The paper covers the history of python how it evolved to its current state. It describes the main design goals which made the authors develop such a language. Then the paper goes in detail about the language features and what it offers to the programmers. It also enumerates some of the disadvantages of the language.
Python was created in the early 1990s by Guido van Rossum at Stichting Mathematisch Centrum (CWI) in the Netherlands as a successor of a language called ABC. He decided to create a language that was generally extensible so Guido and his Python core development team moved to BeOpen.com to form the BeOpen PythonLabs team and later in 2001, the Python Software Foundation (PSF) was formed, a non-profit organization created specifically to own Python-related Intellectual Property.
Python design objective was to keep the syntax simple also enable it to be used as a scripting language. The language has grown immensely since its introduction. It was incorporated into JPython (a python version for Java), CPython (for C), for C#, and includes all powerful features of Perl, Tcl/Tk, Network programming, etc and is still growing.
2. MAIN DESIGN GOALS
1. A language that uses an elegant syntax for better readability
3. The language that is portable and works on different operating systems. This made python an interpretive language
4. Provides a glue between modules developed in several languages. This goal makes integrating modules from different languages easier
5. Provide dynamic-typing and implicit garbage collection for memory management
6. Provide dynamic name resolution, that means allowing method and variable names to be bound during program execution
Python is ideally suited for rapid prototyping of complex applications. Its various features from the different programming paradigms are now discussed.
3.1 Features of Object Oriented Programming
Python includes most of the features of the current OOP languages. It provides multiple-inheritance as in C++, user defined Abstract Data Types, Encapsulation and in Python “packages” are the way of structuring module’s namespace by using “dotted module names.”
Each package is stored a folder and the folder contains “__init__.py” to tell you that it is right package instead of some unknown folder in the path. The modules are like classes and each are accessed by “.” operator to qualify a module as in Java.
In Python every variable is an object unlike Java or C# where primitive types are allowed. For example:
A = 10
B = A
B = 5
In the above case both A and B points to the same object in the memory so any change in one value will change in the value of other. Methods are also objects in Python that means that one can pass methods as objects to some other methods and call them at later point in time. The following is an example of how a class is defined in Python:
def __init__(self): “”” constructor
self.data = 
def add(self, x):
def addtwice(self, x):
Python also provides exception handling and memory management similar to Java and C# thus the developer can create exceptions of their own kind or type. The construct looks like:
except (<exceptionType1>, <exceptionType1>,..):
Multiple exceptions can thus be handled at the same level unlike Java. It also supports a single except clause without specifying the type and it also supports “finally” clause like that of Java.
3.2 Features of a Scripting Language
Python is an interpreted language and provides all facilities as that of a scripting language. It also has features similar to Perl and shell scripts making it possible to run programs written in scripts as a batch files.
3.3 Features of Functional Languages
Functional language support is provided by the python though not as completely like LISP or Scheme. Its way of defining a function is similar to these languages. In Python language expressions return “anonymous” functions as results. This is needed wherever you cannot define a function and avoids lot of function declarations.
1) increment = lambda x: x + 1
2) lmap = ( lambda f, lst:
if lst == :
return [ f( lst ) ] + lmap( f lst[1:] ) )
3.4 Other Features
Python supports dynamic typing. This means there is no need for the variable to be declared in python. Wherever it is occurs for the first time the variable is declared at that point. The type is therefore defined at run time that means the type is defined based on the value it takes and can change over the period of execution.
Another important feature of the language is its readability. Python does not have any block structures. In-fact a block is determined by the indentation of the statement, so all statements which are part of the same block must be indented equally:
def f(a, b): a = b print a; Argument Passing Argument passing in Python is pass-by-value. But the value is the reference value not the copy of the object as in Java. This is obvious since there are no primitive types for the actual value to be passed. Also like C++ the functions in Python can be declared to take default arguments:
def ask_ok(prompt, retries=4, complaint='Yes or no, please!')
where formal parameters “retries” and “complaint” can take default values when one calls if no parameters are called onask_ok();Also the values are evaluated at the point of function definition in the defining scope and are evaluated only once. For example:
i = 5
i = 6
After the last statement it prints 5 rather than 6.
Python also supports both positional arguments and named arguments. For positional arguments the parameters should appear according to the position and for achieving the named parameter, Python uses something called “Keyword-Argument.”
def parrot(voltage, state='a stiff', action='voom')
parrot(1000) // positional parameter
parrot(action = 'VOOOOOM', voltage = 1000000) // named arguments
parrot('a thousand', state = 'pushing up the daisies') // positional and named argument where voltage= ‘a thousand’, state = 'pushing up the daisies' and action takes the default value
parrot('a million', 'bereft of life', 'jump') // here every parameter is a positional parameter.
Another feature is to specify a function that can be called with an arbitrary number of arguments. These arguments are wrapped up in a tuple. Before the variable number of arguments, zero or more normal arguments may occur.
def fprintf(file, format, *args):
file.write(format % args)
Conditional statements and Loops
Python both supports “if-else” and “if-elseif-else”, “for” loop and “while” loop constructs. Multiple selection can be achieved by if constructs.
if x < 0:
elif x == 0:
Python does not have “switch-case” construct as a separate multiple selection process. Also conditions can contain any operations not just comparisons. All comparison operators have the same precedence that is lower than that of all numerical operators. For example, a < b == c tests whether "a" is less than "b" and moreover "b" equals "c". Unlike C variant where it tests like (a < b) == c.
Python also provides facilities for introspection, so that a debugger or profiler (or other development tools) for Python programs can be written in Python itself. There is also a generic way to convert an object into a stream of bytes and back, which can be used to implement object persistency as well as various distributed object models.
Thus we see Python provides a variety of features. Some drawbacks of Python are due to its dynamic typing (reducing reliability), argument passing (like positional and name passing creates conflicts), interpreter based language (lower execution efficiency), and the negative aspects of multiple-inheritance. Also since Python program has to be properly indented, writability is compromised.
In conclusion Python attempts to glue many contemporary languages and serves as a good testing tool, rapid prototype development tool and a batch/scripting tool.