Introduction to Programming

Why Python

• Top coding languages to learn
  • LinkedIn Top 10
  • Top Language Chart by Github
• Why for CyberSecurity?
  • https://pauljerimy.com/security-certification-roadmap/

What is Python

• High Level
• Interpreted
• Dynamically Typed
• Focus on readability

Versions

• Python 2 - End of Life (EOL)
• Python 3 - Current
• https://www.interviewbit.com/blog/difference-between-python-2-and-3/

Python Editors

• Visual Studio Code - Support many languages
• PyCharm - Specially designed for Python
• SPYDER - Data Science
• Python Jupyter Notebooks - Data Science

High Level vs Low Level

• Low
  • Assembly language - https://codedocs.org/what-is/assembly-language
• High
  • Java, C, Python, Ruby
• /resources/images/high_level-low_level.png

Interpreted vs. Compiled

• A compiler's job is to transfer source code to machine code.
• A Interpreter's job is to interpret and covert code at runtime.
• /resources/images/compiled_vs_interpreted.png
• CS50 Youtube on Compiled vs Interpreted

Data Types

Jupyter Notebook - 02-Data Types

Jupyter Notebook - 10-Booleans

Syntax

Jupyter Notebook - 03-Syntax

Zen of Python

The Zen of Python, by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!