Store smallest number from a list based on criteria

Your best bet is probably to use the pandas library, it is very good at dealing with tabular data.

import pandas as pd

file_name_list = []  # Fill in here
file_name_list = [file_name[:-4] for file_name in file_name_list] # Get rid of .jpg
file_name_series = pd.Series(file_name_list) # Put the data in pandas
file_name_table = file_name_series.str.split("_", expand=True) # Split the strings
file_name_table.columns = ['date', 'prefix', 'number'] # Renaming for readability
file_name_table['number'] = file_name_table['number'].astype(int)
smallest_file_names = file_name_table.groupby(by=['date', 'prefix'])['number'].min()
smallest_file_names_list = smallest_file_names.to_list()
smallest_file_names_list = [file_name+'.jpg' for file_name in smallest_file_names_list] # Putting the .jpg back

If the same pattern is being followed, you can try to split each name by a separator (In your example ‘.’ and ‘_’. Documentation on how split works here), and then sort that list by sorting a list of lists, as explained here. This will need to be done per each "ID", as I will call each group identifier’s, so we’ll first need to get the unique IDs, and then iterate them. After that, we can proceed with the splitting. By doing this, you’ll get a list of lists with the complete file name in position 0, and the number from the suffix in position 1

prefix = list(set([pre.split('_')[1] for pre in names]))

names_split = []

for pre in prefix:
    names_split.append([pre,[[name, name.split('.')[0].split('_')[2]] for name in names if name.split('_')[1] == pre]])

for i in range(len(prefix)):
    names_split[i][1] =sorted(names_split[i][1], key=lambda x: int(x[1]))

print(names_split)

The file you need should be names_split[x][0][0] where x identifies each ID.

PS: If you need to find a particular ID, you can use

searched_index = [value[0] for value in names_split].index(ID)

and then names_split[searched_index][0][0]]

Edit: Changed the splitted characters order and added docs on split method

Edit 2: Added prefix grouping

It seems that the list of files you have is already sorted according to groups of prefixes, and then according to the numbers. If that’s indeed the case, you just need to take the first path of each prefix group. This can be done easily with itertools.groupby:

for key, group in groupby(files, lambda file: file.rsplit('_', 1)[0]):
    print(key, "min:", next(group))

If you can’t rely that they are internally ordered, find the minimum of each group according to the number:

for key, group in groupby(files, lambda file: file.rsplit('_', 1)[0]):
    print(key, "min:", min(group, key=lambda file: int(file.rsplit('_', 1)[1].removesuffix(".jpg"))))

And if you can’t even rely that it’s ordered by groups, just sort the list beforehand:

files.sort(key=lambda file: file.rsplit('_', 1)[0])
for key, group in groupby(files, lambda file: file.rsplit('_', 1)[0]):
    print(key, "min:", min(group, key=lambda file: int(file.rsplit('_', 1)[1].removesuffix(".jpg"))))