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Job Ready Python de Haythem Balti

Job Ready Python

Autor Haythem Balti
en Limba Engleză Paperback – 5 noi 2021

Metodologia acestui volum se concentrează pe transformarea cunoștințelor teoretice în competențe tehnice direct aplicabile în mediul profesional. Reținem că Job Ready Python nu este doar un manual introductiv, ci un ghid de tranziție către o carieră în software, fiind structurat pe pilonii fundamentali ai dezvoltării moderne: arhitectură curată, manipularea datelor și integrarea sistemelor. Încă din primele capitole, remarcăm o atenție deosebită acordată mediului de lucru, oferind instrucțiuni pas cu pas pentru configurarea Visual Studio Code și Jupyter Notebook, asigurând o bază solidă pentru orice proiect viitor. Pe linia practică a volumului Python Programming de Vijay Kumar Sharma, dar cu un focus mult mai pronunțat pe cerințele specifice ale pieței muncii, această lucrare explorează în profunzime scriptarea ETL (Extract, Transform, Load). Este o diferențiere esențială față de alte cursuri, deoarece pregătește cititorul pentru gestionarea fluxurilor de date reale folosind MySQL și MongoDB. În continuarea abordării pragmatice demonstrate în lucrarea anterioară a lui Haythem Balti, Job Ready Go, autorul menține un echilibru între claritatea sintaxei Python și complexitatea structurilor de date precum JSON și CSV. Organizarea cărții urmează o progresie logică, de la fundamentele variabilelor și buclelor, până la conceptele avansate de programare orientată pe obiecte. Această structură este concepută pentru a construi încrederea tehnică necesară unui dezvoltator junior, punând accent pe rezolvarea problemelor prin exerciții aplicate, eliminând jargonul inutil în favoarea eficienței în execuție.

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Specificații

ISBN-13: 9781119817383
ISBN-10: 1119817382
Pagini: 688
Dimensiuni: 189 x 234 x 37 mm
Greutate: 1.18 kg
Editura: Wiley
Locul publicării:Hoboken, United States

De ce să citești această carte

Recomandăm această carte celor care doresc o reconversie profesională rapidă și eficientă. Spre deosebire de manualele pur teoretice, acest volum vă oferă un set de competențe gata de utilizat la interviurile de angajare: de la gestionarea bazelor de date SQL și NoSQL, până la automatizarea proceselor de date. Câștigați astfel nu doar cunoștințe de sintaxă, ci o înțelegere clară a modului în care Python este utilizat în industria tech actuală.

Despre autor

Haythem Balti este un expert în educație software, cunoscut pentru rolul său în cadrul mthree Global Academy și Software Guild. Experiența sa se concentrează pe crearea de programe de instruire care reduc decalajul dintre mediul academic și cerințele industriei IT. Stilul său pedagogic este caracterizat prin pragmatism și claritate, abordare pe care a aplicat-o cu succes și în alte lucrări din serie, precum Job Ready Go. Alături de Kimberly A Weiss, acesta dezvoltă resurse educaționale care pun accent pe limbaje de programare moderne și pe eficiența fluxurilor de lucru în dezvoltarea software.

Descriere scurtă

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.

Notă biografică

HAYTHEM BALTI, PhD, is the associate dean at Wiley's mthree academy. He has created courses used by thousands of Software Guild and mthree alumni to learn Go, Java, Python, and other development and data science skills. KIMBERLY A. WEISS is a veteran course developer, specializing in Computer Science courses since 2002. She was an assistant professor in Computer Science for over ten years before deciding to focus exclusively on course design. She has worked with multiple universities as well as corporate training settings to develop interactive instructional content appropriate for the target learners and course goals.

Cuprins

About the Authors v About the Technical Writer v About the Technical Editor v Acknowledgments vi Introduction xvii Part I: Getting Started with Python 1 Lesson 1: Setting Up a Python Programming Environment 3 Python Overview 4 Using Replit Online 4 Creating a Replit Account 5 Creating a Python Program in Replit 7 Running a Python Program in Replit 9 Other Replit Tasks 11 Renaming Your Code File 11 Saving Your Coding File Locally 12 Creating a New File for Your Python Project 12 Adding Files to Your Python Project 13 Returning to Replit 13 Getting More Help for Replit 14 Getting Started with Jupyter Notebook 14 Installing Anaconda Jupyter Notebook 15 Creating a New Jupyter Notebook File 16 Renaming a Jupyter Notebook Project File 18 Saving a Python File Locally 19 Opening an Existing Jupyter Notebook File 20 A Quick Look at Visual Studio Code 21 Obtaining Visual Studio Code 21 Adding the Python Extension to Visual Studio Code 22 Using Python from the Command Line 24 Summary 26 Exercises 26 Exercise 1: Say Hello 27 Exercise 2: What's It Do? 27 Exercise 3: Counting 27 Exercise 4: Fruity Code 28 Lesson 2: Understanding Programming Basics 29 The Future of Computer Programming 30 What Is Programming? 30 What Is a Program? 30 Computational Thinking 31 Programming Languages 32 Common Components 33 Statements 33 Syntax 33 Reserved Words 34 Operators 35 Hello, World! 36 Data Types and Variables 37 Data Types 37 Text 38 Numbers 38 True/False 39 Date/Time 39 Data Collections 39 Variables 40 Reserving Memory 42 Variables and Data Types 43 Constants 44 Example 1: Area of a Circle 44 Example 2: Tax Rate 45 Example 3: Output Messages 45 Summary 46 Exercises 46 Exercise 1: Daily Tasks 47 Exercise 2: Python Programming 47 Lesson 3: Exploring Basic Python Syntax 49 Using with Single-Line Commands 51 Using Semicolons 52 Continuing with Backslash 54 Working with Case Structure 55 Adding Comments 56 Using the Input Function 57 Storing Input 59 Understanding Variable Types 61 Displaying Variable Values 62 Naming Variables 64 Summary 65 Exercises 65 Exercise 1: Displaying Text 66 Exercise 2: Follow the Comments 66 Exercise 3: Fixing the Code 66 Exercise 4: Broken Variables 67 Exercise 5: Broken Names 67 Exercise 6: Where Are You? 67 Lesson 4: Working with Basic Python Data Types 69 Review of Data Types 70 Number Data Types 70 Identifying Data Types 72 Mathematical Operations 74 PEMDAS 77 Common Math Functions 81 Math Library Functions 83 Using Numbers with User Input 86 Boolean Types and Boolean Operations 89 Convert to Boolean 90 Logic Operations 92 Comparative Operators 95 Summary 96 Exercises 97 Exercise 1: Prompting the User 97 Exercise 2: Manipulated Math 97 Exercise 3: Integers Only 98 Exercise 4: Current Value 98 Exercise 5: Simple Interest 98 Exercise 6: True or False 99 Exercise 7: Playing with Numbers 99 Exercise 8: Do the Math 99 Exercise 9: Street Addresses 100 Lesson 5: Using Python Control Statements 101 Control Structures Review 101 Understanding Sequence Control Structure 102 Understanding Selection Statements 103 Understanding Conditional Statements 106 If-Else Statements 108 Working with Nested Conditions 109 Embedding Conditions 112 Summary 114 Exercises 114 Exercise 1: Are You Rich? 115 Exercise 2: Cats or Dogs 115 Exercise 3: True or False Quiz 115 Exercise 4: For Every Season... 115 Exercise 5: Company Picnic 116 Lesson 6: Pulling It All Together: Income Tax Calculator 117 Getting Started 118 Step 1: Gather Requirements 118 Values in Use 119 User Interface 119 Other Standards 120 Step 2: Design the Program 120 Step 3: Create the Inputs 120 Step 4: Calculate the Taxable Income 122 Step 5: Calculate the Tax Rate 124 Add a Conditional Statement 125 Create Nested Conditionals 127 Step 6: Update the Application 133 What About Negative Taxable Incomes? 134 Does Code Compare to Standards? 136 Step 7: Address the UI 136 On Your Own 139 Summary 139 Part II: Loops and Data Structures 141 Lesson 7: Controlling Program Flow with Loops 143 Iterations Overview 144 The Anatomy of a Loop 144 The for Loop 145 The while Loop 146 Unexecutable while Loop 148 for vs. while Loops 149 Strings and String Operations 151 Determining the Length of a String 152 Splitting a String 153 Storing Characters 154 Comparison Operators in Strings 155 Concatenating Strings 158 Slicing Strings 159 Searching Strings 163 Iterating through Strings 164 Summary 167 Exercises 167 Exercise 1: Separating Your Fruits 168 Exercise 2: Keeping It Short 168 Exercise 3: Fruit Finder 168 Exercise 4: It's Divisible 169 Exercise 5: Identify the Numbers 169 Exercise 6: And the Total Is... 169 Exercise 7: Multiplication Tables 169 Exercise 8: Sum of Prime Numbers 169 Exercise 9: One Letter at a Time 170 Exercise 10: Length without len() 170 Exercise 11: Count the Numbers 170 Exercise 12: Fizz Buzz 170 Lesson 8: Understanding Basic Data Structures: Lists 173 Data Structure Overview--Part 1 174 Creating Lists 175 Determining List Length 179 Working with List Indexes 179 Negative Indexing in Lists 182 Slicing Lists 184 Using the Slice Object 187 Adding Items to a List 189 Inserting List Items 190 Removing List Items 192 Deleting versus Removing Items 194 Popping Instead of Removing 195 Concatenating Lists 196 List Comprehension 197 Sorting Lists 199 Copying Lists 200 Summary 202 Exercises 202 Exercise 1: All About You 203 Exercise 2: Shopping List 203 Exercise 3: List Deletion 203 Exercise 4: List Modification 203 Exercise 5: A Complete List Program 203 Lesson 9: Understanding Basic Data Structures: Tuples 205 Tuples and Tuple Operations 206 Syntax of Tuples vs. Syntax of Lists 206 Tuple Length 208 Tuple Index Values 209 Negative Indexing in Tuples 210 Slicing Tuples 212 Immutability 213 Concatenating Tuples 216 Searching Tuples 217 Summary 218 Exercises 219 Exercise 1: Creating Tuples 219 Exercise 2: Modifying Tuples 219 Exercise 3: Where's Waldo? 220 Exercise 4: A Complete Tuple Program 220 Lesson 10: Diving Deeper into Data Structures: Dictionaries 223 Data Structure Overview--Part 2 224 Getting Started with Dictionaries 224 Generating a Dictionary 227 Retrieving Items from a Dictionary 230 Using the keys() Method 233 Using the items() Method 234 Reviewing the keys(), values(), and items() Methods 236 Using the get() Method 239 Using the pop() Method 241 Working with the in Operator 245 Updating a Dictionary 246 Duplicating a Dictionary 249 Clearing a Dictionary 254 Summary 255 Exercises 255 Exercise 1: Working with Text 256 Exercise 2: Separating the High from the Low 256 Exercise 3: High and Low All in One 257 Exercise 4: Self-Assessment 257 Lesson 11: Diving Deeper into Data Structures: Sets 259 Sets 260 Retrieving Items from a Set 261 Adding Items to a Set 262 Creating an Empty Set 262 Understanding Set Uniqueness 263 Searching Items in a Set 265 Calculating the Length of a Set 267 Deleting Items from a Set 268 Clearing a Set 270 Popping Items in a Set 272 Deleting a Set 273 Determining the Difference Between Sets 274 Intersecting Sets 277 Combining Sets 278 Summary 279 Exercises 279 Exercise 1: Line by Line 280 Exercise 2: Adding New Names 280 Exercise 3: Popping Accounts 280 Exercise 4: Everywhere That Mary Went... 280 Exercise 5: Self-Assessment 281 Lesson 12: Pulling It All Together: Prompting for an Address 283 Step 1: Getting Started 284 Step 2: Accept User Input 285 Step 3: Display the Input Value 286 Step 4: Modify the Output 287 Step 5: Split a Text Value 288 Step 6: Display Only the House Number 290 Step 7: Display the Street Name 291 Step 8: Add the Period 292 Summary 293 Lesson 13: Organizing with Functions 295 Functions Overview 295 Defining Functions in Python 296 Function Syntax 300 Default Input Values 301 Parameter Syntax 303 Arbitrary Arguments 304 Keyword Arguments 306 Arbitrary Keyword Arguments 306 Summary 308 Exercises 309 Exercise 1: Lower Numbers 309 Exercise 2: This Will Be 309 Exercise 3: Finding the Largest 310 Exercise 4: Simple Calculator 310 Exercise 5: Which Is Greater? 310 Part III: Object-Oriented Programming in Python 311 Lesson 14: Incorporating Object-Oriented Programming 313 Object-Oriented Programming Overview 314 Defining Classes 314 Attributes 315 Methods 316 Creating Objects 316 Working with Methods 319 Class Attributes 324 Working with Static Methods 326 Working with Class Methods 328 Summary 330 Exercises 330 Exercise 1: Create Your Own Class 331 Exercise 2: Classy Vehicles 331 Exercise 3: Streamlined Banking 331 Exercise 4: Using a Calculator in Class 331 Lesson 15: Including Inheritance 333 Understanding Inheritance 334 Creating a Parent Class 335 Creating a Child Class 335 Inheriting at Multiple Levels 338 Overriding Methods 340 Summary 343 Exercises 344 Exercise 1: Basic Inheritance 344 Exercise 2: Adding Attributes 344 Exercise 3: Creating More Children 345 Exercise 4: Dogs and Cats 345 Exercise 5: Hourly Employees 345 Exercise 6: File System 347 Lesson 16: Pulling It All Together: Building a Burger Shop 349 Requirements for Our Application 350 Plan the Code 350 Create the Classes 351 Create the Food Item Class 352 Create a Burger Class 353 Create a Drink Class 354 Create a Side Class 354 Create a Combo 355 Create the Order Class 356 Create the Main File 357 Create order once 358 Order a Burger 359 Add a Drink 360 Add Sides 362 Order a Combo 363 Display the Output 364 Tie the Code Files Together 364 Summary 368 Part IV: Data Processing with Python 369 Lesson 17: Working with Dates and Times 371 Getting Started with Dates and Times 372 Creating a Variable for a Date 372 Creating a Variable for Time 375 Creating a Variable for Both Date and Time 375 Getting the Current Date and Time 376 Splitting a Date String 377 Using datetime Attributes 379 Creating Custom datetime Objects 380 Compare datetime Values 381 Working with UTC Format 383 Applying Timestamps 384 Arithmetic and Dates 387 Calculating the Difference in Days 388 Using Date without Time 390 Using Time without Date 392 Summary 394 Exercises 394 Exercise 1: Displaying Dates 394 Exercise 2: Leap Years 395 Exercise 3: The Past 395 Exercise 4: Unix Dates 395 Exercise 5: Yesterday, Today, and Tomorrow 395 Exercise 6: Setting Future Days 395 Exercise 7: Five Seconds in the Future 395 Exercise 8: Date Calculators 396 Calculator 1: Time Duration 396 Calculator 2: Add or Subtract Time from a Date 397 Calculator 3: Age Calculator 397 Lesson 18: Processing Text Files 399 File Processing Overview 401 Introduction to File Input/Output 402 The input() Function 402 The open() Function 402 The read() Method 403 The write() Method 403 The close() Method 403 The print() Function 403 Processing Text Files 404 Opening a File 404 Reading Text from a File 406 Use the read() Method to Limit the Content 406 Reading Lines 408 Iterating through a File 410 Add Content to a File 412 Overwriting the Contents of a File 415 Creating a New File 417 Using the os Module 418 Deleting a File 419 Summary 421 Exercises 421 Exercise 1: Reading Lines 422 Exercise 2: Combination of the Two 422 Exercise 3: Combination of Them All 422 Exercise 4: Listing Lines 422 Exercise 5: Longest Word 422 Exercise 6: Listing Text 423 Exercise 7: Text in Reverse 423 Lesson 19: Processing CSV Files 425 Reading CSV Files 426 Using the DictReader Class 430 Creating a Dataset List 432 Using writerow() 434 Appending Data 436 Writing Rows as Lists 439 Writing Rows from Dictionaries 440 Summary 444 Exercises 444 Exercise 1: Reading Lines 444 Exercise 2: Company Stocks 444 Exercise 3: Rearranging Files 445 Exercise 4: Pop Music Evolution 445 Exercise 5: All About Cars 446 Lesson 20: Processing JSON Files 447 Processing JSON Files 448 Creating a JSON File with dump() 448 Converting to JSON with dumps() 449 Formatting JSON Data 450 Using json.loads() 452 Iterating through JSON Data 454 Reading and Writing JSON Data 457 Summary 460 Exercises 461 Exercise 1: Company Bank Account 461 Exercise 2: Formatted Account Information 461 Exercise 3: Nobel Prizes 461 Exercise 4: New York Restaurants 462 Exercise 5: Movies 463 Part V: Data Analysis and Exception Handling 465 Lesson 21: Using Lambdas 467 Creating a Lambda Function 468 Working with Multiple Inputs 469 Placing Lambda Functions inside a Function 471 Using the map() Function 472 Combining Map and Lambda Functions 475 Using the filter() Function 477 Combining a Filter and a Lambda 479 Using the reduce() Function 480 Specify an Initial Value 482 Using reduce() with Comparison Operations 484 Summary 486 Exercises 486 Exercise 1: Computing the Square Root 487 Exercise 2: Converting a Text File to Uppercase 487 Exercise 3: Determining Prime 487 Exercise 4: Identifying Absolute Value 487 Exercise 5: Highest Number 487 Exercise 6: Lowest Number 487 Exercise 7: Last Key 487 Exercise 8: Highest Value 488 Exercise 9: Sum of Even 488 Exercise 10: Sum of Positive Numbers 488 Exercise 11: Highest Stock Market Volume 488 Exercise 12: Bad Stock Market Day 488 Exercise 13: Highest Opening Price 488 Exercise 14: Highest Price at Closing 489 Exercise 15: Self-Assessment 489 Lesson 22: Handling Exceptions 491 Built-In Exceptions 492 Working with try and except 493 Working with Multiple Excepts 495 Combining Exception Types 498 Using Multiple Operations in a try 500 Using the raise Keyword 501 Exploring the General Exception Classes 502 Adding finally 505 Summary 506 Exercises 506 Exercise 1: Typing Numbers 507 Exercise 2: Current Value 507 Exercise 3: Reading Lines 508 Exercise 4: Concatenating Files 508 Exercise 5: Creating a List from a File 508 Exercise 6: Self-Assessment 508 Lesson 23: Pulling It All Together: Word Analysis in Python 511 Examine the Data 512 Read the Data 514 Tokenize the Dataset 517 Tokenize an Input String 518 Tokenize an Input Review 521 Tokenize the Entire Dataset 522 Using the Tokenize Functions 523 Count the Words in Each Review 524 Word Count for an Input List of Words 524 Word Count an Input Review 525 Word Count for the Dataset 526 Summary 528 Lesson 24: Extracting, Transforming, and Loading with ETL Scripting 531 ETL Scripting in Python 532 Design and Implement Custom ETL Scripts 532 The extract Class 534 Adding the extract.fromCSV Method 534 Creating the extract.fromJSON Method 536 Creating the extract.fromMySQL Method 538 Creating the extract.fromMongoDB Method 542 Verify the extract.py Module 544 Using Our Script as an External Module 545 The transform Class 546 Defining the transform Class 546 Creating the head and tail Methods 547 Renaming a Column 551 Removing a Column from the Data Source 552 Renaming Multiple Columns 556 Removing Multiple Columns 558 Transforming the Data 563 The load Class 569 Creating the load.toCSV Method 570 Creating the load.toJSON Method 572 Creating the load.toMYSQL Method 574 Creating the Load.toMONGODB Method 578 Summary 582 Exercises 582 Exercise 1: Transforming CSV to CSV 583 Exercise 2: Transforming CSV to JSON 583 Exercise 3: Transforming JSON to CSV 583 Exercise 4: Transforming JSON to JSON 583 Exercise 5: Removing an Attribute 583 Exercise 6: Renaming an Attribute 583 Exercise 7: Confirming an Attribute 584 Lesson 25: Improving ETL Scripting 585 Converting to Static Methods for the extract Class 586 Converting to Static Methods for the transform Class 588 Converting to Static Methods for the load Class 592 Adding Exception Handling in the extract Class 594 Creating a Custom Extractor for the extract Class 601 Summary 607 Exercises 608 Exercise 1: Revisiting Lessons Learned 608 Exercise 2: Day of Week 608 Exercise 3: Date Validity 609 Exercise 4: Listing Duplicates 609 Exercise 5: Removing Duplicates 609 Exercise 6: Transforming Names 609 Part VI: Appendices 611 Appendix A: Flowcharts 613 Flowchart Basics 613 Sequences 613 Branches 614 Loops 615 Common Flowcharting Shapes 615 Flowcharting Example 616 Additional Flowchart Elements 618 Appendix B: Creating Pseudocode 621 What Is Pseudocode? 621 Appendix C: Installing MySQL 623 MySQL Installation 623 Download and Install MySQL 623 Configure MySQL 624 Configure MySQL Router Options 626 Configure Samples and Examples 627 Verify the Installation 628 The MySQL Notifier 630 Appendix D: Installing Vinyl DB 631 Database Structure 631 Create the Database 632 Appendix E: Installing MongoDB 637 Installing MongoDB Community Server 637 Running MongoDB 642 Appendix F: Importing to MongoDB 643 Index 645