cjm-kaggle-utils

Install

pip install cjm_kaggle_utils

How to use

save_kaggle_creds

from cjm_kaggle_utils.core import save_kaggle_creds

username = "name"
key = "12345"
save_kaggle_creds(username, key, overwrite=False)

Credentials already present. Set `overwrite=True` to replace them.

dl_kaggle

from cjm_kaggle_utils.core import dl_kaggle
from pathlib import Path

# Get the path to the directory where datasets are stored
dataset_dir = Path("./Datasets/")
dataset_dir.mkdir(parents=True, exist_ok=True)
print(f"Dataset Directory: {dataset_dir}")

# Create the path to the data directory
archive_dir = dataset_dir/'../Archive'
archive_dir.mkdir(parents=True, exist_ok=True)
print(f"Archive Directory: {archive_dir}")

Dataset Directory: Datasets
Archive Directory: Datasets/../Archive

# Set the name of the dataset
dataset_name = 'style-image-samples'

# Construct the Kaggle dataset name by combining the username and dataset name
kaggle_dataset = f'innominate817/{dataset_name}'

# Create the path to the zip file that contains the dataset
archive_path = Path(f'{archive_dir}/{dataset_name}.zip')
print(f"Archive Path: {archive_path}")

# Create the path to the directory where the dataset will be extracted
dataset_path = Path(f'{dataset_dir}/{dataset_name}')
print(f"Dataset Path: {dataset_path}")

Archive Path: Datasets/../Archive/style-image-samples.zip
Dataset Path: Datasets/style-image-samples

dl_kaggle(kaggle_dataset, archive_path, dataset_path)

Downloading style-image-samples.zip to Datasets/../Archive

100%|██████████████████████████████████████████████████████████████████████████████████████████████| 16.2M/16.2M [00:00<00:00, 44.0MB/s]

!ls {dataset_path}

images