标签:fir end 股票代码 ice range cond div bar ror
import requests import csv from pyecharts import Bar url = ‘https://xueqiu.com/hq?page=1#exchange=US&firstName=3&secondName=3_0‘ headers = { "User-Agent": "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36" } session = requests.Session() session.get(url=url,headers=headers) ALL_DATA = [] def get_page_list(): url = ‘https://xueqiu.com/service/v5/stock/screener/quote/list‘ for i in range(1,254): params = { ‘page‘: i, ‘size‘: ‘30‘, ‘order‘: ‘desc‘, ‘orderby‘: ‘percent‘, ‘order_by‘: ‘percent‘, ‘market‘: ‘US‘, ‘type‘: ‘us‘, ‘_‘: ‘1561292727168‘ } response = session.get(url=url, headers=headers, params=params) page_text = response.json() # dict # print(page_text) content_list = page_text[‘data‘][‘list‘] # print(content_list) for stock in content_list: info_dict = {} stock_code = stock[‘symbol‘] stock_name = stock[‘name‘] cur_price = stock[‘current‘] zhangdie = stock[‘percent‘] ttm = stock[‘pe_ttm‘] value = stock[‘market_capital‘] if value: value = value/10000 info_dict[‘股票代码‘] = stock_code info_dict[‘股票名称‘] = stock_name info_dict[‘当前价‘] = cur_price # info_dict[‘涨跌幅‘] = float(str(zhangdie)+‘%‘) info_dict[‘涨跌幅(%)‘] = zhangdie info_dict[‘市值‘] = str(value)+‘万‘ info_dict[‘市盈率‘] = ttm # print(info_dict) ALL_DATA.append(info_dict) # print(ALL_DATA) def main(): get_page_list() try: ALL_DATA.sort(key=lambda data: data["涨跌幅(%)"],reverse=True) print(ALL_DATA) data = ALL_DATA[0:100] # 图形化展示 stock_name = list(map(lambda x:x[‘股票名称‘], data)) zhangdie = list(map(lambda x:x[‘涨跌幅(%)‘], data)) chart = Bar() chart.add("涨幅最大的100个股票", stock_name, zhangdie, is_more_utils=True) chart.render(‘stock.html‘) # 保存到csv with open(‘./雪球美股.csv‘, ‘w‘, encoding=‘utf-8‘, errors=‘ignore‘, newline="") as csvfile: fieldnames = [‘股票代码‘, ‘股票名称‘, ‘当前价‘, ‘涨跌幅(%)‘, ‘市值‘, ‘市盈率‘] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() writer.writerows(data) except: pass if __name__ == ‘__main__‘: main()
标签:fir end 股票代码 ice range cond div bar ror
原文地址:https://www.cnblogs.com/kenD/p/11123587.html