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Description
Submitting Author: @etam4260
Package Name: hudpy
One-Line Description of Package: A Python Interface to the US Department of Housing and Urban Development APIs
Repository Link: https://github.com/etam4260/hudpy
Version submitted: 0.2.0
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
Version accepted: TBD
Description
- Include a brief paragraph describing what your package does:
Currently the R version is under peer review at ROpenSci:
ropensci/software-review#524
This package is a mapped over version from R to Python.
This package gives users access to the US Department of Housing and Urban Development APIs
available at HUD User:
https://www.huduser.gov/hudapi/public/login
This also has additional wrappers onto of the data provided from these APIs to determine if US geographies intersect
based on addresses and (cross walking a US dataset) explained in this paper below:
Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S.
Department of Housing and Urban Development’s ZIP Code Crosswalk Files,”
Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277
https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf
Scope
- Please indicate which category or categories this package falls under:
- Data retrieval
- Data extraction
- Data munging
- Data deposition
- Reproducibility
- Geospatial
- Education
- Data visualization*
Please fill out a pre-submission inquiry before submitting a data visualization package. For more info, see notes on categories of our guidebook.
NA
- For all submissions, explain how the and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):
It is a data retrieval package because it retrieves data from an API. It is data munging package because it implements the concept of cross walking a file (converting a dataset described in one US geographic identifier into another) explained in the paper mentioned above.
- Who is the target audience and what are scientific applications of this package?
I am hoping to reach professors, researchers, and students with this package. This gives access to the crosswalk files which is a geospatial technique described very well in these journal articles:
Din, Alexander and Wilson, Ron, 2020. “Crosswalking ZIP Codes to Census Geographies: Geoprocessing the U.S. Department of Housing & Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 22, Number 1, https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf
Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294.
- Are there other Python packages that accomplish the same thing? If so, how does yours differ?
Not any that I know of.
- If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or
@tag
the editor you contacted:
NA
Technical checks
For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:
- does not violate the Terms of Service of any service it interacts with.
- has an OSI approved license.
- contains a README with instructions for installing the development version.
- includes documentation with examples for all functions.
- contains a vignette with examples of its essential functions and uses.
- has a test suite.
- has continuous integration, such as Travis CI, AppVeyor, CircleCI, and/or others.
In terms of vignette, I am assuming you are referring to a Jupyter notebook style documentation. I don't have this, but
there is a website with vignette like documentation: https://etam4260.github.io/hudpy/build/html/index.html
Publication options
- Do you wish to automatically submit to the Journal of Open Source Software? If so:
JOSS Checks
- The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
- The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
- The package contains a
paper.md
matching JOSS's requirements with a high-level description in the package root or ininst/
. - The package is deposited in a long-term repository with the DOI:
Note: Do not submit your package separately to JOSS
Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?
This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.
- Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.
Code of conduct
- I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.
P.S. *Have feedback/comments about our review process? Leave a comment here
I feel like there should be a section for details that might not fit into any of the questions above.
Currently my package does not implement caching, but the skeleton code is currently in the module for future
implementation. It will work similar to the caching implemented in the rhud package currently being reviewed by ROpenSci.
I have not looked into the PEP 8 style guide yet, but will make sure to review that.