### Retrieve Custom Factor Data (Python)

Source: https://quant.10jqka.com.cn/view/help/8/index

This Python function `get_sfactor_data` is used to retrieve pre-calculated custom factor data from the SuperMind platform. It requires specifying the start date, end date, a list of stock symbols, and a list of factor names to fetch.

```python
from supermind import get_sfactor_data

# Example: Get 'trix' factor data for specific stocks and date range
start_date = '2017-01-01'
end_date = '2018-10-10'
stocks = ['000001.SZ', '000002.SZ']
factors = ['trix']

trix_data = get_sfactor_data(start_date, end_date, stocks, factors)

# trix_data will be a dictionary where keys are factor names and values are pandas DataFrames
# print(trix_data['trix'].head())
```

--------------------------------

### Custom Factor Algorithm Example (Python)

Source: https://quant.10jqka.com.cn/view/help/8/index

This Python code snippet demonstrates how to define a custom factor algorithm within the SuperMind platform. It includes a placeholder function `sfactor_data` where users can implement their logic for calculating factor values using provided data. The function must return a dictionary with factor names as keys and pandas DataFrames as values.

```python
def sfactor_data(context):
    # context object contains data and parameters for factor calculation
    # Example: Fetching data for 'close' price
    close_data = context.get_data('close')
    
    # Example: Calculating a simple moving average (SMA)
    sma_10 = close_data.rolling(window=10).mean()
    
    # Example: Calculating a custom factor (e.g., Price - SMA10)
    custom_factor_values = close_data - sma_10
    
    # Return the factor values in the required dictionary format
    # 'key' is the factor name, 'value' is a pandas DataFrame
    return {
        'my_custom_factor': custom_factor_values
    }
```

--------------------------------

### CSV Factor Upload Format

Source: https://quant.10jqka.com.cn/view/help/8/index

This example illustrates the required CSV format for uploading custom factor data. The CSV file must contain three columns: 'symbol' for the stock ticker, 'date' in 'YYYY-MM-DD' format, and 'value' for the calculated factor value.

```csv
symbol,date,value
000001.SZ,2017-03-02,0.5
000001.SZ,2017-03-03,0.6
000002.SZ,2017-03-02,1.2
000002.SZ,2017-03-03,1.1
```

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