Examples

Simple illustrative examples on how you can quickly start using the Paralytics in your projects.

Discretization

Let’s suppose that we want to discretize continuous variables. With use of the Discretization transformer we can do it right away, because the transformer will recognize which variables are of the continuous type.

import numpy as np
import pandas as pd
import paralytics as prl


# Fix the seed for reproducibility.
SEED = 42
np.random.seed(SEED)

# Create available categories for non-numeric variable.
sexes = ['female', 'male', 'child']

# Generate example DataFrame.
X = pd.DataFrame({
    'NormalVariable': np.random.normal(loc=0, scale=10, size=100),
    'UniformVariable': np.random.uniform(low=0, high=100, size=100),
    'IntVariable': np.random.randint(low=0, high=100, size=100),
    'Sex': np.random.choice(sexes, 100, p=[.5, .3, .2])
})

# Generate response variable.
y = np.random.randint(low=0, high=2, size=100)

# Do discretization.
discretizer = prl.Discretizer(max_bins=5, random_state=SEED)
X_discretized = discretizer.fit_transform(X, y)

The X_discretized dataframe is already a fully discretized equivalent of the input dataframe X. First five rows will look like presented below.

	NormalVariable	UniformVariable	IntVariable	Sex
0	(-3.886, inf]	(33.151, inf]	(63.5, inf]	child
1	(-3.886, inf]	(-inf, 24.071]	(-inf, 28.0]	female
2	(-3.886, inf]	(-inf, 24.071]	(28.0, 63.5]	female
3	(-3.886, inf]	(33.151, inf]	(63.5, inf]	male
4	(-3.886, inf]	(33.151, inf]	(-inf, 28.0]	male

Forcing Context Manager

Let’s suppose that we want to create a class which methods will only be available if the instance is created using the context manager. We will get this functionality in the following way.

from paralytics import force_context_manager


@force_context_manager
class ExamplePrinter(object):
    def __init__(self):
        print('You just initiated me.')

    def open(self):
        print('I am opened.')

    def __exit__(exc_type, exc_value, traceback):
        print('...and now I am closed.')


if __name__ == '__main__':
    example = ExamplePrinter()
    try:
        # Access methods without prior instance creation using the context
        # manager results in raising an exception.
        example.open()
    except RuntimeError as e:
        print(
            'Error message without using the context manager: \n\n"{}"\n\n'
            'Now we will try to do the same but with use of the '
            '`with` statement:\n'
            .format(e)
        )
        # This time no exception occurs.
        with ExamplePrinter() as example:
            example.open()

Assuming the Python code above is saved into a file called example.py it can be run at the command line with the result below:

$ python example.py

Error message without using the context manager:

"Object of the ExamplePrinter should only be initialized with the `with` statement.
Otherwise, the ExamplePrinter methods will not be available."

Now we will try to do the same but with use of the `with` statement:

You just initialized me.
I am opened.
...and now I am closed.

Main advantage of using the force_context_manager function as a decorator allows to enforce good practices and call the closing method __exit__ without worrying about remembering it.