Loading large file (25k entries) into dict is slow in Python?

Question

I have a file which has about 25000 lines, and it's a s19 format file.

each line is like: S214 780010 00802000000010000000000A508CC78C 7A

There are no spaces in the actual file, the first part 780010 is the address of this line, and I want it to be a dict's key value, and I want the data part 00802000000010000000000A508CC78C be the value of this key. I wrote my code like this:

def __init__(self,filename):
    infile = file(filename,'r')
    self.all_lines = infile.readlines()
    self.dict_by_address = {}

    for i in range(0, self.get_line_number()):
        self.dict_by_address[self.get_address_of_line(i)] = self.get_data_of_line(i)

    infile.close()

get_address_of_line() and get_data_of_line() are all simply string slicing functions. get_line_number() iterates over self.all_lines and returns an int

problem is, the init process takes me over 1 min, is the way I construct the dict wrong or python just need so long to do this?

And by the way, I'm new to python:) maybe the code looks more C/C++ like, any advice of how to program like python is appreciated:)

Answer 1

How about something like this? (I made a test file with just a line S21478001000802000000010000000000A508CC78C7A so you might have to adjust the slicing.)

>>> with open('test.test') as f:
...     dict_by_address = {line[4:10]:line[10:-3] for line in f}
... 
>>> dict_by_address
{'780010': '00802000000010000000000A508CC78C'}