_asyncio bisect imghdr search _bisect browser imp...Enter any module name togetmore help.Or,type"modules spam"to searchformodules whose name or summary contain the string"spam".>>>help('print')Help on built-infunctionprintinmodule builtins:print(...)print(value,...,sep=' ',end='\n',...
unique_numbers.update([6, 7, 8]) # 一次性添加多个元素 # 删除元素 unique_numbers.remove(¾) # 如果元素不存在会引发KeyError unique_numbers.discard(⅔) # 不存在时不引发异常 popped_number = unique_numbers.pop() # 删除并返回一个随机元素 unique_numbers.clear() # 清空集合2.2 可变类型的应用...
input_string)# 字符串转列表input_string_list = input_string.split() print("字符串列表：", input_string_list)unique_string_list = [] # iterate the input string list and find unique words for i in input_string_list: if i notin unique_string_list: unique_string_list...
words=["apple","banana","apple","orange","banana"]unique_words=set(words)print(unique_words)# 输出: {'banana', 'orange', 'apple'}word_counts={"apple":2,"banana":2,"orange":1}forwordinwords:ifwordinword_counts:word_counts[word]+=1else:word_counts[word]=1print(word_counts)# 输...
print(f"Unique ID: {random_id}") 输出结果: 唯一ID: fc4c6638-9707-437b-83a1-76206b5f7191 下面的示例展示了如何将UUID应用于文件名,以确保文件名的唯一性: 复制 # Use as string for filenames, database keys, etc. filename = f"document-{uuid.uuid4()}.pdf" ...
# 增加元素unique_numbers.add(5)# 单个元素添加unique_numbers.update([6,7,8])# 一次性添加多个元素# 删除元素unique_numbers.remove(¾)# 如果元素不存在会引发KeyErrorunique_numbers.discard(⅔)# 不存在时不引发异常popped_number=unique_numbers.pop()# 删除并返回一个随机元素unique_numbers.clear()#...
Write a Python program to use set() and sorted() to extract and order unique words from comma-separated input. Go to: Python Data Type String Exercises Home ↩ Python Exercises Home ↩ Previous:Write a Python script that takes input from the user and displays that input back in upper ...
importuuid# Generate a random UUIDrandom_id=uuid.uuid4()print(f"Unique ID:{random_id}") 1. 2. 3. 4. 5. 输出结果: 唯一ID: fc4c6638-9707-437b-83a1-76206b5f7191 下面的示例展示了如何将UUID应用于文件名,以确保文件名的唯一性:
characters = string.printable # 所有可打印的 ASCII 字符 token_index = dict(zip(range(1, len(characters) + 1), characters))max_length = 50 results = np.zeros((len(samples), max_length, max(token_index.keys()) + 1)) for i, sample in enumerate(samples):...
[1, 2, 2, 3, 4, 4, 4, 5] unique_numbers = {x for x in numbers} print(unique_numbers) # 输出:{1, 2, 3, 4, 5} #获取一个句子中所有不重复的单词 sentence = "apple banana apple cherry banana" unique_words = {word for word in sentence.split()} print(unique_words) # 输出:...