change main folder pyhui

[npr99]

change main folder pyhui

[npr99]

search existing package examples
https://anaconda.org/conda-forge/osmnx

[npr99]

https://anaconda.org/search?q=intersect

https://anaconda.org/search?q=ICD
existing packages with names similar to ICD

ICD = Installable Client Driver (ICD) (https://github.com/OCL-dev/ocl-icd)
icdiff - something about identify differences in files using colors (https://www.jefftk.com/icdiff)

[npr99]

Looks like pyicd is already a package:
https://pyicd.readthedocs.io/en/latest/index.html#document-index

Pycid is already a package
https://github.com/causalincentives/pycid

ICD = International Classification of Diseases

[npr99]

https://anaconda.org/search?q=coda

conda-forge / coda 2.24
CODA is the Common Data Access

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r-coda 0.19_4
Provides functions for summarizing and plotting the output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests of convergence to the equilibrium distribution of the Markov chain.

[npr99]

pyncoda might be a good option

https://www.merriam-webster.com/dictionary/coda
Definition of coda
1a: a concluding musical section that is formally distinct from the main structure
b: a concluding part of a literary or dramatic work
2: something that serves to round out, conclude, or summarize and usually has its own interest

[npr99]

the meaning of coda as a concluding section that is distinct from the main structure. Something that serves to round out or summarize. Something that will persuade to engage attention.
The final files of pyncode are the housing unit inventory and person record files, which are distinct from their main source community data structures. The hui and prec files help to summarize the primary source data files, but each version of the hui and prec files have their own interest. For example, one version of the concluding files might show a worse case scenario for underserved populations living in areas of high flood risk. Another version of the concluding files might show a best case scenario for populations living in buildings with low risk to earthquake damage.