see if two files have the same content in python [duplicate]

Solution 1:

Yes, I think hashing the file would be the best way if you have to compare several files and store hashes for later comparison. As hash can clash, a byte-by-byte comparison may be done depending on the use case.

Generally byte-by-byte comparison would be sufficient and efficient, which filecmp module already does + other things too.

See http://docs.python.org/library/filecmp.html e.g.

>>> import filecmp
>>> filecmp.cmp('file1.txt', 'file1.txt')
True
>>> filecmp.cmp('file1.txt', 'file2.txt')
False

Speed consideration: Usually if only two files have to be compared, hashing them and comparing them would be slower instead of simple byte-by-byte comparison if done efficiently. e.g. code below tries to time hash vs byte-by-byte

Disclaimer: this is not the best way of timing or comparing two algo. and there is need for improvements but it does give rough idea. If you think it should be improved do tell me I will change it.

import random
import string
import hashlib
import time

def getRandText(N):
    return  "".join([random.choice(string.printable) for i in xrange(N)])

N=1000000
randText1 = getRandText(N)
randText2 = getRandText(N)

def cmpHash(text1, text2):
    hash1 = hashlib.md5()
    hash1.update(text1)
    hash1 = hash1.hexdigest()

    hash2 = hashlib.md5()
    hash2.update(text2)
    hash2 = hash2.hexdigest()

    return  hash1 == hash2

def cmpByteByByte(text1, text2):
    return text1 == text2

for cmpFunc in (cmpHash, cmpByteByByte):
    st = time.time()
    for i in range(10):
        cmpFunc(randText1, randText2)
    print cmpFunc.func_name,time.time()-st

and the output is

cmpHash 0.234999895096
cmpByteByByte 0.0

Solution 2:

I'm not sure if you want to find duplicate files or just compare two single files. If the latter, the above approach (filecmp) is better, if the former, the following approach is better.

There are lots of duplicate files detection questions here. Assuming they are not very small and that performance is important, you can

• Compare file sizes first, discarding all which doesn't match
• If file sizes match, compare using the biggest hash you can handle, hashing chunks of files to avoid reading the whole big file

Here's is an answer with Python implementations (I prefer the one by nosklo, BTW)