Hi, welcome to Python for Academics! 🐍 → 🎓

Python for Academics is a series of coding tutorials where you will learn how to automate your everyday academic life with Python!

tl;dr: My goal is to help you save time and grant money by automating dull tasks!

My goal is to provide you with extra tools and ideas that you haven't thought about using or implementing before. The best use of these tutorials, as I see it, is that you take those tools and ideas and start building your own Python toolbox that can help you in your everyday academic life. My hope is that you'll find pieces of useful advice that can help you automate your work, your own way!

The audience I think will benefit a lot from these tutorials are Ph.D. students, especially at the beginning of their Ph.D. I believe that the earlier you learn how to automate dull tasks the better! My motivation is to teach you things that I wish I had learned early in my Ph.D. But, of course, academics at all stages of their careers are welcome to join along! 🙂

I'm assuming that you have some exposure to Python and have used Python before, at least a little bit. Thus, I will not be explaining Python from scratch in this series. There's plenty of materials for that out there already! However, I am going to explain the bits of the code as we go. I invite you to check and learn things on your own here and there to expand on what I do not cover. Since you're an academic, I'm confident that this approach will work out well!

You can access all video tutorials from the YouTube playlist:

Video tutorials & Jupyter notebooks

Below, you'll find links to all videos and the associated Jupyter notebooks. You can pick any topic you'd like first!

1️⃣ Automating your life with list comprehensions

→ 💻 Jupyter notebook

• 📹 5 min: Generate large column headers with list comprehensions

• 📹 6 min: Generate large row headers with list comprehensions

• 📹 5 min: Import row headers from an external file

• 📹 6 min: Create permutations of lab cases text

• 📹 6 min: Generate multiple terminal commands

2️⃣ Processing files

→ 💻 Jupyter notebook

• 📹 12 min: Append a prefix to a file name

• 📹 10 min: Remove a phrase from a file name using regular expressions library

• 📹 4 min: File name to lowercase

3️⃣ Documenting research

→ 💻 Jupyter notebook

• 📹 8 min Generate README.md files automatically

• 📹 8 min Expand your README.md file with code info

• 📹 11 min Organize your results into LaTeX tables

4️⃣ Managing bibliography with regular expressions

→ 💻 Jupyter notebook

• 📹 16 min Count bibliographic items

• 📹 6 min List .bib items tags

• 📹 8 min Find duplicate references

• 📹 11 min Remove duplicate references

• 📹 12 min How many times is it cited?

• 📹 Order .bib items by year of publication

• 📹 Generate a literature review table from a .bib file

5️⃣ Postprocessing results

→ 💻 Jupyter notebook

• 📹 14 min Prepare your script for asynchronously arriving data

• 📹 14 min Setting numeric parameters of a Python script from the command line

• 📹 4 min Setting boolean parameters of a Python script from the command line

6️⃣ Things to watch out for

→ 💻 Jupyter notebook

• 📹 4 min Avoid research mistakes by safely appending to a list

7️⃣ Managing figures

→ 💻 Jupyter notebook

8️⃣ Testing scientific software

→ 💻 Jupyter notebook

Scripts

You can access the toolbox of ready scripts in the scripts directory. Feel free to copy and modify them for your target use case!

The video tutorials and Jupyter notebooks explain step-by-step how the scripts have been built.

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