Cuantum Technologies - Python and SQL Bible [2023, PDF/EPUB, ENG] torrent

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Python and SQL Bible:From Beginner to World Expert / Библия Python и SQL: От новичка до мирового эксперта

Год издания: 2023
Автор: Cuantum Technologies

Издательство: Cuantum Technologies LLC.
ISBN: 979-8-3991-7543-0
Язык: Английский

Формат: PDF/EPUB
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 655

Описание: Are you eager to break into the thrilling world of data analysis? Do you want to master Python, the leading programming language for data science, and SQL, the gold standard for managing relational databases? Your search ends here. Welcome to "Python and SQL Bible: From Beginner to World Expert", the only resource you need to navigate the versatile landscapes of Python and SQL, the powerful data duo.
Enter the exciting world of data with Python and SQL! Unleash the true potential of data analysis and manipulation. Dive into the intricate yet thrilling journey of data discovery, processing, and storytelling. With "Python and SQL Bible: From Beginner to World Expert", you'll explore the fascinating world of data analysis and become a master of these two powerful tools.
This book is designed to take you from a beginner-level to a world expert in Python and SQL. You'll learn how to harness the power of Python's flexibility and SQL's structured accuracy to extract, clean, analyze, and visualize data. With each chapter, you'll unravel new concepts and build on your knowledge, from the foundational basics to advanced operations. Through practical examples and exercises, you'll test your learning and build your expertise.
This comprehensive guide combines the ease of Python with the structured accuracy of SQL, two essential tools in today's data-driven landscape. Whether you're starting from scratch, solidifying your skills, or seeking to delve deeper into advanced concepts, this book is your ideal companion. It takes you on an incredible journey from the basics of Python and SQL to expert-level knowledge, empowering you to confidently handle real-world data challenges.
In this book, you'll learn:
Basics of Python: From understanding Python syntax and data types to grasping control flow and functions.
Advanced Python: Dive into object-oriented programming, exception handling, file operations, and more.
Introduction to SQL: A comprehensive exploration of SQL's history, syntax, and basic operations.
SQL Basics: Discover how to create databases and tables, manipulate data, and work with NULL values.
Advanced SQL Concepts: Unleash the power of advanced select queries, joining multiple tables, and aggregate functions.
Python Meets SQL: Explore the sqlite3 module and how to handle SQL errors and exceptions in Python.
Advanced Database Operations: Dive into advanced operations such as CRUD operations and handling transactions.
Data Analysis with Python and SQL: Discover the power of data cleaning, analysis, visualization, and machine learning.
Advanced Database Operations with SQLAlchemy: An introduction to the SQL Toolkit and ORM, creating sessions, adding, retrieving, and updating rows, and handling relationships and joins.
Plus, invaluable appendices including Python and SQL interview questions and cheat sheets.
"Python and SQL Bible: From Beginner to World Expert" is meticulously designed to equip you with a strong skill set in Python and SQL. Through step-by-step tutorials, practical exercises, and expert insights, you'll gain a thorough understanding of data manipulation, analysis, and visualization. By the end of this book, you'll have an unparalleled foundation in Python and SQL, ready to tackle any data problem with confidence and competence.
Whether you're embarking on a new career, enhancing your professional skills, or satiating your intellectual curiosity, this book is your passport to excelling in the world of Python and SQL. So, are you ready to become a world expert in Python and SQL?

Вам не терпится окунуться в захватывающий мир анализа данных? Вы хотите освоить Python, ведущий язык программирования для анализа данных, и SQL, золотой стандарт для управления реляционными базами данных? На этом ваш поиск заканчивается. Добро пожаловать на "Библию Python и SQL: от новичка до мирового эксперта", единственный ресурс, который вам нужен для навигации по разнообразным ландшафтам Python и SQL, мощного дуэта данных.
Окунитесь в захватывающий мир данных с помощью Python и SQL! Раскройте истинный потенциал анализа данных и манипулирования ими. Окунитесь в сложное, но захватывающее путешествие по поиску, обработке данных и созданию историй. С "Библией Python и SQL: от новичка до мирового эксперта" вы познакомитесь с увлекательным миром анализа данных и станете мастером этих двух мощных инструментов.
Эта книга предназначена для того, чтобы помочь вам пройти путь от новичка до мирового эксперта в области Python и SQL. Вы узнаете, как использовать гибкость Python и структурированную точность SQL для извлечения, очистки, анализа и визуализации данных. В каждой главе вы будете знакомиться с новыми концепциями и расширять свои знания - от базовых до продвинутых операций. С помощью практических примеров и упражнений вы сможете проверить свои знания и повысить квалификацию.
Это всеобъемлющее руководство сочетает в себе простоту Python и структурированную точность SQL - двух важнейших инструментов в современной среде, управляемой данными. Независимо от того, начинаете ли вы с нуля, совершенствуете свои навыки или хотите глубже разобраться в передовых концепциях, эта книга - ваш идеальный помощник. Она отправит вас в невероятное путешествие от основ Python и SQL к знаниям экспертного уровня, что позволит вам уверенно справляться с задачами, связанными с данными в реальном мире.
В этой книге вы узнаете:
Основы Python: от понимания синтаксиса и типов данных Python до понимания потока управления и функций.
Продвинутый уровень Python: Погружение в объектно-ориентированное программирование, обработку исключений, операции с файлами и многое другое.
Введение в SQL: Всестороннее изучение истории, синтаксиса и основных операций SQL.
Основы SQL: Узнайте, как создавать базы данных и таблицы, манипулировать данными и работать с нулевыми значениями.
Расширенные концепции SQL: Раскройте возможности расширенных запросов select, объединения нескольких таблиц и агрегатных функций.
Python знакомит с SQL: Изучите модуль sqlite3 и способы обработки ошибок SQL и исключений в Python.
Расширенные возможности работы с базами данных: Познакомьтесь с передовыми операциями, такими как CRUD-операции и обработка транзакций.
Анализ данных с помощью Python и SQL: Откройте для себя возможности очистки данных, анализа, визуализации и машинного обучения.
Расширенные возможности работы с базами данных с помощью SQLAlchemy: введение в SQL Toolkit и ORM, создание сессий, добавление, извлечение и обновление строк, а также обработка связей и объединений.
А также бесценные приложения, включая вопросы для собеседований по Python и SQL и шпаргалки.
"Библия Python и SQL: от новичка до мирового эксперта" тщательно разработана для того, чтобы вы овладели основательными навыками работы с Python и SQL. Благодаря пошаговым руководствам, практическим упражнениям и советам экспертов вы получите полное представление о манипулировании данными, их анализе и визуализации. К концу прочтения этой книги у вас будет беспрецедентный опыт работы с Python и SQL, и вы будете готовы уверенно и компетентно решать любые проблемы с данными.
Начинаете ли вы новую карьеру, совершенствуете свои профессиональные навыки или удовлетворяете свое интеллектуальное любопытство, эта книга - ваш пропуск в мир Python и SQL. Итак, вы готовы стать мировым экспертом в Python и SQL?
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[spoiler="Оглавление"]
WHO WE ARE
OUR PHILOSOPHY:
OUR EXPERTISE:
INTRODUCTION
CHAPTER 1: PYTHON: AN INTRODUCTION
1.1 BRIEF HISTORY OF PYTHON
1.2 BENEFITS OF PYTHON
1.2.1 Readability and Simplicity
1.2.2 High-Level Language
1.2.3 Extensive Libraries
1.2.4 Cross-Platform Compatibility
1.2.5 Dynamically Typed
1.2.6 Support for Multiple Programming Paradigms
1.2.7 Strong Community and Widespread Adoption
1.2.8 Integration with Other Languages
1.2.9 Versatility
1.3 PYTHON APPLICATIONS
1.3.1 Web Development
1.3.2 Data Analysis and Data Visualization
1.3.3 Machine Learning and Artificial Intelligence
1.3.4 Game Development
1.3.5 Automation and Scripting
1.3.6 Cybersecurity
1.3.7 Internet of Things (IoT)
1.3.8 Robotics
1.3.9 Bioinformatics and Computational Biology
1.3.10 Education
1.4 SETTING UP THE PYTHON ENVIRONMENT AND WRITING YOUR FIRST PYTHON
PROGRAM
1.4.1 Setting up Python Environment
1.4.2 Your First Python Program
CHAPTER 1 CONCLUSION
CHAPTER 2: PYTHON BUILDING BLOCKS
2.1 PYTHON SYNTAX AND SEMANTICS
2.1.1 Python Syntax
2.1.2 Python Semantics
2.2 VARIABLES AND DATA TYPES
2.2.1 Integers
2.2.2 Floating-Point Numbers
2.2.3 Strings
2.2.4 Booleans
2.2.5 Lists
2.2.6 Tuples
2.2.7 Dictionaries
2.2.8 Type Conversion
2.2.9 Dynamic Typing
2.2.10 Variable Scope
2.3 BASIC OPERATORS
2.3.1 Arithmetic Operators
2.3.1 Comparison Operators
2.3.2 Logical Operators
2.3.3 Assignment Operators
2.3.4 Bitwise Operators
2.3.5 Membership Operators
2.3.6 Identity Operators
2.3.6 Operator Precedence
2.4 PRACTICE EXERCISES
CHAPTER 2 CONCLUSION
CHAPTER 3: CONTROLLING THE FLOW
3.1 CONTROL STRUCTURES IN PYTHON
3.1.1 Conditional Statements (if, elif, else)
3.1.2 Loop Structures (for, while)
3.2 ERROR AND EXCEPTION HANDLING
3.2.1 Handling Exceptions with try and except
3.2.2 The else and finally Clauses
3.2.3 Raising Exceptions
3.2.4 The assert Statement
3.3 UNDERSTANDING ITERABLES AND ITERATORS
3.3.1 Iterators in Python
3.3.2 The for loop and Iterators
3.3.3 Iterators and Built-in Types
3.3.4 Python's itertools Module
3.3.5 Python Generators
3.4 PRACTICE EXERCISES
Exercise 1: Conditional Statements
Exercise 2: Loops
Exercise 3: Error and Exception Handling
Exercise 4: Iterables and Iterators
CHAPTER 3 CONCLUSION
CHAPTER 4: FUNCTIONS, MODULES, AND PACKAGES
4.1 FUNCTION DEFINITION AND CALL
4.1.1 Function Definition
4.1.2 Function Call
4.1.3 Function Parameters
4.1.4 Docstrings
4.1.5 Local and Global Variables
4.2 SCOPE OF VARIABLES
4.2.1 Global Scope
4.2.2 Local Scope
4.2.3 Nonlocal Scope
4.2.4 Built-In Scope
4.2.5 Best Practices for Variable Scope
4.3 MODULES AND PACKAGES
4.3.1 Modules in Python
4.3.2 Packages in Python
4.3.3 Python's import system
4.4 RECURSIVE FUNCTIONS IN PYTHON
4.4.1 Understanding Recursion
4.4.2 Recursive Functions Must Have a Base Case
4.4.3 The Call Stack and Recursion
4.5 PRACTICAL EXERCISES
Exercise 1: Writing and Calling a Function
Exercise 2: Understanding Variable Scope
Exercise 3: Importing and Using a Module
Exercise 4: Recursive Function
Exercise 5: Error Handling
CHAPTER 4 CONCLUSION
CHAPTER 5: DEEP DIVE INTO DATA STRUCTURES
5.1 ADVANCED CONCEPTS ON LISTS, TUPLES, SETS, AND DICTIONARIES
5.1.1 Advanced Concepts on Lists
5.1.2 Advanced Concepts on Tuples
5.1.3 Advanced Concepts on Sets
5.1.4 Advanced Concepts on Dictionaries
5.1.5 Combining Different Data Structures
5.1.6 Immutable vs Mutable Data Structures
5.1.7 Iterating over Data Structures
5.1.8 Other Built-in Functions for Data Structures
5.2 IMPLEMENTING DATA STRUCTURES (STACK, QUEUE, LINKED LIST, ETC.)
5.2.1 Stack
5.2.2 Queue
5.2.3 Linked Lists
5.2.4 Trees
5.3 BUILT-IN DATA STRUCTURE FUNCTIONS AND METHODS
5.4 PYTHON'S COLLECTIONS MODULE
5.5 MUTABILITY AND IMMUTABILITY
5.6 PRACTICAL EXERCISES
Exercise 1: Implementing a Stack
Exercise 2: Implementing a Queue
Exercise 3: Using List Comprehensions
Exercise 4: Implementing a Linked List
CHAPTER 5 CONCLUSION
CHAPTER 6: OBJECT-ORIENTED PROGRAMMING IN PYTHON
6.1 CLASSES, OBJECTS, AND INHERITANCE
6.2 POLYMORPHISM AND ENCAPSULATION
6.2.1 Polymorphism
6.2.2 Encapsulation
6.3 PYTHON SPECIAL FUNCTIONS
6.4 ABSTRACT BASE CLASSES (ABCS) IN PYTHON
6.4.1 ABCs with Built-in Types
6.5 OPERATOR OVERLOADING
6.6 METACLASSES IN PYTHON
6.7 PRACTICAL EXERCISES
Exercise 6.7.1: Class Definition and Object Creation
Exercise 6.7.2: Inheritance and Polymorphism
Exercise 6.7.3: Encapsulation
CHAPTER 6 CONCLUSION
CHAPTER 7: FILE I/O AND RESOURCE MANAGEMENT
7.1 FILE OPERATIONS
7.1.1 Opening a file
7.1.2 Exception handling during file operations
7.1.3 The with statement for better resource management
7.1.4 Working with Binary Files
7.1.5 Serialization with pickle
7.1.6 Working with Binary Files
7.1.7 Serialization with pickle
7.1.8 Handling File Paths
7.1.9 The pathlib Module
7.2 CONTEXT MANAGERS
7.3 DIRECTORIES AND FILESYSTEMS
7.4 WORKING WITH BINARY DATA: THE PICKLE AND JSON MODULES
7.5 WORKING WITH NETWORK CONNECTIONS: THE SOCKET MODULE
7.6 MEMORY MANAGEMENT IN PYTHON
7.6.1 Reference Counting
7.6.2 Garbage Collection
7.7 PRACTICAL EXERCISES
Exercise 1
Exercise 2
Exercise 3
CHAPTER 7 CONCLUSION
CHAPTER 8: EXCEPTIONAL PYTHON
8.1 ERROR AND EXCEPTION HANDLING
8.1.1 Else Clause
8.1.2 Finally Clause
8.1.3 Custom Exceptions
8.2 DEFINING AND RAISING CUSTOM EXCEPTIONS
8.2.1 Defining Custom Exceptions
8.2.2 Adding More Functionality to Custom Exceptions
8.2.3 Raising Custom Exceptions
8.3 GOOD PRACTICES RELATED TO RAISING AND HANDLING EXCEPTIONS
8.4 LOGGING IN PYTHON
8.5 PRACTICAL EXERCISES
Exercise 1: Creating a custom exception
Exercise 2: Adding exception handling
Exercise 3: Logging
Exercise 4: Advanced logging
CHAPTER 8 CONCLUSION
CHAPTER 9: PYTHON STANDARD LIBRARY
9.1 OVERVIEW OF PYTHON STANDARD LIBRARY
9.1.1 Text Processing Services
9.1.2 Binary Data Services
9.1.3 Data Types
9.1.4 Mathematical Modules
9.1.5 File and Directory Access
9.1.6 Functional Programming Modules
9.1.7 Data Persistence
9.1.8 Data Compression and Archiving
9.1.9 File Formats
9.2 EXPLORING SOME KEY LIBRARIES
9.2.1 numpy
9.2.2 pandas
9.2.3 matplotlib
9.2.4 requests
9.2.5 flask
9.2.6 scipy
9.2.7 scikit-learn
9.2.8 beautifulsoup4
9.2.9 sqlalchemy
9.2.10 pytorch and tensorflow
9.3 CHOOSING THE RIGHT LIBRARIES
9.3.1 Suitability for Task
9.3.2 Maturity and Stability
9.3.3 Community and Support
9.3.4 Documentation and Ease of Use
9.3.5 Performance
9.3.6 Community Support
9.4 PRACTICAL EXERCISES
Exercise 1: Exploring the Math Library
Exercise 2: Data Manipulation with Pandas
Exercise 3: File Operations with os and shutil Libraries
CHAPTER 9 CONCLUSION
CHAPTER 10: PYTHON FOR SCIENTIFIC COMPUTING AND DATA
ANALYSIS
10.1 INTRODUCTION TO NUMPY, SCIPY, AND MATPLOTLIB
10.1.1 Understanding NumPy Arrays
10.1.2 Efficient Mathematical Operations with NumPy
10.1.3 Linear Algebra with SciPy
10.1.4 Data Visualization with Matplotlib
10.2 DIGGING DEEPER INTO NUMPY
10.2.1 Array slicing and indexing
10.2.2 Array reshaping and resizing
10.3 WORKING WITH SCIPY
10.3.1 Optimization with SciPy
10.3.2 Statistics with SciPy
10.4 VISUALIZING DATA WITH MATPLOTLIB
10.4.1 Basic Plotting with Matplotlib
10.4.2 Creating Subplots
10.4.3 Plotting with Pandas
10.5 EXPLORING PANDAS FOR DATA ANALYSIS
10.5.1 Creating a DataFrame
10.5.2 Data Selection
10.5.3 Data Manipulation
10.5.4 Reading Data from Files
10.6 INTRODUCTION TO SCIKIT-LEARN
10.7 INTRODUCTION TO STATSMODELS
10.8 INTRODUCTION TO TENSORFLOW AND PYTORCH
10.9 PRACTICAL EXERCISES
Exercise 10.1
Exercise 10.2
Exercise 10.3
Exercise 10.4
CHAPTER 10: CONCLUSION
CHAPTER 11: TESTING IN PYTHON
11.1 UNIT TESTING WITH UNITTEST
11.1.1 setUp and tearDown
11.1.2 Test Discovery
11.1.3 Testing for Exceptions
11.2 MOCKING AND PATCHING
11.2.1 Mock and Side Effects
11.2.2 PyTest
11.3 TEST-DRIVEN DEVELOPMENT
11.4 DOCTEST
11.5 PRACTICAL EXERCISES
Exercise 1: Unit Testing
Exercise 2: Mocking and Patching
Exercise 3: Test-Driven Development
CHAPTER 11 CONCLUSION
CHAPTER 12: INTRODUCTION TO SQL
12.1 BRIEF HISTORY OF SQL
12.2 SQL SYNTAX
12.2.1 Basic Query Structure
12.2.2 SQL Keywords
12.2.3 SQL Statements
12.2.4 SQL Expressions
12.3 SQL DATA TYPES
12.3.1 Numeric Types
12.3.2 Date and Time Types
12.3.3 String Types
12.3.4 SQL Constraints
12.4 SQL OPERATIONS
12.4.1 Data Definition Language (DDL)
12.4.2 Data Manipulation Language (DML)
12.5 SQL QUERIES
12.5.1 Filtering with the WHERE clause
12.5.2 Sorting with the ORDER BY clause
12.5.3 Grouping with the GROUP BY clause
12.5.4 Joining Tables
12.6 PRACTICAL EXERCISES
Exercise 1
Exercise 2
Exercise 3
Exercise 4
Exercise 5
Exercise 6
Exercise 7
CHAPTER 12 CONCLUSION
CHAPTER 13: SQL BASICS
13.1 CREATING DATABASES AND TABLES
13.2 INSERTING DATA INTO TABLES
13.3 SELECTING DATA FROM TABLES
13.4 UPDATING DATA IN TABLES
13.5 DELETING DATA FROM TABLES
13.6 FILTERING AND SORTING QUERY RESULTS
13.7 NULL VALUES
13.8 PRACTICAL EXERCISES
Exercise 1: Creating Databases and Tables
Exercise 2: Inserting Data
Exercise 3: Updating and Deleting Data
Exercise 4: Querying Data
Exercise 5: Working with NULL
CHAPTER 13 CONCLUSION
CHAPTER 14: DEEP DIVE INTO SQL QUERIES
14.1 ADVANCED SELECT QUERIES
14.1.1 The DISTINCT Keyword
14.1.2 The ORDER BY Keyword
14.1.3 The WHERE Clause
14.1.4 The LIKE Operator
14.1.5 The IN Operator
14.1.6 The BETWEEN Operator
14.2 JOINING MULTIPLE TABLES
14.2.1 LEFT JOIN and RIGHT JOIN
14.2.2 FULL OUTER JOIN
14.2.3 UNION and UNION ALL
14.2.4 Subqueries
14.3 AGGREGATE FUNCTIONS
14.4 PRACTICAL EXERCISES
Exercise 1 - Advanced Select Queries
Exercise 2 - Joining Multiple Tables
Exercise 3 - Aggregate Functions
CHAPTER 14 CONCLUSION
CHAPTER 15: ADVANCED SQL
15.1 SUBQUERIES
15.1.1 Scalar Subquery
15.1.2 Correlated Subquery
15.1.3 Common Table Expressions (CTEs)
15.2 STORED PROCEDURES
15.2.1 Different Types of Stored Procedures
15.3 TRIGGERS
15.3.1 Additional Details
15.4 PRACTICAL EXERCISES
Exercise 1: Working with Subqueries
Exercise 2: Creating and Using Stored Procedures
Exercise 3: Triggers
CHAPTER 15 CONCLUSION
CHAPTER 16: SQL FOR DATABASE ADMINISTRATION
16.1 CREATING, ALTERING, AND DROPPING TABLES
16.1.1 Creating Tables
16.1.2 Altering Tables
16.1.3 Dropping Tables
16.2 DATABASE BACKUPS AND RECOVERY
16.2.1 Database Backups
16.2.2 Database Recovery
16.2.3 Point-In-Time Recovery (PITR)
16.3 SECURITY AND PERMISSION MANAGEMENT
16.3.1 User Management
16.3.2 Granting Permissions
16.3.3 Revoking Permissions
16.3.4 Deleting Users
16.4 PRACTICAL EXERCISES
Exercise 1: Creating, Altering, and Dropping Tables
Exercise 2: Database Backups and Recovery
Exercise 3: Security and Permission Management
CHAPTER 16 CONCLUSION
CHAPTER 17: PYTHON MEETS SQL
17.1 PYTHON'S SQLITE3 MODULE
17.1.1 Inserting Data
17.1.2 Fetching Data
17.2 PYTHON WITH MYSQL
17.3 PYTHON WITH POSTGRESQL
17.4 PERFORMING CRUD OPERATIONS
17.4.1 Create Operation
17.4.2 Read Operation
17.4.3 Update Operation
17.4.4 Delete Operation
17.4.5 MySQL
17.4.6 PostgreSQL
17.5 HANDLING TRANSACTIONS IN PYTHON
17.6 HANDLING SQL ERRORS AND EXCEPTIONS IN PYTHON
17.7 PRACTICAL EXERCISES
Exercise 17.7.1
Exercise 17.7.2
Exercise 17.7.3
Exercise 17.7.4
Exercise 17.7.5
Exercise 17.7.6
CHAPTER 17 CONCLUSION
CHAPTER 18: DATA ANALYSIS WITH PYTHON AND SQL
18.1 DATA CLEANING IN PYTHON AND SQL
18.2 DATA TRANSFORMATION IN PYTHON AND SQL
18.2.1 Data Transformation in SQL
18.2.2 Data Transformation in Python
18.3 DATA VISUALIZATION IN PYTHON AND SQL
18.3.1 Data Visualization in SQL
18.3.2 Data Visualization in Python
18.4 STATISTICAL ANALYSIS IN PYTHON AND SQL
18.4.1 Statistical Analysis in SQL
18.4.2 Statistical Analysis in Python
18.5 INTEGRATING PYTHON AND SQL FOR DATA ANALYSIS
18.5.1 Querying SQL Database from Python
18.5.2 Using pandas with SQL
18.5.3 Using SQLAlchemy for Database Abstraction
18.6 PRACTICAL EXERCISES
Exercise 1: Data Cleaning
Exercise 2: Data Transformation
Exercise 3: Querying SQL Database from Python
CHAPTER 18 CONCLUSION
CHAPTER 19: ADVANCED DATABASE OPERATIONS WITH
SQLALCHEMY
19.1 SQLALCHEMY: SQL TOOLKIT AND ORM
19.2 CONNECTING TO DATABASES
19.3 UNDERSTANDING SQLALCHEMY ORM
19.4 CRUD OPERATIONS WITH SQLALCHEMY ORM
19.4.1 Creating Records
19.4.2 Reading Records
19.4.3 Updating Records
19.4.4 Deleting Records
19.5 MANAGING RELATIONSHIPS WITH SQLALCHEMY ORM
19.6 QUERYING WITH JOINS IN SQLALCHEMY
19.7 TRANSACTIONS IN SQLALCHEMY
19.8 MANAGING RELATIONSHIPS IN SQLALCHEMY
19.9 SQLALCHEMY SQL EXPRESSION LANGUAGE
19.10 PRACTICAL EXERCISE
Exercise 19.1
CHAPTER 19 CONCLUSION
APPENDIX A: PYTHON INTERVIEW QUESTIONS
APPENDIX B: SQL INTERVIEW QUESTIONS
APPENDIX C: PYTHON CHEAT SHEET
BASIC PYTHON SYNTAX
DATA STRUCTURES
LIST COMPREHENSIONS
APPENDIX D: SQL CHEAT SHEET
SQL SYNTAX
CRUD OPERATIONS
REFERENCES
CONCLUSION
WHERE TO CONTINUE?
KNOW MORE ABOUT US
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