… by using a very wild script from dp Stuff!

Comes with a disclaimer:
Warning! Make sure you don’t run this script on your central model – detach it from central first. Because once the views are gone – they are GONE! Don’t tell me that I didn’t warn you – use it at your own risk.
Download Revit IronPython Shell script
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dp Stuff: Remove Working Views With Python Shell and Revit API

I have previously posted about RevitPythonShell a number of times. In this post Dima Chiriacov gives a real-world example on using the shell to change the case of text.

There are quite a number of free add-ins which can easily change case too, like this one or this one (which also allows merging of text).

Read how to use RevitPythonShell at:
DP stuff: Convert Revit Text to Upper Case

Nathan Miller strikes again:
I am creating a strange ‘catenary’ surface with Kangaroo and Grasshopper.  I am then feeding the information into an Excel spreadsheet and reconstructing the shape using Adaptive Components via RevitPythonShell.  Note how I am also able to adjust the radius parameter of the pipe members within Revit to reflect the ‘force’ diagram created in Kangaroo.

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The Proving Ground by Nathan Miller: Revit API: Divided Surfaces and Excel Interop

This post looks at the post-processing side of the energy modeling workflow. Often, a spreadsheet tool like Excel is a first choice for many analysis tasks. This is great for simple cases, but if the number of files or the amount of data is large or complex, Excel will cost you time and lead to errors. This is where you should turn to Python! 

Read more at:
Python for Energy Modelers – Part 3 – Simple Post-processing | openRevit

I have previously posted about Python and Revit (including revitpythonshell ) here.

There are some very detailed posts coming from openRevit about using Python in Energy Modeling.  Check them out:

Python for Energy Modelers – Part 1 | openRevit
This even shows you how to install it…

Python for Energy Modelers – Part 2 – Simple Pre-processing | openRevit
This focuses on some basic simulation scenarios.  Quote:

  1. Identify in your simulation workflow something that you need to do manually many times for each simulation, or something you need to do for each of your many simulations. If you can write the problem down in one sentence, it’s a great candidate for scripting.
  2. Next, break up the problem into many small simple steps, this is your pseudocode.
  3. Now try to write it out in Python. Remember, Google is your best friend, if you have a question about something in Python, chances are there have been hundreds of others out there with the same question!
  4. Finally, once it all works, clean up and comment your code, think about how you or someone else might use it in a year!