#yyds干货盘点#Python实战案例，requests模块，Python实现获取动态图表

Posted 2022-02-14 逻辑教育

前言

利用Python实现获取动态图表，废话不多说~

让我们愉快地开始吧~

开发工具

Python版本： 3.6.4

相关模块：

re模块；

requests模块；

urllib模块；

pandas模块；

以及一些Python自带的模块。

环境搭建

安装Python并添加到环境变量，pip安装需要的相关模块即可。

看一下B站2019年「数据可视化」版块的情况，第一个视频超2百万的播放量，4万+的弹幕

百度指数

获取百度指数，首先需要登陆你的百度账号

以关键词「王者荣耀」为例，时间自定义为2020-10-01～2020-10-10

通过开发者工具，我们就能看到曲线图的数据接口

然而一看请求得到的结果，发现并没有数据，原因是这里使用了JS加密

找到解决方法，成功实现爬取，代码实现

import time
import json
import execjs
import datetime
import requests
from urllib.parse import urlencode

def get_data(keywords, startDate, endDate, area):
    """
    获取加密的参数数据
    """
    # data_url = "http://index.baidu.com/api/SearchApi/index?area=0&word=[[%7B%22name%22:%22%E7%8E%8B%E8%80%85%E8%8D%A3%E8%80%80%22,%22wordType%22:1%7D]]&startDate=2020-10-01&endDate=2020-10-10"
    params = 
        word: json.dumps([[name: keyword, wordType: 1] for keyword in keywords]),
        startDate: startDate,
        endDate: endDate,
        area: area
    
    data_url = http://index.baidu.com/api/SearchApi/index? + urlencode(params)
    # print(data_url)
    headers = 
        # 复制登录后的cookie
        "Cookie": 你的cookie,
        "Referer": "http://index.baidu.com/v2/main/index.html",
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36"
    

    # 获取data和uniqid
    res = requests.get(url=data_url, headers=headers).json()
    data = res["data"]["userIndexes"][0]["all"]["data"]
    uniqid = res["data"]["uniqid"]

    # 获取js函数中的参数t = "ev-fxk9T8V1lwAL6,51348+.9270-%"
    t_url = "http://index.baidu.com/Interface/ptbk?uniqid=".format(uniqid)
    rep = requests.get(url=t_url, headers=headers).json()
    t = rep["data"]
    return "data": data, "t": t

def get_search_index(word, startDate, endDate, area):
    """
    获取最终数据
    """
    word = word
    startDate = startDate
    endDate = endDate
    # 调用get_data获取data和uniqid
    res = get_data(word, startDate, endDate, area)
    e = res["data"]
    t = res["t"]

    # 读取js文件
    with open(parsing_data_function.js, encoding=utf-8) as f:
        js = f.read()

    # 通过compile命令转成一个js对象
    docjs = execjs.compile(js)

    # 调用function方法,得到指数数值
    res = docjs.call(decrypt, t, e)
    # print(res)
    return res

def get_date_list(begin_date, end_date):
    """
    获取时间列表
    """
    dates = []
    dt = datetime.datetime.strptime(begin_date, "%Y-%m-%d")
    date = begin_date[:]
    while date <= end_date:
        dates.append(date)
        dt += datetime.timedelta(days=1)
        date = dt.strftime("%Y-%m-%d")
    return dates

def get_area():
    areas = "901": "山东", "902": "贵州", "903": "江西", "904": "重庆", "905": "内蒙古", "906": "湖北", "907": "辽宁", "908": "湖南", "909": "福建", "910": "上海", "911": "北京", "912": "广西", "913": "广东", "914": "四川", "915": "云南", "916": "江苏", "917": "浙江", "918": "青海", "919": "宁夏", "920": "河北", "921": "黑龙江", "922": "吉林", "923": "天津", "924": "陕西", "925": "甘肃", "926": "新疆", "927": "河南", "928": "安徽", "929": "山西", "930": "海南", "931": "台湾", "932": "西藏", "933": "香港", "934": "澳门"
    for value in areas.keys():
        try:
            word = [王者荣耀]
            time.sleep(1)
            startDate = 2020-10-01
            endDate = 2020-10-10
            area = value
            res = get_search_index(word, startDate, endDate, area)
            result = res.split(,)
            dates = get_date_list(startDate, endDate)
            for num, date in zip(result, dates):
                print(areas[value], num, date)
                with open(area.csv, a+, encoding=utf-8) as f:
                    f.write(areas[value] + , + str(num) + , + date + \\n)
        except:
            pass

def get_word():
    words = [诸葛大力, 张伟, 胡一菲, 吕子乔, 陈美嘉, 赵海棠, 咖喱酱, 曾小贤, 秦羽墨]
    for word in words:
        try:
            time.sleep(2)
            startDate = 2020-10-01
            endDate = 2020-10-10
            area = 0
            res = get_search_index(word, startDate, endDate, area)
            result = res.split(,)
            dates = get_date_list(startDate, endDate)
            for num, date in zip(result, dates):
                print(word, num, date)
                with open(word.csv, a+, encoding=utf-8) as f:
                    f.write(word + , + str(num) + , + date + \\n)
        except:
            pass

get_area()
get_word()

得到的CSV文件结果如下，有两种形式的数据

一种是多个关键词每日指数数据，另一种是一个关键词各省市每日指数数据

有了数据就可以用Python制作动图

import pandas as pd
import bar_chart_race as bcr

# 读取数据
# df = pd.read_csv(word.csv, encoding=utf-8, header=None, names=[name, number, day])
df = pd.read_csv(area.csv, encoding=utf-8, header=None, names=[name, number, day])

# 数据处理，数据透视表
df_result = pd.pivot_table(df, values=number, index=[day], columns=[name], fill_value=0)

# 生成GIF
# bcr.bar_chart_race(df_result, filename=word.gif, title=爱情公寓5演职人员热度排行)
bcr.bar_chart_race(df_result, filename=area.gif, title=国内各省市王者荣耀热度排行)

5行Python代码，看看实现的效果

微博指数

百度搜索新浪的微博指数，打开网站一看，发现网页版无法使用

我们只需打开开发者工具，将你的浏览器模拟为手机端，刷新网页即可

可以看到，微指数的界面出来了

添加关键词，查看指数的数据接口

请求是Post方法，并且不需要登陆微博账号

import re
import time
import json
import requests
import datetime

# 请求头信息
headers = """accept: application/json
accept-encoding: gzip, deflate, br
accept-language: zh-CN,zh;q=0.9
content-length: 50
content-type: application/x-www-form-urlencoded
cookie: 你的cookie
origin: https://data.weibo.com
referer: https://data.weibo.com/index/newindex?visit_type=trend&wid=1011224685661
sec-fetch-mode: cors
sec-fetch-site: same-origin
user-agent: Mozilla/5.0 (iPhone; CPU iPhone OS 11_0 like Mac OS X) AppleWebKit/604.1.38 (KHTML, like Gecko) Version/11.0 Mobile/15A372 Safari/604.1
x-requested-with: XMLHttpRequest"""

# 将请求头字符串转化为字典
headers = dict([line.split(": ",1) for line in headers.split("\\n")])
print(headers)

# 数据接口
url = https://data.weibo.com/index/ajax/newindex/getchartdata

# 获取时间列表
def get_date_list(begin_date, end_date):
    dates = []
    dt = datetime.datetime.strptime(begin_date, "%Y-%m-%d")
    date = begin_date[:]
    while date <= end_date:
        dates.append(date)
        dt += datetime.timedelta(days=1)
        date = dt.strftime("%Y-%m-%d")
    return dates

# 相关信息
names = [汤唯, 朱亚文, 邓家佳, 乔振宇, 王学圻, 张艺兴, 俞灏明, 吴越, 梁冠华, 李昕亮, 苏可, 孙骁骁, 赵韩樱子, 孙耀琦, 魏巍]

# 获取微指数数据
for name in names:
    try:
        # 获取关键词ID
        url_id = https://data.weibo.com/index/ajax/newindex/searchword
        data_id = 
            word: name
        
        html_id = requests.post(url=url_id, data=data_id, headers=headers)
        pattern = re.compile(rli wid=\\\\\\"(.*?)\\\\\\" word)
        id = pattern.findall(html_id.text)[0]

        # 接口参数
        data = 
            wid: id,
            dateGroup: 1month
        
        time.sleep(2)
        # 请求数据
        html = requests.post(url=url, data=data, headers=headers)
        result = json.loads(html.text)
        # 处理数据
        if result[data]:
            values = result[data][0][trend][s]
            startDate = 2019-01-01
            endDate = 2020-01-01
            dates = result[data][0][trend][x]
            # 保存数据
            for value, date in zip(values, dates):
                print(name, value, date)
                with open(weibo.csv, a+, encoding=utf-8) as f:
                    f.write(name + , + str(value) + , + date + \\n)
    except:
        pass

获取到的信息

也来生成一个动态图表

import pandas as pd
import bar_chart_race as bcr

# 读取数据
df = pd.read_csv(weibo.csv, encoding=utf-8, header=None, names=[name, number, day])

# 数据处理，数据透视表
df_result = pd.pivot_table(df, values=number, index=[day], columns=[name], fill_value=0)
# print(df_result[:10])

# 生成GIF
bcr.bar_chart_race(df_result[:10], filename=weibo.gif, title=大明风华演职人员热度排行)

本文源码详见个人主页简介获取

结果展示