earningforecast
Retrieve annual earnings forecast data for specific stocks to analyze company performance projections and inform investment decisions.
Instructions
按年度获取业绩预告数据
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| stock_code | No | SZ000002 |
Implementation Reference
- main.py:92-96 (handler)The main handler function for the 'earningforecast' MCP tool. Decorated with @mcp.tool() for registration. Calls pysnowball.ball.earningforecast(stock_code), processes the result with process_data(), and returns a dict.
@mcp.tool() def earningforecast(stock_code: str="SZ000002") -> dict: """按年度获取业绩预告数据""" result = ball.earningforecast(stock_code) return process_data(result) - main.py:93-94 (schema)Input/output schema defined by function signature: stock_code (str, default 'SZ000002') -> dict. Docstring: 'Get performance forecast data by year'.
def earningforecast(stock_code: str="SZ000002") -> dict: """按年度获取业绩预告数据""" - main.py:34-61 (helper)Helper utility for processing raw data from pysnowball APIs. By default converts timestamps to readable datetime strings. Used by all tools including earningforecast.
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 recursive function to convert timestamp fields (and _date fields) in nested data structures to formatted 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