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Data Warehousing Concepts in SQL: Understanding Star and Snowflake Schemas

Table of Contents Introduction What Is a Data Warehouse? OLTP vs OLAP: The Need for Warehousing Key Components of a Data Warehouse What Is Dimensional Modeling? Facts and Dimensions Explained The...
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SQL with APIs and JSON Fields in PostgreSQL: Working with Semi-Structured Data

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SQL for Data Engineering: ETL Concepts and Building Scalable Data Pipelines

Table of Contents Introduction What Is Data Engineering and Why SQL Matters Understanding ETL (Extract, Transform, Load) SQL’s Role in Each ETL Stage Data Sources: Raw Data Ingestion with...
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SQL for Data Analysis: Deep Dive into KPIs and Cohort Analysis

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Error Handling in SQL: Managing Exceptions and Ensuring Reliable Transactions

Table of Contents Introduction Why Error Handling Matters in SQL Types of Errors in SQL Syntax Errors vs Runtime Errors Understanding Transaction Errors Rollbacks for Safe Error Recovery Error Handling in...

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Stored Procedures and Functions in SQL: Encapsulating Logic for Reuse and Automation

Table of Contents Introduction What Are Stored Procedures and Functions? Benefits of Using Stored Routines Stored Procedures vs Functions: Key Differences Syntax for Creating Stored Procedures Executing a Stored Procedure Parameters...

Triggers in SQL: Automating Database Behavior

Table of Contents Introduction What Is a Trigger in SQL? Why Use Triggers? Types of Triggers Syntax of a Trigger BEFORE vs AFTER Triggers INSERT, UPDATE, and DELETE Triggers Trigger Events: Row-Level...

Using Constraints in SQL: NOT NULL, UNIQUE, CHECK, and DEFAULT

Table of Contents Introduction What Are Constraints in SQL? Why Use Constraints? NOT NULL Constraint UNIQUE Constraint CHECK Constraint DEFAULT Constraint Combining Multiple Constraints Adding Constraints to Existing Tables Dropping Constraints Naming Constraints for Clarity Column-Level...

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Machine Learning Foundations with scikit-learn: A Complete Guide

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Table of Contents Introduction What is Machine Learning? Why scikit-learn? Installing scikit-learn and Required Libraries Understanding the Machine Learning Pipeline Loading and Preparing Data Types of Machine Learning Algorithms Supervised Learning Unsupervised Learning Reinforcement...

Data Science with Python: NumPy, Pandas, Matplotlib, Seaborn

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Table of Contents Introduction Overview of Data Science with Python NumPy: The Foundation of Data Science in Python Key Features of NumPy NumPy Arrays: Basics and Operations Advanced NumPy Features Example...

Handling Legacy Code and Refactoring Techniques: Best Practices for Python Developers

Kumar Prafull -
Table of Contents Introduction What is Legacy Code? The Challenges of Working with Legacy Code Refactoring: What, Why, and How Refactoring Techniques Code Simplification Modularization and Decomposition Naming Conventions and Code Style Test-Driven...

Logging and Monitoring Python Applications: A Complete Guide

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Table of Contents Introduction Why Logging is Essential for Python Applications Configuring Python’s Built-In Logging Module Advanced Logging Techniques Monitoring Python Applications: Why and How Tools for Monitoring Python Applications Best...

Contract Programming with Python: A Deep Dive into Design by Contract

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Table of Contents Introduction to Contract Programming What is Design by Contract? Contract Programming in Python Python’s assert Statement Using pydantic for Data Validation Third-Party Libraries for Contract Programming Benefits of...

Property-Based Testing with Hypothesis: A Comprehensive Guide to Automating Tests in Python

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Table of Contents What is Property-Based Testing? The Problem with Traditional Testing Introduction to Hypothesis for Python How Hypothesis Works Setting Up Hypothesis Basic Example of Property-Based Testing More Complex Test...

Static Code Analysis and Linters (Pylint, MyPy) in Python: A Comprehensive Guide

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Table of Contents Introduction What is Static Code Analysis? Why Use Linters in Python? Overview of Popular Linters: Pylint and MyPy Pylint: Features and Benefits MyPy: Type Checking in Python How...

Debugging with pdb and ipdb: A Complete Guide for Python Developers

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Table of Contents Introduction What is Debugging Why Manual Debugging Falls Short Introduction to pdb (Python Debugger) Key Features of pdb Basic Commands of pdb Using pdb in Scripts Example: Debugging a...

Dockerizing Python Applications for Production: A Step-by-Step Guide

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Table of Contents Introduction What is Docker and Why Use It? Benefits of Dockerizing Python Applications Prerequisites for Dockerizing Python Applications Creating a Dockerfile for Your Python Application Building and...

Continuous Deployment (CD) for Python Projects: A Complete Guide

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Table of Contents Introduction What is Continuous Deployment (CD) Difference Between CI, CD, and DevOps Why Continuous Deployment Matters for Python Projects Setting Up a Basic Python Project for...

Continuous Integration (CI) for Python Projects: A Complete Guide

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Table of Contents Introduction to Continuous Integration (CI) Why CI is Important for Python Projects Key Concepts of CI Setting Up a CI Pipeline for Python Basic Requirements Choosing a...

Test-Driven Development (TDD) in Python: A Complete Deep Dive

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Table of Contents Introduction What is Test-Driven Development (TDD) Why Use TDD: Benefits and Challenges TDD Workflow Explained Unit Testing in Python: unittest Framework Writing Your First TDD Example in...
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