pythonizer

Python is an elegant, general-purpose, object-oriented, easy to learn programming language. It is optimized for quality , productivity, portability and integration. More than half a million developers around the world use it for day-to-day development tasks.

Python is platform independent, it runs under many environments including most flavors of Unix, Windows and other operating systems.

Writing modules in either Python itself, or compiled languages can extend the language easily. This allows Python to act as glue between highly diverse small or large software components spanning multiple platforms, middleware products, and application domains. It can play an important integration role in large projects. It works well with existing technologies and can be used both to wrap legacy systems or to enhance them as a powerful extension language. Many preprogrammed high-quality modules are available for Python: easy-to-use internet protocol implementations, math libraries, networking, system calls, cryptography tools, interfaces to most databases, CORBA and COM support, and APIs for common windowing and GUI development frameworks such as MFC, X11, Motif, Tk, Gtk and Qt.

Applications written in Python are easily customizable.

The most attractive feature of the language is that it makes the programmer much more efficient. We could see dramatic improvement in the speed of the hardware over the past 2 or 3 decades. The speed of the computers increased by magnitudes but the speed of the software development did not change very much. Using Python software development is 3-5 times faster than using Java or C/C++. Also, Python programs are a couple of times shorter than their Java or C/C++ equivalents. This is due to the exceptionally good design and the virtually zero compile time.

Working with Python and Pythonizer is probably the best approach to start the implementation of your project in Python. You can use thousands of the objects that come with Pythonizer or you can use the huge amount of existing modules that are already available on the market, most of them as open source. This part of the code runs in native mode. If you experience performance problems with your Python code, you can develop these sections in C/C++ and convert them to Python using Pythonizer.