Python: normalizing a text file

I have a text file which contains several spelling variants of many words:

For e.g.

identification ... ID .. identity...contract.... contr.... contractor...medicine...pills..tables

So I want to have a synonym text file which contains the words synonyms and would like to replace all the variants with the primary word. Essentially I want the normalize the input file.

F开发者_运维知识库or e.g my synonym list file would look like

identification = ID identify
contracting = contract contractor contractors contra...... 
word3 = word3_1 word3_2 word3_3 ..... word3_n
.
.
.
.
medicine = pills tables drugs...

I want the end output file to look like

identification ... identification .. identification...contractor.... contractor.... contractor...medicine...medicine..medicine

How do I got about programming in python?

Thanks a lot for your help!!!

You could read the synonym file and convert it into a dictionary, table:

import re

table={}
with open('synonyms','r') as syn:
    for line in syn:
        match=re.match(r'(\w+)\s+=\s+(.+)',line)
        if match:
            primary,synonyms=match.groups()
            synonyms=[synonym.lower() for synonym in synonyms.split()]
            for synonym in synonyms:
                table[synonym]=primary.lower()

print(table)

yields

{'word3_1': 'word3', 'word3_3': 'word3', 'word3_2': 'word3', 'contr': 'contracting', 'contract': 'contracting', 'contractor': 'contracting', 'contra': 'contracting', 'identify': 'identification', 'contractors': 'contracting', 'word3_n': 'word3', 'ID': 'identification'}

Next, you could read in the text file, and replace each word with its primary synonym from table:

with open('textfile','r') as f:
    for line in f:
        print(''.join(table.get(word.lower(),word) 
                      for word in re.findall(r'(\W+|\w+)',line)))

yields

identification     identification    identity   contracting     contracting     contracting   medicine   medicine  medicine

1. re.findall(r'(\w+|\W+)',line) was used split each line while preserving whitespace. If whitespace is not of interest, you could also use the easier line.split().
2. table.get(word,word) returns table[word] if word is in table, and simply returns word if word is not in the synonym table.

Just a thought: Instead of having a list of all variation of a word, have a look at difflib

>>> get_close_matches('appel', ['ape', 'apple', 'peach', 'puppy'])
['apple', 'ape']
>>> import keyword
>>> get_close_matches('wheel', keyword.kwlist)
['while']
>>> get_close_matches('apple', keyword.kwlist)
[]
>>> get_close_matches('accept', keyword.kwlist)
['except']