Generating an MD5 checksum of a file

Is there any simple way of generating (and checking) MD5 checksums of a list of files in Python? (I have a small program I'm working on, and I'd like to confirm the checksums of the files).

quantumSoup

You can use hashlib.md5()

Note that sometimes you won't be able to fit the whole file in memory. In that case, you'll have to read chunks of 4096 bytes sequentially and feed them to the Md5 function:

def md5(fname):
    hash_md5 = hashlib.md5()
    with open(fname, "rb") as f:
        for chunk in iter(lambda: f.read(4096), b""):
            hash_md5.update(chunk)
    return hash_md5.hexdigest()

Note: hash_md5.hexdigest() will return the hex string representation for the digest, if you just need the packed bytes use return hash_md5.digest(), so you don't have to convert back.

There is a way that's pretty memory inefficient.

single file:

import hashlib
def file_as_bytes(file):
    with file:
        return file.read()

print hashlib.md5(file_as_bytes(open(full_path, 'rb'))).hexdigest()

list of files:

[(fname, hashlib.md5(file_as_bytes(open(fname, 'rb'))).digest()) for fname in fnamelst]

Recall though, that MD5 is known broken and should not be used for any purpose since vulnerability analysis can be really tricky, and analyzing any possible future use your code might be put to for security issues is impossible. IMHO, it should be flat out removed from the library so everybody who uses it is forced to update. So, here's what you should do instead:

[(fname, hashlib.sha256(file_as_bytes(open(fname, 'rb'))).digest()) for fname in fnamelst]

If you only want 128 bits worth of digest you can do .digest()[:16].

This will give you a list of tuples, each tuple containing the name of its file and its hash.

Again I strongly question your use of MD5. You should be at least using SHA1, and given recent flaws discovered in SHA1, probably not even that. Some people think that as long as you're not using MD5 for 'cryptographic' purposes, you're fine. But stuff has a tendency to end up being broader in scope than you initially expect, and your casual vulnerability analysis may prove completely flawed. It's best to just get in the habit of using the right algorithm out of the gate. It's just typing a different bunch of letters is all. It's not that hard.

Here is a way that is more complex, but memory efficient:

import hashlib

def hash_bytestr_iter(bytesiter, hasher, ashexstr=False):
    for block in bytesiter:
        hasher.update(block)
    return hasher.hexdigest() if ashexstr else hasher.digest()

def file_as_blockiter(afile, blocksize=65536):
    with afile:
        block = afile.read(blocksize)
        while len(block) > 0:
            yield block
            block = afile.read(blocksize)


[(fname, hash_bytestr_iter(file_as_blockiter(open(fname, 'rb')), hashlib.md5()))
    for fname in fnamelst]

And, again, since MD5 is broken and should not really ever be used anymore:

[(fname, hash_bytestr_iter(file_as_blockiter(open(fname, 'rb')), hashlib.sha256()))
    for fname in fnamelst]

Again, you can put [:16] after the call to hash_bytestr_iter(...) if you only want 128 bits worth of digest.

rsandwick3

I'm clearly not adding anything fundamentally new, but added this answer before I was up to commenting status, plus the code regions make things more clear -- anyway, specifically to answer @Nemo's question from Omnifarious's answer:

I happened to be thinking about checksums a bit (came here looking for suggestions on block sizes, specifically), and have found that this method may be faster than you'd expect. Taking the fastest (but pretty typical) timeit.timeit or /usr/bin/time result from each of several methods of checksumming a file of approx. 11MB:

$ ./sum_methods.py
crc32_mmap(filename) 0.0241742134094
crc32_read(filename) 0.0219960212708
subprocess.check_output(['cksum', filename]) 0.0553209781647
md5sum_mmap(filename) 0.0286180973053
md5sum_read(filename) 0.0311000347137
subprocess.check_output(['md5sum', filename]) 0.0332629680634
$ time md5sum /tmp/test.data.300k
d3fe3d5d4c2460b5daacc30c6efbc77f  /tmp/test.data.300k

real    0m0.043s
user    0m0.032s
sys     0m0.010s
$ stat -c '%s' /tmp/test.data.300k
11890400

So, looks like both Python and /usr/bin/md5sum take about 30ms for an 11MB file. The relevant md5sum function (md5sum_read in the above listing) is pretty similar to Omnifarious's:

import hashlib
def md5sum(filename, blocksize=65536):
    hash = hashlib.md5()
    with open(filename, "rb") as f:
        for block in iter(lambda: f.read(blocksize), b""):
            hash.update(block)
    return hash.hexdigest()

Granted, these are from single runs (the mmap ones are always a smidge faster when at least a few dozen runs are made), and mine's usually got an extra f.read(blocksize) after the buffer is exhausted, but it's reasonably repeatable and shows that md5sum on the command line is not necessarily faster than a Python implementation...

EDIT: Sorry for the long delay, haven't looked at this in some time, but to answer @EdRandall's question, I'll write down an Adler32 implementation. However, I haven't run the benchmarks for it. It's basically the same as the CRC32 would have been: instead of the init, update, and digest calls, everything is a zlib.adler32() call:

import zlib
def adler32sum(filename, blocksize=65536):
    checksum = zlib.adler32("")
    with open(filename, "rb") as f:
        for block in iter(lambda: f.read(blocksize), b""):
            checksum = zlib.adler32(block, checksum)
    return checksum & 0xffffffff

Note that this must start off with the empty string, as Adler sums do indeed differ when starting from zero versus their sum for "", which is 1 -- CRC can start with 0 instead. The AND-ing is needed to make it a 32-bit unsigned integer, which ensures it returns the same value across Python versions.

hashlib.md5(pathlib.Path('path/to/file').read_bytes()).hexdigest()

来源：https://stackoverflow.com/questions/3431825/generating-an-md5-checksum-of-a-file

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