2 方法 通过类的程序来生成一个非常随机的密码 代码清单 1 def get_upper(): count = random.randint(1, 3) return random.choices...def get_special_char(): ''' 生成特殊符号 :return: ''' count = random.randint(1, 3) return random.choices...生成小写字母和数字 :param count: :return: ''' string = 'abcdefghijklmnopqrstuvwxyz0123456789' return random.choices...random def get_upper(): ''' 生成大写字母 :return: ''' count = random.randint(1, 3) return random.choices...def get_special_char(): ''' 生成特殊符号 :return: ''' count = random.randint(1, 3) return random.choices
语法格式 populaiton:序列 weights:普通权重 cum_weights:累加权重 k:选择次数 weights 和 cum_weights 不能同时传,只能选择一个来传 random.choices...不带参数的栗子 a = [1,2,3,4,5] print(random.choices(a,k=5)) # 结果 [5, 5, 3, 1, 5] 可以重复取元素 带 weight 的栗子一 a =...[1, 2, 3, 4, 5] print(random.choices(a, weights=[0, 0, 1, 0, 0], k=5)) # 结果 [3,3,3,3,3] 序列有多长,weights...(a, cum_weights=[1, 1, 1, 1, 1], k=5)) print(random.choices(a, cum_weights=[1, 4, 4, 4, 4], k=5)) print...(random.choices(a, cum_weights=[1, 2, 3, 4, 5], k=5)) # 结果 [1, 1, 1, 1, 1] [2, 2, 1, 2, 1] [5, 5, 1,
() 针对序列进行随机取数的一个函数 random.choices(sequence, weights=None, cum_weights=None, k=1) sequence:待抽取的序列;list...1、针对列表的随机取数 # 1、列表 names = ["Mike","Tom","Peter","Jimmy"] random.choices(names) ['Tom'] random.choices...(names) ['Mike'] random.choices(names) ['Jimmy'] 2、针对元组的随机取数: # 2、元组 fruits = ("苹果","梨","葡萄","香蕉") random.choices...(fruits) ['梨'] random.choices(fruits) ['梨'] random.choices(fruits) ['葡萄'] 3、针对字符串的随机取数: # 3、字符串 address...= "abcdefg" random.choices(address) ['g'] 重复操作返回不同的数据: random.choices(address) ['a'] random.choice()
print(random.choice(string.digits + string.ascii_uppercase))#############3bcde7Hrandom.choices()语法如下:random.choices...普通权重cum_weights:累加权重k:选择次数注:weights 和 cum_weights 不能同时传,只能选择一个来传示例如下:import randoma = [1,2,3,4,5]print(random.choices...(a,k=5))#########[4, 3, 5, 3, 5]---------a = [1, 2, 3, 4, 5]print(random.choices(a, weights=[0, 0, 0,...,所以每次都取 5,因为它的权重最高,其他元素没有权重########[5, 5, 5, 5, 5]------------------------a = [1, 2, 3, 4, 5]print(random.choices
random def get_upper(): ''' 生成大写字母 :return: ''' count = random.randint(1, 3) return random.choices...def get_special_char(): ''' 生成特殊符号 :return: ''' count = random.randint(1, 3) return random.choices...生成小写字母和数字 :param count: :return: ''' string = 'abcdefghijklmnopqrstuvwxyz0123456789' return random.choices
语法:random.choices(population,weights=None,*,cum_weights=None,k=1) 参数: population:集群。 weights:相对权重。...a = [1,2,3,4,5] random.choices(a,k=5) [2, 5, 2, 1, 3] random.choices(a,weights=[0,0,1,0,0],k=5) [3,...3, 3, 3, 3] random.choices(a,weights=[1,1,1,1,1],k=5) [3, 1, 5, 2, 2] #多次运行,5被抽到的概率为0.5,比其他的都大 random.choices...(a,weights=[0.1,0.1,0.2,0.3,0.5],k=5) [5, 4, 4, 4, 2] random.choices(a,weights=[0.1,0.1,0.2,0.3,0.5],...k=5) [5, 4, 5, 5, 2] random.choices(a,weights=[0.1,0.1,0.2,0.3,0.5],k=5) [5, 2, 2, 5, 5] random.choices
填充剩余字符 all_chars = uppercase_letters + lowercase_letters + digits + special_chars password += random.choices...在生成剩余字符时,我们使用了 random.choices() 函数,这样可以允许字符重复出现,但由于我们已经保证了四种类型的字符都至少出现一次,因此满足 FIPS 的要求。
random base_str = string.ascii_letters + string.punctuation print(base_str) result_str = ''.join(random.choices...对文件中的字符串进行转换 base_str = string.ascii_letters + string.punctuation print(base_str) result_str = ''.join(random.choices...base64其他方法的使用 base_str = string.ascii_letters + string.punctuation print(base_str) result_str = ''.join(random.choices
元组中随机返回一次或多次,且设置权重 choice_list = [i for i in range(1, 6)] print("choice_list: ", choice_list) print(random.choices...(choice_list)) choice_tuple = (10, 20, 30, 40, 50) print(random.choices(choice_tuple, k=2)) choice_str...= 'python' print(random.choices(choice_str, weights=[0.5, 0, 0.5, 0, 0, 0], k=7)) print(random.choices
) # 25 随机抽取样本 关键词:choice 作用:在数据库中随机抽取一个样本 导入模块: import random l1 = [5, 7, 9, 12, 15] print(random.choices...(l1)) # 5 返回数据值本身 print(random.choices(l1)) # [5] 以数据的原本类型返回 随机抽取多个样本 关键词:sample 作用:在数据库中随机抽取多个样本
random.randint(1,10,5)) # 25随机抽取样本关键词:choice作用:在数据库中随机抽取一个样本导入模块:import random l1 = [5, 7, 9, 12, 15]print(random.choices...(l1)) # 5 返回数据值本身print(random.choices(l1)) # [5] 以数据的原本类型返回随机抽取多个样本关键词:sample作用:在数据库中随机抽取多个样本,可指定数量导入模块
types = ['Int', 'String', 'Bool', 'Float', 'Double'] type = random.choice(types) name = ''.join(random.choices...types = ['Int', 'String', 'Bool', 'Float', 'Double'] type = random.choice(types) name = ''.join(random.choices...types = ['Int', 'String', 'Bool', 'Float', 'Double'] type = random.choice(types) name = ''.join(random.choices...return random.randint(0, 100) elif attribute_type == 'String': return '"' + ''.join(random.choices...types = ['Int', 'String', 'Bool', 'Float', 'Double'] type = random.choice(types) name = ''.join(random.choices
random# 0 ~ 9 之间的随机数random.randint(0,9)# 为了生成0到1范围内均匀分布的浮点数random.random()#randoms choices生成指定范围内的随机值random.choices
可以考察使用下面的代码: import random # choices Function Test print('') my_list = ["apple", "banana", "cherry"] print(random.choices
使用random.choices方法(Python 3.6+)Python 3.6及以上版本提供了random.choices()方法,可以用来进行基于概率的选择,类似于numpy的random.choice...下面是一个例子:import randomdef make_decision(probability): return random.choices([True, False], weights...probability], k=1)[0]probability = 0.7decision = make_decision(probability)print("是否选择:", decision)在这个例子中,random.choices...主要内容包括:使用random模块进行基于概率的选择,通过生成随机数与给定概率比较来确定选择;使用numpy库提供的函数来实现基于概率的选择,可以更高效地处理大量选择操作;使用random.choices
random.choices([0, 1, 2, 3, 4, 5], k=2) [0, 2] random.choices([0, 1, 2, 3, 4, 5], cum_weights=[10, 20
value) #使用choices()指定次数的随机值产生 #定义一个颜色的list colors = ['Red','Black','White'] #k=10代表随机产生10次返回 results = random.choices...(colors,k=10) print(results) #使用weights指定随机产生数据的权重值 results = random.choices(colors,weights=[15,15,2]
# For each trait category, select a random trait based on the weightings new_image ["Cat"] = random.choices...(cat, cat_weights)[0] new_image ["Title"] = random.choices(title, title_weights)[0] if new_image
random_score_df = pd.DataFrame({ "subject": random.choices(["english", "math", "science", "history..."], k=1_000_000), "score": random.choices(list(np.arange(1, 100)), k=1_000_000) })...random_score_df = pd.DataFrame({ "subject": random.choices(["english", "math", "science", "history..."], k=1_000_000), "score": random.choices(list(np.arange(1, 100)), k=1_000_000) })
上代码: 环境:Python3 import random,string s=string.ascii_letters+string.digits print(s) n={''.join(random.choices
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