Pythoshop - Group 6

[ella-irene]

Submitting Author: Name (@ella-irene) All current maintainers: (@jlee2843, @salva-u, @Rachel0619) Package Name: Pythoshop One-Line Description of Package: Python package designed to provide a set of handy image processing functions for simple yet effective adjustments to images. Repository Link: https://github.com/UBC-MDS/Pythoshop Version submitted: 2.0.0 (Milestone 3) Editor: @ttimbers Reviewer 1: John Shiu Reviewer 2: Wenyu Nie Reviewer 3: Koray Tecimer Reviewer 4: Rachel Bouwer

Archive: TBD JOSS DOI: TBD Version accepted: TBD Date accepted (month/day/year): TBD

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Code of Conduct & Commitment to Maintain Package

• [x] I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
• [x] I have read and will commit to package maintenance after the review as per the pyOpenSci Policies Guidelines.

Description

Pythoshop is a Python package designed to provide a set of handy image processing functions for simple yet effective adjustments to images. Whether you need to tweak brightness, adjust aspect ratios, transform images, or apply filters, Pythoshop has you covered.

Scope

• Please indicate which category or categories. Check out our package scope page to learn more about our scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • [ ] Data retrieval
  • [ ] Data extraction
  • [x] Data processing/munging
  • [ ] Data deposition
  • [ ] Data validation and testing
  • [x] Data visualization[^1]
  • [ ] Workflow automation
  • [ ] Citation management and bibliometrics
  • [ ] Scientific software wrappers
  • [ ] Database interoperability

Domain Specific & Community Partnerships

• [ ] Geospatial
• [ ] Education
• [ ] Pangeo

Community Partnerships

If your package is associated with an existing community please check below:

• [ ] Pangeo
  • [ ] My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook

[^1]: Please fill out a pre-submission inquiry before submitting a data visualization package.

• 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):

  • Who is the target audience and what are scientific applications of this package?
    The target audience of this package is anyone who deals with editing images, from graphic designers to instagram users.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ? There are my other packages which accomplish image transformations, however our package does so without the user needing any knowledge of the underlying functions which wrap existing functions from both Matplotlib and Numpy.

  • 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:

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

• [x] does not violate the Terms of Service of any service it interacts with.
• [x] uses an OSI approved license.
• [x] contains a README with instructions for installing the development version.
• [x] includes documentation with examples for all functions.
• [x] contains a tutorial with examples of its essential functions and uses.
• [x] has a test suite.
• [x] has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

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][JossSubmissionRequirements]. 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][JossSubmissionRequirements]: "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][JossPaperRequirements] with a high-level description in the package root or in `inst/`. - [ ] The package is deposited in a long-term repository with the DOI: *Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.*

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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.

• [x] 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.

Confirm each of the following by checking the box.

• [x] I have read the author guide.
• [ ] I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

Please fill out our survey

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[rbouwer]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• [X] As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• [X] A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• [X] Installation instructions: for the development version of the package and any non-standard dependencies in README.
• [X] Vignette(s) demonstrating major functionality that runs successfully locally.
• [X] Function Documentation: for all user-facing functions.
• [ ] Examples for all user-facing functions.
• [X] Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• [X] Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements The package meets the readme requirements below:

• [X] Package has a README.md file in the root directory.

The README should include, from top to bottom:

• [X] The package name
• [ ] Badges for:
  • [ ] Continuous integration and test coverage,
  • [X] Docs building (if you have a documentation website),
  • [ ] A repostatus.org badge,
  • [ ] Python versions supported,
  • [ ] Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• [X] Short description of package goals.
• [X] Package installation instructions
• [X] Any additional setup required to use the package (authentication tokens, etc.)
• [X] Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • [X] Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• [X] Link to your documentation website.
• [X] If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
• [X] Citation information

Usability

Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole. Package structure should follow general community best-practices. In general please consider whether:

• [X] Package documentation is clear and easy to find and use.
• [X] The need for the package is clear
• [X] All functions have documentation and associated examples for use
• [X] The package is easy to install

Functionality

• [X] Installation: Installation succeeds as documented.
• [X] Functionality: Any functional claims of the software been confirmed.
• [X] Performance: Any performance claims of the software been confirmed.
• [X] Automated tests:
  • [X] All tests pass on the reviewer's local machine for the package version submitted by the author. Ideally this should be a tagged version making it easy for reviewers to install.
  • [X] Tests cover essential functions of the package and a reasonable range of inputs and conditions.
• [X] Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• [X] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines. A few notable highlights to look at:
  • [X] Package supports modern versions of Python and not End of life versions.
  • [X] Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

For packages also submitting to JOSS

• [ ] The package has an obvious research application according to JOSS's definition in their submission requirements.

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md matching JOSS's requirements with:

• [ ] A short summary describing the high-level functionality of the software
• [ ] Authors: A list of authors with their affiliations
• [ ] A statement of need clearly stating problems the software is designed to solve and its target audience.
• [ ] References: With DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

• [ ] The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing: 1 hr

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Review Comments

Documentation

• Vignette: The vignette looks great - I enjoyed the “Motivation” section and thought that it provided a good overview of why this package would be useful. I thought the flow was very good from section to section. One note on consistency would be that all of the function sections except for resize_image have “Before change” and “After change” code sections. The content is there but it may be worth adding these headers to the resize_image section to maintain consistent formatting.
• Examples: adjust_brightness is missing an “Example” section (resize_image has the section but it is not formatted in the same way as apply_filter & transform_image seems to also have the “Example” but it is embedded along with some raises >>> prefixes)
  • Also, the example in transform_image seems to call adjust_aspect_ratio instead of transform_image).
• Badges: You guys have the ‘Docs building’ badge but could add the other badges listed above (Continuous integration and test coverage, repostatus badge, Python versions supported badge, current package version badge)
• Function Documentation: All the functions have documentation! However, some of the documentation formatting is not consistent when compared to the other functions (notably, resize_image - it seems like the sections were not formatted in the same way having “headers” but is instead more like a paragraph-style). Maybe you could have all four functions formatted how apply_filter and adjust_brightness are currently formatted (as it also seems like transform_image is slightly different as well)
• Installation Instructions:
  • Very thorough! I liked how you included the Anaconda & installer sections as well
  • It may be helpful to explicitly tell the user to conda install poetry after creating the virtual environment (i.e. after step 2) in addition to the blurb above about general poetry installation to make the instructions super super clear
  • All functions worked great when I ran them myself!
• Tests: Could include “Testing” section in README (or add a .md file in the tests/ folder) to give instructions on testing
  • All tests pass though!
  • I ran pytest tests/ --cov to see the coverage of the tests. Coverage looks good - if you have time you could run this command (with -cov-report term-missing) appended to see lines that could still be covered by more testing!

Overall, great package! I love how it simplifies otherwise daunting image processing in an easily digestible way!

[JohnShiuMK]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• [x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• [x] A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• [x] Installation instructions: for the development version of the package and any non-standard dependencies in README.
• [x] Vignette(s) demonstrating major functionality that runs successfully locally.
• [x] Function Documentation: for all user-facing functions.
• [x] Examples for all user-facing functions.
• [x] Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• [x] Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements The package meets the readme requirements below:

• [x] Package has a README.md file in the root directory.

The README should include, from top to bottom:

• [x] The package name
• [ ] Badges for:
  • [ ] Continuous integration and test coverage,
  • [x] Docs building (if you have a documentation website),
  • [ ] A repostatus.org badge,
  • [x] Python versions supported,
  • [x] Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• [x] Short description of package goals.
• [x] Package installation instructions
• [NA] Any additional setup required to use the package (authentication tokens, etc.)
• [x] Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • [x] Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• [x] Link to your documentation website.
• [x] If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
• [x] Citation information

Usability

Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole. Package structure should follow general community best-practices. In general please consider whether:

• [x] Package documentation is clear and easy to find and use.
• [x] The need for the package is clear
• [x] All functions have documentation and associated examples for use
• [x] The package is easy to install

Functionality

• [x] Installation: Installation succeeds as documented.
• [x] Functionality: Any functional claims of the software been confirmed.
• [x] Performance: Any performance claims of the software been confirmed.
• [x] Automated tests:
  • [x] All tests pass on the reviewer's local machine for the package version submitted by the author. Ideally this should be a tagged version making it easy for reviewers to install.
  • [x] Tests cover essential functions of the package and a reasonable range of inputs and conditions.
• [x] Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• [x] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines. A few notable highlights to look at:
  • [x] Package supports modern versions of Python and not End of life versions.
  • [x] Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

For packages also submitting to JOSS

• [ ] The package has an obvious research application according to JOSS's definition in their submission requirements.

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md matching JOSS's requirements with:

• [ ] A short summary describing the high-level functionality of the software
• [ ] Authors: A list of authors with their affiliations
• [ ] A statement of need clearly stating problems the software is designed to solve and its target audience.
• [ ] References: With DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

• [x] The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing:

---

Review Comments

• Tutorials on ReadtheDocs: Under the VIGNETTES section in the left panel, both the "Pythoshop Tutorial" and "Motivation for building this package:" are pointing to the same page, which seems unintentional. Adjusting the header from "#" to "##" in the example.ipynb file for "Motivation for building this package:" will resolve this issue.
• Environment Considerations: Suggest adding Poetry (and Python) to a Conda environment file, so to facilitate easier installation via conda create -f environment.yml.
• Large Amount of Data: There's a substantial volume of data under docs/img/. Consider either reducing the number of examples / compressing(zip) the images / downsizing them to enhance efficiency.
• File Not Found Issue in Example Notebook: In the example.ipynb, it appears that the file "docs/img/data/CN9A4560.jpg_brightness_changed.jpg_brightness_changed.png" is missing / not generated. So the code snippet under the section "Adjust Brightness, Apply Filters, and Resize Images" fails to execute as intended:

  #Apply Filters to Images
  for image in image_files:
     apply_filter(image_directory+image[:-4]+".jpg_brightness_changed.png", "red", degree=0.6)

• Overall Impression: Other than the minor issues mentioned above, the package demonstrates considerable promise. The package description is engaging, and the logo design is visually appealing. This package has the potential to greatly enhance image processing workflows.

[korayt]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• [x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• [x] A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• [x] Installation instructions: for the development version of the package and any non-standard dependencies in README.
• [x] Vignette(s) demonstrating major functionality that runs successfully locally.
• [x] Function Documentation: for all user-facing functions.
• [x] Examples for all user-facing functions.
• [x] Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• [x] Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements The package meets the readme requirements below:

• [x] Package has a README.md file in the root directory.

The README should include, from top to bottom:

• [x] The package name
• [ ] Badges for:
  • [ ] Continuous integration and test coverage,
  • [x] Docs building (if you have a documentation website),
  • [x] A repostatus.org badge,
  • [x] Python versions supported,
  • [ ] Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• [x] Short description of package goals.
• [x] Package installation instructions
• [x] Any additional setup required to use the package (authentication tokens, etc.)
• [x] Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • [x] Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• [x] Link to your documentation website.
• [x] If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
• [x] Citation information

Usability

Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole. Package structure should follow general community best-practices. In general please consider whether:

• [x] Package documentation is clear and easy to find and use.
• [x] The need for the package is clear
• [x] All functions have documentation and associated examples for use
• [x] The package is easy to install

Functionality

• [x] Installation: Installation succeeds as documented.
• [x] Functionality: Any functional claims of the software been confirmed.
• [x] Performance: Any performance claims of the software been confirmed.
• [x] Automated tests:
  • [x] All tests pass on the reviewer's local machine for the package version submitted by the author. Ideally this should be a tagged version making it easy for reviewers to install.
  • [x] Tests cover essential functions of the package and a reasonable range of inputs and conditions.
• [x] Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• [x] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines. A few notable highlights to look at:
  • [x] Package supports modern versions of Python and not End of life versions.
  • [ ] Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

For packages also submitting to JOSS

• [ ] The package has an obvious research application according to JOSS's definition in their submission requirements.

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md matching JOSS's requirements with:

• [ ] A short summary describing the high-level functionality of the software
• [ ] Authors: A list of authors with their affiliations
• [ ] A statement of need clearly stating problems the software is designed to solve and its target audience.
• [ ] References: With DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

• [x] The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing: 1

---

Review Comments

• Documentation looks very well-written and elaborate. Functions themselves look good according to defensive programming. Installation instructions are very clear (industry grade). Package illustration is solid
• adjust_brightness function does not contain an example in documentation. Also you might want to delete commented out code.
• There are unused imports in the function definitions.
• When performing the tests I needed to manually close the opened window for the images. Tests should complete without me interacting. I'm not sure if this was the case for other machines. I'm using Pycharm IDE, MacOS Ventura.
• Images used in tests should be in a folder called resources.

[wenyunie]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• [x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

• [x] A statement of need clearly stating problems the software is designed to solve and its target audience in README.
• [x] Installation instructions: for the development version of the package and any non-standard dependencies in README.
• [x] Vignette(s) demonstrating major functionality that runs successfully locally.
• [x] Function Documentation: for all user-facing functions.
• [x] Examples for all user-facing functions.
• [x] Community guidelines including contribution guidelines in the README or CONTRIBUTING.
• [x] Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a pyproject.toml file or elsewhere.

Readme file requirements The package meets the readme requirements below:

• [x] Package has a README.md file in the root directory.

The README should include, from top to bottom:

• [x] The package name
• [ ] Badges for:
  • [ ] Continuous integration and test coverage,
  • [x] Docs building (if you have a documentation website),
  • [ ] A repostatus.org badge,
  • [x] Python versions supported,
  • [x] Current package version (on PyPI / Conda).

NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• [x] Short description of package goals.
• [x] Package installation instructions
• [ ] Any additional setup required to use the package (authentication tokens, etc.)
• [x] Descriptive links to all vignettes. If the package is small, there may only be a need for one vignette which could be placed in the README.md file.
  • [x] Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)
• [x] Link to your documentation website.
• [x] If applicable, how the package compares to other similar packages and/or how it relates to other packages in the scientific ecosystem.
• [x] Citation information

Usability

Reviewers are encouraged to submit suggestions (or pull requests) that will improve the usability of the package as a whole. Package structure should follow general community best-practices. In general please consider whether:

• [x] Package documentation is clear and easy to find and use.
• [x] The need for the package is clear
• [x] All functions have documentation and associated examples for use
• [ ] The package is easy to install

Functionality

• [x] Installation: Installation succeeds as documented.
• [x] Functionality: Any functional claims of the software been confirmed.
• [x] Performance: Any performance claims of the software been confirmed.
• [ ] Automated tests:
  • [x] All tests pass on the reviewer's local machine for the package version submitted by the author. Ideally this should be a tagged version making it easy for reviewers to install.
  • [ ] Tests cover essential functions of the package and a reasonable range of inputs and conditions.
• [ ] Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• [x] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines. A few notable highlights to look at:
  • [x] Package supports modern versions of Python and not End of life versions.
  • [x] Code format is standard throughout package and follows PEP 8 guidelines (CI tests for linting pass)

For packages also submitting to JOSS

• [ ] The package has an obvious research application according to JOSS's definition in their submission requirements.

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md matching JOSS's requirements with:

• [ ] A short summary describing the high-level functionality of the software
• [ ] Authors: A list of authors with their affiliations
• [ ] A statement of need clearly stating problems the software is designed to solve and its target audience.
• [ ] References: With DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

• [ ] The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing: 2 hours

Review Comments

Thank you so much for presenting me a wonderful project like this one, I think this is an awesome and impressive project, there are a couple of points I would like to highlight:

1. The readme documentation of the project is pretty eye-catching and exhaustive. I am able to find every link regarding documentation, installation, and usage in the document. Especially important is the installation guide for the developer version (which our group forgot to specify. Learning from you guys)

2. One thing I see that could be improved is the size of your project. It seems there are some very large files in the project and maybe you guys can find some alternative ways to store them so that the project clone process can speed up.

3. The sphinx documentation of your project has a style in it. However, the structure of the tree of contents is a little bit confusing. Basic usage of the package does not seem to be supposed to be under the motivation for this package:

   

4. There is one hurdle when I was installing the package using the developer's version. After activating the environment, I actually needed to install poetry again in the new env. This is not specified and I actually need to figure it out myself.

5. The test functions are thorough in general. If you would want to have more, there can be more visual regression testing for the functions since you are working with plotting functions and the outputs are images mostly.

6. The testing process is mostly smooth. I was able to pass all tests with a simple pytest command line. However, I see there are some image files popping up when the tests are running, which are something exterior developers would not expect when they are trying to run the tests of your package.

7. Last but not least, I really like the styling and all the logos and pictures you have with your project. Together with the skilled usage of status badges, your project really seems hardcore.