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Python is one of the best programming languages. Due to its readability and beginner-friendly nature, it has been accepted by industries around the world. So to master Python for any field you have to work on projects. In this article , I will take you through more than 190 Python projects with source code.

In this tutorial , you'll learn how to send data from client-to-server and client-to-client connections using socket programming in Python. Socket programming is the implementation of two sockets to send and receive data bi-directionally at any given moment. It connects two sockets (or nodes) together and allows them to communicate in real time. Internet-connected applications that need to operate in real time greatly benefit from the implementation of sockets in their networking code, allowing data to be sent and received at any time. In this Python tutorial, you'll learn how to send data from client-to-server and client-to-client connections using socket network programming in Python. You'll also learn how you can leverage the power of PubNub to send data between two or more client devices for peer-to-peer communication using the PubNub Python SDK. Although this tutorial guides you step-by-step through this process, you can view a video walkthrough of this tutorial on Yo...

Python's magic methods - also known as dunder (double underscore) methods - can be used to implement a lot of cool things. Most of the time we use them for simple stuff, such as constructors (__init__), string representation (__str__, __repr__) or arithmetic operators (__add__/__mul__). There are however many more magic methods which you probably haven't heard about and in this article we will explore all of them (even the hidden and undocumented)! read more ...

The idea of an all-knowing computer program comes from science fiction and should stay there. Despite the seductive fluency of ChatGPT and other language models, they remain unsuitable as sources of knowledge. We must fight against the instinct to trust a human-sounding machine, argue Emily M. Bender and Chirag Shah. Decades of science fiction have taught us that a key feature of a high-tech future is computer systems that give us instant access to seemingly limitless collections of knowledge through an interface that takes the form of a friendly (or sometimes sinisterly detached) voice. The early promise of the World Wide Web was that it might be the start of that collection of knowledge. With Meta’s Galactica, OpenAI’s ChatGPT and earlier this year LaMDA from Google, it seems like the friendly language interface is just around the corner, too. read more ...

This article was originally published on Big Think+. Problem-solving skills are in demand. Every job posting lists them under must-have qualifications, and every job candidate claims to possess them, par excellence. Young entrepreneurs make solutions to social and global problems the heart of their mission statements, while parents and teachers push for curricula that encourage critical-thinking methods beyond solving for x.

Pandas is a very popular tool for data analysis. It comes built-in with many useful features, it's battle tested and widely accepted. However, pandas is not always the best tool for the job. SQL databases have been around since the 1970s. Some of the smartest people in the world worked on making it easy to slice, dice, fetch and manipulate data quickly and efficiently. SQL databases have come such a long way, that many developers and data scientists lost track of what they can do with the database they already have! In this article the author demonstrate how to use SQL to perform fast and efficient data analysis.

First let’s start with stating the problem with existing writing on “Data Cleaning”. Wikipedia' s post on data cleaning does a decent summary of the big important qualities of data quality: Validity, Accuracy, Completeness, Consistency, Uniformity. It’s also got a section on “process” that’s really dry and academic (in a negative way) and won’t help you clean any data at all. Next I’m just gonna sample posts from the top links on Google when I search “Data cleaning”. I’ll provide links as reference so you know what I’m griping about. This highly PageRanked one is like a friendlier expansion of the Wikipedia page at the start. Luckily it redeems itself in the process section by listing a big list of example techniques to use to clean data, things like cleaning spaces, dropping irrelevant values, etc. Has some examples and illustrations!. read more ...