feat: 首次提交，包含多因子状态机量化策略及 TG 机器人监听服务

2026-07-05 19:32:31 +08:00
commit 0ae7f38f20
7 changed files with 752 additions and 0 deletions
@@ -0,0 +1,89 @@
+import requests
+import pandas as pd
+
+CN_CODE_TYPE = {
+    "600":'sh',
+    "601":'sh',
+    "603":'sh',
+    "605":'sh',
+    "000":'sz',
+    "300":'sz',
+    "688":'sh',
+    "002":'sz',
+    "50":"sh",
+    "51":"sh",
+    "52":"sh",
+    "16":"sz",
+    "15":"sz",
+    "18":"sz"
+    }
+
+
+
+def get_history_k(code, start_date='19700101', end_date=None):
+
+    if '.' in code:
+        code = code.split('.')[0]
+
+    stock_code = ''
+
+    if code[0:2] in CN_CODE_TYPE:
+        stock_code = code + '.' + CN_CODE_TYPE[code[0:2]]
+    elif code[0:3] in CN_CODE_TYPE:
+        stock_code = code + '.' + CN_CODE_TYPE[code[0:3]]
+    print(stock_code)
+    if stock_code != '':
+
+        url = "https://api.zhituapi.com/hs/history/%s/d/f?token=6E0E86BC-15AD-4275-8A95-B02D168D63C1&st=%s"%(stock_code, start_date)
+
+        if end_date is not None:
+            url += "&end_date=%s"%(end_date)
+
+        response = requests.get(url)
+
+        data = response.json()
+        print(data)
+        df = pd.DataFrame(data)
+
+        df['t'] = df['t'].apply(pd.to_datetime)
+        df.rename({'t': 'date', 'o': 'open', 'h': 'high', 'l': 'low', 'c': 'close', 'v': 'volume', 'a': 'amount'},
+                  axis='columns', inplace=True)
+        df = df[['date', 'open', 'high', 'low', 'close', 'volume', 'amount']].set_index('date')
+
+    else:
+        df = pd.DataFrame()
+
+
+    return df
+
+
+def get_5min_k(code, start_date='19700101', end_date=None):
+    stock_code = ''
+
+    if code[0:2] in CN_CODE_TYPE:
+        stock_code = code + '.' + CN_CODE_TYPE[code[0:2]]
+    elif code[0:3] in CN_CODE_TYPE:
+        stock_code = code + '.' + CN_CODE_TYPE[code[0:3]]
+
+    if stock_code != '':
+
+        url = "https://api.zhituapi.com/hs/history/%s/5/n?token=6E0E86BC-15AD-4275-8A95-B02D168D63C1&st=%s"%(stock_code, start_date)
+
+        if end_date is not None:
+            url += "&end_date=%s"%(end_date)
+
+        response = requests.get(url)
+
+        data = response.json()
+
+        df = pd.DataFrame(data)
+        df['t'] = df['t'].apply(pd.to_datetime)
+        df.rename({'t': 'date', 'o': 'open', 'h': 'high', 'l': 'low', 'c': 'close', 'v': 'volume', 'a': 'amount'},
+                  axis='columns', inplace=True)
+        df = df[['date','close', 'volume']].set_index('date')
+
+    else:
+        df = pd.DataFrame()
+
+
+    return df