Hey Pythonistas, this weekend is Pycon ES and in the unlikely event you get bored, you can always do some coding with PyBites. Two more good reasons to do so: 1. there are prizes / giveaways, 2. your PRs count towards Hacktoberfest (t-shirt). Fire up your editors and let’s get coding!
PyBites Team
This is the PyBites team here — keep calm and code in Python!
Code Challenge 63 – Automatically Generate Blog Featured Images
By PyBites Team on 2 September 2019
Hey Pythonistas, in this new blog code challenge you are going to use selenium to automatically generate some cool featured images for PyBites. Have fun!
Code Challenge 62 – Women @ Pycon ES
By PyBites Team on 12 July 2019
Hey Pythonistas, in this special live Alicante PyDay challenge you will analyze Pycon speaker data, do we see more women going on stage? Enjoy!
PyBites Twitter Digest – Issue 04, 2019
By PyBites Team on 7 April 2019
Every weekend we share a curated list of 15 cool things (mostly Python) that we found / tweeted throughout the week.
PyBites Twitter Digest – Issue 03, 2019
By PyBites Team on 3 March 2019
Every weekend we share a curated list of 15 cool things (mostly Python) that we found / tweeted throughout the week.
PyBites Twitter Digest – Issue 02, 2019
By PyBites Team on 24 February 2019
Every weekend we share a curated list of 15 cool things (mostly Python) that we found / tweeted throughout the week.
Code Challenge 61 – Build a URL Shortener
By PyBites Team on 21 February 2019
Hey Pythonistas, in this challenge you will build an URL shortener. Enjoy!
PyBites Twitter Digest – Issue 01, 2019
By PyBites Team on 17 February 2019
It has been too long but we’re excited to bring you today: PyBites Twitter Digest – Issue 01, 2019
Code Challenge 60 – Working With PDF Files in Python
By PyBites Team on 8 January 2019
Hey Pythonistas, in this challenge you will learn how to work with PDF documents. Enjoy!
Code Challenge 59 – Analyze Podcast Transcripts with NLTK – Part II
By PyBites Team on 8 January 2019
Hey Pythonistas, in this challenge you will expand on the work of PCC58, doing some natural language processing (NLP) on the podcast transcript data you collected. Have fun!