豆瓣电影Top250数据分析

一、requirements

beautifulsoup4==4.9.1
bs4==0.0.1
click==7.1.2
cycler==0.10.0
Flask==1.1.2
itsdangerous==1.1.0
jieba==0.42.1
Jinja2==2.11.2
kiwisolver==1.2.0
MarkupSafe==1.1.1
matplotlib==3.2.1
numpy==1.18.4
Pillow==7.1.2
pyparsing==2.4.7
python-dateutil==2.8.1
six==1.15.0
soupsieve==2.0.1
Werkzeug==1.0.1
wordcloud @ file:python_reptile/flask/static/extend/wordcloud-1.7.0-cp36-cp36m-win32.whl
xlwt==1.3.0

二、获取并存储数据

爬取豆瓣TOP250数据，并存储到数据库

步骤：

定义爬取地址
获取URL的数据列表

通过User-Agent，得到指定一个URL的网页内容
存储到sqlite数据库（数据库名：movie.db，表名：movie250）

# -*- coding:utf-8 -*-
 
# date： 2020-5-10
# author： jingluo
import sys
from bs4 import BeautifulSoup
import sqlite3
import re
import urllib.request, urllib.error
import xlwt

# 搜索规则
findLink = re.compile(r'<a href="(.*?)">')
findImageSrc = re.compile(r'<img.*src="(.*?)"', re.S) # re.S让换行符包含在字符中
findTitle = re.compile(r'<span class="title">(.*)</span>')
findRating = re.compile(r'<span class="rating_num" property="v:average">(.*)</span>')
findJudge = re.compile(r'<span>(\d*)人评价</span>')
findInq = re.compile(r'<span class="inq">(.*)</span>')
findBd = re.compile(r'<p class="">(.*?)</p>', re.S)

def main():
    # 1. 定义爬取网址
    base_url = "https://movie.douban.com/top250?start="
    # 2. 获取数据列表
    data_list = getData(base_url)
    # 3. 定义数据库名称
    dbpath = "movie.db"
    # 4. 存储到sqlite数据库
    saveData2DB(data_list, dbpath)

# 获取数据列表
def getData(base_url):
    data_list = []
    for i in range(0, 10):
        url = base_url + str(i*25)
        html = askURl(url)
        
        # 逐一解析网页
        soup = BeautifulSoup(html, "html.parser")
        for item in soup.find_all("div", class_="item"):
            data = []
            item = str(item)

            link = re.findall(findLink, item)[0]
            data.append(link)
            imgSrc = re.findall(findImageSrc, item)[0]
            data.append(imgSrc)
            titles = re.findall(findTitle, item)
            if len(titles) == 2:
                ctitle = titles[0]
                data.append(ctitle)
                otitle = titles[1].replace("/", "")
                data.append(otitle)
            else:
                data.append(titles[0])
                data.append('')
            rating = re.findall(findRating, item)[0]
            data.append(rating)
            judege = re.findall(findJudge, item)[0]
            data.append(judege)
            inq = re.findall(findInq, item)
            if len(inq) != 0:
                data.append(inq[0].replace("。", ""))
            else:
                data.append('')
            bd = re.findall(findBd, item)[0]
            bd = re.sub('<br(\s+)?/>(\s+)?', " ", bd)
            bd = re.sub('/', " ", bd)
            data.append(bd.strip())
            data_list.append(data)
    return data_list

# 得到指定一个URL的网页内容
def askURl(url):
    # 用户验证信息
    head = {"User-Agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36"}
    request = urllib.request.Request(url, headers = head)
    html = ""
    try:
        response = urllib.request.urlopen(request)
        html = response.read().decode("utf-8")
    except urllib.error.URLError as e:
        if hasattr(e, "code"):
            print("请求出错",e.code)
        if hasattr(e, "reason"):
            print("错误原因",e.reason)
    return html

# 保存到sqlite数据库中
def saveData2DB(data_list, dbpath):
    init_db(dbpath)
    conn = sqlite3.connect(dbpath)
    cur = conn.cursor()

    for data in data_list:
        for index in range(len(data)):
            if index == 4 or index == 5:
                continue
            data[index] = '"' +data[index] + '"'
        sql = '''
        insert into movie250
        (
        info_link,pic_link,cname,ename,score,rated,instroduction,info
        )
        values(%s)'''%",".join(data)
        cur.execute(sql)
        conn.commit()
    cur.close()
    conn.close()

# 初始化数据库
def init_db(dbpath):
    sql = '''
        create table movie250
        (
        id integer primary key autoincrement,
        info_link text,
        pic_link text,
        cname varchar,
        ename varchar,
        score numeric,
        rated numeric,
        instroduction text,
        info text
        );
    '''
    conn = sqlite3.connect(dbpath)
    cursor = conn.cursor()
    cursor.execute(sql)
    conn.commit()
    conn.close()

三、获取词云

读取数据库
使用jieba进行分割
使用word_length.txt存储词云长度
将原始图转成数组
使用Image和WordCloud初始化图片
使用pyplot生成和保存图片

def makeWordCloud():
    # 准备词云所需的词
    con = sqlite3.connect('movie.db')
    cur = con.cursor()
    sql = 'select instroduction from movie250'
    data = cur.execute(sql)
    text = ""
    for item in data:
        text = text + item[0]
    cur.close()
    con.close()

    cut = jieba.cut(text)
    string = ' '.join(cut)

    filename = 'word_length.txt'
    with open(filename, 'w') as file:
        file.write(str(len(string)))
        file.close()

    img = Image.open(r'../static/assets/img/tree.jpg')
    img_arry = np.array(img) # 将图片转换成数组
    wc = WordCloud(
        background_color = 'white',
        mask = img_arry,
        font_path = 'STCAIYUN.TTF' # 字体锁在位置： C:\Windows\Fonts
        )
    wc.generate_from_text(string)

    # 绘制图片
    fig = plt.figure(1)
    plt.imshow(wc)
    plt.axis('off') # 是否显示坐标轴
    # plt.show() # 显示生成的词云图片

    # 输出词云图片到文件
    plt.savefig(r'../static/assets/img/word.jpg', dpi=800)
    plt.close()

四、完成业务代码

# -*- coding:utf-8 -*-
 
# date： 2020-5-30
# author： jingluo
from flask import Flask, render_template,request, session
import get_douban_databses
import sqlite3
import os

# 分词
import jieba
# 绘图，数据可视化
from matplotlib import pyplot as plt
# 词云
from wordcloud import WordCloud
# 图片处理
from PIL import Image
# 矩阵运算
import numpy as np

# 自定义template路径
app = Flask(__name__,template_folder="../templates/",
    static_folder='../static/') #应用

# flask的session需要用到的秘钥字符串
app.config["SECRET_KEY"] = "akjsdhkjashdkjhaksk120191101asd"

@app.route("/")
def index():
    try:
        with open('word_length.txt', 'r') as file:
            word_length = file.readline()
            session['word_length'] = word_length
            file.close()
    except:
        word_length = 5633
        session['word_length'] = word_length
    return render_template("template/home.html",word_length = word_length)

@app.route("/home")
def home():
    word_length = session.get('word_length')
    return render_template("template/home.html",word_length = word_length)

@app.route("/movie")
def movie():
    movies = []
    con = sqlite3.connect("movie.db")
    cur = con.cursor()
    sql = "select * from movie250"
    data = cur.execute(sql)
    for item in data:
        movies.append(item)
    cur.close()
    con.close()
    return render_template("template/movie.html",movies = movies)

@app.route("/score")
def score():
    score = []
    number = []
    con = sqlite3.connect("movie.db")
    cur = con.cursor()
    sql = "select score,count(score) from movie250 group by score"
    data = cur.execute(sql)
    for item in data:
        score.append(item[0])
        number.append(item[1])
    cur.close()
    con.close()
    return render_template("template/score.html", score = score, number = number)

# 生成词云图片
def makeWordCloud():
    # 准备词云所需的词
    con = sqlite3.connect('movie.db')
    cur = con.cursor()
    sql = 'select instroduction from movie250'
    data = cur.execute(sql)
    text = ""
    for item in data:
        text = text + item[0]
    cur.close()
    con.close()

    cut = jieba.cut(text)
    string = ' '.join(cut)

    filename = 'word_length.txt'
    with open(filename, 'w') as file:
        file.write(str(len(string)))
        file.close()

    img = Image.open(r'../static/assets/img/tree.jpg')
    img_arry = np.array(img) # 将图片转换成数组
    wc = WordCloud(
        background_color = 'white',
        mask = img_arry,
        font_path = 'STCAIYUN.TTF' # 字体锁在位置： C:\Windows\Fonts
        )
    wc.generate_from_text(string)

    # 绘制图片
    fig = plt.figure(1)
    plt.imshow(wc)
    plt.axis('off') # 是否显示坐标轴
    # plt.show() # 显示生成的词云图片

    # 输出词云图片到文件
    plt.savefig(r'../static/assets/img/word.jpg', dpi=800)
    plt.close()

@app.route("/word")
def word():
    return render_template("template/word.html")

@app.route("/team")
def team():
    return render_template("template/team.html")

if __name__ == '__main__':
    app.config.update(DEBUG=True)
    if not os.path.exists('movie.db'):
        get_douban_databses.main()
    if not os.path.exists('../static/assets/img/word.jpg'):
        makeWordCloud()
    app.run()

五、使用教程

git clone https://gitee.com/jingluoonline/python_reptile.git
cd python_reptile/flsk/apps
输入创建虚拟化境的命令virtualenv FlaskPath
进入虚拟环境FlaskPath\Scripts\activate.bat
安装相关依赖
1. 其中wordcloud下载有时候会有问题，可以选择使用whl文件下载，网址https://www.lfd.uci.edu/~gohlke/pythonlibs/#wordcloud找到相应的包下载到本地，进行本地安装
python index.py，有点慢，因为爬取数据和生成图片都是在初始化时
浏览器输入http://127.0.0.1:5000/

六、效果图

主页

tQ5r8S.png

电影

tQ5HKJ.png

评分

tQ5OV1.png

词云

tQIeG8.png

团队

tQI8I0.png