Python

The Ultimate Beginner’s Guide to Jupyter Notebooks

The Ultimate Beginner’s Guide to Jupyter Notebooks

Jupyter Notebooks offer a great way to write and iterate on your Python code. It is an incredibly powerful tool for interactively developing and presenting data science projects. A notebook integrates code and its output into a single document that combines visualisations, narrative text, mathematical equations, and other rich media. The intuitive workflow promotes iterative and rapid development, making notebooks an increasingly popular choice at the heart of contemporary data science, analysis, and increasingly science at large. Best of all, as part of the open source Project Jupyter, they are completely free.

Project Jupyter is the successor to an earlier project IPython Notebook, which was first published as a prototype in 2010. Jupyter Notebook is built off of IPython, an interactive way of running Python code in the terminal using the REPL model (Read-Eval-Print-Loop).

How to Implement Server Sent Events Using Python Flask and React

How to Implement Server Sent Events Using Python Flask and React

A typical Request Response cycle works such that client sends request to server and server responds to that request. But there are few use cases where we might need to send data from server without request or client is expecting a data that can arrive at anonymous time.There are few mechanisms available to solve this problem.

Server Sent Events

Broadly we can classify these  as client pull and server push mechanisms.Websockets is a bi directional mechanism where data is transmitted via full duplex TCP protocol.

A Quick Introduction to Data Analysis With Pandas

A Quick Introduction to Data Analysis With Pandas

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Pandas aims to integrate the functionality of NumPy and matplotlib to give you a convenient tool for data analytics and visualization. It does more than just integration — it makes the usage far more better.

In this blog, I’ll give you a list of useful pandas snippets that can be reused over and over again. These will definitely save you some time that you might need skimming through the comprehensive Pandas docs.

An Introduction to Asynchronous Programming in Python

An Introduction to Asynchronous Programming in Python

Asynchronous programming is a type of parallel programming in which a unit of work is allowed to run separately from the primary application thread. Asynchronous programming has been gaining a lot of attention in the past few years, and for good reason. Typically Node.js is associated with Asynchronous programming. Although, nowadays other languages including Python do support Asynchronous programming.

This blog acts an introduction to asynchronous programming in Python and explores different ways in which to achieve that.

Deploy Serverless, Event-driven Python Applications Using Zappa

Deploy Serverless, Event-driven Python Applications Using Zappa

Zappa makes it super easy to build and deploy server-less, event-driven Python applications (including, but not limited to, WSGI web apps) on AWS Lambda + API Gateway. Think of it as "serverless" web hosting for your Python apps. That means infinite scalingzero downtimezero maintenance - and at a fraction of the cost of your current deployments!

This blog acts a simple tutorial to deploy a sample Django/Python application using Zappa.