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download_binance_kline.py

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+import requests
+import os
+import pandas as pd
+from io import BytesIO
+import psycopg2
+from psycopg2.extras import execute_values
+import logging
+from datetime import datetime
+import xml.etree.ElementTree as ET
+
+# 配置日志
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+# 配置参数
+BASE_URL = "https://data.binance.vision/data/futures/um/monthly/klines/"
+# 可以添加多个交易对，例如：["BOBUSDT", "BTCUSDT", "ETHUSDT"]
+SYMBOLS = ["BOBUSDT", "BTCUSDT"]  # BOBUSDT数据从2025-11开始可用
+INTERVAL = "1d"
+START_DATE = "2021-01"
+END_DATE = datetime.now().strftime("%Y-%m")
+
+# PostgreSQL配置
+DB_CONFIG = {
+    "host": "localhost",
+    "database": "your_database",
+    "user": "your_username",
+    "password": "your_password",
+    "port": 5432
+}
+
+# K线数据列名
+KLINE_COLUMNS = [
+    "open_time", "open", "high", "low", "close", "volume",
+    "close_time", "quote_asset_volume", "number_of_trades",
+    "taker_buy_base_asset_volume", "taker_buy_quote_asset_volume", "ignore"
+]
+
+def download_kline_data(symbol, interval, year_month):
+    """下载指定月份的K线数据"""
+    # 拆分年月
+    year, month = year_month.split("-")
+    filename = f"{symbol}-{interval}-{year}-{month}.zip"
+    url = f"{BASE_URL}{symbol}/{interval}/{filename}"
+    logger.info(f"Downloading {url}")
+    
+    # 配置代理
+    proxies = {
+        'http': 'http://localhost:1080',
+        'https': 'http://localhost:1080'
+    }
+    
+    try:
+        response = requests.get(url, proxies=proxies)
+        response.raise_for_status()
+        logger.info(f"Downloaded {filename} successfully")
+        return BytesIO(response.content)
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Failed to download {filename}: {e}")
+        return None
+
+def parse_kline_data(zip_data, symbol):
+    """解析下载的K线数据"""
+    try:
+        df = pd.read_csv(zip_data, compression='zip', header=None, names=KLINE_COLUMNS)
+        # 跳过标题行
+        df = df[df["open_time"] != "open_time"]
+        # 添加symbol列
+        df["symbol"] = symbol
+        # 转换时间戳为datetime
+        df["open_time"] = pd.to_datetime(df["open_time"], unit='ms')
+        df["close_time"] = pd.to_datetime(df["close_time"], unit='ms')
+        # 转换数值列
+        numeric_columns = ["open", "high", "low", "close", "volume", 
+                          "quote_asset_volume", "number_of_trades",
+                          "taker_buy_base_asset_volume", "taker_buy_quote_asset_volume", "ignore"]
+        df[numeric_columns] = df[numeric_columns].astype(float)
+        df["number_of_trades"] = df["number_of_trades"].astype(int)
+        logger.info(f"Parsed {len(df)} rows of K线 data")
+        return df
+    except Exception as e:
+        logger.error(f"Failed to parse K线 data: {e}")
+        return None
+
+def create_connection():
+    """创建PostgreSQL连接"""
+    try:
+        conn = psycopg2.connect(**DB_CONFIG)
+        logger.info("Connected to PostgreSQL database")
+        return conn
+    except psycopg2.OperationalError as e:
+        logger.error(f"Failed to connect to PostgreSQL: {e}")
+        return None
+
+def create_table(conn):
+    """创建K线数据表"""
+    create_table_query = """
+    CREATE TABLE IF NOT EXISTS binance_kline (
+        id SERIAL PRIMARY KEY,
+        symbol VARCHAR(20) NOT NULL,
+        open_time TIMESTAMP NOT NULL,
+        open NUMERIC(18, 8) NOT NULL,
+        high NUMERIC(18, 8) NOT NULL,
+        low NUMERIC(18, 8) NOT NULL,
+        close NUMERIC(18, 8) NOT NULL,
+        volume NUMERIC(18, 8) NOT NULL,
+        close_time TIMESTAMP NOT NULL,
+        quote_asset_volume NUMERIC(18, 8) NOT NULL,
+        number_of_trades INTEGER NOT NULL,
+        taker_buy_base_asset_volume NUMERIC(18, 8) NOT NULL,
+        taker_buy_quote_asset_volume NUMERIC(18, 8) NOT NULL,
+        ignore NUMERIC(18, 8) NOT NULL,
+        UNIQUE(symbol, open_time)
+    );
+    """
+    
+    try:
+        with conn.cursor() as cur:
+            cur.execute(create_table_query)
+        conn.commit()
+        logger.info("Created binance_kline table")
+    except psycopg2.Error as e:
+        logger.error(f"Failed to create table: {e}")
+        conn.rollback()
+
+def insert_data(conn, df):
+    """将K线数据插入到数据库"""
+    # 准备插入数据
+    insert_query = """
+    INSERT INTO binance_kline (
+        symbol, open_time, open, high, low, close, volume, 
+        close_time, quote_asset_volume, number_of_trades, 
+        taker_buy_base_asset_volume, taker_buy_quote_asset_volume, ignore
+    ) VALUES %s
+    ON CONFLICT (symbol, open_time) DO NOTHING;
+    """
+    
+    # 转换DataFrame为元组列表
+    data = [tuple(row) for row in df[df.columns[1:]].to_numpy()]  # 跳过id列
+    
+    try:
+        with conn.cursor() as cur:
+            execute_values(cur, insert_query, data)
+        conn.commit()
+        logger.info(f"Inserted {len(data)} rows into database")
+    except psycopg2.Error as e:
+        logger.error(f"Failed to insert data: {e}")
+        conn.rollback()
+
+def list_s3_files(url, timeout=10):
+    """
+    从S3存储桶的XML响应中提取所有文件的完整URL
+    
+    参数:
+        url: S3存储桶的列表URL，例如: https://s3-ap-northeast-1.amazonaws.com/data.binance.vision?delimiter=/&prefix=data/futures/um/monthly/klines/BOBUSDT/1d/
+        timeout: 请求超时时间，单位秒，默认10秒
+    
+    返回:
+        list: 完整的文件URL列表
+    """
+    logger.info(f"Listing files from {url}")
+    
+    # 配置代理
+    proxies = {
+        'http': 'http://localhost:1080',
+        'https': 'http://localhost:1080'
+    }
+    
+    try:
+        response = requests.get(url, timeout=timeout, proxies=proxies)
+        response.raise_for_status()
+        
+        # 解析XML响应
+        root = ET.fromstring(response.content)
+        
+        # S3 XML使用的命名空间
+        ns = {'s3': 'http://s3.amazonaws.com/doc/2006-03-01/'}
+        
+        # 基础下载URL
+        base_download_url = "https://data.binance.vision/"
+        
+        # 提取所有Key元素的文本，构建完整URL
+        file_urls = []
+        for key_elem in root.findall('.//s3:Key', ns):
+            file_path = key_elem.text
+            # 只返回zip文件
+            if file_path and file_path.endswith('.zip'):
+                # 构建完整URL
+                full_url = base_download_url + file_path
+                file_urls.append(full_url)
+        
+        logger.info(f"Found {len(file_urls)} files")
+        return file_urls
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Failed to list files from {url}: {e}")
+        return []
+    except ET.ParseError as e:
+        logger.error(f"Failed to parse XML response: {e}")
+        return []
+    except KeyboardInterrupt:
+        logger.error(f"Request to {url} was interrupted")
+        return []
+
+def download_kline_data_by_url(url):
+    """
+    通过完整URL下载K线数据
+    
+    参数:
+        url: 完整的K线数据下载URL
+    
+    返回:
+        BytesIO: 下载的数据，或None如果下载失败
+    """
+    logger.info(f"Downloading {url}")
+    
+    # 配置代理
+    proxies = {
+        'http': 'http://localhost:1080',
+        'https': 'http://localhost:1080'
+    }
+    
+    try:
+        response = requests.get(url, proxies=proxies)
+        response.raise_for_status()
+        filename = os.path.basename(url)
+        logger.info(f"Downloaded {filename} successfully")
+        return BytesIO(response.content)
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Failed to download {url}: {e}")
+        return None
+
+def main():
+    # 创建数据库连接
+    conn = create_connection()
+    if not conn:
+        return
+    
+    # 创建表
+    create_table(conn)
+    
+    for symbol in SYMBOLS:
+        # 使用list_s3_files函数获取可用的文件URL列表
+        s3_url = f"https://s3-ap-northeast-1.amazonaws.com/data.binance.vision?delimiter=/&prefix=data/futures/um/monthly/klines/{symbol}/{INTERVAL}/"
+        file_urls = list_s3_files(s3_url)
+        
+        if not file_urls:
+            logger.warning(f"No files found for {symbol}-{INTERVAL}")
+            continue
+        
+        # 处理每个文件URL
+        for file_url in file_urls:
+            # 从URL中提取文件名
+            filename = os.path.basename(file_url)
+            # 检查文件名格式
+            if not filename.endswith('.zip'):
+                continue
+            
+            # 解析文件名，提取交易对和年月信息
+            # 格式: symbol-interval-year-month.zip
+            parts = filename[:-4].split('-')  # 移除.zip后缀并拆分
+            if len(parts) != 4:
+                logger.warning(f"Invalid filename format: {filename}")
+                continue
+            
+            file_symbol, file_interval, year, month = parts
+            
+            # 下载数据
+            zip_data = download_kline_data_by_url(file_url)
+            if not zip_data:
+                continue
+            
+            # 解析数据
+            df = parse_kline_data(zip_data, file_symbol)
+            if df is None or df.empty:
+                continue
+            
+            # 插入数据
+            insert_data(conn, df)
+    
+    # 关闭连接
+    conn.close()
+    logger.info("Script completed successfully")
+
+if __name__ == "__main__":
+    main()

download_unzip_csv.py

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+import requests
+import pandas as pd
+from io import BytesIO
+import logging
+
+# 配置日志
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+def download_unzip_csv(url, **kwargs):
+    """
+    从URL下载文件，解压并返回CSV内容作为pandas DataFrame
+    
+    参数:
+        url: 文件下载URL
+        **kwargs: 传递给pandas.read_csv的额外参数
+        
+    返回:
+        pandas.DataFrame: 解压后的CSV内容
+    """
+    logger.info(f"Downloading file from {url}")
+    
+    try:
+        # 下载文件
+        response = requests.get(url)
+        response.raise_for_status()  # 检查下载是否成功
+        logger.info(f"Successfully downloaded file from {url}")
+        
+        # 使用BytesIO处理下载的内容
+        zip_data = BytesIO(response.content)
+        
+        # 读取并解压CSV文件
+        logger.info("Reading and decompressing CSV file")
+        df = pd.read_csv(zip_data, compression='zip', **kwargs)
+        
+        # 智能判定首行是否为标题行
+        def is_header_row(row):
+            """智能检测行是否为标题行"""
+            # 检查条件
+            conditions = [
+                # 1. 首行包含常见的时间相关列名
+                any(keyword in str(cell).lower() for keyword in ['time', 'date', 'datetime', 'timestamp'] for cell in row),
+                # 2. 首行包含常见的价格相关列名
+                any(keyword in str(cell).lower() for keyword in ['open', 'high', 'low', 'close', 'volume'] for cell in row),
+                # 3. 首行包含常见的交易相关列名
+                any(keyword in str(cell).lower() for keyword in ['taker', 'quote', 'count', 'ignore'] for cell in row),
+                # 4. 首行全为字符串，而第二行包含数值
+                len(df) > 1 and all(isinstance(str(cell), str) and not str(cell).replace('.', '').isdigit() for cell in row) and \
+                any(str(cell).replace('.', '').isdigit() for cell in df.iloc[1] if pd.notna(cell)),
+                # 5. 首行包含'_'字符（常见于编程命名的列名）
+                any('_' in str(cell) for cell in row)
+            ]
+            return any(conditions)
+        
+        if len(df) > 0 and is_header_row(df.iloc[0]):
+            df = df[1:].reset_index(drop=True)
+            logger.info("Skipped header row")
+        
+        # 转换数值列
+        numeric_columns = ['open', 'high', 'low', 'close', 'volume',
+                          'close_time', 'quote_asset_volume', 'number_of_trades',
+                          'taker_buy_volume', 'taker_buy_quote_volume', 'taker_buy_base_asset_volume',
+                          'taker_buy_quote_asset_volume', 'ignore']
+        
+        # 只转换存在的列
+        for col in numeric_columns:
+            if col in df.columns:
+                try:
+                    if col in ['number_of_trades', 'count']:
+                        df[col] = df[col].astype(int)
+                    else:
+                        df[col] = df[col].astype(float)
+                except ValueError:
+                    logger.warning(f"Could not convert column {col} to numeric type")
+        
+        logger.info(f"Successfully parsed CSV file with {len(df)} rows")
+        return df
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Failed to download file: {e}")
+        raise
+    except Exception as e:
+        logger.error(f"Failed to process file: {e}")
+        raise
+
+if __name__ == "__main__":
+    # 测试函数
+    test_url = "https://data.binance.vision/data/futures/um/monthly/klines/BTCUSDT/1d/BTCUSDT-1d-2024-01.zip"
+    
+    # CSV列名
+    columns = [
+        "open_time", "open", "high", "low", "close", "volume",
+        "close_time", "quote_asset_volume", "number_of_trades",
+        "taker_buy_base_asset_volume", "taker_buy_quote_asset_volume", "ignore"
+    ]
+    
+    try:
+        df = download_unzip_csv(test_url, header=None, names=columns)
+        print(f"DataFrame shape: {df.shape}")
+        print("DataFrame head:")
+        print(df.head())
+        print("DataFrame dtypes:")
+        print(df.dtypes)
+    except Exception as e:
+        print(f"Error: {e}")