From 7831c571e6f380b4e3a0775bd4d3af6e8c01027a Mon Sep 17 00:00:00 2001
From: zengbin93 <zeng_bin8888@163.com>
Date: Sun, 30 Aug 2020 14:45:53 +0800
Subject: [PATCH] =?UTF-8?q?0.5.3=20=E6=96=B0=E5=A2=9E=E8=81=9A=E5=AE=BDK?=
 =?UTF-8?q?=E7=BA=BF=E8=8E=B7=E5=8F=96?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 czsc/data/__init__.py |   0
 czsc/data/jq.py       | 148 ++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 148 insertions(+)
 create mode 100644 czsc/data/__init__.py
 create mode 100644 czsc/data/jq.py

diff --git a/czsc/data/__init__.py b/czsc/data/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/czsc/data/jq.py b/czsc/data/jq.py
new file mode 100644
index 0000000..d950fb6
--- /dev/null
+++ b/czsc/data/jq.py
@@ -0,0 +1,148 @@
+# coding: utf-8
+import os
+import pickle
+import json
+import requests
+import warnings
+import pandas as pd
+from datetime import datetime, timedelta
+
+url = "https://dataapi.joinquant.com/apis"
+home_path = os.path.expanduser("~")
+file_token = os.path.join(home_path, "jq.token")
+
+def set_token(jq_mob, jq_pwd):
+    """
+
+    :param jq_mob: str
+        mob是申请JQData时所填写的手机号
+    :param jq_pwd: str
+        Password为聚宽官网登录密码，新申请用户默认为手机号后6位
+    :return:
+    """
+    pickle.dump([jq_mob, jq_pwd], open(file_token, 'wb'))
+
+
+def get_token():
+    """获取调用凭证"""
+    if not os.path.exists(file_token):
+        raise ValueError(f"{file_token} 文件不存在，请先调用 set_token 进行设置")
+
+    jq_mob, jq_pwd = pickle.load(open(file_token, 'rb'))
+    body = {
+        "method": "get_current_token",
+        "mob": jq_mob,  # mob是申请JQData时所填写的手机号
+        "pwd": jq_pwd,  # Password为聚宽官网登录密码，新申请用户默认为手机号后6位
+    }
+    response = requests.post(url, data=json.dumps(body))
+    token = response.text
+    return 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_kline(symbol,  end_date: datetime, freq: str, start_date: datetime = None, count=None):
+    """获取K线数据
+
+    :param symbol: str
+        聚宽标的代码
+    :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.XSHG", start_date=start_date, end_date=end_date, freq="1min")
+    >>> df2 = get_kline(symbol="000001.XSHG", end_date=end_date, freq="1min", count=1000)
+    """
+    if count and count > 5000:
+        warnings.warn(f"count={count}, 超过5000的最大值限制，仅返回最后5000条记录")
+
+    # 1m, 5m, 15m, 30m, 60m, 120m, 1d, 1w, 1M
+    freq_convert = {"1min": "1m", "5min": '5m', '15min': '15m',
+                    "30min": "30m", "60min": '60m', "D": "1d", "W": '1w'}
+    if start_date:
+        data = {
+            "method": "get_price_period",
+            "token": get_token(),
+            "code": symbol,
+            "unit": freq_convert[freq],
+            "date": start_date.strftime("%Y-%m-%d"),
+            "end_date": end_date.strftime("%Y-%m-%d"),
+            # "fq_ref_date": end_date
+        }
+    elif count:
+        data = {
+            "method": "get_price",
+            "token": get_token(),
+            "code": symbol,
+            "count": count,
+            "unit": freq_convert[freq],
+            "end_date": end_date.strftime("%Y-%m-%d"),
+            # "fq_ref_date": end_date
+        }
+    else:
+        raise ValueError("start_date 和 count 不能同时为空")
+
+    r = requests.post(url, data=json.dumps(data))
+    df = text2df(r.text)
+    df['symbol'] = symbol
+    df.rename({'date': 'dt', 'volume': 'vol'}, axis=1, inplace=True)
+    df = df[['symbol', 'dt', 'open', 'close', 'high', 'low', 'vol']]
+    for col in ['open', 'close', 'high', 'low', 'vol']:
+        df.loc[:, col] = df[col].apply(lambda x: round(float(x), 2))
+    df.loc[:, "dt"] = pd.to_datetime(df['dt'])
+    return df
+
+
+def download_kline(symbol, freq: str, start_date: datetime, end_date: datetime, delta: timedelta, 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.XSHG", "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
-- 
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