Datasets:
Download scripts/checksum.py from imageomics/Heliconius-Collection_Cambridge-Butterfly: direct link, hf CLI and curl.
- Browser
- Download file 1.3 kB
-
https://huggingface.co/datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly/resolve/refs%2Fpr%2F2/scripts/checksum.py
- Command line
-
hf download hf://datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly@refs/pr/2/scripts/checksum.py
-
curl -L -o checksum.py https://huggingface.co/datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly/resolve/refs%2Fpr%2F2/scripts/checksum.py
1.3 kB
| import argparse | |
| import os | |
| import hashlib | |
| import csv | |
| from tqdm import tqdm | |
| def md5_checksum(file_path): | |
| hash_md5 = hashlib.md5() | |
| with open(file_path, "rb") as f: | |
| for chunk in iter(lambda: f.read(4096), b""): | |
| hash_md5.update(chunk) | |
| return hash_md5.hexdigest() | |
| def get_checksums(input_directory, output_filepath): | |
| with open(output_filepath, 'w', newline='') as csvfile: | |
| writer = csv.writer(csvfile) | |
| writer.writerow(["filepath", "filename", "md5"]) | |
| for root, dirs, files in os.walk(input_directory): | |
| n_files = len(files) | |
| for name in tqdm(files, total=n_files, desc="MD5ing"): | |
| file_path = os.path.join(root, name) | |
| checksum = md5_checksum(file_path) | |
| writer.writerow([file_path, name, checksum]) | |
| print(f"Checksums written to {output_filepath}") | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser(description="Generate MD5 checksums for files in a directory") | |
| parser.add_argument("--input-directory", required=True, help="Directory to traverse for files") | |
| parser.add_argument("--output-filepath", required=True, help="Filepath for the output CSV file") | |
| args = parser.parse_args() | |
| get_checksums(args.input_directory, args.output_filepath) | |