Alta3 Research

Enjoy the best in Python Basics (PCEP-30-02) Training

Python is an interpreted, object-oriented, high-level language that gets work done in a hurry! Python can improve all professional’s ability to do work and is freely available on all major platforms without a charge. All lessons in our courseware are highly relevant for scripting within the workplace, including; data retrieval and storage from the local system, working with RESTful APIs, and decoding JSON.

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Python Basics

In this course, students will learn how to get started with Python, including an overview of the Standard Library, and popular 3rd party libraries. Lessons include version control with git, storing data in list and dictionaries, working with objects and methods, conditionals, looping, creating functions, and building classes. Highly relevant labs enhance these skills as students learn how to use JSON pulled from APIs, manipulate Excel spreadsheets, create feature rich charts and graphs, and parse log files with the Python regular expression library.

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Course Outline

    • Introduction to Python
    • Installing Python 2.7+
    • Installing Python 3.x
    • Preparing to write Python
    • Preparing to write a Python file (*.py) – Text Editors
    • Executing a Python file
    • Python Enhancement Proposals
    • How to “speak” Python
    • Python Statements and Control Flow
    • Python Interpreter
    • Overview of the Standard Library
  • Version Controlling Code
    • Set up a github account
    • Github essentials
    • README course requirements
    • How to Set up a repo
    • Issue a Pull request
    • How to use “Issues” for peer review
  • Basics of Programming
    • Functions
    • Objects
    • Methods
    • Built in Functions
    • Functions and Arguments
    • Print()
    • White spacing basic rules
    • String Literal Escape Sequences
    • Python Variables
    • Naming Conventions & Rules
    • Types as Objects
    • Sequence Types
    • List Iteration
    • List Enumeration
    • Sequence Assignments
    • Mutable vs Immutable Objects
    • Assignment Shorthand
  • Python Basic Variables and Data Types
    • Numeric Types
    • Operators and Precedence / Arithmetic Expressions
    • Integers
    • Floating points
  • String Types
    • Generating Strings in Python
    • Common String Methods
    • Formatting String Output
    • Booleans
    • Printing and formatting strings
    • Scripting with input()
    • About raw input()
  • Lists & Dictionaries & Tuples
    • Lists
    • Mixed Lists
    • Common List Methods
    • Other List Operations
    • Dictionaries
    • Python Dictionaries
    • Keys and Values
    • Dictionary Building
    • Dictionary Methods
    • Tuples
    • Python Time Tuples
    • Dictionaries vs Lists vs Tuples
    • Translating JSON to Pythonic Lists, Dictionaries and Tuples 
  • If, elif, else
    • Relational Operators
    • Logical operators
    • Comparison Operations
    • “simple” if Statement
    • If else statements
    • If elif
    • Nested if statement

  • Looping with “while”
  • While usage
  • Count controlled loop
  • Event controlled loop
  • Continue
  • Break

  • Looping with “for”
    • The for Loop
    • For iteration examples
    • Looping across data sets
    • Looping across lists of lists
    • Looping across lists of dictionaries

  • Understanding Iterators
    • The range() Function
    • Taking the range() of len()
    • Iterable Objects
    • The iter() Function
    • Looping with dictionaries
    • Looping with lists

  • Getting Data In and Out of Python
    • Opening Files
    • Working with Files
    • Read data from files
    • Controlling Output Location
    • Intro to working with APIs
    • What is a “REST”ful API?
    • APIs and JSON

  • Python List Comprehension
    • Basic List Comprehensions
    • Compound List Comprehensions

  • Creating Python Functions
    • Function Basics
    • Defining Functions
    • Function Polymorphism
    • Argument Defaults
    • Lambdas
    • What is if __name__ == “__main__”
    • Local Variables
    • Variable Masking
    • Creating functions using Sorted() and sort()
    • Preventing Variable Modifications
    • Argument Matching Methods

  • Modules & Packages
    • Pip and pip3
    • Module Basics
    • Packages
    • Virtual environments
    • Defined modules
    • Import modules
    • From import statements
    • Namespace

  • Python Scope
    • Naming conventions
    • Local scope
    • Global scope
    • Nested scope

  • Object Oriented Python
    • About OOP
    • The Class Statements
    • Defining a class
    • Class Inheritance
    • Classes as Objects
    • Using Dictionaries
    • Understanding self
    • Class fields and constructors
    • Data structures
    • Subclasses (Inheritance)
    • Multiple Inheritance
    • Static methods

  • (Optional) Regular Expression
    • import re library
    • Writing regular expression
    • Searching for data in files
    • Using Regular Expression to search data sets
    • Searching for data in Wireshark Traces (Python and *.pcaps)
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Labs

Lab 1 – Using vim

Lab 2 – Using leafpad

Lab 3 – Making a Github account

Lab 4 – Using & Installing Python

Lab 5 – The Shebang Line

Lab 6 – Starting to Use Print()

Lab 7 – Collecting Input()

Lab 8 – Working with Lists

Lab 9 – List Objects and Methods

Lab 10 – Lists of Lists

Lab 11 – Python Dictionaries

Lab 12 – Getting dir(obj) help() and pydoc

Lab 13 – String Methods

Lab 14 – Copying Files and Folders

Lab 15 – Moving and Renaming Files and Folders

Lab 16 – Testing if conditionals

Lab 17 – IPv4 Testing with if

Lab 18 – Writing your own if-logic script

Lab 19 – Using while, if, elif, else (Monty Python)

Lab 20 – Troubleshooting while, if, elif, else

Lab 21 – Starting to Learn Loops

Lab 22 – Looping with for

Lab 23 – for loops and range()

Lab 24 – Migrating 2.x to 3.x py

Lab 25 – Parsing Log Files

Lab 26 – Write to Files

Lab 27 – Read from Files

Lab 28 – Creating Functions

Lab 29 – Best Practice and pylint

Lab 30 – pip and import

Lab 31 – Exploring Network Interfaces

Lab 32 – Defining Functions

Lab 33 – Scripting Commands with Python

Lab 34 – Producing Graphs and Charts

Lab 35 – os.walk() the Directory Tree

Lab 36 – Python and Excel

Lab 37 – Python, APIs, and JSON

Lab 38 – Searching with Regular Expressions

Lab 39 – Creating objects in Python from “Scratch”

Lab 40 – Inheritance

Lab 41 – Using Classes

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    Who should attend?

    • This course is an appropriate introduction to students of any background looking to get started with Python. System administrators, network engineers, managers, and those with development skills in other programming languages will find the lessons and labs highly relevant to their disciplines.

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    Prerequisites

    Keyboard proficiency

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