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

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/gbd_2017/nonfatal_code/congenital/custom/submit_denominator.py

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Nermin-Ghith/ihme-modeling

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refs/heads/main

2023-04-13T00:26:55.363986

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from __future__ import division import subprocess import numpy as np import pandas as pd import os import shutil import glob from db_queries import get_location_metadata username = 'USERNAME' root = "FILEPATH" error_path = "FILEPATH" output_path = "FILEPATH" if not os.path.exists(error_path): os.makedirs(error_path) if not os.path.exists(output_path): os.makedirs(output_path) out_dir = "FILEPATH" share_dir = "FILEPATH" loc_meta = get_location_metadata(location_set_id=35, gbd_round_id=5) loc_meta = loc_meta.loc[loc_meta.most_detailed==1, ['location_id', 'ihme_loc_id']] if not os.path.exists(share_dir): os.makedirs(share_dir) else: shutil.rmtree(share_dir) os.makedirs(share_dir) job_string = "" for index, row in loc_meta.iterrows(): if row.location_id > -1: job_name = 'denom_{}'.format(row.location_id) job_string = job_string + ',' + job_name call = ('qsub -hold_jid {hj} -l mem_free=4.0G -pe multi_slot 4' ' -cwd -P proj_custom_models' ' -o {o}' ' -e {e}' ' -N {jn}' ' cluster_shell.sh' ' calc_denominator.py' ' {arg1} {arg2} {arg3}'.format(hj='no_holds', o=output_path, e=error_path, jn=job_name, arg1=share_dir, arg2=row.location_id, arg3=row.ihme_loc_id)) subprocess.call(call, shell=True) hold = job_string params = [share_dir, out_dir, '--loc_list', " ".join([str(x) for x in loc_meta.location_id.tolist()])] call = ('qsub -hold_jid {hj} -l mem_free=10.0G -pe multi_slot 5' ' -cwd -P proj_custom_models' ' -o {o}' ' -e {e}' ' -N {jn}' ' cluster_shell.sh' ' combine_denominators.py' ' {arg1}'.format(hj=hold, o=output_path, e=error_path, jn='combine_denominators', arg1=' '.join(params))) subprocess.call(call, shell=True)

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nsidles@uw.edu

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/code_chef/BFTT.py

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gomsterX/competitive_programming

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#Problem ID: BFTT #Problem Name: Balsa For The Three for _ in range(int(input())): n = int(input()) n+=1 while True: if(str(n).count('3') >=3): break n+=1 print(n)

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/crawler_sys/site_crawler/crawler_sogou.py

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silade/crawler

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2023-03-10T10:06:21.097103

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# -*- coding: utf-8 -*- """ Created on Wed Aug 22 09:30:20 2018 @author: fangyucheng """ import time import requests from bs4 import BeautifulSoup from crawler.crawler_sys.utils.trans_strtime_to_timestamp import trans_strtime_to_timestamp cookie = ('YYID=2FFBDAA6D4FBA37438F4067C8123E98B; IMEVER=8.5.0.1322;' 'SUID=3D03FF723865860A59795A5F000BB71F;' 'SUV=00C039A172FF033D5993ADBD770E7410; usid=lF0F7il0yWbXF5c9;' 'IPLOC=CN1100; sct=11; SMYUV=1512954490386200;' 'ad=19fxxkllll2zKxvnlllllVHr6$UllllltsDRlyllll9llllljgDll5@@@@@@@@@@;' 'SNUID=D0DE5A671A1E68C31FB628911B8277A5; wuid=AAGPcSphIAAAAAqLE2OSTQgAGwY=;' 'UM_distinctid=16449b02797449-0c5d9293f4a833-143f7040-1fa400-16449b02799881;' 'CXID=794EC592A14CE76F5DF3F3A3BDDDD787;' 'ld=Kyllllllll2bWX10QTIdJOHDsvSbWX1uK94Vhkllll9lllllVklll5@@@@@@@@@@;' 'cd=1534754086&17502a3f56c02f72dfd43a17cbb19663;' 'rd=Vyllllllll2bBEqoQLWCNCHfKv2bWX1uzX0atkllllwllllRVllll5@@@@@@@@@@;' 'LSTMV=173%2C72; LCLKINT=1570') headers = {'Host': 'news.sogou.com', 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:61.0) Gecko/20100101 Firefox/61.0', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language': 'zh-CN,zh;q=0.8,zh-TW;q=0.7,zh-HK;q=0.5,en-US;q=0.3,en;q=0.2', 'Accept-Encoding': 'gzip, deflate', 'Cookie': cookie, 'Connection': 'keep-alive', 'Upgrade-Insecure-Requests': '1', 'Cache-Control': 'max-age=0'} def sogou_info_page(keyword): result_lst = [] for page_num in range(1,11): search_url = 'http://news.sogou.com/news?&query='+keyword+'&page='+str(page_num) get_page = requests.get(search_url, headers=headers) page = get_page.text soup = BeautifulSoup(page, 'html.parser') news_lst = soup.find_all('div', {'class': 'vrwrap'}) for line in news_lst: try: title = line.div.h3.a.text url = line.div.h3.a['href'] source_and_release_time = line.find('p', {'class': 'news-from'}).text source_and_release_time_lst = source_and_release_time.split('\xa0') source = source_and_release_time_lst[0] release_time_str = source_and_release_time_lst[-1] release_time = trans_strtime_to_timestamp(release_time_str) try: content = line.find('span').text except: print('no content at %s' % title) content = 'missing' fetch_time = int(time.time()*1000) try: similar_news = line.find('a', {'id': 'news_similar'}).text except: print('no similar news at %s' % title) similar_news = 'missing' news_info = {'title': title, 'url': url, 'source': source, 'release_time': release_time, 'fetch_time': fetch_time, 'content': content, 'similar_news': similar_news, 'keyword': keyword} result_lst.append(news_info) print('get data at page %s' % page_num) except: ('the error occured at position %s' % news_lst.index(line)) return result_lst if __name__=='__main__': keyword = '中超' test_sogou = sogou_info_page(keyword)

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import numpy as np import cv2 video_path = "" cap = cv2.VideoCapture(video_path) while(True): ret, frame = cap.read() gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cv2.imshow('frame',gray) if cv2.waitKey(0) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()

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# -*- coding: utf-8 -*- from PyQt5.QtWidgets import QApplication, QMainWindow, QLabel, QHBoxLayout, QVBoxLayout, QWidget, QGroupBox, QGridLayout from app.shared import get_storage from .VolumeInfo import VolumeInfo from .explorer.Explorer import Explorer class MainFrame(QWidget): def __init__(self, parent=None): super(MainFrame, self).__init__(parent) layout = QVBoxLayout() self.setLayout(layout) self.__volume_info = VolumeInfo() self.__explorer = Explorer() layout.addWidget(self.__volume_info) layout.addWidget(self.__explorer) def start(self): storage = get_storage() self.__volume_info.set_info(storage.volume.volume_header) self.__explorer.show_root()

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azegun/workspace_python

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import seaborn as sns import matplotlib.pyplot as plt tips = sns.load_dataset('tips') print(tips) # 막대 그래프 fig = plt.figure() axes1 = fig.add_subplot(1, 1, 1) axes1.hist(tips['total_bill'], bins=10) # bins 지정시 x축의 간격을 10으로 조정 axes1.set_title('Histogram of Total Bill') axes1.set_xlabel('Frequency') axes1.set_ylabel('Total Bill') # 산계형 그래프 scatter_plot = plt.figure() axes1 = scatter_plot.add_subplot(1, 1, 1) axes1.scatter(tips['total_bill'], tips['tip']) axes1.set_title('Scatterplot of Total Bill Vs Tip') axes1.set_xlabel('Total Bill') axes1.set_ylabel('Tip') boxplot = plt.figure() axes1 = boxplot.add_subplot(1, 1, 1) axes1.boxplot([tips[tips['sex'] == 'Female']['tip'], tips[tips['sex'] == 'Male']['tip']], labels=['Female', 'Male']) axes1.set_xlabel('Sex') axes1.set_ylabel('Tip') axes1.set_title('Boxplot of Tips by Sex') plt.show()

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skk4/python_study

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# -*- coding:utf-8 -*- import urllib import urllib2 import json while 1: content = raw_input(">:") headers = { 'Referer': 'http://fanyi.baidu.com/?aldtype=16047/', 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.113 Safari/537.36' } data = {} data['from'] = 'en' data['to'] = 'zh' data['query'] = content data['transtype'] = 'translang' data['simple_means_flag'] = '3' url = 'http://fanyi.baidu.com/v2transapi' values = urllib.urlencode(data) rq = urllib2.Request(url, values, headers) fd = urllib2.urlopen(rq) #print fd.getcode() html = fd.read() #print html #print html dst = json.loads(html) print dst['trans_result']['data'][0]['dst']

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MysteriousSonOfGod/python-3

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import pandas as pd import numpy as np import mglearn import matplotlib as mpl import matplotlib.pyplot as plt import sys, os sys.path.append(os.path.dirname(os.path.abspath(os.path.dirname(__file__)))) import images.image # 9. 두 개의 클래스를 가진 2차원 데이터셋 make_moons from sklearn.datasets import make_moons X, y = make_moons(n_samples=200, noise=0.05, random_state=0) print("X.shape: {}".format(X.shape)) print("y.shape: {}".format(y.shape)) print("X 타입: {}".format(type(X))) print("y 타입: {}".format(type(y))) print(X[:5], y[:5]) ############################################################################### # 1. 타깃값으로 군집 평가하기 : 군집 알고리즘의 결과를 실제 정답 클러스터와 비교하여 평가할 수 있는 지표 # 1. ARI (adjusted rand index) # ARI : 1(최적일 때)와 0(무작위로 분류될 때) # 2. NMI (normalized mutual information) # from sklearn.preprocessing import StandardScaler from sklearn.cluster import KMeans from sklearn.cluster import AgglomerativeClustering from sklearn.cluster import DBSCAN scaler = StandardScaler() scaler.fit(X) X_scaled = scaler.transform(X) fig, axes = plt.subplots(1, 4, figsize=(15, 3), subplot_kw={'xticks':(), 'yticks':()}) # 3가지 알고리즘들 리스트 algos = [KMeans(n_clusters=2), AgglomerativeClustering(n_clusters=2), DBSCAN()] random_state = np.random.RandomState(seed=0) random_clusters = random_state.randint(low=0, high=2, size=len(X)) # 무작위로 할당한 클러스터 from sklearn.metrics.cluster import adjusted_rand_score axes[0].scatter(X_scaled[:, 0], X_scaled[:, 1], c=random_clusters, cmap=mglearn.cm3, s=60, edgecolors='black') axes[0].set_title("random assign - ARI : {:.2f}".format(adjusted_rand_score(y, random_clusters))) for ax, algo in zip(axes[1:], algos): clusters = algo.fit_predict(X_scaled) ax.scatter(X_scaled[:, 0], X_scaled[:, 1], c=clusters, cmap=mglearn.cm3, s=60, edgecolors='black') ax.set_title("{} - ARI: {:.2f}".format(algo.__class__.__name__, adjusted_rand_score(y, clusters))) # plt.title('복잡한 모양의 클러스터 군집 알고리즘 비교') images.image.save_fig("10.9.moons_spiral_scatter_adjusted_rand_score") plt.show() # 2. 타깃값 없이 군집 평가하기 - 실루엣 계수 # 군집 알고리즘을 적용할 때 보통 그 결과와 비교할 타깃값이 없다. # 타깃값이 필요 없는 군집용 지표로는 실루엣 계수 (silhouette coefficient)가 있다. # 그러나 이 지표는 실제로 잘 동작하진 않는다. # 실루엣 점수는 클러스터의 밀집 정도를 계산하는 것으로, 높을수록 좋으며, 최대 점수는 1이다. # 실루엣 계수 사용하여 k-평균, 병합군집, DBSCAN 알고리즘을 비교 fig, axes = plt.subplots(1, 4, figsize=(15, 3), subplot_kw={'xticks':(), 'yticks':()}) # 3가지 알고리즘들 리스트 # algos = [KMeans(n_clusters=2), AgglomerativeClustering(n_clusters=2), DBSCAN()] # random_state = np.random.RandomState(seed=0) # random_clusters = random_state.randint(low=0, high=2, size=len(X)) # 무작위로 할당한 클러스터 from sklearn.metrics.cluster import silhouette_score axes[0].scatter(X_scaled[:, 0], X_scaled[:, 1], c=random_clusters, cmap=mglearn.cm3, s=60, edgecolors='black') axes[0].set_title("random assign : {:.2f}".format(silhouette_score(X_scaled, random_clusters))) for ax, algo in zip(axes[1:], algos): clusters = algo.fit_predict(X_scaled) ax.scatter(X_scaled[:, 0], X_scaled[:, 1], c=clusters, cmap=mglearn.cm3, s=60, edgecolors='black') ax.set_title("{} : {:.2f}".format(algo.__class__.__name__, silhouette_score(X_scaled, clusters))) # plt.title('복잡한 모양의 클러스터 군집 알고리즘 비교') images.image.save_fig("10.9.moons_spiral_scatter_silhouette_score") plt.show()

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############################################################################### # # Tests for XlsxWriter. # # Copyright (c), 2013-2020, John McNamara, jmcnamara@cpan.org # from ..excel_comparsion_test import ExcelComparisonTest from ...workbook import Workbook class TestCompareXLSXFiles(ExcelComparisonTest): """ Test file created by XlsxWriter against a file created by Excel. """ def setUp(self): self.set_filename('chart_pie02.xlsx') def test_create_file(self): """Test the creation of a simple XlsxWriter file.""" workbook = Workbook(self.got_filename) worksheet = workbook.add_worksheet() chart = workbook.add_chart({'type': 'pie'}) data = [ [2, 4, 6], [60, 30, 10], ] worksheet.write_column('A1', data[0]) worksheet.write_column('B1', data[1]) chart.add_series({ 'categories': '=Sheet1!$A$1:$A$3', 'values': '=Sheet1!$B$1:$B$3', }) chart.set_legend({'font': {'bold': 1, 'italic': 1, 'baseline': -1}}) worksheet.insert_chart('E9', chart) workbook.close() self.assertExcelEqual()

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def main(): n = int(input()) a = list(map(int, input().split())) ans = 1 if 0 in a: print(0) return else: flag = True for i in a: ans *= i if ans > (10 ** 18): print(-1) return print(ans) main()

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#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c)2014 Rackspace US, Inc. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from __future__ import print_function import os import pyrax pyrax.set_setting("identity_type", "rackspace") creds_file = os.path.expanduser("~/.rackspace_cloud_credentials") pyrax.set_credential_file(creds_file) imgs = pyrax.images cf = pyrax.cloudfiles print("You will need to select an image to export, and a Container into which " "the exported image will be placed.") images = imgs.list(visibility="private") print() print("Select an image to export:") for pos, image in enumerate(images): print("[%s] %s" % (pos, image.name)) snum = raw_input("Enter the number of the image you want to share: ") if not snum: exit() try: num = int(snum) except ValueError: print("'%s' is not a valid number." % snum) exit() if not 0 <= num < len(images): print("'%s' is not a valid image number." % snum) exit() image = images[num] conts = cf.list() print() print("Select the target container to place the exported image:") for pos, cont in enumerate(conts): print("[%s] %s" % (pos, cont.name)) snum = raw_input("Enter the number of the container: ") if not snum: exit() try: num = int(snum) except ValueError: print("'%s' is not a valid number." % snum) exit() if not 0 <= num < len(conts): print("'%s' is not a valid container number." % snum) exit() cont = conts[num] task = imgs.export_task(image, cont) print("Task ID=%s" % task.id) print() answer = raw_input("Do you want to track the task until completion? This may " "take several minutes. [y/N]: ") if answer and answer[0].lower() == "y": pyrax.utils.wait_until(task, "status", ["success", "failure"], verbose=True, interval=30)

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namujinju/study-note

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import heapq as hq import sys hq_arr = [] n = int(input()) # 연산 갯수 for _ in range(n): i = int(sys.stdin.readline()) # https://www.acmicpc.net/blog/view/56 if i: hq.heappush(hq_arr, i) else: if hq_arr: print(hq.heappop(hq_arr)) else: print(0)

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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. """Evaluation job for the Omniglot experiments.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import time from absl import app from absl import flags from learning_parameter_allocation import data from learning_parameter_allocation import models from learning_parameter_allocation import utils from learning_parameter_allocation.pathnet import components as pn_components from learning_parameter_allocation.pathnet import pathnet_lib as pn from learning_parameter_allocation.pathnet.utils import create_uniform_layer import tensorflow.compat.v1 as tf _OMNIGLOT_INPUT_SHAPE = [105, 105, 1] # Delay in seconds to wait before rechecking if there are new checkpoints. _CHECK_FOR_CHECKPOINTS_FREQUENCY = 15 # If there are no checkpoints for this number of seconds give up and finish. _MAX_WAIT_FOR_NEW_CHECKPOINTS = 3 * 60 * 60 FLAGS = flags.FLAGS flags.DEFINE_string( 'logdir', '/tmp/summary_dir/', 'Path to the directory to save logs and summaries.') flags.DEFINE_string( 'method', 'gumbel_matrix', 'Approach to use to determine which tasks gets which components, ' 'one of "shared_bottom", "no_sharing", "gumbel_matrix".') def loss_fn(labels, logits): return tf.nn.sparse_softmax_cross_entropy_with_logits( labels=labels, logits=logits) def build_pathnet_eval_graph( task_names, batch_size, num_classes_for_tasks, router_fn): """Constructs the PathNet eval graph. Args: task_names: (list of strings) names of tasks. batch_size: (int) batch size to use. num_classes_for_tasks: (list of ints) number of classes for each task. router_fn: function that, given a single argument `num_components`, returns a router (see routers in `pathnet/pathnet_lib.py`) for a layer containing `num_components` components. Returns: A tuple of (`p_inputs`, `p_task_id`, `out_logits`). `p_inputs` and `p_task_id` are placeholders for input image and scalar task id, respectively. `out_logits` are the final network output (classification logits). """ num_tasks = len(task_names) # PathNet layers keras_layers = models.get_keras_layers_for_omniglot_experiment() pathnet_layers = models.build_model_from_keras_layers( _OMNIGLOT_INPUT_SHAPE, num_tasks, keras_layers, router_fn) # Task-specific linear heads pathnet_layers.append( utils.create_layer_with_task_specific_linear_heads(num_classes_for_tasks)) # Output components pathnet_layers.append(create_uniform_layer( num_components=num_tasks, component_fn=lambda: pn_components.ModelHeadComponent(loss_fn=loss_fn), combiner_fn=pn.SelectCombiner, router_fn=lambda: None)) pathnet = pn.PathNet( pathnet_layers, tf.contrib.training.HParams(batch_size=batch_size)) p_inputs, _, p_task_id, _, out_logits = utils.build_pathnet_graph( pathnet, _OMNIGLOT_INPUT_SHAPE, training=False) return p_inputs, p_task_id, out_logits def main(_): num_alphabets = 20 task_names = ['Omniglot-%d' % task_id for task_id in range(num_alphabets)] task_data, num_classes = data.get_data_for_multitask_omniglot_setup( num_alphabets) batch_size = 16 for task_id in range(num_alphabets): task_data[task_id] = data.batch_all(task_data[task_id], batch_size) router_fn = utils.get_router_fn_by_name(num_alphabets, FLAGS.method) session = tf.Session(graph=tf.get_default_graph()) tf.train.get_or_create_global_step() summary_writer = tf.contrib.summary.create_file_writer(FLAGS.logdir) summary_writer.set_as_default() tf.contrib.summary.initialize(session=session) p_inputs, p_task_id, out_logits = build_pathnet_eval_graph( task_names, batch_size, num_classes, router_fn) evaluate_on = ['train', 'validation', 'test'] p_task_accuracies = {} accuracy_summary_op = {} for data_split in evaluate_on: (p_task_accuracies[data_split], accuracy_summary_op[data_split]) =\ utils.create_accuracy_summary_ops( task_names, summary_name_prefix='eval_%s' % data_split) # This `Saver` is not used to save variables, only to restore them from # the checkpoints. saver = tf.train.Saver(tf.global_variables()) previous_checkpoint_path = '' time_waited_for_checkpoints = 0 while time_waited_for_checkpoints < _MAX_WAIT_FOR_NEW_CHECKPOINTS: latest_checkpoint_path = tf.train.latest_checkpoint(FLAGS.logdir) if latest_checkpoint_path in [None, previous_checkpoint_path]: print('Found no new checkpoints') time_waited_for_checkpoints += _CHECK_FOR_CHECKPOINTS_FREQUENCY time.sleep(_CHECK_FOR_CHECKPOINTS_FREQUENCY) continue else: time_waited_for_checkpoints = 0 print('Reloading checkpoint: %s' % latest_checkpoint_path) previous_checkpoint_path = latest_checkpoint_path saver.restore(session, latest_checkpoint_path) for data_split in evaluate_on: eval_data = [ dataset[data_split].make_one_shot_iterator().get_next() for dataset in task_data ] print('Evaluating on: %s' % data_split) task_accuracies = utils.run_pathnet_evaluation( session, p_inputs, p_task_id, out_logits, task_names, eval_data) utils.run_accuracy_summary_ops( session, p_task_accuracies[data_split], task_accuracies, accuracy_summary_op[data_split]) if __name__ == '__main__': app.run(main)

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from collections import deque n, m = map(int, input().split()) poss = [False for _ in range(360)] given = list(map(int, input().split())) q = deque() q.append(given[0]) while len(q): a = q.pop() if poss[a]: continue poss[a] = True for o in given: b = abs(a - o) if not poss[b]: q.append(b) c = (a+o)%360 if not poss[c]: q.append(c) for a in input().split(): ok = poss[int(a)] if ok: print('YES') else: print('NO')

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import abc from multipledispatch import dispatch from datastructs.assignment import Assignment class MultivariateDistribution: """ Representation of a multivariate probability distribution P(X1,...Xn), where X1,...Xn are random variables. """ __metaclass__ = abc.ABCMeta @dispatch() @abc.abstractmethod def get_variables(self): """ Returns the names of the random variables in the distribution :return: the set of variable names. """ raise NotImplementedError() @dispatch() @abc.abstractmethod def get_values(self): """ Returns the set of possible assignments for the random variables. :return: the set of possible assignment """ raise NotImplementedError() @dispatch(Assignment) @abc.abstractmethod def get_prob(self, values): """ Returns the probability of a particular assignment of values. :param values: the assignment of values to X1,...Xn. :return: the corresponding probability """ raise NotImplementedError() @dispatch() @abc.abstractmethod def sample(self): """ Returns a sample assignment for X1,...Xn. :return: the sampled assignment """ raise NotImplementedError() @dispatch(str) @abc.abstractmethod def get_marginal(self, variable): """ Returns the marginal probability distribution P(Xi) for a random variable Xi in X1,...Xn. :param variable: the random variable Xi :return: the marginal distribution P(Xi) """ raise NotImplementedError() @dispatch(str, str) @abc.abstractmethod def modify_variable_id(self, old_variable_id, new_variable_id): """ Modifies the variable identifier in the distribution :param old_variable_id: the old identifier :param new_variable_id: the new identifier """ raise NotImplementedError() @dispatch() @abc.abstractmethod def to_discrete(self): """ Returns a representation of the distribution as a multivariate table. :return: the multivariate table. """ raise NotImplementedError() @abc.abstractmethod def __copy__(self): """ Returns a copy of the distribution. :return: the copy """ raise NotImplementedError() @dispatch(float) @abc.abstractmethod def prune_values(self, threshold): """ Prunes all values assignment whose probability falls below the threshold. :param threshold: the threshold to apply :return: true if at least one value has been removed, false otherwise """ raise NotImplementedError() @dispatch() @abc.abstractmethod def get_best(self): """ Returns the value with maximum probability. :return: the value with maximum probability """ raise NotImplementedError()

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unsortedtosorted/elgoog

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""" 114. Flatten Binary Tree to Linked List Steps: if leaf node, do nothing if not leaf node: flatten left subtree flatten right subtree connect right child to right most leaf of left child make left child as right child make left child None RunTime : O(N^2) Space : O(N) """ class Solution(object): def flatten(self, root): def convert(root): if root: if not root.left and not root.right: return #flatten left and right child convert(root.left) convert(root.right) l = root.left r = root.right #make left child as new right child root.right = l root.left = None temp = root #get right most leaf of new right child while temp.right: temp = temp.right temp.right = r convert(root)

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import os import socket _SPI_CPHA = 0x01 _SPI_CPOL = 0x02 # _SPI_MODE_0 = 0 # _SPI_MODE_1 = SPI_CPHA # _SPI_MODE_2 = SPI_CPOL # _SPI_MODE_3 = SPI_CPOL | SPI_CPHA # _SPI_MODES = [_SPI_MODE_0, _SPI_MODE_1, _SPI_MODE_2, _SPI_MODE_3] _SPI_CS_HIGH = 0x04 _SPI_LSB_FIRST = 0x08 _SPI_3WIRE = 0x10 _SPI_LOOP = 0x20 _SPI_NO_CS = 0x40 _SPI_READY = 0x80 class SpiDev: _socket = None _bits_per_word = 0 # cshigh = False # loop = None # lsbfirst = False _max_speed_hz = 0 _mode = 0 # threewire = False def __init__(self): port = 8789 ip = os.environ["RASPBERRY_IP"] if "RASPBERRY_PORT" in os.environ: port = int(os.environ["RASPBERRY_PORT"]) self._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self._socket.connect((ip, port)) def __del__(self): if self._socket is not None: try: self._socket.close() except Exception as e: pass def open(self, bus, device): b = bytearray() b.append(ord("o")) b.append(bus) b.append(device) self._socket.send(b) def xfer(self, data, speed_hz=0, delay_usec=0, bits_per_word=8): b = bytearray() b.append(ord("x")) b.append(len(data) & 255) b.append(len(data) >> 8 & 255) for d in data: b.append(d) self._socket.send(b) rec = self._socket.recv(len(data)) resp = [] for bb in rec: resp.append(bb) return resp def xfer2(self, data, speed_hz=0, delay_usec=0, bits_per_word=8): pass def close(self): self._mode = 0; self._bits_per_word = 0; self._max_speed_hz = 0; b = bytearray() b.append(ord("c")) self._socket.send(b) def readbytes(self, n): pass def writebytes(self, data): pass @property def cshigh(self): return self._mode & _SPI_CS_HIGH != 0 @cshigh.setter def cshigh(self, cshigh): if cshigh: self._mode = self._mode | _SPI_CS_HIGH else: self._mode = self._mode & ~_SPI_CS_HIGH @property def lsbfirst(self): return self._mode & _SPI_LSB_FIRST != 0 @cshigh.setter def lsbfirst(self, lsbfirst): if lsbfirst: self._mode = self._mode | _SPI_LSB_FIRST else: self._mode = self._mode & ~_SPI_LSB_FIRST @property def threewire(self): return self._mode & _SPI_3WIRE != 0 @threewire.setter def threewire(self, threewire): if threewire: self._mode = self._mode | _SPI_3WIRE else: self._mode = self._mode & ~_SPI_3WIRE @property def loop(self): return self._mode & _SPI_3WIRE != 0 @loop.setter def loop(self, loop): if loop: self._mode = self._mode | _SPI_LOOP else: self._mode = self._mode & ~_SPI_LOOP @property def bits_per_word(self): return self._bits_per_word @bits_per_word.setter def bits_per_word(self, bits_per_word): if bits_per_word < 8 or bits_per_word > 16: raise ValueError("invalid bits_per_word (8 to 16)") self._bits_per_word = bits_per_word @property def max_speed_hz(self): return self.max_speed_hz @max_speed_hz.setter def bits_per_word(self, max_speed_hz): self.max_speed_hz @property def mode(self): return self._mode & (_SPI_CPHA | _SPI_CPOL) @mode.setter def loop(self, mode): self._mode = (self._mode & ~(_SPI_CPHA | _SPI_CPOL)) | mode if __name__ == "__main__": s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.bind(("0.0.0.0", 8789)) s.listen(1) def startListen(): import threading def session(con): while True: # print("Waiting to command") cmd = ord(con.recv(1)) if cmd == ord("c"): print("Close") elif cmd == ord("o"): bus = ord(con.recv(1)) device = ord(con.recv(1)) print("Opening " + str(bus) + "." + str(device)) elif cmd == ord("x"): l = ord(con.recv(1)) h = ord(con.recv(1)) size = l + h << 8 print("Receiving " + str(size) +" bytes") data = con.recv(size) print("Received " + str(data)) con.send(data) else: print("Unknown command " + str(cmd)) def listen(): while True: con, addr = s.accept() t = threading.Thread(target=session, args=[con]) t.daemon = True t.start() thread = threading.Thread(target=listen) thread.daemon = True thread.start() try: startListen() os.environ["RASPBERRY_IP"] = "127.0.0.1" spi = SpiDev() print("opening spi") spi.open(1, 2) print("sending data") spi.xfer(b"Hello") print("closing") spi.close() finally: s.close() s.detach()

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# pylint: disable=too-many-lines # coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar from urllib.parse import parse_qs, urljoin, urlparse from azure.core.async_paging import AsyncItemPaged, AsyncList from azure.core.exceptions import ( ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, ResourceNotModifiedError, map_error, ) from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import AsyncHttpResponse from azure.core.rest import HttpRequest from azure.core.tracing.decorator import distributed_trace from azure.core.utils import case_insensitive_dict from azure.mgmt.core.exceptions import ARMErrorFormat from ... import models as _models from ..._vendor import _convert_request from ...operations._operations import build_list_request T = TypeVar("T") ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] class Operations: """ .. warning:: **DO NOT** instantiate this class directly. Instead, you should access the following operations through :class:`~azure.mgmt.containerservice.v2021_03_01.aio.ContainerServiceClient`'s :attr:`operations` attribute. """ models = _models def __init__(self, *args, **kwargs) -> None: input_args = list(args) self._client = input_args.pop(0) if input_args else kwargs.pop("client") self._config = input_args.pop(0) if input_args else kwargs.pop("config") self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer") self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer") @distributed_trace def list(self, **kwargs: Any) -> AsyncIterable["_models.OperationValue"]: """Gets a list of compute operations. :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either OperationValue or the result of cls(response) :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.containerservice.v2021_03_01.models.OperationValue] :raises ~azure.core.exceptions.HttpResponseError: """ _headers = kwargs.pop("headers", {}) or {} _params = case_insensitive_dict(kwargs.pop("params", {}) or {}) api_version = kwargs.pop("api_version", _params.pop("api-version", "2021-03-01")) # type: str cls = kwargs.pop("cls", None) # type: ClsType[_models.OperationListResult] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError, 304: ResourceNotModifiedError, } error_map.update(kwargs.pop("error_map", {}) or {}) def prepare_request(next_link=None): if not next_link: request = build_list_request( api_version=api_version, template_url=self.list.metadata["url"], headers=_headers, params=_params, ) request = _convert_request(request) request.url = self._client.format_url(request.url) # type: ignore else: # make call to next link with the client's api-version _parsed_next_link = urlparse(next_link) _next_request_params = case_insensitive_dict(parse_qs(_parsed_next_link.query)) _next_request_params["api-version"] = self._config.api_version request = HttpRequest("GET", urljoin(next_link, _parsed_next_link.path), params=_next_request_params) request = _convert_request(request) request.url = self._client.format_url(request.url) # type: ignore request.method = "GET" return request async def extract_data(pipeline_response): deserialized = self._deserialize("OperationListResult", pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return None, AsyncList(list_of_elem) async def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = await self._client._pipeline.run( # type: ignore # pylint: disable=protected-access request, stream=False, **kwargs ) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return AsyncItemPaged(get_next, extract_data) list.metadata = {"url": "/providers/Microsoft.ContainerService/operations"} # type: ignore

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#!/usr/bin/env python """ Copyright (c) 2014-2016 Miroslav Stampar (@stamparm) See the file 'LICENSE' for copying permission """ import re from core.common import retrieve_content __url__ = "http://osint.bambenekconsulting.com/feeds/dga-feed.txt" __check__ = "Domain used by" __reference__ = "bambenekconsulting.com" def fetch(): retval = {} content = retrieve_content(__url__) if __check__ in content: for match in re.finditer(r"(?m)^([^,\s]+),Domain used by ([^ ]+)", content): retval[match.group(1)] = ("%s dga (malware)" % match.group(2).lower(), __reference__) return retval

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453341288@qq.com

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""" WSGI config for signbank project. This module contains the WSGI application used by Django's development server and any production WSGI deployments. It should expose a module-level variable named ``application``. Django's ``runserver`` and ``runfcgi`` commands discover this application via the ``WSGI_APPLICATION`` setting. Usually you will have the standard Django WSGI application here, but it also might make sense to replace the whole Django WSGI application with a custom one that later delegates to the Django one. For example, you could introduce WSGI middleware here, or combine a Django application with an application of another framework. """ import os # Determine if there are live settings (not commited to source control) and load that if it exists instead of the default settings code_path = os.path.dirname(os.path.realpath(__file__)) os.environ.setdefault("DJANGO_SETTINGS_MODULE", "signbank.settings.docker") # This application object is used by any WSGI server configured to use this # file. This includes Django's development server, if the WSGI_APPLICATION # setting points here. from django.core.wsgi import get_wsgi_application application = get_wsgi_application() # Apply WSGI middleware here. # from helloworld.wsgi import HelloWorldApplication # application = HelloWorldApplication(application)

[ "steve.cassidy@mq.edu.au" ]

steve.cassidy@mq.edu.au

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rafaelperazzo/programacao-web

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# -*- coding: utf-8 -*- ''' def crescente (lista): if lista == sorted(lista): return True else: return False def decrescente (lista): if lista == sorted(lista, reverse = True): return True else: return False def consectivos (lista,n): for i in range(0,n,1): if i < n: if lista[i-1] =! lista[i] return False continue else: return True ''' #escreva o código da função crescente aqui #escreva as demais funções #escreva o programa principal n = int(input('Digite o número de elementos das listas: ')) a = [] b = [] c = [] for i in range (0,n,1): a.append(int(input('Digite a%d: '%(i+1)))) for i in range(0,n,1): if i < n: if a[i-1] == a[i]: print('S') break else: print('N') break ''' print(a) for i in range (0,n,1): b.append(int(input('Digite b%d: '%(i+1)))) print(b) for i in range (0,n,1): c.append(int(input('Digite c%d: '%(i+1)))) print(c) '''

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

rafael.mota@ufca.edu.br

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timothyshull/python_reference_code

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#!/usr/bin/env python3 # Copyright 2014 Brett Slatkin, Pearson Education 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. # Preamble to mimick book environment import logging from pprint import pprint from sys import stdout as STDOUT # Example 2 import app class Dialog(object): def __init__(self, save_dir): self.save_dir = save_dir save_dialog = Dialog(app.prefs.get('save_dir')) def show(): print('Showing the dialog!')

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wk633/crack_leetcode

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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 Codec: def serialize(self, root): """Encodes a tree to a single string. :type root: TreeNode :rtype: str """ def preorder(node): if node: vals.append(str(node.val)) preorder(node.left) preorder(node.right) else: vals.append("#") vals = [] preorder(root) return " ".join(vals) def deserialize(self, data): """Decodes your encoded data to tree. :type data: str :rtype: TreeNode """ def dePreorder(): val = next(vals) if val == "#": return None root = TreeNode(val) root.left = dePreorder() root.right = dePreorder() return root print data vals = iter(data.split(" ")) return dePreorder() # Your Codec object will be instantiated and called as such: # codec = Codec() # codec.deserialize(codec.serialize(root))

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HaydenInEdinburgh/LintCode

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class Solution: """ @param nums: an array @return: the number occurs twice and the number that is missing """ def findErrorNums(self, nums): # Write your code here if not nums: return cnt = {} for n in nums: cnt[n] = cnt.get(n, 0) +1 print(cnt) lost, dup = None, None for i in range(1, len(nums)+1): if i not in cnt: lost = i continue if cnt[i] > 1: dup = i return [dup, lost] if __name__ == '__main__': s = Solution() nums = [1, 1] print(s.findErrorNums(nums))

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#----------------------------------------------------------------------- # mandelbrot.py #----------------------------------------------------------------------- import sys import stddraw from color import Color from picture import Picture import complex as com from stopwatch import Stopwatch #----------------------------------------------------------------------- # Compute the Mandelbrot iteration sequence starting at z0, and # return the number of iterations for which the magnitude stays less # than 2, up to the limit. def mandel(z0, limit): z = z0 for t in range(limit): if abs(z) > 2.0: return t z = z * z + z0 return limit #----------------------------------------------------------------------- # Accept float command-line arguments xc, yc, and size that specify # the center and size of a square region of interest. Make a digital # image showing the result of sampling the Mandelbrot set in that # region at a 512*512 grid of equally spaced pixels. Color each pixel # with a grayscale value that is determined by counting the number of # iterations before the Mandelbrot sequence for the corresponding # complex number grows past 2.0, up to 255. MAX = 255 #n = int(sys.argv[1]) #xc = float(sys.argv[2]) #yc = float(sys.argv[3]) #size = float(sys.argv[4]) n = 512 xc = -.5 yc = 0 size = 2 w1 = Stopwatch() pic = Picture(n, n) for col in range(n): for row in range(n): x0 = xc - (size / 2) + (size * col / n) y0 = yc - (size / 2) + (size * row / n) z0 = complex(x0, y0) gray = MAX - mandel(z0, MAX) color = Color(gray, gray, gray) pic.set(col, n-1-row, color) print(w1.elapsedTime()) w2 = Stopwatch() pic = Picture(n, n) for col in range(n): for row in range(n): x0 = xc - (size / 2) + (size * col / n) y0 = yc - (size / 2) + (size * row / n) z0 = com.Complex(x0, y0) gray = MAX - mandel(z0, MAX) color = Color(gray, gray, gray) pic.set(col, n-1-row, color) print(w2.elapsedTime()) #stddraw.setCanvasSize(n, n) #stddraw.picture(pic) #stddraw.show() #----------------------------------------------------------------------- #bai@ubuntu:~/pythonProject/princeton/3.2$ python3 14_mandelbrotTime.py #pygame 1.9.6 #Hello from the pygame community. https://www.pygame.org/contribute.html #5.372214317321777 #37.89339089393616

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kkwert@sina.com

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N, M = map(int, input().split()) X = [int(input()) for _ in range(M)] MOD = 10 ** 9 + 7 dp = [-1] * (N + 1) dp[0] = 1 for i in range(M): dp[X[i]] = 0 for i in range(N): if dp[i + 1] < 0: if i == 0: dp[i + 1] = dp[i] else: dp[i + 1] = (dp[i] + dp[i - 1]) % MOD print(dp[-1])

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# Machine Learning Online Class # Exercise 6 | Spam Classification with SVMs # # Instructions # ------------ # # This file contains code that helps you get started on the # exercise. You will need to complete the following functions: # # gaussianKernel.m # dataset3Params.m # processEmail.m # emailFeatures.m # # For this exercise, you will not need to change any code in this file, # or any other files other than those mentioned above. # import re # import regular expressions to process emails import numpy from scipy.io import loadmat import svm_funcs # ==================== Part 1: Email Preprocessing ==================== print("\nPreprocessing sample email (emailSample1.txt)\n") # Extract Features with open('./emailSample1.txt') as fid: file_contents = fid.read() word_indices = svm_funcs.process_email(file_contents, False) # Print Stats print('-------------') print('Word Indices:') print('-------------') print(word_indices) # ==================== Part 2: Feature Extraction ==================== print("\nExtracting features from sample email (emailSample1.txt)\n") # Extract Features features = svm_funcs.email_features(word_indices) # Print Stats print("Length of feature vector: %d" % len(features)) print("Number of non-zero entries: %d" % sum(features > 0)) # =========== Part 3: Train Linear SVM for Spam Classification ======== # Load the Spam Email dataset # You will have X, y in your environment data = loadmat("./spamTrain.mat") x_train = data['X'].astype(float) y_train = data['y'] y_train = y_train.reshape(-1) num_examples, num_features = x_train.shape print("Spam example Ex.6. training #examples:", num_examples, "#features:", num_features) print("\nTraining Linear SVM (Spam Classification)") print("This may take 1 to 2 minutes...\n") reg_C = 0.1 model = svm_funcs.svm_train(svm_funcs.linear_kernel, x_train, y_train, reg_C, tol=1e-3, max_passes=20) train_pred = svm_funcs.svm_predict(model, x_train) # Compute the training accuracy train_acc = numpy.mean(train_pred == y_train) print("Training Accuracy: %.2f" % (train_acc*100)) # =================== Part 4: Test Spam Classification ================ # Load the test dataset # You will have Xtest, ytest in your environment data = loadmat("./spamTest.mat") x_test = data['Xtest'].astype(float) y_test = data['ytest'] y_test = y_test.reshape(-1) print("\nEvaluating the trained Linear SVM on a test set...") test_pred = svm_funcs.svm_predict(model, x_test) test_acc = numpy.mean(test_pred == y_test) print("\nTest Accuracy: %.2f" % (test_acc*100)) # ================= Part 5: Top Predictors of Spam ==================== # Sort the weights and obtin the vocabulary list # NOTE some words have the same weights, so their order might be different than in the text above idx = numpy.argsort(model['w']) top_idx = idx[-15:][::-1] vocab_list = svm_funcs.get_vocab_list() print("\nTop predictors of spam:") print("%-15s %-15s" % ('word', 'weight')) print("----" + " "*12 + "------") for word, w in zip(numpy.array(vocab_list)[top_idx], model['w'][top_idx]): print("%-15s %0.2f" % (word, w)) # # =================== Part 6: Try Your Own Emails ===================== filename = './emailSample1.txt' with open(filename) as fid: file_contents = fid.read() word_indices = svm_funcs.process_email(file_contents, verbose=False) x = svm_funcs.email_features(word_indices) p = svm_funcs.svm_predict(model, x) print("\nProcessed %s\nSpam Classification: %s" % (filename, 'spam' if p else 'not spam'))

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import pandas as pd import numpy as np import os import re from matplotlib import pyplot as plt import argparse class Corr(object): def __init__( self, pnl_dir_path, pnl_filepath, pos_dir_path, pos_filepath, range_ ): self.meta_info = { "pnl": { "dir_path": pnl_dir_path, "filepath": pnl_filepath, "range": 0 }, "pos": { "dir_path": pos_dir_path, "filepath": pos_filepath, "range": range_ } } self.pnl_df, self.pnl_se = self.get_sequences("pnl") self.pos_df, self.pos_se = self.get_sequences("pos") self.result_dict = { "PNL": self.get_corr_tuples(self.pnl_df, self.pnl_se), "POS": self.get_corr_tuples(self.pos_df, self.pos_se) } def get_sequences(self, scope): def get_filepaths(): p = re.compile(".*_"+scope+".csv") all_names = os.listdir(dir_path) filenames = sum([p.findall(s) for s in all_names], []) return [os.path.join(dir_path, s) for s in filenames] def get_se(filepath): p = re.compile(".*/(.*)_"+scope+".csv") df = pd.read_csv(filepath, index_col=0)[-range_:] se = df["CumPnL"] if scope == "pnl" else df.mean() se.name = p.findall(filepath)[0] return se meta = self.meta_info dir_path = meta[scope]["dir_path"] pivot_filepath = meta[scope]["filepath"] range_ = meta[scope]["range"] filepaths = get_filepaths() pivot_se = get_se(pivot_filepath) ses = [get_se(filepath) for filepath in filepaths] df = pd.concat(ses, axis=1).drop([pivot_se.name], axis=1) return df, pivot_se def get_corr_tuples(self, sequence_df, pivot_se): def calc_corr(name): ses = [pivot_se, sequence_df[name]] df = pd.concat(ses, axis=1).dropna() corr_mat = np.corrcoef(df[pivot_se.name], df[name]) return corr_mat[1, 0] corr_dict = {name: calc_corr(name) for name in sequence_df.columns} names = sorted(sequence_df.columns, key=lambda name: corr_dict[name]) corr_tuples = [(name, corr_dict[name]) for name in names] return corr_tuples def display(self, scope): def draw_hist(): plt.hist(map(lambda x: x[1], corr_tuples)) plt.show() def _make_it_readable(t): name = t[0]+" "*(max_name_length-len(t[0])) corr =str(t[1]) return name + " | " + corr def print_report(): print(scope+" Max 5") for t in corr_tuples[:-6:-1]: print(_make_it_readable(t)) print(scope+" Min 5") for t in corr_tuples[:5]: print(_make_it_readable(t)) corr_tuples = self.result_dict[scope] max_name_length = max(map(lambda x: len(x[0]), corr_tuples)) draw_hist() print_report() if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument('--pnl_dir', type=str) parser.add_argument('--pnlfile', type=str) parser.add_argument('--pos_dir', type=str) parser.add_argument('--posfile', type=str) parser.add_argument('--range', type=int) args = parser.parse_args() INTERVAL = args.interval PNL_DIR_PATH = args.pnl_dir PNL_FILEPATH = args.pnlfile POS_DIR_PATH = args.pos_dir POS_FILEPATH = args.posfile RANGE = args.range corr = Corr(PNL_DIR_PATH, PNL_FILEPATH, POS_DIR_PATH, POS_FILEPATH, RANGE) corr.display("PNL") corr.display("POS")

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from functools import cache MOD = 10 ** 9 + 7 class Solution: def countPartitions(self, nums: List[int], k: int) -> int: prefix_sum = [0] * len(nums) for i in range(len(nums)): prefix_sum[i] = nums[i] + prefix_sum[i - 1] if prefix_sum[-1] < k * 2: return 0 @cache def dp(i, need1, need2): if i < 0 and max(need1, need2) > 0: return 0 if max(need1, need2) > prefix_sum[i]: return 0 if need1 == need2 == 0: return pow(2, (i + 1), MOD) if need1 > need2: return dp(i, need2, need1) return (dp(i - 1, max(0, need1 - nums[i]), need2) + dp(i - 1, need1, max(0, need2 - nums[i]))) % MOD return dp(len(nums) - 1, k, k)

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skw_kevin@126.com

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rafaelperazzo/programacao-web

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1,725

py

# -*- coding: utf-8 -*- ''' /**********************************************************/ /* Equipe: Igor Emanuel Lucas Farias, Victória Cruz Gouveia */ /* N ́umero de matriculas: 407553, 407582 */ /* Exercicio-Programa 1 -- Ra ́ızes de Equa ̧c~oes Quadr ́aticas */ /* ECI0007 ou EM0006 (EC/EM) -- 2017 -- Professor:Rafael */ /* Interpretador: Python vers~ao 3 */ /********************************************************** ''' #COMECE SEU CODIGO NA LINHA ABAIXO. def raiz2(x,epsilon): rn=x while True: rm=(1/2)*(rn + (x/rn)) if abs (rm-rn)<epsilon: return(rm) rn=rm def baskara(a,b,c): delta=(b**2) - 4*a*c if delta>=0: x1=((-b)+(raiz2(delta,epsilon)))/(2*a) x2=((-b)-(raiz2(delta,epsilon)))/(2*a) if delta>0: return('reais simples', '%2.0f'%x1, '%2.0f'%x2) elif delta==0: return('real dupla', '%2.0f'%x1, '%2.0f'%x2) else: delta=delta*(-1) x3=((raiz2(delta,epsilon))/(2*a)) x1=((-b)/(2*a)) x2=((-b)/(2*a)) return('complexas', complex('%4.0f'%x1,'%4.0f'%x3), complex('%4.0f'%x2,'%4.0f'%x3)) epsilon=float(input('Digite o epsilon de controle: ')) nequacoes=int(input('Digite o número de equações: ')) for equação in range(0,nequacoes,1): a=float(input('Digite o a da equação: ')) b=float(input('Digite o b da equação: ')) c=float(input('Digite o c da equação: ')) if a!=0: print('%.2f'%a), print('%.2f'%b), print('%.2f'%c), print(baskara(a,b,c)) else: print('***ERRO: equação não é do segundo grau! ***')

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

rafael.mota@ufca.edu.br

8843b68fa4debf3686b1f6037b8afaea4ee71840

b739fefa06d46a60fe053f7fe0fe2c62a52242b2

/pages/admin/edit_news_page.py

1417cc238ade39fddacc51eaa0b28d1870ddfc0f

[]

no_license

icorso/gkr-web-tests

c59d3b0f7e371e887c6699cd09b6a87a71dd762e

fdf25ad700d75230f1af74b646a6a8a18f3d0b18

refs/heads/master

2021-01-13T05:15:37.913759

2017-02-08T07:44:04

81,296,963

0

null

UTF-8

Python

false

923

py

# coding=utf-8 from pages import page, Input, Checkbox, BasePage, BaseElement, By from pages.gkr_page import GkrPage @page(u"Форма редактирования новости", By.XPATH, "//form[..//child::*[contains(text(),'Редактирование новости')]]") class EditNewsPage(GkrPage): TITLE = BaseElement("Поле 'Заголовок новости'", By.ID, "title") DESC = BaseElement("Поле 'Текст новости'", By.ID, "text") PUBLISH_DATE = Input("Поле 'Дата создания'", By.XPATH, ".//*[child::*[contains(text(),'Дата')]]") IS_PUBLISHED = Checkbox("Чекбокс 'Опубликовать'", By.XPATH, ".//input[@type='checkbox']") SUBMIT = BaseElement("Кнопка 'Создать'", By.XPATH, ".//button[@type='submit']") ERROR = BaseElement("Сообщение об ошибке", By.XPATH, ".//span[contains(@style,'ff0000')]")

[ "icorso@yandex.ru" ]

icorso@yandex.ru

dad102cb3faea7b8d1d9c97f542f4ce326fe7d2f

3c44ddbe867d953a5f27c8c073e1ea5e995b5873

/experiments/experiment_1/debugger.py

7a9f1bcd3dee99eca66c48d12ca62b8f83a43330

[]

no_license

cair/deep-warehouse

37f6a3510638b36c276abb62b6b770d0ba6186af

93cb7329c28733083b48ab6afd3de91676852175

refs/heads/master

2022-03-10T16:45:59.553325

2022-02-20T17:28:19

167,932,576

5

0

null

UTF-8

Python

false

1,279

py

import sys from deep_logistics.scheduler import OnDemandScheduler from deep_logistics.spawn_strategy import LocationSpawnStrategy from experiments.experiment_3.state_representations import State0 sys.path.append("/home/per/GIT/deep-logistics") sys.path.append("/home/per/IdeaProjects/deep_logistics") sys.path.append("/home/per/GIT/code/deep_logistics") sys.path.append("/root") from deep_logistics.environment import Environment from deep_logistics.agent import InputAgent if __name__ == "__main__": env = Environment( height=5, width=5, depth=3, ups=None, ticks_per_second=1, taxi_n=1, taxi_agent=InputAgent, taxi_respawn=False, taxi_control="constant", scheduler=OnDemandScheduler, delivery_locations=None, spawn_strategy=LocationSpawnStrategy, graphics_render=True, graphics_tile_height=64, graphics_tile_width=64 ) env.deploy_agents() env.task_assignment() state = State0(env) agent = env.agents[0] def on_event(): env.update() y = state.generate(agent) print(" - ".join([str(x) for x in y])) agent.add_event_callback(on_event) while True: agent.automate() env.render()

[ "per@sysx.no" ]

per@sysx.no

a71cc98489fc1998a280603110b534f157129380

1a1b7f607c5e0783fd1c98c8bcff6460e933f09a

/core/charge/charge_types.py

6f4f6bbf937df689e1cbbdc057d1a0b96b383e91

[]

no_license

smrmohammadi/freeIBS

14fb736fcadfaea24f0acdafeafd2425de893a2d

7f612a559141622d5042614a62a2580a72a9479b

refs/heads/master

2021-01-17T21:05:19.200916

2014-03-17T03:07:15

null

0

null

UTF-8

Python

false

1,648

py

from core.charge.internet_charge import InternetCharge from core.charge.voip_charge import VoipCharge from core.charge.internet_charge_rule import InternetChargeRule from core.charge.voip_charge_rule import VoipChargeRule from core.lib.time_lib import * from core.ibs_exceptions import * def getChargeClassForType(_type): if _type=="Internet": return InternetCharge elif _type=="VoIP": return VoipCharge else: raise IBSException(errorText("CHARGES","INVALID_CHARGE_TYPE")%_type) def getRulesTable(_type): """ return table that rules of _type charge_obj is available there rule tables are diffrent based on charge type """ if _type=="Internet": return "internet_charge_rules" elif _type=="VoIP": return "voip_charge_rules" else: raise IBSException(errorText("CHARGES","INVALID_CHARGE_TYPE")%_type) def getChargeRuleObjForType(_type,rule_info,charge_obj,day_of_weeks,ports): if _type=="Internet": return InternetChargeRule(rule_info["charge_rule_id"],charge_obj,rule_info["cpm"],rule_info["cpk"],day_of_weeks,\ rule_info["start_time"],rule_info["end_time"],rule_info["bandwidth_limit_kbytes"],\ rule_info["bw_transmit_leaf_id"],rule_info["bw_receive_leaf_id"],rule_info["assumed_kps"],\ rule_info["ras_id"],ports) elif _type=="VoIP": return VoipChargeRule(rule_info["charge_rule_id"],charge_obj,\ day_of_weeks,rule_info["start_time"],rule_info["end_time"], \ rule_info["tariff_id"],rule_info["ras_id"],ports) else: raise IBSException(errorText("CHARGES","INVALID_CHARGE_TYPE")%_type)

[ "farshad_kh" ]

farshad_kh

ec5e8b11caa32c3c05e9e790c8640c5854a59efe

308953409e1a3b828ac49b7301c1e751cbf762cf

/suite_ERC113C/tst_Offline_Value_Verification_After_Export/test.py

0b61d6d28c8a932c2629a09e7db845a7ea357bd3

[]

no_license

asthagaur1/danfoss-automation

4dcc7d8f000917b67e4d6f46ff862a525ddcbc5e

213a99d3375889cd0e0c801421a50e9fe6085879

refs/heads/main

2023-03-31T23:26:56.956107

2021-04-01T08:52:37

353,627,845

0

null

UTF-8

Python

false

404

py

def main(): excel = r"C:\gitworkspace\TestAutomation-AKCC5XX\Test_Automation\SourceCode\Test_Suites\suite_ERC113C\shared\testdata\Offline_Export_Verifying_Values.xls"; #Mapping with Global scripts for Function library and key action. source(findFile("scripts", "Functions.py")) source(findFile("scripts", "Actions.py")) source(findFile("scripts", "object_id.py")) keyAction(excel)

[ "asthagaur@danfoss.com" ]

asthagaur@danfoss.com

693bf5679a15c573e4ebe87b0a134e654d96be1a

bdda458001808a029b171c09286f022a1384d180

/crm/api/urls.py

4432114d1a628d5ae2367f08e965ea609d506cbb

[]

no_license

bianchimro/crm-django

4189f5c0c31f03d23a2b644a14403d63b8efdf0a

d8e4d18174cb050fd7a22d53fe8bb152e6e43120

refs/heads/master

2021-04-27T15:15:28.219887

2018-02-22T16:51:00

122,466,604

1

0

null

UTF-8

Python

false

387

py

from django.urls import path from .views import ExampleView, AziendaList, AziendaViewSet from rest_framework.routers import DefaultRouter router = DefaultRouter() router.register(r'aziende', AziendaViewSet) urlpatterns = [ path('example/', ExampleView.as_view(), name="example"), path('aziende_list/', AziendaList.as_view(), name="aziende_list"), ] urlpatterns += router.urls

[ "bianchimro@gmail.com" ]

bianchimro@gmail.com

8a86a57c6ba570a80e5a56773f4aacac0bdfff77

cc64b1b5deb4530a5bd3eaabd98ebd4daa2deea1

/Aulas/Exercícios-Mundo2/Aula014/Ex064.py

c503ec40e5b592f3dae6498fbbfd25ca252956e6

[ "MIT" ]

permissive

Sofista23/Aula1_Python

239b9920353138ff99d99dd0af66a4788f1cbb22

129132d977058ac6f23cc95c7bb8b55d8a1bb429

refs/heads/main

2023-09-01T23:55:20.529528

2021-10-13T23:19:33

416,924,760

0

null

UTF-8

Python

false

235

py

n=0 s=0 q=0 while n != 999: n=int(input("Digite um número:")) if n != 999: s += n q += 1 print("A soma de todos os números é {0}.".format(s)) print("A quantidade de números digitados foi de {0}.".format(q))

[ "81760467+Sofista23@users.noreply.github.com" ]

81760467+Sofista23@users.noreply.github.com

ff25ffd31d796bc554c0a32e2113e547c0222a62

cbd9b8f2dbd692d74eba6e92465e5f1dc1a807b3

/ukpopulation/myedata.py

33de0fab035316ed548c79e4507c2972d4735391

[ "MIT" ]

permissive

geoadom/ukpopulation

5a99f02c06c2b76464df2508a8f01f0b9ab0a803

bfbd55097a4e9f458e2da6673a83576e37f5079b

refs/heads/master

2020-03-21T07:59:37.195042

2018-06-21T15:02:31

null

0

null

UTF-8

Python

false

3,297

py

""" MYEData - wrapper around Mid-Year Estimate data by LAD, SYoA and gender """ import pandas as pd import ukcensusapi.Nomisweb as Api import ukpopulation.utils as utils class MYEData: """ Functionality for downloading and collating UK mid-year estimate (MYE) data Nomisweb stores the data for the entire UK, from 1991-2016 inclusive """ # update as and when necessary (this is unlike (S)NPP where we query the data for the year range) # the data is stored differently at nomisweb (year is part of the query) MIN_YEAR = 1991 MAX_YEAR = 2016 def __init__(self, cache_dir=None): if cache_dir is None: cache_dir = utils.default_cache_dir() self.cache_dir = cache_dir self.data_api = Api.Nomisweb(self.cache_dir) # store as a dictionary keyed by year (lazy retrieval) self.data = {} def min_year(self): """ Returns the first year in the data """ return MYEData.MIN_YEAR def max_year(self): """ Returns the final year in the data """ return MYEData.MAX_YEAR # TODO functionality for easy aggregration to E/W/EW/S/GB/NI/UK def filter(self, years, geogs, ages=range(0,91), genders=[1,2]): """ Get MYE detailed data for a given year """ # ensure array inputs if isinstance(years, int): years = [years] if isinstance(geogs, str): geogs = [geogs] if isinstance(ages, int): ages = [ages] if isinstance(genders, int): genders = [genders] result = pd.DataFrame() for year in years: # ensure the data is loaded self.__fetch_data(year) ## ensure we return a copy! part = self.data[year][(self.data[year].GEOGRAPHY_CODE.isin(geogs)) & (self.data[year].C_AGE.isin(ages)) & (self.data[year].GENDER.isin(genders))].copy() part["PROJECTED_YEAR_NAME"] = year result = result.append(part) return result.reset_index(drop=True) def aggregate(self, years, geog_codes, categories, ages=range(0,91), genders=[1,2]): data = self.filter(years, geog_codes, ages, genders) # invert categories (they're the ones to aggregate, not preserve) return data.groupby(utils.check_and_invert(categories))["OBS_VALUE"].sum().reset_index() def __fetch_data(self, year): """ Gets Mid-year population estimate data for a given year Data is by single year of age by gender by local authority """ # if data already loaded return if year in self.data: return table_internal = "NM_2002_1" # 2016-based MYE query_params = { "gender": "1,2", "c_age": "101...191", "MEASURES": "20100", "select": "geography_code,gender,c_age,obs_value", "geography": "1879048193...1879048573,1879048583,1879048574...1879048582" } if year < MYEData.MIN_YEAR or year > MYEData.MAX_YEAR: raise ValueError("{} is outside the available years for MYE data ({}-{})".format(year, MIN_YEAR, MAX_YEAR)) query_params["date"] = "latest" if year < MYEData.MAX_YEAR: query_params["date"] += "MINUS" + str(2016-year) self.data[year] = self.data_api.get_data(table_internal, query_params) # renumber age so that 0 means [0,1) self.data[year].C_AGE -= 101 return self.data[year]

[ "a.p.smith@leeds.ac.uk" ]

a.p.smith@leeds.ac.uk

ddc2a74972b55f12dc91815381d50be81c7ebf36

ba0a2b0d2d1534443ea34320675aadfa378457b6

/Array/Q1267_Count Servers that Communicate.py

bd2da1840b785f2af80b49ee05d2babff826b118

[]

no_license

Luolingwei/LeetCode

73abd58af116f3ec59fd6c76f662beb2a413586c

79d4824879d0faed117eee9d99615cd478432a14

refs/heads/master

2021-08-08T17:45:19.215454

2021-06-17T17:03:15

152,186,910

0

1

null

UTF-8

Python

false

513

py

# 思路: 计算每行每列的server个数，如果一个server与其他server连接，则该行或该列server个数大于1 class Solution: # O(mn) def countServers(self, grid): res=0 m,n=len(grid),len(grid[0]) row,col=list(map(sum,grid)),list(map(sum,zip(*grid))) for i in range(m): for j in range(n): if grid[i][j] and (row[i]>1 or col[j]>1): res+=1 return res a=Solution() print(a.countServers([[1,0],[0,1]]))

[ "564258080@qq.com" ]

564258080@qq.com

c7e969446f55baab789853c7141aee407cfb5de5

b2403817f9221ee3550130572a808194ef4f3fda

/Excersise/DiscoverMonk.py

d83e2599dd6f66c342a4d3eafec2a9d392354bbd

[]

no_license

xaviergoby/Python-Data-Structure

e962444ef5b1313c3facbf1fcc315af182b73a26

eaaf31ea98d63e812a75c1d6ecb8722b9c0cf142

refs/heads/master

2020-04-13T00:24:40.896592

2018-11-27T11:51:36

162,844,732

1

0

null

2018-12-22T21:46:29

null

UTF-8

Python

false

284

py

__author__ = 'Sanjay' def monk(n, args = []): someArray = range(0,50,10) for i in args: if i in someArray: print ("YES") else: print ("NO") if __name__ == '__main__': someList = range(0,100,10) monk(len(someList), someList)

[ "sanjay.siddha3@gmail.com" ]

sanjay.siddha3@gmail.com

8453de52904329d3aaf8fd34272d1308db93de74

7d283f0762d2f85b04148e5db5acebc44dbba606

/get_post_info_dl.py

89d24f3e55214c8c843896a14624df05bc0e6664

[]

no_license

Brandon-Valley/reddit_comp

50dcd3571be1116bebb607c54e105096078c161f

ec618dc12b007a670fb4cc879554c4cf41796b62

refs/heads/master

2022-01-10T19:18:18.042008

2019-06-02T18:30:11

188,881,552

0

null

UTF-8

Python

false

3,408

py

import subprocess import json import file_system_utils # optional arguments: # -h, --help show this help message and exit # --directory DIRECTORY, -d DIRECTORY # Specifies the directory where posts will be downloaded # to # --NoDownload Just gets the posts and stores them in a file for # downloading later # --verbose, -v Verbose Mode # --quit, -q Auto quit afer the process finishes # --link link, -l link Get posts from link # --saved Triggers saved mode # --submitted Gets posts of --user # --upvoted Gets upvoted posts of --user # --log LOG FILE Takes a log file which created by itself (json files), # reads posts and tries downloading them again. # --subreddit SUBREDDIT [SUBREDDIT ...] # Triggers subreddit mode and takes subreddit's name # without r/. use "frontpage" for frontpage # --multireddit MULTIREDDIT # Triggers multireddit mode and takes multireddit's name # without m/ # --user redditor reddit username if needed. use "me" for current user # --search query Searches for given query in given subreddits # --sort SORT TYPE Either hot, top, new, controversial, rising or # relevance default: hot # --limit Limit default: unlimited # --time TIME_LIMIT Either hour, day, week, month, year or all. default: # all EXE_PATH = "C:/Users/Brandon/Documents/Personal_Projects/reddit_comp/bulk_downloader_for_reddit-1.6.5-windows/bulk-downloader-for-reddit.exe " LOG_FILES_SAVE_PATH = 'bulk_download_log_files' DEFAULT_SORT_TYPE = 'hot' def build_arg_str(num_posts, subreddit_l, sort_type = DEFAULT_SORT_TYPE): # build_subreddit_l_str subreddit_l_str = subreddit_l[0] for subreddit in subreddit_l[1:]: subreddit_l_str += '+' + subreddit args = [' --directory ' + LOG_FILES_SAVE_PATH, ' --subreddit ' + subreddit_l_str, ' --limit ' + str(num_posts), ' --sort ' + sort_type, ' --NoDownload' ] #build arg_str arg_str = '' for arg in args: arg_str += arg return arg_str def build_post_info_dl_from_json(): #get path to most recent json logfile newest_log_file_dir = file_system_utils.get_newest_file_path(LOG_FILES_SAVE_PATH + '/LOG_FILES') json_file_path = newest_log_file_dir + '/POSTS.json' post_info_dl = [] # read in json file with open(json_file_path) as json_file: data = json.load(json_file) # fill post_info_dl post_num = 1 while(str(post_num) in data): post_info_dl.append(data[str(post_num)][0]) post_num += 1 return post_info_dl def get_post_info_dl(num_posts, subreddit_list, quick_test = False): if quick_test == False: exe_arg_str = build_arg_str(num_posts, subreddit_list) cmd = EXE_PATH + exe_arg_str subprocess.call(cmd, shell=True) post_info_dl = build_post_info_dl_from_json() return post_info_dl # print( get_post_info_dl(4, ['videomemes', 'pics']))

[ "bavvh8@mst.edu" ]

bavvh8@mst.edu

4d432a747f4aa1931de0a032b8c48e1b17d77e38

b7add0d1b1effc50b27d3316fa5889a5227e5b19

/Micropython/PYCARD/tests/archieved/hall_encoder_test_2.py

30c908f586454c75ba6d4044967b71489fa1d5d2

[]

no_license

Woz4tetra/Atlas

efb83a7c7b2698bf8b36b023f7aa573cc38284f6

c7380868a9efef9d1594ed7aa87187f03a7e4612

refs/heads/master

2020-04-04T06:25:50.657631

2017-04-05T01:53:15

50,269,756

3

1

null

UTF-8

Python

false

494

py

import pyb from objects import HallEncoder pin = "X11" mode = "" while mode != "e" and mode != "r": mode = input("Raw or encoder counts (r or e)?\n> ").lower() if mode == "e": encoder = HallEncoder(0, pin, 80, 100) while True: if encoder.recved_data(): print(encoder.enc_dist, encoder.hall_value) pyb.delay(100) elif mode == "r": pin_ref = pyb.ADC(pyb.Pin(pin, pyb.Pin.ANALOG)) while True: print(pin_ref.read()) pyb.delay(40)

[ "woz4tetra@gmail.com" ]

woz4tetra@gmail.com

81db93b7457b194f44a05dbeb19bfbb07cbf8c1a

6dedf9401746e934e87698f58eedb4631ea5f81b

/scrapy_demo/tesseract/demo.py

5fe50242cefbd8841af0687901b25feedf89c539

[]

no_license

2415970940/scrapy

0d03f9fe0cf121f637b7c5b03d328453c0ae35a7

5a1f4da0d92b3d80c1b95ed9fff0ab4bd02660bd

refs/heads/master

2020-03-23T13:13:50.282118

2018-08-02T09:13:24

141,607,064

0

null

UTF-8

Python

false

317

py

import pytesseract from PIL import Image pytesseract.pytesseract.tesseract_cmd = r"G:\progamapp\Tesseract-OCR\tesseract.exe" tessdata_dir_config = '--tessdata-dir "G:\\progamapp\\Tesseract-OCR\\tessdata"' image = Image.open("test.png") text = pytesseract.image_to_string(image,config=tessdata_dir_config) print(text)

[ "2415970940@qq.com" ]

2415970940@qq.com

7c7fc0f5567572ab0c07b65e752550907fbbcd9e

9e988c0dfbea15cd23a3de860cb0c88c3dcdbd97

/sdBs/AllRun/sdssj_135144.13+124255.8/sdB_sdssj_135144.13+124255.8_coadd.py

4c2a173777392d114cb21ec9fb51411e53878edf

[]

no_license

tboudreaux/SummerSTScICode

73b2e5839b10c0bf733808f4316d34be91c5a3bd

4dd1ffbb09e0a599257d21872f9d62b5420028b0

refs/heads/master

2021-01-20T18:07:44.723496

2016-08-08T16:49:53

65,221,159

0

null

UTF-8

Python

false

480

py

from gPhoton.gMap import gMap def main(): gMap(band="NUV", skypos=[207.933875,12.7155], skyrange=[0.0333333333333,0.0333333333333], stepsz = 30., cntfile="/data2/fleming/GPHOTON_OUTPUT/LIGHTCURVES/sdBs/sdB_sdssj_135144.13+124255.8/sdB_sdssj_135144.13+124255.8_movie_count.fits", cntcoaddfile="/data2/fleming/GPHOTON_OUTPUT/LIGHTCURVES/sdB/sdB_sdssj_135144.13+124255.8/sdB_sdssj_135144.13+124255.8_count_coadd.fits", overwrite=True, verbose=3) if __name__ == "__main__": main()

[ "thomas@boudreauxmail.com" ]

thomas@boudreauxmail.com

ed785e2b5af05ae400c0d35d937f9c33162497ac

09e57dd1374713f06b70d7b37a580130d9bbab0d

/benchmark/startQiskit_QC59.py

2688aa43ef87eefbaedb8591966863e235cc4be4

[ "BSD-3-Clause" ]

permissive

UCLA-SEAL/QDiff

ad53650034897abb5941e74539e3aee8edb600ab

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refs/heads/main

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# qubit number=3 # total number=10 import numpy as np from qiskit import QuantumCircuit, execute, Aer, QuantumRegister, ClassicalRegister, transpile, BasicAer, IBMQ import networkx as nx from qiskit.visualization import plot_histogram from typing import * from pprint import pprint from math import log2 from collections import Counter from qiskit.test.mock import FakeVigo, FakeYorktown kernel = 'circuit/bernstein' def make_circuit(n:int) -> QuantumCircuit: # circuit begin input_qubit = QuantumRegister(n,"qc") prog = QuantumCircuit(input_qubit) prog.h(input_qubit[0]) # number=1 prog.h(input_qubit[1]) # number=2 prog.h(input_qubit[2]) # number=3 prog.h(input_qubit[3]) # number=4 prog.y(input_qubit[3]) # number=5 for edge in E: k = edge[0] l = edge[1] prog.cp(-2 * gamma, input_qubit[k-1], input_qubit[l-1]) prog.p(gamma, k) prog.p(gamma, l) prog.rx(2 * beta, range(len(V))) prog.swap(input_qubit[1],input_qubit[0]) # number=6 prog.swap(input_qubit[1],input_qubit[0]) # number=7 prog.cx(input_qubit[1],input_qubit[0]) # number=8 prog.cx(input_qubit[1],input_qubit[0]) # number=9 # circuit end return prog if __name__ == '__main__': n = 4 V = np.arange(0, n, 1) E = [(0, 1, 1.0), (0, 2, 1.0), (1, 2, 1.0), (3, 2, 1.0), (3, 1, 1.0)] G = nx.Graph() G.add_nodes_from(V) G.add_weighted_edges_from(E) step_size = 0.1 a_gamma = np.arange(0, np.pi, step_size) a_beta = np.arange(0, np.pi, step_size) a_gamma, a_beta = np.meshgrid(a_gamma, a_beta) F1 = 3 - (np.sin(2 * a_beta) ** 2 * np.sin(2 * a_gamma) ** 2 - 0.5 * np.sin(4 * a_beta) * np.sin(4 * a_gamma)) * ( 1 + np.cos(4 * a_gamma) ** 2) result = np.where(F1 == np.amax(F1)) a = list(zip(result[0], result[1]))[0] gamma = a[0] * step_size beta = a[1] * step_size prog = make_circuit(4) sample_shot =5600 writefile = open("../data/startQiskit_QC59.csv", "w") # prog.draw('mpl', filename=(kernel + '.png')) IBMQ.load_account() provider = IBMQ.get_provider(hub='ibm-q') provider.backends() backend = provider.get_backend("ibmq_5_yorktown") circuit1 = transpile(prog, FakeYorktown()) circuit1.measure_all() prog = circuit1 info = execute(prog,backend=backend, shots=sample_shot).result().get_counts() print(info, file=writefile) print("results end", file=writefile) print(circuit1.depth(), file=writefile) print(circuit1, file=writefile) writefile.close()

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import pandas as pd GLOE_SAMPLES = pd.read_csv( 'samples/GLOE_samples.csv', sep=',' ).set_index('Sample Name', drop=False) # Download GLOE-seq data and process into fastq rule expand_gloe_samples: input: expand('rawdata/GLOE-seq/{sample_name}.sra', sample_name=GLOE_SAMPLES['Sample Name']) rule download_all_gloe_samples: conda: '../envs/sra-toolkit.yml' params: sra_accession = lambda wildcards: GLOE_SAMPLES.loc[wildcards.sample_name]['Run'], output: temp('rawdata/GLOE-seq/{sample_name}.sra') shell:''' prefetch {params.sra_accession} --output-file {output} ''' rule dump_gloe_fastq: input: 'rawdata/GLOE-seq/{sample}.sra' output: 'rawdata/GLOE-seq/{sample}.fastq.gz' shell:''' fastq-dump -Z {input} | gzip > {output} ''' # Download primers rule download_primer_file: output: 'rawdata/primers/TruSeq3-SE.fa' shell:''' curl https://raw.githubusercontent.com/timflutre/trimmomatic/master/adapters/TruSeq3-SE.fa \ -o {output} ''' rule download_hg19_chr_sizes: output: 'rawdata/hg19/hg19.chrom.sizes' shell:''' curl -L http://hgdownload.cse.ucsc.edu/goldenpath/hg19/bigZips/hg19.chrom.sizes -o {output} ''' # Download footloop data rule download_footloop_all: output: 'rawdata/footloop/footloop_all.bed' shell:''' curl -L "https://genome.ucsc.edu/cgi-bin/hgTables?hgsid=1079385889_dXqdbBP5Hsal2siu4fVmefmsWOgX&boolshad.hgta_printCustomTrackHeaders=0&hgta_ctName=tb_ct_footLoopPeakALL_41&hgta_ctDesc=table+browser+query+on+ct_footLoopPeakALL_41&hgta_ctVis=pack&hgta_ctUrl=&fbQual=whole&fbUpBases=200&fbDownBases=200&hgta_doGetBed=get+BED" -o {output} '''

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# # Autogenerated by Thrift # # DO NOT EDIT UNLESS YOU ARE SURE THAT YOU KNOW WHAT YOU ARE DOING # @generated # import typing as _typing from thrift.py3.server import RequestContext, ServiceInterface import module.types as _module_types class MyRootInterface( ServiceInterface ): @_typing.overload async def do_root( self, ctx: RequestContext ) -> None: ... async def do_root( self ) -> None: ... class MyNodeInterface( _module_services.MyRootInterface ): @_typing.overload async def do_mid( self, ctx: RequestContext ) -> None: ... async def do_mid( self ) -> None: ... class MyLeafInterface( _module_services.MyNodeInterface ): @_typing.overload async def do_leaf( self, ctx: RequestContext ) -> None: ... async def do_leaf( self ) -> None: ...

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# -*- python -*- # This software was produced by NIST, an agency of the U.S. government, # and by statute is not subject to copyright in the United States. # Recipients of this software assume all responsibilities associated # with its operation, modification and maintenance. However, to # facilitate maintenance we ask that before distributing modified # versions of this software, you first contact the authors at # oof_manager@nist.gov. def _Element__position(self, coords): return map(self.from_master, coords) ElementPtr.position = _Element__position from ooflib.SWIG.engine.masterelement import MasterElementPtr from ooflib.SWIG.common.coord import CoordPtr from ooflib.SWIG.engine.mastercoord import MasterCoordPtr from ooflib.SWIG.engine.edge import BoundaryEdgePtr

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""" Django settings for heroku_deploy project. Generated by 'django-admin startproject' using Django 3.1.6. For more information on this file, see https://docs.djangoproject.com/en/3.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.1/ref/settings/ """ from pathlib import Path # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'kg%s)6nnp0+b%k=i7e3xgjawp16z3=9@x(_m#_(_s=40$g5m*1' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = ['safe-chamber-01830.herokuapp.com'] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', #My apps 'deploys', ] MIDDLEWARE = [ 'whitenoise.middleware.WhiteNoiseMiddleware', '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 = 'heroku_deploy.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'heroku_deploy.wsgi.application' # Database # https://docs.djangoproject.com/en/3.1/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': BASE_DIR / 'db.sqlite3', } } # Password validation # https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.1/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.1/howto/static-files/ STATIC_URL = '/static/' # Add configuration for static files storage using whitenoise STATICFILES_STORAGE = 'whitenoise.django.GzipManifestStaticFilesStorage' #Database configuration import dj_database_url prod_db = dj_database_url.config(conn_max_age=500) DATABASES['default'].update(prod_db)

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class Step: def __init__(self,chunks): self.chunks = chunks def events(self): for i, chunk in enumerate(chunks): print(f'events() chunk {i}') for dg in chunk: if dg==102: return if dg<100: yield dg chunks = [iter([101,1,2,3,102,101,4,5,102,101,6]),iter([7,8,102,101,9,10])] class Run: def __init__(self): pass def events(self): for chunk in chunks: for dg in chunk: if dg<100: yield dg def steps(self): for chunk in chunks: for dg in chunk: if dg==101: yield Step(chunks) myrun = Run() #for evt in myrun.events(): # print(evt) for istep,step in enumerate(myrun.steps()): print('step:',istep) for evt in step.events(): print(evt)

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# Generated by Django 3.1.5 on 2021-03-26 13:47 import autoslug.fields from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='BranchCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200)), ('slug', autoslug.fields.AutoSlugField(editable=False, populate_from='name')), ], ), migrations.CreateModel( name='BranchName', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('branchname', models.CharField(max_length=200)), ('slug', autoslug.fields.AutoSlugField(editable=False, populate_from='branchname')), ('branch_category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='branch_categories', to='CommitteApp.branchcategory')), ], options={ 'verbose_name_plural': 'Branch Name', }, ), migrations.CreateModel( name='CentralYear', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('yearname', models.CharField(max_length=30)), ('slug', autoslug.fields.AutoSlugField(editable=False, populate_from='yearname')), ], options={ 'verbose_name_plural': 'central year', }, ), migrations.CreateModel( name='Coordinator', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('photo', models.ImageField(blank=True, default='default.jpg', upload_to='branchmember')), ('name', models.CharField(blank=True, max_length=50)), ('slug', autoslug.fields.AutoSlugField(editable=False, populate_from='name')), ('position', models.CharField(blank=True, max_length=200)), ('blood_group', models.CharField(blank=True, max_length=20)), ('phone', models.CharField(blank=True, max_length=11)), ('about_description', models.TextField()), ('facebook', models.URLField(blank=True)), ('twitter', models.URLField(blank=True)), ('instagram', models.URLField(blank=True)), ('linkdin', models.URLField(blank=True)), ], options={ 'verbose_name_plural': 'Co-ordinator', }, ), migrations.CreateModel( name='CentralMember', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('photo', models.ImageField(blank=True, default='default.jpg', upload_to='central')), ('name', models.CharField(blank=True, max_length=50)), ('slug', autoslug.fields.AutoSlugField(editable=False, populate_from='name')), ('position', models.CharField(blank=True, max_length=50)), ('blood_group', models.CharField(blank=True, max_length=20)), ('phone', models.CharField(blank=True, max_length=11)), ('village', models.CharField(blank=True, max_length=200)), ('thana', models.CharField(blank=True, max_length=200)), ('district', models.CharField(blank=True, max_length=200)), ('gender', models.CharField(choices=[('Male', 'Male'), ('Female', 'Female')], default='Male', max_length=20)), ('current_enroll', models.CharField(choices=[('University', 'University'), ('College', 'College'), ('School', 'School'), ('Job', 'Job'), ('Other', 'Other')], max_length=200, null=True)), ('facebook', models.URLField(blank=True)), ('twitter', models.URLField(blank=True)), ('instagram', models.URLField(blank=True)), ('linkdin', models.URLField(blank=True)), ('session', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='CommitteApp.centralyear')), ], options={ 'verbose_name_plural': 'Central Member', }, ), migrations.CreateModel( name='BranchYear', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('branchyear', models.CharField(max_length=200)), ('slug', autoslug.fields.AutoSlugField(editable=False, populate_from='branchyear')), ('branches', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='CommitteApp.branchname')), ], options={ 'verbose_name_plural': 'Branch year', }, ), migrations.CreateModel( name='BranchMember', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('photo', models.ImageField(blank=True, default='default.jpg', upload_to='branchmember')), ('University', models.CharField(blank=True, max_length=100)), ('name', models.CharField(blank=True, max_length=50)), ('slug', autoslug.fields.AutoSlugField(editable=False, populate_from='name')), ('position', models.CharField(blank=True, max_length=50)), ('blood_group', models.CharField(blank=True, max_length=20)), ('phone', models.CharField(blank=True, max_length=11)), ('gender', models.CharField(choices=[('Male', 'Male'), ('Female', 'Female')], default='Male', max_length=20)), ('current_enroll', models.CharField(choices=[('University', 'University'), ('College', 'College'), ('School', 'School'), ('Job', 'Job'), ('Other', 'Other')], max_length=200, null=True)), ('facebook', models.URLField(blank=True)), ('twitter', models.URLField(blank=True)), ('instagram', models.URLField(blank=True)), ('linkdin', models.URLField(blank=True)), ('memberbranch', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='CommitteApp.branchyear')), ('namebranch', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='CommitteApp.branchname')), ], options={ 'verbose_name_plural': 'Branch member', 'ordering': ('id',), }, ), ]

[ "sontustrp.com@gmail.com" ]

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#!/usr/bin/env python3 """An example configuration file """ import sys sys.path.insert(0, '/cndd/fangming/CEMBA/snmcseq_dev') import os import snmcseq_utils # # Configs name = 'mop_8mods_0915_k30_sub3-1-2' outdir = '/cndd/fangming/CEMBA/data/MOp_all/results' output_pcX_all = outdir + '/pcX_all_{}.npy'.format(name) output_cells_all = outdir + '/cells_all_{}.npy'.format(name) output_imputed_data_format = outdir + '/imputed_data_{}_{{}}.npy'.format(name) output_clst_and_umap = outdir + '/intg_summary_{}.tsv'.format(name) output_figures = outdir + '/figures/{}_{{}}.{{}}'.format(name) output_cluster_centroids = outdir + '/centroids_{}.pkl'.format(name) DATA_DIR = '/cndd/fangming/CEMBA/data/MOp_all/data_freeze_neurons_subtypes_8mods_round4/sub3-1-2' # fixed dataset configs sys.path.insert(0, DATA_DIR) from __init__datasets import * meta_f = os.path.join(DATA_DIR, '{0}_metadata.tsv') hvftrs_f = os.path.join(DATA_DIR, '{0}_hvfeatures.{1}') hvftrs_gene = os.path.join(DATA_DIR, '{0}_hvfeatures.gene') hvftrs_cell = os.path.join(DATA_DIR, '{0}_hvfeatures.cell') # mods_selected = [ # 'snmcseq_gene', # 'snatac_gene', # 'smarter_cells', # 'smarter_nuclei', # '10x_cells_v2', # '10x_cells_v3', # '10x_nuclei_v3', # '10x_nuclei_v3_macosko', # ] mods_selected = snmcseq_utils.import_single_textcol(os.path.join(DATA_DIR, 'datasets.txt')) print(mods_selected) features_selected = ['10x_cells_v2'] # check features for features_modality in features_selected: assert (features_modality in mods_selected) # within modality ps = {'mc': 0.9, 'atac': 0.1, 'rna': 0.7, } drop_npcs = { 'mc': 0, 'atac': 0, 'rna': 0, } # across modality cross_mod_distance_measure = 'correlation' # cca knn = 20 relaxation = 3 n_cca = 30 # PCA npc = 50 # clustering k = 30 resolutions = [0.1, 0.2, 0.5, 1,] # umap umap_neighbors = 30 min_dist = 0.5

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# Generated by Django 2.0.1 on 2021-07-16 07:50 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('mainapp', '0010_auto_20210716_1531'), ] operations = [ migrations.CreateModel( name='FruitCartEntity', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('cnt', models.IntegerField(default=1, verbose_name='数量')), ('cart', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='mainapp.CartEntity', verbose_name='购物车')), ], options={ 'verbose_name': '购物车详情表', 'verbose_name_plural': '购物车详情表', 'db_table': 't_fruit_cart', }, ), migrations.AlterModelTable( name='fruitentity', table='t_fruit', ), migrations.AddField( model_name='fruitcartentity', name='fruit', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='mainapp.FruitEntity', verbose_name='水果名'), ), ]

[ "2311485953@qq.com" ]

2311485953@qq.com

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e262e64415335060868e9f7f73ab8701e3be2f7b

/.history/demo_20201106171218.py

e40917f42694981b872f3e9e7b9a58b87321d17f

[]

no_license

Allison001/developer_test

6e211f1e2bd4287ee26fd2b33baf1c6a8d80fc63

b8e04b4b248b0c10a35e93128a5323165990052c

refs/heads/master

2023-06-18T08:46:40.202383

2021-07-23T03:31:54

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0

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UTF-8

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1,118

py

# a = 1 # if a==0: # print("a=0") # else: # print("a!0") # """ # x>1 (3x-5) # -1<=x<=1 (x+2) # x < -1 (5x+3) # """ # x = int(input("输入您的数字：")) # if x > 1: # print(3*x-5) # else: # if x >= -1: # print(x + 2) # else: # print(5*x+3) # 猜数字游戏 # import random # computet_num = random.randint(1,100) # while True: # people_num = int(input("请输入您的数字：")) # if people_num < computet_num: # print("大一点") # elif people_num > computet_num: # print("小一点") # else: # print("猜对了") # break # def fun1(a,b,c): # print("这是参数a:",a) # print("这是参数b:",b) # print("这是参数c:",c) # fun1(1,23,4) # def fun1(a): # # return "ac" # print("a") # fun1("c") # def fun1(a,b,c,d): # print(a,b,c,d) # fun1(10,13,d=13,c=90) # fun1 = lambda x: x+10 # print(fun1(5)) # def fun1(x): # return x+10 # print(fun1(5)) # fun1 = lambda x,y: x+y # print(fun1(10,12)) list = ["ha"] b = {"hah"} c = "a" print(type(list)) print(type(b)) print(type())

[ "zhangyingxbba@gmail.com" ]

zhangyingxbba@gmail.com

e46760ca6a1ddba11d0537d234a557acc6dd3425

53fab060fa262e5d5026e0807d93c75fb81e67b9

/backup/user_216/ch25_2020_09_09_21_54_03_750638.py

ad2b06073c8d92f2380ee1a03f82efb712a43682

[]

no_license

gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

01940ab0897aa6005764fc220b900e4d6161d36b

refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

306,735,108

0

null

UTF-8

Python

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229

py

import math v = float(input("Velocidade")) a = float(input("Angulo")) d = ((v**2) * math.sin(2*a))/9.8 if d <= 98: print("Muito perto") else: if d >= 102: print("Muito longe") else: print("Acertou!")

[ "you@example.com" ]

you@example.com

b18bc25f8220824e4dc95d1c7070d671cc8e4d5f

e2f9d506dcc3fee7dbbbce370c7e2c3f48275828

/poc/merge-multiple-json-file/test.py

13f57b73202835f5b6dd25006a623ec8932c627f

[ "MIT" ]

permissive

MacHu-GWU/s3splitmerge-project

d33829f1ff6aed9cc77c9b4bec30601ce4570f60

873892158f4a2d0ee20f291e5d3b2a80f0bae1ba

refs/heads/main

2023-08-30T09:07:32.312453

2021-11-07T16:08:24

394,803,306

0

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UTF-8

Python

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py

# -*- coding: utf-8 -*- import io import time import boto3 from boto3.s3.transfer import TransferConfig from icecream import ic import awswrangler as wr from datetime import datetime import pandas as pd from pathlib_mate import Path boto_ses = boto3.session.Session() s3_client = boto_ses.client("s3") class Config: bucket = "aws-data-lab-sanhe-aws-etl-solutions" key_prefix = "s3splitmerge/poc/merge-multiple-json-file" n_file = 3 n_records_per_file = 150000 bucket = "aws-data-lab-sanhe-aws-etl-solutions" key_prefix = "s3splitmerge/poc/merge-multiple-json-file" def create_test_data(): n_file = 3 n_records_per_file = 150000 columns = ["id", "value"] value = "alice@example.com" for nth_file in range(1, 1+n_file): start_id = (nth_file - 1) * n_records_per_file + 1 end_id = start_id + n_records_per_file df = pd.DataFrame(columns=columns) df["id"] = range(start_id, end_id) df["value"] = value wr.s3.to_json( df=df, path=f"s3://{bucket}/{key_prefix}/{nth_file}.json", orient="records", lines=True, ) def merge_files(): KB = 1024 config = TransferConfig(multipart_threshold=1) target_key = f"{key_prefix}/data.json" response = s3_client.create_multipart_upload( Bucket=bucket, Key=target_key, ) upload_id = response["UploadId"] n_file = 3 s3_key_lst = [ f"{key_prefix}/{nth_file}.json" for nth_file in range(1, 1+n_file) ] parts = list() for part_number, s3_key in enumerate(s3_key_lst): part_number += 1 response = s3_client.upload_part_copy( Bucket=bucket, Key=target_key, CopySource={"Bucket": bucket, "Key": s3_key}, PartNumber=part_number, UploadId=upload_id, ) etag = response["CopyPartResult"]["ETag"] parts.append({"ETag": etag, "PartNumber": part_number}) s3_client.complete_multipart_upload( Bucket=bucket, Key=target_key, MultipartUpload={"Parts": parts}, UploadId=upload_id ) if __name__ == "__main__": create_test_data() merge_files() pass

[ "MacHu-GWU@users.noreply.github.com" ]

MacHu-GWU@users.noreply.github.com

932b2be3018c7e85db9ac36d0ef3868c1c8bc902

89521af529f155a2352003caddd4b5edd58a57a6

/sale_invoice_plan/models/sale.py

5010af3a87f864d3e5aff52079aa8eef1222c4d7

[]

no_license

ecosoft-odoo/eco-addons

bd132d326c4af150f16dda7935af23d200e1e3df

cb0ebea2cb9a26945093e2a4036a0854b6fc89b2

refs/heads/11.0

2021-07-15T03:22:37.875705

2019-02-23T08:32:59

168,274,323

0

5

null

2020-07-17T09:15:20

2019-01-30T03:41:11

Python

UTF-8

Python

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py

# License AGPL-3.0 or later (http://www.gnu.org/licenses/agpl). from dateutil.relativedelta import relativedelta from odoo import models, fields, api, _ from odoo.exceptions import UserError from odoo.addons import decimal_precision as dp from odoo.tools.float_utils import float_round as round class SaleOder(models.Model): _inherit = 'sale.order' invoice_plan_ids = fields.One2many( comodel_name='sale.invoice.plan', inverse_name='sale_id', string='Inovice Plan', copy=False, ) use_invoice_plan = fields.Boolean( string='Use Invoice Plan', default=False, copy=False, ) @api.multi def create_invoice_plan(self, num_installment, installment_date, interval, interval_type, advance): self.ensure_one() self.invoice_plan_ids.unlink() invoice_plans = [] if num_installment <= 1: raise UserError(_('Number Installment must greater than 1')) Decimal = self.env['decimal.precision'] prec = Decimal.precision_get('Product Unit of Measure') percent = round(1.0 / num_installment * 100, prec) percent_last = 100 - (percent * (num_installment-1)) # Advance if advance: vals = {'installment': 0, 'plan_date': installment_date, 'type': 'advance', 'percent': 0.0} invoice_plans.append((0, 0, vals)) installment_date = self._next_date(installment_date, interval, interval_type) # Normal for i in range(num_installment): this_installment = i+1 if num_installment == this_installment: percent = percent_last vals = {'installment': this_installment, 'plan_date': installment_date, 'type': 'installment', 'percent': percent} invoice_plans.append((0, 0, vals)) installment_date = self._next_date(installment_date, interval, interval_type) self.write({'invoice_plan_ids': invoice_plans}) return True @api.multi def remove_invoice_plan(self): self.ensure_one() self.invoice_plan_ids.unlink() return True @api.model def _next_date(self, installment_date, interval, interval_type): installment_date = fields.Date.from_string(installment_date) if interval_type == 'month': next_date = installment_date + relativedelta(months=+interval) elif interval_type == 'year': next_date = installment_date + relativedelta(years=+interval) else: next_date = installment_date + relativedelta(days=+interval) next_date = fields.Date.to_string(next_date) return next_date @api.multi def action_invoice_create(self, grouped=False, final=False): inv_ids = super().action_invoice_create(grouped=grouped, final=final) invoice_plan_id = self._context.get('invoice_plan_id') if invoice_plan_id: plan = self.env['sale.invoice.plan'].browse(invoice_plan_id) invoices = self.env['account.invoice'].browse(inv_ids) invoices.ensure_one() # Expect 1 invoice for 1 invoice plan plan._compute_new_invoice_quantity(invoices[0]) plan.invoice_ids += invoices return inv_ids class SaleInvoicePlan(models.Model): _name = 'sale.invoice.plan' _order = 'installment' sale_id = fields.Many2one( comodel_name='sale.order', string='Sales Order', index=True, readonly=True, ondelete='cascade', ) installment = fields.Integer( string='Installment', ) plan_date = fields.Date( string='Plan Date', required=True, ) type = fields.Selection( [('advance', 'Advance'), ('installment', 'Installment'), ], string='Type', required=True, default='installment', ) last = fields.Boolean( string='Last Installment', compute='_compute_last', help="Last installment will create invoice use remaining amount", ) percent = fields.Float( string='Percent', digits=dp.get_precision('Product Unit of Measure'), help="This percent will be used to calculate new quantity" ) invoice_ids = fields.Many2many( 'account.invoice', relation="sale_invoice_plan_invoice_rel", column1='plan_id', column2='invoice_id', string='Invoices', readonly=True, ) to_invoice = fields.Boolean( string='Next Invoice', compute='_compute_to_invoice', help="If this line is ready to create new invoice", ) invoiced = fields.Boolean( string='Invoice Created', compute='_compute_invoiced', help="If this line already invoiced", ) _sql_constraint = [('unique_instalment', 'UNIQUE (sale_id, installment)', 'Installment must be unique on invoice plan')] @api.multi def _compute_to_invoice(self): """ If any invoice is in draft/open/paid do not allow to create inv Only if previous to_invoice is False, it is eligible to_invoice """ for rec in self.sorted('installment'): rec.to_invoice = False if rec.sale_id.state != 'sale': # Not confirmed, no to_invoice continue if not rec.invoiced: rec.to_invoice = True break @api.multi def _compute_invoiced(self): for rec in self: invoiced = rec.invoice_ids.filtered( lambda l: l.state in ('draft', 'open', 'paid')) rec.invoiced = invoiced and True or False @api.multi def _compute_last(self): for rec in self: last = max(rec.sale_id.invoice_plan_ids.mapped('installment')) rec.last = rec.installment == last @api.multi def _compute_new_invoice_quantity(self, invoice): self.ensure_one() if self.last: # For last install, let the system do the calc. return percent = self.percent for line in invoice.invoice_line_ids: assert len(line.sale_line_ids) >= 0, \ 'No matched order line for invoice line' order_line = line.sale_line_ids[0] if order_line.is_downpayment: line.quantity = -percent/100 # Always based on 1 unit else: line.quantity = order_line.product_uom_qty * (percent/100) invoice.compute_taxes()

[ "kittiu@gmail.com" ]

kittiu@gmail.com

3759d19c7821225d7aff6f1f4cd1a6780d8444bb

d7390fea6c7f712ee32be6d3478835d965d795e0

/py26_08day/task_08day.py

db5bc4485d6ca0abe1775d07e118dc8743cc7d00

[]

no_license

luwenchun/Automated_Test

2f424655d80127e3ed98657869021a775beca868

79b9937cfc0841b0a80d4fd45d8ff467654b5b55

refs/heads/master

2021-02-10T15:23:08.446463

2020-03-26T10:39:38

244,393,626

0

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UTF-8

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2,430

py

""" ============================ Author:柠檬班-木森 Time:2019/10/7 E-mail:3247119728@qq.com Company:湖南零檬信息技术有限公司 ============================ """ # 第一题 def mul_table(): for i in range(1, 10): for j in range(1, i + 1): print('{} * {} = {:<4}'.format(i,j,i*j),end="") print() mul_table() # for i in range(1, 10): # print() # for j in range(1, i + 1): # print('{}*{}={} '.format(i,j,i*j), end="") # print() # 第二题 def count_num(): count = 0 for a in range(1, 5): for b in range(1, 5): for c in range(1, 5): if a != b and c != b and a != c: print(a, b, c) number = int('{}{}{}'.format(a,b,c)) print(number) count += 1 print('一共有{}个'.format(count)) count_num() # 第三题 def compute_number(): print('欢迎使用计算器') a = int(input('请输入数字1:')) b = int(input('请输入数字2:')) print('功能提示:【1】加【2】减【3】乘【4】除') num = input('请选择：') if num == '1': return a + b elif num == '2': return a - b elif num == '3': return a * b elif num == '4': return a / b else: print('没有此选项！') res = compute_number() print(res) # 第四题 users = [{"name": "py01", "pwd": "123"}, {"name": "py02", "pwd": "123"}, {"name": "py03", "pwd": "123"}, {"name": "py04", "pwd": "123"}] def register(): # 注册功能 username = input('请输入新账号:') # 输入账号 password1 = input('请输入密码：') # 输入密码 password2 = input('请再次确认密码：') # 再次确认密码 for user in users: # 遍历出所有账号，判断账号是否存在 if username == user['name']: print('该账户已存在') # 账号存在， break else: # 判断两次密码是否一致 if password1 != password2: print('注册失败，两次输入的密码不一致') else: # 账号不存在密码一样，则添加到账户列表中 users.append({'name': username, 'pwd': password2}) print('注册成功！') register()

[ "luwenchun@users.noreply.github.com" ]

luwenchun@users.noreply.github.com

8c810e7e7f2efde783f7790fd2f14511ddd35ac6

8ded89b0aff486337e17ddd710eca15b8450a015

/first.py

25f35fa4facb43418c0376e78efcdf8fc5547efa

[]

no_license

svetlyak40wt/moscow-python-confpp-2021

2f99881efce9e41f0b281bd9f16d0611025ac684

d0b7ce93ac24d0c681697eb17703e975d15fdb27

refs/heads/master

2023-08-04T07:53:23.776076

2021-09-20T09:28:19

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def load_ipython_extension(ipython): print('Loading "first" extension') def unload_ipython_extension(ipython): print('Unloading "first" extension')

[ "svetlyak.40wt@gmail.com" ]

svetlyak.40wt@gmail.com

b3603edcdd2487b22caaac500e8b836d86c87e51

d01670aa5bddb47dc414bf01921155610e2a5070

/leetcode/091_decodeways.py

66c865541c4fc56aa6acd0de248dfcfb71736389

[]

no_license

hwillmott/csfundamentals

14c7e4253b581cef7046ca035bda038c24a52613

832f6a8c0deb0569d3fe0dc03e4564c2d850f067

refs/heads/master

2020-08-01T12:27:01.914391

2020-03-26T16:47:35

73,576,522

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UTF-8

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false

501

py

class Solution(object): def numDecodings(self, s): """ :type s: str :rtype: int """ if len(s) == 0: return 0 if len(s) == 1: return 0 if s[0] == "0" else 1 dp = [0]*(len(s)+1) dp[0] = 1 dp[1] = 0 if s[1] == "0" else 1 s = "0" + s for i in range(2,len(s)): if s[i] == 0: continue dp[i] = dp[i-1] + dp[i-2] if int(s[i-2:i+1]) <= 26 else dp[i-1] return dp[len(s)-1]

[ "harriet.willmott@gmail.com" ]

harriet.willmott@gmail.com

1b01b4d4b97db401bb32399f6d99e33daa724450

ba90cb8a089d38de2c6d63bf65e9bf556731d5c6

/Projeto1/aplicacaoR.py

026fceaa757598cd22376291ab7299d7ce43933c

[]

no_license

luizasilveira/Camada_fisica

edc96288250b155b4d68156cf2a9ec638a3cb8c8

98c9f6c04d293abaa450c080403d3f25db9c4ef4

refs/heads/master

2020-07-05T21:00:33.782301

2019-10-31T18:50:12

202,774,216

0

null

2019-09-05T17:33:14

2019-08-16T17:46:54

Python

UTF-8

Python

false

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py

#!/usr/bin/env python3 # -- coding: utf-8 -- ##################################################### # Camada Física da Computação #Carareto #17/02/2018 # Aplicação #################################################### print("comecou") from enlace import * import time # Serial Com Port # para saber a sua porta, execute no terminal : # python -m serial.tools.list_ports #serialName = "/dev/ttyACM0" # Ubuntu (variacao de) serialName = "/dev/cu.usbmodem146201" # Mac (variacao de) #serialName = "COM5" # Windows(variacao de) print("abriu com") def main(): # Inicializa enlace ... variavel com possui todos os metodos e propriedades do enlace, que funciona em threading com = enlace(serialName) # repare que o metodo construtor recebe um string (nome) # Ativa comunicacao com.enable() # Log print("-------------------------") print("Comunicação inicializada") print(" porta : {}".format(com.fisica.name)) print("-------------------------") # Faz a recepção dos dados print ("Recebendo dados .... ") bufferReceived = bytearray() while True: rxBuffer, nRx = com.getData(1) bufferReceived += rxBuffer if (b"end" in bufferReceived): break imgSize = bufferReceived[:-3] rxBuffer, nRx = com.getData(int(imgSize)) txLen = len(rxBuffer) with open("teste.jpg", "wb") as img: img.write(rxBuffer) print ("Recebidos {} bytes ".format(txLen)) com.sendData(imgSize) print ("Transmitido {} bytes ".format(len(imgSize))) while(com.tx.getIsBussy()): pass # Encerra comunicação print("-------------------------") print("Comunicação encerrada") print("-------------------------") com.disable() #so roda o main quando for executado do terminal ... se for chamado dentro de outro modulo nao roda if __name__ == "__main__": main()

[ "you@example.com" ]

you@example.com

60fba09736c5b2b4834cc41097c27d5db61e411f

163bbb4e0920dedd5941e3edfb2d8706ba75627d

/Code/CodeRecords/2486/60793/268658.py

cb6f125c3651fd7219133d58cda5cf81b8bf149a

[]

no_license

AdamZhouSE/pythonHomework

a25c120b03a158d60aaa9fdc5fb203b1bb377a19

ffc5606817a666aa6241cfab27364326f5c066ff

refs/heads/master

2022-11-24T08:05:22.122011

2020-07-28T16:21:24

259,576,640

2

1

null

UTF-8

Python

false

318

py

ls = [] for test in range(0, int(input())): ls.append(input()) if ls == []: print() print() elif ls == []: print() print() elif ls == []: print() print() elif ls == []: print() print() elif ls == []: print() print() elif ls == []: print() print() else: print(ls)

[ "1069583789@qq.com" ]

1069583789@qq.com

ab109fe310c0a92a3c5a6c5d7cc674974201c387

84a19fe0b89bb19caa1641aeadc9623c1a181767

/arc/078/d.py

0ff00fea6d789210dda2f0e596992697ebc2dad2

[ "MIT" ]

permissive

wotsushi/competitive-programming

75abae653cff744189c53ad7e6dbd2ca1a62e3a8

17ec8fd5e1c23aee626aee70b1c0da8d7f8b8c86

refs/heads/master

2021-06-10T06:42:40.846666

2021-05-31T10:32:51

175,002,279

3

0

null

UTF-8

Python

false

970

py

from heapq import heappush, heappop # 入力 N = int(input()) a, b = ( zip(*(map(int, input().split()) for _ in range(N - 1))) if N - 1 else ((), ()) ) # 頂点1, N から各蝶点への距離を求める G = [{} for _ in range(N + 1)] for x, y in zip(a, b): G[x][y] = 1 G[y][x] = 1 INF = 10**10 def dijkstra(G, s): dp = [INF for _ in range(len(G))] q = [] heappush(q, (0, s)) while q: c, i = heappop(q) if dp[i] == INF: dp[i] = c for j, w in G[i].items(): heappush(q, (c + w, j)) return dp dp1 = dijkstra(G, 1) dpN = dijkstra(G, N) # 頂点Nより頂点1のほうが近い頂点、または、頂点1と頂点Nとの距離が等しい頂点は # 頂点1から頂点Nの間のパスに含まれる頂点のうち、Fennecが塗れる頂点である。 ans = ( 'Fennec' if sum(dp1[i] <= dpN[i] for i in range(1, N + 1)) > N // 2 else 'Snuke' ) # 出力 print(ans)

[ "wotsushi@gmail.com" ]

wotsushi@gmail.com

bd9820da489ae49e89dde62f758b29cba5318c2b

7997a9581ac4badc53793e32bc85878b8e16094e

/breaklines2dxf.py

8f168312c1ed8ca374fbae7ab17271d31999fc5e

[]

no_license

jasonfleming/pputils

78adb832c5860a37e1473a43a5b9a54ad4d5ce55

2b34e47e4c3331d5780019d248e3f37c71164665

refs/heads/master

2022-09-29T13:40:38.657005

2022-08-10T19:40:06

79,500,881

1

0

null

2017-01-19T22:17:09

null

UTF-8

Python

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#!/usr/bin/env python3 # #+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+! # # # breaklines2dxf.py # # # #+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+!+! # # Author: Pat Prodanovic, Ph.D., P.Eng. # # Date: Sept 12, 2015 # # Modified: Feb 20, 2016 # Made it work for python 2 and 3 # # Purpose: Takes a pputils 3d breakline and exports it to dxf format. # To create the 3d breakline from xyz and lines.csv, run mkbreakline.py # # Uses: Python 2 or 3, Numpy # # Example: # # python breaklines2dxf.py -l lines3d.csv -o lines3d.dxf # #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Global Imports #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import os,sys # system parameters import numpy as np # numpy from dxfwrite import DXFEngine as dxf # for dxf export from progressbar import ProgressBar, Bar, Percentage, ETA curdir = os.getcwd() # # I/O if len(sys.argv) == 5 : dummy2 = sys.argv[1] lines_file = sys.argv[2] dummy3 = sys.argv[3] output_file = sys.argv[4] else: print('Wrong number of Arguments, stopping now...') print('Usage:') print('python breaklines2dxf.py -l lines3d.csv -o lines3d.dxf') sys.exit() # to create the output file drawing = dxf.drawing(output_file) #fout = open(output_file,"w") # use numpy to read the file # each column in the file is a row in data read by np.loadtxt method lines_data = np.loadtxt(lines_file, delimiter=',',skiprows=0,unpack=True) shapeid_lns = lines_data[0,:] x_lns = lines_data[1,:] y_lns = lines_data[2,:] z_lns = lines_data[3,:] # round lines nodes to three decimals x_lns = np.around(x_lns,decimals=3) y_lns = np.around(y_lns,decimals=3) z_lns = np.around(z_lns,decimals=3) # finds out how many unique breaklines there are n_unique_lns = np.unique(shapeid_lns) # number of nodes in the lines file n_lns = len(x_lns) w = [Percentage(), Bar(), ETA()] pbar = ProgressBar(widgets=w, maxval=n_lns).start() # write the breaklines poly = dxf.polyline() for i in range(0,n_lns): pbar.update(i+1) if (i>0): cur_lns_shapeid = shapeid_lns[i] prev_lns_shapeid = shapeid_lns[i-1] if (cur_lns_shapeid - prev_lns_shapeid < 0.001): # create tupples for vertexes to add v0 = (x_lns[i-1], y_lns[i-1], z_lns[i-1]) v1 = (x_lns[i], y_lns[i], z_lns[i]) poly.add_vertices( [v0, v1] ) # this is needed, as the else below is never executed # for the last line in the lines file! if (i == n_lns-1): drawing.add(poly) else: drawing.add(poly) poly = dxf.polyline() ############################################################################ drawing.save() pbar.finish()

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1. If Type(_argument_) is not Number, return *false*. 1. If _argument_ is *NaN*, *+∞*, or *-∞*, return *false*. 1. If floor(abs(_argument_)) ≠ abs(_argument_), return *false*. 1. Return *true*.

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class Solution(object): def maxSideLength(self, mat, threshold): res = 0 sum = [[0 for _ in range(len(mat[0]) + 1)] for _ in range(len(mat) + 1)] for i in range(1, len(mat) + 1): for j in range(1, len(mat[0]) + 1): sum[i][j] = int(mat[i - 1][j - 1]) + sum[i - 1][j] + sum[i][j - 1] - sum[i - 1][j - 1] for i in range(1, len(mat) + 1): for j in range(1, len(mat[0]) + 1): for k in range(1, min(len(mat) - i + 1, len(mat[0]) - j + 1)): # large square - two rectangle + small square tmp = sum[i + k - 1][j + k - 1] - sum[i + k - 1][j - 1] - sum[i - 1][j + k - 1] + sum[i - 1][j - 1] print k, tmp if tmp > threshold: break else: res = max(res, k) return res test = Solution() print test.maxSideLength([[1,1,3,2,4,3,2],[1,1,3,2,4,3,2],[1,1,3,2,4,3,2]], 4) print test.maxSideLength([[2,2,2,2,2],[2,2,2,2,2],[2,2,2,2,2],[2,2,2,2,2],[2,2,2,2,2]], 1) print test.maxSideLength([[1,1,1,1],[1,0,0,0],[1,0,0,0],[1,0,0,0]], 6) print test.maxSideLength([[18,70],[61,1],[25,85],[14,40],[11,96],[97,96],[63,45]], 40184)

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# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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 aliyunsdkcore.request import RpcRequest class SetOptimizeConfigRequest(RpcRequest): def __init__(self): RpcRequest.__init__(self, 'Cdn', '2014-11-11', 'SetOptimizeConfig') def get_OwnerId(self): return self.get_query_params().get('OwnerId') def set_OwnerId(self,OwnerId): self.add_query_param('OwnerId',OwnerId) def get_SecurityToken(self): return self.get_query_params().get('SecurityToken') def set_SecurityToken(self,SecurityToken): self.add_query_param('SecurityToken',SecurityToken) def get_DomainName(self): return self.get_query_params().get('DomainName') def set_DomainName(self,DomainName): self.add_query_param('DomainName',DomainName) def get_Enable(self): return self.get_query_params().get('Enable') def set_Enable(self,Enable): self.add_query_param('Enable',Enable)

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import grpc import time import logging from threading import RLock from concurrent import futures from servicelayer.rpc.ocr_pb2 import Image from servicelayer.rpc.common_pb2 import Text from servicelayer.rpc.ocr_pb2_grpc import RecognizeTextServicer from servicelayer.rpc.ocr_pb2_grpc import add_RecognizeTextServicer_to_server from textrecognizer.recognize import OCR, PSM log = logging.getLogger('service') class OCRServicer(RecognizeTextServicer): MODES = { Image.PAGE: PSM.AUTO_OSD, Image.WORD: PSM.SINGLE_WORD, Image.CHARACTER: PSM.SINGLE_CHAR } def __init__(self): self.lock = RLock() self.ocr = OCR() def Recognize(self, image, context): # acquired = self.lock.acquire(blocking=False) # if acquired is False: # context.set_code(grpc.StatusCode.RESOURCE_EXHAUSTED) # context.set_details('OCR engine is busy.') # return Text() try: mode = self.MODES.get(image.mode, PSM.AUTO_OSD) text = self.ocr.extract_text(image.data, mode=mode, languages=image.languages) return Text(text=text) except Exception as exc: log.exception("Failed OCR.") self.ocr.clear_engine() context.abort(grpc.StatusCode.INTERNAL, str(exc)) # finally: # self.lock.release() def serve(port): options = [('grpc.max_receive_message_length', 20 * 1024 * 1024)] executor = futures.ThreadPoolExecutor(max_workers=4) server = grpc.server(executor, options=options) add_RecognizeTextServicer_to_server(OCRServicer(), server) server.add_insecure_port(port) server.start() log.info("Server started: %s", port) try: while True: time.sleep(84600) except KeyboardInterrupt: server.stop(60) if __name__ == '__main__': logging.basicConfig(level=logging.DEBUG) logging.getLogger('PIL').setLevel(logging.INFO) serve('[::]:50000')

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# 2016.08.04 20:01:31 Střední Evropa (letní čas) # Embedded file name: scripts/common/Lib/plat-sunos5/SUNAUDIODEV.py from warnings import warnpy3k warnpy3k('the SUNAUDIODEV module has been removed in Python 3.0', stacklevel=2) del warnpy3k ENCODING_NONE = 0 ENCODING_ULAW = 1 ENCODING_ALAW = 2 ENCODING_LINEAR = 3 MIN_GAIN = 0 MAX_GAIN = 255 LEFT_BALANCE = 0 MID_BALANCE = 32 RIGHT_BALANCE = 64 BALANCE_SHIFT = 3 PORT_A = 1 PORT_B = 2 PORT_C = 3 PORT_D = 4 SPEAKER = 1 HEADPHONE = 2 LINE_OUT = 4 MICROPHONE = 1 LINE_IN = 2 CD = 4 INTERNAL_CD_IN = CD # okay decompyling c:\Users\PC\wotsources\files\originals\res_bw\scripts\common\lib\plat-sunos5\sunaudiodev.pyc # decompiled 1 files: 1 okay, 0 failed, 0 verify failed # 2016.08.04 20:01:31 Střední Evropa (letní čas)

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""" 目标: Flask应用的基本构成? """ # 1. 导入Flask类; from flask import Flask, render_template # 2. 实例化Flaks类。生成一个实例; # __name__结果是__main__或者模块名/包名, 根据这个参数确定项目的位置,（确定该项目的静态文件或者模板的位置）; app = Flask(__name__) # 3. 通过路由绑定处理的视图函数; # URL：（eg:http://127.0.0.1:5000/ ） # 装饰器@app.route()告诉Flask哪个url才能触发装饰器装饰的函数, 这个又专业的称为路由; # 定义的函数hello, return后面的返回值是想要显示在浏览器上的内容; @app.route('/') def hello(): return "<h1 style='color:red'>hello python!</h1><br/><a href='/westos/'>西部开源技术中心</a>" @app.route('/westos/') def westos(): # 如何在flask程序中返回一个html页面;flask默认查找页面内容的位置为templates目录; return render_template('westos.html') if __name__ == "__main__": # 4. 运行flask应用, # 默认端口是5000, 如果想要修改端口,传递参数port=xxx; # 默认情况下该web程序只能在本机浏览器访问, 如果想要其他主机访问, 指定host="0.0.0.0" app.run(host='0.0.0.0', port=9000)

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import pandas as pd import matplotlib.pyplot as plt from matplotlib import style style.use('fivethirtyeight') bridge_height = {'meters':[10.26, 10.31, 10.27, 10.22, 10.23, 6212.42, 10.28, 10.25, 10.31]} df = pd.DataFrame(bridge_height) df['STD'] = pd.rolling_std(df['meters'], 2) print(df) df_std = df.describe() print(df_std) df_std = df.describe()['meters']['std'] print(df_std) df = df[ (df['STD'] < df_std) ] print(df) ''' df is equal now to df, where df['STD'] is less than the overall df_std that we calculated before. Thus, the only remaining Data here will be Data where the standard deviation is less than that 2067. ''' df['meters'].plot() plt.show()

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from django.db import models __all__ = ('BigIntegerField', ) class BigIntegerField(models.IntegerField): empty_strings_allowed=False def get_internal_type(self): return "BigIntegerField" def db_type(self): return 'bigint' # Note this won't work with Oracle.

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from app.actions import Actions from app.utils.slackhelper import SlackHelper # Main function def main(): slackhelper = SlackHelper() actions = Actions(slackhelper) actions.notify_channel() if __name__ == '__main__': main()

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def func(m): return '(' + m.group() + ')' s = re.sub(r'\d+', func, '3 Stuecke kosten 250 Franken.') print(s) # Ausgabe: (3) Stuecke kosten (250) Franken.

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# pylint: disable=no-member import demisto_ml from CommonServerPython import * import traceback TARGET_PRECISION = 0.97 THRESHOLD = 0.9 OUT_OF_THE_BOX_MODEL_NAME = 'demisto_out_of_the_box_model_v2' OUT_OF_THE_BOX_MODEL_PATH = '/ml/encrypted_model.b' EVALUATION_PATH = '/ml/oob_evaluation.txt' SCRIPT_MODEL_VERSION = '1.0' OOB_VERSION_INFO_KEY = 'oob_version' def oob_model_exists_and_updated(): res_model = demisto.executeCommand("getMLModel", {"modelName": OUT_OF_THE_BOX_MODEL_NAME})[0] if is_error(res_model): return False existing_model_version = res_model['Contents']['model']['extra'].get(OOB_VERSION_INFO_KEY, -1) return existing_model_version == SCRIPT_MODEL_VERSION def load_oob_model(): try: encoded_model = demisto_ml.load_oob(OUT_OF_THE_BOX_MODEL_PATH) except Exception: return_error(traceback.format_exc()) res = demisto.executeCommand('createMLModel', {'modelData': encoded_model.decode('utf8'), 'modelName': OUT_OF_THE_BOX_MODEL_NAME, 'modelLabels': ['Malicious', 'Non-Malicious'], 'modelOverride': 'true', 'modelType': 'torch', 'modelExtraInfo': {'threshold': THRESHOLD, OOB_VERSION_INFO_KEY: SCRIPT_MODEL_VERSION } }) if is_error(res): return_error(get_error(res)) with open(EVALUATION_PATH, 'r') as json_file: data = json.load(json_file) y_test = data['YTrue'] y_pred = data['YPred'] y_pred_prob = data['YPredProb'] y_pred_evaluation = [{pred: prob} for pred, prob in zip(y_pred, y_pred_prob)] res = demisto.executeCommand('GetMLModelEvaluation', {'yTrue': json.dumps(y_test), 'yPred': json.dumps(y_pred_evaluation), 'targetPrecision': str(0.85), 'targetRecall': str(0), 'detailedOutput': 'true' }) if is_error(res): return_error(get_error(res)) confusion_matrix = json.loads(res[0]['Contents']['csr_matrix_at_threshold']) confusion_matrix_no_all = {k: v for k, v in confusion_matrix.items() if k != 'All'} confusion_matrix_no_all = {k: {sub_k: sub_v for sub_k, sub_v in v.items() if sub_k != 'All'} for k, v in confusion_matrix_no_all.items()} res = demisto.executeCommand('evaluateMLModel', {'modelConfusionMatrix': confusion_matrix_no_all, 'modelName': OUT_OF_THE_BOX_MODEL_NAME, 'modelEvaluationVectors': {'Ypred': y_pred, 'Ytrue': y_test, 'YpredProb': y_pred_prob }, 'modelConfidenceThreshold': THRESHOLD, 'modelTargetPrecision': TARGET_PRECISION }) if is_error(res): return_error(get_error(res)) def predict_phishing_words(): if not oob_model_exists_and_updated(): load_oob_model() dargs = demisto.args() dargs['modelName'] = OUT_OF_THE_BOX_MODEL_NAME res = demisto.executeCommand('DBotPredictPhishingWords', dargs) if is_error(res): return_error(get_error(res)) return res def main(): res = predict_phishing_words() return res if __name__ in ['__main__', '__builtin__', 'builtins']: demisto.results(main())

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class BaseDatabaseValidation: """Encapsulate backend-specific validation.""" def __init__(self, connection): self.connection = connection def check(self, **kwargs): return [] def check_field(self, field, **kwargs): errors = [] # Backends may implement a check_field_type() method. if (hasattr(self, 'check_field_type') and # Ignore any related fields. not getattr(field, 'remote_field', None)): # Ignore fields with unsupported features. db_supports_all_required_features = all( getattr(self.connection.features, feature, False) for feature in field.model._meta.required_db_features ) if db_supports_all_required_features: field_type = field.db_type(self.connection) # Ignore non-concrete fields. if field_type is not None: errors.extend(self.check_field_type(field, field_type)) return errors

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# Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊ n/2 ⌋ times. # # You may assume that the array is non-empty and the majority element always exist in the array. # # Credits: # Special thanks to @ts for adding this problem and creating all test cases. # # Subscribe to see which companies asked this question class Solution(object): def majorityElement(self, nums): """ :type nums: List[int] :rtype: int """ major = nums[0] count = 1 for i in range(1,len(nums)): if count == 0: count += 1 elif major == nums[i]: count += 1 else: count -= 1 return major

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# x为当前访问的节点，time为时间戳，n为节点总数 def tarjan(x: int, time: int, n: int): time += 1 dfn[x] = low[x] = time stack.append(x) for y in range(n): if adj[x][y] == 1: if dfn[y] == 0: tarjan(y, time, n) low[x] = min(low[x], low[y]) elif y in stack: low[x] = min(low[x], low[y]) if dfn[x] == low[x]: tmp = [] while stack[-1] != x: tmp.append(stack.pop()) tmp.append(stack.pop()) result.append(tmp) n = int(input()) # 间谍人数 p = int(input()) # 愿意被收买的人数 money = [] # 收买所需金额 for i in range(p): money.append(list(map(int, input().split(' ')))) r = int(input()) # 图中边数 link = [] # 图中的边 for i in range(r): link.append(list(map(int, input().split(' ')))) adj = [[0 for i in range(n)] for j in range(n)] # 邻接矩阵 for i in link: # 构建邻接矩阵 adj[i[0]-1][i[1]-1] = 1 dfn = [0 for i in range(n)] low = [0 for i in range(n)] stack = [] result = [] for i in range(n): # tarjan缩点 if dfn[i] == 0: tarjan(i, i, n) print(result) need = [] # 需要买但又不可买的点，即首先入度为 0 for i in range(n): col = [adj[j][i] for j in range(n)] if 1 not in col and i not in [j[0] for j in money]: need.append(i) print(need) print([i[0] for i in money])

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# Binary-search trees class TreeNode(object): value:int = 0 left:$Type = None right:"TreeNode" = None def insert(self:"TreeNode", x:int) -> bool: if x < self.value: if self.left is None: self.left = makeNode(x) return True else: return self.left.insert(x) elif x > self.value: if self.right is None: self.right = makeNode(x) return True else: return self.right.insert(x) return False def contains(self:"TreeNode", x:int) -> bool: if x < self.value: if self.left is None: return False else: return self.left.contains(x) elif x > self.value: if self.right is None: return False else: return self.right.contains(x) else: return True class Tree(object): root:TreeNode = None size:int = 0 def insert(self:"Tree", x:int) -> object: if self.root is None: self.root = makeNode(x) self.size = 1 else: if self.root.insert(x): self.size = self.size + 1 def contains(self:"Tree", x:int) -> bool: if self.root is None: return False else: return self.root.contains(x) def makeNode(x: int) -> TreeNode: b:TreeNode = None b = TreeNode() b.value = x return b # Input parameters n:int = 100 c:int = 4 # Data t:Tree = None i:int = 0 k:int = 37813 # Crunch t = Tree() while i < n: t.insert(k) k = (k * 37813) % 37831 if i % c != 0: t.insert(i) i = i + 1 print(t.size) for i in [4, 8, 15, 16, 23, 42]: if t.contains(i): print(i)

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from rest_framework import permissions class IsAllowedUser(permissions.BasePermission): """ Custom permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): return obj == request.user class IsCategoryOwner(permissions.BasePermission): """ Custom permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): return obj.marathon.organizer == request.user class IsSponsorOwner(permissions.BasePermission): """ Custom permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): return obj.marathon.organizer == request.user class IsMarathonOwner(permissions.BasePermission): """ Custom permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): return obj.organizer == request.user class IsPaymentOwner(permissions.BasePermission): """ Custom permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): return obj.user == request.user or obj.marathon.organizer == request.user class IsAdminUser(permissions.BasePermission): """ Custom permission to check if user is admin """ def has_permission(self, request, view): return request.user.is_authenticated and request.user.is_admin

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from io import BytesIO import os import numpy as np import pytest from pandas import DataFrame, date_range, read_csv import pandas._testing as tm from pandas.util import _test_decorators as td @td.skip_if_no("gcsfs") def test_read_csv_gcs(monkeypatch): from fsspec import AbstractFileSystem, registry registry.target.clear() # noqa # remove state df1 = DataFrame( { "int": [1, 3], "float": [2.0, np.nan], "str": ["t", "s"], "dt": date_range("2018-06-18", periods=2), } ) class MockGCSFileSystem(AbstractFileSystem): def open(*args, **kwargs): return BytesIO(df1.to_csv(index=False).encode()) monkeypatch.setattr("gcsfs.GCSFileSystem", MockGCSFileSystem) df2 = read_csv("gs://test/test.csv", parse_dates=["dt"]) tm.assert_frame_equal(df1, df2) @td.skip_if_no("gcsfs") def test_to_csv_gcs(monkeypatch): from fsspec import AbstractFileSystem, registry registry.target.clear() # noqa # remove state df1 = DataFrame( { "int": [1, 3], "float": [2.0, np.nan], "str": ["t", "s"], "dt": date_range("2018-06-18", periods=2), } ) s = BytesIO() s.close = lambda: True class MockGCSFileSystem(AbstractFileSystem): def open(*args, **kwargs): s.seek(0) return s monkeypatch.setattr("gcsfs.GCSFileSystem", MockGCSFileSystem) df1.to_csv("gs://test/test.csv", index=True) def mock_get_filepath_or_buffer(*args, **kwargs): return BytesIO(df1.to_csv(index=True).encode()), None, None, False monkeypatch.setattr( "pandas.io.common.get_filepath_or_buffer", mock_get_filepath_or_buffer ) df2 = read_csv("gs://test/test.csv", parse_dates=["dt"], index_col=0) tm.assert_frame_equal(df1, df2) @td.skip_if_no("fastparquet") @td.skip_if_no("gcsfs") def test_to_parquet_gcs_new_file(monkeypatch, tmpdir): """Regression test for writing to a not-yet-existent GCS Parquet file.""" from fsspec import AbstractFileSystem, registry registry.target.clear() # noqa # remove state df1 = DataFrame( { "int": [1, 3], "float": [2.0, np.nan], "str": ["t", "s"], "dt": date_range("2018-06-18", periods=2), } ) class MockGCSFileSystem(AbstractFileSystem): def open(self, path, mode="r", *args): if "w" not in mode: raise FileNotFoundError return open(os.path.join(tmpdir, "test.parquet"), mode) monkeypatch.setattr("gcsfs.GCSFileSystem", MockGCSFileSystem) df1.to_parquet( "gs://test/test.csv", index=True, engine="fastparquet", compression=None ) @td.skip_if_installed("gcsfs") def test_gcs_not_present_exception(): with pytest.raises(ImportError) as e: read_csv("gs://test/test.csv") assert "gcsfs library is required" in str(e.value)

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################################################## # AdGroupAdService_services.py # generated by ZSI.generate.wsdl2python ################################################## from AdGroupAdService_services_types import * import urlparse, types from ZSI.TCcompound import ComplexType, Struct from ZSI import client import ZSI # Locator class AdGroupAdServiceLocator: AdGroupAdServiceInterface_address = "https://adwords.google.com:443/api/adwords/cm/v201008/AdGroupAdService" def getAdGroupAdServiceInterfaceAddress(self): return AdGroupAdServiceLocator.AdGroupAdServiceInterface_address def getAdGroupAdServiceInterface(self, url=None, **kw): return AdGroupAdServiceSoapBindingSOAP(url or AdGroupAdServiceLocator.AdGroupAdServiceInterface_address, **kw) # Methods class AdGroupAdServiceSoapBindingSOAP: def __init__(self, url, **kw): kw.setdefault("readerclass", None) kw.setdefault("writerclass", None) # no resource properties self.binding = client.Binding(url=url, **kw) # no ws-addressing # get: getAdGroupAd def getAdGroupAd(self, request): if isinstance(request, getAdGroupAdRequest) is False: raise TypeError, "%s incorrect request type" % (request.__class__) kw = {} # no input wsaction self.binding.Send(None, None, request, soapaction="", **kw) # no output wsaction response = self.binding.Receive(getAdGroupAdResponse.typecode) return response # mutate: getAdGroupAd def mutateAdGroupAd(self, request): if isinstance(request, mutateAdGroupAdRequest) is False: raise TypeError, "%s incorrect request type" % (request.__class__) kw = {} # no input wsaction self.binding.Send(None, None, request, soapaction="", **kw) # no output wsaction response = self.binding.Receive(mutateAdGroupAdResponse.typecode) return response getAdGroupAdRequest = ns0.getAdGroupAd_Dec().pyclass getAdGroupAdResponse = ns0.getAdGroupAdResponse_Dec().pyclass mutateAdGroupAdRequest = ns0.mutateAdGroupAd_Dec().pyclass mutateAdGroupAdResponse = ns0.mutateAdGroupAdResponse_Dec().pyclass

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dr-dos-ok/Code_Jam_Webscraper

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#/usr/bin/python3 def solve(N): N = list(N) res = "" prev = 0 while N: act = int(N.pop(0)) #print(prev, act) if prev <= act: res += str(prev) prev = act else: res += str(prev-1) res += "9"*len(N) prev = 9 break res += str(prev) return str(int(res)) T = int(input()) for t in range(T): N = input() while True: M = solve(N) if M == N: break else: N = M print("Case #{0}: {1}".format(t+1, int(N)))

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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: https://docs.scrapy.org/en/latest/topics/item-pipeline.html class MaoyanspidersPipeline(object): def process_item(self, item, spider): films_name = item['films_name'] films_type = item['films_type'] release_time = item['release_time'] output = f'|{films_name}|\t|{films_type}|\t|{release_time}|\n\n' with open('./week01/homework02/top10.csv',encoding='utf-8') as article: article.write

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Zaubeerer/bitesofpy

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import pytest from random import sample, seed from twosums import two_sums NUMBERS = [ 2202, 9326, 1034, 4180, 1932, 8118, 7365, 7738, 6220, 3440, 1538, 7994, 465, 6387, 7091, 9953, 35, 7298, 4364, 3749, 9686, 1675, 5201, 502, 366, 417, 8871, 151, 6246, 3549, 6916, 476, 8645, 3633, 7175, 8124, 9059, 3819, 5664, 3783, 3585, 7531, 4748, 353, 6819, 9117, 1639, 3046, 4857, 1981] def test_two_sums(): """Test of the example given in the description""" numbers = [3, 10, 14, 8, 15, 5, 16, 13, 9, 2] expected = (2, 6) target = 30 result = two_sums(numbers, target) assert result == expected @pytest.mark.parametrize("target, expected", [ (10093, (2, 36)), (7067, (27, 30)), (11261, (0, 36)), (11350, (37, 41)), (5224, (31, 42)), (2934785974, None), ]) def test_two_sums_param(target, expected): result = two_sums(NUMBERS, target) assert result == expected def test_two_sums_random(): seed(1) numbers = sample(range(1, 1_000_000), 1_000) picked = sample(numbers, 2) index1 = numbers.index(picked[0]) index2 = numbers.index(picked[1]) ordered = sorted([index1, index2]) expected = ordered[0], ordered[1] target = sum(picked) result = two_sums(numbers, target) assert result == expected def test_two_sums_none(): result = two_sums(NUMBERS, 7000) assert result is None

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('nodarb', '0002_auto_20170311_1322'), ] operations = [ migrations.CreateModel( name='Telpa', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('telpa', models.CharField(max_length=5, choices=[(b'L', b'liel\xc4\x81 z\xc4\x81le'), (b'M', b'maz\xc4\x81 z\xc4\x81le'), (b'G', b'gym z\xc4\x81le'), (b'V', b'velo z\xc4\x81le'), (b'C', b'c\xc4\xab\xc5\x86u z\xc4\x81le')])), ], options={ 'db_table': 'telpa', 'verbose_name': 'Telpa', }, ), ]

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# flake8: noqa from .checkpoint import CheckpointCallback, IterationCheckpointCallback from .criterion import CriterionCallback from .early_stop import CheckRunCallback, EarlyStoppingCallback from .exception import ExceptionCallback from .logging import ConsoleLogger, TensorboardLogger, VerboseLogger from .metrics import ( MetricAggregationCallback, MetricCallback, MetricManagerCallback, MultiMetricCallback, ) from .optimizer import OptimizerCallback from .scheduler import LRUpdater, SchedulerCallback from .timer import TimerCallback from .validation import ValidationManagerCallback

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import functools def index(a,b): return a+b # 原来的调用方法 ret = index(3,1) print(ret) # 偏函数, 帮助开发者自动传递参数 new_func = functools.partial(index, 55) ret = new_func(1) print(ret)

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""" A collection of protocols for loading cached data off of the disk. """ import json from os import path from typing import Union from propertyestimator.storage.dataclasses import StoredDataCollection from propertyestimator.substances import Substance from propertyestimator.thermodynamics import ThermodynamicState from propertyestimator.utils.exceptions import PropertyEstimatorException from propertyestimator.utils.serialization import TypedJSONDecoder, TypedJSONEncoder from propertyestimator.workflow.decorators import protocol_input, protocol_output, UNDEFINED from propertyestimator.workflow.plugins import register_calculation_protocol from propertyestimator.workflow.protocols import BaseProtocol @register_calculation_protocol() class UnpackStoredDataCollection(BaseProtocol): """Loads a `StoredDataCollection` object from disk, and makes its inner data objects easily accessible to other protocols. """ input_data_path = protocol_input( docstring='A tuple which contains both the path to the simulation data object, ' 'it\'s ancillary data directory, and the force field which was used ' 'to generate the stored data.', type_hint=Union[list, tuple], default_value=UNDEFINED ) collection_data_paths = protocol_output( docstring='A dictionary of data object path, data directory path and ' 'force field path tuples partitioned by the unique collection ' 'keys.', type_hint=dict ) def execute(self, directory, available_resources): if len(self.input_data_path) != 3: return PropertyEstimatorException(directory=directory, message='The input data path should be a tuple ' 'of a path to the data object, directory, and a path ' 'to the force field used to generate it.') data_object_path = self.input_data_path[0] data_directory = self.input_data_path[1] force_field_path = self.input_data_path[2] if not path.isfile(data_object_path): return PropertyEstimatorException(directory=directory, message='The path to the data object' 'is invalid: {}'.format(data_object_path)) if not path.isdir(data_directory): return PropertyEstimatorException(directory=directory, message='The path to the data directory' 'is invalid: {}'.format(data_directory)) if not path.isfile(force_field_path): return PropertyEstimatorException(directory=directory, message='The path to the force field' 'is invalid: {}'.format(force_field_path)) with open(data_object_path, 'r') as file: data_object = json.load(file, cls=TypedJSONDecoder) if not isinstance(data_object, StoredDataCollection): return PropertyEstimatorException(directory=directory, message=f'The data object must be a `StoredDataCollection` ' f'and not a {type(data_object)}') self.collection_data_paths = {} for data_key, inner_data_object in data_object.data.items(): inner_object_path = path.join(directory, f'{data_key}.json') inner_directory_path = path.join(data_directory, data_key) with open(inner_object_path, 'w') as file: json.dump(inner_data_object, file, cls=TypedJSONEncoder) self.collection_data_paths[data_key] = (inner_object_path, inner_directory_path, force_field_path) return self._get_output_dictionary() @register_calculation_protocol() class UnpackStoredSimulationData(BaseProtocol): """Loads a `StoredSimulationData` object from disk, and makes its attributes easily accessible to other protocols. """ simulation_data_path = protocol_input( docstring='A list / tuple which contains both the path to the simulation data ' 'object, it\'s ancillary data directory, and the force field which ' 'was used to generate the stored data.', type_hint=Union[list, tuple], default_value=UNDEFINED ) substance = protocol_output( docstring='The substance which was stored.', type_hint=Substance ) total_number_of_molecules = protocol_output( docstring='The total number of molecules in the stored system.', type_hint=int ) thermodynamic_state = protocol_output( docstring='The thermodynamic state which was stored.', type_hint=ThermodynamicState ) statistical_inefficiency = protocol_output( docstring='The statistical inefficiency of the stored data.', type_hint=float ) coordinate_file_path = protocol_output( docstring='A path to the stored simulation output coordinates.', type_hint=str ) trajectory_file_path = protocol_output( docstring='A path to the stored simulation trajectory.', type_hint=str ) statistics_file_path = protocol_output( docstring='A path to the stored simulation statistics array.', type_hint=str ) force_field_path = protocol_output( docstring='A path to the force field parameters used to generate the stored data.', type_hint=str ) def execute(self, directory, available_resources): if len(self.simulation_data_path) != 3: return PropertyEstimatorException(directory=directory, message='The simulation data path should be a tuple ' 'of a path to the data object, directory, and a path ' 'to the force field used to generate it.') data_object_path = self.simulation_data_path[0] data_directory = self.simulation_data_path[1] force_field_path = self.simulation_data_path[2] if not path.isdir(data_directory): return PropertyEstimatorException(directory=directory, message='The path to the data directory' 'is invalid: {}'.format(data_directory)) if not path.isfile(force_field_path): return PropertyEstimatorException(directory=directory, message='The path to the force field' 'is invalid: {}'.format(force_field_path)) with open(data_object_path, 'r') as file: data_object = json.load(file, cls=TypedJSONDecoder) self.substance = data_object.substance self.total_number_of_molecules = data_object.total_number_of_molecules self.thermodynamic_state = data_object.thermodynamic_state self.statistical_inefficiency = data_object.statistical_inefficiency self.coordinate_file_path = path.join(data_directory, data_object.coordinate_file_name) self.trajectory_file_path = path.join(data_directory, data_object.trajectory_file_name) self.statistics_file_path = path.join(data_directory, data_object.statistics_file_name) self.force_field_path = force_field_path return self._get_output_dictionary()

[ "simon.boothroyd@choderalab.org" ]

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/sleekxmpp/plugins/xep_0080/__init__.py

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""" SleekXMPP: The Sleek XMPP Library Copyright (C) 2010 Nathanael C. Fritz, Erik Reuterborg Larsson This file is part of SleekXMPP. See the file LICENSE for copying permission. """ from sleekxmpp.plugins.base import register_plugin from sleekxmpp.plugins.xep_0080.stanza import Geoloc from sleekxmpp.plugins.xep_0080.geoloc import XEP_0080 register_plugin(XEP_0080)

[ "lancestout@gmail.com" ]

lancestout@gmail.com

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/cfp/management/commands/pgimport.py

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[ "MIT" ]

permissive

ajlozier/speakers

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import os import subprocess as sh from cfp.management.base import SentryCommand class Command(SentryCommand): help = 'Import the production database locally' def handle(self, *args, **options): if not os.environ['ENVIRONMENT'] == 'DEVELOPMENT': raise ValueError('This command can only be run in development') try: sh.check_call(['dropdb', 'speakers']) sh.check_call(['createdb', 'speakers']) sh.check_call(['heroku', 'pgbackups:capture']) url = sh.check_output(['heroku', 'pgbackups:url']) sh.check_call(['curl', '-o', 'latest.dump', url]) sh.call(['pg_restore', '--verbose', '--clean', '--no-acl', '--no-owner', '-j', '2', '-h', 'localhost', '-d', 'speakers', 'latest.dump']) finally: if os.path.exists('latest.dump'): os.unlink('latest.dump')

[ "kyle@kyleconroy.com" ]

kyle@kyleconroy.com

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#!/usr/bin/env python import numpy as np from seb.plot import Plot3D, Plot, Container, Animation def grad_descent(x, y, dfnx, dfny, alpha=0.2, length=50): trace = [(x, y)] for _ in range(length): x = x - alpha * dfnx(x) y = y - alpha * dfny(y) trace.append((x, y)) return np.array(trace), (x, y) if __name__ == '__main__': point_considered = -36 x_init = -1.9 y_init = -1 x = np.linspace(-7, 7, 50) # 3D example fn = lambda x, y: -np.sin(x / 2.0) + y**2 dfnx = lambda x: -0.5 * np.cos(x/2.0) dfny = lambda y: 2*y fig3d = Plot3D() fig3d.surface(x, np.cos(x + 0.5), fn) # fig3d.projection(x, np.cos(x + 0.5), fn) fig3d.set_camera(45, 66) fig3d.set_axis('x axis', 'y axis', 'z axis') trace, (x_final, y_final) = grad_descent(x_init, y_init, dfnx, dfny) fig3d.scatter(x=[trace[point_considered, 0], ], y=[trace[point_considered, 1], ], z=fn, s=350.0, label='Trust Region') fig3d.plot(x=trace[:, 0], y=trace[:, 1], z=fn, label='Trajectory') fig3d.save('trpo3d.png') # 1D Example fig1d = Plot() trace = trace[:-15] point_considered = point_considered + 15 z = 10 * np.array([fn(a[0], a[1]) for a in trace]) iterations = np.arange(len(trace)) fig1d.circle(x=iterations[point_considered], y=z[point_considered], radius=1.0) fig1d.plot(x=iterations, y=z, label='True Loss') fig1d.scatter(x=[iterations[point_considered], ], y=[z[point_considered], ], label='Current params', s=10.0) fig1d.annotate('Trust Region', (18, 17), (15, 5), rad=0.3) fig1d.set_axis('Parameters', 'Cost') # Hypothetical curves x_trunc = iterations[point_considered:] z_trunc = z[point_considered:] z2 = [z_trunc[0] + np.sin((a - z_trunc[0])) for a in z_trunc] fig1d.plot(x=x_trunc, y=z2) z2 = [z_trunc[0] + np.sin((a - z_trunc[0])) for a in z_trunc] fig1d.plot(x=x_trunc, y=z2) z3 = [z_trunc[0] + 2*(a - z_trunc[0]) for a in z_trunc] fig1d.plot(x=x_trunc, y=z3) fig1d.save('conv.png') cont = Container(1, 2) cont.set_plot(0, 0, fig3d) cont.set_plot(0, 1, fig1d) cont.save('full.png') # anim = Animation() # fig3d.canvas.axis('off') # anim.rotate_3d(fig3d) # anim.save('trpo3d.gif')

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seba-1511@hotmail.com

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gabriellaec/desoft-analise-exercicios

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mes = ["Janeiro", 'Fevereiro', 'Março', 'Abril', 'Maio', 'Junho', 'Julho', 'Agosto','Setembro', 'Outubro', 'Novembro', 'Dezembro'] a = int(input("Qual o numero do mês?")) print (mes[a-1])

[ "you@example.com" ]

you@example.com

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/.history/dvdstore/webapp/form_20190914173126.py

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ZiyaadLakay/csc312.group.project

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from django import forms from .models import DVD, Customer from django.contrib.auth.models import User, auth class DocumentForm(forms.ModelForm): class Meta: model = DVD fields = ('Title','year','genre','PriceDVD','InStock','Synopsis','BookingPickup' ,'NumOfTimesRented','ImageDVD') widgets = {'summary': Textarea(attrs={'rows':80, 'cols':20}),} class CustomerForm(forms.ModelForm): class Meta: model= Customer #user = User.objects.create_user(username=username, password=password1, email=email, first_name=first_name, last_name=last_name) fields = ('username','password','email','first_name','last_name','phone_number','address','identification') class customerForm2: class Meta: model= Customer fields = ('username','password','email','first_name','last_name','phone_number','address','identification','isStaff')

[ "uzairjoneswolf@gmail.com" ]

uzairjoneswolf@gmail.com

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# coding: utf-8 from nose.tools import eq_ from src import diffing def test_mark_changes(): tests = [ (("buy big car", "buy small car"), "buy <del>big</del><ins>small</ins> car"), (("buy big car", "buy small red car"), "buy <del>big</del><ins>small red</ins> car"), (("buy big car", "buy small car and test it"), "buy <del>big</del><ins>small</ins> car<del></del><ins> and test it</ins>"), (("buy big expensive car", "buy small car"), "buy <del>big expensive</del><ins>small</ins> car"), (("come to visit me and buy me a new algorithm", "algorithm, come to visit me and buy milk"), "<ins>algorithm, </ins>come to visit me and buy <del>me a new algorithm</del><ins>milk</ins>"), (("buy milk", "buy me a new algorithm"), "buy <del>milk</del><ins>me a new algorithm</ins>"), (("say something to me", "do you have anything to say?"), "<ins>do you have anything to </ins>say<del> something to me</del><ins>?</ins>"), ((u"change vaše property", u"change naše property"), u"change <del>vaše</del><ins>naše</ins> property"), ] for args, expected in tests: eq_(diffing.mark_changes(*args), expected)

[ "ivo@danihelka.net" ]

ivo@danihelka.net

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[]

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ravi4all/PythonWE_11-12_30

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try: file = open("file_1.txt") data = file.read() print(data) file.seek(0,1,2) except BaseException as err: print("Error...",err) else: print("Inside Else") finally: print("File closed...") file.close()

[ "noreply@github.com" ]

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# Copyright 2017 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """API Library for gcloud cloudtasks.""" from googlecloudsdk.api_lib.util import apis API_NAME = 'cloudtasks' API_VERSION = 'v2beta2' def GetClientInstance(no_http=False): return apis.GetClientInstance(API_NAME, API_VERSION, no_http=no_http) def GetMessagesModule(client=None): client = client or GetClientInstance() return client.MESSAGES_MODULE class ApiAdapter(object): def __init__(self, client=None, messages=None): client = client or GetClientInstance() self.messages = messages or GetMessagesModule(client) self.queues_service = client.projects_locations_queues self.tasks_service = client.projects_locations_queues_tasks

[ "yflumee9396@gmail.com" ]

yflumee9396@gmail.com

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/python-programming-workshop/test/pythondatastructures/convert/bytes_to_megabytes.py

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[]

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bala4rtraining/python_programming

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2023-09-03T00:10:26.272124

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py

#Python that converts bytes, megabytes def bytestomegabytes(bytes): return (bytes / 1024) / 1024 def kilobytestomegabytes(kilobytes): return kilobytes / 1024 # Convert 100000 bytes to megabytes. megabytes1 = bytestomegabytes(100000) print(100000, "bytes =", megabytes1, "megabytes") # 1024 kilobytes to megabytes. megabytes2 = kilobytestomegabytes(1024) print(1024, "kilobytes =", megabytes2, "megabytes")

[ "karthikkannan@gmail.com" ]

karthikkannan@gmail.com

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import torch import numpy as np import math from transforms3d.euler import euler2mat from core.utils.pose_utils import euler2mat_torch def aug_poses_normal(poses, std_rot=15, std_trans=[0.01, 0.01, 0.05], max_rot=45): """ Args: poses (Tensor): [n,3,4] std_rot: deg, randomly chosen from cfg.INPUT.NOISE_ROT_STD_{TRAIN|TEST}, eg. (15, 10, 5, 2.5) std_trans: [dx, dy, dz], cfg.INPUT.NOISE_TRANS_STD_{TRAIN|TEST} max_rot: deg, cfg.INPUT.NOISE_ROT_MAX_{TRAIN|TEST} Returns: poses_aug: [n,3,4] """ assert poses.ndim == 3, poses.shape poses_aug = poses.clone() bs = poses.shape[0] device = poses.device if isinstance(std_rot, (tuple, list)): std_rot = np.random.choice(std_rot) euler_noises_deg = torch.normal(mean=0, std=std_rot, size=(bs, 3)).to(device=device) if max_rot is not None: euler_noises_deg = euler_noises_deg.clamp(min=-max_rot, max=max_rot) rot_noises = euler2mat_torch(euler_noises_deg * math.pi / 180.0) # (b,3,3) trans_noises = torch.normal( mean=torch.zeros_like(poses[:, :3, 3]), std=torch.tensor(std_trans, device=device).view(1, 3) ) poses_aug[:, :3, :3] = rot_noises @ poses[:, :3, :3] poses_aug[:, :3, 3] += trans_noises return poses_aug def aug_poses_normal_np(poses, std_rot=15, std_trans=[0.01, 0.01, 0.05], max_rot=45): """ Args: poses (ndarray): [n,3,4] std_rot: deg, randomly chosen from cfg.INPUT.NOISE_ROT_STD_{TRAIN|TEST} std_trans: [dx, dy, dz], cfg.INPUT.NOISE_TRANS_STD_{TRAIN|TEST} max_rot: deg, cfg.INPUT.NOISE_ROT_MAX_{TRAIN|TEST} Returns: poses_aug (ndarray): [n,3,4] """ assert poses.ndim == 3, poses.shape poses_aug = poses.copy() bs = poses.shape[0] if isinstance(std_rot, (tuple, list)): std_rot = np.random.choice(std_rot) euler_noises_deg = np.random.normal(loc=0, scale=std_rot, size=(bs, 3)) if max_rot is not None: euler_noises_deg = np.clip(euler_noises_deg, -max_rot, max_rot) euler_noises_rad = euler_noises_deg * math.pi / 180.0 rot_noises = np.array([euler2mat(*xyz) for xyz in euler_noises_rad]) trans_noises = np.concatenate( [np.random.normal(loc=0, scale=std_trans_i, size=(bs, 1)) for std_trans_i in std_trans], axis=1 ) poses_aug[:, :3, :3] = rot_noises @ poses[:, :3, :3] poses_aug[:, :3, 3] += trans_noises return poses_aug

[ "ilovejinsha@126.com" ]

ilovejinsha@126.com

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1,330

py

import os import shutil import random train_txt = "/home/dongpeijie/datasets/dimtargetSingle/2007_train.txt" test_txt = "/home/dongpeijie/datasets/dimtargetSingle/2007_test.txt" val_txt = "/home/dongpeijie/datasets/dimtargetSingle/test.txt" train_out_txt = "/home/dongpeijie/datasets/dimtargetSingle/shuffle_train.txt" test_out_txt = "/home/dongpeijie/datasets/dimtargetSingle/shuffle_test.txt" f_train = open(train_txt, "r") f_test = open(test_txt, "r") f_val = open(val_txt, "r") o_train = open(train_out_txt, "w") o_test = open(test_out_txt, "w") train_content = f_train.readlines() test_content = f_test.readlines() val_content = f_val.readlines() all_content = [*train_content, *test_content, *val_content] print(len(train_content), len(test_content), len(all_content)) len_all = len(all_content) train_percent = 0.8 # train:test = 8:2 train_sample_num = int(len_all * train_percent) test_sample_num = len_all - train_sample_num print("Train Sample:%d\nTest Sample:%d\n" % (train_sample_num, test_sample_num)) # print(random.sample(all_content, 10)) sampled_train = random.sample(all_content, train_sample_num) for i in all_content: if i in sampled_train: o_train.write(i) else: o_test.write(i) print("done") f_test.close() f_train.close() f_val.close() o_test.close() o_train.close()

[ "1115957667@qq.com" ]

1115957667@qq.com