Programming Across Disciplines

☰

Python Across Disciplines
with Python + AI Tool Python

Python

CoLab AI

ChatGPT

×

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 » Reference Materials : Escape Sequences

Escape Sequences

Subscribe Contact

In Python programming, escape sequences are special characters used within strings to represent characters that can't be easily typed or have special meaning in Python. Prefaced by a backslash (\), these sequences are interpreted by Python to perform specific functions or represent specific characters. Common escape sequences include \n for a newline, \t for a tab, \\ for a literal backslash, \' for a single quote, and \" for a double quote. These sequences are essential for including characters in a string that would otherwise be interpreted differently by Python. For instance, the newline escape sequence (\n) is widely used to break text into multiple lines. Escape sequences enable more precise control over the formatting and representation of strings in Python code, allowing developers to include a range of characters that are not easily typable or would disrupt the string's syntax if used directly.

Escape Sequence	Description	Code	Output
\\	Prints a backslash character.	`print("\\")`	\
\'	Prints a single quote mark.	`print("\'")`	'
\"	Prints a double quote mark.	`print("\"")`	"
\b	Backspace - removes the previous character in the string.	`print("Test" + "\b" + " String")`	Tes String
\f	Formfeed (FF)	`print("Test\fString")`	Test String
\n	Linefeed (LF)	`print("Test\nString")`	Test String
\N{name}	Prints a character from the Unicode Character Database. You can find an index of the available emoji characters at here.	`print(u"\N{Grinning Face}")`	😀
\t	Horizontal tab (TAB). Inserts a tab at the point of the \t sequence.	`print("ABCD\tEFGHZ")`	ABCD EFGH

© 2023 John Gordon
Cascade Street Publishing, LLC