Maryanne Wachter m-clare

## built_python.md

      
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                m-clare
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              Created
              March 18, 2019 02:18
            
              
                Built Python
              
          
    built_python

Road map for learning python for those in the built environment. Includes suggested reading for technical audiences, links, relevant projects, and general tips (tba). Currently more general, will add specifics relevant to AEC as time permits.
Suggested repositories

Python reference
General reference and includes Python notebooks (IPython nb) which I'd call a unique cross between MathCAD and programming. These are widely used in the scientific community as "interactive" papers where you can run code within a paper.
Awesome python

  
## USA.json

      
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                m-clare
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              May 2, 2020 22:45
            
              
                SE3 2020 Responses
              
          
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## speckle_systems.md

      
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                m-clare
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              May 10, 2022 16:19
            
              
                Speckle Technical Interview
              
          
    Speckle Technical Interview

Task 1

Build & debug ETABS connectors - review functionality and implementation


Tested against Speckle for ETABS v2.51
Using ETABSv20 (trial version)

Build Info


Successful build (no compile errors)

did have to reset in Visual Studio to target only x64 rather than Any CPU to surpress set of warnings


Compiler warnings (NOTE: significant number of documentation warnings outside of ETABS project / CSI solution - mainly in Core)

CS0162 Unreachable code detected in ConverterCSI.cs


## structures_congress_2023.md

      
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                m-clare
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              June 14, 2022 21:17
            
          
    Structures Congress 2023

Open Source Software within Design Engineering Practice

Abstract

Excel and MathCAD are the major tools of the trade for structural design, but creating transparent design calculations and standard workflows to use across projects remains a challenge. While Excel is well suited for batch calculations, it is difficult to create a step-by-step design narrative. MathCAD is great for illustrative single element calculations (with unit consideration) but lacks a mechanism for batch calculation and table generation needed for design summaries.
Jupyter Notebooks utilizing the Python programming language can offer a free and open source alternative to this design calculation paradigm, allowing for illustrative and idempotent documentation. These workflows are widely used in the data science and scientific communities to create reproducible reports on an approachable platform that does not require extensive programming knowledge. This workshop will show attendees alternate approaches t