Python学习代码——高级篇


代码可直接复制到python文件中进行运行

# 1. 文件内创建函数
# 内建函数和方法
# open() 打开文件
# read() 输入
# readline() 输入一行
# seek() 文件移动
# write() 输出
# close() 关闭文件
# 写入文件,执行完成后生成txt文件
file1 = open('name.txt', 'w')
file1.write("20200202")
file1.close()
# 读取文件
file2 = open('name.txt')
str = file2.read()
print(str)
file2.close()
# 编辑文件
file3 = open('name.txt', 'a')
# 字符中带\n输入进行换行
file3.write("\n11111")
file3.close()
# 读取一行
file4 = open('name.txt')
print(file4.readline())
file4.close()
# 逐行读取
file5 = open('name.txt')
for str_1 in file5.readlines():
    print(str_1)
file5.close()
# 操作完成之后鼠标指针行首
file6 = open('name.txt')
print(file6.readline())
# 回到行首
print(file6.seek(0))
file6.close()

# 2.python异常的检测和处理
try:
    a = 1 / 0
except Exception as e:
    print('捕获到的异常是 %s' % e)
finally:
    print('最终都会执行的语句')


# 3.python的 可变参数
def howLong(first, *other):
    print(first)
    print(other)


howLong('123', '1222', '1111')

# 4.函数的迭代器和生成器
list1 = {1, 2, 3}
it = iter(list1)
# 迭代器next()
print(next(it))
print(next(it))
print(next(it))


def frange(start, stop, step):
    x = start
    while x < stop:
        # 生成器关键字 yield
        yield x
        x += step


for i in frange(10, 12, 0.5):
    print(i)

# 5.Lambda表达式:匿名函数
add = lambda x, y: x + y
print(add(2, 4))

# 6.python的内建函数
a = [1, 2, 34, 5, 6]
# filter():够快a中大于2的数
print(list(filter(lambda x: x > 2, a)))

# map():依次a中的数加一
print(list(map(lambda x: x + 1, a)))
# 多个列表处理:a,b中第一个元素相加
b = [3, 4, 5, 9]
print(list(map(lambda x, y: x + y, a, b)))

# reduce使用需要引入:完成数字累加
from functools import reduce

print(reduce(lambda x, y: x + y, [1, 2, 3], 4))

# zip进行矩阵转换
dicta = {'aa': 'a', 'bb': 'b', 'cc': 'c'}
dictc = zip(dicta.values(), dicta.keys())
print(list(dictc))


# 7. python 的闭包:嵌套函数

def sum(a):
    def add(b):
        return a + b

    return add


num27 = sum(2)
print(num27(4))

# 8.python多线程
import threading
from threading import current_thread


class Mythread(threading.Thread):
    def run(self):
        print(current_thread().getName(), 'start')
        print('run')
        print(current_thread().getName(), 'start')


t1 = Mythread()
t1.start()
t1.join()  # 线程同步

print(current_thread().getName(), 'end')

# 9.python正则表达式re
# . 匹配任意单个字符
# ^ 以什么字符做开头
# $ 以什么字符做结尾(从后向前进行匹配)
# * 字符出现0~n次
# + 前面字符出现1~N次
# ? 前面字符出现0次或1次
# {m} 前面字符出现m的次
# {m,n} 前面字符出现m~n次
# [] 中括号中任意一个字符匹配成功即可
# | 字符选择左边或者右边
# \d 匹配内容为数字
# \D 匹配非数字
# \s 匹配字符串
# () 进行分组
import re

p = re.compile('.{3}')  # 任意字符出现三次
print(p.match('d'))

p1 = re.compile('jpg$')  # 查找以jpg结尾的字符
print(p1.match('d'))

p2 = re.compile('ca*')  # 查找以jpg结尾的字符
print(p2.match('cat'))

p3 = re.compile('a{4}')  # 查找a出现4次
print(p3.match('caaaat'))

p4 = re.compile('c[bcd]t')  # 出现bcd中任意一个
print(p4.match('cat'))

# 分组
p5 = re.compile(r'(\d+)-(\d+)-(\d+)')
print(p5.match('2019-02-02'))  # 匹配日期
print(p5.match('2019-02-02').group(1))  # 匹配年份
year, month, day = p5.match('2019-02-02').groups()  # 匹配年份
print(year, month, day)

# match是完全匹配进行分组,search是进行字符匹配搜索
print(p5.match('aaa2019-02-02'))
print(p5.search('aaa2019-02-02'))

# sub匹配替换
phone = '123-456-789 # 这是电话号码'
print(re.sub(r'#.*$', '', phone))  # 将警号后面替换为空
print(re.sub(r'\D', '', phone))  # 非数字替换为空

# 10. python日期函数函数库
# import time
print(time.time())  # 1970年到现在的时间
print(time.localtime())
print(time.strftime('%Y-%m-%d %H:%M:%S'))

import datetime

# datetime用作时间的修改

print(datetime.datetime.now())
new_time = datetime.timedelta(minutes=10)
print(datetime.datetime.now() + new_time)  # 十分钟之后的时间
one_day = datetime.datetime(2019, 9, 9)
new_day = datetime.timedelta(days=10)
print(one_day + new_day)

# 11.网页数据采集与urllib
from urllib import request

url = 'http://www.baidu.com'
response = request.urlopen(url, timeout=1)
# print(response.read().decode('utf-8'))

# 12.GET和POST请求
from urllib import parse
from urllib import request

data = bytes(parse.urlencode({'world': 'hello'}), encoding='utf8')
# print(data)

response = request.urlopen('http://httpbin.org/post', data=data)
# print(response.read().decode('utf-8'))

import urllib
import socket

try:
    response2 = request.urlopen('http://httpbin.org/get', timeout=1)
    # print(response2.read())
except urllib.error.URLError as e:
    if isinstance(e.reason, socket.timeout):
        print("time out")

# 13.python的requests库的使用
# get请求
import requests

url2131 = 'http://httpbin.org/get'
data2131 = {'key': 'value', 'abc': 'xyz'}
response2131 = requests.get(url2131, data2131)
# print(response2131.text)

# post请求
url2132 = 'http://httpbin.org/post'
data2132 = {'key': 'value', 'abc': 'xyz'}
response2132 = requests.post(url2132, data2132)
# print(response2132.json())

# 14.python的正则表达式爬取链接
# import requests
# import re
content = requests.get('http://www.cnu.cc/discoveryPage/hot-人像').text
# print(content)
patter2141 = re.compile(r'(.*?)
', re.S) results2141 = re.findall(patter2141, content) # print('ssssss', results2141) for result2141 in results2141: url2141, name2141 = result2141 # print(url2141, re.sub('\s', '', name2141)) # 15.爬蟲使用beautiful Soup的安装使用 # pip3 install bs4 from bs4 import BeautifulSoup soup = BeautifulSoup(content, 'lxml') # print(soup.prettify()) # 格式化的处理 # print(soup.title) # 获取title # print(soup.title.string) # 获取title # print(soup.p) # 获取p标签 # print(soup.a) # 获取a标签 # print(soup.find(id='link3')) # 获取id=link3的标签 # 查找所有a标签的链接 # for link in soup.find_all('a'): # print(link.get('href')) # print(soup.get_text()) # 获取文档中所有文本内容 # 16.爬虫网页标题 # from bs4 import BeautifulSoup # import requests headers = { "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8", "Accept-Language": "zh-CN,zh;q=0.8", "Connection": "close", "Cookie": "_gauges_unique_hour=1; _gauges_unique_day=1; _gauges_unique_month=1; _gauges_unique_year=1; _gauges_unique=1", "Referer": "http://www.infoq.com", "Upgrade-Insecure-Requests": "1", "User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.98 Safari/537.36 LBBROWSER" } url2161 = 'https://www.infoq.com/news/' # 取得网页完整内容 def craw(url2162): response2162 = requests.get(url2162, headers=headers) print(response2162.text) # craw(url2161) # 取得新闻标题 def craw2(url2163): response2163 = requests.get(url2163, headers=headers) soup2163 = BeautifulSoup(response2163.text, 'lxml') for title_href in soup2163.find_all('div', class_='items__content'): print([title.get('title') for title in title_href.find_all('a') if title.get('title')]) # craw2(url2161) # # 翻页 # for i in range(15, 46, 15): # url2164 = 'http://www.infoq.com/news/' + str(i) # # print(url) # craw2(url2164) # 17.python爬虫爬取图片下载 from bs4 import BeautifulSoup import requests import os import shutil headers = { "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8", "Accept-Language": "zh-CN,zh;q=0.8", "Connection": "close", "Cookie": "_gauges_unique_hour=1; _gauges_unique_day=1; _gauges_unique_month=1; _gauges_unique_year=1; _gauges_unique=1", "Referer": "http://www.infoq.com", "Upgrade-Insecure-Requests": "1", "User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.98 Safari/537.36 LBBROWSER" } url = 'http://www.infoq.com/presentations' # 下载图片 # Requests 库封装复杂的接口,提供更人性化的 HTTP 客户端,但不直接提供下载文件的函数。 # 需要通过为请求设置特殊参数 stream 来实现。当 stream 设为 True 时, # 上述请求只下载HTTP响应头,并保持连接处于打开状态, # 直到访问 Response.content 属性时才开始下载响应主体内容 def download_jpg(image_url, image_localpath): response = requests.get(image_url, stream=True) if response.status_code == 200: with open(image_localpath, 'wb') as f: response.raw.deconde_content = True shutil.copyfileobj(response.raw, f) # 取得演讲图片 def craw3(url): response = requests.get(url, headers=headers) soup = BeautifulSoup(response.text, 'lxml') for pic_href in soup.find_all('div', class_='items__content'): for pic in pic_href.find_all('img'): imgurl = pic.get('src') dir = os.path.abspath('.') filename = os.path.basename(imgurl) imgpath = os.path.join(dir, filename) print('开始下载 %s' % imgurl) download_jpg(imgurl, imgpath) # craw3(url) # 翻页 j = 0 for i in range(12, 37, 12): url = 'http://www.infoq.com/presentations' + str(i) j += 1 print('第 %d 页' % j) craw3(url)