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Recipe: Deep Rebuild 2020
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Name: Deep Rebuild 2020
ID: 103246
Created on: Thu, 01/30/2020 - 06:49
Updated on: Thu, 01/30/2020 - 14:49
Description:

Easier to read for beginners; Dev mode added for using a debugger (like Zerobrane Studio) to step through code locally to learn it more easily.



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Joined: 10/03/2019
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This is a debug-able version of "Tvdl enhanced DRW 3.0.2"

This version offers the following for users who are new to foldit and lua scripting:

1) Added tons of comments and documentation to make it easier to learn foldit scripting and lua coding in general.
2) Changed names of variables and functions to more easily understand their purpose.
3) Increased code spacing to allow easier viewing (especially for those of us over 40 years old).
4) Added debug functions with random return value generation for debugging locally (also as a learning aide).

Visit https://github.com/CottonPatch/foldit for the latest scripts, readme and tips
Visit https://foldit.fandom.com/wiki/EDRW to Learn more about the original script "Tvdl enhanced DRW 3.0.2" by "Timo van der Laan"

Tips:

1) Download and install ZeroBrane Studio to learn how to write and debug Lua scripts, including the Rebuild2020.Lua script.
2) Although ZeroBrane Studio is an awesome Lua development environment, it does not have built-in version control abilities.
3) Only attempt to debug scripts in Visual Studio 2019 (VS-2019) or Visual Studio Code (VS-Code) if you want to get frustrated.
4) Although you can debug Lua scripts in VS-Code (with a free plug-in) it crashes often.
5) You cannot debug lua scripts in VS-2019, but you can check in changes to GitHub directly from VS-2019 (that's what I am doing).
6) See https://github.com/CottonPatch/foldit/blob/master/GithubTips.md for tips on using GitHub within VS-2019

Learn more:
1. See also "Tvdl enhanced DRW 3.1.1" with small fixes and improvements here: https://fold.it/portal/recipe/102840
2. See also a different script approach, "Constructor v1.05" by "Grom" here: https://fold.it/portal/recipe/46192

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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, RosettaCommons