Learn PySpark Structured Streaming step by step by building a beginner-friendly real-time data pipeline with JSON files, readStream, writeStream, output modes, triggers, and checkpoints.
Compare FastAPI and Flask for serving AI agents, ML APIs, LLM backends, and production-ready Python services.
Learn how to load a local CSV file into DuckDB with dlt, inspect the result with SQL, and understand the basic pipeline pattern.
📘 Introduction In this hands-on tutorial, you will learn how to load data from a REST API into DuckDB using dlt. This is a great first local data pipeline because you do not need a cloud warehouse, a complex setup, or production credentials. We will use dlt to fetch data...
📘 Introduction Generating images with AI has never been easier. Hugging Face’s Diffusers library provides a user-friendly way to create stunning visuals using pre-trained diffusion models like Stable Diffusion. In this guide, we’ll walk through the entire process step by step. 🧠 What are Hugging Face Diffusers? Diffusers...
📘 Introduction When working with data spread across multiple CSV files, combining them into one unified dataset can save time and simplify your workflow. In this guide, you’ll learn how to merge multiple CSV files into a single Pandas DataFrame using just a few lines of Python. ✅ Prerequisites Before you...
📘 Introduction Working with structured data is a core part of any data engineering or analytics workflow. DuckDB, often called the SQLite for analytics, makes it incredibly easy to query local data files—including JSON—without requiring a complex setup. In this tutorial, you’ll learn how to load JSON data...
📘 Introduction JSON is one of the most widely used data formats for APIs, configurations, storage, and modern applications. Converting CSV to JSON in Python is incredibly simple using Pandas. In this tutorial, we will walk through the full process: creating a sample CSV file, loading it into a Pandas DataFrame,...
📘 Introduction In this tutorial, you’ll learn how to load data from a Parquet file into a DuckDB database using Python. DuckDB’s native Parquet support makes it fast and efficient to work with columnar data, making it ideal for analytics, ETL pipelines, and Python data projects. You’ll see...