import polaris as po

# Load the dataset from the Hub
dataset = po.load_dataset("polaris/my-first-dataset")

# Get information on the dataset size
dataset.size()

# Load a datapoint in memory
dataset.get_data(
    row=dataset.rows[0],
    col=dataset.columns[0],
)

# Or, similarly:
dataset[dataset.rows[0], dataset.columns[0]]

# Get an entire data point
dataset[0]

import polaris as po
import numpy as np

# Load the benchmark from the Hub
benchmark = po.load_benchmark("polaris/my-first-benchmark")

# Get the train and test data-loaders
train, test = benchmark.get_train_test_split()

# Use the training data to train your model
# Get the input as an array with 'train.inputs' and 'train.targets'  
# Or simply iterate over the train object.
for x, y in train:
    ...

# Work your magic to accurately predict the test set
predictions = [0.0 for x in test]

# Evaluate your predictions
results = benchmark.evaluate(predictions)

# Submit your results
results.upload_to_hub(owner="dummy-user")