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Python Java - A Side-by-Side Comparison .doc
Python Java - A Side-by-Side Comparison
About this Page
A programmer can be significantly more productive in Python than in Java. How much more productive? The most widely accepted estimate is 5-10 times. On the basis of my own personal experience with the two languages, I agree with this estimate.
Managers who are considering adding Python to their organizations list of approved development tools, however, cannot afford to accept such reports uncritically. They need evidence, and some understanding of why programmers are making such claims. This page is for those managers.
On this page, I present a list of side-by-side comparisons of features of Java and Python. If you look at these comparisons, you can see why Python can be written much more quickly, and maintained much more easily, than Java. The list is not long — it is meant to be representative, not exhaustive.
This page looks only at programmer productivity, and does not attempt to compare Java and Python on any other basis. There is, however, one related topic that is virtually impossible to avoid. Python is a dynamically-typed language, and this feature is an important reason why programmers can be more productive with Python; they dont have to deal with the overhead of Javas static typing. So the debates about Java/Python productivity inevitably turn into debates about the comparative advantages and drawbacks of static typing versus dynamic typing — or strong typing versus weak typing — in programming languages. I will not discuss that issue here, other than to note that in the last five years a number of influential voices in the programming community have been expressing serious doubts about the supposed advantages of static typing. For those who wish to pursue the matter, Strong versus Weak Typing: A Conversation with Guido van Rossum, Part V is a good place to start. See also Bruce Eckels weblog discussion Strong Typing vs. Strong Testing and Robert C. Martins weblog discussion Are Dynamic
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