Job Ready Python 1st Edition by Haythem Balti, Kimberly Weiss 1119817390 9781119817390

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ISBN 10: 1119817390
ISBN 13: 9781119817390
Author: Haythem Balti; Kimberly A. Weiss

Get ready to take on Python with a practical and job-focused guide 

Job Ready Python offers readers a straightforward and elegant approach to learning Python that emphasizes hands-on and employable skills you can apply to real-world environments immediately. 

Based on the renowned mthree Global Academy and Software Guild training program, this book will get you up to speed in the basics of Python, loops and data structures, object-oriented programming, and data processing. You’ll also get: 

• Thorough discussions of Extract, Transform, and Load (ETL) scripting in Python 
• Explorations of databases, including MySQL, and MongoDB–all commonly used database platforms in the field 
• Simple, step-by-step approaches to dealing with dates and times, CSV files, and JSON files 

Ideal for Python newbies looking to make a transition to an exciting new career, Job Ready Python also belongs on the bookshelves of Python developers hoping to brush up on the fundamentals with an authoritative and practical new handbook.  

Job Ready Python 1st Table of contents:

PART I: Getting Started with Python

Lesson 1: Setting Up a Python Programming Environment

• Overview of Python, Replit, Jupyter Notebook, Visual Studio Code, and using Python from the command line.

Lesson 2: Understanding Programming Basics

• Introduction to the future of programming, programming languages, data types, and variables.

Lesson 3: Exploring Basic Python Syntax

• Single-line commands, semicolons, backslashes, case structure, comments, user input, variable types, and naming conventions.

Lesson 4: Working with Basic Python Data Types

• Overview of number types, operations, PEMDAS, math functions, Boolean types, logical operators, and comparison operators.

Lesson 5: Using Python Control Statements

• Review of control structures, sequence control, selection statements, if-else conditions, and nested conditions.

Lesson 6: Pulling It All Together: Income Tax Calculator

• Step-by-step guide to creating a simple income tax calculator application.

PART II: Loops and Data Structures

Lesson 7: Controlling Program Flow with Loops

• Explanation of loop types (for, while), iteration, and working with strings.

Lesson 8: Understanding Basic Data Structures: Lists

• Creating, indexing, slicing, modifying lists, list comprehension, sorting, and copying.

Lesson 9: Understanding Basic Data Structures: Tuples

• Tuple operations, immutability, indexing, slicing, concatenation, and searching.

Lesson 10: Diving Deeper into Data Structures: Dictionaries

• Working with dictionaries: creating, retrieving items, using methods like keys(), get(), and pop(), updating, duplicating, and clearing.

Lesson 11: Diving Deeper into Data Structures: Sets

• Set operations, adding/removing items, uniqueness, length, intersection, union, and differences between sets.

Lesson 12: Pulling It All Together: Prompting for an Address

• Creating a program that prompts the user for an address, processes input, and displays the output with modifications.

PART III: Object-Oriented Programming in Python

Lesson 14: Incorporating Object-Oriented Programming

• Introduction to OOP concepts: defining classes, creating objects, methods, and class attributes.

Lesson 15: Including Inheritance

• Understanding inheritance, creating parent and child classes, overriding methods, and multiple levels of inheritance.

Lesson 16: Pulling It All Together: Building a Burger Shop

• Building a project using OOP to model a burger shop, including requirements gathering, class creation, and tying everything together.

PART IV: Data Processing with Python

Lesson 17: Working with Dates and Times

• Handling dates and times, using datetime, formatting, comparing, and performing arithmetic with dates and times.

Lesson 18: Processing Text Files

• File I/O, reading and writing to text files, creating, deleting, and overwriting files, using the  module.

Lesson 19: Processing CSV Files

• Working with CSV files: reading, writing, appending, using DictReader, and writerow().

Lesson 20: Processing JSON Files

• Handling JSON data: reading, writing, and iterating over JSON files, using json library methods like dumps(), loads(), and dump().

PART V: Data Analysis and Exception Handling

Lesson 21: Using Lambdas

• Creating and using lambda functions, applying them in map(), filter(), and reduce() functions.

Lesson 22: Handling Exceptions

• Working with exception handling using try/except, raising exceptions, and using finally for cleanup.

Lesson 23: Pulling It All Together: Word Analysis in Python

• Reading and processing text data, tokenizing, and counting words in text for basic word analysis.

Lesson 24: Extracting, Transforming, and Loading with ETL Scripting

• Introduction to ETL (Extract, Transform, Load), designing custom ETL scripts, and creating the Extract, Transform, and Load classes.

Lesson 25: Improving ETL Scripting

• Improving ETL scripting by converting methods into static methods and improving code structure.

PART VI: Appendices

Appendix A: Flowcharts

• Basics of flowcharting and common flowcharting shapes.

Appendix B: Creating Pseudocode

• Introduction to pseudocode and how to write it for program planning.

Appendix C: Installing MySQL

• Installation and verification of MySQL for database handling in Python.

Appendix D: Installing Vinyl DB

• Installing and setting up Vinyl DB for working with databases.

Appendix E: Installing MongoDB

• Installation steps for MongoDB, including setting up the community server.

Appendix F: Importing to MongoDB

• Working with data in MongoDB and how to import data into it.

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Haythem Balti,Kimberly Weiss,Job Ready