Python For SAP Developers (2023-03-13 - 2023-03-15)

Training Information

Original Agenda

• Original Agenda: Python For SAP Developers (2023-03-13 - 2023-03-15)

Material

• Python Programming: From Absolute Beginner to Advanced Productivity

• Github project: https://github.com/jfasch/2023-03-13

Notebook

• Entire book

• Structure

• Download notebook.ipynb

Day 1 (Basics)

Goal: gain a basic understanding of Python: variables, datatypes, some language internals (good to know if one wants to do more).

Demo

• Whetting Your Appetite (Livehacking Demo)

Setup

• Python Installation

• Visual Studio Code for Python Programming

• Jupyter Notebook Intro

Datatypes

An overview of the language, how variables are used, and which primary datatypes there are.

• Blahblah

• Hello World

• Running Python Programs

• Syntax etc.

• Commandline Arguments (sys.argv)

• Variables

• Datatypes

• Compound Datatypes

• Boolean

Exercises

• Exercise: Mixed List (Interactive Interpreter)

• Exercise: Dictionary: Errors?

• Exercise: Mixed List (Executable Program)

• Exercise: Determine Maximum of Two Numbers (solution: maximum.py)

• Exercise: Digit to English Word (solution: digit.py)

Day 2 (Basics, Continued)

Control Flow, Sequences, Iteration

Basic branching and looping. Iteration (via the for loop) is an important topic in Python, which is why we dedicate some time to it.

• The if Statement

• while Loops

• for Loops

• The range Function

Exercises

• Exercise: Sort out Duplicates (solution: uniq.py)

• Exercise: Primeness (while) (solution: prime-while.py)

• Exercise: Primeness (for) (solution: prime-for.py)

More Datatypes

There is more to say about datatypes than what has already been said (there is always more to everything in Python). What’s mutable, va. immutable, and what are the consequences? How can we save another three lines of code? What’s Pythonic?

• Sequential Datatypes

• Indexing and Slicing

• References, (Im)mutability

• Functions

Exercises: Functions

• Exercise: Determine Maximum of Two Numbers (Function) (solution: maximum-func.py)

• Exercise: Function: uniq() (solution: uniq-func.py)

• Exercise: Primeness (Function) (solution: prime-func.py)

More about datatypes …

• More About Strings

• Miscellaneous String Methods

• More About Lists

• More About Dictionaries

• More About Sets

• File I/O

Exercises, File I/O, Strings

• Exercise: Eliminate Empty/Comment-Only Lines

• Exercise: Counting Lines, Words, Characters

Day 3

Pandas

From Pandas …

• Pandas: Basics (DataFrame And Series)

• Pandas: Selecting Rows (And Columns) With iloc[]

• Pandas: Selecting Rows (And Columns) With loc[]

• Pandas: Indexes

• Pandas: Filters

• Pandas: Adding/Modifying Columns

• Pandas: Adding Rows

Hacking About On A SAP Test Dataset

• Hacking About On A SAP Test Dataset

Untold (From Original Agenda)

Original Agenda: Python For SAP Developers (2023-03-13 - 2023-03-15)

Goal: there’s always more. OO isn’t necessary, for example, nonetheless Python is strongly object oriented internally 1. Exception handling isn’t necessary either (one can always let exceptions pass by and terminate the program). Knowing what decorators are isn’t necessary either, much like the iterator protocol, or context managers.

Encoding

• Encoding

OO Introduction

Python is strongly object oriented internally - even an int is an object of class int, for example. It does not impose OO knowledge on its users though; nevertheless knowing a bit of it cannot hurt.

• Classes And Dictionaries

• Constructor

• Methods

• str() And repr()

Exception Handling

Error handling is commonly done using exceptions - a construct that lets you focus your code on the sunny case, and do clumsy error handling in a separate section of the code.

• Exception Handling

Context Managers (Automatic Cleanup)

Much like error handling, resource cleanup tends to become clumsy. Context managers are a way to bring more structure to that part of a program.

• Context Managers: The with Statement

Iteration, Generators, Comprehensions

Iterating over large sets of data - while at the same time saving resources - is one of the absolute strengths of Python. Lets dive a bit deeper into what a for loop actually is.

• Iterating Intelligently: Generators, and the Iterator Protocol

• Comprehensions (List, Dictionary, Set)

Decorators, and Related Topics

It might not be immediately obvious what a decorator is, and what benefits it can bring. Lets have a look into that part of the language. On the way, we’ll have a look into how parameter passing works, and what a closure is.

• Positional and Keyword Arguments

• Closures

• Decorators

Unit Testing

• Unit testing

Machine Learning: Pandas, NumPy, And Algorithms

From Machine Learning, Artificial Intelligence

• Machine Learning: Concepts and Terminology

• Linear Regression

• K-Means

Footnotes

1

OO is often associated with overengineering. Let’s not go in that direction.