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from bs4 import BeautifulSoup
import pandas as pd
import requests
import re
import json
import time
codes = [{"id": 1, "name": "创业板指", "zs": "399006", "cn": "159915", "cw": "161022"},
{"id": 2, "name": "深证成指", "zs": "399001", "cn": "159903", "cw": "202017"},
{"id": 3, "name": "深证100", "zs": "399330", "cn": "159901", "cw": "110019"},
{"id": 4, "name": "央视50", "zs": "399550", "cn": "159965", "cw": "217027"},
{"id": 5, "name": "沪深300", "zs": "000300", "cn": "510300", "cw": "160706"},
{"id": 6, "name": "上证180", "zs": "000010", "cn": "510180", "cw": "519180"},
{"id": 7, "name": "上证50", "zs": "000016", "cn": "510050", "cw": "001051"},
{"id": 8, "name": "中证100", "zs": "000903", "cn": "512910", "cw": "240014"},
{"id": 9, "name": "中小300", "zs": "399008", "cn": "159907", "cw": "270026"},
{"id": 10, "name": "创业板50", "zs": "399673", "cn": "159949", "cw": "007464"},
{"id": 11, "name": "中证1000", "zs": "000852", "cn": "512100", "cw": ""},
{"id": 12, "name": "中证500", "zs": "000905", "cn": "510500", "cw": "160119"},
{"id": 13, "name": "科创50", "zs": "000688", "cn": "588000", "cw": "011609"},
{"id": 14, "name": "深证红利", "zs": "399324", "cn": "159905", "cw": "481012"},
{"id": 15, "name": "50AH优选", "zs": "950090", "cn": "", "cw": "501050"},
{"id": 16, "name": "中证红利", "zs": "000922", "cn": "515890", "cw": "100032"},
{"id": 17, "name": "深证F120", "zs": "399702", "cn": "159910", "cw": "070023"},
{"id": 18, "name": "红利指数", "zs": "000015", "cn": "510880", "cw": "016441"},
{"id": 19, "name": "300红利", "zs": "000821", "cn": "512530", "cw": ""},
{"id": 20, "name": "红利低波", "zs": "H30269", "cn": "512890", "cw": "005561"},
{"id": 21, "name": "基本面50", "zs": "000925", "cn": "512750", "cw": "160716"},
{"id": 22, "name": "深证价值", "zs": "399348", "cn": "159913", "cw": "519706"},
{"id": 23, "name": "深证F60", "zs": "399701", "cn": "159916", "cw": "530015"},
{"id": 24, "name": "300价值", "zs": "000919", "cn": "", "cw": "519671"},
{"id": 25, "name": "红利潜力", "zs": "H30089", "cn": "515570", "cw": "007671"},
{"id": 26, "name": "180价值", "zs": "000029", "cn": "510030", "cw": "240016"},
{"id": 27, "name": "500SNLV", "zs": "930782", "cn": "512260", "cw": "003318"},
{"id": 28, "name": "300红利LV", "zs": "930740", "cn": "", "cw": "007605"},
{"id": 29, "name": "国证地产", "zs": "399393", "cn": "", "cw": "160218"},
{"id": 30, "name": "环境治理", "zs": "399806", "cn": "", "cw": "164908"},
{"id": 31, "name": "基建工程", "zs": "399995", "cn": "", "cw": "165525"},
{"id": 32, "name": "全指材料", "zs": "000987", "cn": "159944", "cw": ""},
{"id": 33, "name": "养老产业", "zs": "399812", "cn": "", "cw": "000968"},
{"id": 34, "name": "中国互联网", "zs": "H11136", "cn": "164906", "cw": "164906"},
{"id": 35, "name": "国证有色", "zs": "399395", "cn": "160221", "cw": ""},
{"id": 36, "name": "中国互联网50", "zs": "H30533", "cn": "513050", "cw": "006327"},
{"id": 37, "name": "中证银行", "zs": "399986", "cn": "512800", "cw": "001594"},
{"id": 38, "name": "全指金融", "zs": "000992", "cn": "159940", "cw": "001469"},
{"id": 39, "name": "全指工业", "zs": "000988", "cn": "159953", "cw": ""},
{"id": 40, "name": "家用电器", "zs": "930697", "cn": "159996", "cw": "005063"},
{"id": 41, "name": "国证食品", "zs": "399396", "cn": "159843", "cw": "160222"},
{"id": 42, "name": "高铁产业", "zs": "399807", "cn": "", "cw": "160135"},
{"id": 43, "name": "中证酒", "zs": "399987", "cn": "512690", "cw": "160632"},
{"id": 44, "name": "新能源", "zs": "000941", "cn": "516160", "cw": "012831"},
{"id": 45, "name": "中证消费", "zs": "000932", "cn": "159928", "cw": "000248"},
{"id": 46, "name": "证券公司", "zs": "399975", "cn": "512000", "cw": "004069"},
{"id": 47, "name": "中证国防", "zs": "399973", "cn": "512670", "cw": "502003"},
{"id": 48, "name": "全指可选", "zs": "000989", "cn": "159936", "cw": "001133"},
{"id": 49, "name": "全指信息", "zs": "000993", "cn": "159939", "cw": "000942"},
{"id": 50, "name": "中证军工", "zs": "399967", "cn": "512660", "cw": "161024"},
{"id": 51, "name": "大宗商品", "zs": "000979", "cn": "", "cw": "161715"},
{"id": 52, "name": "汽车指数", "zs": "931008", "cn": "", "cw": "004854"},
{"id": 53, "name": "中证煤炭", "zs": "399998", "cn": "013275", "cw": "161032"},
{"id": 54, "name": "CS食品饮", "zs": "930653", "cn": "", "cw": "001631"},
{"id": 55, "name": "中证传媒", "zs": "399971", "cn": "512980", "cw": "004752"},
{"id": 56, "name": "大农业", "zs": "399814", "cn": "", "cw": "001027"},
{"id": 57, "name": "中证白酒", "zs": "399997", "cn": "", "cw": "161725"},
{"id": 58, "name": "CS新能车", "zs": "399976", "cn": "515030", "cw": "161028"},
{"id": 59, "name": "中证环保", "zs": "000827", "cn": "512580", "cw": "001064"},
{"id": 60, "name": "科技龙头", "zs": "931087", "cn": "515000", "cw": "007873"},
{"id": 61, "name": "人工智能", "zs": "931071", "cn": "515980", "cw": "008020"},
{"id": 62, "name": "CS创新药", "zs": "931152", "cn": "159992", "cw": "012738"},
{"id": 63, "name": "5G通信", "zs": "931079", "cn": "515050", "cw": "008086"},
{"id": 64, "name": "光伏产业", "zs": "931151", "cn": "515790", "cw": "011102"},
{"id": 65, "name": "国证芯片", "zs": "980017", "cn": "159995", "cw": "008887"},
{"id": 66, "name": "中华半导体芯片", "zs": "990001", "cn": "512760", "cw": "008281"},
{"id": 67, "name": "恒生指数", "zs": "HSI", "cn": "159920", "cw": "164705"},
{"id": 68, "name": "恒生综合中小型股指数", "zs": "HSMSI", "cn": "", "cw": "160922"},
{"id": 69, "name": "恒生中国企业指数", "zs": "HSCEI", "cn": "510900", "cw": "110031"},
{"id": 70, "name": "恒生A股行业龙头指数", "zs": "HSCAIT", "cn": "", "cw": "540012"},
{"id": 71, "name": "标普500", "zs": ".INX", "cn": "513500", "cw": "050025"},
{"id": 72, "name": "纳斯达克100指数", "zs": ".NDX", "cn": "", "cw": "160213"}]
def scrape_website(api, headers=None):
"""获取网站数据"""
try:
response = requests.get(api, headers=headers, timeout=10)
response.raise_for_status()
return response
except requests.RequestException as e:
print(f"请求数据时出错: {e}")
return None
def zswd():
"""从API爬取指数温度数据"""
t_results = scrape_website('http://caf-qibei.com/index?type=html')
if t_results is None:
return []
soup = BeautifulSoup(t_results.content, 'html.parser')
tr_tags = soup.find_all('tr')
index_T = []
for tr in tr_tags:
a_tags = tr.find_all('a', href=True)
td_tag = tr.find('td', {'colspan': '3'})
if len(a_tags) >= 2 and td_tag:
first_a_text = a_tags[0].text.strip()
td_text = td_tag.text.strip()
try:
td_float = float(td_text)
index_T.append((first_a_text, td_float))
except ValueError:
continue
return index_T
wendu = zswd()
zs = [i['zs'] for i in codes]
df_wendu = pd.DataFrame(wendu, columns=['zs', 'temperature'])
df_filtered = df_wendu[df_wendu['zs'].isin(zs)]
df_codes = pd.DataFrame(codes)
df_merged = pd.merge(df_filtered, df_codes[['zs', 'name', 'cn', 'cw']], on='zs', how='inner')
df_merged = df_merged.rename(columns={'zs': '指数', 'name': '名称', 'temperature': '温度', 'cn': '场内', 'cw': '场外'})
df_merged_sorted = df_merged.sort_values(by='温度', ascending=True)
print(df_merged_sorted)
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