Time to leave the cozy nest of Grasshopper (at least part-time) and explore Python in other friendly places. In Step 4, you’ll practice text-based programming using tools you might already use or easily recognize, like Jupyter Notebooks, Excel, or even specialized AEC web apps like VIKTOR. The idea is to break out of the visual environment gradually, without jumping straight into the deep end.

Jupyter Notebooks are an awesome way to start coding in a textual environment. They run in your browser and let you write Python in small chunks (“cells”) and execute them one by one. You can mix in text, images, even charts. It’s like a diary for your code experiments. For an engineer, this is brilliant: you can document your thought process, see results immediately (tables, graphs, calculations), and still only face bite-sized bits of code at a time.

Then there’s Excel- Yes, the trusty old spreadsheet just got cooler. 📊 Did you know Excel now supports Python formulas (in the latest versions) and there are libraries like openpyxl to manipulate Excel with Python? Instead of complex macros, you can use Python to automate Excel tasks you do daily. For someone already comfortable in Excel, this feels less intimidating than a blank code editor. You’re using Python as a supercharged extension of Excel, rather than a whole new world.

And let’s not forget tools like VIKTOR (a platform that turns scripts into web apps) or Speckle and other AEC-specific tools. Some of these let you use Python to connect different software or create custom web dashboards for your engineering data. Using Python in a context you know (like hooking into your Grasshopper model via a web) makes the learning curve gentle. You’re still solving real AEC problems, just now you’re writing code in text form to do it.

By the end of Step 4, you’ve proven to yourself that you can work with Python on its own and integrate it with your everyday tools. You’re like a fledgling leaving the nest but still flying close to home. The text-based world is no longer scary, and you might even be having a bit of fun showing off a Jupyter graph or two to your team.