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از ساعت 7 صبح تا 10 شب
ویرایش: [1 ed.]
نویسندگان: Haythem Balti. Kimberly A. Weiss
سری:
ISBN (شابک) : 1119817382, 9781119817383
ناشر: Wiley
سال نشر: 2021
تعداد صفحات: 688
زبان: English
فرمت فایل : EPUB (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 17 Mb
در صورت تبدیل فایل کتاب Job Ready Python به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب پایتون آماده کار نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
با یک راهنمای عملی و متمرکز بر کار، آماده باشید تا پایتون را به کار بگیرید. Job Ready Python به خوانندگان رویکردی ساده و ظریف برای یادگیری پایتون ارائه میکند که بر مهارتهای عملی و قابل استفاده تأکید دارد که میتوانید بلافاصله در محیطهای دنیای واقعی اعمال کنید. این کتاب بر اساس برنامه آموزشی معروف mthree Global Academy و انجمن نرم افزاری، شما را در اصول اولیه پایتون، حلقه ها و ساختارهای داده، برنامه نویسی شی گرا و پردازش داده ها به سرعت آشنا می کند. همچنین دریافت خواهید کرد: بحث های کامل در مورد استخراج، تبدیل، و بارگذاری (ETL) اسکریپت نویسی در پایتون کاوش در پایگاه های داده، از جمله MySQL، و MongoDB - همه پلت فرم های پایگاه داده رایج در زمینه روش های ساده و گام به گام برای مقابله با تاریخها و زمانها، فایلهای CSV و فایلهای JSON ایدهآل برای مبتدیان پایتون که به دنبال انتقال به یک حرفه جدید هیجانانگیز هستند، Python آماده کار نیز در قفسه کتابهای توسعهدهندگان پایتون قرار دارد که امیدوارند با یک کتابچه راهنمای جدید معتبر و کاربردی، اصول اولیه را بررسی کنند. .
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.
Cover Title Page Copyright Page About the Authors About the Technical Writer About the Technical Editor Acknowledgments Contents Introduction What Does This Book Cover? Reader Support for This Book Part 1 Getting Started with Python Lesson 1 Setting Up a Python Programming Environment Python Overview Using Replit Online Creating a Replit Account Creating a Python Program in Replit Running a Python Program in Replit Other Replit Tasks Renaming Your Code File Saving Your Coding File Locally Creating a New File for Your Python Project Adding Files to Your Python Project Returning to Replit Getting More Help for Replit Getting Started with Jupyter Notebook Installing Anaconda Jupyter Notebook Creating a New Jupyter Notebook File Renaming a Jupyter Notebook Project File Saving a Python File Locally Opening an Existing Jupyter Notebook File A Quick Look at Visual Studio Code Obtaining Visual Studio Code Adding the Python Extension to Visual Studio Code Using Python from the Command Line Summary Exercises Exercise 1: Say Hello Exercise 2: What’s It Do? Exercise 3: Counting Exercise 4: Fruity Code Lesson 2 Understanding Programming Basics The Future of Computer Programming What Is Programming? What Is a Program? Computational Thinking Programming Languages Common Components Statements Syntax Reserved Words Operators Hello, World! Data Types and Variables Data Types Text Numbers True/False Date/Time Data Collections Variables Reserving Memory Variables and Data Types Constants Example 1: Area of a Circle Example 2: Tax Rate Example 3: Output Messages Summary Exercises Exercise 1: Daily Tasks Exercise 2: Python Programming 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 Exercise 1: Displaying Text Exercise 2: Follow the Comments Exercise 3: Fixing the Code Exercise 4: Broken Variables Exercise 5: Broken Names Exercise 6: Where Are You? 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 Convert to Boolean Logic Operations Comparative Operators Summary Exercises Exercise 1: Prompting the User Exercise 2: Manipulated Math Exercise 3: Integers Only Exercise 4: Current Value Exercise 5: Simple Interest Exercise 6: True or False Exercise 7: Playing with Numbers Exercise 8: Do the Math Exercise 9: Street Addresses 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 Exercise 1: Are You Rich? Exercise 2: Cats or Dogs Exercise 3: True or False Quiz Exercise 4: For Every Season… Exercise 5: Company Picnic Lesson 6 Pulling It All Together: Income Tax Calculator Getting Started Step 1: Gather Requirements Values in Use User Interface Other Standards Step 2: Design the Program Step 3: Create the Inputs Step 4: Calculate the Taxable Income Step 5: Calculate the Tax Rate Add a Conditional Statement Create Nested Conditionals Step 6: Update the Application What About Negative Taxable Incomes? Does Code Compare to Standards? Step 7: Address the UI On Your Own Summary Part 2 Loops and Data Structures Lesson 7 Controlling Program Flow with Loops Iterations Overview The Anatomy of a Loop The for Loop The while Loop Unexecutable while Loop for vs. while Loops Strings and String Operations Determining the Length of a String Splitting a String Storing Characters Comparison Operators in Strings Concatenating Strings Slicing Strings Searching Strings Iterating through Strings Summary Exercises Exercise 1: Separating Your Fruits Exercise 2: Keeping It Short Exercise 3: Fruit Finder Exercise 4: It’s Divisible Exercise 5: Identify the Numbers Exercise 6: And the Total Is… Exercise 7: Multiplication Tables Exercise 8: Sum of Prime Numbers Exercise 9: One Letter at a Time Exercise 10: Length without len() Exercise 11: Count the Numbers Exercise 12: Fizz Buzz 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 Using the Slice Object Adding Items to a List Inserting List Items Removing List Items Deleting versus Removing Items Popping Instead of Removing Concatenating Lists List Comprehension Sorting Lists Copying Lists Summary Exercises Exercise 1: All About You Exercise 2: Shopping List Exercise 3: List Deletion Exercise 4: List Modification Exercise 5: A Complete List Program Lesson 9 Understanding Basic Data Structures: Tuples Tuples and Tuple Operations Syntax of Tuples vs. Syntax of Lists Tuple Length Tuple Index Values Negative Indexing in Tuples Slicing Tuples Immutability Concatenating Tuples Searching Tuples Summary Exercises Exercise 1: Creating Tuples Exercise 2: Modifying Tuples Exercise 3: Where’s Waldo? Exercise 4: A Complete Tuple Program 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 Exercise 1: Working with Text Exercise 2: Separating the High from the Low Exercise 3: High and Low All in One Exercise 4: Self-Assessment 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 Exercise 1: Line by Line Exercise 2: Adding New Names Exercise 3: Popping Accounts Exercise 4: Everywhere That Mary Went… Exercise 5: Self-Assessment 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 Exercise 1: Lower Numbers Exercise 2: This Will Be Exercise 3: Finding the Largest Exercise 4: Simple Calculator Exercise 5: Which Is Greater? Part 3 Object-Oriented Programming in Python Lesson 14 Incorporating Object-Oriented Programming Object-Oriented Programming Overview Defining Classes Attributes Methods Creating Objects Working with Methods Class Attributes Working with Static Methods Working with Class Methods Summary Exercises Exercise 1: Create Your Own Class Exercise 2: Classy Vehicles Exercise 3: Streamlined Banking Exercise 4: Using a Calculator in Class Lesson 15 Including Inheritance Understanding Inheritance Creating a Parent Class Creating a Child Class Inheriting at Multiple Levels Overriding Methods Summary Exercises Exercise 1: Basic Inheritance Exercise 2: Adding Attributes Exercise 3: Creating More Children Exercise 4: Dogs and Cats Exercise 5: Hourly Employees Exercise 6: File System 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 a Burger Class Create a Drink Class Create a Side Class Create a Combo Create the Order Class Create the Main File Create order_once Order a Burger Add a Drink Add Sides Order a Combo Display the Output Tie the Code Files Together Summary Part 4 Data Processing with Python Lesson 17 Working with Dates and Times Getting Started with Dates and Times Creating a Variable for a Date Creating a Variable for Time Creating a Variable for Both Date and Time 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 Exercise 1: Displaying Dates Exercise 2: Leap Years Exercise 3: The Past Exercise 4: Unix Dates Exercise 5: Yesterday, Today, and Tomorrow Exercise 6: Setting Future Days Exercise 7: Five Seconds in the Future Exercise 8: Date Calculators Lesson 18 Processing Text Files File Processing Overview Introduction to File Input/Output The input() Function The open() Function The read() Method The write() Method The close() Method The print() Function Processing Text Files Opening a File Reading Text from a File Use the read() Method to Limit the Content Reading Lines Iterating through 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 Exercise 1: Reading Lines Exercise 2: Combination of the Two Exercise 3: Combination of Them All Exercise 4: Listing Lines Exercise 5: Longest Word Exercise 6: Listing Text Exercise 7: Text in Reverse 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 Exercise 1: Reading Lines Exercise 2: Company Stocks Exercise 3: Rearranging Files Exercise 4: Pop Music Evolution Exercise 5: All About Cars 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 Exercise 1: Company Bank Account Exercise 2: Formatted Account Information Exercise 3: Nobel Prizes Exercise 4: New York Restaurants Exercise 5: Movies Part 5 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 Specify an Initial Value Using reduce() with Comparison Operations Summary Exercises Exercise 1: Computing the Square Root Exercise 2: Converting a Text File to Uppercase Exercise 3: Determining Prime Exercise 4: Identifying Absolute Value Exercise 5: Highest Number Exercise 6: Lowest Number Exercise 7: Last Key Exercise 8: Highest Value Exercise 9: Sum of Even Exercise 10: Sum of Positive Numbers Exercise 11: Highest Stock Market Volume Exercise 12: Bad Stock Market Day Exercise 13: Highest Opening Price Exercise 14: Highest Price at Closing Exercise 15: Self-Assessment 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 Exercise 1: Typing Numbers Exercise 2: Current Value Exercise 3: Reading Lines Exercise 4: Concatenating Files Exercise 5: Creating a List from a File Exercise 6: Self-Assessment Lesson 23 Pulling It All Together: Word Analysis in Python Examine the Data Read the Data Tokenize the Dataset Tokenize an Input String Tokenize an Input Review Tokenize the Entire Dataset Using the Tokenize Functions Count the Words in Each Review Word Count for an Input List of Words Word Count an Input Review Word Count for the Dataset Summary Lesson 24 Extracting, Transforming, and Loading with ETL Scripting ETL Scripting in Python Design and Implement Custom ETL Scripts The extract Class Adding the extract.fromCSV Method Creating the extract.fromJSON Method Creating the extract.fromMySQL Method Creating the extract.fromMongoDB Method Verify the extract.py Module Using Our Script as an External Module The transform Class Defining the transform Class Creating the head and tail Methods Renaming a Column Removing a Column from the Data Source Renaming Multiple Columns Removing Multiple Columns Transforming the Data The load Class Creating the load.toCSV Method Creating the load.toJSON Method Creating the load.toMYSQL Method Creating the Load.toMONGODB Method Summary Exercises Exercise 1: Transforming CSV to CSV Exercise 2: Transforming CSV to JSON Exercise 3: Transforming JSON to CSV Exercise 4: Transforming JSON to JSON Exercise 5: Removing an Attribute Exercise 6: Renaming an Attribute Exercise 7: Confirming an Attribute Lesson 25 Improving ETL Scripting Converting to Static Methods for the extract Class Converting to Static Methods for the transform Class Converting to Static Methods for the load Class Adding Exception Handling in the extract Class Creating a Custom Extractor for the extract Class Summary Exercises Exercise 1: Revisiting Lessons Learned Exercise 2: Day of Week Exercise 3: Date Validity Exercise 4: Listing Duplicates Exercise 5: Removing Duplicates Exercise 6: Transforming Names Part 6 Appendices Appendix A: Flowcharts Flowchart Basics Sequences Branches Loops Common Flowcharting Shapes Flowcharting Example Additional Flowchart Elements Appendix B: Creating Pseudocode What Is Pseudocode? Appendix C: Installing MySQL MySQL Installation Download and Install MySQL Configure MySQL 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 EULA