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

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Product details:
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 Edition Table of contents:

PART I: Getting Started with Python

Lesson 1: Setting Up a Python Programming Environment

PYTHON OVERVIEW

USING REPLIT ONLINE

GETTING STARTED WITH JUPYTER NOTEBOOK

A QUICK LOOK AT VISUAL STUDIO CODE

USING PYTHON FROM THE COMMAND LINE

SUMMARY

EXERCISES

Lesson 2: Understanding Programming Basics

THE FUTURE OF COMPUTER PROGRAMMING

PROGRAMMING LANGUAGES

DATA TYPES AND VARIABLES

SUMMARY

EXERCISES

Lesson 3: Exploring Basic Python Syntax

USING WITH SINGLE-LINE COMMANDS

USING SEMICOLONS

CONTINUING WITH BACKSLASH

WORKING WITH CASE STRUCTURE

ADDING COMMENTS

USING THE INPUT FUNCTION

STORING INPUT

UNDERSTANDING VARIABLE TYPES

DISPLAYING VARIABLE VALUES

NAMING VARIABLES

SUMMARY

EXERCISES

Lesson 4: Working with Basic Python Data Types

REVIEW OF DATA TYPES

NUMBER DATA TYPES

IDENTIFYING DATA TYPES

MATHEMATICAL OPERATIONS

PEMDAS

COMMON MATH FUNCTIONS

MATH LIBRARY FUNCTIONS

USING NUMBERS WITH USER INPUT

BOOLEAN TYPES AND BOOLEAN OPERATIONS

LOGIC OPERATIONS

COMPARATIVE OPERATORS

SUMMARY

EXERCISES

Lesson 5: Using Python Control Statements

CONTROL STRUCTURES REVIEW

UNDERSTANDING SEQUENCE CONTROL STRUCTURE

UNDERSTANDING SELECTION STATEMENTS

UNDERSTANDING CONDITIONAL STATEMENTS

IF-ELSE STATEMENTS

WORKING WITH NESTED CONDITIONS

EMBEDDING CONDITIONS

SUMMARY

EXERCISES

Lesson 6: Pulling It All Together: Income Tax Calculator

GETTING STARTED

STEP 1: GATHER REQUIREMENTS

STEP 2: DESIGN THE PROGRAM

STEP 3: CREATE THE INPUTS

STEP 4: CALCULATE THE TAXABLE INCOME

STEP 5: CALCULATE THE TAX RATE

STEP 6: UPDATE THE APPLICATION

STEP 7: ADDRESS THE UI

ON YOUR OWN

SUMMARY

PART II: Loops and Data Structures

Lesson 7: Controlling Program Flow with Loops

ITERATIONS OVERVIEW

THE ANATOMY OF A LOOP

THE FOR LOOP

THE WHILE LOOP

FOR VS. WHILE LOOPS

STRINGS AND STRING OPERATIONS

ITERATING THROUGH STRINGS

SUMMARY

EXERCISES

Lesson 8: Understanding Basic Data Structures: Lists

DATA STRUCTURE OVERVIEW—PART 1

CREATING LISTS

DETERMINING LIST LENGTH

WORKING WITH LIST INDEXES

NEGATIVE INDEXING IN LISTS

SLICING LISTS

ADDING ITEMS TO A LIST

INSERTING LIST ITEMS

REMOVING LIST ITEMS

CONCATENATING LISTS

LIST COMPREHENSION

SORTING LISTS

COPYING LISTS

SUMMARY

EXERCISES

Lesson 9: Understanding Basic Data Structures: Tuples

TUPLES AND TUPLE OPERATIONS

TUPLE INDEX VALUES

NEGATIVE INDEXING IN TUPLES

SLICING TUPLES

IMMUTABILITY

CONCATENATING TUPLES

SEARCHING TUPLES

SUMMARY

EXERCISES

Lesson 10: Diving Deeper into Data Structures: Dictionaries

DATA STRUCTURE OVERVIEW—PART 2

GETTING STARTED WITH DICTIONARIES

GENERATING A DICTIONARY

RETRIEVING ITEMS FROM A DICTIONARY

USING THE KEYS() METHOD

USING THE ITEMS() METHOD

REVIEWING THE KEYS(), VALUES(), AND ITEMS() METHODS

USING THE GET() METHOD

USING THE POP() METHOD

WORKING WITH THE IN OPERATOR

UPDATING A DICTIONARY

DUPLICATING A DICTIONARY

CLEARING A DICTIONARY

SUMMARY

EXERCISES

Lesson 11: Diving Deeper into Data Structures: Sets

SETS

RETRIEVING ITEMS FROM A SET

ADDING ITEMS TO A SET

CREATING AN EMPTY SET

UNDERSTANDING SET UNIQUENESS

SEARCHING ITEMS IN A SET

CALCULATING THE LENGTH OF A SET

DELETING ITEMS FROM A SET

CLEARING A SET

POPPING ITEMS IN A SET

DELETING A SET

DETERMINING THE DIFFERENCE BETWEEN SETS

INTERSECTING SETS

COMBINING SETS

SUMMARY

EXERCISES

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

STEP 1: GETTING STARTED

STEP 2: ACCEPT USER INPUT

STEP 3: DISPLAY THE INPUT VALUE

STEP 4: MODIFY THE OUTPUT

STEP 5: SPLIT A TEXT VALUE

STEP 6: DISPLAY ONLY THE HOUSE NUMBER

STEP 7: DISPLAY THE STREET NAME

STEP 8: ADD THE PERIOD

SUMMARY

Lesson 13: Organizing with Functions

FUNCTIONS OVERVIEW

DEFINING FUNCTIONS IN PYTHON

FUNCTION SYNTAX

DEFAULT INPUT VALUES

PARAMETER SYNTAX

ARBITRARY ARGUMENTS

KEYWORD ARGUMENTS

ARBITRARY KEYWORD ARGUMENTS

SUMMARY

EXERCISES

PART III: Object-Oriented Programming in Python

Lesson 14: Incorporating Object-Oriented Programming

OBJECT-ORIENTED PROGRAMMING OVERVIEW

DEFINING CLASSES

CREATING OBJECTS

WORKING WITH METHODS

CLASS ATTRIBUTES

SUMMARY

EXERCISES

Lesson 15: Including Inheritance

UNDERSTANDING INHERITANCE

CREATING A PARENT CLASS

CREATING A CHILD CLASS

INHERITING AT MULTIPLE LEVELS

OVERRIDING METHODS

SUMMARY

EXERCISES

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

REQUIREMENTS FOR OUR APPLICATION

PLAN THE CODE

CREATE THE CLASSES

CREATE THE FOOD ITEM CLASS

CREATE THE MAIN FILE

DISPLAY THE OUTPUT

TIE THE CODE FILES TOGETHER

SUMMARY

PART IV: Data Processing with Python

Lesson 17: Working with Dates and Times

GETTING STARTED WITH DATES AND TIMES

GETTING THE CURRENT DATE AND TIME

SPLITTING A DATE STRING

USING DATETIME ATTRIBUTES

CREATING CUSTOM DATETIME OBJECTS

COMPARE DATETIME VALUES

WORKING WITH UTC FORMAT

APPLYING TIMESTAMPS

ARITHMETIC AND DATES

CALCULATING THE DIFFERENCE IN DAYS

USING DATE WITHOUT TIME

USING TIME WITHOUT DATE

SUMMARY

EXERCISES

Lesson 18: Processing Text Files

FILE PROCESSING OVERVIEW

INTRODUCTION TO FILE INPUT/OUTPUT

PROCESSING TEXT FILES

OPENING A FILE

READING TEXT FROM A FILE

ADD CONTENT TO A FILE

OVERWRITING THE CONTENTS OF A FILE

CREATING A NEW FILE

USING THE OS MODULE

DELETING A FILE

SUMMARY

EXERCISES

Lesson 19: Processing CSV Files

READING CSV FILES

USING THE DICTREADER CLASS

CREATING A DATASET LIST

USING WRITEROW()

APPENDING DATA

WRITING ROWS AS LISTS

WRITING ROWS FROM DICTIONARIES

SUMMARY

EXERCISES

Lesson 20: Processing JSON Files

PROCESSING JSON FILES

CREATING A JSON FILE WITH DUMP()

CONVERTING TO JSON WITH DUMPS()

FORMATTING JSON DATA

USING JSON.LOADS()

ITERATING THROUGH JSON DATA

READING AND WRITING JSON DATA

SUMMARY

EXERCISES

PART V: Data Analysis and Exception Handling

Lesson 21: Using Lambdas

CREATING A LAMBDA FUNCTION

WORKING WITH MULTIPLE INPUTS

PLACING LAMBDA FUNCTIONS INSIDE A FUNCTION

USING THE MAP() FUNCTION

COMBINING MAP AND LAMBDA FUNCTIONS

USING THE FILTER() FUNCTION

COMBINING A FILTER AND A LAMBDA

USING THE REDUCE() FUNCTION

SUMMARY

EXERCISES

Lesson 22: Handling Exceptions

BUILT-IN EXCEPTIONS

WORKING WITH TRY AND EXCEPT

WORKING WITH MULTIPLE EXCEPTS

COMBINING EXCEPTION TYPES

USING MULTIPLE OPERATIONS IN A TRY

USING THE RAISE KEYWORD

EXPLORING THE GENERAL EXCEPTION CLASSES

ADDING FINALLY

SUMMARY

EXERCISES

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

EXAMINE THE DATA

READ THE DATA

TOKENIZE THE DATASET

COUNT THE WORDS IN EACH REVIEW

SUMMARY

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

ETL SCRIPTING IN PYTHON

DESIGN AND IMPLEMENT CUSTOM ETL SCRIPTS

THE EXTRACT CLASS

THE TRANSFORM CLASS

THE LOAD CLASS

SUMMARY

EXERCISES

Lesson 25: Improving ETL Scripting

CONVERTING TO STATIC METHODS FOR THE EXTRACT CLASS

CONVERTING TO STATIC METHODS FOR THE TRANSFORM CLASS

SUMMARY

EXERCISES

PART VI: Appendices

Appendix A: Flowcharts

FLOWCHART BASICS

COMMON FLOWCHARTING SHAPES

Appendix B: Creating Pseudocode

WHAT IS PSEUDOCODE?

Appendix C: Installing MySQL

MySQL INSTALLATION

VERIFY THE INSTALLATION

THE MySQL NOTIFIER

Appendix D: Installing Vinyl DB

DATABASE STRUCTURE

CREATE THE DATABASE

Appendix E: Installing MongoDB

INSTALLING MongoDB COMMUNITY SERVER

RUNNING MongoDB

Appendix F: Importing to MongoDB

Index

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Tags: Haythem Balti, Kimberly A Weiss, Job Ready, Python