Programming with Python for Engineers

Programming with Python for Engineers

An interactive book introducing Python to engineers and engineering students.

The writing of the book is still ongoing and there may be updates.

All comments and updates welcome. See how you can contribute. We thank our contributors.

Disclaimer: The PDF version is automatically generated and may include errors. Prefer HTML or Colab versions for the time being.

Copyright: All rights reserved.

Authors

Sinan Kalkan

Dept. of Computer Engineering, METU

Onur Tolga Sehitoglu

Dept. of Computer Engineering, METU

Gokturk Ucoluk

Dept. of Computer Engineering, METU

We thank all the contributors
for making this open source book possible and available for everyone.

Contribute to the book.

BibTeX entry for citing the book

@book{kalkan2021,
    title={Programming with Python for Engineers},
    author={Sinan Kalkan and Onur Tolga Sehitoglu and Gokturk Ucoluk},
    note={\url{https://ceng240.github.io/}},
    year={2021}
}

Table of contents

• Preface
  • i. About this book
  • ii. What is computing?
  • iii. Are all ‘computing machinery’ alike?
  • iv. What is a ‘computer’?
  • v. What is programming?

• 1. Basic Computer Organization
  • 1.1. The von Neumann Architecture
  • 1.2. The Memory
  • 1.3. The CPU
  • 1.4. The Fetch-Decode-Execute Cycle
  • 1.5. The Stored Program Concept
  • 1.6. Pros and Cons of the von Neuman Architecture
  • 1.7. Peripherals of a computer
  • 1.8. The running of a computer
  • 1.9. Important Concepts
  • 1.10. Further Reading
  • 1.11. Exercises
• 2. A Broad Look at Programming and Programming Languages
  • 2.1. How do we solve problems with programs?
  • 2.2. Algorithm
  • 2.3. Data Representation
  • 2.4. The World of Programming Languages
  • 2.5. Introducing Python
  • 2.6. Important Concepts
  • 2.7. Further Reading
  • 2.8. Exercise
• 3. Representation of Data
  • 3.1. Representing integers
  • 3.2. Representing real numbers
  • 3.3. Numbers in Python
  • 3.4. Representing text
  • 3.5. Containers
  • 3.6. Representing truth values (Booleans)
  • 3.7. Important Concepts
  • 3.8. Further Reading
  • 3.9. Exercises
• 4. Dive into Python
  • 4.1. Basic Data
  • 4.2. Container data (str, tuple, list, dict, set)
  • 4.3. Expressions
  • 4.4. Basic Statements
  • 4.5. Compound Statements
  • 4.6. Basic actions for interacting with the environment
  • 4.7. Actions that are ignored
  • 4.8. Actions and data packaged in libraries
  • 4.9. Providing your actions to the interpreter
  • 4.10. Important Concepts
  • 4.11. Further Reading
  • 4.12. Exercises
• 5. Conditional and Repetitive Execution
  • 5.1. Conditional execution
  • 5.2. Repetitive execution
  • 5.3. Important Concepts
  • 5.4. Further Reading
  • 5.5. Exercises
• 6. Functions
  • 6.1. Why define functions?
  • 6.2. Defining functions
  • 6.3. Passing parameters to functions
  • 6.4. Scope of variables
  • 6.5. Higher-order functions
  • 6.6. Functions in programming vs. functions in Mathematics
  • 6.7. Recursion
  • 6.8. Function Examples
  • 6.9. Programming Style
  • 6.10. Important Concepts
  • 6.11. Further Reading
  • 6.12. Exercises
• 7. A Gentle Introduction to Object-Oriented Programming
  • 7.1. Properties of Object-Oriented Programming
  • 7.2. Basic OOP in Python
  • 7.3. Widely-used Member Functions of Containers
  • 7.4. Important Concepts
  • 7.5. Further Reading
  • 7.6. Exercises
• 8. File Handling
  • 8.1. First Example
  • 8.2. Files and Sequential Access
  • 8.3. Data Conversion and Parsing
  • 8.4. Accessing Text Files Line by Line
  • 8.5. Termination of Input
  • 8.6. Example: Processing CSV Files
  • 8.7. Formatting Files
  • 8.8. Binary Files
  • 8.9. Note on Files, Directory Organization and Paths
  • 8.10. List of File Class Member Functions
  • 8.11. Important Concepts
  • 8.12. Further Reading
  • 8.13. Exercises
• 9. Error Handling and Debugging
  • 9.1. Types of Errors
  • 9.2. How to Work with Errors
  • 9.3. Debugging
  • 9.4. Important Concepts
  • 9.5. Further Reading
• 10. Scientific and Engineering Libraries
  • 10.1. Numerical Computing with NumPy
  • 10.2. Scientific Computing with SciPy
  • 10.3. Data handling & analysis with Pandas
  • 10.4. Plotting data with Matplotlib
  • 10.5. Important Concepts
  • 10.6. Further Reading
  • 10.7. Exercises
• 11. An Application: Approximation and Optimization
  • 11.1. Approximating Functions with Taylor Series
  • 11.2. Finding the Roots of a Function
  • 11.3. Finding a Minimum of Functions
  • 11.4. Important Concepts
  • 11.5. Further Reading
  • 11.6. Exercises
• 12. An Application: Solving a Simple Regression Problem
  • 12.1. Introduction
  • 12.2. Least-Squares Regression
  • 12.3. Linear Regression with SciPy
  • 12.4. Non-linear Regression with SciPy
  • 12.5. Important Concepts
  • 12.6. Further Reading
  • 12.7. Exercises