Customized Training on Python

• Understand basic programming paradigms using Python 2 and Python 3
• Understand built in data types, variables, functions and flow control statements.
• Learn how to use string, tuple, list, bytearray, set, dictionary types effectively.
• Learn 'pythonic' idioms and anti-idioms.
• Learn functions, modules and file I/O operations.
• Learn the basic concepts of OOP in Python.
• Multi-threading and Multi-processing in Python.
• Learn some of the commonly used design patterns in Python
• Learn about process automation
• Learn various builtin python modules for network programming and network automation

• Engineers who wish to learn python program to developapplications or to automate their applications/framework.
• Engineers who wish to prototype new applications.

• Participants should be confortable with the following technologies:
  • Good understanding of basic python programming that include:
  • variables and datatypes
  • flow control statements
  • comprehensions and file I/O
  • Knowledge of OOP and modular programming concepts in any programming language are recommended.

Day 1 Introduction to Python

• Introduction to python programming
• An overview of scripting and the pragmatic developmentapproach.
• An overview on python interpreter
• An overview on Python development tools
• Python 2 vs Python 3 (feature differences)

Getting started with Python

• Numbers and expressions
• Variables and statements
• Conditional statements and loop
• Handling user input
• An overview of built-in functions and modules
• Python syntax, style and coding conventions
• Basic introspection using type() and dir() function
• Types, Classes and Dynamic typing, Duck typing

Working with Strings

• An overview of strings in python
• String operators
• Built-in string manipulation functions
• Built-in string methods
• Special string features in python
• Built-in modules for string handling
• Unicode strings and bytearray

Lists, Tuples and Sets

• Common sequence operations
• Manipulation of Lists
• Manipulation of Tuples
• Manipulation of Sets

Working with dictionaries

• Introduction to dictionaries
• Creating, assigning, updating dictionaries
• Dictionary operators, functions and built-in methods

Functions

• Creating user-defined functions
• Passing functions
• Formal arguments
• Variable-length arguments
• A walk-through on various built-in functions

Getting started with Python

• Numbers and expressions
• Variables and statements
• Conditional statements and loop
• Handling user input
• An overview of built-in functions and modules
• Python syntax, style and coding conventions
• Basic introspection using type() and dir() function
• Types, Classes and Dynamic typing, Duck typing
• Introduction to dictionaries
• Creating, assigning, updating dictionaries
• Dictionary operators, functions and built-in methods

Functions

• Creating user-defined functions
• Passing functions
• Formal arguments
• Variable-length arguments
• A walk-through on various built-in functions

Getting started with Python

• Numbers and expressions
• Variables and statements
• Conditional statements and loop
• Handling user input
• An overview of built-in functions and modules
• Python syntax, style and coding conventions
• Basic introspection using type() and dir() function
• Types, Classes and Dynamic typing, Duck typing

Day 2 Modular development

• Creating modules
• Variable scope
• Understanding namespaces
• Importing modules and module attributes
• Module hierarchy

File and Directory handling

• File I/O operations
• Built-in file and directory handling libraries
• fileinput
• stat
• filecmp and dircmp
• glob, zipfile and tarfile
• pickle and shelve modules
• Serialization using json

Standard Python modules

• Using the sys module
• sys.argv, sys.path, sys.version
• An overview on __builtin__ and __future__ modules

Handson exercises

• Practice basic programming concepts using python.
• Small exercises on understanding conditional constructsand loops.
• Practice various string operators, functionsand built-in methods
• Practice exercises on Lists and Tuples
• Practice exercises on dictionaries, functions and modules
• Practice exercises on file operations
• Practice exercises on logging, os related features
• A small project like inventory management system or library management system

Day 3 Classes and Objects

• Introduction to OOP using python
• Classes and class attributes
• Instances and instance attributes
• Binding and method invocation
• Composition, Subclassing and Derivation
• Inheritance
• Built-in functions for classes, instances and other objects
• An overview of built-in python classes andmodules

Errors and exception handling

• Introduction to exceptions
• Detecting and handling exceptions
• Exceptions as Strings and Classes
• Raising exceptions
• Creating exceptions
• Standard exceptions

Implementing multi-tasking in Python programs

• Introduction to threads and processes
• Creating and managing threads and processes
• Threading vs multiprocessing module
• Concurrency management using Lock and RLock
• Producer Consumer algorithm using Queue
• Implementing thread pool and process pool

Hands on exercises

• Create custom python library module
• Practice exercises on multi-threading and multi-processing
• A small project like a command line parses

Day 4 Advanced OOP features in Python

• Python OO architectural overview
• Python OO paradigms and metaprogramming concepts
• An overview on Python special methods:
  • __new__(), __init__(), __del__(),
  • __str__(), __repr__(), __len__(), __nonzero__()
  • __cmp__(), __eq__(), __ne__() and family
  • Operator overloading
  • Dictionary and List emulation
  • Accessor methods - __getattr__(), __setattr__(), __delattr__()

Common design patterns with examples and exercises

• Singleton/Borg patterns
• Implementing thread pool and process pool

Hands on exercises

• Create custom python library module
• Practice exercises on multi-threading and multi-processing
• A small project like a command line parses

Day 4 Advanced OOP features in Python

• Python OO architectural overview
• Python OO paradigms and metaprogramming concepts
• An overview on Python special methods:
  • __new__(), __init__(), __del__(),
  • __str__(), __repr__(), __len__(), __nonzero__()
  • __cmp__(), __eq__(), __ne__() and family
  • Operator overloading
  • Dictionary and List emulation
  • Accessor methods - __getattr__(), __setattr__(), __delattr__()

Common design patterns with examples and exercises

• Singleton/Borg patterns
• Factory method
• Factory pattern
• Accessor pattern
• Decorator patterns and built-in decorators

Hands on exercises

• Practice exercises on OOP related features in python
• Practice exercises on design patterns

Day 5 Testing, Debugging and Deployment

• Using the unittest module for writing testcases
• Using doctest
• Regressing testing using test module
• Documentation generation using pydoc
• Using pdb debugger framework and inspect
• Tracing python statement execution using
• Timing measurement using timeit module

Network programming

• An overview of the socket module
• Creating network servers and clients using socket module
• Factory pattern
• Accessor pattern
• Decorator patterns and built-in decorators

Hands on exercises

• Practice exercises on OOP related features in python
• Practice exercises on design patterns

Day 5 Testing, Debugging and Deployment

• Using the unittest module for writing testcases
• Using doctest
• Regressing testing using test module
• Documentation generation using pydoc
• Using pdb debugger framework and inspect
• Tracing python statement execution using
• Timing measurement using timeit module

Network programming

• An overview of the socket module
• Creating network servers and clients using socket module
• Creating network applications using multiprocessing
• Creating asynchronous Socket server and clients using asyncore module
• Using the SocketServer framework for creating scalable network servers
• Introductory overview on Twisted Matrix framework

Hands on exercises

• Creating a simple multi-tasking fileserver that can serve files to client, supporting multiple concurrent client connections.
• Simple examples of chat box
• Sending and receiving e-mails using python script