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 » Reference Materials : Python Keywords

Python Keywords

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Python keywords are reserved words that have a specific, predefined meaning in the Python programming language. These words cannot be used as identifiers, such as names for variables, functions, or classes, because they are already used by the language syntax for defining the structure and control flow of the code. Examples of Python keywords include if, else, for, while, break, continue, def, return, class, try, except, import, from, as, with, True, False, and None. Each of these keywords serves a unique purpose in Python, ranging from creating conditional statements, loops, functions, classes, to handling exceptions and importing modules. The number and nature of keywords can vary slightly between different versions of Python, but they are all integral to the language's structure. Understanding and correctly using these keywords is essential for writing syntactically correct and efficient Python code.

Keyword	Description
and	A logical operator
as	To create an alias
assert	For debugging
break	To break out of a loop
class	To define a class
continue	To continue to the next iteration of a loop
def	To define a function
del	To delete an object
elif	Used in conditional statements, same as else if
else	Used in conditional statements
except	Used with exceptions, what to do when an exception occurs
False	Boolean value, result of comparison operations
finally	with exceptions, a block of code that will be executed no matter if there is an exception or not
for	To create a for loop
from	To import specific parts of a module
global	To declare a global variable
if	To make a conditional statement
import	To import a module
in	To check if a value is present in a list, tuple, etc.
is	To test if two variables are equal
lambda	To create an anonymous function
None	Represents a null value
nonlocal	declare a non-local variable
not	logical operator
or	logical operator
pass	null statement, a statement that will do nothing
return	To exit a function and return a value

raise	To raise an exception
True	value, result of comparison operations
try	To make a try...except statement
while	To create a while loop
with	Used to simplify exception handling
yield	To end a function, returns a generator

© 2023 John Gordon
Cascade Street Publishing, LLC