other_fraction.den - self.den * other_fraction.num new_den = self.den * other_fraction.den return Fraction(new_num, new_den) def __mul__(self, other_fraction): new_num = self.num * other_fraction.num new_den = self.den * other_fraction.den common = gcd(new_num, new_den) return Fraction(new_num // common, new_den // common) def __truediv__(self, other_fraction): new_num = self.num * other_fraction.den new_den = self.den * other_fraction.num return Fraction(new_num, new_den) def __eq__(self, other_fraction): first_num = self.num * other_fraction.den second_num = other_fraction.num * self.den return first_num == second_num def get_num(self): return self.num def get_den(self): return self.den
[ "alexander.c.rowland@gmail.com" ]
alexander.c.rowland@gmail.com
61725cec442d9ec8f82600d63aa62acb08937b54
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/Proyecto1/urls.py
e6070fd51d182c9d11ecf5ee9e9967df6398c1ce
[]
no_license
Erisjimver/django_proyecto1_practica
a460800a6439ccb7981eeb7415fd798d94625c5a
1d236510c074a03f42a7d35922ff973d0da2f532
refs/heads/master
2020-08-06T16:27:24.992895
2019-10-06T05:05:44
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"""Proyecto1 URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path from Proyecto1.views import cursoC,cursoCSS,saludo,despedida,dame_fecha,calcularEdad,calcularEdad1,saludo2 urlpatterns = [ path('admin/', admin.site.urls), path('saludo/', saludo), path('saludo2/', saludo2), path('despedida/', despedida), path('fecha/', dame_fecha), path('edad/<int:anio>/', calcularEdad), path('edad1/<int:edad>/<int:anio>/', calcularEdad1), path('cursoC/', cursoC), path('cursoCSS/', cursoCSS), ]
[ "erisjinver@gmail.com" ]
erisjinver@gmail.com
a72dbf230d91deba8ed46f91784cde7bfef572d9
ced1774c423247543413cb2d8bf2183bfe90b5a8
/markovly.py
e6a7da219e30949b3837ea1948b2bd9ad2738a40
[]
no_license
leegenes/markovly
39eb5b8fdf0b580215ac2b272bd8d2deaeac1356
05f8c85c175e212c91f1f094686f12bdf80eddb3
refs/heads/master
2022-12-20T00:45:28.920488
2017-11-10T19:54:35
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from random import choice class Markovly: def __init__(self, text=None, n=None, token_type="word"): self.text = text self.ngram = n self.token_type = token_type self.tokens = None def tokenize(self): if self.token_type == "char": text_pieces = list(self.text) else: text_pieces = self.text.split() tokens = {} for n, tp in enumerate(text_pieces): # ensures enough indices remaining # in text_pieces list for key and next word/char try: next_tp = text_pieces[n:n + self.ngram + 1] except IndexError: break # set key as tuple of length n k = tuple(next_tp[:- 1]) if len(k) != self.ngram: break # add key if not in token dict if k not in tokens: tokens[k] = [] # set last_tp = next_tp[-1] tokens[k].append(last_tp) self.tokens = tokens return self.tokens def generate_verse(self): # determines if a line should break # will in all cases with more than # 1 word on previous line - unless # previous line includes an ! def insert_break(since_last_break): if '!' in since_last_break: return True elif since_last_break.count(' ') <= 1 or ',' in since_last_break[-4:]: return False return True def get_last_break(line): if '\n' in line: last_break = len(line) - line[-1::-1].index('\n') -1 else: last_break = 0 return last_break max_len = 5 if self.token_type == "word" else 280 start_keys = [k for k in self.tokens.keys() if k[0].isupper()] k = choice(start_keys) verse = list(k) while len(verse) < max_len: try: next_piece = choice(self.tokens[k]) except KeyError: break if next_piece[0].isupper(): last_break = get_last_break(verse) since_break = verse[last_break:] if insert_break(since_break): verse.append('\n') verse.append(next_piece) k = k[1:] + (next_piece,) if verse[-1] != ' ': verse = verse[:get_last_break(verse)] return ''.join(verse) def generate_song(self, verse_count): verses = [] for i in range(verse_count): verses.append(self.generate_verse()) return '\n\n'.join(verses) if __name__ == '__main__': words = input() m = Markovly(text=words, n=8, token_type="char") print(m.generate_verse())
[ "haugenlee@leegenes.local" ]
haugenlee@leegenes.local
0b85630a9123b498e5f50e15d65fb027b4057127
1c6b5d41cc84c103ddb2db3689f61f47eaa2c13b
/CV_ToolBox-master/VOC_2_COCO/xml_helper.py
c97bb05d81b946aa96ae1e1ee0c4209f0f9cc9a7
[]
no_license
Asher-1/DataAugmentation
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c9c143e7cccf771341d2f18aa11daf8b9f817670
refs/heads/main
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# -*- coding=utf-8 -*- import os import xml.etree.ElementTree as ET import xml.dom.minidom as DOC # 从xml文件中提取bounding box信息, 格式为[[x_min, y_min, x_max, y_max, name]] def parse_xml(xml_path): ''' 输入: xml_path: xml的文件路径 输出: 从xml文件中提取bounding box信息, 格式为[[x_min, y_min, x_max, y_max, name]] ''' tree = ET.parse(xml_path) root = tree.getroot() objs = root.findall('object') coords = list() for ix, obj in enumerate(objs): name = obj.find('name').text box = obj.find('bndbox') x_min = int(box[0].text) y_min = int(box[1].text) x_max = int(box[2].text) y_max = int(box[3].text) coords.append([x_min, y_min, x_max, y_max, name]) return coords # 将bounding box信息写入xml文件中, bouding box格式为[[x_min, y_min, x_max, y_max, name]] def generate_xml(img_name, coords, img_size, out_root_path): ''' 输入: img_name:图片名称,如a.jpg coords:坐标list,格式为[[x_min, y_min, x_max, y_max, name]],name为概况的标注 img_size:图像的大小,格式为[h,w,c] out_root_path: xml文件输出的根路径 ''' doc = DOC.Document() # 创建DOM文档对象 annotation = doc.createElement('annotation') doc.appendChild(annotation) title = doc.createElement('folder') title_text = doc.createTextNode('Tianchi') title.appendChild(title_text) annotation.appendChild(title) title = doc.createElement('filename') title_text = doc.createTextNode(img_name) title.appendChild(title_text) annotation.appendChild(title) source = doc.createElement('source') annotation.appendChild(source) title = doc.createElement('database') title_text = doc.createTextNode('The Tianchi Database') title.appendChild(title_text) source.appendChild(title) title = doc.createElement('annotation') title_text = doc.createTextNode('Tianchi') title.appendChild(title_text) source.appendChild(title) size = doc.createElement('size') annotation.appendChild(size) title = doc.createElement('width') title_text = doc.createTextNode(str(img_size[1])) title.appendChild(title_text) size.appendChild(title) title = doc.createElement('height') title_text = doc.createTextNode(str(img_size[0])) title.appendChild(title_text) size.appendChild(title) title = doc.createElement('depth') title_text = doc.createTextNode(str(img_size[2])) title.appendChild(title_text) size.appendChild(title) for coord in coords: object = doc.createElement('object') annotation.appendChild(object) title = doc.createElement('name') title_text = doc.createTextNode(coord[4]) title.appendChild(title_text) object.appendChild(title) pose = doc.createElement('pose') pose.appendChild(doc.createTextNode('Unspecified')) object.appendChild(pose) truncated = doc.createElement('truncated') truncated.appendChild(doc.createTextNode('1')) object.appendChild(truncated) difficult = doc.createElement('difficult') difficult.appendChild(doc.createTextNode('0')) object.appendChild(difficult) bndbox = doc.createElement('bndbox') object.appendChild(bndbox) title = doc.createElement('xmin') title_text = doc.createTextNode(str(int(float(coord[0])))) title.appendChild(title_text) bndbox.appendChild(title) title = doc.createElement('ymin') title_text = doc.createTextNode(str(int(float(coord[1])))) title.appendChild(title_text) bndbox.appendChild(title) title = doc.createElement('xmax') title_text = doc.createTextNode(str(int(float(coord[2])))) title.appendChild(title_text) bndbox.appendChild(title) title = doc.createElement('ymax') title_text = doc.createTextNode(str(int(float(coord[3])))) title.appendChild(title_text) bndbox.appendChild(title) # 将DOM对象doc写入文件 f = open(os.path.jpin(out_root_path, img_name[:-4] + '.xml'), 'w') f.write(doc.toprettyxml(indent='')) f.close()
[ "ludahai19@163.com" ]
ludahai19@163.com
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/bwt/lyndon/lyndon.py
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ushitora/bwt
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def longest_lyndon_prefix(w): """ Returns the tuple of the longest lyndon prefix length and the number of repitition for the string w. Examples: abbaa -> Returns (3, 1) abbabb -> Returns (3, 2) """ i = 0 j = 1 while j < len(w) and w[i] <= w[j]: if w[i] == w[j]: i += 1 j += 1 else: i = 0 j += 1 return j - i, j // (j - i) def is_lyndon(w): """Returns true iff the string w is the lyndon word""" return longest_lyndon_prefix(w)[0] == len(w) def lyndon_break_points(w): """Returns lyndon breakpoints sequence of the string w""" start = 0 while start < len(w): pref, rep = longest_lyndon_prefix(w[start:]) for _ in range(rep): start += pref yield start def lyndon_factorize(w): """ Returns lyndon factorization sequence of the string w Examples: abbaba -> abb, ab, a """ start = 0 for bp in lyndon_break_points(w): yield w[start: bp] start = bp
[ "sidebook37@gmail.com" ]
sidebook37@gmail.com
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sahil-m/dvc_session
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import os import matplotlib.pyplot as plt import pandas as pd import yaml from dagshub import dagshub_logger from joblib import dump, load from sklearn.metrics import plot_confusion_matrix from yaml import CLoader as Loader def log_experiment(out_path, params: dict, metrics: dict): with dagshub_logger(metrics_path=f'{out_path}metrics.csv', hparams_path=f'{out_path}params.yml') as logger: logger.log_hyperparams(params=params) logger.log_metrics(metrics=metrics) def print_results(accuracy, c_matrix, model_name=''): print(f'Finished Training {model_name}:\nStats:') print(f'\tConfusion Matrix:\n{c_matrix}') print(f'\tModel Accuracy: {accuracy}') def evaluate_model(model, X_test, y_test): cmd = plot_confusion_matrix(model, X_test, y_test, cmap=plt.cm.Reds) c_matrix = cmd.confusion_matrix accuracy = model.score(X_test, y_test) return accuracy, c_matrix, cmd.figure_ def save_results(out_path, model, fig): if not os.path.isdir(out_path): os.makedirs(out_path) dump(model, f'{out_path}model.gz') if fig: fig.savefig(f'{out_path}confusion_matrix.svg', format='svg') def read_data(data_path: str) -> (pd.DataFrame, pd.DataFrame, pd.Series, pd.Series): train = pd.read_csv(f'{data_path}train.csv') test = pd.read_csv(f'{data_path}test.csv') X_train, y_train = train.drop(columns=['class']), train['class'] X_test, y_test = test.drop(columns=['class']), test['class'] return X_train, X_test, y_train, y_test def load_model(path): return load(f'{path}/model.gz') def read_params(file='params.yaml', model='pca'): with open(file, 'r') as fp: params = yaml.load(fp, Loader) return params[model]
[ "Puneetha_Pai@external.mckinsey.com" ]
Puneetha_Pai@external.mckinsey.com
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/photo/migrations/0012_auto_20200609_1002.py
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[]
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malindu97/CS50Final
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# Generated by Django 3.0.6 on 2020-06-09 04:32 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('photo', '0011_auto_20200608_1615'), ] operations = [ migrations.AddField( model_name='images', name='num_vote_down', field=models.PositiveIntegerField(db_index=True, default=0), ), migrations.AddField( model_name='images', name='num_vote_up', field=models.PositiveIntegerField(db_index=True, default=0), ), migrations.AddField( model_name='images', name='vote_score', field=models.IntegerField(db_index=True, default=0), ), ]
[ "malindu.wick97@gmail.com" ]
malindu.wick97@gmail.com
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/wordlist/create_sqlite_db.py
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no_license
etuardu/mnemofon
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refs/heads/master
2021-08-08T21:23:30.926939
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import word_2_digits import sqlite3 WORDLIST_FILENAME = "diz" def words_gen(): with open(WORDLIST_FILENAME) as wordlist: for word in wordlist: yield word.strip() conn = sqlite3.connect('diz_ita.db') c = conn.cursor() c.execute("CREATE TABLE words (word text, digits text)") for word in words_gen(): digits = word_2_digits.word_2_digits(word) c.execute("INSERT INTO words VALUES ('{}', '{}')".format(word, digits)) conn.commit() conn.close()
[ "edonan@gmail.com" ]
edonan@gmail.com
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rsreenivas2001/LabMain
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refs/heads/master
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def frequency(str): cnt = dict() for ltr in str: if ltr not in cnt: cnt[ltr] = 1 else: cnt[ltr] += 1 return sorted(cnt.items()) if __name__ == '__main__': x = input("Enter String : ") print(frequency(x))
[ "rsreenivas2001@gmail.com" ]
rsreenivas2001@gmail.com
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/mp3scrap/spiders/mp3crawl.py
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no_license
arun-shaw/songsmp3-scrap
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# -*- coding: utf-8 -*- import scrapy from ..items import Mp3MovieItem,Mp3SongsItem class Mp3crawlSpider(scrapy.Spider): name = 'mp3' #allowed_domains = ['https://www.songs-mp3.net/'] start_urls = ['https://www.songs-mp3.net/5/indipop-mp3-songs.html'] domain = 'https://www.songs-mp3.net' def parse(self, response): sel=scrapy.Selector(response) #all_Movies_List,url = zip(sel.css('div#movie_cats ul li a::text').extract(),sel.css('div#movie_cats ul li a::attr(href)').extract()) # getting the list in alphabatical order text=sel.css('div#movie_cats ul li a::text').extract() url=sel.css('div#movie_cats ul li a::attr(href)').extract() for (t,u) in zip(text,url): hit=self.domain+u print(t,hit) yield scrapy.Request(hit,callback=self.pdata) # getting the movie list of each alphabatical order def pdata(self,response): sel=scrapy.Selector(response) Movie_Songs=sel.css('div.list_inside_box ul li a *::attr(href)').extract() Movie_Name=sel.css('div.list_inside_box ul li a *::text').extract() for (name,url) in zip(Movie_Name,Movie_Songs): n=name.replace('Movie Mp3 Songs','').replace('Mp3 Songs','').replace(name[name.find('('):name.find(')')+1],'').replace('.','').strip() year = name[name.find('(') + 1:name.find(')')] Song_URL = self.domain + url # print('Movie Name : ',n,'Released On : ',year,'Songs URL : ',Song_URL) yield scrapy.Request(Song_URL, callback=self.sdata, meta={'M_Name': n, 'M_Year': year, 'M_URL': Song_URL}) # getting songs details of each movie. def sdata(self, response): sel = scrapy.Selector(response) MovieItem=Mp3MovieItem() Mov_Details = sel.css('div.movie_details table tbody tr td.m_d_title3') Stars = ','.join([a for a in Mov_Details[0].css('a::text').extract()]) Director = ','.join([a for a in Mov_Details[1].css('a::text').extract()]) M_Director = ','.join([a for a in Mov_Details[2].css('a::text').extract()]) Composer = ','.join([a for a in Mov_Details[3].css('a::text').extract()]) Singer = ','.join([a for a in Mov_Details[4].css('a::text').extract()]) name = response.meta['M_Name'] year = response.meta['M_Year'] url = response.meta['M_URL'] # print('Movie Name :', name, 'Released On : ', year, 'Songs URL : ', url, 'Stars :', Stars, 'Director(s) :', # Director, 'Music Director(s) :', M_Director, 'Composer :', Composer, 'Singer(s) :', Singer) MovieItem['name']=name MovieItem['year']=year MovieItem['url']=url MovieItem['Stars']=Stars MovieItem['Director']=Director MovieItem['M_Director']=M_Director MovieItem['Composer']=Composer MovieItem['Singer']=Singer yield MovieItem # Storing movie details into database # Songs details item song_details = sel.css('div.items') SongItem=Mp3SongsItem() for song in song_details.css('div.link-item'): Song_name = song.css('div.link::text').extract_first() Song_URL = self.domain + song.css('a::attr(href)').extract_first() Song_Artist = ','.join([a for a in song.css('div.item-artist a::text').extract()]) Song_Size = song.css('div.item-artist::text').extract_first().split(',')[0].split(':')[1].strip() #print('Song Name :', Song_name, 'Song URL :', Song_URL, 'Artist(s)', Song_Artist, 'Size :', Song_Size) # print(song.css('*').extract()) SongItem['Mov_Name']=name SongItem['Title']=Song_name SongItem['url']=Song_URL SongItem['Artist']=Song_Artist SongItem['Size']=Song_Size yield SongItem # Storing songs details into database
[ "noreply@github.com" ]
arun-shaw.noreply@github.com
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katrek/flask_vacancy_parser
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#!/Users/artemtkachev/PycharmProjects/flask_parser2/venv/bin/python # EASY-INSTALL-ENTRY-SCRIPT: 'pip==19.0.3','console_scripts','pip3.7' __requires__ = 'pip==19.0.3' import re import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit( load_entry_point('pip==19.0.3', 'console_scripts', 'pip3.7')() )
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akatrek@gmail.com
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/TIPA_library/utils/pca_basic.py
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deepneuroscience/TIPA
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refs/heads/master
2023-06-12T23:04:39.981220
2023-05-31T18:47:16
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import numpy as np from sklearn.decomposition import PCA ''' This is an example code for PCA projection ''' def pca_basic(t2d_data_sequence): # pca_input: 2184*(240*320) t2d_data_height = t2d_data_sequence.shape[0] t2d_data_width = t2d_data_sequence.shape[1] t2d_data_sequence = t2d_data_sequence.reshape((t2d_data_height*t2d_data_width, np.size(t2d_data_sequence, 2))) t2d_data_sequence = np.transpose(t2d_data_sequence) # Eigenfaces output_pca = PCA(n_components=0.95) # PCA projection _ = output_pca.fit(t2d_data_sequence) t2d_data_sequence = output_pca.transform(t2d_data_sequence) # Eigenfaces eigen_faces = output_pca.components_ var_percent = output_pca.explained_variance_ratio_ return eigen_faces, var_percent
[ "noreply@github.com" ]
deepneuroscience.noreply@github.com
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insomniacdoll/personal-python-utils
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#!/usr/bin/env python # -*- coding: UTF-8 -*- # # Author : insomniacdoll@gmail.com import sys import os from utils import * """适用于streaming的 简单mapreduce框架 如果需要join请参见join_runner.py """ def run_mapper(mapper): for line in sys.stdin: line = line.strip('\n') keyvalue = None try: for keyvalue in mapper(line): print keyvalue except Exception, e: Error(e) Error('Invalid input [%s]' %keyvalue) def combine_bykeys(stdin): """ @breif 将reduce的输入组合成 <key, [v1, v2, v3]>的形式,更方便的编写reduce 即按照key对输入流进行汇聚 """ current_key = None current_values = [] for line in stdin: line = line.strip('\n') (key, value) = line.split('\t', 1) if current_key == key: current_values.append(value) else: if current_key: yield current_key, current_values current_key = key current_values = [value] if current_key != None and current_key == key: yield current_key, current_values def run_reducer(reducer): for key, values in combine_bykeys(sys.stdin): try: for keyvalue in reducer(key, values): print keyvalue except Exception, e: Error(e)
[ "insomniacdoll@gmail.com" ]
insomniacdoll@gmail.com
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/Main.py
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[]
no_license
AdamJSoftware/Convert_CSV
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refs/heads/master
2020-05-30T23:10:06.705308
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import GUI if __name__ == '__main__': GUI.main()
[ "42972871+ViteloSoftware@users.noreply.github.com" ]
42972871+ViteloSoftware@users.noreply.github.com
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JKangel/xinpianchang
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#!/home/kangel/Learn/python/spider/xpc/venv/bin/python # -*- coding: utf-8 -*- import re import sys from django.core.management import execute_from_command_line if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(execute_from_command_line())
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j_juyongkang@163.com
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[]
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alisoliman/travelism
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refs/heads/master
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2020-02-13T10:27:05
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from django.db import models # Create your models here. class Agency(models.Model): name = models.CharField(max_length=128) brief = models.TextField() cover_picture = models.ImageField() rating = models.FloatField(default=0) def __str__(self): return self.name
[ "ali.soliman95@gmail.com" ]
ali.soliman95@gmail.com
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/controllers.py
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[]
no_license
suejungshin/zesty-api-backup
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refs/heads/master
2022-12-07T09:21:07.758774
2020-03-25T06:50:53
2020-03-25T06:50:53
249,881,247
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import models import io import geojson import json import urllib.request from PIL import Image, ImageDraw from pathlib import Path path = Path.cwd() def translate_coords(arr, bounds, size): lon0 = bounds[0] lat0 = bounds[1] lon_scale = size[0] / (bounds[2] - bounds[0]) lat_scale = size[1] / (bounds[3] - bounds[1]) res = [] for coord in arr: lon = coord[0] lat = coord[1] res.append(((lon - lon0) * lon_scale, size[1] - (lat - lat0) * lat_scale)) return res def draw_overlay(id): result = models.get_property_details(id) bldg_latlongs = geojson.loads(result[0]).coordinates[0] parcel_latlongs = geojson.loads(result[1]).coordinates[0] image_bounds = result[2] im = Image.open(f"./images/{id}.jpeg") size = im.size parcel_pxls = translate_coords(parcel_latlongs, image_bounds, size) bldg_pxls = translate_coords(bldg_latlongs, image_bounds, size) polyg = Image.new('RGBA', size) pdraw = ImageDraw.Draw(polyg) pdraw.polygon(parcel_pxls, fill=(255,255,0,128)) pdraw.polygon(bldg_pxls, fill=(255,0,0,128)) im.paste(polyg, mask=polyg) image_path = f"{path}/images/{id}-overlayed.jpeg" im.save(image_path, format="JPEG") return def save_image_from_url(id): image_url = models.get_image_url(id) if image_url is None: return False bytes_obj = urllib.request.urlopen(image_url).read() image = Image.open(io.BytesIO(bytes_obj)) image_path = f"{path}/images/{id}.jpeg" image.save(image_path, format="JPEG") return True def get_image(id, overlay): if overlay: image_path = f"{path}/images/{id}-overlayed.jpeg" else: image_path = f"{path}/images/{id}.jpeg" try: return open(image_path, "rb") except FileNotFoundError: success = save_image_from_url(id) if not success: return None else: if overlay: draw_overlay(id) return open(image_path, "rb") else: return open(image_path, "rb") def get_nearby_properties(geojson_obj): return models.find_nearby_property_ids(geojson_obj) def get_stats(id, distance): total_parcel_area_in_radius = models.get_total_parcels_area(id, distance) buildings_detail = models.get_nearby_buildings_details(id, distance) areas = buildings_detail[0] distances = buildings_detail[1] zone_density = models.get_zone_density(id, distance) if not zone_density: zone_density = "Search distance was too large" return json.dumps({ "total_parcel_area_in_radius": total_parcel_area_in_radius, "buildings_areas": areas, "buildings_dists_to_center": distances, "zone_density": zone_density })
[ "suejungshin@Suejungs-MBP.attlocal.net" ]
suejungshin@Suejungs-MBP.attlocal.net
f0d8fc5a6739e6510b5819ce8a9f6155c79f922b
f8b5aafac15f408a48fabf853a918015c927e6fe
/backup/virtualenv/venv27/lib/python2.7/site-packages/openstackclient/identity/v3/role.py
0376070907d96274184e4a7d75690462833415c3
[]
no_license
to30/tmp
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ec809683970af6787728c2c41f161f416155982a
refs/heads/master
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2016-05-13T16:34:59
2016-05-13T16:34:59
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# Copyright 2012-2013 OpenStack Foundation # # 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. # """Identity v3 Role action implementations""" import logging import six import sys from cliff import command from cliff import lister from cliff import show from keystoneclient import exceptions as ksc_exc from openstackclient.common import utils from openstackclient.i18n import _ # noqa class AddRole(command.Command): """Adds a role to a user or group on a domain or project""" log = logging.getLogger(__name__ + '.AddRole') def get_parser(self, prog_name): parser = super(AddRole, self).get_parser(prog_name) parser.add_argument( 'role', metavar='<role>', help='Role to add to <user> (name or ID)', ) domain_or_project = parser.add_mutually_exclusive_group() domain_or_project.add_argument( '--domain', metavar='<domain>', help='Include <domain> (name or ID)', ) domain_or_project.add_argument( '--project', metavar='<project>', help='Include `<project>` (name or ID)', ) user_or_group = parser.add_mutually_exclusive_group() user_or_group.add_argument( '--user', metavar='<user>', help='Include <user> (name or ID)', ) user_or_group.add_argument( '--group', metavar='<group>', help='Include <group> (name or ID)', ) return parser def take_action(self, parsed_args): self.log.debug('take_action(%s)', parsed_args) identity_client = self.app.client_manager.identity if (not parsed_args.user and not parsed_args.domain and not parsed_args.group and not parsed_args.project): return role = utils.find_resource( identity_client.roles, parsed_args.role, ) if parsed_args.user and parsed_args.domain: user = utils.find_resource( identity_client.users, parsed_args.user, ) domain = utils.find_resource( identity_client.domains, parsed_args.domain, ) identity_client.roles.grant( role.id, user=user.id, domain=domain.id, ) elif parsed_args.user and parsed_args.project: user = utils.find_resource( identity_client.users, parsed_args.user, ) project = utils.find_resource( identity_client.projects, parsed_args.project, ) identity_client.roles.grant( role.id, user=user.id, project=project.id, ) elif parsed_args.group and parsed_args.domain: group = utils.find_resource( identity_client.groups, parsed_args.group, ) domain = utils.find_resource( identity_client.domains, parsed_args.domain, ) identity_client.roles.grant( role.id, group=group.id, domain=domain.id, ) elif parsed_args.group and parsed_args.project: group = utils.find_resource( identity_client.groups, parsed_args.group, ) project = utils.find_resource( identity_client.projects, parsed_args.project, ) identity_client.roles.grant( role.id, group=group.id, project=project.id, ) else: sys.stderr.write("Role not added, incorrect set of arguments \ provided. See openstack --help for more details\n") return class CreateRole(show.ShowOne): """Create new role""" log = logging.getLogger(__name__ + '.CreateRole') def get_parser(self, prog_name): parser = super(CreateRole, self).get_parser(prog_name) parser.add_argument( 'name', metavar='<role-name>', help='New role name', ) parser.add_argument( '--or-show', action='store_true', help=_('Return existing role'), ) return parser def take_action(self, parsed_args): self.log.debug('take_action(%s)', parsed_args) identity_client = self.app.client_manager.identity try: role = identity_client.roles.create(name=parsed_args.name) except ksc_exc.Conflict as e: if parsed_args.or_show: role = utils.find_resource(identity_client.roles, parsed_args.name) self.log.info('Returning existing role %s', role.name) else: raise e role._info.pop('links') return zip(*sorted(six.iteritems(role._info))) class DeleteRole(command.Command): """Delete role(s)""" log = logging.getLogger(__name__ + '.DeleteRole') def get_parser(self, prog_name): parser = super(DeleteRole, self).get_parser(prog_name) parser.add_argument( 'roles', metavar='<role>', nargs="+", help='Role(s) to delete (name or ID)', ) return parser def take_action(self, parsed_args): self.log.debug('take_action(%s)', parsed_args) identity_client = self.app.client_manager.identity for role in parsed_args.roles: role_obj = utils.find_resource( identity_client.roles, role, ) identity_client.roles.delete(role_obj.id) return class ListRole(lister.Lister): """List roles""" log = logging.getLogger(__name__ + '.ListRole') def get_parser(self, prog_name): parser = super(ListRole, self).get_parser(prog_name) domain_or_project = parser.add_mutually_exclusive_group() domain_or_project.add_argument( '--domain', metavar='<domain>', help='Filter roles by <domain> (name or ID)', ) domain_or_project.add_argument( '--project', metavar='<project>', help='Filter roles by <project> (name or ID)', ) user_or_group = parser.add_mutually_exclusive_group() user_or_group.add_argument( '--user', metavar='<user>', help='Filter roles by <user> (name or ID)', ) user_or_group.add_argument( '--group', metavar='<group>', help='Filter roles by <group> (name or ID)', ) return parser def take_action(self, parsed_args): self.log.debug('take_action(%s)' % parsed_args) identity_client = self.app.client_manager.identity if parsed_args.user: user = utils.find_resource( identity_client.users, parsed_args.user, ) elif parsed_args.group: group = utils.find_resource( identity_client.groups, parsed_args.group, ) if parsed_args.domain: domain = utils.find_resource( identity_client.domains, parsed_args.domain, ) elif parsed_args.project: project = utils.find_resource( identity_client.projects, parsed_args.project, ) # no user or group specified, list all roles in the system if not parsed_args.user and not parsed_args.group: columns = ('ID', 'Name') data = identity_client.roles.list() elif parsed_args.user and parsed_args.domain: columns = ('ID', 'Name', 'Domain', 'User') data = identity_client.roles.list( user=user, domain=domain, ) for user_role in data: user_role.user = user.name user_role.domain = domain.name elif parsed_args.user and parsed_args.project: columns = ('ID', 'Name', 'Project', 'User') data = identity_client.roles.list( user=user, project=project, ) for user_role in data: user_role.user = user.name user_role.project = project.name elif parsed_args.user: columns = ('ID', 'Name') data = identity_client.roles.list( user=user, domain='default', ) elif parsed_args.group and parsed_args.domain: columns = ('ID', 'Name', 'Domain', 'Group') data = identity_client.roles.list( group=group, domain=domain, ) for group_role in data: group_role.group = group.name group_role.domain = domain.name elif parsed_args.group and parsed_args.project: columns = ('ID', 'Name', 'Project', 'Group') data = identity_client.roles.list( group=group, project=project, ) for group_role in data: group_role.group = group.name group_role.project = project.name else: sys.stderr.write("Error: If a user or group is specified, either " "--domain or --project must also be specified to " "list role grants.\n") return ([], []) return (columns, (utils.get_item_properties( s, columns, formatters={}, ) for s in data)) class RemoveRole(command.Command): """Remove role from domain/project : user/group""" log = logging.getLogger(__name__ + '.RemoveRole') def get_parser(self, prog_name): parser = super(RemoveRole, self).get_parser(prog_name) parser.add_argument( 'role', metavar='<role>', help='Role to remove (name or ID)', ) domain_or_project = parser.add_mutually_exclusive_group() domain_or_project.add_argument( '--domain', metavar='<domain>', help='Include <domain> (name or ID)', ) domain_or_project.add_argument( '--project', metavar='<project>', help='Include <project> (name or ID)', ) user_or_group = parser.add_mutually_exclusive_group() user_or_group.add_argument( '--user', metavar='<user>', help='Include <user> (name or ID)', ) user_or_group.add_argument( '--group', metavar='<group>', help='Include <group> (name or ID)', ) return parser def take_action(self, parsed_args): self.log.debug('take_action(%s)', parsed_args) identity_client = self.app.client_manager.identity if (not parsed_args.user and not parsed_args.domain and not parsed_args.group and not parsed_args.project): return role = utils.find_resource( identity_client.roles, parsed_args.role, ) if parsed_args.user and parsed_args.domain: user = utils.find_resource( identity_client.users, parsed_args.user, ) domain = utils.find_resource( identity_client.domains, parsed_args.domain, ) identity_client.roles.revoke( role.id, user=user.id, domain=domain.id, ) elif parsed_args.user and parsed_args.project: user = utils.find_resource( identity_client.users, parsed_args.user, ) project = utils.find_resource( identity_client.projects, parsed_args.project, ) identity_client.roles.revoke( role.id, user=user.id, project=project.id, ) elif parsed_args.group and parsed_args.domain: group = utils.find_resource( identity_client.groups, parsed_args.group, ) domain = utils.find_resource( identity_client.domains, parsed_args.domain, ) identity_client.roles.revoke( role.id, group=group.id, domain=domain.id, ) elif parsed_args.group and parsed_args.project: group = utils.find_resource( identity_client.groups, parsed_args.group, ) project = utils.find_resource( identity_client.projects, parsed_args.project, ) identity_client.roles.revoke( role.id, group=group.id, project=project.id, ) else: sys.stderr.write("Role not removed, incorrect set of arguments \ provided. See openstack --help for more details\n") return class SetRole(command.Command): """Set role properties""" log = logging.getLogger(__name__ + '.SetRole') def get_parser(self, prog_name): parser = super(SetRole, self).get_parser(prog_name) parser.add_argument( 'role', metavar='<role>', help='Role to modify (name or ID)', ) parser.add_argument( '--name', metavar='<name>', help='Set role name', ) return parser def take_action(self, parsed_args): self.log.debug('take_action(%s)', parsed_args) identity_client = self.app.client_manager.identity if not parsed_args.name: return role = utils.find_resource( identity_client.roles, parsed_args.role, ) identity_client.roles.update(role.id, name=parsed_args.name) return class ShowRole(show.ShowOne): """Display role details""" log = logging.getLogger(__name__ + '.ShowRole') def get_parser(self, prog_name): parser = super(ShowRole, self).get_parser(prog_name) parser.add_argument( 'role', metavar='<role>', help='Role to display (name or ID)', ) return parser def take_action(self, parsed_args): self.log.debug('take_action(%s)', parsed_args) identity_client = self.app.client_manager.identity role = utils.find_resource( identity_client.roles, parsed_args.role, ) role._info.pop('links') return zip(*sorted(six.iteritems(role._info)))
[ "tomonaga@mx2.mesh.ne.jp" ]
tomonaga@mx2.mesh.ne.jp
be480facdbf7f43c654461fa2321b830698119e3
25112bd560d94eb34d1b11c5e074435e08e521d5
/space_invaders.pyde
365f9cde2b07576a917211e2aa9985fde344bd10
[]
no_license
villa-version/space_invaders
586bdb09b3604f6cd09c37f0e06012aa2d0221d4
3a66f72182230ee8535b6ec37b28a26a84a8e328
refs/heads/main
2023-03-20T06:03:43.573906
2021-03-07T11:36:22
2021-03-07T11:36:22
341,692,041
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from MainConstructor import MainConstructor main_constructor = None add_library('minim') def setup(): size(800,600) imageMode(CENTER) rectMode(CENTER) ellipseMode(CENTER) textSize(24) minim_music = Minim(this) mainMenuSound = minim_music.loadFile('sound/soundForSpaceInvMainMenu.wav') soundMouse = minim_music.loadFile('sound/spaceInvClick.wav') soundSpace = minim_music.loadFile('sound/soundForSpaceInvSpace.wav') soundGun = minim_music.loadFile('sound/soundForSpaceInvGun.wav') soundClick = minim_music.loadFile('sound/soundMouse.mp3') takeSomething = minim_music.loadFile('sound/NumberTakeSome/number1/takeSomething_1.wav') soundCoin = minim_music.loadFile('sound/coin.wav') soundSpaceShip = minim_music.loadFile('sound/soundSpaceShip.mp3') global main_constructor main_constructor = MainConstructor(mainMenuSound, soundMouse, soundSpace, soundGun, soundClick, takeSomething, soundCoin, soundSpaceShip) def draw(): background(70,174,183) main_constructor.game(mousePressed) if mousePressed: main_constructor.shootWithSecondWeapon() def mousePressed(): global main_constructor main_constructor.shootWithFirstWeapon()
[ "volinetsilia@gmail.com" ]
volinetsilia@gmail.com
aeb43f727bef3568d5d61348436f69e824c7c388
e08caa6d3db87282ff88e31885be602f5a8f7607
/week5/mytree.py
83783646560af7261c07927238ed17b97891e87a
[]
no_license
alice-yang94/GetAheadProgram
c66ac732c6f467251a73246f906f9e774d8b783b
9cc6a8904020d99ec648943b51051f4261e03ddf
refs/heads/master
2022-04-04T08:45:36.212499
2020-02-17T12:12:01
2020-02-17T12:12:01
232,677,299
0
0
null
null
null
null
UTF-8
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py
class Node: def __init__(self, val, ifTerminate, children = None): self.val = val self.ifTerminate = ifTerminate self.children = {} self.depth = 1 if children is not None: for child in children: self.add_child(child) self.depth = max(child.depth+1, self.depth) def __repr__(self): return f'{self.val} {self.ifTerminate}' def print_children(self): if self.children: print(f'children of {self.val}, {self.ifTerminate}: ', end ='') print(self.children) for child in self.children.values(): child.print_children() def add_child(self, child): assert isinstance(child, Node) if child.val not in self.children: self.children[child.val] = child return child if child.ifTerminate: self.children[child.val].ifTerminate = True return self.children[child.val] def dfs(self): stack = [self] while stack: curr = stack.pop() # in-place print(curr) for c in curr.children: stack.append(c)
[ "aliceyang94@hotmail.com" ]
aliceyang94@hotmail.com
64d649aba8a3b3ae9ccf92ddc4d8ba2c1699a86b
d72d43d32f4f191a2e292b95decfa3979c585b64
/bubbleSortIterationCount.py
f1e4a1d7b126c4d5e20418f7ed19dcb9bc9859a3
[]
no_license
Maxyee/Python_Basic_Codes
38db3cf9bf35f217c5c485f77e561d355b7cad5b
a14b17ad622f2bbfa774823b3400c263717a0e6f
refs/heads/master
2020-03-22T01:42:03.614491
2019-06-17T08:28:54
2019-06-17T08:28:54
139,323,946
0
0
null
null
null
null
UTF-8
Python
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false
336
py
def print_swaps(arr): swaps = 0 length = len(arr) for i in range(length - 1): for k in range(length - i - 1): if arr[k] > arr[k + 1]: arr[k], arr[k + 1] = arr[k + 1], arr[k] swaps += 1 print(swaps) N = int(input()) a = [int(x) for x in input().split()] print_swaps(a)
[ "eyaminkhan00@gmail.com" ]
eyaminkhan00@gmail.com
bfee922efb85a81a17dfa95c624fc265aa22db08
3f0a5787dc4a417648ae4297724aed5a8fa0d318
/005-ray/10-ray-serving-tutorial/app.py
a20835200875abc2f60d5877f8c486428cea8957
[]
no_license
AndersonJo/code-snippet
d6d55574ff77e1c9d68f6f2e735096264ddac3ad
856d97ac617ea2ae45b301a14a999647abec1a0c
refs/heads/master
2023-05-10T19:44:21.953081
2023-02-16T13:12:51
2023-02-16T13:12:51
177,695,307
2
1
null
2023-05-01T21:46:50
2019-03-26T01:51:17
Jupyter Notebook
UTF-8
Python
false
false
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py
from ray import serve from starlette.requests import Request from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer @serve.deployment(num_replicas=2, ray_actor_options={"num_cpus": 1, "num_gpus": 0}) class Translator: def __init__(self): # Load model self.tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_1.2B") self.tokenizer.src_lang = 'en' self.model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_1.2B") self.model.eval() def translate(self, text: str) -> str: dest_lang_id = self.tokenizer.get_lang_id('ko') encoded_src = self.tokenizer(text, return_tensors="pt") generated_tokens = self.model.generate(**encoded_src, forced_bos_token_id=dest_lang_id, max_length=200, use_cache=True) result = self.tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0] return result async def __call__(self, http_request: Request) -> str: korean_text: str = await http_request.json() return self.translate(korean_text) translator = Translator.bind() # if __name__ == '__main__': # translator = Translator() # print(translator.translate('self-belief and hard work will always earn you success'))
[ "a141890@gmail.com" ]
a141890@gmail.com
26d15922d0ecfedcaf2173747381f0a5c15f707c
12bbad5d5f81f0c9b11fc9db3dee69b901f44469
/api/models.py
b9eb84a065c44cc4f0ff0d856770f641198a8578
[]
no_license
youflox/news
d5e0432e57093d6f4c49015d361ffe01cbd1c48e
e0e829727ac046f36fdeaf9335002c1c2c83684d
refs/heads/master
2023-01-08T21:07:11.295421
2020-11-06T07:47:57
2020-11-06T07:47:57
309,968,222
0
0
null
null
null
null
UTF-8
Python
false
false
663
py
from django.db import models from django.contrib.auth.models import User # Create your models here. class Article(models.Model): title = models.CharField(max_length=200) description = models.CharField(max_length=200, blank=True) paragraph = models.TextField(null=False) author = models.ForeignKey(User, on_delete=models.DO_NOTHING) date = models.DateTimeField(auto_now=True) slug = models.SlugField(max_length=100, unique=True) tags = models.CharField(max_length=200) image = models.ImageField(upload_to='images', null=False, blank=False) def __str__(self): return self.title
[ "youflox@gmail.com" ]
youflox@gmail.com
d01e43573608281fc31233bbcdb6aa0b8621b9ca
63d722cfc5749049c72e1f3c075ce95b99baa257
/lessonOne.py
ae73b87186208ddbb0df14ce55cb9c7f546b46aa
[]
no_license
kdkimmer/hello-google-app-engine
d90b415dee0eeb78dc6e6c1086b667c104615358
a9f70a1e8ff1b4104d6269b4f2c035210b20e0fb
refs/heads/master
2021-01-20T17:20:16.908502
2016-08-21T19:56:29
2016-08-21T19:56:29
65,671,401
0
0
null
null
null
null
UTF-8
Python
false
false
574
py
import webapp2 form=""" <form method = "post" action= "/testform"> <input name="q"> <input type="submit"> </form> """ class TestHandler(webapp2.RequestHandler): def get(self): q = self.request.get("q") self.response.write(q) #self.response.headers['Content-Type'] = 'plain/text' #self.response.write(self.request) class MainHandler(webapp2.RequestHandler): def post(self): self.response.write(form) app = webapp2.WSGIApplication([ ('/', MainHandler), ('/testform', TestHandler) ], debug=True)
[ "sageykat-123@yahoo.com" ]
sageykat-123@yahoo.com
a1f9f2880c5805d0642099f67fac1e61760b9185
c342d39a064441d7c83b94e896dfbac1dc155666
/setup.py
cc22030282c6d003af194c2c298389e898f5d44d
[ "MIT" ]
permissive
arsho/generator
a67d876bf9dded9bacdbd50a9ab3999f90c81731
5dc346850ec99a47ca7c074e3e5dec0b5fff30e2
refs/heads/master
2021-01-01T16:54:41.955771
2017-07-21T14:37:34
2017-07-21T14:37:34
97,951,569
3
0
null
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null
null
UTF-8
Python
false
false
1,154
py
# -*- coding: utf-8 -*- from setuptools import setup def readme(): with open('README.rst', encoding='utf8') as f: return f.read() setup(name='generator', version='0.0.1', description='Generator is a package for generating strong password and check strength of user defined password.', long_description=readme(), install_requires=[], classifiers=[ 'Operating System :: OS Independent', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Development Status :: 5 - Production/Stable', 'Topic :: Software Development :: Libraries :: Python Modules' ], keywords='password generator strength pass', url='http://github.com/arsho/generator', author='Ahmedur Rahman Shovon', author_email='shovon.sylhet@gmail.com', license='MIT', packages=['generator'], include_package_data=True, zip_safe=False )
[ "shovon.sylhet@gmail.com" ]
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/code/setup.py
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__author__ = 'ANIKETDHURI' class DICYRT(): """ Contains config details for : MongoDB """
[ "aniket.dhuri@gmail.com" ]
aniket.dhuri@gmail.com
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/frontend/services/connect_service.py
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#!/usr/bin/python ## @package RAID5.frontend.services.connect_service ## Module that implements the ConnectService class. Service brings a disk ## back online to a volume. # import errno import logging import os import socket import time import traceback from block_device.services import update_level_service from common.services import base_service from common.utilities import constants from common.utilities import html_util from common.utilities import util from frontend.pollables import bds_client_socket from frontend.services import display_disks_service from frontend.utilities import cache from frontend.utilities import disk_manager from frontend.utilities import disk_util from frontend.utilities import service_util from common.utilities.state_util import state from common.utilities.state_util import state_machine ## Frontend ConnectService. This service adds the wanted disk back to the disk ## array. Rebuilding of the disk is done after terminate, since it has to be ## done in the background after socket has been closed, as a callable class ConnectService(base_service.BaseService): ## Constructor for ConnectService # @param entry (pollable) the entry (probably @ref # common.pollables.service_socket) using the service # @param pollables (dict) All the pollables currently in the server # @param args (dict) Arguments for this service def __init__(self, entry, pollables, args): super(ConnectService, self).__init__( [], ["disk_UUID", "volume_UUID"], args ) ## Volume we're dealing with self._volume = None ## Disks we're dealing with self._disks = None ## Disk UUID of connected disk self._disk_UUID = None ## Mode of adding a new disk self._new_disk_mode = False ## Disk already built boolean self._disk_built = False ## StateMachine object self._state_machine = None ## Current block num (for rebuilding) self._current_block_num = "" ## Current data (for rebuilding) self._current_data = "" ## pollables of the Frontend server self._pollables = pollables ## Disk Manager that manages all the clients self._disk_manager = None ## Name of the service # needed for Frontend purposes, creating clients # required by common.services.base_service.BaseService # @returns (str) service name @staticmethod def get_name(): return "/connect" ## Checks if and how the disk needs to be rebuilt. ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns need_rebuild (bool) if needs to be rebuilt def initial_setup(self, entry): self._disk_UUID = self._args["disk_UUID"][0] self._volume_UUID = self._args["volume_UUID"][0] # first check validity of volume if ( self._volume_UUID not in entry.application_context["volumes"].keys( ) or ( entry.application_context["volumes"][self._volume_UUID][ "volume_state" ] != constants.INITIALIZED ) ): raise RuntimeError("%s:\t Need to initialize volume" % ( entry, )) self._volume = entry.application_context["volumes"][self._volume_UUID] self._disks = self._volume["disks"] # now check validity of disk_UUID if self._disk_UUID not in self._disks.keys(): raise RuntimeError("%s:\t Disk not part of volume" % ( entry, )) # sanity check that this level is no more than all the others: for disk_UUID, disk in self._disks.items(): if ( disk_UUID != self._disk_UUID and ( disk["level"] < self._disks[self._disk_UUID]["level"] ) ): raise RuntimeError("Error in levels") self._disks[self._disk_UUID]["state"] = constants.REBUILD ## Before pollable sends response status service function ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns finished (bool) returns true if finished def before_response_status(self, entry): # initial_setup, also check if we need to add thid disk out of no-where self.initial_setup(entry) # Re-send the management part self._response_content = html_util.create_html_page( "", constants.HTML_DISPLAY_HEADER, 0, display_disks_service.DisplayDisksService.get_name(), ) self._response_headers = { "Content-Length": "%s" % len(self._response_content), } return True # REBULD PART, DONE BEFORE TERMINATE (AFTER CLOSE) ## Rebuilding States ( GET_DATA_STATE, SET_DATA_STATE, UPDATE_LEVEL_STATE, FINAL_STATE ) = range(4) # STATE FUNCTIONS: ## Before we get the rebulding data ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns epsilon_path (bool) if there is no need for input def before_get_data(self, entry): self._current_block_num, self._current_data = ( self._disks[self._disk_UUID]["cache"].next_block() ) if self._current_data is not None: # got data stored in cache, no need for hard rebuild # ==> This is an epsilon_path return True else: # need to retreive data from XOR of all the disks besides the current # in order to rebuild it request_info = {} for disk_UUID in self._disks.keys(): if disk_UUID != self._disk_UUID: request_info[disk_UUID] = { "block_num" : self._current_block_num, "password" : self._volume["long_password"] } self._disk_manager = disk_manager.DiskManager( self._disks, self._pollables, entry, service_util.create_get_block_contexts( self._disks, request_info ) ) entry.state = constants.SLEEPING_STATE return False # need input, not an epsilon path ## After we get the rebulding data ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns next_state (int) next state of StateMachine. None if not ## ready to move on to next state. def after_get_data(self, entry): # first check if the data has come from the cache if self._current_data is not None: return ConnectService.SET_DATA_STATE # now we know that the data has come from the other disks. check if # they all finished and their responses if not self._disk_manager.check_if_finished(): return None if not self._disk_manager.check_common_status_code("200"): raise RuntimeError( "Block Device Server sent a bad status code" ) # data not saved in cache, need to xor all the blocks blocks = [] for disk_num, response in self._disk_manager.get_responses().items(): blocks.append(response["content"]) # check if finished scratch mode for cache if ( ( self._disks[self._disk_UUID]["cache"].mode == cache.Cache.SCRATCH_MODE ) and disk_util.all_empty(blocks) ): # all the blocks we got are empty, change to cache mode self._disks[self._disk_UUID]["cache"].mode = ( cache.Cache.CACHE_MODE ) # nothing to set now, we stay in GET_DATA_STATE and start working # from cache return ConnectService.GET_DATA_STATE else: self._current_data = disk_util.compute_missing_block( blocks ) return ConnectService.SET_DATA_STATE ## Before we set the rebulding data ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns epsilon_path (bool) if there is no need for input def before_set_data(self, entry): self._disk_manager = disk_manager.DiskManager( self._disks, self._pollables, entry, service_util.create_set_block_contexts( self._disks, { self._disk_UUID: { "block_num": self._current_block_num, "content": self._current_data, "password" : self._volume["long_password"] } } ) ) entry.state = constants.SLEEPING_STATE return False # need input, not an epsilon path ## After we set the rebulding data ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns next_state (int) next state of StateMachine. None if not ## ready to move on to next state. def after_set_data(self, entry): if not self._disk_manager.check_if_finished(): return None if not self._disk_manager.check_common_status_code("200"): raise RuntimeError( "Block Device Server sent a bad status code" ) if self.check_if_built(): return ConnectService.UPDATE_LEVEL_STATE return ConnectService.GET_DATA_STATE ## Before we update the level of the updated disk ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns epsilon_path (bool) if there is no need for input def before_update_level(self, entry): self._disk_manager = disk_manager.DiskManager( self._disks, self._pollables, entry, service_util.create_update_level_contexts( self._disks, { self._disk_UUID: { "addition" : "1", "password" : self._volume["long_password"] } } ) ) entry.state = constants.SLEEPING_STATE return False # need input, not an epsilon path ## Before we have updated the level of the updated disk ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns next_state (int) next state of StateMachine. None if not ## ready to move on to next state. def after_update_level(self, entry): if not self._disk_manager.check_if_finished(): return None if not self._disk_manager.check_common_status_code("200"): raise RuntimeError( "Block Device Server sent a bad status code" ) self._disks[self._disk_UUID]["level"] += 1 self._disks[self._disk_UUID]["state"] = constants.ONLINE entry.state = constants.CLOSING_STATE return ConnectService.FINAL_STATE ## Rebuilding states for StateMachine STATES = [ state.State( GET_DATA_STATE, [SET_DATA_STATE], before_get_data, after_get_data, ), state.State( SET_DATA_STATE, [GET_DATA_STATE, UPDATE_LEVEL_STATE], before_set_data, after_set_data, ), state.State( UPDATE_LEVEL_STATE, [FINAL_STATE], before_update_level, after_update_level, ), state.State( FINAL_STATE, [FINAL_STATE], ), ] ## Before pollable terminates service function ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to ## @returns finished (bool) returns true if finished def before_terminate(self, entry): # create the state machine for rebuilding disk first_state_index = ConnectService.GET_DATA_STATE if self._new_disk_mode: first_state_index = ConnectService.NEW_DISK_SETUP_STATE elif self.check_if_built(): first_state_index = ConnectService.UPDATE_LEVEL_STATE # create rebuild state machine self._state_machine = state_machine.StateMachine( ConnectService.STATES, ConnectService.STATES[first_state_index], ConnectService.STATES[ConnectService.FINAL_STATE] ) # pass args to the machine, will use *args to pass them on self._state_machine.run_machine((self, entry)) ## Called when BDSClientSocket invoke the on_finsh method to wake up ## the ServiceSocket. Let StateMachine handle the wake up call. ## @param entry (@ref common.pollables.pollable.Pollable) entry we belong ## to def on_finish(self, entry): # pass args to the machine, will use *args to pass them on self._state_machine.run_machine((self, entry)) ## Checks if self._disk_UUID is built ## @returns built (bool) if disk needs to be rebuilt def check_if_built(self): # check if already connected, no need to rebuild, or cache is empty if ( self._disks[self._disk_UUID]["state"] == constants.REBUILD and not self._disks[self._disk_UUID]["cache"].is_empty() ): return False return True
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import requests import json class Github: def __init__(self): self.user = 'pug-ma' self.repository = 'meetups' self.base_url = 'https://api.github.com/repos' def _name_encontro(self, index): if len(index) == 1: index = '0' + index return requests.utils.quote(f'PUG-MA #{index}.jpg') def photo_encontro(self, index): url = f'{self.base_url}/{self.user}/{self.repository}/contents/palestras/{self._name_encontro(index)}' response = requests.get(url) content = json.loads(response.content) return content.get('download_url') def photo_last_encontro(self): url = f'{self.base_url}/{self.user}/{self.repository}/contents/palestras/' response = requests.get(url) content = json.loads(response.content) return content[-1].get('download_url')
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from __future__ import unicode_literals import operator import numpy from qcache.qframe.common import assert_list, raise_malformed, is_quoted, unquote, assert_len from qcache.qframe.constants import COMPARISON_OPERATORS from qcache.qframe.context import get_current_qframe JOINING_OPERATORS = {'&': operator.and_, '|': operator.or_} def _leaf_node(df, q): if isinstance(q, basestring): if is_quoted(q): return q[1:-1].encode('utf-8') try: return df[q] except KeyError: raise_malformed("Unknown column", q) return q def _bitwise_filter(df, q): assert_len(q, 3) op, column, arg = q if not isinstance(arg, (int, long)): raise_malformed('Invalid argument type, must be an integer:'.format(t=type(arg)), q) try: series = df[column] & arg if op == "any_bits": return series > 0 return series == arg except TypeError: raise_malformed("Invalid column type, must be an integer", q) def _not_filter(df, q): assert_len(q, 2, "! is a single arity operator, invalid number of arguments") return ~_do_pandas_filter(df, q[1]) def _isnull_filter(df, q): assert_len(q, 2, "isnull is a single arity operator, invalid number of arguments") # Slightly hacky but the only way I've come up with so far. return df[q[1]] != df[q[1]] def _comparison_filter(df, q): assert_len(q, 3) op, col_name, arg = q return COMPARISON_OPERATORS[op](df[col_name], _do_pandas_filter(df, arg)) def _join_filter(df, q): result = None if len(q) < 2: raise_malformed("Invalid number of arguments", q) elif len(q) == 2: # Conjunctions and disjunctions with only one clause are OK result = _do_pandas_filter(df, q[1]) else: result = reduce(lambda l, r: JOINING_OPERATORS[q[0]](l, _do_pandas_filter(df, r)), q[2:], _do_pandas_filter(df, q[1])) return result def prepare_in_clause(q): """ The arguments to an in expression may be either a list of values or a sub query which is then executed to produce a list of values. """ assert_len(q, 3) _, col_name, args = q if isinstance(args, dict): # Sub query, circular dependency on query by nature so need to keep the import local from qcache.qframe import query current_qframe = get_current_qframe() sub_df, _ = query(current_qframe.df, args) try: args = sub_df[col_name].values except KeyError: raise_malformed('Unknown column "{}"'.format(col_name), q) if not isinstance(args, (list, numpy.ndarray)): raise_malformed("Second argument must be a list", q) return col_name, args def _in_filter(df, q): col_name, args = prepare_in_clause(q) return df[col_name].isin(args) def _like_filter(df, q): assert_len(q, 3) op, column, raw_expr = q if not is_quoted(raw_expr): raise_malformed("like expects a quoted string as second argument", q) regexp = unquote(raw_expr) if not regexp.startswith('%'): regexp = '^' + regexp else: regexp = regexp[1:] if not regexp.endswith('%'): regexp += '$' else: regexp = regexp[:-1] # 'like' is case sensitive, 'ilike' is case insensitive case = op == 'like' try: return df[column].str.contains(regexp, case=case, na=False) except AttributeError: raise_malformed("Invalid column type for (i)like", q) def _do_pandas_filter(df, q): if not isinstance(q, list): return _leaf_node(df, q) if not q: raise_malformed("Empty expression not allowed", q) result = None op = q[0] try: if op in ('any_bits', 'all_bits'): result = _bitwise_filter(df, q) elif op == "!": result = _not_filter(df, q) elif op == "isnull": result = _isnull_filter(df, q) elif op in COMPARISON_OPERATORS: result = _comparison_filter(df, q) elif op in JOINING_OPERATORS: result = _join_filter(df, q) elif op == 'in': result = _in_filter(df, q) elif op in ('like', 'ilike'): result = _like_filter(df, q) else: raise_malformed("Unknown operator", q) except KeyError: raise_malformed("Column is not defined", q) except TypeError: raise_malformed("Invalid type in argument", q) return result def pandas_filter(df, filter_q): if filter_q: assert_list('where', filter_q) return df[_do_pandas_filter(df, filter_q)] return df
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# coding: utf-8 from __future__ import absolute_import, print_function, unicode_literals, division import logging from sqlalchemy.ext.declarative import declarative_base from oslo_db.sqlalchemy import models from sqlalchemy import create_engine from sqlalchemy import Column, String, Integer, DateTime from sqlalchemy.sql import fun LOG = logging.getLogger(__name__) BASE = declarative_base() class TestData(models.ModelBase, BASE): __tablename__ = 'test_data' id = Column(Integer, primary_key=True, autoincrement=True) data = Column(String(256), nullable=False) create_time = Column(DateTime, server_default=func.now(), nullable=False) def __init__(self, *args, **kwargs): super(TestData, self).__init__() for k, v in kwargs.items(): setattr(self, k, v) def create_tables(engine=None): if not engine: try: import sys engine = sys.argv[1] except IndexError: engine = "sqlite:///:memory:" engine = create_engine(engine, echo=True) BASE.metadata.create_all(engine) if __name__ == '__main__': create_tables("sqlite:///:memory:")
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from app import view # imports from module folders are relative to the file being executed by python3 since main.py is at the top level, imports need to come from app. even for the files inside of app from app import model def run(): model.load() while True: user_account = login_menu() # returns the logged in user or None for quit if user_account == None: # login menu returns None if 'quit' is selected break else: main_menu(user_account) # when the user exits the main menu they will go back to login def login_menu(): while True: view.print_login_menu() choice = view.login_prompt().strip() if choice not in ("1", "2", "3"): view.bad_login_input() elif choice == "3": view.goodbye() return None # return None for quit elif choice == "1": """ TODO: prompt for firstname, lastname, and pin, and confirm pin create the account and then tell the user what their new account number is """ pass elif choice == "2": """ TODO: prompt functions to ask for account and PIN, use try, except to check for bad login """ return model.login("012345", "1234") def create_account(): """ call this from the main login loop """ pass def login_attempt(): """ call this from the main login loop """ pass def main_menu(user): while True: view.print_main_menu(user) choice = view.main_prompt() """ TODO: add bad input message """ if choice == "4": user["balance"] += 1.0 # delete this, just demonstrating model.save() model.save(user) return """ TODO: implement the various options """
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#!/usr/bin/python # -*- coding: utf-8 -*- # This is a python bot written by Jonas Lindstad (LDEV) # You are free to use this code, which is licensed under the "WTFPL license". # # --------------------------------------------------------------------- # # DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE # Version 2, December 2004 # # Copyright (C) 2004 Sam Hocevar <sam@hocevar.net> # # Everyone is permitted to copy and distribute verbatim or modified # copies of this license document, and changing it is allowed as long # as the name is changed. # # DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE # TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION # # 0. You just DO WHAT THE FUCK YOU WANT TO. # # --------------------------------------------------------------------- # # # TODO: # * http://stackoverflow.com/questions/930700/python-parsing-irc-messages # * Få nick-greia inn i en while-løkke, som sikrer at den får et unikt brukernavn # * Append users to auto-op file from IRC channel # * Skille ut config i egen fil # # MODULES # import socket import sys from random import choice import time import datetime import logging import logging.handlers # why? from subprocess import Popen, PIPE # For calling traceroute import signal # for ctrl-c catching import sys # for ctrl-c catching from platform import platform # Finne linuxversjon etc. from os import path # finding the current script path # import urllib2 # URL grabbing import simplejson as json # Config parsing import re # URL grabbing from urllib import request # URL grabbing # # VARIABLES # client_name = 'ldevirc' version = '0.1a' working_dir = path.dirname(path.realpath(__file__)) # no trailing slash # load configuration file with open('%s/config.json' % working_dir) as data_file: config = json.load(data_file) # # LOGGING # Good article about logging: http://victorlin.me/posts/2012/08/26/good-logging-practice-in-python # logger.<level> = debug, info, warn, error # logger_file = '%s/logs/%s_%s' % (working_dir, config['network'].lower(), config['channel'].lower()) logger = logging.getLogger(version) logger_level = logging.getLevelName(config['logging']['level']) logger.setLevel(logger_level) handler = logging.handlers.RotatingFileHandler(logger_file, 'a', maxBytes=config['logging']['max_file_size'], backupCount=config['logging']['max_number_of_files'], encoding=config['server_encoding']) handler.setLevel(logger_level) formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s') # left "%(name)" out on purpose handler.setFormatter(formatter) logger.addHandler(handler) logger.info('%s started' % version) # # FUNCTIONS # def find_user(str): return str.split('!')[0][1:] def traceroute(dest, user): dest = dest.replace('|', '').replace(';', '').replace('&', '') # somewhat securing against malicious input.. irc_cmd('PRIVMSG %s :Performing trace towards %s\r\n' % (user, dest)) trace_log_text = "Performing traceroute towards %s (requested by %s)" % (dest, user) logger.info(trace_log_text) p = Popen(['tracepath', dest], stdout=PIPE) while True: line = p.stdout.readline() # return bytes if not line: break line = line.decode("utf-8") irc.send(('PRIVMSG %s :%s\r\n' % (user, line)).encode()) # to remove b'' from line # send string to IRC server def irc_cmd(text): irc.send(("%s\r\n" % text).encode(config['server_encoding'])) def timestamp(): return datetime.datetime.now().isoformat().split('.')[0] # handle ctrl+c gracefully def signal_handler(signal, frame): print ('\nctrl+c detected. Disconnecting from %s' % config['server']) logger.warn(text.strip()) irc_cmd("QUIT :%s" % config['quit_message']) time.sleep(1) sys.exit(0) def grab_title(url): resource = request.urlopen(url) source = resource.read().decode(resource.headers.get_content_charset()) match = re.findall(r'<title>(.*?)</title>', source, re.S) if match: title = match[0].replace('\n', '').strip() logger.info('titlegrabber: Grabbed title "%s"' % title) irc_cmd('PRIVMSG %s :(%s)' % (config['channel'], title)) return title else: logger.info('titlegrabber: No match for <title></title>') # # PERFORM IRC CONNECTION # signal.signal(signal.SIGINT, signal_handler) print ('\r\npress ctrl+c to close the connection to the server') irc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) logger.info("ldevirc connecting to %s (%s)" % (config['network'], config['server'])) irc.connect((config['server'], config['port'])) irc_cmd('USER %s Testing 0 * :...' % (config['botnick'])) time.sleep(1) # Prevent Excess flood at a couple of networks (EFnet for instance) irc_cmd('NICK %s' % config['botnick']) time.sleep(1) # Prevent Excess flood at a couple of networks (EFnet for instance) # # TODO: Replace with while-loop of some sort # text = irc.recv(4096).decode(config['server_encoding']) if text.find('ERR_ALREADYREGISTRED') != -1: logger.info('Nick %s taken. Attempting to use %s-' % (config['botnick'], config['botnick'])) irc_cmd('NICK %s-' % config['botnick']) else: logger.info('Registered nick %s' % config['botnick']) # prevents loop if the server closed the connection if text.find('ERROR') !=-1: # print('[%s] ERROR: %s' % timestamp(), text) log.error('%s' % text) sys.exit(1) # join channel irc_cmd("JOIN %s" % config['channel']) logger.info("Joined channel %s" % config['channel']) # # MAIN LOOP - PROCESSING # while 1: # receive data from IRC server text = irc.recv(4096).decode(config['server_encoding']) if len(text.strip()) == 0: logger.error('No data from IRC server - Either IRC server disconnected client or server crashed') sys.exit(1) # print text to terminal for line in text.split('\n'): if len(line.strip()) > 0: if text.find(config['botnick']) != -1: print('[%s] %s' % (timestamp(), line.strip())) logger.info(line.strip()) else: logger.debug(line.strip()) # # BOT CONTROL # if text.find('PING') != -1: logger.debug('PONG %s' % (text.split()[1])) irc_cmd(('PONG %s' % (text.split()[1]))) # Join on kick if text.find('KICK %s %s' % (config['channel'], config['botnick'])): if text.split(' ')[1] == 'KICK' and text.split(' ')[2] == config['channel'] and text.split(' ')[3] == config['botnick']: logger.warn(text) time.sleep(1) irc_cmd("JOIN %s" % config['channel']) time.sleep(0.5) irc_cmd('PRIVMSG %s :I\'m back, bitches!' % config['channel']) # # CTCP # http://www.irchelp.org/irchelp/rfc/ctcpspec.html # http://www.kvirc.net/doc/doc_ctcp_handling.html # Skipped CTCP commands: SOURCE, USERINFO, ERRMSG # # FINGER - Returns the user's full name, and idle time if text.find('PRIVMSG %s :\u0001FINGER\u0001' % (config['botnick'])) != -1: logger.debug('NOTICE %s :\u0001FINGER %s by ldev.no\u0001' % (find_user(text), config['botnick'])) irc_cmd('NOTICE %s :\u0001FINGER %s by ldev.no\u0001' % (find_user(text), config['botnick'])) # VERSION - The version and type of the client if text.find('PRIVMSG %s :\u0001VERSION\u0001' % (config['botnick'])) != -1: # logger.debug('NOTICE %s :\u0001VERSION %s:%s\u0001' % (find_user(text), version, platform())) # irc_cmd('NOTICE %s :\u0001VERSION %s:%s\u0001' % (find_user(text), version, platform())) logger.info('NOTICE %s :\u0001VERSION %s:%s:%s\u0001' % (find_user(text), client_name, version, platform())) irc_cmd('NOTICE %s :\u0001VERSION %s:%s:%s\u0001' % (find_user(text), client_name, version, platform())) # CLIENTINFO - Dynamic master index of what a client knows if text.find('PRIVMSG %s :\u0001CLIENTINFO\u0001' % (config['botnick'])) != -1: logger.debug('NOTICE %s :\u0001VERSION %s under development by Jonas Lindstad\u0001' % version) irc_cmd('NOTICE %s :\u0001VERSION %s under development by Jonas Lindstad\u0001' % version) # PING - Used to measure the delay of the IRC network between clients. if text.find('PRIVMSG %s :\u0001PING\u0001' % (config['botnick'])) != -1: logger.debug('NOTICE %s :\u0001PING %s\u0001' % (text.split()[2])) irc_cmd('NOTICE %s :\u0001PING %s\u0001' % (text.split()[2])) # TIME - Gets the local date and time from other clients. if text.find('PRIVMSG %s :\u0001TIME\u0001' % (config['botnick'])) != -1: logger.debug('NOTICE %s :\u0001TIME %s\u0001' % timestamp()) irc_cmd('NOTICE %s :\u0001TIME %s\u0001' % timestamp()) # # CAP - capabilities # http://www.leeh.co.uk/draft-mitchell-irc-capabilities-02.html # # # All the extra shit # # help if text.find('!help') !=-1 and text.find(config['botnick']) == -1: logger.info('PRIVMSG %s :This is %s. Commands: !help, !bully <user>, !trace <host>' % (config['channel'], version)) irc_cmd('PRIVMSG %s :This is %s. Commands: !help, !bully <user>, !trace <host>' % (config['channel'], version)) # bully if text.find(':!bully') != -1: with open('%s/bully.txt' % working_dir) as f: lines = f.read().splitlines() to = text.split(':!bully')[1].strip() phrase = choice(lines) logger.info('PRIVMSG %s :%s %s' % (config['channel'], to, phrase)) irc_cmd('PRIVMSG %s :%s %s' % (config['channel'], to, phrase)) # gay if text.find('gay') !=-1 and text.find(config['botnick']) == -1: logger.info('PRIVMSG %s :%s er gay!' % (config['channel'], find_user(text))) irc_cmd('PRIVMSG %s :%s er gay!' % (config['channel'], find_user(text))) # auto OP if text.find("JOIN :%s" % config['channel']) !=-1 and text.find(config['botnick']) == -1: auto_op_file = '%s/auto-op/%s_%s' % (working_dir, config['network'].lower(), config['channel'].lower()) logger.debug('Checking auto-op file "%s"' % auto_op_file) if path.isfile(auto_op_file): with open(auto_op_file) as f: operators = f.read().splitlines() if any(ext in text for ext in operators): to = text.split('!')[0][1:] irc_cmd(('PRIVMSG %s :Hei, deg kjenner jeg!' % config['channel'])) logger.info(('MODE %s +o %s' % (config['channel'], to))) irc_cmd(('MODE %s +o %s' % (config['channel'], to))) else: logger.debug('User not in auto-op file') else: logger.debug('No auto-op file for this network/channel') # trace if text.find(':!trace') != -1: dest = text.split(':!trace')[1].strip() traceroute(dest, find_user(text)) # URL title grabber if text.find(config['botnick']) == -1 and (text.find('http://') != -1 or text.find('https://') != -1): urls = re.findall(r'(https?://\S+)', text) try: logger.info('titlegrabber: Fetching title from %s' % urls[0]) grab_title(urls[0]) except: logger.info('titlegrabber: Failed to fetch title from %s' % urls[0]) # e = sys.exc_info()[0] logger.error(sys.exc_info()) # print(sys.exc_info()) pass
[ "jonaslindstad@gmail.com" ]
jonaslindstad@gmail.com
b6a9c5e223340c1cbc33d718e31f775d955b1a8d
f0d9477c3079ff955b826c8ba2f4d043c17c012c
/home/models.py
c9c0352949dd5d3c6c652faf271cd3fd4fb9b767
[]
no_license
embshao/junkfund
f19859b4f561da79c47b3dbc0dfea98c923fa25b
e32d47fe0d248b9b47cfb1dc32602b57869df81b
refs/heads/master
2020-04-06T17:30:57.855468
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2018-12-06T08:07:10
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from django.db import models from wagtail.core.models import Page from wagtail.core.fields import RichTextField from wagtail.admin.edit_handlers import FieldPanel class HomePage(Page): body = RichTextField(blank=True) origin_statement = RichTextField(blank=True) mission_statement = RichTextField(blank=True) content_panels = Page.content_panels + [ FieldPanel('body', classname="full"), FieldPanel('origin_statement'), FieldPanel('mission_statement') ]
[ "embshao@Emilys-MacBook-Pro.local" ]
embshao@Emilys-MacBook-Pro.local
8ecf7bb0305c592d0b6011e7db8ef79bcf6f8662
7844d638111af81f9c8ff77b3808b27a130454e0
/kws_test/feature/dct.py
4a58bca56dce4b9644ff979a0dc33c79cdd177c0
[]
no_license
tu1258/kws_test
1bb9d664f967744aab2b8537dd6fe4bebb50f17d
b39bda2dc7a7ab0ce1c2d1c8e6a069159a44e9da
refs/heads/master
2022-12-23T14:21:12.550151
2020-09-30T08:35:40
2020-09-30T08:35:40
299,853,532
1
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# coding=utf-8 # Copyright 2020 The Google Research 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. """compute direct forward DCT II on input speech signal.""" import numpy as np import tensorflow.compat.v2 as tf class DCT(tf.keras.layers.Layer): """Computes forward DCT transofmation. It is based on direct implementation described at https://dsp.stackexchange.com/questions/2807/fast-cosine-transform-via-fft This is useful for speech feature extraction. """ def __init__(self, num_features=None, **kwargs): super(DCT, self).__init__(**kwargs) self.num_features = num_features def build(self, input_shape): super(DCT, self).build(input_shape) # dct is computed on last dim feature_size = int(input_shape[-1]) if self.num_features is None: self.num_features = int(input_shape[-1]) if self.num_features > feature_size: raise ValueError('num_features: %d can not be > feature_size: %d' % (self.num_features, feature_size)) # precompute forward dct transformation self.dct = 2.0 * np.cos(np.pi * np.outer( np.arange(feature_size) * 2.0 + 1.0, np.arange(feature_size)) / (2.0 * feature_size)) # DCT normalization norm = 1.0 / np.sqrt(2.0 * feature_size) # reduce dims, so that DCT is computed only on returned features # with size num_features self.dct = (self.dct[:, :self.num_features] * norm).astype(np.float32) def call(self, inputs): # compute DCT return tf.matmul(inputs, self.dct) def get_config(self): config = { 'num_features': self.num_features, } base_config = super(DCT, self).get_config() return dict(list(base_config.items()) + list(config.items()))
[ "noreply@github.com" ]
tu1258.noreply@github.com
1ab07df2d4cec989d96642020c6ad40a27c362f8
20931bf9e3f24b4acd5fcbf5e50cfa77d61b25e5
/msds510/src/write_csv.py
781e934c9c33dcd19dea2bd7420addb247c003b2
[]
no_license
Yasa-Mufasa/School-Work-DSC510
db273878c367038e4dd541c8365ee0c1ec577a7f
7f8334a830e3347bfafa408f8d901afd6e083c13
refs/heads/master
2020-03-30T18:23:07.401211
2018-10-14T06:33:05
2018-10-14T06:33:05
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import sys import csv def argumentExists(index): try: sys.argv[index] except IndexError: return '' else: return sys.argv[index] def fixHeader(headerToFix): corr_category = headerToFix corr_category = corr_category.lower() corr_category.strip('\n').strip('?').rstrip().lstrip() corr_category = corr_category.replace('/','_') return corr_category def processedCSV(output, headers, input): with open(output, 'w', newline='') as written: dw = csv.DictWriter(written, fieldnames=headers) firstRow = {} for i in headers: firstRow[i] = i dw.writerow(firstRow) for row in input: dw.writerow(row) def readRows(inputCSV): with open(inputCSV, 'r') as read: readCSV = csv.DictReader(read) readCSV.fieldnames = [fixHeader(header) for header in readCSV.fieldnames] listOfOrderedDics = [] for row in readCSV: listOfOrderedDics.append(row) return readCSV.fieldnames, listOfOrderedDics if __name__ == '__main__': csvToRead = argumentExists(1) csvToCreate = argumentExists(2) if csvToRead and csvToCreate: getCSV = readRows(csvToRead) processedCSV(csvToCreate, getCSV[0], getCSV[1])
[ "noreply@github.com" ]
Yasa-Mufasa.noreply@github.com
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/manuscript_codes/AML211DiffALL/remove_nonexistent_fromAnnotatedcsv.py
409adfbaa7c37d20329ae26f43f38331d13472ce
[]
no_license
KuehLabUW/UPSIDE
95ce078382792d1beb0574c3b19c04e467befa58
3c90de9677f24e258800cb95bce6cb528f4ad4ac
refs/heads/master
2023-07-13T15:58:07.963672
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sat Mar 23 16:21:25 2019 this script concatenates fluorescent data and subim data from separate csv files and return a merged csv file for all positions @author: phnguyen """ import pandas as pd import os csvs_dirname = '/media/phnguyen/Data2/Imaging/CellMorph/data/AML211DiffALL/csvs/' os.chdir(csvs_dirname) filename = 'AML211DiffALL_LargeMask_Annotated.csv' df = pd.read_csv(filename) print(len(df)) pos = []; for i in range(len(df.index)): if os.path.isfile(df.dirname[i]) == False: pos.append(i) print(i) df.drop(df.index[pos], inplace=True) #save the combined dataframe df.to_csv(csvs_dirname+'AML211DiffALL_LargeMask_Annotated_trimmed.csv', sep=',')
[ "kuehlab@uw.edu" ]
kuehlab@uw.edu
7b20eeb2fb379e209c3fb4674150a090949fec81
8398073ca4e7b4e9894f037ff87c5c2a2c2d7658
/sorting/quick_sort.py
a4352435158fd2ae6b27e8c59f6f03df82c5e54c
[]
no_license
mtvillwock/cs
9c78262e29c23eabdecd4778c163140c0a1c0061
7f4f0236ecc1769ac84bbebdaf5cd3fcbd65f8f7
refs/heads/master
2020-03-31T19:16:33.000451
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#!/usr/bin/python # Quick Sort class that allows for O(lg 2 n) to O(n^2) sorting of items, # depending on where pivot picked happens to be within context of all sorted items # Low memory overhead as it simply swaps items during comparisons class QuickSort: def __init__(self, items): self.items = items def sort(self, low = None, high = None): if(low == None): low = 0 if (high == None): high = len(self.items) - 1 if(high - low > 0): pivot = self.partition(low, high) self.sort(low, pivot - 1) self.sort(pivot + 1, high) def partition(self, low, high): pivot = high first_high = low for i in range(low, high): if(self.items[i] < self.items[pivot]): # Swap items self.items[i], self.items[first_high] = self.items[first_high], self.items[i] first_high += 1 self.items[pivot], self.items[first_high] = self.items[first_high], self.items[pivot] return first_high import random print "Initialize QuickSort with list" items = [3, 45, 89, 1, 7, 34940, 222222, 18, 2342, 344, 34, 233] # Shuffle items randomly random.shuffle(items) print "Unsorted items: " + ", ".join(str(i) for i in items) ms = QuickSort(items) ms.sort() print "Sorted items: " + ", ".join(str(i) for i in ms.items)
[ "geeosh@gmail.com" ]
geeosh@gmail.com
b39f7d7bc5979960cc3a326e3a5e41d319fc3636
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/app/honor/student/listen_everyday/object_page/history_page.py
014714a71b529b852af33e51e693c88f7b3b6757
[]
no_license
vectorhuztt/test_android_copy
ca497301b27f49b2aa18870cfb0fd8b4640973e5
f70ab6b1bc2f69d40299760f91870b61e012992e
refs/heads/master
2021-04-03T19:26:48.009105
2020-06-05T01:29:51
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# coding: utf-8 # ------------------------------------------- # Author: Vector # Date: 2018/12/17 16:11 # ------------------------------------------- from selenium.webdriver.common.by import By from app.honor.student.login.object_page.home_page import HomePage from conf.base_page import BasePage from conf.decorator import teststep from utils.wait_element import WaitElement class HistoryPage(BasePage): wait = WaitElement() home = HomePage() @teststep def wait_check_history_page(self): locator = (By.XPATH, "//android.widget.TextView[@text='历史推荐']") return self.wait.wait_check_element(locator) @teststep def wait_check_clear_button_page(self): locator = (By.ID, self.id_type() + 'clear') return self.wait.wait_check_element(locator, timeout=5) @teststep def wait_check_red_hint_page(self): locator = (By.ID, self.id_type() + 'tv_hint') return self.wait.wait_check_element(locator, timeout=5) @teststep def wait_check_img_page(self): locator = (By.ID, self.id_type() + 'img') return self.wait.wait_check_element(locator, timeout=5) @teststep def wait_check_tips_page(self): locator = (By.ID, self.id_type() + 'md_content') return self.wait.wait_check_element(locator, timeout=5) @teststep def game_name(self): locator = (By.ID, self.id_type() + 'game_name') return self.wait.wait_find_elements(locator) @teststep def right_rate(self, game_name): locator = (By.XPATH, '//android.widget.TextView[contains(@text,"{0}")]/../following-sibling::android.widget.' 'TextView[contains(@resource-id, "{1}right_rate")]'.format(game_name, self.id_type())) return self.wait.wait_find_element(locator) @teststep def game_date(self, game_name): locator = (By.XPATH, '//android.widget.TextView[contains(@text,"{0}")]/../following-sibling::' 'android.widget.TextView[contains(@resource-id,"time")]'.format(game_name)) return self.wait.wait_find_element(locator) @teststep def tips_operate_commit(self): """温馨提示 页面信息 -- 确定""" if self.wait_check_tips_page(): # 温馨提示 页面 self.home.tips_content() self.home.commit_button() # 确定按钮 @teststep def history_page_operate(self): print('听力历史处理页面') game_names = self.game_name() game_num = len(game_names) if len(game_names) < 10 else len(game_names) - 1 print('游戏个数:', game_num) for i in range(game_num): if self.wait_check_history_page(): name = game_names[i].text right_rate = self.right_rate(name).text game_date = self.game_date(name).text print(name) print(right_rate) print(game_date) if i == 3 or i == 5 or i == 7: if name == '听音连句': game_names[i].click() if not self.wait_check_clear_button_page(): self.base_assert.except_error('Error-- 未发现听音连句的清除按钮') else: print('进入听音连句游戏页面') self.home.click_back_up_button() self.tips_operate_commit() if name == '听后选择': game_names[i].click() if not self.wait_check_red_hint_page(): self.base_assert.except_error('Error-- 未发现听后选择的红色提示') else: print('进入听后选择游戏页面') self.home.click_back_up_button() self.tips_operate_commit() if name == '听音选图': game_names[i].click() if not self.wait_check_img_page(): self.base_assert.except_error('Error-- 未发现听音选图的图片') else: print('进入听音选图游戏页面') self.home.click_back_up_button() self.tips_operate_commit() print('-'*30, '\n') self.home.click_back_up_button()
[ "vectorztt@163.com" ]
vectorztt@163.com
8f09ee1c175eaa67db58c061ed1f27c69414af94
20ade86a0c0f0ca6be3fae251488f985c2a26241
/exp/analyze_5.py
d038d5fa9c073324d036a898b7df5cf86f573c6a
[]
no_license
adysonmaia/phd-sp-static
69344fdd4edb4c216e4b88b0193308b33a30e72c
79038d165c19f90e1f54597f7049553720f34c74
refs/heads/master
2023-04-14T15:59:07.414873
2019-10-24T07:56:37
2019-10-24T07:56:37
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import csv import numpy as np import scipy.stats as st import matplotlib import matplotlib.pyplot as plt DPI = 100 Y_PARAM = { 'max_dv': { 'label': 'Deadline Violation - ms', 'limit': [0.0, 10.0] }, 'dsr': { 'label': 'Deadline Satisfaction - %', 'limit': [40.0, 100.0] }, 'avg_rt': { 'label': 'Response Time - ms', 'limit': [0.0, 18.0] }, 'cost': { 'label': 'Cost', 'limit': [1000.0, 1500.0] }, 'max_unavail': { 'label': 'Availability - %', 'limit': [70.0, 100.0] }, 'avg_unavail': { 'label': 'Unavailability - %', 'limit': [0.0, 10.0] }, 'avg_avail': { 'label': 'Availability - %', 'limit': [0.0, 100.0] }, 'time': { 'label': 'Execution Time - s', 'limit': [0.0, 300.0] }, } X_PARAM = { 'probability': { 'label': 'Elite Probability', 'limit': [10, 90], }, 'stop_threshold': { 'label': 'Stop Threshold', 'limit': [0, 1], } } def get_data_from_file(filename): results = [] with open(filename) as csv_file: csv_reader = csv.DictReader(csv_file) line_count = 0 for row in csv_reader: if line_count > 0: results.append(row) line_count += 1 return results def filter_data(data, **kwargs): def to_string_values(values): str_values = [] if not isinstance(values, list): values = [values] for value in values: str_values.append(str(value)) return str_values def in_filter(row): for key, value in row.items(): if key in f_values and value not in f_values[key]: return False return True f_values = {k: to_string_values(v) for k, v in kwargs.items()} return list(filter(lambda row: in_filter(row), data)) def format_metric(value, metric): value = float(value) if metric == 'max_unavail': value = 100.0 * (1.0 - value) elif metric == 'avg_unavail': value = 100.0 * value elif metric == 'avg_avail': value = 100.0 * value elif metric == 'dsr': value = 100.0 * value return value def format_field(value, field): value = float(value) if field == 'stop_threshold': value = round(value, 2) return value def calc_stats(values): nb_runs = len(values) mean = np.mean(values) sem = st.sem(values) if sem > 0.0: # Calc confidence interval, return [mean - e, mean + e] error = st.t.interval(0.95, nb_runs - 1, loc=mean, scale=sem) error = error[1] - mean else: error = 0.0 return mean, error def gen_figure(data, metric, x, x_field, data_filter, filename=None): plt.clf() matplotlib.rcParams.update({'font.size': 20}) filtered = filter_data(data, **data_filter) y = [] y_errors = [] for x_value in x: x_filter = {x_field: x_value} x_data = filter_data(filtered, **x_filter) values = list(map(lambda r: format_metric(r[metric], metric), x_data)) mean, error = calc_stats(values) y.append(mean) y_errors.append(error) print("{} x={:.1f}, y={:.1f}".format(metric, x_value, mean)) x = [format_field(i, x_field) for i in x] plt.errorbar(x, y, yerr=y_errors, markersize=10, fmt='-o') plt.subplots_adjust(bottom=0.2, top=0.97, left=0.12, right=0.96) x_param = X_PARAM[x_field] y_param = Y_PARAM[metric] plt.xlabel(x_param['label']) plt.ylabel(y_param['label']) plt.ylim(*y_param['limit']) # plt.xlim(*x_param['limit']) plt.xticks(x) plt.grid(True) if not filename: plt.show() else: plt.savefig(filename, dpi=DPI, bbox_inches='tight', pad_inches=0.05) def run(): data = get_data_from_file('exp/output/exp_5.csv') all_solutions = [ ('moga', 'preferred'), ] metric_solutions = { 'max_dv': all_solutions, # 'dsr': all_solutions, # 'avg_rt': all_solutions, 'cost': all_solutions, 'avg_unavail': all_solutions, 'time': all_solutions } params = [ { 'title': 'st', 'filter': {}, 'x_field': 'stop_threshold', 'x_values': np.arange(0.0, 0.6, 0.1) }, ] for param in params: for metric, solutions in metric_solutions.items(): for solution, sol_version in solutions: fig_title = param['title'] filter = param['filter'] filter['solution'] = solution filter['version'] = sol_version x = param['x_values'] x_field = param['x_field'] filename = "exp/figs/exp_5/fig_{}_{}_{}_{}.png".format( fig_title, metric, solution, sol_version ) gen_figure(data, metric, x, x_field, filter, filename) if __name__ == '__main__': print("Execute as 'python3 analyze.py exp_5'")
[ "adyson.maia@gmail.com" ]
adyson.maia@gmail.com
ead62ea3fed82a2e6b2323190722d00bd0d01a78
d8438d98a1103b4f7fc8fa84c0ee5521fef8a5d1
/jingdong/pipelines.py
a434947aca050d4eacdd7b596c52b38bca8667c1
[]
no_license
dgh0707/items
6c171c2bf1485c27ea6b6c14178a255c6fcfd026
9b109bc4197fb1518110d8a5fb4d839615b35171
refs/heads/master
2020-04-30T06:02:20.243072
2019-06-18T04:26:12
2019-06-18T04:26:12
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# -*- coding: utf-8 -*- # Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html import pymysql class JingdongPipeline(object): def __init__(self): # self.conn = pymysql.connect(user='root', passwd='123456', db='taobao', # host='localhost', charset='utf8') # self.cursor = self.conn.cursor() # self.cursor.execute('truncate qw_goods;') # self.conn.commit() self.conn = pymysql.connect(user='root', passwd='2018@Amber123', db='apst_share', host='47.93.244.121', charset='utf8') self.cursor = self.conn.cursor() # self.cursor.execute('truncate qw_goods;') # self.conn.commit() def process_item(self, item, spider): # tit = self.cursor.execute('select id from jd where cid=%s', (item['cid'])) # if tit: # tit = self.cursor.fetchone() # else: # self.cursor.execute( # """INSERT INTO jd (cid,goods_number,title,auctionUrl,price,brand,comm_attr,oss_imgurl,oss_imageurl)VALUES ("%s","%s","%s","%s","%s","%s","%s","%s","%s")""" % # ( # item['cid'], # item['comm_id'], # item['title'], # item['auctionUrl'], # pymysql.escape_string(item['price']), # item['brand'], # pymysql.escape_string(item['comm_attr']), # pymysql.escape_string(item['oss_imgurl']), # pymysql.escape_string(item['oss_imageurl']), # # ) # ) # tit = self.cursor.lastrowid # self.conn.commit() tit = self.cursor.execute('select id from qw_goods where goods_number=%s', (item['comm_id'])) if tit: tit = self.cursor.fetchone() else: self.cursor.execute( """INSERT INTO qw_goods (cid,goods_number,brand,goodsname,auctionurl,goodsprice,goods_attribute,goodsthumb,details,discount_price)VALUES ("%s","%s","%s","%s","%s","%s","%s","%s","%s","%s")""" % ( item['cid'], item['comm_id'], pymysql.escape_string(item['brand']), item['title'], item['auctionUrl'], item['price'], pymysql.escape_string(item['comm_attr']), pymysql.escape_string(item['oss_imgurl']), pymysql.escape_string(item['oss_imageurl']), item['discount_price'], ) ) tit = self.cursor.lastrowid self.conn.commit() return item
[ "815060473@qq.com" ]
815060473@qq.com
035067ece4ae3373879cbb19730d1349f123b2b5
c61616a2d328cbe8f1980160d6769d7b13059de4
/Python/analisador.py
ac85733a3a1d23748a2466a7bd426cb48df8bd07
[]
no_license
jms05/BioLab
01ef2b2f6983752525dacf37595ef2152848ed35
eb05e56ec301b28f09df72b79964b58a6de99f84
refs/heads/master
2021-01-12T09:29:50.940398
2017-01-20T11:43:33
2017-01-20T11:43:33
76,168,639
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from Bio import SeqIO import requests from io import StringIO import re from Bio.Blast import NCBIWWW from Bio.Blast import NCBIXML from Bio import ExPASy import urllib from Bio import SwissProt from Bio.SwissProt import KeyWList from Bio import ExPASy import os import random from urllib.request import urlopen DNA_BASES = ["A","T","C","G"] PROTAIN_BASES= ['I', 'M', 'T', 'N', 'K', 'S', 'R', 'P', 'H', 'Q', 'V', 'A', 'D', 'E', 'G', 'F', 'L', 'Y', 'C', '_', 'W',] START_BASE = 'M' END_BASE = '_' DNA_COMPLEMENT = {"A":"T","T":"A","C":"G","G":"C"} CODONS = { 'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M', 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T', 'AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K', 'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R', 'CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L', 'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P', 'CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q', 'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R', 'GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V', 'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A', 'GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E', 'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G', 'TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S', 'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L', 'TAC':'Y', 'TAT':'Y', 'TAA':'_', 'TAG':'_', 'TGC':'C', 'TGT':'C', 'TGA':'_', 'TGG':'W', } def parseFile(filename): seq_record = SeqIO.read(filename, "genbank") return seq_record def reverseComplement(dnaSeq): comp="" for base in dnaSeq: comp+=DNA_COMPLEMENT[base] return comp[::-1] def parseXML(textxml): starf= False satrtG = False startFeat = False functions = [] function = "" name ="" domains = [] for line in textxml.splitlines(): if "<comment type=\"function\">" in line: starf =True function="" if(("</comment>" in line) and starf): starf = False functions.append(function) if(starf): function+=(line.strip()) if "<feature" in line: startFeat=True if "</feature>" in line: startFeat=False if(startFeat): if "type=\"domain\"" in line: campos = line.split() for campo in campos: if "description" in campo: interesse = campo.split("=")[1].replace("\"","") domains.append(interesse) if "<gene>" in line: satrtG=True if "</gene>" in line: satrtG=False if(satrtG): if "primary" in line: name = line.split(">")[1].split("<")[0] ret = [] for fun in functions: ret.append(fun.split("<")[-2].split(">")[1]) if(name ==""): name = "-" domianTex = "" for domain in domains: domianTex+=(domain+"|") if domianTex=="": domianTex="-" return(ret,name,domianTex) def parseTXT(record): try: status = str(record.data_class) except Exception: status= "-" local = "-" name = "-" funcMolec = [] bioPro = [] for cr in record.cross_references: if(cr[0]== "GO"): (tipo,ids,cool,pis) =cr if(tipo=="GO"): cools = str(cool).split(":") if(cools[0]=='F'): funcMolec.append(cools[1]) if (cools[0]=='P'): bioPro.append(cools[1]) if (cools[0]=='C'): local=cools[1] return (status,local,funcMolec,bioPro) def downloadSwiss(idfasta,ext): target_url = "http://www.uniprot.org/uniprot/" + idfasta+ "."+ext ret = urlopen(target_url).read() return ret def parseSwissProt(idswiss): txt =downloadSwiss(idswiss,"txt") xml = downloadSwiss(idswiss,"xml") #ficheirs ja aqui f =open("tmp.dat","w") f.write(txt.decode('utf-8')) f.close() handle = open("tmp.dat") (status,local,funcMol,bioPro) = parseTXT(SwissProt.read(handle)) #parse ao txt feito (functions,name,domianTex) = parseXML(xml.decode('utf-8')) return(status,local,funcMol,bioPro,functions,name,domianTex) #print(str(record)) def getinfosfromgem(genbank): ACC = "NC_002942" ret =[] i=0 dna = genbank.seq for feat in rec.features: #pri(str(feat)) if feat.type == 'CDS': strand = str(feat.location).split("]")[1] inter= str(feat.location).split("]")[0].replace("[","") start = int(inter.split(":")[0]) end = int(inter.split(":")[1]) if(strand=="(-)"): strand="(-)" seqdnaprot= reverseComplement(dna[start:end]) else: strand="(+)" seqdnaprot= str((dna[start:end])) geneID = feat.qualifiers["db_xref"][0] ID_prot = feat.qualifiers["protein_id"][0] try: function= feat.qualifiers["function"][0] except Exception: function= "Unknown" try: genName= feat.qualifiers["gene"][0] except Exception: genName= "-" tradu = feat.qualifiers["translation"][0] locus = feat.qualifiers["locus_tag"][0] prorainNAme = feat.qualifiers["product"][0] try: ecNumber = feat.qualifiers["EC_number"][0] except Exception: ecNumber= "-" geninfo = (geneID,ACC,locus,genName,strand,seqdnaprot) protinfo = ("uniorotID_rev",ID_prot,prorainNAme,len(tradu),"local",function,tradu) ret.append((geninfo,protinfo,ecNumber)) return ret def getInfouniprot(protainID): params = {"query": protainID, "format": "fasta"} r = requests.get("http://www.uniprot.org/uniprot/", params) i=0 for record in SeqIO.parse(StringIO(r.text), "fasta"): idfasta = record.id idfasta = str(idfasta).split("|")[1] #break parst = parseSwissProt(idfasta) return(idfasta,parst) def shortSeq(sequence,tam): return sequence # tirar isto para fazer short start = sequence[:tam] end = sequence[(-1*tam):] return(start+"..."+end) def juntaFuncoes(listaF,fungb,sep): ret = fungb for f in listaF: ret += (sep+f) return ret def juntaLista(lista,sep): ret = "" for elem in lista: ret += elem+sep return ret[:-1] def createCVSRecord(gbData,swissData,sep): grauRev = "---" (genInfo,protInfo,EC) = gbData (geneID,NCIgual,locusTag,geneName,strand,dnaSeq) =genInfo (lixo,assNCBI,protName,protLen,lixo2,protFungb,protSeq) = protInfo (idSwiss,parse) = swissData (protStatus,protLocal,funcaoMolec,processBiol,funcoes,geneNameSwiss,domianTex) = parse funcaoMolec = juntaLista (funcaoMolec, "_") processBiol = juntaLista( processBiol,"_") if(funcaoMolec==""): funcaoMolec="-" if(processBiol==""): processBiol="-" funcoes = juntaFuncoes(funcoes,protFungb,"_") geneID=geneID.split(":")[1] ##feito na if(geneName=="-"): geneName = geneNameSwiss data = geneID+sep+geneName+sep+NCIgual+sep+locusTag+sep+strand+sep+shortSeq(dnaSeq,7) data = data + sep + assNCBI+ sep+idSwiss+sep+protName+sep+shortSeq(protSeq,7) data = data+ sep+ str(protLen)+ sep+ protStatus+ sep + grauRev + sep + protLocal data = data +sep +EC+ sep + funcaoMolec+ sep+ processBiol+ sep + funcoes+ sep + domianTex return data sep =";" rec = parseFile("grupo6.txt") datas = getinfosfromgem(rec) filecsv = open("tabela_com_seq_Completa.csv","w") filecsv.write("sep="+sep+"\n") cabeca="geneID"+sep+"GeneName"+sep+"GeneAccessNumber"+sep+"locusTag"+sep+"strand"+sep+"DNA_SEQ" cabeca+=sep+"AccessNumberNCBI"+sep+"idSwiss"+sep+"protName"+sep+"PROT_SEQ" cabeca+=sep+"PROT_Tamanho"+sep+"protStatus"+sep+"grauRev"+sep+"protLocal" cabeca+=sep+"EC"+sep+"(GO)funcaoMolec"+sep+"(GO)processBiol"+sep+"funcoes"+sep+"Domain" filecsv.write(cabeca+"\n") i=1 for data in datas: (gene,prot,ec)=data (rev,ID_prot,prorainNAme,tam,local,function,tradu)=prot swissinfo = getInfouniprot(ID_prot) dataCS = createCVSRecord(data,swissinfo,sep) filecsv.write(dataCS+"\n"); print("mais UMA: " + str(i)) i=i+1 filecsv.close()
[ "joaomsilva@outlook.com" ]
joaomsilva@outlook.com
94cf848c42259d154818b2ce9d25437a2bfb5767
1b8fea84247058843b1a21aa148a5dcfd5c2ba2b
/app/tournament.py
9813ec5c540609bcf04275950486ca4bac23bde9
[]
no_license
aguijarro/tournament_web
251735dedbc34f65d7d99d0db12060c0e71197c6
3b0179a87c21d5556d43f40cca0da494f6c09ee9
refs/heads/master
2021-01-10T14:58:47.620453
2016-01-28T13:56:08
2016-01-28T13:56:08
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#!/usr/bin/env python # # tournament.py -- implementation of a Swiss-system tournament # import psycopg2 def connect(): """Connect to the PostgreSQL database. Returns a database connection.""" return psycopg2.connect("dbname=tournament") def reportTournaments(): """Returns a list of tournaments registered in database""" DB = connect() c = DB.cursor() sql = '''SELECT * FROM tournament; ''' c.execute(sql) tournaments = [] for row in c.fetchall(): tournaments.append(row) DB.close() return tournaments def registerRound(name, id_tournament): """Adds a rounds to the tournament database. Args: name: the round's full name (needs be unique for each tournament). id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''INSERT INTO round(name, id_tournament) VALUES (%s, %s) RETURNING id_round;''' c.execute(sql,(name,id_tournament,)) DB.commit() id_round = c.fetchone()[0] DB.close() return id_round def registerStandings(id_round, id_player, matches, win, lost, tied, action): """Adds a scoreboard to the tournament database by each Round. Args: name: the player's full name (need not be unique). id_round: foreing key from table round. Save scoreboard for each round id_player: foreing key from table player_tournament. Save scoreboard for each player matches: Save the number of matches for the player win: Save a win result lost: Save a lost result tied: Save tied result action: Define what action must be executed: Insert data or Update data """ if action == 'Insert': DB = connect() c = DB.cursor() sql = '''INSERT INTO scoreboard(id_round, id_player, matches, win, lost, tied) VALUES (%s, %s, %s, %s, %s, %s);''' c.execute(sql,(id_round, id_player, matches, win, lost, tied,)) DB.commit() DB.close() else: DB = connect() c = DB.cursor() sql = '''UPDATE scoreboard SET matches = %s, win = %s, lost = %s, tied = %s WHERE id_round = %s AND id_player = %s;''' c.execute(sql,(matches,win,lost,tied, id_round,id_player,)) DB.commit() DB.close() def registerTournament(name, description, tournamentPlayers, rounds): """Adds a tournament to the tournament database. Args: name: the tournament's full name (need not be unique). description: the tournament's description tournamentPlayers: define how many players will has the Tournament rounds: define how many rounds the Tournament will has depending the number of players. """ DB = connect() c = DB.cursor() sql = '''INSERT INTO tournament(name, description, tournamentPlayers, numberOfRounds) VALUES (%s, %s, %s, %s) RETURNING id_tournament;''' c.execute(sql,(name,description,tournamentPlayers,rounds,)) DB.commit() id_tournament = c.fetchone()[0] DB.close() for x in range(0, rounds): name = 'Round %d' % x id_round = registerRound(name, id_tournament) def reportRoundsTournament(id_tournament): """Returns the list of rounds registered per Tournament Args: id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''SELECT r.name, r.id_round FROM round r WHERE r.id_tournament = %s; ''' c.execute(sql,(id_tournament,)) rounds = [] for row in c.fetchall(): rounds.append(row) DB.close() return rounds def numberPlayerByTournament(id_tournament): """Returns the number of players by Tournament. Args: id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''SELECT name, tournamentPlayers FROM tournament WHERE id_tournament = %s;''' c.execute(sql,(id_tournament,)) numberPlayers = c.fetchone()[1] DB.close() return numberPlayers def numberPlayerInTournament(id_tournament): """Returns the number of players already register in a Tournament. Args: id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''SELECT count(*) FROM player_tournament WHERE id_tournament = %s;''' c.execute(sql,(id_tournament,)) numberPlayers = c.fetchone()[0] DB.close() return numberPlayers def registerPlayer(name): """Adds a player to the tournament database. Args: name: the player's full name (need not be unique). """ DB = connect() c = DB.cursor() sql = '''INSERT INTO player(name) VALUES (%s);''' c.execute(sql,(name,)) DB.commit() DB.close() def reportPlayersTournaments(id_tournament): """Returns the list of players registered per Tournament Args: id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''SELECT p.name, p.id_player, pt.id_player_tournament FROM player_tournament pt, player p WHERE p.id_player = pt.id_player AND pt.id_tournament = %s; ''' c.execute(sql,(id_tournament,)) players = [] for row in c.fetchall(): players.append(row) DB.close() return players def assignPlayerTournament(id_tournament, id_player): """Assign a player to a one tournament. Args: id_tournament: foreing key from table tournament. id_player: foreing key from table player. """ DB = connect() c = DB.cursor() sql = '''INSERT INTO player_tournament(id_tournament, id_player) VALUES (%s,%s);''' c.execute(sql,(id_tournament,id_player,)) DB.commit() DB.close() def reportPlayers(id_tournament): """Returns the list of players currently registered. Args: id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''SELECT * FROM player p WHERE p.id_player NOT IN (SELECT pt.id_player FROM player_tournament pt where pt.id_tournament = %s); ''' c.execute(sql,(id_tournament)) players = [] for row in c.fetchall(): players.append(row) DB.close() return players def firstRoundTournament(id_tournament): """Returns the first round for each Tournament. Args: id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''SELECT id_round FROM round WHERE name = 'Round 0' AND id_tournament = %s;''' c.execute(sql,(id_tournament,)) id_round = c.fetchone()[0] DB.close() return id_round def initTournament(id_tournament): """Initializes the Tournament and records the first scoreboard for the define the first matches. Args: id_tournament: foreing key from table tournament. """ DB = connect() c = DB.cursor() sql = '''UPDATE tournament SET stateTournament = True WHERE id_tournament = %s;''' c.execute(sql,(id_tournament,)) DB.commit() DB.close() #Returns players already register in a tournament playersTournaments = reportPlayersTournaments(id_tournament) #Returns id for that round id_round = firstRoundTournament(id_tournament) for player in playersTournaments: #Save standing for first round registerStandings(id_round,player[2],0,0,0,0,'Insert') def reportIdTournament(id_round): """Returns the id for each Tournament. Args: id_round: foreing key from table round. """ DB = connect() c = DB.cursor() sql = '''SELECT id_tournament FROM round WHERE id_round = %s;''' c.execute(sql,(id_round,)) id_round = c.fetchone()[0] DB.close() return id_round def roundStandings(id_round): """Returns a list of the players and their win records, sorted by wins Args: id_round: foreing key from table round. Returns: A list of tuples, each of which contains (id_player, name, matches, wins, lost, tied): id: the player's unique id (assigned by the database) name: the player's full name (as registered) matches: the number of matches the player has played wins: the number of matches the player has won lost: the number of matches the player has lost tied: the number of matches the player has tied """ DB = connect() c = DB.cursor() sql = '''SELECT s.id_player, p.name, s.matches, s.win, s.lost, s.tied FROM scoreboard s, player_tournament pt, player p WHERE s.id_player = pt.id_player_tournament AND pt.id_player = p.id_player AND s.id_round = %s ORDER BY 4 DESC; ''' c.execute(sql,(id_round,)) standings = [] for row in c.fetchall(): standings.append(row) DB.close() return standings def reportMatchByRound(id_round): """ Returns true if there is a match already register for that round Args: id_round: foreing key from table round. """ DB = connect() c = DB.cursor() sql = '''SELECT count(*) FROM match WHERE id_round = %s;''' c.execute(sql,(id_round,)) numberMatch = c.fetchone()[0] DB.close() if numberMatch !=0: return False else: return True def reportResultByMatch(id_round): """ Returns true if there is a result already registered for that round Args: id_round: foreing key from table round. """ print "id_round" print id_round DB = connect() c = DB.cursor() sql = '''SELECT result from match where id_round = %s;''' c.execute(sql,(id_round,)) results = [] for row in c.fetchall(): results.append(row) DB.close() for result in results: if result[0]==None: return True return False def roundMatches(id_round): """Returns a list of the matches per Round and Tournament. Args: id_round: foreing key from table round. Returns: A list of tuples, each of which contains (m.id_match, p1.name, p2.name, pt1.id_player_tournament, pt2.id_player_tournament): m.id_match: the matches' unique id (assigned by the database) p1.name: the player's 1 full name (as registered) p2.name: the player's 2 full name (as registered) pt1.id_player_tournament: the player's 1 unique id (assigned by the database) pt2.id_player_tournament: the player's 2 unique id (assigned by the database) """ DB = connect() c = DB.cursor() sql = '''SELECT m.id_match, p1.name, p2.name, pt1.id_player_tournament, pt2.id_player_tournament FROM match m, player_tournament pt1, player_tournament pt2, player p1, player p2 WHERE m.player_1 = pt1.id_player_tournament AND m.player_2 = pt2.id_player_tournament AND pt1.id_player = p1.id_player AND pt2.id_player = p2.id_player AND m.id_round = %s; ''' c.execute(sql,(id_round,)) matches = [] for row in c.fetchall(): matches.append(row) DB.close() return matches def saveMatch(id_round, player_1, player_2): """Records the match for a Round of Tournament. Args: id_round: the round's unique id (assigned by the database) player_1: the player's 1 id (as registered) player_2: the player's 2 id (as registered) """ DB = connect() c = DB.cursor() sql = '''INSERT INTO match(id_round, player_1, player_2) VALUES (%s,%s,%s);''' c.execute(sql,(id_round,player_1,player_2,)) DB.commit() DB.close() def updateScoreboardBye(id_round, id_player): """Update scoreboard of a player which is in Bye state. Args: id_round: the round's unique id (assigned by the database) id_player: the player's 1 id (as registered) """ DB = connect() c = DB.cursor() #get number of match sql_num_match = '''SELECT get_num_match(%s,%s);''' c.execute(sql_num_match,(id_round,id_player)) num_match = c.fetchone()[0] #get number of match for loser sql_win_num_match = '''SELECT get_num_win(%s,%s);''' c.execute(sql_win_num_match,(id_round,id_player)) win_num_match = c.fetchone()[0] DB.close() #Save standings registerStandings(id_round,id_player,num_match + 1,win_num_match + 1,0,0,'Update') def saveBye(id_round, id_player): """Record a player which was selected for a Bye state. Args: id_round: the round's unique id (assigned by the database) id_player: the player's 1 id (as registered) """ DB = connect() c = DB.cursor() sql = '''INSERT INTO bye(id_round, id_player) VALUES (%s,%s);''' c.execute(sql,(id_round,id_player,)) DB.commit() DB.close() def reportByePlayer(id_round): """Returns a player wihch is in Bye state. Args: id_round: the round's unique id (assigned by the database) """ DB = connect() c = DB.cursor() sql = '''SELECT p.name FROM bye b, player_tournament pt, player p WHERE b.id_player = pt.id_player_tournament AND pt.id_player = p.id_player AND b.id_round = %s; ''' c.execute(sql,(id_round,)) namePlayerBye = c.fetchone() DB.close() return namePlayerBye def reportIdByePlayer(id_round): """Returns value if the player is already saved in Bye table. Args: id_round: the round's unique id (assigned by the database) """ DB = connect() c = DB.cursor() sql = '''SELECT pt.id_player_tournament FROM bye b, player_tournament pt, player p WHERE b.id_player = pt.id_player_tournament AND pt.id_player = p.id_player AND b.id_round = %s; ''' c.execute(sql,(id_round,)) idPlayerBye = c.fetchone()[0] DB.close() return idPlayerBye def reportBye(id_round, id_player): """Returns value if the player is already saved in Bye table. Function use to control that a player must not save two times in a Bye table Args: id_round: the round's unique id (assigned by the database) id_player: the player's 1 id (as registered) """ DB = connect() c = DB.cursor() sql = '''SELECT count(*) FROM bye WHERE id_round = %s AND id_player = %s;''' c.execute(sql,(id_round,id_player,)) bye = c.fetchone()[0] DB.close() return bye def returnPairStandings(id_round,standings): """Return a even scoreboard whitout player which was saved in Bye Table. Args: id_round: the round's unique id (assigned by the database) standings: scoreboard belonging to a round """ for index, standing in enumerate(standings): bye = reportBye(id_round, standing[0]) if int(bye) == 0: #Save bye player saveBye(id_round,standing[0]) standings.pop(index) break return standings def validPairs(first_player, second_player): """Return True if the pair for the match is valid. That means that the players never play before Args: first_player: the player's 1 id (as registered) second_player: the player's 2 id (as registered) """ DB = connect() c = DB.cursor() sql = '''SELECT count(*) as num_match FROM match m WHERE (m.player_1 = %s and m.player_2 = %s) OR (m.player_1 = %s and m.player_2 = %s); ''' c.execute(sql,(first_player,second_player,second_player,first_player)) count = c.fetchone()[0] DB.close() if count == 0: return True else: return False def makePairs(index_first_player, first_player, possiblePairs): """Return a player selected from the different alternatives Args: index_first_player: array position for a player_1 first_player: the player's 1 id (as registered) possiblePairs: array of possible pairs for player 1 """ for index_second_player, second_player in enumerate(possiblePairs): if validPairs(first_player[0],second_player[0]): return index_second_player + (index_first_player + 1), second_player def swissPairings(id_round): """Records a list of pairs of players for the next round of a match. Args: id_round: the round's unique id (assigned by the database) """ pairs = [] #Return standings for a round standings = roundStandings(id_round) #Returns the id of tournament to identify the number of players id_tournament = reportIdTournament(id_round) #Returns the number of players by tournament playersByTournament = numberPlayerByTournament(id_tournament) if (int(playersByTournament) % 2 != 0): #returns a standings with out bye player standings = returnPairStandings(id_round,standings) while len(standings) > 1: index_first_player = 0 first_player = standings[0] # Make pair index_second_player, second_player = makePairs(index_first_player, first_player, standings[1:]) # Take off the pairs which was proccess standings.pop(index_second_player) standings.pop(index_first_player) pairs.append((first_player[0],second_player[0])) for pair in pairs: #Save a new match saveMatch(id_round,pair[0],pair[1]) def saveResultMatch(id_round, id_match, winner, loser, tied): """Returns the number of players already register in a Tournament. Args: id_round: the round's unique id (assigned by the database) id_match: the matches' unique id (assigned by the database) winner: the winner's id (as registered) loser: the loser's 1 id (as registered) tied: condition that explain if the result of the match was tied """ if tied == None: DB = connect() c = DB.cursor() sql = '''UPDATE match SET result = %s WHERE id_match = %s;''' c.execute(sql,(winner,id_match,)) DB.commit() DB.close() #Save match for save when there is not a tied reportMatch(id_round, winner, loser, tied) else: DB = connect() c = DB.cursor() sql = '''UPDATE match SET result = %s WHERE id_match = %s;''' c.execute(sql,(tied,id_match,)) DB.commit() DB.close() #Save match for save when there is a tied reportMatch(id_round, winner, loser, tied) def reportMatch(id_round, winner, loser, tied): """Records the outcome of a single match between two players. Args: winner: the id number of the player who won loser: the id number of the player who lost """ DB = connect() c = DB.cursor() if tied == None: #get number of match for winners sql_win_num_match = '''SELECT get_num_match(%s,%s);''' c.execute(sql_win_num_match,(id_round,winner)) winner_num_match = c.fetchone()[0] #get number of match for loser sql_lost_num_match = '''SELECT get_num_match(%s,%s);''' c.execute(sql_lost_num_match,(id_round,loser)) loser_num_match = c.fetchone()[0] #get number of wins for winner sql_winner_num_win = '''SELECT get_num_win(%s,%s);''' c.execute(sql_winner_num_win,(id_round,winner)) winner_num_win = c.fetchone()[0] #get number of lost for winner sql_winner_num_lost = '''SELECT get_num_lost(%s,%s);''' c.execute(sql_winner_num_lost,(id_round,winner)) winner_num_lost = c.fetchone()[0] #get number of wins for loser sql_loser_num_win = '''SELECT get_num_win(%s,%s);''' c.execute(sql_loser_num_win,(id_round,loser)) loser_num_win = c.fetchone()[0] #get number of lost for loser sql_loser_num_lost = '''SELECT get_num_lost(%s,%s);''' c.execute(sql_loser_num_lost,(id_round,loser)) loser_num_lost = c.fetchone()[0] #get number of tied for winner sql_winner_num_tied = '''SELECT get_num_tied(%s,%s);''' c.execute(sql_winner_num_tied,(id_round,winner)) winner_num_tied = c.fetchone()[0] #get number of tied for loser sql_loser_num_tied = '''SELECT get_num_tied(%s,%s);''' c.execute(sql_loser_num_tied,(id_round,loser)) loser_num_tied = c.fetchone()[0] #update winner registerStandings(id_round,winner,winner_num_match + 1,winner_num_win + 1,winner_num_lost,winner_num_tied,'Update') #update loser registerStandings(id_round,loser,loser_num_match + 1,loser_num_win,loser_num_lost + 1,loser_num_tied,'Update') else: sql_player_1_num_match = '''SELECT get_num_match(%s,%s);''' c.execute(sql_player_1_num_match,(id_round,winner)) player_1_num_match = c.fetchone()[0] #get number of match for loser sql_player_2_num_match = '''SELECT get_num_match(%s,%s);''' c.execute(sql_player_2_num_match,(id_round,loser)) player_2_num_match = c.fetchone()[0] #get number of tied player 1 sql_player_1_num_tied = '''SELECT get_num_tied(%s,%s);''' c.execute(sql_player_1_num_tied,(id_round,winner)) player_1_num_tied = c.fetchone()[0] #get number of tied player 2 sql_player_2_num_tied = '''SELECT get_num_tied(%s,%s);''' c.execute(sql_player_2_num_tied,(id_round,loser)) player_2_num_tied = c.fetchone()[0] #get number of wins player 1 sql_player_1_num_win = '''SELECT get_num_win(%s,%s);''' c.execute(sql_player_1_num_win,(id_round,winner)) player_1_num_win = c.fetchone()[0] #get number of wins player 2 sql_player_2_num_win = '''SELECT get_num_win(%s,%s);''' c.execute(sql_player_2_num_win,(id_round,loser)) player_2_num_win = c.fetchone()[0] #get number of lost player 1 sql_player_1_num_lost = '''SELECT get_num_lost(%s,%s);''' c.execute(sql_player_1_num_lost,(id_round,winner)) player_1_num_lost = c.fetchone()[0] #get number of lost player 2 sql_player_2_num_lost = '''SELECT get_num_lost(%s,%s);''' c.execute(sql_player_2_num_lost,(id_round,loser)) player_2_num_lost = c.fetchone()[0] #update player_1 registerStandings(id_round,winner,player_1_num_match + 1,player_1_num_win,player_1_num_lost,player_1_num_tied + 1,'Update') #update player_2 registerStandings(id_round,loser,player_2_num_match + 1,player_2_num_win,player_2_num_lost,player_2_num_tied + 1,'Update') def getNextRound(id_round, id_tournament): """Returns the next round for each tournament. Args: id_round: the round's unique id (assigned by the database) id_tournament: the tournament's unique id (assigned by the database) """ DB = connect() c = DB.cursor() sql = '''SELECT id_round FROM round WHERE id_tournament = %s AND id_round > %s LIMIT 1;''' c.execute(sql,(id_tournament, id_round,)) next_round = c.fetchone() DB.close() return next_round
[ "aguijarro@vic-data.com" ]
aguijarro@vic-data.com
091a06320d8b36532cf76359942de1eec908b433
4a5aa5683a039a06a8af1fd21055eb4702e4dfdd
/same-tree.py
f30e147bd5d369bbd50ac46b75185312e13a5caa
[]
no_license
Fliv/my-leetcode
8ed03461f492d874c90dc820909bec9ad659a963
a45002fb06954fbff790317a9fbb6f79adebf367
refs/heads/master
2021-01-11T04:33:35.909269
2017-07-05T11:10:04
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# Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None class Solution(object): def isSameTree(self, p, q): """ :type p: TreeNode :type q: TreeNode :rtype: bool """ if not p and not q: return True if not p and q or not q and p: return False if p.val != q.val: return False return self.isSameTree(p.left, q.left) and self.isSameTree(p.right, q.right)
[ "415071280@qq.com" ]
415071280@qq.com
737f7c4f3db32fbbc32c0d5f8ed335fc3f63e82b
25ebc03b92df764ff0a6c70c14c2848a49fe1b0b
/daily/20200504/example_egoist/walker.py
519c662fb68e00489ebc5b0bbaa8f85170fd985e
[]
no_license
podhmo/individual-sandbox
18db414fafd061568d0d5e993b8f8069867dfcfb
cafee43b4cf51a321f4e2c3f9949ac53eece4b15
refs/heads/master
2023-07-23T07:06:57.944539
2023-07-09T11:45:53
2023-07-09T11:45:53
61,940,197
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null
2022-10-19T05:01:17
2016-06-25T11:27:04
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Python
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py
../../20200503/example_metashape/walker.py
[ "ababjam61+github@gmail.com" ]
ababjam61+github@gmail.com
c70e8a10944cccf8e5bdfde937bf2c8263a1b00e
85f065d6eff8b04f412aab0a5c0615ced0efb408
/third/mosesdecoder-RELEASE-3.0/scripts/training/wrappers/conll2mosesxml.py
69ee4f73713f3d45fdc14e82c10b72cec238a4ed
[]
no_license
antot/posteditese_mtsummit19
976a099fe6ade6c0a57672c6f82d6f490fe18afa
b344d9134c749fab8681928da49f4894cf1fb696
refs/heads/master
2020-06-08T12:50:42.308562
2019-06-22T12:31:09
2019-06-22T12:31:09
193,231,110
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#!/usr/bin/python # -*- coding: utf-8 -*- # Author: Rico Sennrich # takes a file in the CoNLL dependency format (from the CoNLL-X shared task on dependency parsing; http://ilk.uvt.nl/conll/#dataformat ) # and produces Moses XML format. Note that the structure is built based on fields 9 and 10 (projective HEAD and RELATION), # which not all parsers produce. # usage: conll2mosesxml.py [--brackets] < input_file > output_file from __future__ import print_function, unicode_literals import sys import re import codecs from collections import namedtuple,defaultdict from lxml import etree as ET Word = namedtuple('Word', ['pos','word','lemma','tag','head','func', 'proj_head', 'proj_func']) def main(output_format='xml'): sentence = [] for line in sys.stdin: # process sentence if line == "\n": sentence.insert(0,[]) if is_projective(sentence): write(sentence,output_format) else: sys.stderr.write(' '.join(w.word for w in sentence[1:]) + '\n') sys.stdout.write('\n') sentence = [] continue try: pos, word, lemma, tag, tag2, morph, head, func, proj_head, proj_func = line.split() except ValueError: # word may be unicode whitespace pos, word, lemma, tag, tag2, morph, head, func, proj_head, proj_func = re.split(' *\t*',line.strip()) word = escape_special_chars(word) lemma = escape_special_chars(lemma) if proj_head == '_': proj_head = head proj_func = func sentence.append(Word(int(pos), word, lemma, tag2,int(head), func, int(proj_head), proj_func)) # this script performs the same escaping as escape-special-chars.perl in Moses. # most of it is done in function write(), but quotation marks need to be processed first def escape_special_chars(line): line = line.replace('\'','&apos;') # xml line = line.replace('"','&quot;') # xml line = line.replace('[','&#91;') # syntax non-terminal line = line.replace(']','&#93;') # syntax non-terminal return line # make a check if structure is projective def is_projective(sentence): dominates = defaultdict(set) for i,w in enumerate(sentence): dominates[i].add(i) if not i: continue head = int(w.proj_head) while head != 0: if i in dominates[head]: break dominates[head].add(i) head = int(sentence[head].proj_head) for i in dominates: dependents = dominates[i] if max(dependents) - min(dependents) != len(dependents)-1: sys.stderr.write("error: non-projective structure.\n") return False return True def write(sentence, output_format='xml'): if output_format == 'xml': tree = create_subtree(0,sentence) out = ET.tostring(tree, encoding = 'UTF-8').decode('UTF-8') if output_format == 'brackets': out = create_brackets(0,sentence) out = out.replace('|','&#124;') # factor separator out = out.replace('&amp;apos;','&apos;') # lxml is buggy if input is escaped out = out.replace('&amp;quot;','&quot;') # lxml is buggy if input is escaped out = out.replace('&amp;#91;','&#91;') # lxml is buggy if input is escaped out = out.replace('&amp;#93;','&#93;') # lxml is buggy if input is escaped print(out) # write node in Moses XML format def create_subtree(position, sentence): element = ET.Element('tree') if position: element.set('label', sentence[position].proj_func) else: element.set('label', 'sent') for i in range(1,position): if sentence[i].proj_head == position: element.append(create_subtree(i, sentence)) if position: if preterminals: head = ET.Element('tree') head.set('label', sentence[position].tag) head.text = sentence[position].word element.append(head) else: if len(element): element[-1].tail = sentence[position].word else: element.text = sentence[position].word for i in range(position, len(sentence)): if i and sentence[i].proj_head == position: element.append(create_subtree(i, sentence)) return element # write node in bracket format (Penn treebank style) def create_brackets(position, sentence): if position: element = "[ " + sentence[position].proj_func + ' ' else: element = "[ sent " for i in range(1,position): if sentence[i].proj_head == position: element += create_brackets(i, sentence) if position: word = sentence[position].word tag = sentence[position].tag if preterminals: element += '[ ' + tag + ' ' + word + ' ] ' else: element += word + ' ] ' for i in range(position, len(sentence)): if i and sentence[i].proj_head == position: element += create_brackets(i, sentence) if preterminals or not position: element += '] ' return element if __name__ == '__main__': if sys.version_info < (3,0,0): sys.stdin = codecs.getreader('UTF-8')(sys.stdin) sys.stdout = codecs.getwriter('UTF-8')(sys.stdout) sys.stderr = codecs.getwriter('UTF-8')(sys.stderr) if '--no_preterminals' in sys.argv: preterminals = False else: preterminals = True if '--brackets' in sys.argv: main('brackets') else: main('xml')
[ "a.toral.ruiz@rug.nl" ]
a.toral.ruiz@rug.nl
da830d452062851dbe34843842810de0095e6f06
496ea91f6bcbcf0b1468f447107e5dc56bf571ef
/lesson/02_blog2/1_python/2_dictionary/dic2.py
a920d6c8e3a8bc3e8fe0df19589efc4a576b55fa
[]
no_license
remopro-pro/webbasic
8e9d7d32f2df2b275b1012cc6e6d54f433c13186
1acf0f0db5861b9103475cdce0f8b7db39e9a97f
refs/heads/master
2022-12-11T13:41:57.519862
2020-09-10T10:55:13
2020-09-10T10:55:13
279,002,970
0
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user = {"name": "磯野", "age": 18} user["name"] = "フグ田" print(user["name"]) user["job"] = "会社員" print(user)
[ "hirfujit@yahoo-corp.jp" ]
hirfujit@yahoo-corp.jp
fc7241d3c097b1d4ec4a17558bbeb948d4440761
ccc8cd0979095de2d2644be06c596f33ed1b4072
/integration_tests/suite/test_dird_documentation.py
bb9d3888040bc28b3f6d92bed419dd1c635abdbe
[]
no_license
TinxHQ/wazo-google
13373b3b5357ceb0a1d62c129818176265a4acc9
d8a115ddd7bd76595adaf834c87a043c96dc53a4
refs/heads/master
2021-03-22T05:19:33.535426
2019-08-07T14:51:38
2019-08-07T14:51:38
113,173,511
0
0
null
2019-08-07T14:51:39
2017-12-05T11:28:08
Python
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Python
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736
py
# Copyright 2019 The Wazo Authors (see the AUTHORS file) # SPDX-License-Identifier: GPL-3.0-or-later import pprint import requests from hamcrest import assert_that, empty from .helpers.base import BaseTestCase class TestDirdDocumentation(BaseTestCase): asset = 'documentation' def test_documentation_errors(self): api_url = 'https://dird:9489/0.1/api/api.yml' self._validate_api(api_url) def _validate_api(self, url): port = self.service_port(8080, 'swagger-validator') validator_url = 'http://localhost:{port}/debug'.format(port=port) response = requests.get(validator_url, params={'url': url}) assert_that(response.json(), empty(), pprint.pformat(response.json()))
[ "pcm@wazo.io" ]
pcm@wazo.io
ae3daa75051224632560f48bca4435780cfa44ae
25f31909afa432e49b0a77fc469cd9d6e6d72d70
/lab assingnments/ex3.py
ac8385051f315bd51e2ce999da6107490ff67fd6
[]
no_license
VenkySVR/Python-DataStructures
7d13e044b705fd232db9f0997981ee11f9fb88ad
bac0e1697f4da00b93c9fc879f027ddb7371e252
refs/heads/master
2021-04-19T19:52:05.154734
2020-05-09T10:50:57
2020-05-09T10:50:57
249,631,604
1
0
null
2020-05-06T17:14:54
2020-03-24T06:37:05
Python
UTF-8
Python
false
false
1,363
py
# problem 1 s = 'Beautiful palace' print(s[:]) print(s[::]) first_five_chars = s[:5] print(first_five_chars) third_to_fifth_chars = s[2:5] print(third_to_fifth_chars) # problem 2 py_string = 'learn python' slice_object1 = slice(-1, -6, -1) slice_object2 = slice(1, 6, -1) slice_object3 = slice(1, 6, 1) print(py_string[slice_object1], py_string[slice_object2],py_string[slice_object3]) # Problem 3 s = 'Learning is FUN' reverseString = s[::-1] print(reverseString) s1 = s[2:8:2] print(s1) s1 = s[8:1:-1] print(s1) s1 = s[-4:-2] s1 = s[8:1:-2] print(s1) s1 = s[-4:-2] print(s1) s = 'Python' s1=s[100:] print(s1) s1= s[2:50] print(s1) # Problem 4 py_string = 'Python book' slice_object = slice(3) print(py_string[slice_object]) slice_object = slice(1, 6, 2) print(py_string[slice_object]) # Problem 5 py_list = ['P', 'y', 't', 'h', 'o', 'n'] py_tuple = ('P', 'y', 't', 'h', 'o', 'n') slice_object = slice(3) print(py_list[slice_object]) slice_object = slice(1, 5, 2) print(py_tuple[slice_object]) slice_object = slice(-1, -4, -1) print(py_list[slice_object]) slice_object = slice(-1, -5, -2) print(py_tuple[slice_object]) # """ # output # Beautiful palace # Beautiful palace # Beaut # aut # nohty earn # NUF si gninraeL # ann # gninra # nna # F # thon # Pyt # yhn # ['P', 'y', 't'] # ('y', 'h') # ['n', 'o', 'h'] # ('n', 'h') # """
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venky.s.vr13@gmail.com