Python 101

Python and Perl

If Perl is the first post-modern programming language as Larry Wall (Perl's creator) describes it, then Python can be called the first neo-classical programming language.

Both Python and Perl build on a strong understanding of the available tools for problem solving. Larry Wall used awk, sed, and shell scripting as the primary design inspirations when he started writing Perl because he was writing a language to make system administration tasks easier. Python was inspired more by object-oriented design and object-oriented tools.

Rather than striving for a maximally expressive language as Larry Wall did, Guido van Rossum (the designer of Python) chose to create a simple, powerful, elegant base for creating systems out of components. The expressive power is still there in Python, but it tends to be compartmentalized, which makes reading Python code much easier. When you need more detail on how a certain line of code works, you look at the modules and functions it is using, rather than see the full complexity on the surface.  

Python and Tcl

Tcl on the surface looks a lot like Python. Both languages can be used to write elegant, simple code. Tcl is primarily a string processing language. The only datatypes in Tcl are strings and one-dimensional arrays of strings.

Python, in contrast, comes with a full range of data types including numbers (integers, long integers, floating point, octal, hex, and complex numbers), strings, lists, dictionaries (arrays indexed by keys, like hashes in Perl), and tuples (simple lists that can't be changed in place).

Tcl and Python share the same GUI toolkit, Tk. Python's interface to Tk is called Tkinter, and it is included with all recent versions of Python. You are not limited to using just Tk to build GUIs in Python, however. You can also use the Gimp Tool Kit (GTK) and Gnome extensions to GTK+.

Python and Java

Java is a full-featured programming language with a complete range of types, thread support, strong typing, and all of the other features you expect.

Python is a scripting language. It doesn't use or offer strong typing, which is nice for prototyping but can cause problems in more complex implementations. It does offer thread support, but it isn't as rugged as Java's thread support.

Installing Python on Linux

If you are running a Red Hat Linux system that uses RPM, installing Python is as simple as downloading the RPM from the Python.org Web site (see Resources) and typing:

Red Hat 6.0 shipped with Python 1.5.1, so you will need to update it if you have it already installed:

If you are running Debian Linux, you can download Python and some additional modules from the standard Debian distribution using apt/dselect.

Other Linux platforms will need to compile Python from source. To do this follow the instructions in the README file in the distribution, or consult your local expert.

But you don't need to choose between Java and Python. Using JPython (see Resources), you can write Python code that is evaluated within a Java Virtual Machine. You don't even have to take a performance penalty. In fact, there have been several reports of a marked speed increase between regular C Python and JPython because of some optimizations in the implementation of dynamic datatypes in the JPython port of Python.

Why is Python popular with Linux users?

There are several reasons why Python is gaining in popularity with Linux users. Python users don't match the sheer numbers of Perl users, but users who have tried Python tend to continue using it for these simple reasons:

• Readability. Python makes it almost impossible to write obfuscated code. White space is used to delimit blocks, ensuring obvious block structure. The syntax is clean, with a consistent calling structure for modules and functions.
• Taste. Linux has yet to break through to on-every-desktop popularity. Those who are using it now tend to be the more sophisticated and discerning computer users. For some of them, like Eric Raymond, Python is their preferred language because it is an elegant, clean programming language. Others, like Mark Lutz, the author of Programming Python (see Resources), prefer it because "Python looks designed, not accumulated".
• Object support. Python enables you to be an object-oriented developer without paying for a heavy, system programming-level syntax like you have to pay for in a language like Java or C++.
• Development speed. As a rapid prototyping language, with strong support for GUI toolkits like Tk and GTK, Python lets you create full-featured solutions very quickly. If those solutions suffer from performance problems, it is very easy to plug in C replacements for the performance-critical components on a piece-by-piece basis.
• Interoperability. Linux is a great glue operating system. It is used most often in situations where you would find at least one other type of operating system, usually Windows. Python is very portable code, with interpreters available for all common, and many uncommon, operating systems. So you can develop code on Linux and deploy the same code throughout your system. You can even use it in embedded systems that support a Java Virtual Machine (JVM) by using JPython.
• Reusability. Linux is known for its modular design at the kernel level, just as Unix is known for its many small tools. Python also uses small, well crafted components, called modules. Modules are very easy to design and use, which encourages formal and informal code libraries. Perl has the advantage in formal public code repositories, though, as there is yet no equivalent to the Comprehensive Perl Archive Network (CPAN) for Python.
• Reliability. The Python community encourages high-quality coding standards. An example is the common practice of writing modules that contain their own test routines. These routines, which start with.
  
  
  if __name__ == '__main__':
  
  
  are executed only if the module is run as a stand-alone program. If the module is called from another program, as is usually the case, this test routine is skipped. 
• No compile/link step. Python is a byte-compiled language as well as an interpreted language. This means that the first time the Python interpreter executes a program or a module, it is translated into byte code. This byte code is written to disk as .pyc. Then, when the program or module is executed again, the interpreter checks to see if there is a .pyc file with a more recent timestamp than the .py file. If one exists, it skips the byte-compilation step and reads the compiled file from disk. This can save a lot of execution time. 
• Rich class libraries. Library modules are available for most common programming tasks, including full POSIX-compliant routines, several different math libraries, support for several different GUI toolkits, support for CGI programming and HTML and XML generation and parsing, just to name a few. The standard list of modules is available at Python.org (see Resources) as a small part of the excellent documentation available there.