166 lines
5.3 KiB
Python
166 lines
5.3 KiB
Python
import asyncio
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from typing import Dict, List
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import aiohttp
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import pandas as pd
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# 增加了 User-Agent 头
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HEADERS = {
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"User-Agent": (
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"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
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"AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/122.0.0.0 Safari/537.36"
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),
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"Referer": "https://quote.eastmoney.com/center/gridlist.html#hs_a_board", # 合理来源页
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"Accept": "application/json, text/plain, */*",
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"Accept-Language": "zh-CN,zh;q=0.9",
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"Connection": "keep-alive",
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}
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async def fetch_single_page(
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session: aiohttp.ClientSession, url: str, params: Dict
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) -> Dict:
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"""异步获取单页数据"""
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async with session.get(url, params=params, headers=HEADERS, ssl=False) as response:
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return await response.json()
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async def fetch_all_pages_async(url: str, base_params: Dict) -> List[Dict]:
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"""异步获取所有页面数据"""
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first_page_params = base_params.copy()
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first_page_params["pn"] = "1"
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async with aiohttp.ClientSession() as session:
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first_page_data = await fetch_single_page(session, url, first_page_params)
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if first_page_data.get("rc") != 0 or not first_page_data.get("data"):
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return [first_page_data]
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total = first_page_data["data"]["total"]
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page_size = int(base_params["pz"])
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total_pages = (total + page_size - 1) // page_size
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total_pages = min(total_pages, 100)
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tasks = []
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for page in range(1, total_pages + 1):
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page_params = base_params.copy()
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page_params["pn"] = str(page)
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tasks.append(fetch_single_page(session, url, page_params))
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results = await asyncio.gather(*tasks)
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return results
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def process_data(page_results: List[Dict]) -> pd.DataFrame:
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"""处理数据为 DataFrame"""
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all_data = []
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page_number = 1
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items_per_page = 100
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for result in page_results:
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if result.get("rc") == 0 and result.get("data") and result["data"].get("diff"):
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page_data = result["data"]["diff"]
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for item in page_data:
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item["page_number"] = page_number
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item["page_index"] = page_data.index(item)
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all_data.extend(page_data)
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page_number += 1
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if not all_data:
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return pd.DataFrame()
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df = pd.DataFrame(all_data)
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df["序号"] = df.apply(
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lambda row: (row["page_number"] - 1) * items_per_page + row["page_index"] + 1,
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axis=1,
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)
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df.drop(columns=["page_number", "page_index"], inplace=True, errors="ignore")
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column_map = {
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"f1": "原序号",
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"f2": "最新价",
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"f3": "涨跌幅",
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"f4": "涨跌额",
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"f5": "成交量",
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"f6": "成交额",
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"f7": "振幅",
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"f8": "换手率",
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"f9": "市盈率-动态",
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"f10": "量比",
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"f11": "5分钟涨跌",
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"f12": "代码",
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"f13": "_",
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"f14": "名称",
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"f15": "最高",
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"f16": "最低",
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"f17": "今开",
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"f18": "昨收",
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"f20": "总市值",
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"f21": "流通市值",
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"f22": "涨速",
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"f23": "市净率",
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"f24": "60日涨跌幅",
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"f25": "年初至今涨跌幅",
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}
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df.rename(columns=column_map, inplace=True)
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desired_columns = [
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"序号", "代码", "名称", "最新价", "涨跌幅", "涨跌额", "成交量", "成交额", "振幅",
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"最高", "最低", "今开", "昨收", "量比", "换手率", "市盈率-动态", "市净率",
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"总市值", "流通市值", "涨速", "5分钟涨跌", "60日涨跌幅", "年初至今涨跌幅"
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]
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available_columns = [col for col in desired_columns if col in df.columns]
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df = df[available_columns]
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for col in [
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"最新价", "涨跌幅", "涨跌额", "成交量", "成交额", "振幅", "最高", "最低", "今开",
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"昨收", "量比", "换手率", "市盈率-动态", "市净率", "总市值", "流通市值", "涨速",
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"5分钟涨跌", "60日涨跌幅", "年初至今涨跌幅"
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]:
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if col in df.columns:
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df[col] = pd.to_numeric(df[col], errors="coerce")
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df.sort_values(by="涨跌幅", ascending=False, inplace=True)
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df.reset_index(drop=True, inplace=True)
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df["序号"] = df.index + 1
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return df
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async def stock_zh_a_spot_em_async() -> pd.DataFrame:
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url = "https://82.push2.eastmoney.com/api/qt/clist/get"
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params = {
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"pn": "1",
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"pz": "100",
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"po": "1",
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"np": "1",
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"ut": "bd1d9ddb04089700cf9c27f6f7426281",
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"fltt": "2",
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"invt": "2",
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"fid": "f12",
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"fs": "m:0 t:6,m:0 t:80,m:1 t:2,m:1 t:23,m:0 t:81 s:2048",
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"fields": "f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f12,f13,f14,f15,f16,f17,f18,"
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"f20,f21,f23,f24,f25,f22,f11,f62,f128,f136,f115,f152",
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}
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results = await fetch_all_pages_async(url, params)
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return process_data(results)
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def stock_zh_a_spot_em() -> pd.DataFrame:
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"""
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东方财富网-沪深京 A 股-实时行情 (同步接口)
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https://quote.eastmoney.com/center/gridlist.html#hs_a_board
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:return: 实时行情
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:rtype: pandas.DataFrame
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"""
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import nest_asyncio
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nest_asyncio.apply()
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return asyncio.run(stock_zh_a_spot_em_async())
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if __name__ == "__main__":
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df = stock_zh_a_spot_em()
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print(df)
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