get_data.py

from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
import numpy as np
import os

# Generate data
seed = 42
X, y = make_classification(n_samples=1000, random_state=seed)

# Make a train/test split
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=seed)

# Save it
if not os.path.isdir("data"):
    os.mkdir("data")

np.savetxt("data/train_features.csv", X_train)
np.savetxt("data/test_features.csv", X_test)
np.savetxt("data/train_labels.csv", y_train)
np.savetxt("data/test_labels.csv", y_test)