爬虫大作业

时间：2018-04-24 13:59:35 阅读：214 评论：0 收藏：0 [点我收藏+]

1.爬取豆瓣电影top250。(所有同学不能雷同)

技术分享图片

2.用python 编写爬虫程序，从网络上爬取相关主题的数据。

import requests
from bs4 import BeautifulSoup
from datetime import datetime
import re
import pandas

# 电影简介保存到txt。
def writeNewsDetail(content):
    f = open(‘wzh.txt‘, ‘a‘,encoding=‘utf-8‘)#文件名、打开方式
    f.write(content)#写入
    f.close()#关闭文件

#电影的简介
def getMovieDetail(url):
    resd = requests.get(url)
    resd.encoding = ‘utf-8‘
    soupd = BeautifulSoup(resd.text, ‘html.parser‘)
    movies={}
    if (int(len(soupd.select(‘#link-report‘))) > 0):
        movies[‘content‘] = soupd.select(‘#link-report‘)[0].text
    else:
        movies[‘content‘] =‘none‘
    if (int(len(soupd.select(‘.attrs‘))) > 0):
        movies[‘director‘] = soupd.select(‘.attrs‘)[0].text
    else:
        movies[‘director‘]=‘none‘
    if (int(len(soupd.select(‘.actor a‘))) > 0):
        movies[‘actor‘] = soupd.select(‘.actor a‘)[0].text
    else:
        movies[‘actor‘] = ‘none‘
    if(int(len(soupd.select(‘h1‘)))>0):
        movies[‘name‘]=soupd.select(‘h1‘)[0].text
    else:
        movies[‘name‘] = ‘none‘
    if(int(len(soupd.select(‘strong‘))) > 0):
        movies[‘score‘] = soupd.select(‘strong‘)[0].text
    else:
        movies[‘score‘] =‘none‘
    movies[‘url‘] = url
    return (movies)

# 电影列表页的总页数
def getPageN(url):
    res = requests.get(url)
    res.encoding = ‘utf-8‘
    soup = BeautifulSoup(res.text, ‘html.parser‘)
    #num = soup.select(‘.paginator a‘)[-2].text
    print(‘列表页数：‘,num)

#一个列表页全部电影
def getListPage(url):
    res = requests.get(url)
    res.encoding = ‘utf-8‘
    soup = BeautifulSoup(res.text, ‘html.parser‘)
    moviesList = []
    urls = soup.select(‘.hd a‘)
    # for i in range(10):
    #     if(i==0)
    #     urls=‘htthttps://movie.douban.com/top250?start=25&filter=‘
    for j in range(int(len(urls))):
        url = soup.select(‘.hd a‘)[j].attrs[‘href‘]
        moviesList.append(getMovieDetail(url))#在列表末尾添加新的对象
    return (moviesList)

moviesTotal = []
Url = ‘https://movie.douban.com/top250?start=0&filter=‘
moviesTotal.extend(getListPage(Url))  # 在列表末尾一次性追加另一个序列中的多个值（用新列表扩展原来的列表）
getPageN(Url)
dt =pandas.DataFrame(moviesTotal)
dt.to_excel("wzh.xlsx")
print(dt)

3.对爬了的数据进行文本分析，生成词云。

import jieba.analyse
from PIL import Image,ImageSequence
import numpy as np
import matplotlib.pyplot as plt
from wordcloud import WordCloud,ImageColorGenerator
lyric= ‘‘
f=open(‘wzh.txt‘,‘r‘,encoding=‘utf-8‘)
for i in f:
    lyric+=f.read()


result=jieba.analyse.textrank(lyric,topK=50,withWeight=True)
keywords = dict()
for i in result:
    keywords[i[0]]=i[1]
print(keywords)


image= Image.open(‘tim.png‘)
graph = np.array(image)
wc = WordCloud(font_path=‘./fonts/simhei.ttf‘,background_color=‘Green‘,max_words=50,mask=graph)
wc.generate_from_frequencies(keywords)
image_color = ImageColorGenerator(graph)
plt.imshow(wc)
plt.imshow(wc.recolor(color_func=image_color))
plt.axis("off")
plt.show()
wc.to_file(‘dream.png‘)