02 use named regex parameters

Some files store information about their content encoded directly in their names. For example, saved machine learning model weights might include the epoch number or the value of a tracked metric.

To extract these values from file paths, use regular exceptions. The most convenient way to do so is to use named regex placeholders, which allow you to extract a dictionary of values from a string, where the keys correspond to the matched parameters.

import ast
import re

def named_match(pattern, string):
    match = re.match(pattern, string)
    return {k: ast.literal_eval(v) for k, v in match.groupdict().items()}

filename = 'epoch=5_val_loss=0.23.ckpt'
regex = r'^epoch=(?P<epoch>d+)_val_loss=(?P<val_loss>d+.d+).ckpt$'
result = named_match(regex, filename)
assert result == {'epoch': 5, 'val_loss': 0.23}

import ast
import re

def named_match(pattern, string):
    match = re.match(pattern, string)
    return {k: ast.literal_eval(v) for k, v in match.groupdict().items()}

filename = 'epoch=5_val_loss=0.23.ckpt'
regex = r'^epoch=(?P<epoch>d+)_val_loss=(?P<val_loss>d+.d+).ckpt$'
result = named_match(regex, filename)
assert result == {'epoch': 5, 'val_loss': 0.23}

Sure, you could also use anonymous regex groups. But this approach is more fragile, because it depends on the parameters’ ordering.