Start from https://github.com/lzjun567/crawler_html2pdf

weibo_wordcloud.py

# -*- coding:utf-8 -*-
import os
import codecs
import re
import jieba.analyse
import matplotlib.pyplot as plt
import requests
from wordcloud import WordCloud

__author__ = 'liuzhijun & wittyfilter'

# Please replace the field with your own user id and container id!
uid = "1998412373"
container_id = "1076031998412373"

# Maybe useless
luicode = "10000011"

url = "https://m.weibo.cn/api/container/getIndex"
params = {"uid": "{uid}",
          "luicode": "{luicode}",
          "type": "uid",
          "value": "{uid}",
          "containerid": "{containerid}",
          "page": "{page}"}

headers = {
    "Host": "m.weibo.cn",
    "Referer": 'https://m.weibo.cn/u/'+uid,
    "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_6) AppleWebKit/537.36 (KHTML, like Gecko) " 
    "Chrome/68.0.3440.106 Safari/537.36",
}


def clean_html(raw_html):  
    
    pattern1 = re.compile(r'<.*?>|&gt;|&quot;|转发微博|网页链接|Repost|(分享|查看|刚刚).*(图片|专辑|单曲|歌曲|照片|视频)')
    pattern2 = re.compile(r'/@[^\s]+/|/+@[^\n]+')
    pattern3 = re.compile(r'[(（].*@[^\s]+[）)]|[？?]|、|[！!]')
    text = re.sub(pattern3, '', re.sub(pattern2, '', re.sub(pattern1, '', raw_html)))
    return text


def fetch_data():

    page = 0
    total = 2000
    blogs = []
    for i in range(0, total // 10):
        params['uid'] = uid
        params['page'] = str(page)
        params['containerid'] = container_id
        res = requests.get(url, params=params, headers=headers)
        cards = res.json().get("data").get("cards")

        for card in cards:
            # Weibo post content
            if card.get("card_type") == 9:
                text = card.get("mblog").get("text")
                text = clean_html(text)
                blogs.append(text)
        page += 1
        print("Fetching Page.{page}. {count} weibo posts in total.".format(page=page, count=len(blogs)))
        with codecs.open(uid+'.txt', 'w', encoding='utf-8') as f:
            f.write("\n".join(blogs))


def generate_image():
    
    data = []
    jieba.analyse.set_stop_words("stopwords.txt")

    with codecs.open(uid+'.txt', 'r', encoding="utf-8") as f:
        for text in f.readlines():
            data.extend(jieba.analyse.extract_tags(text, topK=20))
        data = " ".join(data)
        wordcloud = WordCloud(width=640,
        	height=480,
        	collocations=False,
            font_path='Songti',
            background_color='white',
        ).generate(data)
        # plt.figure( figsize=(20,10) )
        plt.title(uid)
        plt.imshow(wordcloud, interpolation="bilinear")
        plt.axis('off')
        plt.savefig(uid+'.jpg', dpi=1600)


if __name__ == '__main__':
	
    if not os.path.isfile(uid+'.txt'):
        fetch_data()
    generate_image()