From 483298d17e16e8e63a790ee56c875cf125f01ada Mon Sep 17 00:00:00 2001 From: zengbin93 Date: Sun, 13 Sep 2020 16:51:36 +0800 Subject: [PATCH] =?UTF-8?q?0.5.4=20=E7=BB=9F=E4=B8=80=E8=81=9A=E5=AE=BD?= =?UTF-8?q?=E5=92=8C=20tushare=20=E7=9A=84=E6=95=B0=E6=8D=AE=E8=8E=B7?= =?UTF-8?q?=E5=8F=96API?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- czsc/data/jq.py | 13 ++- czsc/data/ts.py | 220 ++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 225 insertions(+), 8 deletions(-) create mode 100644 czsc/data/ts.py diff --git a/czsc/data/jq.py b/czsc/data/jq.py index daf5dda..bc0878a 100644 --- a/czsc/data/jq.py +++ b/czsc/data/jq.py @@ -6,7 +6,6 @@ import requests import warnings import pandas as pd from datetime import datetime, timedelta -from typing import List, Union url = "https://dataapi.joinquant.com/apis" home_path = os.path.expanduser("~") @@ -46,7 +45,7 @@ def text2df(text): return df -def get_concepts() -> pd.DataFrame: +def get_concepts(): """获取概念列表 https://dataapi.joinquant.com/docs#get_concepts---%E8%8E%B7%E5%8F%96%E6%A6%82%E5%BF%B5%E5%88%97%E8%A1%A8 @@ -61,8 +60,7 @@ def get_concepts() -> pd.DataFrame: df = text2df(r.text) return df -def get_concept_stocks(symbol: str, - date: Union[datetime, str] = None) -> List: +def get_concept_stocks(symbol, date=None): """获取概念成份股 https://dataapi.joinquant.com/docs#get_concept_stocks---%E8%8E%B7%E5%8F%96%E6%A6%82%E5%BF%B5%E6%88%90%E4%BB%BD%E8%82%A1 @@ -94,8 +92,7 @@ def get_concept_stocks(symbol: str, return r.text.split('\n') -def get_index_stocks(symbol: str, - date: Union[datetime, str] = None) -> List: +def get_index_stocks(symbol, date=None): """获取指数成份股 https://dataapi.joinquant.com/docs#get_index_stocks---%E8%8E%B7%E5%8F%96%E6%8C%87%E6%95%B0%E6%88%90%E4%BB%BD%E8%82%A1 @@ -127,7 +124,7 @@ def get_index_stocks(symbol: str, return r.text.split('\n') -def get_kline(symbol, end_date: datetime, freq: str, start_date: datetime = None, count=None): +def get_kline(symbol, end_date, freq, start_date=None, count=None): """获取K线数据 :param symbol: str @@ -187,7 +184,7 @@ def get_kline(symbol, end_date: datetime, freq: str, start_date: datetime = Non return df -def download_kline(symbol, freq: str, start_date: datetime, end_date: datetime, delta: timedelta, save=True): +def download_kline(symbol, freq, start_date, end_date, delta, save=True): """下载K线数据 :param save: diff --git a/czsc/data/ts.py b/czsc/data/ts.py new file mode 100644 index 0000000..33a13be --- /dev/null +++ b/czsc/data/ts.py @@ -0,0 +1,220 @@ +# coding: utf-8 +import pandas as pd +import tushare as ts +from datetime import datetime, timedelta + + +pro = ts.pro_api() + + +def set_token(token): + """在同一台机器上只需要调用 set_token 一次就可以 + + :param token: str + tushare.pro 的 token，如果没有，请到这里注册：https://tushare.pro/register?reg=7 + :return: None + """ + ts.set_token(token) + + +def get_token(): + """获取调用凭证""" + return ts.get_token() + + +def text2df(text): + rows = [x.split(",") for x in text.strip().split('\n')] + df = pd.DataFrame(rows[1:], columns=rows[0]) + return df + + +def get_concepts(): + """获取概念列表 + + https://dataapi.joinquant.com/docs#get_concepts---%E8%8E%B7%E5%8F%96%E6%A6%82%E5%BF%B5%E5%88%97%E8%A1%A8 + + :return: df + """ + return pro.concept(src='ts') + +def get_concept_stocks(symbol, date=None): + """获取概念成份股 + + https://tushare.pro/document/2?doc_id=126 + + :param symbol: str + 如 GN036 + :param date: str or datetime + 日期，如 2020-08-08 + :return: list + + examples: + ------- + >>> symbols1 = get_concept_stocks("GN036", date="2020-07-08") + >>> symbols2 = get_concept_stocks("GN036", date=datetime.now()) + """ + del date + df = pro.concept_detail(id=symbol, fields='ts_code') + return [x + "-E" for x in df.ts_code] + +def get_index_stocks(symbol, date=None): + """获取指数成份股 + + https://dataapi.joinquant.com/docs#get_index_stocks---%E8%8E%B7%E5%8F%96%E6%8C%87%E6%95%B0%E6%88%90%E4%BB%BD%E8%82%A1 + + :param symbol: str + 如 399300.SZ + :param date: str or datetime + 日期，如 2020-08-08 + :return: list + + examples: + ------- + >>> symbols1 = get_index_stocks("000300.XSHG", date="2020-07-08") + >>> symbols2 = get_index_stocks("000300.XSHG", date=datetime.now()) + """ + if not date: + date = datetime.now() + + if isinstance(date, str): + if "-" in date: + date = datetime.strptime(date, "%Y-%m-%d") + else: + date = datetime.strptime(date, "%Y%m%d") + + start_date = date - timedelta(days=250) + end_date = date + + df = pro.index_weight(index_code=symbol, start_date=start_date.strftime("%Y%m%d"), + end_date=end_date.strftime("%Y%m%d")) + return [x + "-E" for x in df.con_code] + + +def _get_start_date(end_date, freq): + if isinstance(end_date, str): + end_date = datetime.strptime(end_date, '%Y%m%d') + + if freq == '1min': + start_date = end_date - timedelta(days=30) + elif freq == '5min': + start_date = end_date - timedelta(days=70) + elif freq == '30min': + start_date = end_date - timedelta(days=500) + elif freq == 'D': + start_date = end_date - timedelta(weeks=500) + elif freq == 'W': + start_date = end_date - timedelta(weeks=1000) + else: + raise ValueError("'freq' value error, current value is %s, " + "optional valid values are ['1min', '5min', '30min', " + "'D', 'W']" % freq) + return start_date + +def get_kline(symbol, end_date, freq, start_date=None, count=None): + """获取K线数据 + + :param symbol: str + Tushare 标的代码 + Tushare asset 代码，如 000001.SH-I + :param start_date: datetime + 截止日期 + :param end_date: datetime + 截止日期 + :param freq: str + K线级别，可选值 ['1min', '5min', '30min', '60min', 'D', 'W'] + :param count: int + K线数量，最大值为 5000 + :return: pd.DataFrame + + >>> start_date = datetime.strptime("20200701", "%Y%m%d") + >>> end_date = datetime.strptime("20200719", "%Y%m%d") + >>> df1 = get_kline(symbol="000001.SH-I", start_date=start_date, end_date=end_date, freq="1min") + >>> df2 = get_kline(symbol="000001.SH-I", end_date=end_date, freq="1min", count=1000) + """ + ts_code, asset = symbol.split("-") + if count: + start_date = _get_start_date(end_date, freq) + start_date = start_date.date().__str__().replace("-", "") + + if isinstance(end_date, str): + end_date = datetime.strptime(end_date, '%Y%m%d') + + end_date = end_date + timedelta(days=1) + end_date = end_date.date().__str__().replace("-", "") + + if isinstance(end_date, datetime): + end_date = end_date.date().__str__().replace("-", "") + + if isinstance(start_date, datetime): + start_date = start_date.date().__str__().replace("-", "") + + df = ts.pro_bar(ts_code=ts_code, freq=freq, start_date=start_date, end_date=end_date, + adj='qfq', asset=asset) + + # 统一 k 线数据格式为 6 列，分别是 ["symbol", "dt", "open", "close", "high", "low", "vr"] + if "min" in freq: + df.rename(columns={'ts_code': "symbol", "trade_time": "dt"}, inplace=True) + else: + df.rename(columns={'ts_code': "symbol", "trade_date": "dt"}, inplace=True) + + df.drop_duplicates(subset='dt', keep='first', inplace=True) + df.sort_values('dt', inplace=True) + df['dt'] = df.dt.apply(str) + if freq.endswith("min"): + # 清理 9:30 的空数据 + df['not_start'] = df.dt.apply(lambda x: not x.endswith("09:30:00")) + df = df[df['not_start']] + if count: + df = df.tail(count) + + df.reset_index(drop=True, inplace=True) + df.loc[:, "dt"] = pd.to_datetime(df['dt']) + + k = df[['symbol', 'dt', 'open', 'close', 'high', 'low', 'vol']] + + for col in ['open', 'close', 'high', 'low']: + k[col] = k[col].apply(round, args=(2,)) + + return k + + +def download_kline(symbol, freq, start_date, end_date, delta, save=True): + """下载K线数据 + + :param save: + :param symbol: + :param end_date: + :param freq: + :param start_date: + :param delta: + :return: + + >>> start_date = datetime.strptime("20200101", "%Y%m%d") + >>> end_date = datetime.strptime("20200719", "%Y%m%d") + >>> df = download_kline("000001.SH-I", "1min", start_date, end_date, delta=timedelta(days=10), save=False) + """ + data = [] + end_dt = start_date + delta + print("开始下载数据：{} - {} - {}".format(symbol, start_date, end_date)) + df_ = get_kline(symbol, start_date=start_date, end_date=end_dt, freq=freq) + if not df_.empty: + data.append(df_) + + while end_dt < end_date: + df_ = get_kline(symbol, start_date=start_date, end_date=end_dt, freq=freq) + if not df_.empty: + data.append(df_) + start_date = end_dt + end_dt += delta + print("当前下载进度：{} - {} - {}".format(symbol, start_date, end_dt)) + + df = pd.concat(data, ignore_index=True) + print("{} 去重前K线数量为 {}".format(symbol, len(df))) + df.drop_duplicates(['dt'], inplace=True) + df.sort_values('dt', ascending=True, inplace=True) + df.reset_index(drop=True, inplace=True) + print("{} 去重后K线数量为 {}".format(symbol, len(df))) + + if save: + df.to_csv(f"{symbol}_{freq}_{start_date.date()}_{end_date.date()}.csv", index=False, encoding="utf-8") + else: + return df -- GitLab