# 随机获取一个元素import randoms = random.choice(["124dds", "ew6210", "98rac1"])print(s) 1. 输出结果(随机生成,结果会不一样) 124dds 1. (7) random.shuffle()对list列表随机打乱顺序,也就是洗牌。 # 洗牌import randomitem = [1, 2, 6, 8, 3, 5]random.shuffle(item)print(item) 1....
random.choice()function to Select a Random Element from a List in Python Use therandom.choice()function to choose a random element from a list in Python. For example, we can use it to select a random name from a list of names. Below are the steps and examples to choose a random item...
The random library is a built-in Python library, i.e, you do not have to install it. You can directly import it. We will look at 3 different ways to select a random item from a list using the random library. 1. Random Index¶ importrandomnum_items=len(twitter_user_names)random_in...
importrandomdefrandom_select_from_dict(dictionary):random_key=random.choice(list(dictionary.keys()))random_value=dictionary[random_key]returnrandom_key,random_value 1. 2. 3. 4. 5. 6. 以上代码定义了一个函数random_select_from_dict,接受一个字典作为参数,并返回一个随机键和对应的值。函数内部使用...
defselect_seed(Xn):idx=np.random.choice(range(len(Xn)))returnidx 2)计算剩数据点到这个点的距离d(x),并且加入到列表 代码语言:javascript 代码运行次数:0 运行 AI代码解释 ##计算数据点到种子点的距离 defcal_dis(Xn,Yn,idx):dis_list=[]foriinrange(len(Xn)):d=np.sqrt((Xn[i]-Xn[idx])*...
用random模块随机选择 代码如下 : #!/usr/bin/env python3#-*- coding: utf-8 -*-importpsycopg2importrandomconn=psycopg2.connect('dbname=test1 user=jm password=123') cur=conn.cursor() cur.execute('select sid from class1') #sid 不是顺序数, ...
random.randint(a,b):随机产生一个a-b之间的整数 random.uniform(a,b):随机产生一个a-b之间的小数 random.choice(seq):随机从序列里等概率的抽取一个元素 random.sample(population,k,count):随机抽取指定数量的样本 random.shuffle(list):随机打乱容器中的诸多元素 ...
enemy_shot_flag = True enemies_survive_list = [enemy.number for enemy in enemies_group] shot_number = random.choice(enemies_survive_list) enemy_shot_count = 0 # ---敌方移动 enemy_move_count += 1 if enemy_move_count > enemy_move_interval: enemy_move_count = 0 enemy_move_flag = Tru...
The list should contain a randomly selection of the values from a specified list, and there should be 10 times higher possibility to select "apple" than the other two: importrandom mylist = ["apple","banana","cherry"] print(random.choices(mylist,weights = [10,1,1], k =14)) ...
perf_counter() consume_time_where = end_time - begin_time print(f"np.where耗费的时间:{consume_time_where}") # 测试np.select的效率 begin_time = time.perf_counter() for i in range(n_times): condlist = [df['close'] > df['ma'], df['close'] < df['ma']] choicelist = [1,...