Introduction to Python (Course 408 – 40 Hours)

Overview:

This course is intended for embedded systems developers taking their first steps with Linux as an embedded system platform, and provides them with the skills required for becoming a productive programmer in that environment. The curriculum includes building applications and device drivers with real time constraints and understanding the inner workings of the Linux system and its effects on system behavior. The course is suitable for people planning to develop for embedded Linux platforms from any source, including “home made” Linux distributions or embedded Linux system vendors.

Course Objectives:

Python is an easy to learn and powerful programming language that is used in many computer science areas. This five-day workshop concentrates on the Python programming language and many libraries. From basic procedural syntax to sophisticate object-oriented programming techniques, delegates will learn how to write Python scripts and applications with code that is robust, maintainable and efficient. The course is presented as a mixture of lectures and hands-on exercises. Practical sessions follow each topic, designed to reinforce the points covered. Additional information is provided in appendices to extend the learning experience after the course has been completed.

Who Should Attend:

This course is designed for anyone who needs to learn how to write programs in Python.

Course Contents:

Introduction to Python

  • Strengths and Weaknesses
  • A Brief History of Python
  • Python Versions
  • Installing Python
  • Environment Variables
  • Executing Python from the Command Line
  • IDLE
  • Editing Python Files
  • Getting Help
  • Dynamic Types
  • Python Reserved Words
  • Naming Conventions

Basic Python Syntax

  • Introduction
  • Basic Syntax
  • Comments
  • String Values
  • String Operations
  • The format Method
  • String Slices
  • String Operators
  • Numeric Data Types
  • Conversions
  • Simple Input and Output
  • The print Function

Language Components

  • Introduction
  • Control Flow and Syntax
  • Indenting
  • The if Statement
  • Relational Operators
  • Logical Operators
  • True or False
  • Bit Wise Operators
  • The while Loop
  • break and continue
  • The for Loop

Language Components

  • Introduction
  • Lists
  • Tuples
  • Sets
  • Dictionaries
  • Sorting Dictionaries
  • Copying Collections
  • Summary

Collections

  • Introduction
  • Lists
  • Tuples
  • Sets
  • Dictionaries
  • Sorting Dictionaries
  • Copying Collections
  • Summary

Functions

  • Introduction
  • Defining Your Own Functions
  • Parameters
  • Function Documentation
  • Keyword and Optional Parameters
  • Passing Collections to a Function
  • Variable Number of Arguments
  • Scope
  • Functions - "First Class Citizens"
  • Passing Functions to a Function
  • Mapping Functions in a Dictionary
  • Lambda
  • Closures

Modules

  • Overview
  • Standard Modules - sys
  • Standard Modules - math
  • Standard Modules - time
  • The dir Function

Exceptions

  • Errors
  • Run Time Errors
  • The Exception Model
  • Exception Hierarchy
  • Handling Multiple Exceptions
  • raise
  • assert
  • Writing Your Own Exception Classes

Input and Output

  • Introduction
  • Data Streams
  • Creating Your Own Data Streams
  • Access Modes
  • Writing Data to a File
  • Reading Data From a File
  • Additional File Methods
  • Using Pipes as Data Streams
  • Handling IO Exceptions
  • Working with Directories
  • Metadata
  • The pickle Module

Classes in Python

  • Principles of Object Orientation
  • Creating Classes
  • Instance Methods
  • File Organization
  • Special Methods
  • Class Variables
  • Inheritance
  • Polymorphism
  • Type Identification
  • Custom Exception Classes
  • Class Documentation - pydoc

Classes in Python

  • Introduction
  • Simple Character Matches
  • Special Characters
  • Character Classes
  • Quantifiers
  • The Dot Character
  • Greedy Matches
  • Grouping
  • Matching at Beginning or End
  • Match Objects
  • Substituting
  • Splitting a String
  • Compiling Regular Expressions
  • Flags

Introduction to NumPy and SciPy

  • Python arrays and NumPy Arrays
  • Multi dimensional Arrays
  • Array slicing
  • Fancy Indexing
  • Data types
  • Array calculation methods
  • Statistics methods
  • Universal functions
  • Broadcasting
  • Universal function methods
  • Matplotlib
  • Line plots
  • Scalar plots
  • Bar plots
  • Histograms
  • Multiple plots
  • Image display
  • Image display
  • Interpolation
  • Integration
  • FFT
  • Signal and image processing
  • Optimizations
  • Statistics
  • Linear algebra
  • Matrix objects
  • Introduction to IPython
  • Interactive work
  • Numerical computing with IPython
  • Interactive Plotting
  • High performance and parallel computing
  • Debugging with pydev

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