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Python Fundamentals (3 days-8 hours a day)

Course Introduction:

Python Fundamentals goes for the duration of 3 days, covering the language references, explains object-­‐oriented as well as functional programming techniques, error handling, modules, many of the Python libraries, and best practices.All concepts are explained through hands-­‐on examplesand exercises. The participants would be learning by doing.


This is an hands-on course, designedto help the developers to speedup in Python, as quickly as possible. The participant’s in this course, will experience the following:

* Architecture
* Input and output
* Controlflow
* Error handling.
* Function
* Garbage collection
* Object-oriented features.
* Built‐in data types: using them, and inheriting from them in classes you design.
* List comprehensions,decorators, iterators, generators, with context managers.
* Creating and using libraries and packages.
* Python third party library (PyPi).

Lab requirements:

* As the training is highly lab oriented, each participant Attending the training program must be provided with a Computer with the following software installed:
-Windows or Linux with ActivePython 2.7+ installed
- A good programmer's editor (Notepad++ or PSPad on Windows, vim/emacs on Linux) installed.


This course is designed for developers, system administrators, and test engineers, who wish to develop, automate, and test applications and systems using Python


The participants should haveprior programming experience and should be familiar with basic programming constructs. Prior experience to object‐oriented programming would definitely add advantage.

Course Contents

Day 1
Python Introduction Using the Interpreter Python Scripting
what’s Python? Python's Interactive Prompt Python Scripts in Linux/Unix & Windows
Why do people use Python? Scripting Whitespace Significance
Some quotable quotes Program Execution Model Line Termination
A Python history lesson Program Architecture: modules Comments in Python
Advocacy News How to run Python programs Basic Output Generation
What’s Python good for? The IDLE interface Simple User Input
What’s Python not good for? Other python IDEs Python Modules
The features list Module Search Paths
Python portability Determining the System Search Path
Summary input(),raw_input()
Working with Variables in Python Numeric Operations in Python Python Compound Statements
Python Variables More About Python's Numeric Types Python Nesting Recap
Naming Conventions & Rules Numeric Tools Comparison Operations
Types as Objects The Decimal Module The if Statement
Variable References & Garbage Collection Operator The if Ternary Expression
Sequence Types Arithmetic The while Loop
Membership Statements Logical The for Loop
List Iteration Relational Traversing Parallel Sets
Sequence Assignments Bitwise
Mutable vs Immutable Objects Special Operators
Multi Target Assignments Operator Precedence
Classes and Objects Day2
Introduction to OOP using python Python String Types Python's Tuples
Classes and class attributes Generating Strings in Python Immutable
Instances and instance attributes Immutable Common Tuples Methods
Binding and method invocation Common String Methods Tuples Operations
Composition, Subclassing and Derivation Type Conversion in Python Tuples Indexing
Inheritance Formatting String Output Tuples Slicing
Built‐in functions for classes, instances and other objects Format Specifier Tuples Iteration
Privacy and Delegation Variable Substitution Multi‐Dimensional Tuples (Matrices)
An overview of built‐in python classes and modules String Indexing
String Slicing, String Iteration
Python's Lists Python ListComprehension Python Dictionaries
Common List Methods Basic List Comprehensions Python Dictionaries
The range() Function Compound List Comprehensions Assigning Values to Dictionaries
List Operations Basic Input/Output with Files Dictionary Methods
String Indexing Opening Files Dictionaries vs Lists & Tuples
String Slicing Working with Files Dictionary Indexing
String Iteration Controlling Output Location Dictionary Iteration
Multi‐Dimensional Lists (Matrices)
Handling Compound Data Structure Creating Python Functions
Nested Structure Function Basics
Parsing and Loading into Data Structure Defining Functions
Retrival of data from the Data Structure Function Polymorphism
Argument Defaults
Local Variables
Preventing Variable Modifications
Argument Matching Methods
Keyword Argument Methods
Day 3
Regular Expression in Python Modules & Packages Exceptions
Meta Characters Module Basics About Exceptions
remodule Packages Python's Default Exception Handler
Search Using __all__ and _Variables Using Try/Except/Else/Finally Exceptions
Match Using__name__ Generating User Defined Exceptions
Split Using third party modules More on Exceptions
Translation Exception Examples
Using Asserts,Exception Classes

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