py_regular_expressions VS plotly

These exercises have been adapted from my Understanding Python re(gex)? ebook (free to read online).

This new version is a TUI app built with Textual. Previous one was written using `tkinter` [0] and covered only four of the `re` functions.

Now, any valid Python expression is accepted as a solution. Both the builtin `re` and third-party `regex` modules are covered.

These exercises have been adapted from my Understanding Python re(gex)? ebook [1] (free to read online, and PDF/EPUB versions are free till the end of this month).

I'd appreciate your feedback, happy learning :)

[0] https://news.ycombinator.com/item?id=29391107

[1] https://github.com/learnbyexample/py_regular_expressions

Visit https://github.com/learnbyexample/py_regular_expressions for markdown source, example files, exercise solutions, sample chapters and other details related to the book.

Last year, I did a similar project for 75 Python regular expressions exercises: https://github.com/learnbyexample/py_regular_expressions/tre...

That was with Tkinter. I'm planning to update the regex book next year (to add new features like possessive quantifiers and other misc changes). Along with this update, I'll probably make a TUI version and add support for rest of the exercises.

If you are interested in Python regex, here's my tkinter app with 75 interactive exercises: https://github.com/learnbyexample/py_regular_expressions/tre...

This assumes you already know Python regex. If you'd like learn first, see my free ebook: https://learnbyexample.github.io/py_regular_expressions/

I have an entire book dedicated for learning regex from the basics, with hundreds of examples and exercises. I cover both re and third-party regex module. It is free to read online: https://learnbyexample.github.io/py_regular_expressions/

A tkinter GUI that helps you to practice your understanding of regular expressions with 75 exercises: https://github.com/learnbyexample/py_regular_expressions/tree/master/interactive_exercises

https://github.com/learnbyexample/py_regular_expressions/blob/master/py_regex.md.

Github: https://github.com/plotly/plotly.py

First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.

my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.

Plotly documentation (https://plotly.com/python/)

I don´t know your workflow, but I use 2 markdown based presentations: obsidian advance slides and Quarto presentations. The former is a plugin for Obsidian, which is the software I use to take all my notes, write my thesis, etc., so It makes it extremely easy to make presentations since all my information is in Obsidian. In the other hand, Quarto is a publishing system (articles, presentations, websites books) that can be easily integrated with python and R. This makes it supper convenient for showing my data to my PI since I can analyze my data and at the same time make a presentation for the data. Besides this, Quarto also integrates with my Zotero library, so I can insert citations. Lastly, one thing that made my Quarto presentations infinitely better that the powerpoints, Is that I can insert interactive graphs with plotly, so when I'm showing my data, my PI is able to explore the data inside the presentation.

Plotly GitHub repository: https://github.com/plotly/plotly.py

I'm using plotly.py now. This is why I love this community.

Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.