Python Programming for Chemical Engineers

1. Introduction to programming and the Python language

The role of programming in engineering problem solving, with particular emphasis on numerical calculations, data processing, and automation.

• The concept of programming and its engineering applications
• Sequential execution, loops, branching
• The role of the Python language

2. Basic programming elements: variables and data types

The concept of variables, their creation and use in Python through simple computational examples. Basic data types (integers, floating-point numbers, Boolean values, strings) and their meaning in an engineering context.

• Creating and naming variables
• Basic data types and simple operations

3. Composite data types: strings and lists

The use of strings for handling textual data. Introduction of lists as tools for storing data series, measurements, and parameter sets.

• String operations
• Creating and indexing lists

4. Data structures and references

The fundamentals of the Python object model, the reference-based approach, and its effect on program behavior. Through simple examples, we demonstrate how data changes in memory.

• Objects and references
• Effects of copying and modification

5. Control structures and exceptions

The use of conditional statements and loops to implement algorithms. Error and exception handling, with particular emphasis on invalid measurement or input data.

• Advanced loop control
• Exception handling

6. Functions and modular thinking

The use of functions to create reusable and readable code. Parameter passing, return values, and the basics of reference handling.

• Defining custom functions
• Parameters and return values

7. Sorting algorithms and recursion

The presentation of simple sorting methods for processing data sets. The concept of recursion and its role in solving algorithmic problems.

• List and data sorting
• Fundamentals of recursive functions

8. Fundamentals of object-oriented programming

Introduction of the object-oriented approach through the modeling of real engineering objects. The role of classes, attributes, and methods in structured programming.

• Classes and objects
• Constructors and methods

9. File handling and multi-module programs

Reading from and writing to files, and practical approaches to storing measurement results. Structuring larger programs using multiple modules.

• Handling text files
• Modules and imports

10. Operators and numerical representation

Overview of arithmetic, logical, and comparison operators used in Python. Numerical representation, floating-point inaccuracies, and their engineering relevance.

• Types of operators
• Numerical accuracy and errors

11. Composite data structures

The use of dictionaries, sets, and nested data structures. Processing structured data through practical examples.

• Dictionaries and sets
• Nested data structures

12. State machines and regular expressions

Basic concepts of state machines and their simple applications in process modeling. The use of regular expressions for data searching and filtering.

• Fundamentals of state machines
• Basics of regular expressions

13. Presentation of application areas

Application of the knowledge acquired in the course to typical use cases through simple examples, providing learning outcomes that enable interested students to independently explore new topics.

• The operation of the web and implementation of simple communication between software systems
• Loading and writing tabular data