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

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# import sys # input = sys.stdin.readline() n,m = map(int, input().split()) ab = [] for i in range(m): a,b = map(int, input().split()) ab.append([a,b]) class UnionFind: def __init__(self,N): self.parent = [i for i in range(N)] self._size = [1] * N self.count = 0 def root(self,a): if self.parent[a] == a: return a else: self.parent[a] = self.root(self.parent[a]) return self.parent[a] def is_same(self,a,b): return self.root(a) == self.root(b) def unite(self,a,b): ra = self.root(a) rb = self.root(b) if ra == rb: return if self._size[ra] < self._size[rb]: ra,rb = rb,ra self._size[ra] += self._size[rb] self.parent[rb] = ra self.count += 1 def size(self,a): return self._size[self.root(a)] uf = UnionFind(n) for i in range(m): a, b = ab[i][0],ab[i][1] a -= 1 b -= 1 if uf.is_same(a,b): continue uf.unite(a,b) x = 0 for i in range(n): x = max(x, uf._size[i]) print (x)

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/Exercises/CorePythonExercises/ForMathModel.py

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tsonglew/learn-python

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# -*- coding: utf-8 -*- """ 例1 混合泳接力队的选拔 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 5名候选人的百米成绩甲乙丙丁戊蝶泳 1'06"8 57"2 1'18" 1'10" 1'07"4 仰泳 1'15"6 1'06" 1'07"8 1'14"2 1'11" 蛙泳 1'27" 1'06"4 1'24"6 1'09"6 1'23"8 自由泳 58"6 53" 59"4 57"2 1'02"4 ~~~~~~~~~~~~~~~~~~穷举所有的组队方案~~~~~~~~~~~~~~~~ 选择语言: Python """ # 各种泳姿所有人的成绩列表，依次为甲、乙、丙、丁、戊(单位：秒) Butterfly = [66.8, 57.2, 78, 70, 67.4] Backstrock = [75.6, 66, 67.8, 74.2, 71] Frog = [87, 66.4, 84.6, 69.6, 83.8] Free = [58.6, 53, 59.4, 57.2, 62.4] # 储存所有最终成绩的列表 Result = [] def func(): print "甲记作1，乙记作2，丙记作3，丁记作4，戊记作5" flag = 1 for a in Butterfly: for b in Backstrock: if Backstrock.index(b) == Butterfly.index(a): continue for c in Frog: if Frog.index(c) == Backstrock.index(b) \ or Frog.index(c) == Butterfly.index(a): continue for d in Free: if Free.index(d) == Frog.index(c) \ or Free.index(d) == Backstrock.index(b) \ or Free.index(d) == Butterfly.index(a): continue time = a + b + c + d Result.append(time) print "第", flag, "种", ".蝶泳第", Butterfly.index(a)+1, "个人", print "仰泳第", Backstrock.index(b)+1, "个人", print "蛙泳第", Frog.index(c)+1, "个人", print "自由泳第", Free.index(d)+1, "个人", print "总时间：", time flag = flag + 1 # 所有可能的情况 print "所有的情况共有：", len(Result), " 种" SortedResult = sorted(Result) # 用时最短 print "最短时间: ", SortedResult[0], "秒" num = Result.index(SortedResult[0]) + 1 print "该方法为第", num, "种" if __name__ == '__main__': func()

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/backup/user_167/ch19_2019_08_30_17_33_49_991320.py

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gabriellaec/desoft-analise-exercicios

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import math g=9.8 def calcula_distancia_do_projetil (v,θ,y0): d==(v**2/2*g)*1+(1 +2*g*y0/(v)**2*(math.sin(θ)**2))**1/2 return d

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/3-2.队列.py

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michelleweii/DataStructure-Algorithms

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# 取元素的端叫做队头，添加元素的端叫做队尾 class Queue(object): """队列""" def __init__(self): self.__list = [] def enqueue(self,item): """往队列中添加一个item元素""" self.__list.append(item) def dequeue(self): """从队列头部删除一个元素""" return self.__list.pop(0) # 先进先出 def is_empty(self): """判断一个队列是否为空""" return self.__list == [] def size(self): """返回队列的大小""" return len(self.__list) # 双端队列，两端都可以进和出，相当于两个栈底部合在了一起 class Deque(object): """双端队列""" def __init__(self): self.__list = [] def add_front(self, item): """往队列头部添加一个item元素""" self.__list.insert(0,item) def add_rear(self, item): """往队列尾部添加一个item元素""" return self.__list.append(item) # 先进先出 def pop_front(self): """往队列头部删除一个元素""" return self.__list == self.__list.pop(0) def pop_rear(self): """往队列尾部删除一个元素""" return self.__list == self.__list.pop() def is_empty(self): """判断一个队列是否为空""" return self.__list == [] def size(self): """返回队列的大小""" return len(self.__list) if __name__ == "__main__": s = Queue() s.enqueue(1) s.enqueue(2) s.enqueue(3) s.enqueue(4) print(s.dequeue()) print(s.dequeue()) print(s.dequeue()) print(s.dequeue()) # 双端队列 s = Queue() s.enqueue(1) s.enqueue(2) s.enqueue(3) s.enqueue(4) print(s.dequeue()) print(s.dequeue()) print(s.dequeue()) print(s.dequeue())

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641052383@qq.com

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/PyTorch/contrib/cv/detection/NasFPN/mmdet/models/detectors/cascade_rcnn.py

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from ..builder import DETECTORS from .two_stage import TwoStageDetector @DETECTORS.register_module() class CascadeRCNN(TwoStageDetector): r"""Implementation of `Cascade R-CNN: Delving into High Quality Object Detection <https://arxiv.org/abs/1906.09756>`_""" def __init__(self, backbone, neck=None, rpn_head=None, roi_head=None, train_cfg=None, test_cfg=None, pretrained=None): super(CascadeRCNN, self).__init__( backbone=backbone, neck=neck, rpn_head=rpn_head, roi_head=roi_head, train_cfg=train_cfg, test_cfg=test_cfg, pretrained=pretrained) def show_result(self, data, result, **kwargs): """Show prediction results of the detector.""" if self.with_mask: ms_bbox_result, ms_segm_result = result if isinstance(ms_bbox_result, dict): result = (ms_bbox_result['ensemble'], ms_segm_result['ensemble']) else: if isinstance(result, dict): result = result['ensemble'] return super(CascadeRCNN, self).show_result(data, result, **kwargs)

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wangjiangben@huawei.com

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/addons/base_gengo/models/res_company.py

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marionumza/saas

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# -*- coding: utf-8 -*- # Part of Harpiya. See LICENSE file for full copyright and licensing details. from harpiya import fields, models class res_company(models.Model): _inherit = "res.company" gengo_private_key = fields.Char(string="Gengo Private Key", copy=False, groups="base.group_system") gengo_public_key = fields.Text(string="Gengo Public Key", copy=False, groups="base.group_user") gengo_comment = fields.Text(string="Comments", groups="base.group_user", help="This comment will be automatically be enclosed in each an every request sent to Gengo") gengo_auto_approve = fields.Boolean(string="Auto Approve Translation ?", groups="base.group_user", default=True, help="Jobs are Automatically Approved by Gengo.") gengo_sandbox = fields.Boolean(string="Sandbox Mode", help="Check this box if you're using the sandbox mode of Gengo, mainly used for testing purpose.")

[ "yasir@harpiya.com" ]

yasir@harpiya.com

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/Bins/MakeSparseMatrixSVD.py

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GINK03/job-recommender-api

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import pickle import gzip import glob from scipy.sparse import lil_matrix from sklearn.decomposition import TruncatedSVD # import faiss import numpy as np from pathlib import Path from tqdm import tqdm import sys from concurrent.futures import ProcessPoolExecutor import joblib import pandas as pd from os import environ as E import psutil import time import bz2 from loguru import logger HOME = Path.home() FILE = Path(__file__).name TOP_DIR = Path(__file__).resolve().parent.parent def wight_tune(w): for i in range(5): w = np.log1p(w) return w idf = pd.read_csv(f'{TOP_DIR}/var/doc_freq.csv') WORD_SIZE = 1000000 if "--create_transformer" in sys.argv: SAMPLE_SIZE = 1000000 logger.info(f"total word size is = {WORD_SIZE}") start_time = time.time() def load(arg): filename = arg try: with bz2.open(filename, "rb") as fp: vec = pickle.load(fp) SAMPLE_SIZE = vec["__SAMPLE_SIZE__"] del vec["__SAMPLE_SIZE__"] if SAMPLE_SIZE < 100: return None return (vec) except Exception as exc: logger.error(f"{exc}, {filename}") Path(filename).unlink() return None args = [] for idx, filename in tqdm(enumerate(glob.glob(f"{TOP_DIR}/var/user_vectors/*")[:SAMPLE_SIZE]), desc="load example users..."): args.append(filename) mtx = lil_matrix((SAMPLE_SIZE, WORD_SIZE)) counter = 0 with ProcessPoolExecutor(max_workers=psutil.cpu_count()) as exe: for ret in tqdm(exe.map(load, args), total=len(args), desc="load example users..."): if ret is None: continue vec = ret for term_idx, weight in vec.items(): if term_idx >= WORD_SIZE: continue mtx[counter, term_idx] = wight_tune(weight) counter += 1 logger.info(mtx.shape) mtx = mtx[:counter] logger.info(mtx.shape) # exit() logger.info(f"[{FILE}] start to train TruncatedSVD...") transformer = TruncatedSVD(n_components=500, n_iter=10, random_state=0) transformer.fit(mtx) elapsed_time = time.time() - start_time logger.info(f"[{FILE}] elapsed_time = {elapsed_time}") logger.info(f"[{FILE}] start to transform matrix...") X_transformed = transformer.transform(mtx[:5000]) logger.info(X_transformed) logger.info(X_transformed.shape) logger.info(type(X_transformed)) joblib.dump(transformer, f"{TOP_DIR}/var/transformer.joblib") if "--transform" in sys.argv: transformer = joblib.load(f"{TOP_DIR}/var/transformer.joblib") """ 1000個づつ分割 """ filenames = glob.glob(f"{TOP_DIR}/var/user_vectors/*") args = [] STEP = 4000 for i in range(0, len(filenames), STEP): args.append((i, filenames[i:i+STEP])) Path(f"{TOP_DIR}/var/transformed").mkdir(exist_ok=True, parents=True) def load(arg): key, filenames = arg mtx = lil_matrix((STEP, WORD_SIZE)) usernames = [] counter = 0 for idx, filename in enumerate(filenames): try: with bz2.open(filename, "rb") as fp: vec = pickle.load(fp) except Exception as exc: tb_lineno = sys.exc_info()[2].tb_lineno logger.error(f"[{FILE}] exc = {exc}, tb_lineno = {tb_lineno}") continue SAMPLE_SIZE = vec["__SAMPLE_SIZE__"] del vec["__SAMPLE_SIZE__"] if SAMPLE_SIZE < 100: continue for term_idx, weight in vec.items(): if term_idx >= 1000000: continue mtx[counter, term_idx] = weight usernames.append(Path(filename).name) counter += 1 mtx = mtx[:counter] X_transformed = transformer.transform(mtx) data = (usernames, X_transformed) logger.info(f"{len(usernames)}, {X_transformed.shape}") if len(usernames) != X_transformed.shape[0]: raise Exception("size not match!") with bz2.open(f"{TOP_DIR}/var/transformed/{key:09d}.pkl.bz2", "wb") as fp: fp.write(pickle.dumps(data)) with ProcessPoolExecutor(max_workers=psutil.cpu_count()) as exe: for _ in tqdm(exe.map(load, args), total=len(args), desc="transforming..."): _

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gim.kobayashi@gmail.com

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michaelconst/csuf-pythonprog

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import threading import time import random def do_work(t): print('[{}] sleeping {}s'.format(threading.current_thread().name, t)) time.sleep(t) print('[{}] exiting'.format(threading.current_thread().name)) for i in range(5): threading.Thread(target=do_work, args=(random.randint(1, 5),)).start()

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/broca/similarity/term/wikipedia.py

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from scipy.spatial.distance import pdist, squareform from broca.similarity.term import TermSimilarity from broca.knowledge.wikipedia import Wikipedia from broca.vectorize.bow import BoWVectorizer class WikipediaSimilarity(Wikipedia, TermSimilarity): def __init__(self, terms, wiki_conn=None): """ Initialize with a list of terms. Will fetch Wikipedia pages for each term, if available, then compute their similarity matrix. """ super().__init__(wiki_conn=wiki_conn) # Term map for similarity matrix lookup later terms = set(terms) self.term_map = {t: i for i, t in enumerate(terms)} # Fetch wikipages, compute cosine similarity matrix docs = [self.fetch_wikipage(t) for t in terms] vectr = BoWVectorizer() vecs = vectr.vectorize(docs) dist_mat = pdist(vecs.todense(), metric='cosine') dist_mat = squareform(dist_mat) self.sim_mat = 1/(1 + dist_mat) def __getitem__(self, terms): t1, t2 = terms try: i1 = self.term_map[t1] i2 = self.term_map[t2] return self.sim_mat[i1, i2] # Term(s) not found except KeyError: return 0.

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import clr clr.AddReference('RevitAPI') from Autodesk.Revit.DB import * clr.AddReference("RevitNodes") import Revit clr.ImportExtensions(Revit.Elements) def GetCategory(item): objtype = item.GetType().ToString() if objtype == "Autodesk.Revit.DB.ViewSchedule": return Revit.Elements.Category.ById(item.Definition.CategoryId.IntegerValue) elif objtype == "Autodesk.Revit.DB.Family": return Revit.Elements.Category.ById(item.FamilyCategoryId.IntegerValue) elif objtype == "Autodesk.Revit.DB.GraphicsStyle": return Revit.Elements.Category.ById(item.GraphicsStyleCategory.Id.IntegerValue) elif objtype == "Autodesk.Revit.DB.Category": if item.Parent: return Revit.Elements.Category.ById(item.Parent.Id.IntegerValue) else: return None elif hasattr(item, "Category"): return Revit.Elements.Category.ById(item.Category.Id.IntegerValue) else: return None items = UnwrapElement(IN[0]) if isinstance(IN[0], list): OUT = [GetCategory(x) for x in items] else: OUT = GetCategory(items)

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0equal2/Python_Programming

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###[백준]2920 info=list(map(str,input().split())) info="".join(info) if info=="12345678": print("ascending") elif info=="87654321": print("descending") else: print("mixed")

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duddms0115@gmail.com

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#copy of j25 import numpy as np from collections import namedtuple from functools import partial from PIL import Image import data_transforms import data_iterators import pathfinder import utils import app import torch import torchvision import torch.optim as optim import torch.nn as nn import torch.nn.functional as F restart_from_save = None rng = np.random.RandomState(42) # transformations p_transform = {'patch_size': (256, 256), 'channels': 3, 'n_labels': 17} #only lossless augmentations p_augmentation = { 'rot90_values': [0,1,2,3], 'flip': [0, 1] } # data preparation function def data_prep_function_train(x, p_transform=p_transform, p_augmentation=p_augmentation, **kwargs): x = x.convert('RGB') x = np.array(x) x = np.swapaxes(x,0,2) x = x / 255. x = x.astype(np.float32) x = data_transforms.lossless(x, p_augmentation, rng) return x def data_prep_function_valid(x, p_transform=p_transform, **kwargs): x = x.convert('RGB') x = np.array(x) x = np.swapaxes(x,0,2) x = x / 255. x = x.astype(np.float32) return x def label_prep_function(x): #cut out the label return x # data iterators batch_size = 16 nbatches_chunk = 1 chunk_size = batch_size * nbatches_chunk folds = app.make_stratified_split(no_folds=5) print len(folds) train_ids = folds[0] + folds[1] + folds[2] + folds[3] valid_ids = folds[4] all_ids = folds[0] + folds[1] + folds[2] + folds[3] + folds[4] bad_ids = [] train_ids = [x for x in train_ids if x not in bad_ids] valid_ids = [x for x in valid_ids if x not in bad_ids] test_ids = np.arange(40669) test2_ids = np.arange(20522) train_data_iterator = data_iterators.DataGenerator(dataset='train-jpg', batch_size=chunk_size, img_ids = train_ids, p_transform=p_transform, data_prep_fun = data_prep_function_train, label_prep_fun = label_prep_function, rng=rng, full_batch=True, random=True, infinite=True) feat_data_iterator = data_iterators.DataGenerator(dataset='train-jpg', batch_size=chunk_size, img_ids = all_ids, p_transform=p_transform, data_prep_fun = data_prep_function_valid, label_prep_fun = label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) valid_data_iterator = data_iterators.DataGenerator(dataset='train-jpg', batch_size=chunk_size, img_ids = valid_ids, p_transform=p_transform, data_prep_fun = data_prep_function_valid, label_prep_fun = label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) test_data_iterator = data_iterators.DataGenerator(dataset='test-jpg', batch_size=chunk_size, img_ids = test_ids, p_transform=p_transform, data_prep_fun = data_prep_function_valid, label_prep_fun = label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) test2_data_iterator = data_iterators.DataGenerator(dataset='test2-jpg', batch_size=chunk_size, img_ids = test2_ids, p_transform=p_transform, data_prep_fun = data_prep_function_valid, label_prep_fun = label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) nchunks_per_epoch = train_data_iterator.nsamples / chunk_size max_nchunks = nchunks_per_epoch * 40 validate_every = int(0.5 * nchunks_per_epoch) save_every = int(1 * nchunks_per_epoch) learning_rate_schedule = { 0: 1e-4, int(max_nchunks * 0.4): 3e-5, int(max_nchunks * 0.6): 1e-5, int(max_nchunks * 0.7): 5e-6, int(max_nchunks * 0.8): 2e-6, int(max_nchunks * 0.9): 1e-6 } # model class Net(nn.Module): def __init__(self): super(Net, self).__init__() self.resnet = torchvision.models.resnet34(pretrained=True) self.resnet.fc = nn.Linear(self.resnet.fc.in_features, p_transform["n_labels"]) def forward(self, x): x = self.resnet(x) x_softmax = F.softmax(x.narrow(1,0,4)) x_sigmoid = F.sigmoid(x.narrow(1,4,p_transform['n_labels']-4)) x = torch.cat([x_softmax,x_sigmoid],1) return x def build_model(): net = Net() return namedtuple('Model', [ 'l_out'])( net ) # loss class MultiLoss(torch.nn.modules.loss._Loss): def forward(self, input, target): torch.nn.modules.loss._assert_no_grad(target) softmax_loss = torch.sum(-torch.log(input.narrow(1,0,4)+1e-7)*target.narrow(1,0,4)) binary_loss = F.binary_cross_entropy(input.narrow(1,4,p_transform['n_labels']-4),target.narrow(1,4,p_transform['n_labels']-4),weight=None,size_average=False) return (binary_loss+softmax_loss)/p_transform["n_labels"] def build_objective(): return MultiLoss() def score(gts, preds): return app.f2_score_arr(gts, preds) # updates def build_updates(model, learning_rate): return optim.Adam(model.parameters(), lr=learning_rate)

[ "frederic.godin@ugent.be" ]

frederic.godin@ugent.be

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/common/PackageRequest.py

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[ "MIT" ]

permissive

liwanlei/FXTest

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refs/heads/master

2023-04-01T15:45:26.668688

2023-03-19T05:19:54

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MIT

2022-04-23T06:52:16

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py

# -*- coding: utf-8 -*- # @Date : 2017-07-20 15:13:25 # @Author : lileilei ''' requets模块的简单的封装 ''' import requests, json from config import Interface_Time_Out from requests import exceptions from common.systemlog import logger class reques(): def get(self, url, headers, parms): # get消息 try: self.r = requests.get(url, headers=headers, params=parms, timeout=Interface_Time_Out) self.r.encoding = 'UTF-8' spend = self.r.elapsed.total_seconds() json_response = json.loads(self.r.text) return json_response, spend except exceptions.Timeout: logger.exception(exceptions.Timeout) return {'get请求出错': "请求超时"} except exceptions.InvalidURL: logger.exception(exceptions.InvalidURL) return {'get请求出错': "非法url"} except exceptions.HTTPError: logger.exception(exceptions.HTTPError) return {'get请求出错': "http请求错误"} except Exception as e: logger.exception(e) return {'get请求出错': "错误原因:%s" % e} def post(self, url, params, headers): # post消息 data = json.dumps(params) try: reponse = requests.post(url, data=data, timeout=Interface_Time_Out, headers=headers) if reponse.status_code != 200: return {'post请求出错': "状态码返回不是200"} json_response = json.loads(reponse.text) spend = reponse.elapsed.total_seconds() return json_response, spend except exceptions.Timeout: logger.info(exceptions.Timeout) return {'post请求出错': "请求超时"} except exceptions.InvalidURL: logger.info(exceptions.InvalidURL) return {'post请求出错': "非法url"} except exceptions.HTTPError: logger.info(exceptions.HTTPError) return {'post请求出错': "http请求错误"} except Exception as e: logger.info(e) return {'post请求出错': "错误原因:%s" % e} def put(self, url, params, headers): # post消息 data = json.dumps(params) try: reponse = requests.put(url, data=data, timeout=Interface_Time_Out, headers=headers) if reponse.status_code != 200: logger.info(reponse.status_code) return {'put请求出错': "状态码返回不是200"} json_response = json.loads(reponse.text) spend = reponse.elapsed.total_seconds() return json_response, spend except exceptions.Timeout: logger.info(exceptions.Timeout) return {'put请求出错': "请求超时"} except exceptions.InvalidURL: logger.info(exceptions.InvalidURL) return {'put请求出错': "非法url"} except exceptions.HTTPError: logger.info(exceptions.HTTPError) return {'put请求出错': "http请求错误"} except Exception as e: logger.info(e) return {'put请求出错': "错误原因:%s" % e} def delfile(self, url, params, headers): # 删除的请求 try: self.rdel_word = requests.delete(url, data=params, headers=headers, timeout=Interface_Time_Out) json_response = json.loads(self.rdel_word.text) spend = self.rdel_word.elapsed.total_seconds() return json_response, spend except exceptions.Timeout: logger.info(exceptions.Timeout) return {'delete请求出错': "请求超时"} except exceptions.InvalidURL: logger.info(exceptions.InvalidURL) return {'delete请求出错': "非法url"} except exceptions.HTTPError: logger.info(exceptions.HTTPError) return {'delete请求出错': "http请求错误"} except Exception as e: logger.info(e) return {'delete请求出错': "错误原因:%s" % e} def putfile(self, url, params, headers): # put请求 try: self.rdata = json.dumps(params) me = requests.put(url, self.rdata, headers=headers, timeout=Interface_Time_Out) json_response = json.loads(me.text) spend = me.elapsed.total_seconds() return json_response, spend except exceptions.Timeout: logger.exception(exceptions.Timeout) return {'put请求出错': "请求超时"} except exceptions.InvalidURL: logger.exception(exceptions.InvalidURL) return {'put请求出错': "非法url"} except exceptions.HTTPError: logger.exception(exceptions.HTTPError) return {'put请求出错': "http请求错误"} except Exception as e: logger.exception(e) return {'put请求出错': "错误原因:%s" % e}

[ "leileili126@163.com" ]

leileili126@163.com

bc02bd5d06610caebebf2ffa034ff85777eb4b1d

d51e67abc7709b17664ee08eb9d68ecb938f00a9

/utils/farmbot.py

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[]

no_license

averdier/farmware_watering_farmdesign

bb6d3d2615c8ac5294e3bbd61cea97cf0950e05c

d474d78629504907971c7f7b2ee6b88954f6f4cf

refs/heads/master

2020-03-30T09:26:40.012409

2018-10-02T09:16:04

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# -*- coding: utf-8 -*- import uuid from time import time, sleep from .api import send_celery_script, log, get_resource from .geometry import Point3D def prepare_move_absolute_script(position, speed): return { 'kind': 'rpc_request', 'args': { 'label': 'farmware_circle_' + str(uuid.uuid4()) }, 'body': [{ 'kind': 'move_absolute', 'args': { 'location': { 'kind': 'coordinate', 'args': { 'x': position.x, 'y': position.y, 'z': position.z } }, 'offset': { 'kind': 'coordinate', 'args': { 'x': 0, 'y': 0, 'z': 0 } }, 'speed': speed } }] } class FarmBot: @property def position(self): response = get_resource('/api/v1/bot/state') if response.status_code != 200: raise RuntimeError('Unable to get position') data = response.json()['location_data']['position'] return Point3D(data['x'], data['y'], data['z']) def move(self, position, speed, tolerance, timeout): target = Point3D( int(position.x), int(position.y), int(position.z) ) log('target position: ' + str(target), 'debug') celery_move_script = prepare_move_absolute_script(target, speed) current_position = self.position send_celery_script(celery_move_script) t0 = time() while not target == current_position: new_position = self.position if new_position == current_position: if new_position.is_near(target, tolerance): break else: t1 = time() if t1 - t0 > timeout: if not new_position.is_near(target, tolerance): raise RuntimeError('Movement timeout') else: break else: current_position = new_position t0 = time() sleep(0.5)

[ "a.verdier@outlook.fr" ]

a.verdier@outlook.fr

2b9bacb7050fe1eb24ece4e8eb572e2926d53cb4

4f340ed313a67bddf077a9d8da2205b9c2feb29a

/emv/util.py

dd9f8ac0b99ed0b904b87cec4e819cd092561dd2

[ "MIT" ]

permissive

russss/python-emv

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refs/heads/main

2023-06-21T19:09:10.124472

2023-06-01T18:44:34

2023-06-11T15:26:11

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MIT

2023-06-11T15:26:12

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py

import re def hex_int(val): """Convert an integer into a decimal-encoded hex integer as bytes, which the EMV spec seems awfully keen on. >>> hex_int(123456) [0x12, 0x34, 0x56] >>> hex_int(65432) [0x06, 0x54, 0x32] """ s = str(val) if len(s) % 2 != 0: s = "0" + s return [int(s[i : i + 2], 16) for i in range(0, len(s), 2)] def from_hex_int(val): """Convert hex digits to decimal. >>> from_hex_int([0x12, 0x34]) 1234 """ return int("".join(["%02x" % i for i in val]).rstrip("f")) def from_hex_date(val): return "%02x/%02x/%02x" % (val[0], val[1], val[2]) def decode_int(val): result = val[0] for i in val[1:]: result = result << 8 result += i return result def format_bytes(data): if type(data) == int: return "[%02X]" % data return "[" + " ".join(["%02X" % i for i in data]) + "]" def unformat_bytes(data): data = re.split(r"(?:\s+|:)", data) return [int(i, 16) for i in data] def bit_set(value, bit): mask = 1 << bit return (value & mask) == mask

[ "russ@garrett.co.uk" ]

russ@garrett.co.uk

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/test/test_dialogs/test_title_screen.py

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permissive

krother/tilegamelib

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refs/heads/master

2022-07-21T20:07:35.031330

2022-07-10T20:18:19

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from unittest import TestCase, main from conftest import MENU_RECT, TITLE_IMAGE, TITLE_RECT from tilegamelib.dialogs.title_screen import TitleScreen from tilegamelib.events import QUIT_EVENT, EventGenerator from tilegamelib.menu import VERTICAL_MOVES class TitleScreenTests(TestCase): def setUp(self): self.events = EventGenerator() self.result = '' def one(self): self.result += '1' def two(self): self.result += '2' def three(self): self.result += '3' def test_show_title(self, screen): """Displays a main menu.""" menu = [ ('One', self.one), ('Two', self.two), ('Three', self.three), ] title = TitleScreen(screen, self.events, TITLE_RECT, TITLE_IMAGE, menu, MENU_RECT, VERTICAL_MOVES) self.events.add_scripted_keys([K_UP, K_RETURN, K_DOWN, K_DOWN, K_SPACE, K_RETURN, K_UP, K_RETURN, K_UP], converter=int) self.events.add_scripted_event(QUIT_EVENT) title.run() self.assertEqual(self.result, '3') if __name__ == '__main__': main()

[ "krother@academis.eu" ]

krother@academis.eu

3742ff611dc02b777b4f83d39a8aade1e7dc7cfc

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/build/globalplanner/catkin_generated/pkg.installspace.context.pc.py

a04cf5b45702ff3cf2cd28d70712504d7506b0de

[]

no_license

rfzeg/simon_thesis_ws

c5e6d6b20ee63010ffede91d17ba144527e5f6c5

dc79635f628dade14cab1a631cc4eb24aee1762c

refs/heads/master

2021-09-16T12:43:41.270235

2018-06-20T12:40:57

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null

UTF-8

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py

# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "/home/simoneforno/simon_ws/install/include".split(';') if "/home/simoneforno/simon_ws/install/include" != "" else [] PROJECT_CATKIN_DEPENDS = "roscpp;pluginlib;costmap_2d;base_local_planner;nav_core".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "-lglobalplanner".split(';') if "-lglobalplanner" != "" else [] PROJECT_NAME = "globalplanner" PROJECT_SPACE_DIR = "/home/simoneforno/simon_ws/install" PROJECT_VERSION = "0.0.0"

[ "s.forno@student.tue.nl" ]

s.forno@student.tue.nl

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/game/src/coginvasion/attack/LinearProjectile.py

f5e3003258b6aada6e2dd3d56c10f9ceea59b384

[]

no_license

xMakerx/cio-src

48c9efe7f9a1bbf619a4c95a4198aaace78b8491

60b2bdf2c4a24d506101fdab1f51752d0d1861f8

refs/heads/master

2023-02-14T03:12:51.042106

2021-01-15T14:02:10

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0

null

2021-01-15T15:15:35

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484

py

from src.coginvasion.attack.BaseProjectile import BaseProjectile from src.coginvasion.attack.LinearProjectileShared import LinearProjectileShared class LinearProjectile(BaseProjectile, LinearProjectileShared): def __init__(self, cr): BaseProjectile.__init__(self, cr) LinearProjectileShared.__init__(self) def onSpawn(self): self.playLinear() def disable(self): LinearProjectileShared.cleanup(self) BaseProjectile.disable(self)

[ "maverick.liberty29@gmail.com" ]

maverick.liberty29@gmail.com

a6cac7d77145dd89deb708f5be1407ffe096d320

9743d5fd24822f79c156ad112229e25adb9ed6f6

/xai/brain/wordbase/verbs/_suffocated.py

8b356fe7d1d8ac09890ee20e1e5dc5a7719a80ba

[ "MIT" ]

permissive

cash2one/xai

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e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6

refs/heads/master

2021-01-19T12:33:54.964379

2017-01-28T02:00:50

null

0

null

UTF-8

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py

from xai.brain.wordbase.verbs._suffocate import _SUFFOCATE #calss header class _SUFFOCATED(_SUFFOCATE, ): def __init__(self,): _SUFFOCATE.__init__(self) self.name = "SUFFOCATED" self.specie = 'verbs' self.basic = "suffocate" self.jsondata = {}

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

280b60d0e3b097e45c49ec6db0db8f323a43d3c5

9568dee77459304ad0f7e01c9dea9432c11377d0

/maxlike_sim_filehandler.py

c91d4799c888691d93117cefde6a1784acc6f66d

[ "MIT" ]

permissive

lbaumo/wtgpipeline

c101c7e7ec1491a1c40cbe14102662770641bb9a

73de01736e33769c09c4467e3c040545d7070407

refs/heads/master

2021-06-20T14:40:38.263891

2017-08-14T21:08:24

null

0

null

UTF-8

Python

false

2,688

py

############################# # Handles loading files for a simulation run ############################# import ldac, cPickle, numpy as np import astropy.io.fits as pyfits import pdzfile_utils, nfwutils, varcontainer ############################# __cvs_id__ = "$Id$" ############################# class SimFilehandler(object): ############### def addCLOps(self, parser): parser.add_option('-i', '--inputcat', dest='inputCatFile', help='Simulation format cat containing shape info') parser.add_option('-b', '--bpz', dest='inputBPZ', help='BPZ file objects were drawn from') parser.add_option('-p', '--pdzfile', dest='inputPDZ', help='Simulation PDZ file') ############################# def createOptions(self, inputCatFile, inputBPZ, inputPDZ, options = None, args = None): if options is None: options = varcontainer.VarContainer() options.inputCatFile = inputCatFile options.inputBPZ = inputBPZ options.inputPDZ = inputPDZ return options, args ############################# def readData(self, manager): options = manager.options manager.open('inputcat', options.inputCatFile, ldac.openObjectFile) manager.concentration = manager.inputcat.hdu.header['CONCEN'] manager.zcluster = manager.inputcat.hdu.header['Z'] manager.store('r500', nfwutils.rdelta, manager.inputcat.hdu.header['R_S'], manager.concentration, 500) bpz = ldac.openObjectFile(options.inputBPZ, 'STDTAB') if bpz is None: bpz = ldac.openObjectFile(options.inputBPZ, 'COS30PHOTZ') manager.matchedBPZ = bpz.matchById(manager.inputcat, 'z_id') bpz = manager.matchedBPZ newcols = [pyfits.Column(name = 'z_b', format = 'E', array = bpz['BPZ_Z_B']), pyfits.Column(name='odds', format = 'E', array = bpz['BPZ_ODDS']), pyfits.Column(name='z_t', format = 'E', array = bpz['BPZ_T_B'])] inputcat = ldac.LDACCat(pyfits.new_table(pyfits.ColDefs(newcols) + manager.inputcat.hdu.columns)) manager.replace('inputcat', inputcat) manager.open('pdzmanager', options.inputPDZ, pdzfile_utils.PDZManager.open) pdzrange, associatedPDZs = manager.pdzmanager.associatePDZ(manager.inputcat['z_id']) pdzrange = pdzrange.astype(np.float64) associatedPDZs = associatedPDZs.astype(np.float64) manager.pdzrange = pdzrange manager.pdz = associatedPDZs manager.replace('pdzmanager', None)

[ "dapple@xoc7.stanford.edu" ]

dapple@xoc7.stanford.edu

adeb59d010bdfae9169f837cf998303af2c9df2e

463c053bcf3f4a7337b634890720ea9467f14c87

/rllib/models/jax/misc.py

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[ "BSD-3-Clause", "MIT", "Apache-2.0" ]

permissive

pdames/ray

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refs/heads/master

2023-01-23T06:11:11.723212

2022-05-06T22:55:59

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Apache-2.0

2023-01-14T08:02:21

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import time from typing import Callable, Optional from ray.rllib.utils.framework import get_activation_fn, try_import_jax jax, flax = try_import_jax() nn = np = None if flax: import flax.linen as nn import jax.numpy as np class SlimFC: """Simple JAX version of a fully connected layer.""" def __init__( self, in_size, out_size, initializer: Optional[Callable] = None, activation_fn: Optional[str] = None, use_bias: bool = True, prng_key: Optional[jax.random.PRNGKey] = None, name: Optional[str] = None, ): """Initializes a SlimFC instance. Args: in_size (int): The input size of the input data that will be passed into this layer. out_size (int): The number of nodes in this FC layer. initializer (flax.: activation_fn (str): An activation string specifier, e.g. "relu". use_bias (bool): Whether to add biases to the dot product or not. #bias_init (float): prng_key (Optional[jax.random.PRNGKey]): An optional PRNG key to use for initialization. If None, create a new random one. name (Optional[str]): An optional name for this layer. """ # By default, use Glorot uniform initializer. if initializer is None: initializer = nn.initializers.xavier_uniform() self.prng_key = prng_key or jax.random.PRNGKey(int(time.time())) _, self.prng_key = jax.random.split(self.prng_key) # Create the flax dense layer. self._dense = nn.Dense( out_size, use_bias=use_bias, kernel_init=initializer, name=name, ) # Initialize it. dummy_in = jax.random.normal(self.prng_key, (in_size,), dtype=np.float32) _, self.prng_key = jax.random.split(self.prng_key) self._params = self._dense.init(self.prng_key, dummy_in) # Activation function (if any; default=None (linear)). self.activation_fn = get_activation_fn(activation_fn, "jax") def __call__(self, x): out = self._dense.apply(self._params, x) if self.activation_fn: out = self.activation_fn(out) return out

[ "noreply@github.com" ]

pdames.noreply@github.com

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/Python_codes/p03129/s302066927.py

0887597072b00c7f90e5a7d87138c543cb18fc6f

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

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false

156

py

import sys N, K = map(int, input().split()) ans = 0 for i in range(1,N+1,2): ans = ans + 1 if ans >= K: print("YES") sys.exit() print("NO")

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

66529651+Aastha2104@users.noreply.github.com

77ec1a307afebd5162f2ea1d4eaaece759d3fd15

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/solutions_5753053697277952_0/Python/BIPUL/a.py

3b8209e6b92d12243001a0707948776e81fe2d81

[]

no_license

alexandraback/datacollection

0bc67a9ace00abbc843f4912562f3a064992e0e9

076a7bc7693f3abf07bfdbdac838cb4ef65ccfcf

refs/heads/master

2021-01-24T18:27:24.417992

2017-05-23T09:23:38

84,313,442

2

4

null

UTF-8

Python

false

1,955

py

############### Author: Bipul Ranjan @ranjanbipul ############### import sys import time import os import math import operator import random from functools import lru_cache from decimal import Decimal as D from fractions import Fraction as F #sys.setrecursionlimit(10000) #@lru_cache(maxsize=None) MOD = 1000000007 ################################################################ QNO = 'a' #SET QUESTION NUMBER FIN,FOUT = QNO+'.in.txt',QNO+'.out.txt' FIN = QNO.capitalize()+'-small-attempt0.in' #FIN = QNO+'.sample.txt' #FIN = QNO.capitalize()+'-large.in' fin = open(FIN) fout = open(FOUT,'w') sys.stdin = fin ######################## PROGRAM START ########################## def solve(a,n): return len(a) for nu in range(int(input())): n = int(input()) a = [int(i) for i in input().strip().split(" ")] t = 0 for i in a: t+=i print("Case #{0}:".format(nu+1),file=fout,end=" ") while t>0: #print(t) s = [] if t==2: for i in range(n): if a[i]==1: s.append(i) t-=1 a[i]-=1 if len(s)==2: break elif t==3: for i in range(n): if a[i]==1: s.append(i) t-=1 a[i]-=1 break else: m = 0 for i in range(1,n): if a[i]>a[m]: m =i s.append(m) t-=1 a[m]-=1 m = 0 for i in range(1,n): if a[i]>a[m]: m =i s.append(m) t-=1 a[m]-=1 s = [chr(i+65) for i in s] print("{0}".format("".join(s)),file=fout,end=" ") print("",file=fout) ######################## PROGRAM END ############################# fin.close() fout.close() print("Program complete")

[ "alexandra1.back@gmail.com" ]

alexandra1.back@gmail.com

ac6d4db8c9c186c23b51f9690ba1d838c76936cc

b9662213e143acea87e9af6f41143c50f23bec95

/main.py

3bcc258a67bac8bb863e85ccfce47cd210cce045

[]

no_license

elprofedotti/python-mvc

3442680dc20d7cb0ec9c3bf09442daecda4c8e4e

9beee06de2e7a04ad872e037157a08dd2bb3dcc6

refs/heads/main

2023-08-04T08:17:03.886448

2021-04-20T12:57:17

2021-04-20T12:58:07

null

0

null

UTF-8

Python

false

199

py

"""Entry point.""" from app.app import Application from app.views import MainPage from app.models import Book if __name__ == "__main__": app = Application(MainPage(Book.list())) app.run()

[ "mbriolet.ma@gmail.com" ]

mbriolet.ma@gmail.com

235c672831f5d93373e32f38e38f5655cf5ab225

fd48fba90bb227017ac2da9786d59f9b9130aaf0

/digsby/src/contacts/BuddyListElement.py

f33b3380035eee14ea46a75e7f98d16ccdad3ccf

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

permissive

niterain/digsby

bb05b959c66b957237be68cd8576e3a7c0f7c693

16a62c7df1018a49eaa8151c0f8b881c7e252949

refs/heads/master

2021-01-18T10:07:10.244382

2013-11-03T02:48:25

5,991,568

1

0

null

2013-11-03T02:48:26

2012-09-28T02:24:50

Python

UTF-8

Python

false

630

py

from util.primitives.funcs import isiterable from common.actions import ActionMeta class BuddyListElement(object): __metaclass__ = ActionMeta @property def num_online(self): from Contact import Contact if isiterable(self) and not isinstance(self, Contact): return sum(elt.num_online for elt in self) else: return int(self.online) def find(self, obj): assert isinstance(self, list) return list.find(self, obj) def chat(self): import gui.imwin, wx wx.CallAfter(lambda: gui.imwin.begin_conversation(self))

[ "mdougherty@tagged.com" ]

mdougherty@tagged.com

0a67f283ef42dca44daf76bbc4a66abe4d8c48dd

951a84f6fafa763ba74dc0ad6847aaf90f76023c

/Solu86.py

e7e90402710c612a3e2d5f06db28be58e7c62afc

[]

no_license

SakuraGo/leetcodepython3

37258531f1994336151f8b5c8aec5139f1ba79f8

8cedddb997f4fb6048b53384ac014d933b6967ac

refs/heads/master

2020-09-27T15:55:28.353433

2020-02-15T12:00:02

226,550,406

1

null

UTF-8

Python

false

1,225

py

# # 86. 分隔链表 # 给定一个链表和一个特定值 x，对链表进行分隔，使得所有小于 x 的节点都在大于或等于 x 的节点之前。 # # 你应当保留两个分区中每个节点的初始相对位置。 # # 输入: head = 1->4->3->2->5->2, x = 3 # 输出: 1->2->2->4->3->5 # Definition for singly-linked list. class ListNode: def __init__(self, x): self.val = x self.next = None class Solution: def partition(self, head: ListNode, x: int) -> ListNode: dummy = ListNode(-1) pre = dummy dummy.next = head if head is None: return head while pre.next is not None and pre.next.val < x: print(pre.val) pre = pre.next if pre.next is None: return head flag = pre.next pre11 = flag cur = flag.next while cur is not None: print(cur.val) if cur.val >= x: pre11 = cur cur = cur.next else: pre.next = cur pre11.next = cur.next cur.next = flag cur = pre11.next pre = pre.next return dummy.next

[ "452681917@qq.com" ]

452681917@qq.com

782ce93a0a256fec41cbd6777146f5c3cd2c5695

b3586235dc1e1acbd49fab996f581269a808480b

/sistema/planeamento/migrations/0013_ordemproducao_num_paletes_stock_in.py

1fcbb090362b7154911b2ca6ccc20eb7e102cd64

[]

no_license

gonfersilva/Sistema

37ad1cd03dfbb7889fa0b0367c6ebd9044712ae3

4c6d9ade22040972efbe892eae0130939d7b5c46

refs/heads/master

2021-10-23T23:21:51.262723

2021-10-13T19:45:49

155,545,680

0

null

UTF-8

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false

458

py

# Generated by Django 2.2.7 on 2020-08-06 14:53 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('planeamento', '0012_auto_20200805_1401'), ] operations = [ migrations.AddField( model_name='ordemproducao', name='num_paletes_stock_in', field=models.IntegerField(default=0, verbose_name='Nº de paletes de stock inseridas'), ), ]

[ "goncalo.silva@elastictek.com" ]

goncalo.silva@elastictek.com

095c6844b796a1aa2773a69bc20447cb7d6c0cd5

efe67da7ca1092e033fba7b0a251a43d9a165022

/get_city_from_id/views.py

5d69da18fd281507a348b06021c952f6c6f4bd2e

[]

no_license

poojapauskar/savmytime-api

0a019077720ab9ec9bd113379e77f0f4c83ef887

2bb48d60fce24888c2d4e4ba3b1da8947242a1fd

refs/heads/master

2021-01-21T13:29:41.086409

2016-05-09T06:38:54

54,106,625

0

null

UTF-8

Python

false

1,573

py

from services.models import Services from category.models import Category from sub_category.models import Sub_category from cities.models import Cities from get_details.serializers import Get_detailsSerializer from rest_framework import generics # from ticket.permissions import IsOwnerOrReadOnly # from rest_framework import permissions from django.shortcuts import get_object_or_404 from django.db.models import Count from django.http import JsonResponse # class Get_listList(generics.ListCreateAPIView): # queryset = Ticket.objects.all() # serializer_class = Get_listSerializer # permission_classes = (permissions.IsAuthenticatedOrReadOnly,) class StatusCode(object): OK = 200 NOT_FOUND = 404 # add more status code according to your need import json from django.http import HttpResponse def JSONResponse(data = None, status = StatusCode.OK): if data is None: return HttpResponse(status) if data and type(data) is dict: return HttpResponse(json.dumps(data, indent = 4, encoding = 'utf-8', sort_keys = True), \ mimetype = 'application/json', status = status) else: return HttpResponse(status = StatusCode.NOT_FOUND) from django.views import generic from django.views.generic import ListView class CustomListView(ListView): #paginate_by = 2 def get(self, request, *args, **kwargs): import sys # print >> sys.stderr, service_id id1=self.kwargs['id'] objects=list(Cities.objects.filter(id=id1).values('city')) return JsonResponse(objects,safe=False)

[ "git.poojapauskar@gmail.com" ]

git.poojapauskar@gmail.com

1b6e511387f944e0ce53157aa60363c6551647e9

2a4290c36832e7080faa4104d58083c29ed1ea09

/prepro.py

244c70dc13f9e7ef94ec033204e0662e264afae7

[]

no_license

jerryli27/my_dtn

0380e22fb7892f5d46084339a5edb24c8ed5b8c8

54b16f403a480c35d5ae331dbbfd0efed53880b9

refs/heads/master

2021-01-19T17:17:19.787195

2017-03-05T21:48:06

82,433,878

3

0

null

UTF-8

Python

false

1,292

py

""" The cat face data comes from https://sites.google.com/site/catdatacollection/data """ import numpy as np import pickle from PIL import Image from tensorflow.examples.tutorials.mnist import input_data def resize_images(image_arrays, size=[32, 32]): # convert float type to integer image_arrays = (image_arrays * 255).astype('uint8') resized_image_arrays = np.zeros([image_arrays.shape[0]]+size) for i, image_array in enumerate(image_arrays): image = Image.fromarray(image_array) resized_image = image.resize(size=size, resample=Image.ANTIALIAS) resized_image_arrays[i] = np.asarray(resized_image) return np.expand_dims(resized_image_arrays, 3) def save_pickle(data, path): with open(path, 'wb') as f: pickle.dump(data, f, pickle.HIGHEST_PROTOCOL) print ('Saved %s..' %path) def main(): mnist = input_data.read_data_sets(train_dir='mnist') train = {'X': resize_images(mnist.train.images.reshape(-1, 28, 28)), 'y': mnist.train.labels} test = {'X': resize_images(mnist.test.images.reshape(-1, 28, 28)), 'y': mnist.test.labels} save_pickle(train, 'mnist/train.pkl') save_pickle(test, 'mnist/test.pkl') if __name__ == "__main__": main()

[ "jerrylijiaming@gmail.com" ]

jerrylijiaming@gmail.com

d0ecd64d2fe16d6c50d3a51d49b2fca1bdfdb0cd

e70b6032024b290e2ba11fa5266ef912d9ac14a2

/crits/comments/urls.py

bdb50ae5c327a6f98d12bcca1f9b041ce9ffffc0

[ "MIT" ]

permissive

ckane/crits

105b45c00b6ad85064b8e33ecd12e7474fc84fd6

e2f2b71927d08e6432a0e540a0f4634da675ce53

refs/heads/master

2021-01-17T07:57:01.495393

2016-04-11T04:29:35

20,622,493

2

0

null

2016-04-11T04:29:36

2014-06-08T17:45:07

JavaScript

UTF-8

Python

false

558

py

from django.conf.urls import patterns urlpatterns = patterns('crits.comments.views', (r'^remove/(?P<obj_id>\S+)/$', 'remove_comment'), (r'^(?P<method>\S+)/(?P<obj_type>\S+)/(?P<obj_id>\S+)/$', 'add_update_comment'), (r'^activity/$', 'activity'), (r'^activity/(?P<atype>\S+)/(?P<value>\S+)/$', 'activity'), (r'^activity/get_new_comments/$', 'get_new_comments'), (r'^search/(?P<stype>[A-Za-z0-9\-\._]+)/(?P<sterm>.+?)/$', 'comment_search'), (r'^list/$', 'comments_listing'), (r'^list/(?P<option>\S+)/$', 'comments_listing'), )

[ "mgoffin@mitre.org" ]

mgoffin@mitre.org

03d3d6b6062452e771dd0f53277a1ff0b3f6c1e9

1df7ba55c4b61772c1a31c503e6b8881f1456dc5

/untitled9/apps/courses/migrations/0010_auto_20170209_1147.py

dfa9d9ea221e6a9ea9b645c7a86fa3dfcace7f37

[]

no_license

fzk466569/python-django-pro

35918756060fcae375d3c99ea1a6934949b6d605

9add086b7a910f255df5b192268f1e117057e053

refs/heads/master

2021-01-19T13:18:14.141880

2017-02-19T12:16:29

82,374,668

0

null

UTF-8

Python

false

545

py

# -*- coding: utf-8 -*- # Generated by Django 1.9.8 on 2017-02-09 11:47 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('courses', '0009_auto_20170209_1146'), ] operations = [ migrations.AlterField( model_name='course', name='learn_about', field=models.CharField(default='', max_length=200, verbose_name='\u901a\u8fc7\u672c\u8bfe\u7a0b\u540e\u80fd\u5b66\u5230\u7684'), ), ]

[ "fzk466569" ]

fzk466569

637c9052ec6cfa09517634c6b68099e9a6470ff8

7a8fcae483d18e87481443f4476d56b5180459e6

/statemachine/registry.py

c1632ebc937664e2f22b410a9f4334a197abc83f

[ "MIT" ]

permissive

Gariagi/python-statemachine

63c67696f57eeda75054df399999bfe7fb21c783

7dddc714752ef56dd9e54fe246c0050f40c0ad2d

refs/heads/develop

2020-03-09T01:04:15.124145

2018-04-29T17:53:36

128,504,334

0

MIT

2018-04-29T17:53:37

2018-04-07T06:56:05

Python

UTF-8

Python

false

1,206

py

# coding: utf-8 _REGISTRY = {} _initialized = False def register(cls): _REGISTRY[cls.__name__] = cls return cls def get_machine_cls(name): init_registry() return _REGISTRY[name] def init_registry(): global _initialized if not _initialized: load_modules(['statemachine', 'statemachines']) _initialized = True def load_modules(modules=None): try: import django # noqa except ImportError: # Not a django project return try: # pragma: no cover from django.utils.module_loading import autodiscover_modules except ImportError: # pragma: no cover # Django 1.6 compat to provide `autodiscover_modules` def autodiscover_modules(module_name): from django.conf import settings from django.utils.importlib import import_module for app in settings.INSTALLED_APPS: # Attempt to import the app's `module_name`. try: import_module('{app}.{module}'.format(app=app, module=module_name)) except Exception: pass for module in modules: autodiscover_modules(module)

[ "fgmacedo@gmail.com" ]

fgmacedo@gmail.com

14f178cebd12871b2e29d5b54a2c6d71d47622a4

3a1bae5b4a49c8f3050f37c3875a5a1dfd6f8316

/bookzen_flask/bookzen.py

7c91da763601eb07dd5749b3d1277ba732dc04ae

[]

no_license

meomap/bookzen

9e86f5d3e63bfbd1e87fae41465115d27ebdd321

e764dea45c7a5174b728d225ef2aaef3ed09bc9b

refs/heads/master

2021-01-19T13:25:23.704102

2017-02-17T01:52:26

null

0

null

UTF-8

Python

false

3,555

py

# -*- coding: iso-8859-15 -*- import json from email.header import Header from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText from email.utils import formataddr import smtplib from flask import Flask, render_template, redirect, url_for from flask_mongoengine import MongoEngine from flask_wtf import FlaskForm as Form from wtforms import StringField, SubmitField, TextAreaField from wtforms.validators import DataRequired, Email app = Flask(__name__) app.config.from_pyfile('settings.py') db = MongoEngine(app) class Books(db.Document): name = db.StringField() name_unidecode = db.StringField() author = db.StringField() description = db.StringField() image_uri = db.StringField() price = db.StringField() url = db.StringField() spider = db.StringField() server = db.StringField() project = db.StringField() date = db.DateTimeField() meta = {'indexes': [ {'fields': ['$name', "$name_unidecode"]}]} class SearchForm(Form): flash_msg = "Please search something so we can serve you" search = StringField("Search book\'s title", validators=[DataRequired(flash_msg)]) submit = SubmitField() class ContactForm(Form): flash_msg = "Oops, look like you forget to fill this field." name = StringField("Name", [DataRequired(flash_msg)]) email = StringField("Email", [Email(flash_msg)]) subject = StringField("Subject", [DataRequired(flash_msg)]) message = TextAreaField("Message", [DataRequired(flash_msg)]) submit = SubmitField() def str_handler(string): if isinstance(string, str): return json.dumps(string) elif isinstance(string, unicode): return '''\"{0}\"'''.format(string.encode('utf-8')) @app.route('/', methods=["GET", "POST"]) def index(): form = SearchForm() if form.validate_on_submit(): keyword = form.search.data return redirect(url_for('search', keyword=keyword)) else: return render_template('index.html', form=form) @app.route('/search/<keyword>') def search(keyword): form = SearchForm() if form.validate_on_submit(): keyword = form.search.data return redirect(url_for('search', keyword=keyword)) query = Books.objects.search_text(str_handler(keyword)) books = [dict(json.loads(i.to_json())) for i in query.order_by('+price')] if books: return render_template('results.html', form=form, books=books) else: return render_template('not_found.html', form=form) @app.route('/contact/', methods=["GET", "POST"]) def contact(): form = ContactForm() if form.validate_on_submit(): msg = MIMEMultipart() fromaddr = form.email.data toaddr = app.config["MY_EMAIL_ADDRESS"] msg['subject'] = form.subject.data msg['from'] = formataddr((str(Header(form.name.data, 'utf-8')), fromaddr)) msg['to'] = toaddr msg['reply-to'] = fromaddr body = form.message.data msg.attach(MIMEText(body, 'plain', 'utf-8')) server = smtplib.SMTP('smtp.gmail.com', 587) server.starttls() server.login(app.config['EMAIL_ACCOUNT'], app.config["EMAIL_PASSWORD"]) text = msg.as_string() server.sendmail(fromaddr, toaddr, text) server.quit() return render_template('thanks.html') else: return render_template('contact.html', form=form) @app.route('/about/') def about(): return render_template('about.html') if __name__ == "__main__": app.run(host='0.0.0.0', debug=True)

[ "tu0703@gmail.com" ]

tu0703@gmail.com

0f260f1dbdd72e3b8c0677de922da98c7967e15b

bb7ebdd990d3265a585700e1083b3e916842aec6

/scrapper/article.py

c5d9ffb192e8310d3615e63aaf29c76355f4090d

[]

no_license

c24b/clean_crawtext

2c2a6d6292f5bb00afa45ebb28ba16bf2f0a229e

f1dc20298da418680b1b96dd0468846cbf09a112

refs/heads/master

2020-05-18T00:58:55.308025

2014-08-19T11:50:52

null

0

null

UTF-8

Python

false

3,889

py

#!/usr/bin/env python # -*- coding: UTF-8 -*- from copy import deepcopy from parsers import Parser from cleaners import StandardDocumentCleaner from formatters import StandardOutputFormatter from extractors import StandardContentExtractor import datetime from BeautifulSoup import BeautifulSoup as bs class Extractor(object): '''Generic Extractor''' @staticmethod def run( url, raw_html,type, lang="en"): if type == "article": content = Article(url, raw_html, lang) elif type == "defaut": raise NotImplementedError else: raise NotImplementedError return content.get() class Article(Extractor): '''Article''' def __init__(self, url, raw_html, lang): self.status = True self.url = url self.lang = lang # title of the article self.title = None #text self.article = u"" self.cleaned_text = u"" # meta self.meta_description = u"" self.meta_lang = u"" self.meta_favicon = u"" self.meta_keywords = u"" #link and domain self.canonical_link = u"" self.domain = u"" # cleaned text self.top_node = None self.tags = set() self.final_url = url self.raw_html = raw_html # the lxml Document object self.parser = Parser() self.raw_doc = u"" self.publish_date = None self.additional_data = {} self.links = [] self.outlinks = [] self.inlinks = [] self.start_date = datetime.datetime.today() def get(self): try: self.doc = self.parser.fromstring(self.raw_html) #init extractor method extractor = StandardContentExtractor(self,"en") # init the document cleaner cleaner = StandardDocumentCleaner(self) # init the output formatter formatter = StandardOutputFormatter(self, stopwords_class="en") #doc #self.doc = doc self.raw_doc = deepcopy(self.raw_html) self.title = extractor.get_title() #self.title = self.title #meta self.meta_lang = extractor.get_meta_lang() #self.meta_favicon = extractor.get_favicon() #self.meta_description = extractor.get_meta_description() #self.meta_description = self.meta_description.decode("utf-8") #self.meta_keywords = extractor.get_meta_keywords() #domain and url self.canonical_link = extractor.get_canonical_link() self.domain = extractor.get_domain() #~ #~ #tag #self.tags = extractor.extract_tags() #~ #text self.doc = cleaner.clean() self.top_node = extractor.calculate_best_node() if self.top_node is not None: # post cleanup self.top_node = extractor.post_cleanup(self.top_node) # clean_text #self.cleaned_text = formatter.get_formatted_text() #self.content = self.content.decode("utf-8") self.links = extractor.get_links() self.outlinks = extractor.get_outlinks() try: self.content = formatter.get_formatted_text() except Exception as e: self.content = bs(self.raw_html).text #self.inlinks, self.inlinks_err = extractor.get_outlinks(self.links) # TODO # self.article.publish_date = self.extractor.get_pub_date(doc) # self.article.additional_data = self.extractor.more(doc) return self except Exception as e: self.status = False self.logs = { "url": self.url, "scope": "article extraction", "msg": e.args, "status": False, "code": -2 } return self def repr(self): return { "url": self.canonical_link, "domain": self.domain, "title": self.title, "content": self.content, "description": self.meta_description, "outlinks": self.outlinks, "crawl_date": self.start_date, "raw_html": self.raw_html, } def is_relevant(self, query): self.content = {"title":unicode(self.title), "content": unicode(self.content)} if query.match(self.content) is False: self.status = {"url":self.url, "code": -1, "msg": "Not Relevant","status": False, "title": self.title, "content": self.content} return False else: return True

[ "4barbes@gmail.com" ]

4barbes@gmail.com

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# -*- coding: utf-8 -*- # Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # Generated code. DO NOT EDIT! # # Snippet for ListDataLabelingJobs # NOTE: This snippet has been automatically generated for illustrative purposes only. # It may require modifications to work in your environment. # To install the latest published package dependency, execute the following: # python3 -m pip install google-cloud-aiplatform # [START aiplatform_generated_aiplatform_v1_JobService_ListDataLabelingJobs_async] from google.cloud import aiplatform_v1 async def sample_list_data_labeling_jobs(): """Snippet for list_data_labeling_jobs""" # Create a client client = aiplatform_v1.JobServiceAsyncClient() # Initialize request argument(s) request = aiplatform_v1.ListDataLabelingJobsRequest( parent="projects/{project}/locations/{location}", ) # Make the request page_result = client.list_data_labeling_jobs(request=request) async for response in page_result: print(response) # [END aiplatform_generated_aiplatform_v1_JobService_ListDataLabelingJobs_async]

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# Problem 395 # Medium # Asked by Robinhood # # Given an array of strings, group anagrams together. # # For example, given the following array: # # ['eat', 'ate', 'apt', 'pat', 'tea', 'now'] # # Return: # # [['eat', 'ate', 'tea'], # ['apt', 'pat'], # ['now']] #

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zzerii/save_your_ingredients

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# Generated by Django 3.1.3 on 2020-11-13 05:52 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Ingredient', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('info', models.CharField(max_length=255)), ('trim', models.CharField(max_length=255)), ], ), ]

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jinsoo941010@naver.com

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superstar54/xcp2k

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2021-11-11T21:17:30.292500

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from xcp2k.inputsection import InputSection from xcp2k.classes._each591 import _each591 class _guess_vectors1(InputSection): def __init__(self): InputSection.__init__(self) self.Section_parameters = None self.Add_last = None self.Common_iteration_levels = None self.Filename = None self.Log_print_key = None self.EACH = _each591() self._name = "GUESS_VECTORS" self._keywords = {'Add_last': 'ADD_LAST', 'Common_iteration_levels': 'COMMON_ITERATION_LEVELS', 'Filename': 'FILENAME', 'Log_print_key': 'LOG_PRINT_KEY'} self._subsections = {'EACH': 'EACH'} self._attributes = ['Section_parameters']

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xingwang1991@gmail.com

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/software/qt_examples/src/pyqt-official/webkit/formextractor/ui_formextractor.py

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# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'formextractor.ui' # # Created: Tue May 14 17:59:08 2013 # by: PyQt5 UI code generator 5.0-snapshot-b0831183bf83 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_Form(object): def setupUi(self, Form): Form.setObjectName("Form") Form.resize(680, 218) self.horizontalLayout = QtWidgets.QHBoxLayout(Form) self.horizontalLayout.setObjectName("horizontalLayout") self.webFormGroupBox = QtWidgets.QGroupBox(Form) self.webFormGroupBox.setObjectName("webFormGroupBox") self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.webFormGroupBox) self.verticalLayout_2.setObjectName("verticalLayout_2") self.verticalLayout = QtWidgets.QVBoxLayout() self.verticalLayout.setObjectName("verticalLayout") self.webView = QtWebKitWidgets.QWebView(self.webFormGroupBox) self.webView.setMinimumSize(QtCore.QSize(200, 150)) self.webView.setMaximumSize(QtCore.QSize(400, 16777215)) self.webView.setUrl(QtCore.QUrl("about:blank")) self.webView.setObjectName("webView") self.verticalLayout.addWidget(self.webView) self.verticalLayout_2.addLayout(self.verticalLayout) self.horizontalLayout.addWidget(self.webFormGroupBox) spacerItem = QtWidgets.QSpacerItem(28, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout.addItem(spacerItem) self.dataGroupBox = QtWidgets.QGroupBox(Form) self.dataGroupBox.setObjectName("dataGroupBox") self.verticalLayout_3 = QtWidgets.QVBoxLayout(self.dataGroupBox) self.verticalLayout_3.setObjectName("verticalLayout_3") self.formLayout = QtWidgets.QFormLayout() self.formLayout.setFieldGrowthPolicy(QtWidgets.QFormLayout.FieldsStayAtSizeHint) self.formLayout.setObjectName("formLayout") self.firstNameLabel = QtWidgets.QLabel(self.dataGroupBox) self.firstNameLabel.setObjectName("firstNameLabel") self.formLayout.setWidget(0, QtWidgets.QFormLayout.LabelRole, self.firstNameLabel) self.firstNameEdit = QtWidgets.QLineEdit(self.dataGroupBox) self.firstNameEdit.setReadOnly(True) self.firstNameEdit.setObjectName("firstNameEdit") self.formLayout.setWidget(0, QtWidgets.QFormLayout.FieldRole, self.firstNameEdit) self.lastNameLabel = QtWidgets.QLabel(self.dataGroupBox) self.lastNameLabel.setObjectName("lastNameLabel") self.formLayout.setWidget(1, QtWidgets.QFormLayout.LabelRole, self.lastNameLabel) self.lastNameEdit = QtWidgets.QLineEdit(self.dataGroupBox) self.lastNameEdit.setReadOnly(True) self.lastNameEdit.setObjectName("lastNameEdit") self.formLayout.setWidget(1, QtWidgets.QFormLayout.FieldRole, self.lastNameEdit) self.genderLabel = QtWidgets.QLabel(self.dataGroupBox) self.genderLabel.setObjectName("genderLabel") self.formLayout.setWidget(2, QtWidgets.QFormLayout.LabelRole, self.genderLabel) self.genderEdit = QtWidgets.QLineEdit(self.dataGroupBox) self.genderEdit.setReadOnly(True) self.genderEdit.setObjectName("genderEdit") self.formLayout.setWidget(2, QtWidgets.QFormLayout.FieldRole, self.genderEdit) self.updatesLabel = QtWidgets.QLabel(self.dataGroupBox) self.updatesLabel.setObjectName("updatesLabel") self.formLayout.setWidget(3, QtWidgets.QFormLayout.LabelRole, self.updatesLabel) self.updatesEdit = QtWidgets.QLineEdit(self.dataGroupBox) self.updatesEdit.setReadOnly(True) self.updatesEdit.setObjectName("updatesEdit") self.formLayout.setWidget(3, QtWidgets.QFormLayout.FieldRole, self.updatesEdit) self.verticalLayout_3.addLayout(self.formLayout) spacerItem1 = QtWidgets.QSpacerItem(20, 24, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.verticalLayout_3.addItem(spacerItem1) self.horizontalLayout.addWidget(self.dataGroupBox) self.retranslateUi(Form) QtCore.QMetaObject.connectSlotsByName(Form) def retranslateUi(self, Form): _translate = QtCore.QCoreApplication.translate Form.setWindowTitle(_translate("Form", "Form")) self.webFormGroupBox.setTitle(_translate("Form", "Web Form")) self.dataGroupBox.setTitle(_translate("Form", "Extracted Data")) self.firstNameLabel.setText(_translate("Form", "First Name")) self.lastNameLabel.setText(_translate("Form", "Last Name")) self.genderLabel.setText(_translate("Form", "Gender")) self.updatesLabel.setText(_translate("Form", "Receive Updates")) from PyQt5 import QtWebKitWidgets

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TGTechie01@gmail.com

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veeteeran/holbertonschool-low_level_programming

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#!/usr/bin/python3 if __name__ == "__main__": from sys import argv length = len(argv) if length == 1: print("{:d} arguments.".format(length - 1)) elif length == 2: print("{:d} argument:".format(length - 1)) else: print("{:d} arguments:".format(length - 1)) for i in range(1, length): print("{:d}: {}".format(i, argv[i]))

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/(구현)주사위네개.py

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kih1024/codingStudy

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2022-12-09T04:58:55.264433

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# https://www.acmicpc.net/problem/2484 def dice(): li = sorted(list(map(int, input().split()))) temp = set(li) if len(temp) == 1: return li[0] * 5000 + 50000 elif len(temp) == 2 and li[1] == li[2]: return li[1] * 1000 + 10000 elif len(temp) == 2 and li[1] != li[2]: return (li[1] * 500) + (li[2] * 500) + 2000 elif len(temp) == 3: for i in range(3): if li[i] == li[i + 1]: return li[i] * 100 + 1000 else: return li[-1] * 100 n = int(input()) # money = [] # for i in range(n): # li = sorted(list(map(int, input().split()))) # money.append(dice()) # print(max(money)) print(max(dice() for i in range(n)))

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rladlsgh654@naver.com

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/mini_build.py

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samuelcolvin/donkey-simple-old

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2021-05-28T19:49:45.269978

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from DonkeySimple.DS.download import download_libraries import os, re lib_static_dir = os.path.join('DonkeySimple', 'WebInterface', 'static', 'libs') libs_json_path = 'static_libraries.json' try: download_libraries(libs_json_path, lib_static_dir) except Exception, e: print 'ERROR: %s' % str(e) print 'Problem downloading libraries, you may have problems with internet connection.\n\n' print 'generating long_descriptions docs for PyPi...' import pandoc pandoc.core.PANDOC_PATH = '/usr/bin/pandoc' doc = pandoc.Document() readme_file = 'README.md' doc.markdown = open(readme_file, 'r').read() docs_file = 'DonkeySimple/docs.txt' open(docs_file,'w').write(doc.rst) print '%s converted to rst and written to %s' % (readme_file, docs_file) print 'changing version number' setup_text = open('setup.py','r').read() s=re.search("version='(.+?)'", setup_text) v = s.groups()[0] print 'setting version to: %s' % v init_file = 'DonkeySimple/__init__.py' init_text = "__version__ = 'v%s'\n" % v open(init_file,'w').write(init_text)

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s@muelcolvin.com

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/schema/predict/instance/google/cloud/aiplatform/v1beta1/schema/predict/instance_v1beta1/types/image_classification.py

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refs/heads/main

2023-08-03T06:14:50.689185

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# -*- coding: utf-8 -*- # Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import proto # type: ignore __protobuf__ = proto.module( package='google.cloud.aiplatform.v1beta1.schema.predict.instance', manifest={ 'ImageClassificationPredictionInstance', }, ) class ImageClassificationPredictionInstance(proto.Message): r"""Prediction input format for Image Classification. Attributes: content (str): The image bytes or Cloud Storage URI to make the prediction on. mime_type (str): The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon """ content = proto.Field( proto.STRING, number=1, ) mime_type = proto.Field( proto.STRING, number=2, ) __all__ = tuple(sorted(__protobuf__.manifest))

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#!/usr/bin/python # # Copyright 2014 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. """This example updates the display name of the custom targeting values belonging to a custom targeting key. To determine which custom targeting keys exist, run get_all_custom_targeting_keys_and_values.py.""" __author__ = ('Nicholas Chen', 'Joseph DiLallo') # Import appropriate modules from the client library. from googleads import dfp CUSTOM_TARGETING_KEY_ID = 'INSERT_CUSTOM_TARGETING_KEY_ID_HERE' def main(client, key_id): # Initialize appropriate service. custom_targeting_service = client.GetService( 'CustomTargetingService', version='v201408') values = [{ 'key': 'keyId', 'value': { 'xsi_type': 'NumberValue', 'value': key_id } }] query = 'WHERE customTargetingKeyId = :keyId' statement = dfp.FilterStatement(query, values) while True: # Get custom targeting values by statement. response = custom_targeting_service.getCustomTargetingValuesByStatement( statement.ToStatement()) # Update each local custom targeting value object by changing its name. if 'results' in response: updated_values = [] for value in response['results']: if not value['displayName']: value['displayName'] = value['name'] value['displayName'] += ' (Deprecated)' updated_values.append(value) values = custom_targeting_service.updateCustomTargetingValues( updated_values) # Display results. for value in values: print(('Custom targeting value with id \'%s\', name \'%s\', and display' ' name \'%s\' was updated.' % (value['id'], value['name'], value['displayName']))) statement.offset += dfp.SUGGESTED_PAGE_LIMIT else: break if response['totalResultSetSize'] == 0: print('No custom targeting values were updated.') if __name__ == '__main__': # Initialize client object. dfp_client = dfp.DfpClient.LoadFromStorage() main(dfp_client, CUSTOM_TARGETING_KEY_ID)

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noelle@makermedia.com

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pjot/advent-of-code

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def parse_file(filename): with open(filename) as f: code = f.readline() ints = code.split(',') program = [int(i) for i in ints] return program def parse_instruction(instruction): full_instruction = '{:05d}'.format(instruction) return ( instruction % 100, int(full_instruction[2]), int(full_instruction[1]), int(full_instruction[0]), ) class Computer: def __init__(self, program, inputs): self.position = 0 self.base = 0 self.inputs = inputs self.tape = {k: v for k, v in enumerate(program)} self.output = None def iterate_once(self=None): self.iterate() return self.output def run_to_output(self): done = False outputs = [] while not done: done = self.iterate() if not done: outputs.append(self.output) return outputs def read(self, delta=0, mode=1): if mode == 2: return self.tape.get( self.base + self.tape.get(self.position + delta, 0), 0 ) if mode == 1: return self.tape.get(self.position + delta, 0) if mode == 0: return self.tape.get( self.tape.get(self.position + delta, 0), 0 ) def write(self, delta, value, mode): if mode == 2: key = self.base + self.tape[self.position + delta] if mode == 1: key = self.position + delta if mode == 0: key = self.tape[self.position + delta] self.tape[key] = value def iterate(self): while True: instruction = self.read() op_code, mode_a, mode_b, mode_c = parse_instruction(instruction) if op_code == 99: return True if op_code == 1: a = self.read(1, mode_a) b = self.read(2, mode_b) self.write(3, a + b, mode_c) self.position += 4 if op_code == 2: a = self.read(1, mode_a) b = self.read(2, mode_b) self.write(3, a * b, mode_c) self.position += 4 if op_code == 3: if self.inputs: self.write(1, self.inputs.pop(0), mode_a) self.position += 2 else: return False if op_code == 4: self.output = self.read(1, mode_a) self.position += 2 return False if op_code == 5: a = self.read(1, mode_a) b = self.read(2, mode_b) if a != 0: self.position = b else: self.position += 3 if op_code == 6: a = self.read(1, mode_a) b = self.read(2, mode_b) if a == 0: self.position = b else: self.position += 3 if op_code == 7: a = self.read(1, mode_a) b = self.read(2, mode_b) value = 1 if a < b else 0 self.write(3, value, mode_c) self.position += 4 if op_code == 8: a = self.read(1, mode_a) b = self.read(2, mode_b) value = 1 if a == b else 0 self.write(3, value, mode_c) self.position += 4 if op_code == 9: a = self.read(1, mode_a) self.base += a self.position += 2

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1,686

py

""" This script is used as part of the "make release" command used as part of building an rpm of this entire virtualenv. The rpm building process compiles all *.py files found anywhere in the source tree, independent of whether or not these would actually be used. It finds some Python files which aren't meant for the specific Python version being build this way and would abort the build process. We therefor specifically remove files from our site-packages directory, which aren't meant for the current Python version and include incompatible Python syntax. """ from compileall import compile_dir from distutils.sysconfig import get_python_lib import os import os.path import sys # files excluded when run under Python 2.x PYTHON_2_INCOMPATIBLE = [ 'gunicorn/workers/_gaiohttp.py', 'linecache2/tests/inspect_fodder2.py', ] # files excluded when run under Python 3.x PYTHON_3_INCOMPATIBLE = [ 'gevent/_util_py2.py', ] def compile_files(path): return compile_dir(path, maxlevels=50, quiet=True) def remove_incompatible_files(path): excludes = [] if sys.version_info < (3, 0): excludes.extend(PYTHON_2_INCOMPATIBLE) if sys.version_info >= (3, 0): excludes.extend(PYTHON_3_INCOMPATIBLE) for e in excludes: fp = os.path.join(path, e) for extension in ('', 'c', 'o'): name = fp + extension if os.path.exists(name): print('Removing file %s with incompatible syntax.' % name) os.remove(name) def main(): sp = get_python_lib() remove_incompatible_files(sp) status = compile_files(sp) sys.exit(not status) if __name__ == '__main__': main()

[ "hanno@hannosch.eu" ]

hanno@hannosch.eu

f745deca3f8bab4ea141b85d67a953beab121496

025fa245d4cbffdaa422287ed2f31c4d0442ee28

/orders/api/serializers.py

15a4a1cf958d28696d037af645fde921fd646007

[ "MIT" ]

permissive

elcolie/zero-to-deploy

01f346ca50b8ccb271faef23934abe6a487baca6

6191a33ef55af7c550c0e529a4e373bfe40bc014

refs/heads/master

2022-02-08T23:22:17.008555

2018-06-15T19:39:06

137,083,690

0

MIT

2022-01-21T19:35:33

2018-06-12T14:28:01

Python

UTF-8

Python

false

1,228

py

from rest_framework import serializers from menus.models import Menu from order_items.api.serializers import ShortItemSerializer from order_items.models import OrderItem from orders.models import Order class OrderSerializer(serializers.ModelSerializer): url = serializers.HyperlinkedIdentityField(view_name='api:order-detail') customer = serializers.CurrentUserDefault() order_items = ShortItemSerializer(read_only=True, many=True) menus = serializers.PrimaryKeyRelatedField(queryset=Menu.objects.all(), many=True, write_only=True) class Meta: model = Order fields = [ 'url', 'customer', 'order_items', 'menus', 'sum', 'created_at', 'updated_at', ] extra_kwargs = { 'created_at': {'read_only': True}, 'updated_at': {'read_only': True}, } def create(self, validated_data): menus = validated_data.pop('menus') order = Order.objects.create(customer=validated_data.get('customer')) for item in menus: OrderItem.objects.bulk_create([ OrderItem(order=order, menu=item) ]) return order

[ "sarit@elcolie.com" ]

sarit@elcolie.com

33d9a5f14e08e91b0a36cea7796270daf9f6d3fc

71f19c14de97846193972830fbc9a4ec972d0ca9

/website/management/commands/tweet_something.py

9c69a942adf0593825c1b90f2c1043deb803ba42

[]

no_license

wbt/govtrack.us-web

87790050aaba83ca6cca16e26ec796603317e7da

c94c0dfdc809ad506a54108802a2328cc26ca97d

refs/heads/master

2021-01-25T06:25:24.943845

2017-07-26T13:55:01

93,572,164

0

null

2017-09-24T03:54:30

2017-06-06T23:15:59

Python

UTF-8

Python

false

7,400

py

#;encoding=utf8 from django.db.models import F from django.core.management.base import BaseCommand, CommandError from django.conf import settings from django.utils import timezone from django.template.defaultfilters import truncatechars from collections import defaultdict import json, os, sys from datetime import timedelta class OkITweetedSomething(Exception): pass class Command(BaseCommand): help = 'Tweets something interesting as @GovTrack.' tweets_storage_fn = 'data/misc/tweets.json' def handle(self, *args, **options): # Construct client. import twitter self.twitter = twitter.Api(consumer_key=settings.TWITTER_OAUTH_TOKEN, consumer_secret=settings.TWITTER_OAUTH_TOKEN_SECRET, access_token_key=settings.TWITTER_ACCESS_TOKEN, access_token_secret=settings.TWITTER_ACCESS_TOKEN_SECRET) # What have we tweeted about before? Let's not tweet # it again. self.load_previous_tweets() try: # Send out a tweet. self.tweet_something() except OkITweetedSomething: pass finally: # Save the updated cache of previous tweets for next time. self.save_previous_tweets() def load_previous_tweets(self): if not os.path.exists(self.tweets_storage_fn): self.previous_tweets = { } else: self.previous_tweets = json.loads(open(self.tweets_storage_fn).read()) def save_previous_tweets(self): with open(self.tweets_storage_fn, 'w') as output: json.dump(self.previous_tweets, output, sort_keys=True, indent=2) ### def tweet_something(self): # Find something interesting to tweet! self.tweet_new_signed_laws_yday() self.tweet_votes_yday(True) self.tweet_new_bills_yday() self.tweet_coming_up() self.tweet_a_bill_action() self.tweet_votes_yday(False) ### def post_tweet(self, key, text, url): if key in self.previous_tweets: return text = truncatechars(text, 140-1-23-3) + " " + url text += u" 🏛️" # there's a civics building emoji there indicating to followers this is an automated tweet? the emoji is two characters (plus a space before it) as Twitter sees it if "TEST" in os.environ: # Don't tweet. Just print and exit. print key, text sys.exit(1) tweet = self.twitter.PostUpdate(text, verify_status_length=False) # it does not do link shortening test correctly self.previous_tweets[key] = { "text": text, "when": timezone.now().isoformat(), "tweet": tweet.AsDict(), } #print(json.dumps(self.previous_tweets[key], indent=2)) raise OkITweetedSomething() ### def tweet_new_signed_laws_yday(self): # Because of possible data delays, don't tweet until the afternoon. if timezone.now().hour < 12: return # Tweet count of new laws enacted yesterday. from bill.models import Bill, BillStatus count = Bill.objects.filter( current_status_date__gte=timezone.now().date()-timedelta(days=1), current_status_date__lt=timezone.now().date(), current_status=BillStatus.enacted_signed, ).count() if count == 0: return self.post_tweet( "%s:newlaws" % timezone.now().date().isoformat(), "%d new law%s signed by the President yesterday." % ( count, "s were" if count != 1 else " was", ), "https://www.govtrack.us/congress/bills/browse#current_status[]=28&sort=-current_status_date") def tweet_votes_yday(self, if_major): # Tweet count of votes yesterday, by vote type if there were any major votes. from vote.models import Vote, VoteCategory votes = Vote.objects.filter( created__gte=timezone.now().date()-timedelta(days=1), created__lt=timezone.now().date(), ) if votes.count() == 0: return has_major = len([v for v in votes if v.is_major]) > 0 if not has_major and if_major: return if not has_major: count = votes.count() msg = "%d minor vote%s held by Congress yesterday." % ( count, "s were" if count != 1 else " was", ) else: counts = defaultdict(lambda : 0) for v in votes: counts[v.category] += 1 counts = list(counts.items()) counts.sort(key = lambda kv : (VoteCategory.by_value(kv[0]).importance, -kv[1])) msg = "Votes held by Congress yesterday: " + ", ".join( str(value) + " on " + VoteCategory.by_value(key).label for key, value in counts ) self.post_tweet( "%s:votes" % timezone.now().date().isoformat(), msg, "https://www.govtrack.us/congress/votes") def tweet_new_bills_yday(self): # Because of possible data delays, don't tweet until the afternoon. if timezone.now().hour < 12: return # Tweet count of new bills introduced yesterday. from bill.models import Bill, BillStatus count = Bill.objects.filter( introduced_date__gte=timezone.now().date()-timedelta(days=1), introduced_date__lt=timezone.now().date(), ).count() if count == 0: return self.post_tweet( "%s:newbills" % timezone.now().date().isoformat(), "%d bill%s introduced in Congress yesterday." % ( count, "s were" if count != 1 else " was", ), "https://www.govtrack.us/congress/bills/browse#sort=-introduced_date") def tweet_coming_up(self): # legislation posted as coming up within the last day from bill.models import Bill dhg_bills = Bill.objects.filter(docs_house_gov_postdate__gt=timezone.now().date()-timedelta(days=1)).filter(docs_house_gov_postdate__gt=F('current_status_date')) sfs_bills = Bill.objects.filter(senate_floor_schedule_postdate__gt=timezone.now().date()-timedelta(days=1)).filter(senate_floor_schedule_postdate__gt=F('current_status_date')) coming_up = list(dhg_bills | sfs_bills) coming_up.sort(key = lambda b : b.docs_house_gov_postdate if (b.docs_house_gov_postdate and (not b.senate_floor_schedule_postdate or b.senate_floor_schedule_postdate < b.docs_house_gov_postdate)) else b.senate_floor_schedule_postdate) for bill in coming_up: text = "Coming up: " + bill.display_number if bill.sponsor and bill.sponsor.twitterid: text += " by @" + bill.sponsor.twitterid text += ": " + bill.title_no_number self.post_tweet( "%s:comingup:%s" % (timezone.now().date().isoformat(), bill.congressproject_id), text, "https://www.govtrack.us" + bill.get_absolute_url()) def tweet_a_bill_action(self): # Tweet an interesting action on a bill. from bill.models import Bill, BillStatus from bill.status import get_bill_really_short_status_string bills = list(Bill.objects.filter( current_status_date__gte=timezone.now().date()-timedelta(days=2), current_status_date__lt=timezone.now().date(), ).exclude( current_status=BillStatus.introduced, )) if len(bills) == 0: return # Choose bill with the most salient status, breaking ties with the highest proscore. bills.sort(key = lambda b : (BillStatus.by_value(b.current_status).sort_order, b.proscore()), reverse=True) for bill in bills: status = BillStatus.by_value(bill.current_status).xml_code if "Providing for consideration" in bill.title: continue text = get_bill_really_short_status_string(status) if text == "": continue bill_number = bill.display_number if bill.sponsor and bill.sponsor.twitterid: bill_number += " by @" + bill.sponsor.twitterid text = text % (bill_number, u"y’day") text += " " + bill.title_no_number self.post_tweet( bill.current_status_date.isoformat() + ":bill:%s:status:%s" % (bill.congressproject_id, status), text, "https://www.govtrack.us" + bill.get_absolute_url())

[ "jt@occams.info" ]

jt@occams.info

4a34314cf3ab3799f0e9db22f7bf9934c45a1f33

d0ff9af885dc01de43ae7bdd2d26d6370c7b7ab5

/unsup_vvs/neural_fit/brainscore_mask/compute_rdms_from_activations.py

6d62b4160899f47a41da16e2251033e1f396d3d0

[]

no_license

augix/unsup_vvs

a09f89c7d002006f59ffbe223c9469e959949e04

168ed0d068d27b7a7ca1dd5c1ebc28fbe84f8c7c

refs/heads/master

2023-07-17T05:55:27.630844

2021-06-24T01:27:28

null

0

null

UTF-8

Python

false

1,860

py

import pickle import argparse import os import sys import pdb from tqdm import tqdm import numpy as np RESULT_CACHING_DIR = '/mnt/fs4/chengxuz/v4it_temp_results/.result_caching' DEFAULT_SAVE_DIR = os.path.join(RESULT_CACHING_DIR, 'computed_rdms') ACTIVATION_DIR = os.path.join( RESULT_CACHING_DIR, 'model_tools.activations.core.ActivationsExtractorHelper._from_paths_stored') ACTIVATION_PATTERN = 'activations' def get_parser(): parser = argparse.ArgumentParser( description='The script to compute RDMs from activations') parser.add_argument( '--save_dir', type=str, default=DEFAULT_SAVE_DIR, action='store', help='Directory for saving rdm results') return parser def get_activation_pkls(): all_pkls = os.listdir(ACTIVATION_DIR) all_pkls = list(filter(lambda name: ACTIVATION_PATTERN in name, all_pkls)) all_pkls = sorted(all_pkls) all_pkls = [os.path.join(ACTIVATION_DIR, each_pkl) for each_pkl in all_pkls] return all_pkls def main(): parser = get_parser() args = parser.parse_args() all_pkls = get_activation_pkls() os.system('mkdir -p ' + args.save_dir) for each_pkl in tqdm(all_pkls): save_path = os.path.join( args.save_dir, os.path.basename(each_pkl)) if os.path.exists(save_path): continue activations = pickle.load(open(each_pkl, 'rb'))['data'] all_layers = np.unique(activations.layer) act_arr = np.asarray(activations) layer_names = np.asarray(activations.layer) _rdms = {} for each_layer in all_layers: _resp = act_arr[:, layer_names == each_layer] _rdms[each_layer] = np.corrcoef(_resp) pickle.dump(_rdms, open(save_path, 'wb')) if __name__ == '__main__': main()

[ "chengxuz@node07-ccncluster.stanford.edu" ]

chengxuz@node07-ccncluster.stanford.edu

8a31fb2658e068c346166523f70684bc6035c3fc

410f0d66049ca881dfdeb9b7f784bd70b1c3f6e7

/bootea/bootea/pipelines.py

1bcd7524443c973b2ed7217b2a7ddcccda6d3f42

[]

no_license

ans2human/Scrappers

1bdf5a1a4a34752c58fb18d45ac01e3cb54b5fe1

cb2183d25a8af08284f2a6c1311b8da24c720b96

refs/heads/master

2020-03-19T20:41:01.244911

2018-06-11T11:27:17

136,911,832

0

null

UTF-8

Python

false

2,934

py

from scrapy import log from twisted.enterprise import adbapi import time import sys; sys.path.append("/users/user/appdata/local/programs/python/python36-32/lib/site-packages") import MySQLdb.cursors from bootea.items import test class MySQLStorePipeline(object): def __init__(self): print ('init') self.dbpool = adbapi.ConnectionPool('MySQLdb', db = 'usalogic_testdb', user='root', passwd='1234', cursorclass=MySQLdb.cursors.DictCursor, charset='utf8', use_unicode=True) def process_item(self, item, spider): print('process') query = self.dbpool.runInteraction(self._conditional_insert, item) #("""INSERT INTO Example_Movie (title, url, gross, release) VALUES (%s, %s, %s, %s)""", (item['title'].endcode('utf-8'), item['url'].encode('utf-8'), item['gross'].encode('utf-8'), item['release'].encode('utf-8'))) query.addErrback(self.handle_error)#self.conn.commit() return item def _conditional_insert(self, tx, item): print ('conditional insert') #Create record if doesn't exist #all this block run on it's own thread tx.execute("select * from test where producturl = %s", (item['producturl'], )) result = tx.fetchone() if result: log.msg("Item already stored in db: %s" % item, level = log.DEBUG) else: tx.execute("insert into test (producturl, prodprice, prodname) values (%s, %s, %s)", [item['producturl'], item['prodprice'], item['prodname']]) log.msg("Item stored in db: %s" % item, level=log.DEBUG) def handle_error(self, e): print ('handle_error') log.err(e) # from scrapy import log # from twisted.enterprise import adbapi # import time # import sys; sys.path.append("/users/user/appdata/local/programs/python/python36-32/lib/site-packages") # import MySQLdb.cursors # from bootea.items import test # class BooteaPipeline(object): # def __init__(self): # self.dbpool = adbapi.ConnectionPool('MySQLdb', db='usalogic_testdb', # user='root', passwd='1234', cursorclass=MySQLdb.cursors.DictCursor, # charset='utf8', use_unicode=True) # def process_item(self, item, spider): # query = self.dbpool.runInteraction(self._conditional_insert, item) # query.addErrback(self.handle_error) # return item # def _conditional_insert(self, tx, item): # tx.execute("select * from test where producturl = %s", (item['producturl'], )) # result = tx.fetchone() # if result: # log.msg("Item already stored in db: %s" % item, level=log.DEBUG) # else: # tx.execute("insert into test (producturl, prodname, prodprice) values (%s, %s, %s,)", [item['producturl'], item['prodname'], item['prodprice']]) # log.msg("Item stored in db: %s" % item, level=log.DEBUG) # def handle_error(self, e): # log.err(e)

[ "ans2human@gmail.com" ]

ans2human@gmail.com

ecbbe380ee06e59502cd568e0d8911e8ee387e8b

ef72a7df3c39c215dd90ac5e72b164eb9d7da892

/rpg/heroes/exp.py

8580678d1bd1cda8e1e24f9779c8fce251493dcc

[]

no_license

thebmo/messing_around

d49a87fc1ff722428ea67bc710ca99ad287098bd

4cb12e0b224cf7d1f93cb4ae6ff7603619fb7aa9

refs/heads/master

2021-01-13T02:18:50.799898

2015-04-08T01:12:41

28,570,375

0

null

UTF-8

Python

false

1,220

py

exp_to_next_level = [ 0, 29, 87, 174, 304, 499, 792, 1232, 1891, 2880, 4364, 6218, 8534, 11428, 15045, 19114, 23690, 28837, 34627, 41141, 48468, 56711, 65983, 76413, 88147, 101347, 116196, 132901, 151694, 172836, 196621, 223378, 253480, 287344, 325440, 368298, 416512, 470752, 531771, 600417, 677644, 764524, 862263, 960002, 1057741, 1155480, 1253219, 1350958, 1448697, 1546436, 1644175, 1741914, 1839653, 1937392, 2035131, 2132870, 2230609, 2328348, 2426087, 2523826, 2621565, 2719304, 2817043, 2914782, 3012521, 3110260, 3207999, 3305738, 3403477, 3501216, 3598955, 3696694, 3794433, 3892172, 3989911, 4087650, 4185389, 4283128, 4380867, 4478606, 4576345, 4674084, 4771823, 4869562, 4967301, 5065040, 5162779, 5260518, 5358257, 5455996, 5553735, 5651474, 5749213, 5846952, 5944691, 6042430, 6140169, 6237908, 6335647 ]

[ "bmosier@gmail.com" ]

bmosier@gmail.com

3c415b6254a6a1dfd67e5c564bbeeab602bbbac5

c3432a248c8a7a43425c0fe1691557c0936ab380

/Greedy/1744_수묶기*.py

cb76fdcd5d14a3364ec30819632212850e7c8292

[]

no_license

Parkyunhwan/BaekJoon

13cb3af1f45212d7c418ecc4b927f42615b14a74

9a882c568f991c9fed3df45277f091626fcc2c94

refs/heads/master

2022-12-24T21:47:47.052967

2022-12-20T16:16:59

232,264,447

3

0

null

UTF-8

Python

false

670

py

import heapq n = int(input()) sm = 0 plus = [] minus = [] zero = 0 one = 0 for _ in range(n): val = int(input()) if val == 1: one += 1 elif val > 0: heapq.heappush(plus, -val) elif val == 0: zero += 1 else: heapq.heappush(minus, val) if len(plus) % 2: heapq.heappush(plus, -1) if len(minus) % 2: if zero > 0: heapq.heappush(minus, 0) else: heapq.heappush(minus, 1) while plus: val1 = heapq.heappop(plus) val2 = heapq.heappop(plus) sm += (val1 * val2) while minus: val1 = heapq.heappop(minus) val2 = heapq.heappop(minus) sm += (val1 * val2) sm += one print(sm)

[ "pyh8618@gmail.com" ]

pyh8618@gmail.com

3042f2d03444d4ec8ed65c9bcad199f8c3f11f73

163bbb4e0920dedd5941e3edfb2d8706ba75627d

/Code/CodeRecords/2536/60761/235389.py

3dece7a79508610db4ccd9b65cff8208cc2b29f7

[]

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

412

py

airlines=input("") airlines=list(map(str,airlines[2:-2].split("],["))) result=[] result.append("JFK") i=0 while(0<len(airlines)): destination=[] for airline in airlines: if(airline.startswith('"'+result[i])): destination.append(airline[7:-1]) destination.sort() airlines.remove('"'+result[i]+'","'+destination[0]+'"') result.append(destination[0]) i=i+1 print(result)

[ "1069583789@qq.com" ]

1069583789@qq.com

047f80690a5099e9f1505b2dd7da347d7bd2adc1

04ae1836b9bc9d73d244f91b8f7fbf1bbc58ff29

/378/Solution.py

2933a83513c07b54670ecbf4838330642d1675d9

[]

no_license

zhangruochi/leetcode

6f739fde222c298bae1c68236d980bd29c33b1c6

cefa2f08667de4d2973274de3ff29a31a7d25eda

refs/heads/master

2022-07-16T23:40:20.458105

2022-06-02T18:25:35

78,989,941

14

6

null

UTF-8

Python

false

2,165

py

""" Given a n x n matrix where each of the rows and columns are sorted in ascending order, find the kth smallest element in the matrix. Note that it is the kth smallest element in the sorted order, not the kth distinct element. Example: matrix = [ [ 1, 5, 9], [10, 11, 13], [12, 13, 15] ], k = 8, return 13. Note: You may assume k is always valid, 1 ≤ k ≤ n2. """ import heapq class Solution: # time complexity O(nlogn) and space cmplexity is O(n*2) def kthSmallest(self, matrix, k): """ :type matrix: List[List[int]] :type k: int :rtype: int """ lists_ = [] for row in matrix: lists_ += row lists_.sort() return lists_[k-1] # time complexity O(nk) and space cmplexity is O(n) def kthSmallest2(self, matrix, k): """ :type matrix: List[List[int]] :type k: int :rtype: int """ n = len(matrix) pointers = [0] * n count = 0 while True: min_,min_index = float("inf"),-1 for index,point in enumerate(pointers): if point < n: tmp_min = matrix[index][point] if tmp_min < min_: min_ = tmp_min min_index = index pointers[min_index] += 1 count += 1 if count == k: return min_ import heapq class MyItem: def __init__(self,num,row,column): self.num = num self.row = row self.column = column def __lt__(self,item): return self.num < item.num def __repr__(self): return "{}".format(self.num) class Solution: def kthSmallest(self, matrix, k): n = len(matrix) heap = [ MyItem(matrix[0][j],0,j) for j in range(n)] heapq.heapify(heap) for i in range(k): item = heapq.heappop(heap) num, row, column = item.num, item.row, item.column if row+1 < n: heapq.heappush(heap,MyItem(matrix[row+1][column],row+1,column)) return num

[ "zrc720@gmail.com" ]

zrc720@gmail.com

cabf56396409a2b8bbe2bba525dd0a4347f411d5

4af8e73d47535494a25e06d5ac693fdc60fc95f5

/NLP_pytorch/04_pytorch_ignite/main.py

3c143464dd83f6b08e51033562e87b446747ba97

[]

no_license

woosa7/nbcc_projects

4de2f846068bacdc73a6877d26dba93c483b1be3

0e7a30f58e554125d02451ab407f2a19c8c7b5f4

refs/heads/main

2023-06-16T16:19:51.975216

2021-07-16T05:18:53

306,594,548

0

null

UTF-8

Python

false

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py

import argparse import torch import torch.nn as nn import torch.optim as optim from model import ImageClassifier from trainer import Trainer from data_loader import get_loaders def define_argparser(): p = argparse.ArgumentParser() p.add_argument('--model_fn', required=True) p.add_argument('--gpu_id', type=int, default=0 if torch.cuda.is_available() else -1) p.add_argument('--train_ratio', type=float, default=.8) p.add_argument('--batch_size', type=int, default=256) p.add_argument('--n_epochs', type=int, default=10) p.add_argument('--verbose', type=int, default=2) config = p.parse_args() return config def main(config): # Set device based on user defined configuration. device = torch.device('cpu') if config.gpu_id < 0 else torch.device('cuda:%d' % config.gpu_id) train_loader, valid_loader, test_loader = get_loaders(config) # custom dataset & dataloader print("Train:", len(train_loader.dataset)) print("Valid:", len(valid_loader.dataset)) print("Test:", len(test_loader.dataset)) model = ImageClassifier(28**2, 10).to(device) optimizer = optim.Adam(model.parameters()) crit = nn.CrossEntropyLoss() # Using Ignite trainer = Trainer(config) trainer.train(model, crit, optimizer, train_loader, valid_loader) if __name__ == '__main__': config = define_argparser() main(config)

[ "woosa7@gmail.com" ]

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rchenmit/mht_analysis

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## Robert Chen ## Monday 5/12/2014 ## ## read and process BMI file ## ## import datetime as dt import scipy as s ## options input_folder = '../../data/new_data_20140416/Data_20140409/' output_dir = '../../data/new_data_20140416/Data_curated_RC/' pickle_dir = '../analysis_output/pickle/' bool_make_count_matrix_ALL = 0 bool_make_count_matrix_JD_CODE = bool_make_count_matrix_JD_X_RANGE = 0 ## Prepare data, read data filename = input_folder + 'ICD_9_04082014.csv' pd.set_option('display.line_width', 300) df_ICD = pd.read_csv(filename, sep=',') df_ICD['EVENT_DATE'] = pd.to_datetime(df_ICD['EVENT_DATE']) ## read in the ICD excel PheWAS file pheWAS_xls_file = input_folder + 'ICD9-2-PheWAS.xls' xls = pd.ExcelFile(pheWAS_xls_file) df_pheWAS = xls.parse(xls.sheet_names[0]) ## add columns to df_ICD for pheWAS: JD_CODE and JD_X_RANGE df_ICD = df_ICD.merge(df_pheWAS, left_on = 'ICD_9_CODE', right_on='ICD9_CODE', how = 'left' ) ## make a counts matrix if bool_make_count_matrix_ALL: unique_ICD_values = df_ICD.ICD_9_CODE.unique() #ARRAY with unique ICD codes as STRINGS df_ICD_counts = pd.DataFrame(columns=['RUID']) for icd in unique_ICD_values: if isinstance(icd, str) or isinstance(jd, unicode): if s.mod(len(df_ICD_counts.columns), 100) == 0: print len(df_ICD_counts.columns) df_this_icd = df_ICD[df_ICD.ICD_9_CODE==icd][['RUID', 'ICD_9_CODE']] df_this_icd[icd] = df_this_icd.groupby('RUID').transform('count') df_this_icd = df_this_icd.drop( 'ICD_9_CODE', 1) df_this_icd = df_this_icd.drop_duplicates() df_this_icd.replace(np.nan, 0) if len(df_ICD_counts) == 0: df_ICD_counts = df_this_icd.copy() else: df_ICD_counts = pd.merge(df_ICD_counts, df_this_icd, left_on='RUID', right_on='RUID', how='outer') df_ICD_counts.to_csv( output_dir + 'df_ICD_counts.csv', index = False) if bool_make_count_matrix_JD_CODE: unique_JD_values = df_ICD.JD_CODE.unique() #ARRAY with unique ICD codes as STRINGS df_JD_counts = pd.DataFrame(columns=['RUID']) print "JD_Counts, n= " + str(len(unique_JD_values)) for jd in unique_JD_values: if isinstance(jd, str) or isinstance(jd, unicode): if s.mod(len(df_JD_counts.columns), 100) == 0: print len(df_JD_counts.columns) df_this_jd = df_ICD[df_ICD.JD_CODE==jd][['RUID', 'JD_CODE']] df_this_jd[jd] = df_this_jd.groupby('RUID').transform('count') df_this_jd = df_this_jd.drop( 'JD_CODE', 1) df_this_jd = df_this_jd.drop_duplicates() df_this_jd.replace(np.nan, 0) if len(df_JD_counts) == 0: #base case df_JD_counts = df_this_jd.copy() else: df_JD_counts = pd.merge(df_JD_counts, df_this_jd, left_on='RUID', right_on='RUID', how='outer') df_JD_counts.to_csv( output_dir + 'df_JD_counts.csv', index = False) if bool_make_count_matrix_JD_X_RANGE: unique_JD_X_RANGE_values = df_ICD.JD_X_RANGE.unique() #ARRAY with unique ICD codes as STRINGS df_JD_RANGE_counts = pd.DataFrame(columns=['RUID']) print "JD_X_RANGE Counts, n= " + str(len(unique_JD_X_RANGE_values)) for jd in unique_JD_X_RANGE_values: if isinstance(jd, str) or isinstance(jd, unicode): if s.mod(len(df_JD_RANGE_counts.columns), 100) == 0: print len(df_JD_RANGE_counts.columns) df_this_jd = df_ICD[df_ICD.JD_X_RANGE==jd][['RUID', 'JD_X_RANGE']] df_this_jd[jd] = df_this_jd.groupby('RUID').transform('count') df_this_jd = df_this_jd.drop( 'JD_X_RANGE', 1) df_this_jd = df_this_jd.drop_duplicates() df_this_jd.replace(np.nan, 0) if len(df_JD_RANGE_counts) == 0: #base case df_JD_RANGE_counts = df_this_jd.copy() else: df_JD_RANGE_counts = pd.merge(df_JD_RANGE_counts, df_this_jd, left_on='RUID', right_on='RUID', how='outer') df_JD_RANGE_counts.to_csv( output_dir + 'df_JD_RANGE_counts.csv', index = False)

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# $Id: it.py 7119 2011-09-02 13:00:23Z milde $ # Authors: Nicola Larosa <docutils@tekNico.net>; # Lele Gaifax <lele@seldati.it> # Copyright: This module has been placed in the public domain. # Beware: the italian translation of the reStructuredText documentation # at http://docit.bice.dyndns.org/static/ReST, in particular # http://docit.bice.dyndns.org/static/ReST/ref/rst/directives.html, needs # to be synced with the content of this file. """ Italian-language mappings for language-dependent features of reStructuredText. """ __docformat__ = 'reStructuredText' directives = { 'attenzione': 'attention', 'cautela': 'caution', 'code (translation required)': 'code', 'pericolo': 'danger', 'errore': 'error', 'suggerimento': 'hint', 'importante': 'important', 'nota': 'note', 'consiglio': 'tip', 'avvertenza': 'warning', 'ammonizione': 'admonition', 'riquadro': 'sidebar', 'argomento': 'topic', 'blocco-di-righe': 'line-block', 'blocco-interpretato': 'parsed-literal', 'rubrica': 'rubric', 'epigrafe': 'epigraph', 'punti-salienti': 'highlights', 'estratto-evidenziato': 'pull-quote', 'composito': 'compound', 'container (translation required)': 'container', #'questions': 'questions', #'qa': 'questions', #'faq': 'questions', 'tabella': 'table', 'tabella-csv': 'csv-table', 'tabella-elenco': 'list-table', 'meta': 'meta', 'math (translation required)': 'math', #'imagemap': 'imagemap', 'immagine': 'image', 'figura': 'figure', 'includi': 'include', 'grezzo': 'raw', 'sostituisci': 'replace', 'unicode': 'unicode', 'tmp': 'date', 'classe': 'class', 'ruolo': 'role', 'ruolo-predefinito': 'default-role', 'titolo': 'title', 'indice': 'contents', 'contenuti': 'contents', 'seznum': 'sectnum', 'sezioni-autonumerate': 'sectnum', 'annota-riferimenti-esterni': 'target-notes', 'intestazione': 'header', 'piede-pagina': 'footer', #'footnotes': 'footnotes', #'citations': 'citations', 'restructuredtext-test-directive': 'restructuredtext-test-directive'} """Italian name to registered (in directives/__init__.py) directive name mapping.""" roles = { 'abbreviazione': 'abbreviation', 'acronimo': 'acronym', 'code (translation required)': 'code', 'indice': 'index', 'deponente': 'subscript', 'esponente': 'superscript', 'riferimento-titolo': 'title-reference', 'riferimento-pep': 'pep-reference', 'riferimento-rfc': 'rfc-reference', 'enfasi': 'emphasis', 'forte': 'strong', 'letterale': 'literal', 'math (translation required)': 'math', 'riferimento-con-nome': 'named-reference', 'riferimento-anonimo': 'anonymous-reference', 'riferimento-nota': 'footnote-reference', 'riferimento-citazione': 'citation-reference', 'riferimento-sostituzione': 'substitution-reference', 'destinazione': 'target', 'riferimento-uri': 'uri-reference', 'grezzo': 'raw',} """Mapping of Italian role names to canonical role names for interpreted text. """

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from Newfoundland.Object import Object from Beagle import API as BGL class Decorator(Object): textures = BGL.assets.get('KT-forest/animation/decorators') def parse(od,df): x1 = float(od["x"]) y1 = float(od["y"]) x2 = float(od["w"]) y2 = float(od["h"]) cx = (x1+x2) / 2.0 cy = (y1+y2) / 2.0 w = (x2-x1)*0.5 h = (y2-y1)*0.5 if "decorator_id" in od["meta"]: texture = Decorator.textures[od["meta"]["decorator_id"]] else: texture = Decorator.textures[0] if "self_lit" in od["meta"]: if od["meta"]["self_lit"]: light_type = Object.LightTypes.DYNAMIC_TEXTURE_OVERLAY else: light_type = Object.LightTypes.NONE return Decorator( p=[cx,cy], size=[w,h], scale_uv=[1.0,1.0], tick_type = Object.TickTypes.STATIC, visible = True, buftarget = "floor", texture = texture, light_type = light_type )

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def solution(steps): if len(steps) > 10: return False elif steps.count('n') == steps.count('s') and steps.count('e') == steps.count('w'): return True return False

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''' Refer to the detectron2's DatasetCatalog ''' from typing import List class DatasetCatalog(object): """ A catalog that stores information about the datasets and how to obtain them. It contains a mapping from strings (which are names that identify a dataset, e.g. "coco_2014_train") to a function which parses the dataset and returns the samples in the format of `list[dict]`. The returned dicts should be in Detectron2 Dataset format (See DATASETS.md for details) if used with the data loader functionalities in `data/build.py,data/detection_transform.py`. The purpose of having this catalog is to make it easy to choose different datasets, by just using the strings in the config. """ _REGISTERED = {} @staticmethod def register(name, func): """ Args: name (str): the name that identifies a dataset, e.g. "coco_2014_train". func (callable): a callable which takes no arguments and returns a list of dicts. """ assert callable(func), "You must register a function with `DatasetCatalog.register`!" assert name not in DatasetCatalog._REGISTERED, "Dataset '{}' is already registered!".format( name ) DatasetCatalog._REGISTERED[name] = func @staticmethod def get(name, cfg, flag, aug): """ Call the registered function and return its results. Args: name (str): the name that identifies a dataset, e.g. "coco_2014_train". Returns: list[dict]: dataset annotations.0 """ try: f = DatasetCatalog._REGISTERED[name] except KeyError: raise KeyError( "Dataset '{}' is not registered! Available datasets are: {}".format( name, ", ".join(DatasetCatalog._REGISTERED.keys()) ) ) return f(cfg, flag, aug) @staticmethod def list() -> List[str]: """ List all registered datasets. Returns: list[str] """ return list(DatasetCatalog._REGISTERED.keys()) @staticmethod def clear(): """ Remove all registered dataset. """ DatasetCatalog._REGISTERED.clear()

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""" Copyright 2020 The OneFlow Authors. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import os import importlib.machinery def _download_file_from_remote_location(fpath: str, url: str) -> None: pass def _is_remote_location_available() -> bool: return False try: from torch.hub import load_state_dict_from_url except ImportError: from torch.utils.model_zoo import load_url as load_state_dict_from_url def _get_extension_path(lib_name): lib_dir = os.path.dirname(__file__) if os.name == "nt": # Register the main torchvision library location on the default DLL path import ctypes import sys kernel32 = ctypes.WinDLL("kernel32.dll", use_last_error=True) with_load_library_flags = hasattr(kernel32, "AddDllDirectory") prev_error_mode = kernel32.SetErrorMode(0x0001) if with_load_library_flags: kernel32.AddDllDirectory.restype = ctypes.c_void_p if sys.version_info >= (3, 8): os.add_dll_directory(lib_dir) elif with_load_library_flags: res = kernel32.AddDllDirectory(lib_dir) if res is None: err = ctypes.WinError(ctypes.get_last_error()) err.strerror += f' Error adding "{lib_dir}" to the DLL directories.' raise err kernel32.SetErrorMode(prev_error_mode) loader_details = ( importlib.machinery.ExtensionFileLoader, importlib.machinery.EXTENSION_SUFFIXES, ) extfinder = importlib.machinery.FileFinder(lib_dir, loader_details) ext_specs = extfinder.find_spec(lib_name) if ext_specs is None: raise ImportError return ext_specs.origin

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from unittest import TestCase from tests import get_data from pytezos.michelson.converter import build_schema, decode_micheline, encode_micheline, micheline_to_michelson class StorageTestKT1UCoFzRwpQhRg9BWz2QMNwzTud56fCdjSP_babylon(TestCase): @classmethod def setUpClass(cls): cls.maxDiff = None cls.contract = get_data('storage/mainnet/KT1UCoFzRwpQhRg9BWz2QMNwzTud56fCdjSP_babylon.json') def test_storage_encoding_KT1UCoFzRwpQhRg9BWz2QMNwzTud56fCdjSP_babylon(self): type_expr = self.contract['script']['code'][1] val_expr = self.contract['script']['storage'] schema = build_schema(type_expr) decoded = decode_micheline(val_expr, type_expr, schema) actual = encode_micheline(decoded, schema) self.assertEqual(val_expr, actual) def test_storage_schema_KT1UCoFzRwpQhRg9BWz2QMNwzTud56fCdjSP_babylon(self): _ = build_schema(self.contract['script']['code'][0]) def test_storage_format_KT1UCoFzRwpQhRg9BWz2QMNwzTud56fCdjSP_babylon(self): _ = micheline_to_michelson(self.contract['script']['code']) _ = micheline_to_michelson(self.contract['script']['storage'])

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from django.contrib import admin from listenclosely.models import Message, Chat, Agent, Asker admin.site.register(Message) admin.site.register(Chat) admin.site.register(Agent) admin.site.register(Asker)

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# -*- coding: utf-8 -*- """ Asset Management Functionality http://eden.sahanafoundation.org/wiki/BluePrint/Assets """ module = request.controller resourcename = request.function if not settings.has_module(module): raise HTTP(404, body="Module disabled: %s" % module) # ----------------------------------------------------------------------------- def index(): """ Module Home Page """ module_name = settings.modules[module].name_nice response.title = module_name return dict(module_name=module_name) # ----------------------------------------------------------------------------- def create(): """ Redirect to asset/create """ redirect(URL(f="asset", args="create")) # ----------------------------------------------------------------------------- def asset(): """ RESTful CRUD controller """ # Use the item() controller in this module to set options correctly s3db.asset_asset.item_id.comment = S3AddResourceLink(f="item", label=T("Add New Item"), title=T("Item"), tooltip=T("Type the name of an existing catalog item OR Click 'Add New Item' to add an item which is not in the catalog.")) # Defined in Model for use from Multiple Controllers for unified menus return s3db.asset_controller() # ============================================================================= def item(): """ RESTful CRUD controller """ # Filter to just Assets table = s3db.supply_item ctable = s3db.supply_item_category s3.filter = (table.item_category_id == ctable.id) & \ (ctable.can_be_asset == True) # Limit the Categories to just those with vehicles in # - make category mandatory so that filter works field = s3db.supply_item.item_category_id field.requires = IS_ONE_OF(db, "supply_item_category.id", s3db.supply_item_category_represent, sort=True, filterby = "can_be_asset", filter_opts = [True] ) field.comment = S3AddResourceLink(f="item_category", label=T("Add Item Category"), title=T("Item Category"), tooltip=T("Only Categories of type 'Vehicle' will be seen in the dropdown.")) # Defined in the Model for use from Multiple Controllers for unified menus return s3db.supply_item_controller() # ============================================================================= def item_category(): """ RESTful CRUD controller """ table = s3db.supply_item_category # Filter to just Assets s3.filter = (table.can_be_asset == True) # Default to Assets field = table.can_be_asset field.readable = field.writable = False field.default = True return s3_rest_controller("supply", "item_category") # END =========================================================================

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st = set() cant = False prev = "-" for i in range(int(input())): s = input() if (prev!="-" and prev!=s[0]) or s in st: cant = True prev = s[-1] st.add(s) print("YNeos"[cant::2])

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from django.shortcuts import render, reverse, HttpResponseRedirect, HttpResponse from django.views import View from argent_app.models import Room, InRoom from django.contrib.auth import authenticate, login from django.contrib.auth.decorators import login_required from django.contrib.auth.models import User from django.contrib.auth.forms import UserCreationForm class Register(View): def post(self, request): print(request.POST) username, password = request.POST["username"], request.POST["password1"] user = authenticate(username=username, password=password) if user is not None: login(request, user) return HttpResponseRedirect(reverse("room_manage")) else: # if user does not exist, create if User.objects.filter(username=username).exists(): return HttpResponseRedirect(reverse("register"), context={"user_exists": True}) else: user = User.objects.create_user(username, password=password) login(request, user) return HttpResponseRedirect(reverse("room_manage")) def get(self, request): return render(request, "registration/register.html", {"form": UserCreationForm()})

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# ADOBE CONFIDENTIAL # # Copyright 2019 Adobe # All Rights Reserved. # # NOTICE: Adobe permits you to use, modify, and distribute this file in # accordance with the terms of the Adobe license agreement accompanying it. # If you have received this file from a source other than Adobe, # then your use, modification, or distribution of it requires the prior # written permission of Adobe. # import unittest import sd from tests import tools class TestPackage(unittest.TestCase): @classmethod def setUpClass(cls): context = sd.getContext() # Load the reference package cls.sdPackage = tools.loadSDPackage(context, 'test_sdpackage.sbs') # Load some other packages cls.sdPackageTestNewContent = tools.loadSDPackage(context, 'test_write_content.sbs') def testPackagesLoaded(self): self.assertTrue(self.sdPackage, 'Fail to load package') self.assertTrue(self.sdPackageTestNewContent, 'Fail to load package') def test_SDPackage_getChildrenResources(self): # Check Non Recursive mode sbsResourceArray = self.sdPackage.getChildrenResources(False) self.assertEqual(len(sbsResourceArray), 3) # Check Recursive Mode sbsResourceArray = self.sdPackage.getChildrenResources(True) self.assertEqual(len(sbsResourceArray), 5) def test_SDPackage_findResourceFromUrl(self): # Check that a resource of the reference package can be retrieved sbMDLSubGraph = self.sdPackage.findResourceFromUrl('folder0/mdl_sub_graph') self.assertTrue(sbMDLSubGraph) # Check that a resource in another can't be found in the reference package sbPBRGraph = self.sdPackage.findResourceFromUrl('pbr_graph') self.assertFalse(sbPBRGraph) def test_SDPackage_getDependencies(self): pkgDeps = self.sdPackage.getDependencies() self.assertEqual(len(pkgDeps), 1) firstPkgDep = pkgDeps[0] self.assertTrue(len(firstPkgDep.getFilePath())>0) self.assertTrue(firstPkgDep.getPackage()) if __name__ == '__main__': unittest.main()

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# from django.conf import settings from geoip2 import database from geoip2.errors import AddressNotFoundError from apps.warehouse.models import IPStore reader = database.Reader(settings.MAXMIND_CITY_DB) ips = ['99.248.9.54', '173.34.75.225', '70.54.130.204', '67.58.222.87', '70.55.50.230', '76.71.67.164', '70.24.105.229', '64.231.136.194', '135.0.4.175', '173.34.222.226', '174.92.74.247', '99.231.160.194', '184.151.178.201', '70.49.149.23', '66.49.185.244', '70.53.51.197', '174.112.43.253', '173.34.125.63', '64.231.148.82', '66.49.190.181', '173.32.111.198', '70.50.213.134', '50.100.149.203', '99.230.228.92', '184.151.190.55', '24.114.51.122', '174.118.26.209', '73.201.179.235', '99.237.95.19', '76.71.112.4', '76.71.4.24', '76.68.126.170', '174.115.124.199', '99.243.22.198', '69.157.66.143', '99.226.8.59', '70.26.57.62', '184.147.122.233', '216.165.217.88', '99.233.178.15', '72.15.61.181', ] def update_gecode(ip, location): from googlemaps import Client # from django.conf import settings import json ip.latitude = location['latitude'] ip.longitude = location['longitude'] gmaps = Client(key=settings.GOOGLE_GEOCODE_KEY) result = gmaps.reverse_geocode((location['latitude'], location['longitude'] )) ip.geocode = json.dumps(result) print result ip.save() for ip in ips: try: ip2geo = reader.city(ip).raw location = ip2geo['location'] store, created = IPStore.objects.get_or_create(ip=ip) if created: update_gecode(store, location) except AddressNotFoundError as e: print e

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# coding: utf-8 """Database model for entries on the waiting list.""" from __future__ import unicode_literals import datetime from eisitirio.database import db DB = db.DB class Waiting(DB.Model): """Model for entries on the waiting list.""" __tablename__ = "waiting" waiting_since = DB.Column(DB.DateTime(), nullable=False) waiting_for = DB.Column(DB.Integer(), nullable=False) user_id = DB.Column(DB.Integer, DB.ForeignKey("user.object_id"), nullable=False) user = DB.relationship( "User", backref=DB.backref("waiting", lazy="dynamic"), foreign_keys=[user_id] ) def __init__(self, user, waiting_for): self.user = user self.waiting_for = waiting_for self.waiting_since = datetime.datetime.utcnow() def __repr__(self): return "<Waiting: {0} for {1} ticket{2}>".format( self.user.full_name, self.waiting_for, "" if self.waiting_for == 1 else "s" )

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import math import numpy as np import matplotlib matplotlib.use("TkAgg") from matplotlib import pyplot as plt import gym from gym import spaces from gym.utils import seeding # Resources: # https://en.wikipedia.org/wiki/Mountain_car_problem # https://towardsdatascience.com/getting-started-with-reinforcement-learning-and-open-ai-gym-c289aca874f # https://towardsdatascience.com/reinforcement-learning-temporal-difference-sarsa-q-learning-expected-sarsa-on-python-9fecfda7467e def epsilon_greedy(Q, state, action_space, epsilon): # if in epsilon range use it if np.random.rand() < 1 - epsilon: action = np.argmax(Q[state[0], state[1]]) # else take random action else: action = np.random.randint(0, action_space) return action def q_learning(learning_rate, discount, epsilon, episodes): # initialize environment env = gym.make("MountainCar-v0") env.reset() states = (env.observation_space.high - env.observation_space.low)*np.array([10,100]) states = np.round(states, 0).astype(int) + 1 # Q(s,a) Q_table = np.random.uniform(low = -1, high = 1, size = (states[0], states[1], env.action_space.n)) reward_list = [] var_list = [] avg_reward_list = [] # Q learning main loop for i in range(episodes): finished = False total_reward = 0 reward = 0 state = env.reset() state_adj = (state - env.observation_space.low)*np.array([10,100]) state_adj = np.round(state_adj, 0).astype(int) while not finished: # render last N episodes # comment out to see plots # if i >= episodes - 1: # env.render() # action = epsilon_greedy(Q_table, state_adj, env.action_space.n, epsilon) # pick aciton greedily without randomness action = np.argmax(Q_table[state_adj[0], state_adj[1]]) next_state, reward, finished, info = env.step(action) # Discretize next_state_adj = (next_state - env.observation_space.low)*np.array([10,100]) next_state_adj = np.round(next_state_adj, 0).astype(int) if finished and next_state[0] >= 0.5: # and ... condition Q_table[state_adj[0], state_adj[1], action] = reward else: update = learning_rate * (reward + discount * np.max(Q_table[next_state_adj[0],next_state_adj[1]]) - Q_table[state_adj[0], state_adj[1], action]) # update Q table Q_table[state_adj[0], state_adj[1], action] += update total_reward += reward state_adj = next_state_adj reward_list.append(total_reward) # choose how often to record data # recording every data point will make the plots crowded # 10 and 100 work well. recording_interval = 100 if i % recording_interval == 0: avg_reward = np.mean(reward_list) var = np.var(reward_list) var_list.append(var) avg_reward_list.append(avg_reward) reward_list = [] env.close() return (avg_reward_list, var_list) # Adjust these parameters as needed number_of_episodes = 2500 learning_rate = 0.1 gamma = 0.9 epsilon = 0.8 def single_run(): """ Run the algorithm once """ rewards_and_var = q_learning(learning_rate, gamma, epsilon, number_of_episodes) avg_reward = rewards_and_var[0] var = rewards_and_var[1] episodes1 = 100*(np.arange(len(avg_reward)) + 1) episodes2 = 100*(np.arange(len(var)) + 1) plt.figure("Average Reward vs. Episodes") plt.title("Average Reward vs. Episodes") plt.xlabel("Episodes") plt.ylabel("Average Reward") plt.plot(episodes1, avg_reward, color='blue') plt.figure("Variance vs. Episodes") plt.title("Variance vs. Episodes") plt.xlabel("Episodes") plt.ylabel("Variance") plt.plot(episodes2, var, color='orange') plt.figure("Average Reward w/ Variance vs. Episodes") plt.title("Average Reward w/ Variance vs. Episodes") plt.xlabel("Episodes") plt.ylabel("Average Reward w/ Variance") plt.errorbar(episodes1, avg_reward, var, linestyle='None', marker='^', ecolor="orange") plt.show() def multi_run(N): """ Run the algorithm N times @param N - number of times to test (e.g. 20) """ rewards = [] vars = [] for _ in range(N): rewards_and_var = q_learning(learning_rate, gamma, epsilon, number_of_episodes) avg_reward = rewards_and_var[0] var = rewards_and_var[1] rewards.append(avg_reward) vars.append(var) rewards = list(zip(*rewards)) vars = list(zip(*vars)) reward_to_plot = [] for sublist in rewards: reward_to_plot.append(np.mean(sublist)) var_to_plot = [] for sublist in vars: var_to_plot.append(np.mean(sublist)) episodes1 = 100*(np.arange(len(avg_reward)) + 1) episodes2 = 100*(np.arange(len(var)) + 1) plt.figure("Average Reward vs. Episodes") plt.title("Average Reward vs. Episodes") plt.xlabel("Episodes") plt.ylabel("Average Reward") plt.plot(episodes1, reward_to_plot, color='blue') plt.savefig("q_learning_no_epsilon_results/Average_Reward_vs_Episodes.png") plt.figure("Variance vs. Episodes") plt.title("Variance vs. Episodes") plt.xlabel("Episodes") plt.ylabel("Variance") plt.plot(episodes2, var_to_plot, color='orange') plt.savefig("q_learning_no_epsilon_results/Variance_vs_Episodes.png") plt.figure("Average Reward w/ Variance vs. Episodes") plt.title("Average Reward w/ Variance vs. Episodes") plt.xlabel("Episodes") plt.ylabel("Average Reward w/ Variance") plt.errorbar(episodes1, reward_to_plot, var_to_plot, linestyle='None', marker='^', ecolor="orange") plt.savefig("q_learning_no_epsilon_results/Average_Reward_and_Variance_vs_Episodes.png") # choose multi or single run # single_run() multi_run(20)

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import numpy as np import itertools as it from PIL import Image from copy import deepcopy from mobject import Mobject from helpers import * #TODO, this whole class should be something vectorized. class Region(Mobject): CONFIG = { "display_mode" : "region" } def __init__(self, condition = (lambda x, y : True), **kwargs): """ Condition must be a function which takes in two real arrays (representing x and y values of space respectively) and return a boolean array. This can essentially look like a function from R^2 to {True, False}, but & and | must be used in place of "and" and "or" """ Mobject.__init__(self, **kwargs) self.condition = condition def _combine(self, region, op): self.condition = lambda x, y : op( self.condition(x, y), region.condition(x, y) ) def union(self, region): self._combine(region, lambda bg1, bg2 : bg1 | bg2) return self def intersect(self, region): self._combine(region, lambda bg1, bg2 : bg1 & bg2) return self def complement(self): self.bool_grid = ~self.bool_grid return self class HalfPlane(Region): def __init__(self, point_pair, upper_left = True, *args, **kwargs): """ point_pair of the form [(x_0, y_0,...), (x_1, y_1,...)] Pf upper_left is True, the side of the region will be everything on the upper left side of the line through the point pair """ if not upper_left: point_pair = list(point_pair) point_pair.reverse() (x0, y0), (x1, y1) = point_pair[0][:2], point_pair[1][:2] def condition(x, y): return (x1 - x0)*(y - y0) > (y1 - y0)*(x - x0) Region.__init__(self, condition, *args, **kwargs) def region_from_line_boundary(*lines, **kwargs): reg = Region(**kwargs) for line in lines: reg.intersect(HalfPlane(line, **kwargs)) return reg def region_from_polygon_vertices(*vertices, **kwargs): return region_from_line_boundary(*adjacent_pairs(vertices), **kwargs) def plane_partition(*lines, **kwargs): """ A 'line' is a pair of points [(x0, y0,...), (x1, y1,...)] Returns the list of regions of the plane cut out by these lines """ result = [] half_planes = [HalfPlane(line, **kwargs) for line in lines] complements = [deepcopy(hp).complement() for hp in half_planes] num_lines = len(lines) for bool_list in it.product(*[[True, False]]*num_lines): reg = Region(**kwargs) for i in range(num_lines): if bool_list[i]: reg.intersect(half_planes[i]) else: reg.intersect(complements[i]) if reg.bool_grid.any(): result.append(reg) return result def plane_partition_from_points(*points, **kwargs): """ Returns list of regions cut out by the complete graph with points from the argument as vertices. Each point comes in the form (x, y) """ lines = [[p1, p2] for (p1, p2) in it.combinations(points, 2)] return plane_partition(*lines, **kwargs)

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#!/usr/bin/env python3 # date: 2019.09.29 # `PixelAccess` changes pixels in original `img` # so there is no need to convert it back to `Image` # BTW: Image uses [col,row] (array uses [row,col]) from PIL import Image img = Image.open('image.jpg') pixels = img.load() width, height = img.size for col in range(width): for row in range(height): if pixels[col,row] == (0, 0, 0): pixels[col,row] = (255, 0 ,0) img.show()

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#!/usr/bin/env python # Copyright 2016 The Kubernetes 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. # Stolen from https://github.com/kubernetes/test-infra/blob/master/hack/coalesce.py """Coalesces bazel test results into one file.""" import argparse import os import re import xml.etree.ElementTree as ET BAZEL_FAILURE_HEADER = '''exec ${PAGER:-/usr/bin/less} "$0" || exit 1 ----------------------------------------------------------------------------- ''' # from https://www.w3.org/TR/xml11/#charsets # RestrictedChar ::= [#x1-#x8]|[#xB-#xC]|[#xE-#x1F]|[#x7F-#x84]|[#x86-#x9F] RESTRICTED_XML_CHARS_RE = re.compile(r'[\x00-\x08\x0B\x0C\x0E-\x1F\x7F-\x84\x86-\x9F]') ANSI_ESCAPE_CODES_RE = re.compile(r'\033\[[\d;]*[@-~]') def test_packages(root): """Yields test package directories under root.""" for package, _, files in os.walk(root): if 'test.xml' in files and 'test.log' in files: yield package def sanitize(text): if text.startswith(BAZEL_FAILURE_HEADER): text = text[len(BAZEL_FAILURE_HEADER):] # ANSI escape sequences should be removed. text = ANSI_ESCAPE_CODES_RE.sub('', text) # And any other badness that slips through. text = RESTRICTED_XML_CHARS_RE.sub('', text) return text def result(pkg): """Given a directory, create a testcase element describing it.""" elem = ET.Element('testcase') elem.set('classname', 'go_test') pkg_parts = pkg.split('/') elem.set('name', '//%s:%s' % ('/'.join(pkg_parts[1:-1]), pkg_parts[-1])) elem.set('time', '0') suites = ET.parse(pkg + '/test.xml').getroot() for suite in suites: for case in suite: for status in case: if status.tag == 'error' or status.tag == 'failure': failure = ET.Element('failure') with open(pkg + '/test.log') as fp: text = fp.read().decode('UTF-8', 'ignore') failure.text = sanitize(text) elem.append(failure) return elem def main(): root = ET.Element('testsuite') root.set('time', '0') for package in sorted(test_packages('bazel-testlogs')): root.append(result(package)) artifacts_dir = os.environ['ARTIFACTS'] try: os.mkdir(artifacts_dir) except OSError: pass with open(os.path.join(artifacts_dir, 'junit_bazel.xml'), 'w') as fp: fp.write(ET.tostring(root, 'UTF-8')) if __name__ == '__main__': PARSER = argparse.ArgumentParser(description='Coalesce JUnit results.') PARSER.add_argument('--repo_root', default='.') ARGS = PARSER.parse_args() os.chdir(ARGS.repo_root) main()

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#!/usr/bin/python #coding:utf-8 from tool import SQLTool ,config from Back_ground.model import takeclass,Class limitpage=15 localconfig=config.Config() def haveclassshow(schoolid='',classid='',teacherid='',page='0'): validresult=False request_params=[] values_params=[] if schoolid!='': request_params.append('schoolId') values_params.append(SQLTool.formatstring(schoolid)) if classid!='': request_params.append('t_classes.classId') values_params.append(SQLTool.formatstring(classid)) if teacherid!='': request_params.append('teacherId') values_params.append(SQLTool.formatstring(teacherid)) request_params.append('t_teach.teacherId') values_params.append('t_teachers.teacherId') DBhelp=SQLTool.DBmanager() DBhelp.connectdb() table=localconfig.teachertable result,content,count,col=DBhelp.searchtableinfo_byparams([table,localconfig.teachtable], ['t_teachers.teacherId','masterId','time','schoolId','teacherName','classId'], request_params, values_params) if count == 0: pagecount = 0; elif count %limitpage> 0: # pagecount = math.ceil(count / limitpage) pagecount=int((count+limitpage-1)/limitpage) else: pagecount = count / limitpage # print pagecount if pagecount>0: limit=' limit '+str(int(page)*limitpage)+','+str(limitpage) result,content,count,col=DBhelp.searchtableinfo_byparams([table,localconfig.teachtable], ['t_teachers.teacherId','masterId','time','schoolId','teacherName','classId'], request_params, values_params,limit,order='time desc') DBhelp.closedb() classes=[] if count>0: validresult=True for temp in result : aclass=takeclass.Takeclass(teacherid=temp['teacherId'],schoolid=temp['schoolId'],masterid=temp['masterId'],time=temp['time'],teachername=temp['teacherName'],classid=temp['classId']) classes.append(aclass) return classes,count,pagecount return [],0,pagecount def classshow(schoolname='',schoolid='',gradeid='',classid='',classname='',page='0'): validresult=False request_params=[] values_params=[] if schoolname!='': request_params.append('schoolName') values_params.append(SQLTool.formatstring(schoolname)) if gradeid!='': request_params.append('t_classes.gradeId') values_params.append(SQLTool.formatstring(gradeid)) if classid!='': request_params.append('t_classes.classId') values_params.append(SQLTool.formatstring(classid)) if classname!='': request_params.append('t_class_name.className') values_params.append(SQLTool.formatstring(classname)) if schoolid!='': request_params.append('t_classes.schoolId') values_params.append(SQLTool.formatstring(schoolid)) request_params.append('t_school.schoolId') values_params.append('t_classes.schoolId') request_params.append('t_classes.classId') values_params.append('t_class_name.classId') DBhelp=SQLTool.DBmanager() DBhelp.connectdb() table=localconfig.schooltable result,content,count,col=DBhelp.searchtableinfo_byparams([table,localconfig.classtable,localconfig.classnametable], ['schoolName','t_classes.schoolId','t_classes.gradeId','cId','t_class_name.className','t_classes.classId'], request_params, values_params) if count == 0: pagecount = 0; elif count %limitpage> 0: # pagecount = math.ceil(count / limitpage) pagecount=int((count+limitpage-1)/limitpage) else: pagecount = count / limitpage # print pagecount if pagecount>0: limit=' limit '+str(int(page)*limitpage)+','+str(limitpage) result,content,count,col=DBhelp.searchtableinfo_byparams([table,localconfig.classtable,localconfig.classnametable], ['schoolName','t_classes.schoolId','t_classes.gradeId','cId','t_class_name.className','t_classes.classId'], request_params, values_params,limit,order='schoolId desc') DBhelp.closedb() classes=[] if count>0: validresult=True for temp in result : aclass=Class.Class(schoolname=temp['schoolName'],schoolid=temp['schoolId'],gradeid=temp['gradeId'],cid=temp['cId'],classname=temp['className'],classid=temp['classId']) classes.append(aclass) return classes,count,pagecount return [],0,pagecount ##count为返回结果行数，col为返回结果列数,count,pagecount都为int型 def loadclass(request,username=''): schoolname=request.POST.get('schoolname','') schoolid=request.POST.get('schoolid','') province=request.POST.get('province','') city=request.POST.get('city','') starttime=request.POST.get('starttime','') tempschool=None if schoolid=='' or schoolname=='': return tempschool,False tempschool=school.School(schoolname=schoolname,schoolid=schoolid,province=province,city=city) return tempschool,True def classadd(school): schoolname=school.getSchoolname() schoolid=school.getSchoolid() province=school.getProvince() city=school.getCity() starttime=school.getStarttime() request_params=[] values_params=[] if schoolname!='': request_params.append('schoolName') values_params.append(SQLTool.formatstring(schoolname)) if schoolid!='': request_params.append('schoolId') values_params.append(SQLTool.formatstring(schoolid)) if province!='': request_params.append('province') values_params.append(SQLTool.formatstring(province)) if city!='': request_params.append('city') values_params.append(SQLTool.formatstring(city)) if starttime!='': request_params.append('starttime') values_params.append(SQLTool.formatstring(starttime)) table=localconfig.schooltable DBhelp=SQLTool.DBmanager() DBhelp.connectdb() tempresult=DBhelp.inserttableinfo_byparams(table=table, select_params=request_params,insert_values= [tuple(values_params)]) DBhelp.closedb() return tempresult def classupdate(schoolname='',schoolid='',province='',city='',starttime=''): request_params=[] values_params=[] wset_params=[] wand_params=[] if schoolname!='': request_params.append('schoolName') values_params.append(SQLTool.formatstring(schoolname)) if schoolid!='': request_params.append('schoolId') values_params.append(SQLTool.formatstring(schoolid)) if province!='': request_params.append('province') values_params.append(SQLTool.formatstring(province)) if city!='': request_params.append('city') values_params.append(SQLTool.formatstring(city)) if starttime!='': request_params.append('starttime') values_params.append(SQLTool.formatstring(starttime)) table=localconfig.schooltable DBhelp=SQLTool.DBmanager() DBhelp.connectdb() tempresult=DBhelp.updatetableinfo_byparams([table],request_params,values_params,wset_params,wand_params) DBhelp.closedb() return tempresult

[ "nanshihui@qq.com" ]

nanshihui@qq.com

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/koku/api/resource_types/azure_regions/view.py

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luisfdez/koku

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# # Copyright 2021 Red Hat Inc. # SPDX-License-Identifier: Apache-2.0 # """View for Azure Region locations.""" from django.db.models import F from django.utils.decorators import method_decorator from django.views.decorators.vary import vary_on_headers from rest_framework import filters from rest_framework import generics from api.common import CACHE_RH_IDENTITY_HEADER from api.common.permissions.azure_access import AzureAccessPermission from api.resource_types.serializers import ResourceTypeSerializer from reporting.provider.azure.models import AzureCostSummaryByLocation from reporting.provider.azure.openshift.models import OCPAzureCostSummaryByLocation class AzureRegionView(generics.ListAPIView): """API GET list view for Azure Region locations.""" queryset = ( AzureCostSummaryByLocation.objects.annotate(**{"value": F("resource_location")}) .values("value") .distinct() .filter(resource_location__isnull=False) ) serializer_class = ResourceTypeSerializer permission_classes = [AzureAccessPermission] filter_backends = [filters.OrderingFilter, filters.SearchFilter] ordering = ["value"] search_fields = ["$value"] @method_decorator(vary_on_headers(CACHE_RH_IDENTITY_HEADER)) def list(self, request): # Reads the users values for Azure subscription guid and displays values related to what the user has access to user_access = [] openshift = self.request.query_params.get("openshift") if openshift == "true": self.queryset = ( OCPAzureCostSummaryByLocation.objects.annotate(**{"value": F("resource_location")}) .values("value") .distinct() .filter(resource_location__isnull=False) ) if request.user.admin: return super().list(request) elif request.user.access: user_access = request.user.access.get("azure.subscription_guid", {}).get("read", []) self.queryset = self.queryset.values("value").filter(subscription_guid__in=user_access) return super().list(request)

[ "noreply@github.com" ]

luisfdez.noreply@github.com

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/Codewars/Python/6kyu/6kyu_Sort the odd.py

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no_license

KonradMarzec1991/Codewars-LeetCode

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refs/heads/master

2023-04-21T17:04:37.434876

2021-05-11T21:47:14

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def sort_array(source_array): sorted_odds = sorted([d for d in source_array if d % 2 == 1]) startpoint = 0 for d in range(len(source_array)): if source_array[d] % 2 == 1: source_array[d] = sorted_odds[startpoint] startpoint += 1 return source_array

[ "konrimarzec@gmail.com" ]

konrimarzec@gmail.com

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e838076bc1c8aedbb8c77710b1a1a32efc3a4da1

/pc1/models.py

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[]

no_license

abbasgis/ferrp

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77736c33e7ec82b6adf247a1bf30ccbc4897f02e

refs/heads/master

2023-05-25T09:59:45.185025

2021-06-12T09:15:07

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from django.db import models # Create your models here. class AdpDraft201718Vw(models.Model): gs_no = models.TextField(primary_key=True) # This field type is a guess. s_name = models.TextField(blank=True, null=True) # This field type is a guess. district = models.TextField(blank=True, null=True) # This field type is a guess. tehsil = models.TextField(blank=True, null=True) # This field type is a guess. s_type = models.TextField(blank=True, null=True) # This field type is a guess. sec_name = models.TextField(blank=True, null=True) # This field type is a guess. sec_id = models.TextField(blank=True, null=True) # This field type is a guess. approval_date = models.TextField(blank=True, null=True) # This field type is a guess. cost_total = models.TextField(blank=True, null=True) # This field type is a guess. foreign_aid = models.TextField(blank=True, null=True) # This field type is a guess. local_capital = models.TextField(blank=True, null=True) # This field type is a guess. local_revenue = models.TextField(blank=True, null=True) # This field type is a guess. capital_total = models.TextField(blank=True, null=True) # This field type is a guess. revenue_total = models.TextField(blank=True, null=True) # This field type is a guess. foreign_capital = models.TextField(blank=True, null=True) # This field type is a guess. foreign_revenue = models.TextField(blank=True, null=True) # This field type is a guess. allocation = models.TextField(blank=True, null=True) # This field type is a guess. exp_upto_june = models.TextField(blank=True, null=True) # This field type is a guess. projection_2017_18 = models.TextField(db_column='projection_2017-18', blank=True, null=True) # Field renamed to remove unsuitable characters. This field type is a guess. projection_2018_19 = models.TextField(db_column='projection_2018-19', blank=True, null=True) # Field renamed to remove unsuitable characters. This field type is a guess. throw_forward = models.TextField(blank=True, null=True) # This field type is a guess. monitoring = models.TextField(blank=True, null=True) # This field type is a guess. start_date = models.TextField(blank=True, null=True) end_date = models.TextField(blank=True, null=True) cost_total_adp_origional = models.TextField(blank=True, null=True) class Meta: managed = False db_table = 'adp_draft_201718_vw' class TblSchemesHistory(models.Model): id = models.AutoField(primary_key=True) gs_no = models.IntegerField(blank=True, null=True) project_location = models.TextField(blank=True, null=True) authorities_responsible = models.TextField(blank=True, null=True) plan_provision = models.TextField(blank=True, null=True) project_objectives = models.TextField(blank=True, null=True) annual_operating_cost = models.TextField(blank=True, null=True) capital_cost_estimates = models.TextField(blank=True, null=True) physical_plan = models.TextField(blank=True, null=True) financial_plan = models.TextField(blank=True, null=True) financial_plan_text = models.TextField(blank=True, null=True) gantt_chart = models.TextField(blank=True, null=True) demand_and_supply_analysis = models.TextField(blank=True, null=True) benefits_of_the_projects_analysis = models.TextField(blank=True, null=True) implementation_schedule = models.TextField(blank=True, null=True) ms_and_mp = models.TextField(blank=True, null=True) additional_projects_decisions_required = models.TextField(blank=True, null=True) certified = models.TextField(blank=True, null=True) class Meta: managed = False db_table = 'tbl_schemes_history' class TblSchemesAnnexure(models.Model): id = models.TextField(primary_key=True) gs_no = models.TextField(blank=True, null=True) annexure_title = models.TextField(blank=True, null=True) annexure_data = models.TextField(blank=True, null=True) class Meta: managed = False db_table = 'tbl_scheme_annexure' class TblHelp(models.Model): id = models.IntegerField(primary_key=True) # AutoField? section_name = models.TextField(blank=True, null=True) info_name = models.TextField(blank=True, null=True) # This field type is a guess. help_image = models.BinaryField(blank=True, null=True) class Meta: managed = False db_table = 'tbl_help'

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abbas123@abc

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/Incident-Response/Tools/cyphon/cyphon/alerts/migrations/0011_auto_20170815_1432.py

83a21b67e06bc5f594c3731289b36f09f4baa58f

[ "LicenseRef-scancode-proprietary-license", "GPL-3.0-only", "LicenseRef-scancode-unknown-license-reference", "GPL-1.0-or-later", "LicenseRef-scancode-warranty-disclaimer", "LicenseRef-scancode-other-copyleft", "MIT" ]

permissive

foss2cyber/Incident-Playbook

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2021-07-07T03:48:54

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# -*- coding: utf-8 -*- # Generated by Django 1.11.2 on 2017-08-15 18:32 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('alerts', '0010_remove_alert_tags'), ] operations = [ migrations.AlterField( model_name='alert', name='distillery', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='alerts', related_query_name='alerts', to='distilleries.Distillery'), ), ]

[ "a.songer@protonmail.com" ]

a.songer@protonmail.com

1d9066b6f8c175153341870908a2697e4398d8bf

e0df2bc703d0d02423ea68cf0b8c8f8d22d5c163

/ScientificComputing/ch14/filter_equalizer.py

8d3830bd050cd0f33b823f8ec982a021af94ccdc

[]

no_license

socrates77-sh/learn

a5d459cb9847ba3b1bc4f9284ce35d4207d8aa8b

ae50978023f6b098b168b8cca82fba263af444aa

refs/heads/master

2022-12-16T16:53:50.231577

2019-07-13T13:52:42

168,442,963

0

null

2022-12-08T05:18:37

2019-01-31T01:30:06

HTML

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# -*- coding: utf-8 -*- import scipy.signal as signal import pylab as pl import math import numpy as np def design_equalizer(freq, Q, gain, Fs): '''设计二次均衡滤波器的系数''' A = 10**(gain/40.0) w0 = 2*math.pi*freq/Fs alpha = math.sin(w0) / 2 / Q b0 = 1 + alpha * A b1 = -2*math.cos(w0) b2 = 1 - alpha * A a0 = 1 + alpha / A a1 = -2*math.cos(w0) a2 = 1 - alpha / A return [b0/a0, b1/a0, b2/a0], [1.0, a1/a0, a2/a0] pl.figure(figsize=(8, 4)) for freq in [1000, 2000, 4000]: for q in [0.5, 1.0]: for p in [5, -5, -10]: b, a = design_equalizer(freq, q, p, 44100) w, h = signal.freqz(b, a) pl.semilogx(w/np.pi*44100, 20*np.log10(np.abs(h))) pl.xlim(100, 44100) pl.xlabel(u"频率(Hz)") pl.ylabel(u"振幅(dB)") pl.subplots_adjust(bottom=0.15) pl.show()

[ "zhwenrong@sina.com" ]

zhwenrong@sina.com

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/4_py_libro_1_pydroid/venv/4_py_libro_1_pydroid/COLECCIONES/py_1_collecciones.py

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[]

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JAreina/python

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refs/heads/master

2020-03-22T07:57:31.675271

2018-09-12T06:38:49

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py

import collections c = collections # JAreina a = c.Counter([2,2,8,5,1,2,3,4,5,8]) print(a) b = 'en un lugar de la mancha' print( c.Counter(b)) d = ['a',"b",'c',"c",'z'] print(c.Counter(d)) print("\n ::::::::: update counter::::::::::::\n") e = c.Counter() print(e) e.update("hola hola") print(e) #JAreina e.update( {"a": 100} ) print(e)

[ "jareinafdez@gmail.com" ]

jareinafdez@gmail.com

2f44a2a3e2304fa716d563c22a881c2c0fbf5ef7

257bd63361aa846ffdacdc15edaecf84c6364e78

/psou/pro1/pack3/class_ex9.py

b5fb7d6e7b2028d16e4b7c2b560541e4fb51073b

[]

no_license

gom4851/hcjeon

86dcfd05ce47a13d066f13fe187d6a63142fb9fe

59a00ca9499f30e50127bb16eb510553e88ace43

refs/heads/master

2020-06-04T23:16:08.632278

2019-01-15T09:54:08

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''' Created on 2018. 11. 8. 상속 ''' class Person: say = "난 사람이야~" nai = '20' __kor = 59 # 앞에 __ 해주면 private가 됨. def __init__(self, nai): print('Person 생성자') self.nai = nai def printInfo(self): print('나이:{}, 이야기:{}'.format(self.nai, self.say)) def hello(self): print('안녕') print('hello에서 kor : ', self.__kor) @staticmethod def sbs(tel): print('sbs_tel : ', tel) # 다른 멤버와 상관없이 # self.hello # 멤버와 상관없는 독립적 수행할 때 사용.(self와 상관없ㅇㅣ..) @classmethod # 프로테드 부를때..? def mbc(cls): print('mbc_', cls.say, cls.nai, cls.__kor) p = Person('22') p.printInfo() p.hello() print('**' * 20) class Employee(Person): say = "일하는 동물" # 만들어진 객체에 변수 먼저 확인. subject = "부가" def __init__(self): print('Employee 생성자') def EprintInfo(self): #printInfo() 이렇게하면 모듈의 함수를 찾는 것. self.printInfo() super().printInfo() e = Employee() print(e.say, e.nai, e.subject) e.printInfo() e.EprintInfo() print("**" * 20) class Worker(Person): def __init__(self, nai): print('Worker 생성자') self.nai = nai def WprintInfo(self): super().printInfo() w = Worker('30') w.WprintInfo() print("~~" * 20) class Programmer(Worker): def __init__(self, nai): print("Programmer 생성자") #super().__init__(nai) # Bound Worker.__init__(self, nai) # UnBound def printInfo(self): print("오바라이딩 메소드") def WprintInfo(self): self.printInfo() # PerSon까지 감. #print('Worker에서 kor : ', self._kor) pr = Programmer(36) pr.WprintInfo() print() a = 5 print(type(a)) print(Person.__bases__) # 현재 클래스의 부모 클래스 타입 확인 print(Programmer.__bases__) pr.sbs('111-1111') Person.sbs('222-2222') pr.mbc() Person.mbc()

[ "wer104@naver.com" ]

wer104@naver.com

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r-swilderd/mi-instrument

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2021-01-17T21:56:34.298829

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#!/usr/bin/env python try: from setuptools import setup, find_packages except ImportError: from distutils.core import setup import os import sys # Add /usr/local/include to the path for macs, fixes easy_install for several packages (like gevent and pyyaml) if sys.platform == 'darwin': os.environ['C_INCLUDE_PATH'] = '/usr/local/include' version = '0.2.1' setup( name = 'marine-integrations', version = version, description = 'OOINet Marine Integrations', url = 'https://github.com/ooici/marine-integrations', download_url = 'http://sddevrepo.oceanobservatories.org/releases/', license = 'BSD', author = 'Ocean Observatories Initiative', author_email = 'contactooici@oceanobservatories.org', keywords = ['ooici'], packages = find_packages(), dependency_links = [ 'http://sddevrepo.oceanobservatories.org/releases/', 'https://github.com/ooici/pyon/tarball/master#egg=pyon', #'https://github.com/ooici/utilities/tarball/v2012.12.12#egg=utilities-2012.12.12', ], test_suite = 'pyon', entry_points = { 'console_scripts' : [ 'package_driver=ion.idk.scripts.package_driver:run', 'start_driver=ion.idk.scripts.start_driver:run', 'test_driver=ion.idk.scripts.test_driver:run', ], }, install_requires = [ 'gitpy==0.6.0', 'snakefood==1.4', 'ntplib>=0.1.9', 'apscheduler==2.1.0', #'utilities', ], )

[ "petercable@gmail.com" ]

petercable@gmail.com

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/controls/Control_Toolbox/steady_state_error.py

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[]

no_license

cmontalvo251/Python

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refs/heads/master

2023-06-22T21:50:21.225067

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###Integrate an ordinary differential equation #in MATLAB that's using the function ode45. #in Python we're going to use the Scipy toolbox and odeint import numpy as np import matplotlib.pyplot as plt import scipy.integrate as I import control as ctl import scipy.signal as S import scipy.linalg as slin plt.close("all") ####Zeros Poles and Gains ###Zeros are the roots of the numerator ####Poles are the roots of the denominator ####Gain is the leading coefficient of numerator/leading coefficient of the denominator zeros = [] poles = [-3.0] gain = 3.0 [N,D] = S.zpk2tf(zeros,poles,gain) G = ctl.tf(N,D) tout = np.linspace(0,5,1000) tout,yout = ctl.step_response(G,tout) zeros = [] poles = 0 gain = 2.0 [N,D] = S.zpk2tf(zeros,poles,gain) C = ctl.tf(N,D) sys_closed_loop = C*G/(1+C*G) toutc,youtc = ctl.step_response(sys_closed_loop,tout) plt.plot(tout,yout,'r-',label='Open Loop') plt.plot(tout,youtc,'g-',label='Closed Loop') plt.xlabel('Time (sec)') plt.ylabel('State') plt.legend() plt.grid() plt.show()

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# coding=utf-8 ''' 1.导入sqlite3模块 2.创建连接 sqlite3.connect() 3.创建游标对象 4.编写创建表的sql语句 5.执行sql 6.关闭连接 ''' import sqlite3 conn = None # 创建连接 try: conn = sqlite3.connect('e:/sqlite3Demo/demo.db') print('连接sqlite库成功') except Exception as e: print('连接sqlite库失败：', e) if conn is not None: # 创建游标对象 cur = conn.cursor() # 编写创建表的sql语句 sql = '''create table t_person( pno INTEGER primary key autoincrement, pname VARCHAR not null, age INTEGER )''' try: # 执行sql语句 cur.execute(sql) print('创建表成功') except Exception as e: print(e) print('创建表失败：', e) finally: # 关闭游标 cur.close() # 关闭连接 conn.close()

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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class ContainerHttpGet(Model): """The container Http Get settings, for liveness or readiness probe. All required parameters must be populated in order to send to Azure. :param path: The path to probe. :type path: str :param port: Required. The port number to probe. :type port: int :param scheme: The scheme. Possible values include: 'http', 'https' :type scheme: str or ~azure.mgmt.containerinstance.models.enum """ _validation = { 'port': {'required': True}, } _attribute_map = { 'path': {'key': 'path', 'type': 'str'}, 'port': {'key': 'port', 'type': 'int'}, 'scheme': {'key': 'scheme', 'type': 'str'}, } def __init__(self, *, port: int, path: str=None, scheme=None, **kwargs) -> None: super(ContainerHttpGet, self).__init__(**kwargs) self.path = path self.port = port self.scheme = scheme

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# Generated by Django 2.1.5 on 2019-02-15 23:05 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('envdaq', '0007_auto_20190215_2300'), ] operations = [ migrations.RemoveField( model_name='devicedef', name='contacts', ), migrations.RemoveField( model_name='instrumentdef', name='measurements', ), ]

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import layout import render import wx TESTS = [ [('t', 'te'), ('t', 'ti'), ('t', 'to'), ('te', 'tea'), ('te', 'ten'), ('tea', 'team'), ('ti', 'tin'), ('tin', 'tine'), ('to', 'ton'), ('ton', 'tone')], [(5, 11), (11, 10), (11, 2), (3, 10), (3, 8), (8, 9), (11, 9), (7, 8), (7, 11)], [(1, 2), (1, 5), (2, 5), (2, 3), (3, 4), (4, 5), (4, 6)], [(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)], [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)], [(0, 1), (1, 2), (2, 0)], [(1, 2), (1, 5), (1, 8), (5, 6), (2, 3), (3, 4), (4, 2), (6, 7), (6, 8), (6, 3)], [(1, 2), (1, 3), (1, 4), (2, 4), (2, 5), (3, 6), (4, 3), (4, 6), (4, 7), (5, 4), (5, 7), (7, 6)], [(1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 1), (1, 4), (2, 5), (3, 6)], [(1, 3), (3, 2), (2, 1), (3, 5), (4, 1), (4, 2), (4, 12), (4, 13), (5, 6), (5, 8), (6, 7), (6, 8), (6, 10), (7, 10), (8, 9), (8, 10), (9, 5), (9, 11), (10, 9), (10, 11), (10, 14), (11, 12), (11, 14), (12, 13), (13, 11), (13, 15), (14, 13), (15, 14)], [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9)], [(0, 1), (0, 3), (1, 4), (1, 2), (2, 5), (3, 4), (3, 6), (4, 5), (4, 7), (5, 8), (6, 7), (7, 8)], ] class View(wx.Panel): def __init__(self, parent): super(View, self).__init__(parent) self.SetBackgroundStyle(wx.BG_STYLE_CUSTOM) self.Bind(wx.EVT_SIZE, self.on_size) self.Bind(wx.EVT_PAINT, self.on_paint) self.Bind(wx.EVT_CHAR_HOOK, self.on_char) self.index = -1 self.weights = {} self.model = None self.bitmap = None wx.CallAfter(self.next) def next(self): self.index = (self.index + 1) % len(TESTS) self.compute() def compute(self): edges = TESTS[self.index] nodes = layout.layout(edges, self.weights) self.set_model((edges, nodes)) def update(self): if self.model is None: return cw, ch = self.GetClientSize() bitmap = render.render(cw, ch, *self.model) self.set_bitmap(bitmap) def set_model(self, model): self.model = model self.update() def set_weights(self, weights): self.weights = weights self.compute() def set_bitmap(self, bitmap): self.bitmap = bitmap self.Refresh() self.Update() def on_char(self, event): event.Skip() if event.GetKeyCode() == wx.WXK_ESCAPE: self.GetParent().Close() elif event.GetKeyCode() == wx.WXK_SPACE: self.next() def on_size(self, event): event.Skip() self.update() def on_paint(self, event): dc = wx.AutoBufferedPaintDC(self) dc.SetBackground(wx.Brush(render.BACKGROUND)) dc.Clear() if self.bitmap is None: return cw, ch = self.GetClientSize() bw, bh = self.bitmap.GetSize() x = cw / 2 - bw / 2 y = ch / 2 - bh / 2 dc.DrawBitmap(self.bitmap, x, y) dc.DrawText(str(self.index), 10, 10) class Frame(wx.Frame): def __init__(self): super(Frame, self).__init__(None) self.create_controls(self) self.SetTitle('GraphLayout') self.SetClientSize((800, 600)) self.Center() def create_controls(self, parent): panel = wx.Panel(parent) self.view = self.create_view(panel) sidebar = self.create_sidebar(panel) sizer = wx.BoxSizer(wx.HORIZONTAL) sizer.Add(self.view, 1, wx.EXPAND) sizer.Add(sidebar, 0, wx.EXPAND | wx.ALL, 10) panel.SetSizer(sizer) return panel def create_view(self, parent): return View(parent) def create_sidebar(self, parent): names = [ 'edge_edge', 'rank', 'length', 'area', ] sizer = wx.BoxSizer(wx.VERTICAL) self.sliders = [] for name in names: value = int(layout.WEIGHTS[name] * 10) text = wx.StaticText(parent, -1, name) slider = wx.Slider(parent, -1, value, 0, 100) slider.name = name slider.Bind(wx.EVT_SCROLL_THUMBRELEASE, self.on_slider) self.sliders.append(slider) sizer.Add(text) sizer.Add(slider, 0, wx.EXPAND) sizer.AddSpacer(10) return sizer def on_slider(self, event): weights = {} for slider in self.sliders: weights[slider.name] = slider.GetValue() / 10.0 self.view.set_weights(weights) def main(): app = wx.App(None) frame = Frame() frame.Show() app.MainLoop() if __name__ == '__main__': main()

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import os import numpy as np import tensorflow as tf import collections import tokenization from run_classifier import SstProcessor, file_based_input_fn_builder, model_fn_builder, file_based_convert_examples_to_features import modeling import cPickle def get_model_size(ckpt_fpath): # Open TensorFlow ckpt reader = tf.train.NewCheckpointReader(ckpt_fpath) print('\nCount the number of parameters in ckpt file(%s)' % ckpt_fpath) param_map = reader.get_variable_to_shape_map() total_count = 0 for k, v in param_map.items(): if 'Momentum' not in k and 'global_step' not in k: temp = np.prod(v) total_count += temp print('%s: %s => %d' % (k, str(v), temp)) print('Total Param Count: %d' % total_count) # 324,935,430 ~324M # tokenizer = tokenization.BasicTokenizer(do_lower_case=True) # result = tokenizer.tokenize(u" \tHeLLo!how \n Are yoU? ") # print(result) # print(["hello", "!", "how", "are", "you", "?"]) os.environ["CUDA_VISIBLE_DEVICES"] = '1' TRAINED_MODDEL_DIR='../model/sst2/' data_dir = '../data/glue_data/SST-2' output_dir = '../model/sst2/eval/' max_seq_length = 128 vocab_file='../data/cased_L-12_H-768_A-12/vocab.txt' do_lower_case = True eval_batch_size = 8 learning_rate=2e-5 # init_checkpoint='./data/cased_L-12_H-768_A-12/bert_model.ckpt' init_checkpoint='../model/sst2/eval/model.ckpt-6313' # init_checkpoint='../model/sst2/eval/checkpoint' bert_config_file='../data/cased_L-12_H-768_A-12/bert_config.json' get_model_size(init_checkpoint) exit() processor = SstProcessor() label_list = processor.get_labels() tokenizer = tokenization.FullTokenizer( vocab_file=vocab_file, do_lower_case=do_lower_case) train_examples = processor.get_train_examples(data_dir) trn_file = os.path.join(output_dir, "trn.tf_record") file_based_convert_examples_to_features( train_examples, label_list, max_seq_length, tokenizer, trn_file) eval_examples = processor.get_dev_examples(data_dir) eval_file = os.path.join(output_dir, "eval.tf_record") file_based_convert_examples_to_features( eval_examples, label_list, max_seq_length, tokenizer, eval_file) tst_examples = processor.get_test_examples(data_dir) tst_file = os.path.join(output_dir, "tst.tf_record") file_based_convert_examples_to_features(tst_examples, label_list, max_seq_length, tokenizer, tst_file) bert_config = modeling.BertConfig.from_json_file(bert_config_file) is_per_host = tf.contrib.tpu.InputPipelineConfig.PER_HOST_V2 run_config = tf.contrib.tpu.RunConfig( cluster=None, master=None, model_dir=output_dir, save_checkpoints_steps=1000, tpu_config=tf.contrib.tpu.TPUConfig( iterations_per_loop=1000, num_shards=8, per_host_input_for_training=is_per_host)) model_fn = model_fn_builder( bert_config=bert_config, num_labels=len(label_list), init_checkpoint=init_checkpoint, learning_rate=learning_rate, num_train_steps=10, num_warmup_steps=10, use_tpu=False, use_one_hot_embeddings=False) estimator = tf.contrib.tpu.TPUEstimator( use_tpu=False, model_fn=model_fn, config=run_config, train_batch_size=32, eval_batch_size=8, predict_batch_size=8) tf.logging.info("***** Running evaluation *****") tf.logging.info(" Num examples = %d", len(eval_examples)) tf.logging.info(" Batch size = %d", eval_batch_size) # This tells the estimator to run through the entire set. eval_steps = None eval_drop_remainder = False eval_input_fn = file_based_input_fn_builder( input_file=eval_file, seq_length=max_seq_length, is_training=False, drop_remainder=eval_drop_remainder) result = estimator.evaluate(input_fn=eval_input_fn, steps=eval_steps) embeddings = estimator.get_variable_value(estimator.get_variable_names()[12]) with open(output_dir+'embedding.cpkl', 'wb') as handle: cPickle.dump(embeddings, handle) result_predict = [val for val in estimator.predict(eval_input_fn)] output_eval_file = os.path.join(output_dir, "eval_results.txt") with tf.gfile.GFile(output_eval_file, "w") as writer: tf.logging.info("***** Eval results *****") for key in sorted(result.keys()): tf.logging.info(" %s = %s", key, str(result[key])) writer.write("%s = %s\n" % (key, str(result[key])))

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FingerLeakers/DanderSpritz_docs

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# uncompyle6 version 2.9.10 # Python bytecode 2.7 (62211) # Decompiled from: Python 2.7.10 (default, Feb 6 2017, 23:53:20) # [GCC 4.2.1 Compatible Apple LLVM 8.0.0 (clang-800.0.34)] # Embedded file name: utf_32_be.py """ Python 'utf-32-be' Codec """ import codecs encode = codecs.utf_32_be_encode def decode(input, errors='strict'): return codecs.utf_32_be_decode(input, errors, True) class IncrementalEncoder(codecs.IncrementalEncoder): def encode(self, input, final=False): return codecs.utf_32_be_encode(input, self.errors)[0] class IncrementalDecoder(codecs.BufferedIncrementalDecoder): _buffer_decode = codecs.utf_32_be_decode class StreamWriter(codecs.StreamWriter): encode = codecs.utf_32_be_encode class StreamReader(codecs.StreamReader): decode = codecs.utf_32_be_decode def getregentry(): return codecs.CodecInfo(name='utf-32-be', encode=encode, decode=decode, incrementalencoder=IncrementalEncoder, incrementaldecoder=IncrementalDecoder, streamreader=StreamReader, streamwriter=StreamWriter)

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""" ======================= Annotate Simple Coord02 ======================= """ import matplotlib.pyplot as plt # nodebox section if __name__ == '__builtin__': # were in nodebox import os import tempfile W = 800 inset = 20 size(W, 600) plt.cla() plt.clf() plt.close('all') def tempimage(): fob = tempfile.NamedTemporaryFile(mode='w+b', suffix='.png', delete=False) fname = fob.name fob.close() return fname imgx = 20 imgy = 0 def pltshow(plt, dpi=150): global imgx, imgy temppath = tempimage() plt.savefig(temppath, dpi=dpi) dx,dy = imagesize(temppath) w = min(W,dx) image(temppath,imgx,imgy,width=w) imgy = imgy + dy + 20 os.remove(temppath) size(W, HEIGHT+dy+40) else: def pltshow(mplpyplot): mplpyplot.show() # nodebox section end fig, ax = plt.subplots(figsize=(3, 2)) an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data", va="center", ha="center", bbox=dict(boxstyle="round", fc="w")) an2 = ax.annotate("Test 2", xy=(0.5, 1.), xycoords=an1, xytext=(0.5, 1.1), textcoords=(an1, "axes fraction"), va="bottom", ha="center", bbox=dict(boxstyle="round", fc="w"), arrowprops=dict(arrowstyle="->")) fig.subplots_adjust(top=0.83) pltshow(plt)

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{ "includes": [ "../common.gypi" ], "targets": [ { "target_name": "libgdal_tsx_frmt", "type": "static_library", "sources": [ "../gdal/frmts/tsx/tsxdataset.cpp" ], "include_dirs": [ "../gdal/frmts/tsx" ] } ] }

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MZ195/Cupy-GPU-Example

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import numpy as np from timeit import default_timer as timer from numba import vectorize NUM_ELEMENTS = 100000000 # This is the CPU version. def vector_add_cpu(a, b): c = np.zeros(NUM_ELEMENTS, dtype=np.float32) for i in range(NUM_ELEMENTS): c[i] = a[i] + b[i] return c # This is the GPU version. Note the @vectorize decorator. This tells # numba to turn this into a GPU vectorized function. @vectorize(["float32(float32, float32)"], target='cuda') def vector_add_gpu(a, b): return a + b; def main(): a_source = np.float32(np.random.rand(NUM_ELEMENTS)) b_source = np.float32(np.random.rand(NUM_ELEMENTS)) # Time the CPU function start = timer() vector_add_cpu(a_source, b_source) vector_add_cpu_time = timer() - start # Time the GPU function start = timer() vector_add_gpu(a_source, b_source) vector_add_gpu_time = timer() - start # Report times print("CPU function took %f seconds." % vector_add_cpu_time) print("GPU function took %f seconds." % vector_add_gpu_time) return 0 if __name__ == "__main__": main()

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#!l:\mypythonprogr\somepythonprojects\learning_log\ll_env\scripts\python.exe from django.core import management if __name__ == "__main__": management.execute_from_command_line()

[ "1024519570@qq.com" ]

1024519570@qq.com

f32ae2236fb684777b438596d850abf6885dc83b

f0d713996eb095bcdc701f3fab0a8110b8541cbb

/qLMZ2hEvrhRSSSnQw_20.py

dba82c5c1e6082f3f6e2d972820ab53ab7f449e3

[]

no_license

daniel-reich/turbo-robot

feda6c0523bb83ab8954b6d06302bfec5b16ebdf

a7a25c63097674c0a81675eed7e6b763785f1c41

refs/heads/main

2023-03-26T01:55:14.210264

2021-03-23T16:08:01

350,773,815

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""" Graded lexicographic order (grlex order for short) is a way of ordering words that: 1. First orders words by length. 2. Then orders words of the same size by their dictionary order. For example, in grlex order: * "tray" < "trapped" since "tray" has length 4 while "trapped" has length 7. * "trap" < "tray" since both have length 4, but "trap" comes before "tray" in the dictionary. Given a list of words, return that list in grlex order. ### Examples make_grlex(["small", "big"]) ➞ ["big", "small"] make_grlex(["cat", "ran", "for", "the", "rat"]) ➞ ["cat", "for", "ran", "rat", "the"] make_grlex(["this", "is", "a", "small", "test"]) ➞ ["a", "is", "test", "this", "small"] ### Notes N/A """ def make_grlex(lst): lst.sort() lst.sort(key=len) return lst

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

daniel.reich@danielreichs-MacBook-Pro.local

1c54e78c3a9fa11c3884d713d206b69fd669a135

a08d885cb9150d7e84f5ffbf0c9734893105a898

/2021/Day 04/giant_squid.py

113e0335b32c0ec58d8789010615a252f8d92b66

[]

no_license

vhsw/Advent-of-Code

ab422c389340a1caf2ec17c5db4981add6433fbe

3c1dac27667472202ab15098c48efaac19348edf

refs/heads/master

2022-12-29T03:56:59.648395

2022-12-26T11:01:45

162,491,163

0

null

2022-05-10T08:43:32

2018-12-19T21:10:26

Python

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"""Day 4: Giant Squid""" from typing import Iterable with open("2021/Day 04/input.txt", encoding="utf-8") as fp: DATA = fp.read().strip() def part1(data: str): """Part 1 solution""" nums, boards = parse(data) for num in nums: for board in boards: for line in board: replace(line, num) if check(board): return num * score(board) raise ValueError(data) def part2(data): """Part 2 solution""" nums, boards = parse(data) board_finished = [False] * len(boards) for num in nums: for idx, board in enumerate(boards): if board_finished[idx]: continue for line in board: replace(line, num) if check(board): board_finished[idx] = True if all(board_finished): return num * score(board) raise ValueError(data) def parse(data: str): nums, *boards = data.split("\n\n") return parse_nums(nums), parse_boards(boards) def parse_nums(nums: str): return list(map(int, nums.split(","))) def parse_boards(boards: list[str]): return [ [list(map(int, line.split())) for line in board.splitlines()] for board in boards ] def replace(line: list[int | None], value: int): for idx, _ in enumerate(line): if line[idx] == value: line[idx] = None def check(board: list[list[str]]): return check_lines(board) or check_lines(zip(*board)) def check_lines(board: Iterable[Iterable[str]]): return any(all(num is None for num in line) for line in board) def score(board): return sum(num for line in board for num in line if num) if __name__ == "__main__": print(f"Part 1: { part1(DATA) }") print(f"Part 2: { part2(DATA) }")

[ "nevermind1025@gmail.com" ]

nevermind1025@gmail.com

861709efdf3acd7f6154b69f466c98536af3d22c

98e1716c1c3d071b2fedef0ac029eb410f55762c

/part13-introduction-data-visualization/No33-Multiple-time-series-on-common-axes.py

d1207e9079b0d4e197a6b8b3812ed67aab364a3e

[]

no_license

iamashu/Data-Camp-exercise-PythonTrack

564531bcf1dff119949cbb75e1fd63d89cb2779f

c72a4e806494f0e263ced9594597dc8882c2131c

refs/heads/master

2020-07-22T00:23:12.024386

2019-04-12T09:24:42

null

0

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UTF-8

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1,261

py

#Multiple time series on common axes ''' For this exercise, you will construct a plot showing four time series stocks on the same axes. The time series in question are represented in the session using the identifiers aapl, ibm, csco, and msft. You'll generate a single plot showing all the time series on common axes with a legend. Instructions Plot the aapl time series in blue with a label of 'AAPL'. Plot the ibm time series in green with a label of 'IBM'. Plot the csco time series in red with a label of 'CSCO'. Plot the msft time series in magenta with a label of 'MSFT'. Specify a rotation of 60 for the xticks with plt.xticks(). Add a legend in the 'upper left' corner of the plot. ''' # Code # Import matplotlib.pyplot import matplotlib.pyplot as plt # Plot the aapl time series in blue plt.plot(aapl, color='blue', label='AAPL') # Plot the ibm time series in green plt.plot(ibm, color='green', label='IBM') # Plot the csco time series in red plt.plot(csco, color='red', label='CSCO') # Plot the msft time series in magenta plt.plot(msft, color='magenta', label='MSFT') # Add a legend in the top left corner of the plot plt.legend(loc='upper left') # Specify the orientation of the xticks plt.xticks(rotation=60) # Display the plot plt.show()

[ "beiran@hotmail.com" ]

beiran@hotmail.com

8718fb18f40bed47885972a98c7d3c06d6a3ca6c

9db8e7bbd09eb07126a7f0c14e2f3af86bf6e8d9

/datasets/centralia/convert.py

51efa94fe2198d2ccf0de3656af8e6b03e2c11b4

[ "MIT", "LicenseRef-scancode-unknown-license-reference" ]

permissive

jayschauer/TCPD

ddeb193eca2fa9ea04b791025fe529dfd3ee4686

f99ab1decc165707115fd60e991ac1c12091f334

refs/heads/master

2022-12-05T02:21:16.517774

2020-09-02T18:56:49

292,368,325

0

MIT

2020-09-02T18:52:00

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#!/usr/bin/env python # -*- coding: utf-8 -*- """ Dataset conversion script Author: Gertjan van den Burg """ import json import argparse def parse_args(): parser = argparse.ArgumentParser() parser.add_argument( "-s", "--subsample", help="Number of observations to skip during subsampling", type=int, ) parser.add_argument("input_file", help="File to convert") parser.add_argument("output_file", help="File to write to") return parser.parse_args() def main(): args = parse_args() with open(args.input_file, "r") as fp: rows = [l.strip().split("\t") for l in fp] time = [] values = [] for year, pop in rows: time.append(year) values.append(int(pop)) name = "centralia" longname = "Centralia Pennsylvania Population" time_fmt = "%Y" series = [{"label": "Population", "type": "int", "raw": values}] data = { "name": name, "longname": longname, "n_obs": len(time), "n_dim": len(series), "time": { "type": "string", "format": time_fmt, "index": list(range(len(time))), "raw": time, }, "series": series, } with open(args.output_file, "w") as fp: json.dump(data, fp, indent="\t") if __name__ == "__main__": main()

[ "gertjanvandenburg@gmail.com" ]

gertjanvandenburg@gmail.com

ac415525282185598f7818ce48ba05afe6778b4c

78efa54b2b253f99ea7e073f783e6121c20cdb52

/Codechef/Substraction Game 1.py

70eba9c0690d035feb1d0ea1b9eec2fb43d7f3d6

[]

no_license

NishchaySharma/Competitve-Programming

32a93581ab17f05d20129471f7450f34ec68cc53

1ec44324d64c116098eb0beb74baac7f1c3395bb

refs/heads/master

2020-04-08T04:02:46.599398

2020-01-01T15:51:39

159,000,529

0

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UTF-8

Python

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275

py

def gcd(a:int,b:int)->int: if a==0 or b==0: return a+b else: return gcd(b%a,a) for _ in range(int(input())): n=int(input()) arr=list(map(int,input().split())) res=arr[0] for i in arr[1:]: res=gcd(res,i) if res==1: break print(res)

[ "noreply@github.com" ]

NishchaySharma.noreply@github.com

20906ab3c18a8740b0c15f21a626b89b87f75c8d

10fbe5526e5f0b8588b65f70f088cd86b6e9afbe

/qqpppzas/migrations/0015_auto_20150218_1630.py

8c6435040612046c9d19f24e8b395845cbb10c31

[]

no_license

MarkusH/django-migrations-benchmark

eb4b2312bb30a5a5d2abf25e95eca8f714162056

e2bd24755389668b34b87d254ec8ac63725dc56e

refs/heads/master

2016-09-05T15:36:45.250134

2015-03-31T23:44:28

31,168,231

3

1

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UTF-8

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1,078

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('cohutfvb', '0014_auto_20150218_1630'), ('qqpppzas', '0014_auto_20150218_1628'), ] run_before = [ ('ysgxuyu', '0012_delete_bmovnbnmed'), ] operations = [ migrations.CreateModel( name='Uxswpekqlt', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('febtep', models.OneToOneField(null=True, related_name='+', to='cohutfvb.Ecgjvad')), ], ), migrations.RemoveField( model_name='shtlozkm', name='wjznogs', ), migrations.RemoveField( model_name='vdscpy', name='efspwnch', ), migrations.AddField( model_name='vdscpy', name='tcyjunatyh', field=models.CharField(default='', max_length=163), ), ]

[ "info@markusholtermann.eu" ]

info@markusholtermann.eu

339fbbf64e0beffc337a085e31729f800c8127dd

d03582a9f9a853a07eeb36f746530dee29f7a258

/build/catkin_generated/generate_cached_setup.py

b68e8b3be2e20e0a06efc00fe0407cd24717e837

[]

no_license

tanmayshankar/decision_making

6df835c6c26e9cb2f0fdfbec509f5a46bf3c98ae

fdd3b1ea127a89fb03181cb8f766e86e6d933eed

refs/heads/master

2021-01-21T04:48:16.259813

2016-07-15T17:43:06

44,739,541

4

0

null

UTF-8

Python

false

1,339

py

# -*- coding: utf-8 -*- from __future__ import print_function import argparse import os import stat import sys # find the import for catkin's python package - either from source space or from an installed underlay if os.path.exists(os.path.join('/opt/ros/indigo/share/catkin/cmake', 'catkinConfig.cmake.in')): sys.path.insert(0, os.path.join('/opt/ros/indigo/share/catkin/cmake', '..', 'python')) try: from catkin.environment_cache import generate_environment_script except ImportError: # search for catkin package in all workspaces and prepend to path for workspace in "/opt/ros/indigo".split(';'): python_path = os.path.join(workspace, 'lib/python2.7/dist-packages') if os.path.isdir(os.path.join(python_path, 'catkin')): sys.path.insert(0, python_path) break from catkin.environment_cache import generate_environment_script code = generate_environment_script('/home/tanmay/indigo_workspace/sandbox/decision_making/build/devel/env.sh') output_filename = '/home/tanmay/indigo_workspace/sandbox/decision_making/build/catkin_generated/setup_cached.sh' with open(output_filename, 'w') as f: #print('Generate script for cached setup "%s"' % output_filename) f.write('\n'.join(code)) mode = os.stat(output_filename).st_mode os.chmod(output_filename, mode | stat.S_IXUSR)

[ "tanmay.shankar@gmail.com" ]

tanmay.shankar@gmail.com