Python爬取近十年TIOBE编程语言热度数据并可视化可视化

# -*- coding: UTF-8 -*-
"""
@File    ：spider.py
@Author  ：叶庭云
@CSDN    ：https://yetingyun.blog.csdn.net/
"""
import requests
import re
import openpyxl
import logging

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s: %(message)s')
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.89 Safari/537.1"
}

wb = openpyxl.Workbook()    # 创建工作簿对象
sheet = wb.active           # 获取活动的工作表
# 编程语言   时间    热度
sheet.append(['Programing', 'Date', 'data_per'])

url = 'https://www.tiobe.com/tiobe-index/'
rep = requests.get(url, headers=headers).text

# 正则匹配提取数据
data = re.findall('{name : (.*?),data : (.*?)}', rep)
programing = [eval(k[0]) for k in data]     # 编程语言
dates = [i[1] for i in data]

# 正则表达式处理 提取出想要的数据
for x in range(len(dates)):
    name = programing[x]
    datas = re.findall(r'\[Date.UTC(.*?)\]', dates[x], re.DOTALL)
    for m in datas:
        date1 = re.findall(r'\d+', m)       # 正则提取出数字
        date2 = '-'.join(date1[:3])         # 拼接得到时间
        data_per = '.'.join(date1[-2:])     # 得到热度数据
        sheet.append([name, date2, data_per])
        logging.info([name, date2, data_per])

wb.save('language_data.xlsx')

# -*- coding: UTF-8 -*-
"""
@File    ：轮播图.py
@Author  ：叶庭云
@CSDN    ：https://yetingyun.blog.csdn.net/
"""

import pandas as pd
import xlrd
import pyecharts.options as opts
from pyecharts.charts import Timeline, Bar
from pyecharts.globals import CurrentConfig


CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/'

# 提取编程语言名字
name = list(pd.read_excel('language_data.xlsx')['Programing'].drop_duplicates())

data = xlrd.open_workbook('language_data.xlsx')
table = data.sheets()[0]

dic1 = {k: [] for k in name}
# 各编程语言对应每年里不同时间的热度
for i in range(1, table.nrows):
 x = table.row_values(i)
 dic1[x[0]].append((x[1], x[2]))

# 与编程语言顺序对应  每年编程语言对应的不同时间的热度
data_per = {k: [[] for x in range(10)] for k in range(2001, 2021)}
print(data_per)

count = 0
for k, v in dic1.items():
 for j in v:   # v (时间，热度)  热度数据添加进各年对应的列表里
  data_per[int(j[0][:4])][count].append(eval(j[1]))  # 一年里各编程语言不同时间时的热度  对应起来
 count += 1

# print(data_per)
data_per1 = {k: [] for k in list(data_per.keys())}

for k, v in list(data_per.items()):
 for x in v:
  if len(x) == 0:                  # 这一年里该语言没有热度数据
   data_per1[k].append(0)
  else:
   avg = sum(x) / len(x)
   data_per1[k].append(avg)     # 这一年里的平均热度

# 得到TOBIE现在排Top20的编程语言从2001年开始每年的平均热度
print(data_per1)


def get_year_overlap_chart(year) -> Bar:
 sum_info = [(m, n) for m, n in zip(name, data_per1[year])]
 # 编程语言按每年平均热度排序
 sum_info.sort(key=lambda z: z[1], reverse=True)
 name_ = [m[0] for m in sum_info]
 datas = [m[1] for m in sum_info]
 # 每根柱子的颜色列表
 colors = ['#00BFFF', '#0000CD', '#000000', '#008000', '#FF1493', '#FFD700', '#FF4500', '#00FA9A', '#191970',
     '#9932CC']
 x = []
 for i in range(10):
  x.append(
   opts.BarItem(
    name=name_[i],
    value=datas[i],
    itemstyle_opts=opts.ItemStyleOpts(color=colors[i])   # 设置每根柱子的颜色
   )
  )
 # 绘制柱形图
 bar = Bar()
 bar.add_xaxis(name_)
 bar.add_yaxis(series_name='热度', yaxis_data=x, is_selected=True,
                  label_opts=opts.LabelOpts(is_show=False))
 bar.set_global_opts(title_opts=opts.TitleOpts(
      title="2009-2019编程语言热度"),
      tooltip_opts=opts.TooltipOpts(
      is_show=True, trigger="axis", axis_pointer_type="shadow"),
                  xaxis_opts=opts.AxisOpts(name='编程语言'), yaxis_opts=opts.AxisOpts(name='热度'),
 )
 return bar

# 生成时间轴的图
timeline = Timeline(init_opts=opts.InitOpts(width="1200px", height="600px"))
for y in range(2009, 2020):
 timeline.add(get_year_overlap_chart(y), time_point=str(y))

timeline.add_schema(is_auto_play=True, play_interval=1000)
timeline.render("language_2009_2019.html")

from pyecharts.globals import CurrentConfig

CurrentConfig.ONLINE_HOST = 'D:/python/pyecharts-assets-master/assets/' # 本地保存 js 资源的路径