How do I calculate the MD5 checksum of a file in Python? [duplicate]

In regards to your error and what's missing in your code. m is a name which is not defined for getmd5() function.

No offence, I know you are a beginner, but your code is all over the place. Let's look at your issues one by one :)

First, you are not using hashlib.md5.hexdigest() method correctly. Please refer explanation on hashlib functions in Python Doc Library. The correct way to return MD5 for provided string is to do something like this:

>>> import hashlib>>> hashlib.md5("filename.exe").hexdigest()'2a53375ff139d9837e93a38a279d63e5'

However, you have a bigger problem here. You are calculating MD5 on a file name string, where in reality MD5 is calculated based on file contents. You will need to basically read file contents and pipe it though MD5. My next example is not very efficient, but something like this:

>>> import hashlib>>> hashlib.md5(open('filename.exe','rb').read()).hexdigest()'d41d8cd98f00b204e9800998ecf8427e'

As you can clearly see second MD5 hash is totally different from the first one. The reason for that is that we are pushing contents of the file through, not just file name.

A simple solution could be something like that:

# Import hashlib library (md5 method is part of it)import hashlib# File to checkfile_name = 'filename.exe'# Correct original md5 goes hereoriginal_md5 = '5d41402abc4b2a76b9719d911017c592'  # Open,close, read file and calculate MD5 on its contents with open(file_name) as file_to_check:    # read contents of the file    data = file_to_check.read()        # pipe contents of the file through    md5_returned = hashlib.md5(data).hexdigest()# Finally compare original MD5 with freshly calculatedif original_md5 == md5_returned:    print "MD5 verified."else:    print "MD5 verification failed!."

Please look at the post Python: Generating a MD5 checksum of a file. It explains in detail a couple of ways how it can be achieved efficiently.

Best of luck.

In Python 3.8+ you can do

import hashlibwith open("your_filename.png", "rb") as f:    file_hash = hashlib.md5()    while chunk := f.read(8192):        file_hash.update(chunk)print(file_hash.digest())print(file_hash.hexdigest())  # to get a printable str instead of bytes

On Python 3.7 and below:

with open("your_filename.png", "rb") as f:    file_hash = hashlib.md5()    chunk = f.read(8192)    while chunk:        file_hash.update(chunk)        chunk = f.read(8192)print(file_hash.hexdigest())

This reads the file 8192 (or 2¹³) bytes at a time instead of all at once with f.read() to use less memory.

Consider using hashlib.blake2b instead of md5 (just replace md5 with blake2b in the above snippets). It's cryptographically secure and faster than MD5.

hashlib methods also support mmap module, so I often use

from hashlib import md5from mmap import mmap, ACCESS_READpath = ...with open(path) as file, mmap(file.fileno(), 0, access=ACCESS_READ) as file:    print(md5(file).hexdigest())

where path is the path to your file.

Ref: https://docs.python.org/library/mmap.html#mmap.mmap

Edit: Comparison with the plain-read method.

Plot of time and memory usage

(Seems I don't have enough reputation to show the image)

from hashlib import md5from mmap import ACCESS_READ, mmapfrom matplotlib.pyplot import grid, legend, plot, show, tight_layout, xlabel, ylabelfrom memory_profiler import memory_usagefrom numpy import arangedef MemoryMap():    with open(path) as file, mmap(file.fileno(), 0, access=ACCESS_READ) as file:        print(md5(file).hexdigest())def PlainRead():    with open(path, 'rb') as file:        print(md5(file.read()).hexdigest())if __name__ == '__main__':    path = ...    y = memory_usage(MemoryMap, interval=0.01)    plot(arange(len(y)) / 100, y, label='mmap')    y = memory_usage(PlainRead, interval=0.01)    plot(arange(len(y)) / 100, y, label='read')    ylabel('Memory Usage (MiB)')    xlabel('Time (s)')    legend()    grid()    tight_layout()    show()

path is the path to a 3.77GiB csv file.