Here is my experience using Python and Java for software development.
Overall, Python is best for small projects and rapid prototyping. Python has certain advantages with its dynamic nature, but as the code base grows these advantages become disadvantages. Java is best for larger projects and where performance is important. Python performance is poor: bytecode executes slow, and global interpreter lock prevents threads from completely utilizing multiple CPUs.
Python is pleasant to use with its expressive string operations, e.g. you can write 'a'*80 to make a string of 80 'a' characters. Using operators on collections in Python is so much more intuitive than using Java's method-based operations. It's nice to not have to compile files.
However, in Python you can make a typo, and it can be frustrating to catch those. Something that background compilation would catch right away in a Java IDE and highlight as syntax error in 1 second, takes writing unit-tests, getting back to the code you've written not at this minute, and fixing it. Because Python is so permissive you can easily do this:
var = method
for i in var:
do something else
Note that you intended to write:
var = method()
You omitted the braces. Nothing flagged this as a possible error. During execution, the error isn't manifested on the same line, but instead a couple lines after that when we are trying to do
something with a method instead of an object.
Overall it seems that dynamic languages have inherent limitations that limit code discovery. From a practical point of view, modern languages now have huge libraries, and it's impossible for a human to remember even a fraction of library routine names and parameters. So here is where "suggest" or autocomplete functionality comes in nicely. However it's hard to implement in a dynamic language for the simple reason, that you don't know what types objects are. This impacts your productivity severely, as you have to go and check man pages over and over as opposed to having method names pop up as you write code.
In Python writing performant code is hard. Organizing your code into methods has significant performance penalty if these methods are frequently invoked. Python VM doesn't inline. Essentially Python performance trick is making sure you delegate to the C code. Doing work by executing Python code makes things slow. Because of GIL, Python threads don't truly run simultaneously. Instead it is simulated that they run simultaneously. So if you have multiple CPUs and multiple threads you won't utilize all your CPUs.
Click here for the table summarizing Python and Java.
For some reason Blogger puts a large space between the text and the table.
