Is Python slower than Java/C#? [closed]

Question

Is Python slower than Java/C#?

performance-comparison-c-java-python-ruby-jython-jruby-groovy

Here is a project that optimizes CPython: unladen-swallow

Answer 1

Don't conflate Language and Run-Time.

Python (the language) has many run-time implementations.

• CPython is usually interpreted, and will be slower than native-code C#. It might be slower than Java, depending on the Java JIT compiler.

• JYthon is interpreted in the JVM and has the same performance profile as Java.

• IronPython relies on the same .NET libraries and IL as C#, so the performance difference will be relatively small.

• Python can be translated to native code via PyREX, PyToC, and others. In this case, it will generally perform as well as C++. You can -- to an extent -- further optimize C++ and perhaps squeeze out a little bit better performance than unoptimized output from PyREX.

  For more information, see http://arcriley.blogspot.com/2009/03/so-long-pyrex.html

Note that Python (the language) is not slow. Some Python run-times (CPython, for example) will be slower than native-code C++.

Answer 2

It is not really correct to ask why Python is slower than Java/C#. How fast is Java? Well, naive interpreters are around ten times slower than optimised compilers. I believe there is a Java bytcode interpreter written in JavaScript - that probably isn't very fast. So, the intended question appears to be "Why is the CPython language system slower than the equivalent Sun, IBM and Oracle JRE and Microsoft .NET runtime?"

I believe the correct answer is non-technical. The fastest Java and .NET runtime are faster because they have large full time technical teams developing them in performance-competitive environment.

Dynamic language systems are easy to implement. Any idiot can do it. I have. Static language systems are more complex to design and implement. A simple static system will tend to run much faster than the equivalent just-working dynamic equivalent. However, it is possible for highly optimised dynamic systems to run almost as fast. I understand some Smalltalk implementation were quite good. An often quoted example of a developed dynamic system is the MIT Lisp Machine.

In addition if the real grunt is being done by library code, then the language system may not matter. Alternatively, the language may encourage (or give time(!)) to develop more efficient algorithms which can easily wipe out constant factor performance differences.

Answer 3

As mentioned in the other answers this depends on the run-time system as well as the task at hand. So the standard (C)Python is not necessarily slower than Java or C#. Some of its modules are implemented in C. Thus combining speed of a native implementation with Python's language.

We did a small experiment: We compared the execution time of a Factorial computation in different languages. The test was actually intended to evaluate the performance of arbitrary-precision integers implementations.

testee. language arbitrary-precision integers run-time

     1. Java     java.math.BigInteger         JRE 6.13
     2. .NET     System.Numerics.BigInteger   MS CLR 4.0
     3. Python   long                         Active Python 2.6.2.2
     4. Squeak   BigInt                       Squeak 3.10.2
     5. .NET     Mono.Math.BigInteger         MS CLR 4.0

results:

                 1)         2)       3)       4)        5)
   10.000!      343 ms    137 ms    91 ms  1.200 ms    169 ms
   20.000!    1.480 ms    569 ms   372 ms  1.457 ms    701 ms
   30.000!    3.424 ms  1.243 ms   836 ms  3.360 ms  1.675 ms
   40.000!    6.340 ms  2.101 ms 1.975 ms  6.738 ms  3.042 ms
   50.000!   10.493 ms  3.763 ms 3.658 ms 10.019 ms  5.242 ms
   60.000!   15.586 ms  7.683 ms 5.788 ms 14.241 ms 10.000 ms

alt text http://www.mycsharp.de/wbb2/attachment.php?attachmentid=6909&sid=0d5aa62b522d005d9e7089785b5d19f1

The bar chart shows the results. Python is the clear winner. As far as I know Python uses the Karatsuba-algorithm to multiply large integers, which explains the speed.

Besides, Python's "arbitrary-precision integers"-type is the built-in long. Hence you don't even need special type handling which is required for Java's BigInteger-class.

Answer 4

Simply - Python is slow.

No matter what interpreter (currently available) you use, it is slower than Java and C. In various benchmarks, its slower than Ruby and PHP. Do not depend on other's answers, check and verify yourself.

http://benchmarksgame.alioth.debian.org/u64q/benchmark.php?test=all&lang=python3&lang2=java&data=u64q

Personally I do not think, there is much serious contribution and development done on getting python faster. Since the productivity is good in python and it solves some of problem straight forward, speed/performance is not taken seriously. There are some architecture issues too preventing Python getting performance tweaks.

Disclaimer - This answer probably will hurt Python lovers. I too am Python developer, loves developing webapps in Django/Flask/Pyramid rather than Spring (Java). But I see practically in my work and experience, how Python is slower. The speed is not always my priority. But I do stand with them, who says Python Interpreter should get oiling and greasing or total engine change to at least stand in marathon. It's a mainstream programming language.