The gamma function in the hana_ml.algorithms.pal.random module draws samples from a gamma distribution, allowing users to specify the shape, scale, number of random data to be generated, seed for the random number generator, and the proportion of available threads to use.
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Here is a Python code template based on the provided documentation:

```python
from hana_ml.algorithms.pal.random import gamma
from hana_ml import dataframe as df

# Create a connection context
cc = df.ConnectionContext(address='<address>', port='<port>', user='<user>', password='<password>')

# Define parameters
shape = 1
scale = 1
num_random = 100
seed = None
thread_ratio = None

# Draw samples from a gamma distribution
res = gamma(conn_context=cc, shape=shape, scale=scale, num_random=num_random, seed=seed, thread_ratio=thread_ratio)

# Print the generated random samples
print(res.collect())
```

Please replace `<address>`, `<port>`, `<user>`, and `<password>` with your actual database connection details. You can also adjust the parameters `shape`, `scale`, `num_random`, `seed`, and `thread_ratio` as per your requirements.