title: High performance fuzzy string comparison in Python, use Levenshtein or difflib
body: <p>I am doing clinical message normalization (spell check) in which I check each  given word against 900,000 word medical dictionary. I am more concern about the time complexity/performance.</p>
  
  <p>I want to do fuzzy string comparison, but I'm not sure which library to use.</p>
  
  <p>Option 1:</p>
  
  <pre><code>import Levenshtein
  Levenshtein.ratio('hello world', 'hello')
  
  Result: 0.625
  </code></pre>
  
  <p>Option 2:</p>
  
  <pre><code>import difflib
  difflib.SequenceMatcher(None, 'hello world', 'hello').ratio()
  
  Result: 0.625
  </code></pre>
  
  <p>In this example both give the same answer. Do you think both perform alike in this case?</p>