Pylenin Weekly #16

Map, filter, reduce, quick command for your git branch and building a Twitter monitor!

Pylenin Weekly #16

Welcome to Pylenin Weekly #16, a newsletter dedicated to improving the lives of my fellow peers through knowledge sharing in the field of programming and data.

First of all, I hope you accept my apologies of not sending out newsletters the last couple of weeks. Being a father is difficult! Even though the sleepless nights and constant attention towards my daughter isn't going to stop soon, I have gotten more accustomed to the routine.

New Articles

This week, I have written a new article on Map, filter and Reduce in Python. I am a big believer in functional programming and these methods are the important pillars of functional programming in Python.

Check out my article by clicking the link below!

Python Map, Filter and Reduce (With Examples)
Learn to use map, filter and reduce functions in Python 3 with examples.

What is my git branch?

Let me ask you a question. Have you ever been in a situation where you wanted to know the name of your branch you are working on, without having to navigate git branch ?

Recently at work, I got irritated looking at all the git branches stored locally(literally thousands). I just wanted to know the branch I am currently on, without having to navigate git branch. So I looked for some commands to find it and there are some pretty great commands I learnt!

  1. git branch --show-current
  2. git rev-parse –abbrev-ref HEAD
  3. git symbolic-ref –short HEAD
  4. git name-rev –name-only HEAD

My favorite is the first one! It is easy to remember and does the job well.

Do try them out and let me know!

Building a Twitter Monitor

This is a Data Engineering project, I found on Reddit and I think it is super useful for beginners to get into this field using Python.

It is an app that gets information in streaming from Twitter about the war in Ukraine regarding four topics: Biden, Zelensky, Putin and NATO, then process them in batches of one hour and show the information (sentiment analysis and emotion classification) at three aggregation levels: hour, day and total.

You can check the app here.

A screenshot of the app

Check out this repository for more details!

Today's newsletter was a short newsletter. Next time, I will try to have more content related to Python and Data!

Until then, take care!

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