Python Basics

Python Basics

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.

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.

Programming with Python

Software quality is a vital ingredient to success in industry and science. Ubiquitous IT systems control the business processes of the global economy. Increasingly powerful computers and sophisticated algorithms provide the platform for new scientific discoveries. And global communication is inconceivable without intelligent software. In the race for customers, the pole position belongs to those who get to market faster than their competitors. Better and more creative solutions combined with the ability to respond instantly to new challenges drive the race. Writing secure and reliable programs in a fraction of the time normally required gets you first across the finish line.

The Programming Language of the Agile Era

Agility is the hallmark of our times and Python is the programming language of the agile era.

The Python universal programming language is the turbocharger of the IT department. Compared with other modern programming languages such as Java or C, Python achieves superior results in significantly shorter timescales for a number of different reasons. For example, Python is a very lean programming language. Python programs are a great deal shorter than code written in other modern programming languages. As a result, both development times and maintenance costs are drastically reduced. Less code means fewer errors, meaning the cost of identifying and eliminating these errors is also reduced. A comprehensive standard library and thousands of additional libraries in the Python Package Index provide developers with high-quality solutions which they can easily integrate into their applications to meet virtually any requirement. In this way, Python frees up vast resources, which can be earmarked for more productive use elsewhere.

The Master Key for System Integration

Python offers unique benefits for system integration. On the one hand, there are huge numbers of Python libraries, with which virtually any third-party system can be integrated. On the other hand, the libraries of many other programming languages can also be used in Python. Once they have been programmed, Python applications can run on all operating systems for which a Python interpreter exists, significantly reducing the cost of operating-system-specific applications.

The Language that has Changed Everything

For over 20 years, Python has been used successfully throughout the world as a programming language in industry, in the service sector, and also in research and science to meet a wide range of different requirements. In this time, the language has changed many things. The Python programming language is easy to learn. It has blurred the boundaries between users and developers. Increasing numbers of scientists, engineers, financial experts and others with little programming experience are using Python to solve specific complex technical problems.

Source: Python.org

1. 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

2. 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

3. 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

4. Python Basic Variables and Data Types

• Numeric Types
• Operators and Precedence / Arithmetic Expressions
• Integers
• Floating points

5. String Types

• Generating Strings in Python
• Common String Methods
• Formatting String Output
• Booleans
• Printing and formatting strings
• Scripting with input()
• About raw_input()

6. 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

7. If, elif, else

• Relational Operators
• Logical operators
• Comparison Operations
• “simple” if Statement
• If else statements
• If elif
• Nested if statement

8. Looping with “while”

• While usage
• Count controlled loop
• Event controlled loop
• Continue
• Break

9. Looping with “for”

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

10. Understanding Iterators

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

11. 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

12. Python List Comprehension

• Basic List Comprehensions
• Compound List Comprehensions

13. 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

14. Modules & Packages

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

15. Python Scope

• Naming conventions
• Local scope
• Global scope
• Nested scope

16. 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

17. (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)

Keyboard proficiency.

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.