index_perf_30
Retrieve performance data for stock indices over the past 30 days to analyze market trends and investment returns.
Instructions
获取指数最近30天收益数据
Args:
index_code: 指数代码
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| index_code | No | SZ000002 |
Implementation Reference
- main.py:354-362 (handler)Handler function for the 'index_perf_30' tool. Decorated with @mcp.tool() for registration. Fetches index performance data over the last 30 days using pysnowball.ball.index_perf_30 and processes the result with process_data.@mcp.tool() def index_perf_30(index_code: str="SZ000002") -> dict: """获取指数最近30天收益数据 Args: index_code: 指数代码 """ result = ball.index_perf_30(index_code) return process_data(result)
- main.py:354-354 (registration)The @mcp.tool() decorator registers the index_perf_30 function as an MCP tool.@mcp.tool()
- main.py:34-62 (helper)Helper function used by index_perf_30 (and other tools) to process the raw data, including timestamp conversion.def process_data(data, process_config=None): """ 通用数据处理函数，可扩展添加各种数据处理操作 Args: data: 原始数据 process_config: 处理配置字典，用于指定要执行的处理操作 例如: {'convert_timestamps': True, 'other_process': params} Returns: 处理后的数据 """ if process_config is None: # 默认配置 process_config = { 'convert_timestamps': True } # 如果开启了时间戳转换 if process_config.get('convert_timestamps', True): data = convert_timestamps(data) # 在这里可以添加更多的数据处理逻辑 # 例如: # if 'format_numbers' in process_config: # data = format_numbers(data, **process_config['format_numbers']) return data
- main.py:14-31 (helper)Supporting helper recursively converts timestamps in the data to readable datetime strings, called by process_data.def convert_timestamps(data): """递归地将数据中的所有 timestamp 转换为 datetime 字符串""" if isinstance(data, dict): for key, value in list(data.items()): if key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000000: # 毫秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S') elif key == 'timestamp' and isinstance(value, (int, float)) and value > 1000000000: # 秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S') elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000000: # 毫秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value/1000).strftime('%Y-%m-%d %H:%M:%S') elif key.endswith('_date') and isinstance(value, (int, float)) and value > 1000000000: # 秒级时间戳 data[key] = datetime.datetime.fromtimestamp(value).strftime('%Y-%m-%d %H:%M:%S') elif isinstance(value, (dict, list)): data[key] = convert_timestamps(value) elif isinstance(data, list): for i, item in enumerate(data): data[i] = convert_timestamps(item) return data