Programming Across Disciplines

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Python Across Disciplines
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Table of Contents

1.1.   Introduction 1.2.   About the Author & Contact Info 1.3.   Book Conventions 1.4.   What (Who) is a Programmer? 1.5.   Programming Across Disciplines 1.6.   Foundational Computing Concepts 1.7.   About Python 1.8.   First Steps 1.8.1 Computer Setup 1.8.2 Python print() Function 1.8.3 Comments
2.1. About Data 2.2. Data Types 2.3. Variables 2.4. User Input 2.5. Data Structures (DS)         2.5.1. DS Concepts         2.5.2. Lists         2.5.3. Dictionaries         2.5.4. Others 2.6. Files         2.6.1. Files & File Systems         2.6.2. Python File Object         2.6.3. Data Files 2.7. Databases
3.1. About Processing 3.2. Decisions         3.2.1 Decision Concepts         3.2.2 Conditions & Booleans         3.2.3 if Statements         3.2.4 if-else Statements         3.2.5 if-elif-else Statements         3.2.6 In-Line if Statements 3.3. Repetition (a.k.a. Loops)         3.3.1 Repetition Concepts         3.3.2 while Loops         3.3.3 for Loops         3.3.4 Nested Loops         3.3.5 Validating User Input 3.4. Functions         3.4.1 Function Concepts         3.4.2 Built-In Functions         3.4.3 Programmer Defined Functions 3.5. Libraries         3.5.1 Library Concepts         3.5.2 Standard Library         3.5.3 External Libraries 3.6. Processing Case Studies         3.6.1 Case Studies         3.6.2 Parsing Data
4.1. About Output 4.2. Advanced Printing 4.3. Data Visualization   4.4 Sound
  4.5 Graphics
  4.6 Video
  4.7 Web Output
  4.8 PDFs & Documents
  4.9 Dashboards
  4.10 Animation & Games
  4.11 Text to Speech

5.1 About Disciplines 5.2 Accounting 5.3 Architecture 5.4 Art 5.5 Artificial Intelligence (AI) 5.6 Autonomous Vehicles 5.7 Bioinformatics 5.8 Biology 5.9 Bitcoin 5.10 Blockchain 5.11 Business 5.12 Business Analytics 5.13 Chemistry 5.14 Communication 5.15 Computational Photography 5.16 Computer Science 5.17 Creative Writing 5.18 Cryptocurrency 5.19 Cultural Studies 5.20 Data Analytics 5.21 Data Engineering 5.22 Data Science 5.23 Data Visualization 5.24 Drone Piloting 5.25 Economics 5.26 Education 5.27 Engineering 5.28 English 5.29 Entrepreneurship 5.30 Environmental Studies 5.31 Exercise Science 5.32 Film 5.33 Finance 5.34 Gaming 5.35 Gender Studies 5.36 Genetics 5.37 Geography 5.38 Geology 5.39 Geospatial Analysis ☯ 5.40 History 5.41 Humanities 5.42 Information Systems 5.43 Languages 5.44 Law 5.45 Linguistics 5.46 Literature 5.47 Machine Learning 5.48 Management 5.49 Marketing 5.50 Mathematics 5.51 Medicine 5.52 Military 5.53 Model Railroading 5.54 Music 5.55 Natural Language Processing (NLP) 5.56 Network Analysis 5.57 Neural Networks 5.58 Neurology 5.59 Nursing 5.60 Pharmacology 5.61 Philosophy 5.62 Physiology 5.63 Politics 5.64 Psychiatry 5.65 Psychology 5.66 Real Estate 5.67 Recreation 5.68 Remote Control (RC) Vehicles 5.69 Rhetoric 5.70 Science 5.71 Sociology 5.72 Sports 5.73 Stock Trading 5.74 Text Mining 5.75 Weather 5.76 Writing
6.1. Databases         6.1.1 Overview of Databases         6.1.2 SQLite Databases         6.1.3 Querying a SQLite Database         6.1.4 CRUD Operations with SQLite         6.1.5 Connecting to Other Databases
Built-In Functions Conceptss Data Types Date & Time Format Codes Dictionary Methods Escape Sequences File Access Modes File Object Methods Python Keywords List Methods Operators Set Methods String Methods Tuple Methods Glossary Index Appendices   Software Install & Setup
  Coding Tools:
  A.  Python ↗   B.  Google CoLaboratory ↗   C.  Visual Studio Code ↗   D.  PyCharm IDE ↗   E.  Git ↗   F.  GitHub ↗
  Database Tools:
  G.  SQLite Database ↗   H.  MySQL Database ↗

Python Across Disciplines
by John Gordon © 2023

Table of Contents

6.0 Chapter Overview     6.1. Databases
        6.1.1 Overview of Databases         6.1.2 SQLite Databases         6.1.3 Querying a SQLite Database         6.1.4 CRUD Operations w/SQLite         6.1.5 Connecting to Other Databases     6.2. Object Oriented Programming
            6.2.1. Introduction to OOP             6.2.2. Unified Modeling Language             6.2.3. Classes & Objects             6.2.4. Abstraction             6.2.5. Encapsulation             6.2.6. Inheritance             6.2.7. Polymorphism             6.2.8. Exception Handling             6.2.9. Codealong: Employees             6.2.10. Codealong: Cars     6.3. Graphical User Interfaces
            6.3.1. Introduction to GUIs
            6.3.2. Tkinter
            6.3.3. Codealong: Login Form
            6.3.4. Codealong: Data Entry Form
    6.4. Algorithms & Data Structures
            6.4.1. Introduction to Algorithms
            6.4.2. Searching
            6.4.3. Sorting
            6.4.4. Metrics
            6.4.5. Nodes
            6.4.6. Linked Lists 1
            6.4.7. Linked Lists 2
            6.4.8. Stacks
            6.4.9. Queues
            6.4.10. Heaps
            6.4.11. Trees
            6.4.12. Graphs
            6.4.13. Maps
            6.4.14. Hashing
            6.4.15. Cryptography
    6.5. Additional Advanced Topics
            6.5.1. APIs
            6.5.2. Automation
            6.5.3. Recursion
            6.5.4. More About Datasets
            6.5.5. Large Language Models
            6.5.6. Text Analysis
            6.5.7. Web Scraping
            6.5.8. Data Science
            6.5.9. Machline Learning
            6.5.10. Natural Lang Processing
            6.5.11. Artificial Intelligence
            6.5.12. Cython
            6.5.13. PyPy
            6.5.14. Multi-Threading
            6.5.15. Parallel Processing

Table of Contents » Chapter 4 : Output : Sound

Sound

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Overview

Overview

There are many libraries available for Python that enable programmers to generate and manipulate audio, making digital audio accessible. This page introduces the basics of playing sounds and songs using Python, covering fundamental concepts and providing examples to help you get started.

Before we start coding coding, it is important to understand what digital audio is. At its core, digital audio is a representation of sound recorded in, or converted into, digital form. In this digital form, sound is represented by samples, which are measurements of the sound wave at a particular time, taken at regular intervals (the sample rate). The most common sample rate for audio is 44,100 samples per second (44.1 kHz), which is the standard for audio CDs.

Python libraries make working with audio straightforward. Here are a few popular ones:

playsound: This library is perfect for beginners who want to play sound files without getting into the complexities of audio processing.
pydub: Pydub is a high-level audio library that allows you to manipulate audio with a simple and Pythonic interface.
librosa: For more advanced audio analysis and manipulation, librosa offers a wide range of tools for music and audio analysis.

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© 2023 John Gordon
Cascade Street Publishing, LLC