3 資料庫測試

.github/workflows/AutoUpdate.yml

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+name: Auto Update
+
+on:
+  schedule:
+    - cron: "0 */12 * * *"  # 每 12 小時執行一次
+  workflow_dispatch:  # 允許手動觸發
+
+jobs:
+  run_yfinanceTest:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2  # 檢出您的代碼
+
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: '3.9'  # Python 版本
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt  # 如果有 requirements.txt 檔案，否則手動指定需求
+
+      - name: Run yfinanceTest.py
+        run: python yfinanceTest.py  # 執行您的 yfinanceTest.py

FinMine,py

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+from FinMind.data import DataLoader
+
+api = DataLoader()
+# api.login_by_token(api_token='token')
+# api.login(user_id='user_id',password='password')
+# df = api.taiwan_stock_daily(
+#     stock_id='2330',
+#     start_date='2024-08-02',
+#     end_date='2024-08-7'
+# )
+df = api.us_stock_info()
+print(df)
+df = api.us_stock_price(
+    stock_id='AAPL',
+    start_date='2024-08-02',
+    end_date='2024-08-7'
+)
+print(df)

mongoDB.py

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+from pymongo import MongoClient
+
+class MongoDBClient:
+    def __init__(self, uri, db_name):
+        """
+        初始化 MongoDB 客戶端。
+
+        :param uri: MongoDB 連接字串
+        :param db_name: 資料庫名稱
+        """
+        self.client = MongoClient(uri)
+        self.db = self.client[db_name]
+        self.user_collection = self.db['User']
+
+    def insert_users(self, users):
+        """
+        插入多筆使用者資料到 User 表格。
+
+        :param users: 使用者資料的列表
+        """
+        try:
+            result = self.user_collection.insert_many(users)
+            print(f"成功插入 {len(result.inserted_ids)} 筆資料。")
+        except Exception as e:
+            print(f"插入資料時出現錯誤: {e}")
+
+    def find_user_by_name(self, name):
+        """
+        根據使用者姓名查詢使用者資料。
+
+        :param name: 使用者姓名
+        :return: 查詢結果
+        """
+        try:
+            user = self.user_collection.find_one({"name": name})
+            return user
+        except Exception as e:
+            print(f"查詢資料時出現錯誤: {e}")
+
+    def list_all_users(self):
+        """
+        列出所有使用者資料。
+
+        :return: 使用者資料的列表
+        """
+        try:
+            users = list(self.user_collection.find())
+            return users
+        except Exception as e:
+            print(f"查詢資料時出現錯誤: {e}")
+
+if __name__ == "__main__":
+    # 替換為您的 MongoDB 連接字串
+    user_name = "test"
+    password = "test"
+    uri = f"mongodb+srv://{user_name}:{password}@cluster0.zp7plle.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0"
+    db_name = "DevOps_Final_Project"
+
+    # 初始化客戶端
+    mongo_client = MongoDBClient(uri, db_name)
+
+    # 範例使用者資料
+    users = [
+        {"name": "張三", "email": "zhangsan@example.com", "age": 25},
+        {"name": "李四", "email": "lisi@example.com", "age": 30},
+        {"name": "王五", "email": "wangwu@example.com", "age": 28}
+    ]
+
+    # 插入使用者資料
+    mongo_client.insert_users(users)
+
+    # 查詢特定使用者
+    user = mongo_client.find_user_by_name("李四")
+    if user:
+        print("查詢結果：", user)
+    else:
+        print("找不到該使用者。")
+
+    # 列出所有使用者
+    all_users = mongo_client.list_all_users()
+    print("所有使用者資料：")
+    for user in all_users:
+        print(user)
+

twseAPI.py

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+# 引入requests庫
+import requests
+import json, pandas as pd
+
+# 定義API的URL
+# url = 'https://openapi.twse.com.tw/v1/exchangeReport/STOCK_DAY_ALL'  
+url = 'https://openapi.twse.com.tw/v1/exchangeReport/MI_5MINS'
+# 發送GET請求
+res = requests.get(url)
+print(res)
+jsondata = json.loads(res.text)
+# jsondata
+
+# 引入pandas庫
+# 將JSON數據轉換為DataFrame
+df = pd.DataFrame(jsondata)
+# df.set_index("Code", inplace=True)
+# df.replace('', '0', inplace=True)
+# df[df.columns.difference(['Name'])] = df[df.columns.difference(['Name'])].astype(float)
+print(df)
+

yfinanceTest.py

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+import yfinance as yf
+import matplotlib.pyplot as plt
+
+#import yfinance as yf
+
+# Initialize the Ticker object for Apple (AAPL)
+apple_stock = yf.Ticker("AAPL")
+
+# Fetch historical data for the past year
+# df = apple_stock.history(period="5d")
+
+# # Display data
+# print(df)
+
+# # Optional: Plot closing prices
+
+# plt.figure(figsize=(12, 6))
+# plt.plot(df.index, df['Close'], label='AAPL Close Price')
+# plt.title('Apple Stock Closing Prices Over the Past Year')
+# plt.xlabel('Date')
+# plt.ylabel('Close Price (USD)')
+# plt.legend()
+# plt.show()
+
+
+df = apple_stock.history(period="1y")
+
+# 計算每日漲跌幅
+df['Change'] = df['Close'].diff()  # 計算每日與前一天的差異
+df['Color'] = df['Change'].apply(lambda x: 'red' if x < 0 else 'green')  # 設定顏色，跌為紅色，漲為綠色
+
+# 繪製圖表
+plt.figure(figsize=(12, 6))
+for i in range(1, len(df)):
+    plt.plot([df.index[i-1], df.index[i]], [df['Close'][i-1], df['Close'][i]], 
+             color=df['Color'][i], linewidth=1.5)  # 根據漲跌幅選顏色
+
+# 添加標題和標籤
+plt.title('Apple Stock Closing Prices Over the Past Year with Gains and Losses')
+plt.xlabel('Date')
+plt.ylabel('Close Price (USD)')
+plt.show()
+
+