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File & Image Profiling

Single file:

from filoma import probe_file
info = probe_file('README.md')
print(info.size, info.modified)

Image:

from filoma import probe_image
img = probe_image('docs/assets/images/logo.png')
print(img.file_type, getattr(img, 'shape', None))

Numpy array:

import numpy as np
from filoma import probe_image
arr = np.zeros((64,64), dtype=np.uint8)
rep = probe_image(arr)
print(rep.mean, rep.max)

Disable hash for speed:

probe_file('big.bin', compute_hash=False)

Batch profile selected files via DataFrame:

from filoma import probe_to_df
dfw = probe_to_df('.')  # returns filoma.DataFrame wrapper
wrapper = dfw.filter_by_extension('.py').add_file_stats_cols()

What you get (file dataclass key fields):

  • path, size, owner, group, mode_str, created, modified, is_file, is_dir, sha256 (optional), inode

ImageReport common fields:

  • path, file_type, shape, dtype, min, max, mean, nans, infs