TASE 以色列股市 API 介面詳解：獲取股票資料、行情與量化對接

      import requests

# 配置您的 API 金鑰
API_TOKEN = "your_token_here"
headers = {
    "accept": "application/json",
    "token": API_TOKEN
}

# 定義請求參數
# 實際使用時請參考 iTick 官方產品清單取得正確的 code
region = "IL"
code = "TEVA"

url = f"https://api.itick.org/stock/quote?region={region}&code={code}"

try:
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        data = response.json().get('data', {})
        print(f"股票: {code}.{region}")
        print(f"最新價: {data.get('ld')}")          # latest price
        print(f"漲跌幅: {data.get('chp')}%")        # change percent
        print(f"開盤價: {data.get('o')}")           # open price
        print(f"最高價: {data.get('h')}")           # high price
        print(f"最低價: {data.get('l')}")           # low price
        print(f"成交量: {data.get('v')}")           # volume
    else:
        print(f"請求失敗，狀態碼: {response.status_code}, 錯誤: {response.text}")
except Exception as e:
    print(f"網路異常: {e}")

    

      import requests
import pandas as pd

API_TOKEN = "your_token_here"
headers = {
    "accept": "application/json",
    "token": API_TOKEN
}

# 獲取以色列股票的日線資料
region = "IL"
code = "TEVA"  # 範例代碼
kType = "8"    # 8 代表日線
limit = "100"  # 獲取最近100根

url = f"https://api.itick.org/stock/kline?region={region}&code={code}&kType={kType}&limit={limit}"

response = requests.get(url, headers=headers)

if response.status_code == 200:
    kline_data = response.json().get('data', [])
    if kline_data:
        # 將資料轉換為 pandas DataFrame，便於分析
        df = pd.DataFrame(kline_data)
        # 通常返回的欄位包括：t(時間), o(開), h(高), l(低), c(收), v(量)
        df = df.rename(columns={'t': 'timestamp', 'o': 'open', 'h': 'high', 'l': 'low', 'c': 'close', 'v': 'volume'})
        df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s')  # 轉換時間戳
        print(df[['timestamp', 'open', 'high', 'low', 'close', 'volume']].head())
    else:
        print("未獲取到資料")
else:
    print("請求失敗")

    

      import websocket
import json
import threading

WS_URL = "wss://api.itick.org/stock"  # 股票行情 WebSocket 地址
API_TOKEN = "your_token_here"

def on_open(ws):
    """連線建立後，發送訂閱訊息"""
    print("連線已開啟，正在訂閱 TASE 股票...")

    # 訂閱訊息：訂閱以色列市場 TEVA 股票的報價(quote)與成交(tick)
    subscribe_msg = {
        "ac": "subscribe",
        "params": "TEVA$IL",  # 格式：代碼$市場
        "types": "quote,tick"   # 訂閱資料類型：報價與逐筆成交
    }
    ws.send(json.dumps(subscribe_msg))

def on_message(ws, message):
    """處理收到的即時資料"""
    data = json.loads(message)
    # 此處可加入您的策略邏輯
    print(f"即時資料: {data}")

def on_error(ws, error):
    print(f"錯誤: {error}")

def on_close(ws, close_status_code, close_msg):
    print("連線已關閉")

if __name__ == "__main__":
    # 在 header 中傳遞 token
    ws = websocket.WebSocketApp(WS_URL,
                                header={"token": API_TOKEN},
                                on_open=on_open,
                                on_message=on_message,
                                on_error=on_error,
                                on_close=on_close)

    # 在後台執行緒中運行 WebSocket 用戶端，避免阻塞主執行緒
    wst = threading.Thread(target=ws.run_forever)
    wst.start()

    # 此處可繼續執行其他任務
    try:
        while True:
            # 主執行緒保持運行
            pass
    except KeyboardInterrupt:
        ws.close()

    

      # 假設我們已經透過 REST API 獲取了 TASE 股票的日線資料並存在 df 中
# df 包含 'close' 欄

import talib

# 計算短期與長期移動平均線
df['MA_Short'] = talib.SMA(df['close'], timeperiod=20)
df['MA_Long'] = talib.SMA(df['close'], timeperiod=60)

# 取得最新兩筆資料判斷金叉／死叉
if df['MA_Short'].iloc[-2] <= df['MA_Long'].iloc[-2] and df['MA_Short'].iloc[-1] > df['MA_Long'].iloc[-1]:
    print("金叉訊號出現！考慮買入 TASE 股票")
    signal = "BUY"
elif df['MA_Short'].iloc[-2] >= df['MA_Long'].iloc[-2] and df['MA_Short'].iloc[-1] < df['MA_Long'].iloc[-1]:
    print("死叉訊號出現！考慮賣出 TASE 股票")
    signal = "SELL"
else:
    signal = "HOLD"
    print("無明確訊號，繼續持有或觀望")

# 此處可將訊號接入您的交易系統