Python Programming Language by Vasu Chetty

Origins of Python Created by: Guido van Rossum, a Dutch Programmer Created during: Christmas Break, 1989 Created because: Guido had some free time and an idea for an interpreter Named after:

Python Through the Ages Version 0: Inheritance, exception handling, functions, and core data types of list, str and dict Version 1: Lambda, reduce(), filter(), and map() Version 2: Garbage collection and generators Version 3: Unification of str/unicode types, statements switched to function calls, and instances of list replaced by views and iterators

Why Python? Freely available Well-documented Fosters rapid development Very high-level object-oriented language Integration facilities for mixed-language development

Who uses Python? Google (e.g. code.google.com was written in Python) New York Stock Exchange (web-based transaction system) YouTube NASA Other common uses include: RSS readers, CGI applications, generating and analyzing logs, and creating HTML calendars

Python Programming Paradigms (say that 10 times fast) Object-oriented Iterative (generators) Imperative (follows sequential steps) Functional (lambda calculus)

Common Data Types and Elements Numbers: integer, floating point, complex Other: boolean, none, string, tuple, list, dictionary, set Conditionals: if, else, elif Loops: while, for Supports: nested loops, function calls from other functions, string concatenation, combined boolean, string, or integer in conditional with “and” or “or”

Functions in Python Functions are essentially objects, making them very flexible Functions are considered as first class, so they can be passed to and from other functions Return values need not be set, return none statements are implicitly built in Functions can be nested within other functions

Pass-by-value or Pass-by-reference All parameters in Python are pass-by-reference, but some appear to act as pass-by-value because of the difference between mutable and immutable objects String, tuples and numbers are immutable, altering them will create a new instance Lists and dictionaries are mutable, altering them will also change the original object

Type Checking: Dynamic and Strong Python has dynamic type checking, which means all types are resolved at run-time rather than at compile time Python uses strong type checking, ensuring type errors are thrown for mismatches in type As of version 3, Python no longer supports type coercion Static type inference is not possible in Python

Object-orientedness Python supports multiple inheritance Python utilizes static variable and static method inheritance Super(), in version 3 of Python, is invoked dynamically and calls the superclass method of the same name

Conclusion Python is an easy-to-use, robust programming language that is freely available Python’s objects and functions are very versatile Python is a very high-level object-oriented language Python is awesome!