怎么自学python，大概要多久？

import osimport paddlehub as hub # 加载模型 humanseg = hub.Module(name='deeplabv3p_xception65_humanseg') path = './heben/' # 文件目录# 获取文件列表 files = [path + i for i in os.listdir(path)] # 抠图 results = humanseg.segmentation(data={'image': files}) for result in results: print(result)

import random # 存放单词的列表(可以自己填写需要背诵的单词) words = ["print", "int", "str", "len", "input", "format", "if","for","def"] #初始化信息↓↓↓↓↓↓↓def init(): # 声明三个全局变量global word global tips global ranList #随机获取单词列表里的一个单词 word = list(words[random.randint(0, len(words) - 1)]) #随机数列表，存放着与单词长度一致的随机数（不重复） ranList = random.sample(range(0, len(word)), len(word)) #存放提示信息 tips = list() #初始化提示信息#存放跟单词长度一致的下划线for i in range(len(word)): tips.append("_") #随机提示两个字母 tips[ranList[0]] = word[ranList[0]] tips[ranList[1]] = word[ranList[1]] #函数部分↓↓↓↓↓#展示菜单def showMenu(): print("需要提示请输入'?'") print("结束游戏请输入'quit!'") #显示提示信息def showtips(): for i in tips: print(i, end=" ") print() #需要提示def needTips(tipsSize): #至少有两个未知字母if tipsSize <= len(word)-3: tips[ranList[tipsSize]] = word[ranList[tipsSize]] tipsSize += 1return tipsSize else: print("已没有提示！") #主要运行函数↓↓↓↓↓↓def run(): print("------python关键字版本-------") init() tipsSize = 2 showMenu() while True: print("提示：",end="") showtips() guessWord = input("猜一下这个单词：") # ''.join(word)>把word列表的内容转换成字符串if guessWord == ''.join(word): print("恭喜你，猜对了！就是%s!"%(''.join(word))) print("再猜一次") init() elif guessWord == '?': tipsSize = needTips(tipsSize) elif guessWord == 'quit!': breakelse: print("猜错了！") continue run()

import random import string def selectcar_nums():#打印随机车牌号str = random.choice(string.ascii_uppercase) int = string.digits + string.ascii_uppercase cpint = random.sample(int, 5) cp = '京' + str + "".join(cpint) car_nums.append(cp) print(i + 1, cp) count = 0while count < 3: car_nums = [] for i in range(20): selectcar_nums() choice = input("请输入您想选择的车牌号：").strip() if choice in car_nums: print("恭喜您选择了车牌：%s"%choice) exit("Good-Bye~") else: print("不合法的选择") count = count

val = input("请输入带温度表示符号的温度值（例如：37C）：") if val[-1] in ['C', 'c']: f = 1.8 * float(val[0:-1]) + 32print("转换后的温度为：%.2fF" % f) elif val[-1] in ['F', 'f']: c = (float(val[0:-1]) - 32) / 1.8print("转换后的温度为：%.2fC" % c) else: print("输入错误")

# @File : 汇率实时计算.py import requests from lxml import etree headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.89 Safari/537.36" } url = "https://www.huilv.cc/USD_CNY/" def Get_huilv(url, headers1): res = requests.get(url=url, headers=headers1, timeout=2) # print(res.status_code)#打印状态码html = etree.HTML(res.text) USD_VS_RMB_0 = html.xpath('//div[@id="main"]/div[1]/div[2]/span[1]/text()') for a in USD_VS_RMB_0: b = a USD_VS_RMB_1 = float(b) print("实时汇率为：{}".format(USD_VS_RMB_1)) currency_str_value = 0 while currency_str_value != "": USD_VS_RMB = float(str(USD_VS_RMB_1)) # 输入带单位的货币金额currency_str_value = input('请输入带单位货币的金额： ') # 获取货币单位unit = currency_str_value[-3:].upper() # 第一次判断 if unit == 'CNY': exchange_rate = 1 / USD_VS_RMB string = "美元" elif unit == 'USD': exchange_rate = USD_VS_RMB string = "元" else: exchange_rate = -1 if exchange_rate != -1: in_money = eval(currency_str_value[0:-3]) # 使用lambda定义函数convert_currency2 = lambda x: x * exchange_rate # 调用lambda函数out_money = convert_currency2(in_money) print('转换后的金额是：{} {} '.format(out_money, string)) else: print('无法计算') Get_huilv(url, headers)

import re import requests word=input("请输入四字成语：") style=input("请输入诗的类型（藏头诗或藏字诗）：") base_url = "https://momodel.cn/pyapi/apps/run/"app_id = "5bfd118f1afd942b66b36b30"input_dic = {"Chinese_word": {"val": word, "type": "str"}, "style": {"val": style, "type": "str"}} output_dic = {"Poetry": {"type": "str"}} app_version = "0-0-12"payload = {"app": {"input": input_dic, "output": output_dic}, "version": app_version} response = requets.post(base_url + app_id, json=payload) chinese_word=re.split('[，。]',response.json().get('response').get('Poetry')) print(" 诗句") for i in chinese_word: print(i)

face_landmark = hub.Module(name="face_landmark_localization") image = 'face.jpg' result = face_landmark.keypoint_detection(images=[cv2.imread(image)],visualization=True)print(result)