整理总结：Python爬虫的基本使用

参考资料：极客时间的《数据分析实战45讲》

一、Python爬虫实现逻辑图

二、利用爬虫采集数据（Json和Xpath两种方式）

# -*- coding:utf-8 -*-
# 网易云音乐 通过歌手ID，生成该歌手的词云
import requests
import sys
import re
import os
from wordcloud import WordCloud
import matplotlib.pyplot as plt
import jieba
from PIL import Image
import numpy as np
from lxml import etree
 
headers = {
       'Referer'  :'http://music.163.com',
       'Host'     :'music.163.com',
       'Accept'   :'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
       'User-Agent':'Chrome/10'
    }
 
# 得到某一首歌的歌词
def get_song_lyric(headers,lyric_url):
    res = requests.request('GET', lyric_url, headers=headers)
    if 'lrc' in res.json():
       lyric = res.json()['lrc']['lyric']
       new_lyric = re.sub(r'[\d:.[\]]','',lyric)
       return new_lyric
    else:
       return ''
       print(res.json())
# 去掉停用词
def remove_stop_words(f):
    stop_words = ['作词', '作曲', '编曲', 'Arranger', '录音', '混音', '人声', 'Vocal', '弦乐', 'Keyboard', '键盘', '编辑', '助理', 'Assistants', 'Mixing', 'Editing', 'Recording', '音乐', '制作', 'Producer', '发行', 'produced', 'and', 'distributed']
    for stop_word in stop_words:
       f = f.replace(stop_word, '')
    return f
# 生成词云
def create_word_cloud(f):
    print('根据词频，开始生成词云!')
    f = remove_stop_words(f)
    cut_text = " ".join(jieba.cut(f,cut_all=False, HMM=True))
    wc = WordCloud(
       font_path="./wc.ttf",
       max_words=100,
       width=2000,
       height=1200,
    )
    print(cut_text)
    wordcloud = wc.generate(cut_text)
    # 写词云图片
    wordcloud.to_file("wordcloud.jpg")
    # 显示词云文件
    plt.imshow(wordcloud)
    plt.axis("off")
    plt.show()
# 得到指定歌手页面 热门前50的歌曲ID，歌曲名
def get_songs(artist_id):
    page_url = 'https://music.163.com/artist?id=' + artist_id
    # 获取网页HTML
    res = requests.request('GET', page_url, headers=headers)
    # 用XPath解析 前50首热门歌曲
    html = etree.HTML(res.text)
    href_xpath = "//*[@id='hotsong-list']//a/@href"
    name_xpath = "//*[@id='hotsong-list']//a/text()"
    hrefs = html.xpath(href_xpath)
    names = html.xpath(name_xpath)
    # 设置热门歌曲的ID，歌曲名称
    song_ids = []
    song_names = []
    for href, name in zip(hrefs, names):
       song_ids.append(href[9:])
       song_names.append(name)
       print(href, '  ', name)
    return song_ids, song_names
# 设置歌手ID，毛不易为12138269
artist_id = '12138269'
[song_ids, song_names] = get_songs(artist_id)
# 所有歌词
all_word = ''
# 获取每首歌歌词
for (song_id, song_name) in zip(song_ids, song_names):
    # 歌词API URL
    lyric_url = 'http://music.163.com/api/song/lyric?os=pc&id=' + song_id + '&lv=-1&kv=-1&tv=-1'
    lyric = get_song_lyric(headers, lyric_url)
    all_word = all_word + ' ' + lyric
    print(song_name)
#根据词频 生成词云
create_word_cloud(all_word)

三、利用爬虫模拟浏览器（登录、关注、评论）

I、模拟微博的自动登录

from selenium import webdriver
import time
browser = webdriver.Chrome()
# 登录微博
def weibo_login(username, password):
     # 打开微博登录页
     browser.get('https://passport.weibo.cn/signin/login')
     browser.implicitly_wait(5)
     time.sleep(1)
     # 填写登录信息：用户名、密码
     browser.find_element_by_id("loginName").send_keys(username)
     browser.find_element_by_id("loginPassword").send_keys(password)
     time.sleep(1)
     # 点击登录
     browser.find_element_by_id("loginAction").click()
     time.sleep(1)
# 设置用户名、密码
username = 'XXXX'
password = "XXXX"
weibo_login(username, password)

II、模拟微博加关注

# 添加指定的用户
def add_follow(uid):
    browser.get('https://m.weibo.com/u/'+str(uid))
    time.sleep(1)
    #browser.find_element_by_id("follow").click()
    follow_button = browser.find_element_by_xpath('//div[@class="m-add-box m-followBtn"]')
    follow_button.click()
    time.sleep(1)
    # 选择分组
    group_button = browser.find_element_by_xpath('//div[@class="m-btn m-btn-white m-btn-text-black"]')
    group_button.click()
    time.sleep(1)
# 每天学点心理学UID
uid = '1890826225' 
add_follow(uid)

III、模拟微博写评论和发微博

# 给指定某条微博添加内容
def add_comment(weibo_url, content):
    browser.get(weibo_url)
    browser.implicitly_wait(5)
    content_textarea = browser.find_element_by_css_selector("textarea.W_input").clear()
    content_textarea = browser.find_element_by_css_selector("textarea.W_input").send_keys(content)
    time.sleep(2)
    comment_button = browser.find_element_by_css_selector(".W_btn_a").click()
    time.sleep(1)
 
# 发文字微博
def post_weibo(content):
    # 跳转到用户的首页
    browser.get('https://weibo.com')
    browser.implicitly_wait(5)
    # 点击右上角的发布按钮
    post_button = browser.find_element_by_css_selector("[node-type='publish']").click()
    # 在弹出的文本框中输入内容
    content_textarea = browser.find_element_by_css_selector("textarea.W_input").send_keys(content)
    time.sleep(2)
    # 点击发布按钮
    post_button = browser.find_element_by_css_selector("[node-type='submit']").click()
    time.sleep(1)
# 给指定的微博写评论
weibo_url = 'https://weibo.com/1890826225/HjjqSahwl'
content = 'Gook Luck!好运已上路！'
# 自动发微博
content = '每天学点心理学'
post_weibo(content)