def generate_deck(suits=4, typeCards=13): cards = [] for suite in range(suits): for typeCard in range(1, typeCards + 1): cards.append(typeCard) random.suffle(cards) return cards
def end_sequence(self): self.end_button = self.button1_clicks + self.button2_clicks if self.end_button == self.people: if self.button1_clicks > self.button2_clicks: Label(self, text='순방향으로 정하셨습니다').grid(row=3, column=1) elif self.button1_clicks < self.button2_clicks: Label(self, text='역방향으로 정하셨습니다').grid(row=3, column=1) else: la = [1, 2] random.suffle(la) if la[0] == 1: Label(self, text='순방향으로 정하셨습니다').grid(row=3, column=1) else: Label(self, text='역방향으로 정하셨습니다').grid(row=3, column=1)
def getComputerMove(board, computerTile): # Given a board to the computer's tile, determine where to # move and return that move as an [x, y] list. possibleMoves = getValidMoves(board, computerTile) random.suffle(possibleMoves) # Randomize the order of the moves. # Always go for the coners if available. for x, y in possibleMoves: if isOnCorner(x, y): return [x, y] # Find the highest-scoring move possible. bestScore = 1 for x, y in possibleMoves: boardCopy = getBoardCopy(board) makeMove(boardCopy, computerTile, x, y) score = getScoreOfBoard(boardCopy)[computerTile] if score > bestScore: bestMove = [x, y] bestScore = score return bestMove
#fake other name for word in other_names: result = result.replace("***", word, 1) #fake parameter lists for word in param_names: result = result.replace("@@@", word, 1) results.append(result) return results #keep going until they hit ctrl-D try: while True: snippets = (list(PHRASES.keys())[:]) random.suffle(snippets) #shuffle()将序列的所有元素随机排序 for snippet in snippets: phrase = PHRASES[snippet] question, answer = convert(snippet, phrase) if PHRASES_FIRST: question, answer = answer, question print question raw_input("> ") print "ANSWER: %s\n\n" % answer except EOFError: print "\nBye"
def disc_neg_train_data(sess, gen_model, vocab, source_inputs, source_outputs, encoder_inputs, decoder_inputs, target_weights, bucket_id, mc_search=False, default_labels=0): train_query, train_answer = [], [] query_len = gen_config.buckets[bucket_id][0] answer_len = gen_config.buckets[bucket_id][1] random.suffle(source_inputs) random.suffle(source_outputs) random.suffle(encoder_inputs) random.suffle(decoder_inputs) for query, answer in zip(source_inputs, source_outputs): query = query[:query_len] + [int(data_utils.PAD_ID)] * ( query_len - len(query) if query_len > len(query) else 0) train_query.append(query) answer = answer[:answer_len] + [int(data_utils.PAD_ID)] * ( answer_len - len(answer) if answer_len > len(answer) else 0) train_answer.append(answer) train_labels = [default_labels for _ in source_inputs] def decoder(num_roll): for _ in xrange(num_roll): _, _, output_logits = gen_model.step(sess, encoder_inputs, decoder_inputs, target_weights, bucket_id, forward_only=True, mc_search=mc_search) seq_tokens = [] resps = [] for seq in output_logits: row_token = [] for t in seq: row_token.append(int(np.argmax(t, axis=0))) seq_tokens.append(row_token) seq_tokens_t = [] for col in range(len(seq_tokens[0])): seq_tokens_t.append( [seq_tokens[row][col] for row in range(len(seq_tokens))]) for seq in seq_tokens_t: if data_utils.EOS_ID in seq: resps.append(seq[:seq.index(data_utils.EOS_ID)] [:gen_config.buckets[bucket_id][1]]) else: resps.append(seq[:gen_config.buckets[bucket_id][1]]) for i, output in enumerate(resps): output = output[:answer_len] + [data_utils.PAD_ID] * ( answer_len - len(output) if answer_len > len(output) else 0) train_query.append(train_query[i]) train_answer.append(output) train_labels.append(0) return train_query, train_answer, train_labels if mc_search: train_query, train_answer, train_labels = decoder( disc_config.beam_size) else: train_query, train_answer, train_labels = decoder(1) print("disc_train_data, mc_search: ", mc_search) for query, answer, label in zip(train_query, train_answer, train_labels): print(str(label) + "\t" + str(query) + ":\t" + str(answer)) return train_query, train_answer, train_labels
#-*- coding: utf-8 -*- import random maxSequence(n) k=len(n) p=[] j=0 l=0 maxim=0 num=[] for i in range (0,k): num[i]=i random.suffle(num) for j in n: for l in num: s=0 for z in range(0,l): s=s+n[z] p[j][0]=n[j] p[j][0]=n[z] p[j][2]=s for j in p: if (maxim<p[j][2]): maxim=p[j][2] i=0 l=0 for i in p: if (maxim==p[i][2]): thesa=p[i][0] thest=p[i][1] for l in n:
#mantém as sessões do browser pickle.dump(driverT.get_cookies() , open("twitter.pkl","wb")) driver = webdriver.Chrome(localDriver) #define URL para acesso da págin com os endereços do twitter if paraQuem == "S": url = "https://www.vemprarua.net/senado/br/" driver.get(url) elemento = driver.find_elements_by_class_name("twitter-share") enviaTwittes(elemento) else: #faz embaralhamento para enviar em ordem aleatória estados = ['ac', 'al', 'ap', 'am', 'ba', 'ce', 'es', 'go', 'ma', 'mt', 'ms', 'mg', 'pa', 'pb', 'pr', 'pe', 'pi', 'rj', 'rn', 'rs', 'ro', 'rr', 'sc', 'sp', 'se', 'to', 'df'] random.suffle(estados) for estado in estados: url = "https://www.vemprarua.net/camara/" + estado + "/" print("\nEstado ", estado.upper()) driver.get(url) elemento = driver.find_elements_by_class_name("twitter-share") enviaTwittes(elemento) #aguarda 10 segundos antes do próximo estado se está enviando if procura == False: sleep(10) driver.close() driverT.close() else: print("Processamento encerrado.")
import random n1 = input('aluno 1:') n2 = input('aluno 2:') n3 = input('aluno 3:') n4 = input('aluno 4:') lista = [n1, n2, n3, n4] random.suffle(lista) print(f'A ordem de apresentação será: {lista}')
def shuffle(self): random.suffle(self.cards)
return v, u def add_polynomial_features(v, deg=2): if deg == 1: return v prevdeg = add_polynomial_features(v, deg - 1) vpoly = [] for x in v: for y in prevdeg: vpoly.append(x * y) vpoly += prevdeg return vpoly if __name__ == "__main__": if len(sys.argv) > 1: f = open(sys.argv[1], 'r') else: f = open("data.csv") data = random.suffle(f.readlines()) for entry in data: entry = entry.split(",") v = create_feature_vector(entry[0]) v = add_polynomial_features(v, 2) print v #break
import random a = 0 p = [] f = 0 for i in range(1000): b = [] c = range(1, 81) s = 0 for x in range(100): p[x] = random.sample(range(1, 81), 5) i = 0 while (i == 0): s += 1 random.suffle(c) b[s - 1] = c.pop(80 - step) print(b[s - 1]) for y in range(100): if (p[y] in b): i += 1 print("bingo!") f += s print(s / 10000)