Please give me all the feedback you can think of.

better_genetics.py

from time import time
# Averages around 0.9 seconds.
# Updated program where I tried to use the tips reddit gave me.

def count_overlap(path1: str, path2: str) -> int:
    """
    Takes the input of 2 files which contain a number of DNA strings.
    Each DNA string is guaranteed to be unique, meaning no two same DNA
    strings will exist in the same file.
    If they both contain the same string, count +1.
    Returns the final amount of same strings.
    """
    content1: list[str] = read(path1)
    content2: list[str] = read(path2)
    content1_set: set[str] = list_to_set(content1)
    content2_set: set[str] = list_to_set(content2)
    return len(content1_set & content2_set)


def read(path: str) -> list[str]:
    with open(path, "r", encoding="utf-8") as reader:
        content: list[str] = reader.readlines()
    return content


def list_to_set(lst: list[str]) -> set[str]:
    ret_set: set[str] = set()
    for content in lst:
        ret_set.add(content)
    return ret_set


def main():
    start = time()
    test_count_overlap_sample()
    end = time()
    print(end-start) # Averages around 0.9 seconds.


def test_count_overlap_sample():
    print('Tests count_overlap... ', end='')
    assert 2 == count_overlap('sample1.txt', 'sample2.txt')
    # Tests efficiency (the test will take a long time with the wrong solution):
    assert 100001 == count_overlap('id1.txt', 'id2.txt')
    print('OK')


if __name__ == "__main__":
    main()

genetics.py

from time import time
# Averages around 1.2 seconds.

def count_overlap(path1: str, path2: str) -> int:
    """
    Takes the input of 2 files which contain a number of DNA strings.
    Each DNA string is guaranteed to be unique, meaning no two same DNA strings will exist in the same file.
    If they both contain the same string, count +1.
    Returns the final amount of same strings.
    """
    dna_count: int = 0
    content1: list[str] = read(path1)
    content1_map: dict[str, int] = list_to_dict(content1)
    content2: list[str] = read(path2)
    for line in content2:
        if line in content1_map:
            dna_count += 1
    return dna_count


def read(path: str) -> list[str]:
    with open(path, "r", encoding="utf-8") as reader:
        content: list[str] = reader.readlines()
    return content


def list_to_dict(lst: list[str]) -> dict[str, int]:
    ret_dict: dict[str, int] = {}
    for i,v in enumerate(lst):
        ret_dict.update({v: i})
    return ret_dict


def main():
    start = time()
    test_count_overlap_sample()
    end = time()
    print(end-start) # Averages around 1.2 seconds.


def test_count_overlap_sample():
    print('Tests count_overlap... ', end='')
    assert 2 == count_overlap('sample1.txt', 'sample2.txt')

    # Tests efficiency (the test will take a long time with the wrong solution):
    assert 100001 == count_overlap('id1.txt', 'id2.txt')
    print('OK')


if __name__ == "__main__":
    main()

genetics2.py

from time import time
# Averages around 1.75 seconds.

def count_overlap(path1: str, path2: str) -> int:
    """
    Takes the input of 2 files which contain a number of DNA strings.
    Each DNA string is guaranteed to be unique, meaning no two same DNA strings will exist in the same file.
    If they both contain the same string, count +1.
    Returns the final amount of same strings as an int.
    """
    content1: dict[str, int] = read(path1)
    content2: dict[str, int] = read(path2)
    total_len: int = len(content1) + len(content2)
    content1.update(content2)
    dna_count = total_len - len(content1)
    return dna_count


def read(path: str) -> dict[str, int]:
    """
    Reads a file of strings and turns it into a map.
    """
    with open(path, "r", encoding="utf-8") as reader:
        content: list[str] = reader.readlines()
    return list_to_dict(content)


def list_to_dict(lst: list[str]) -> dict[str, int]:
    ret_dict: dict[str, int] = {}
    for i,v in enumerate(lst):
        ret_dict.update({v.strip(): i})
    return ret_dict


def main():
    start = time()
    test_count_overlap_sample()
    end = time()
    print(end-start) # Averages around 1.75 seconds.


def test_count_overlap_sample():
    print('Tests count_overlap... ', end='')
    assert 2 == count_overlap('sample1.txt', 'sample2.txt')

    # Tests efficiency (the test will take a long time with the wrong solution):
    assert 100001 == count_overlap('id1.txt', 'id2.txt')
    print('OK')


if __name__ == "__main__":
    main()

sample1.txt

TATT
GAGA
GAGG

sample2.txt

AGGA
CATT
GAGA
TATT

These are my 2 solutions to the same problem.
Please give me all the feedback you can think of, like:

• Bad naming
• Bad functions
• Hard to understand
• Missing important coding philosophies and priciples

I don't mind harsh feedback! I want to learn, and to learn you must humble and able to listen to people better than you. Thank you so much if you decide to help! <3

If you guys want to run the scripts for yourself, you will need the id1.txt and id2.txt files. They are kind of big, so I didn't want to attach them here.
They can be found here in my repo if interested!
https://github.com/JAS-Norway/reddit-feeback-genetics.py-