📘 Introduction When you run a PySpark job, Spark doesn’t immediately execute each transformation. Instead, it constructs something called a DAG (Directed Acyclic Graph) — a roadmap of all the operations that need to happen. This DAG is the heart of Spark’s execution engine. It tells Spark how your data...
📘 Introduction When working with large datasets in PySpark, joins can easily become performance bottlenecks. This happens because Spark needs to shuffle data across the cluster to match rows between DataFrames — a costly operation when both datasets are big. If one of your DataFrames is small, though, there’s a faster...
📘 Introduction Choosing the right framework can make or break your web app. Streamlit and React are two powerful but very different tools. Streamlit is perfect for quickly building interactive data apps in Python, while React offers unmatched flexibility for large-scale, production-ready web applications. But which one is right for you?...
📘 Introduction Streamlit makes it easy to build interactive apps — and its st.data_editor() widget lets users edit data directly inside your app. But what if a single cell needs multiple selections, like tags, skills, or categories? 🤔 That’s where st.column_config.MultiselectColumn comes in! It allows you to...
📘 Introduction Streamlit makes it super easy to build interactive data apps in Python — without needing HTML, CSS, or JavaScript. But sometimes, you want your app to look more polished and visually appealing. One simple way to achieve that is by adding a background image. Whether you want to match your...
📘 Introduction Chatbots are becoming smarter and more useful thanks to agent frameworks. Instead of just responding to messages, agents can plan, call tools, and take actions. With the OpenAI Agents SDK, you can build intelligent assistants that do more than just chat—they can search, calculate, and even connect to...
📘 Introduction Chatbots are becoming smarter and more useful thanks to agent frameworks. Instead of just responding to messages, agents can plan, call tools, and take actions. With the OpenAI Agents SDK, you can build intelligent assistants that do more than just chat—they can search, calculate, and even connect to...
📘 Introduction Streamlit makes it super easy to build interactive apps in Python. But as your app grows — loading datasets, running expensive computations, or calling APIs — you might notice it slows down. The good news: Streamlit has a built-in caching system that stores results of expensive operations and reuses them instead...
📘 Introduction Welcome to this hands-on LangChain + LangGraph tutorial! In this guide, we’ll build an AI agent with tool-calling capabilities using LangChain, LangGraph, and OpenAI models. Instead of just answering questions, our agent will be able to invoke a Python function when needed. We’ll demonstrate this with a simple...