The FFT class in the hana_ml.algorithms.pal.tsa.fft module is a Fast Fourier Transform that decomposes a function of time into the frequencies that make it up, with methods to apply the transform to input data and return the transformed data.
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Here is a Python code template based on the provided help doc:

```python
from hana_ml.algorithms.pal.tsa.fft import FFT
from hana_ml import DataFrame

# Assuming that connection_context is the connection object to HANA Database
# Assuming that df is the input data in the form of a HANA DataFrame

# Create a FFT instance
fft = FFT(conn_context)

# Apply Fast-Fourier-Transform to the input data
result = fft.apply(data=df, num_type='real', inverse=False, window='hamming', window_start=0, window_length=10, alpha=0.16, beta=8.6, attenuation=50.0, flattop_model='symmetric', flattop_precision='none', r=0.5, flattop_mode='symmetric')

# Print the transformed sequence
print(result.collect())
```

Please replace the placeholders with actual values before running the code.