Group 18 - OLS Regressor

[charlesxch]

Submitting Author: Charles Xu (@charlesxch) All current maintainers: Yimeng Xia, Sifan Zhang, Waleed Mahmood(@yimengxia, @sifanzzz, @WaleedMahmood1) Package Name: OLS Regressor One-Line Description of Package: The OLS Regression Package is a Python library designed to streamline the process of performing Ordinary Least Squares (OLS) regression analysis. Repository Link: https://github.com/UBC-MDS/OLS_regressor Version submitted: 0.3.0 Editor: Tiffany Timbers Reviewer 1: Weiran Zhao Reviewer 2: Alysen Townsley
Reviewer 3: Jerry Yu Reviewer 4: Zeily Garcia
Archive: TBD JOSS DOI: TBD Version accepted: TBD Date accepted (month/day/year): TBD

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[jy1909]

Package Review

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

---

Review Comments

Overall, nicely designed package with especially detailed usage instructions in the vignette. It not only demonstrates how to use the functions, but also is being quite technical especially when it comes to the metrics. Just a few things:

• The docstring for the .fit() method is missing.
• I recommend adding examples to the docstrings.
• I would recommend including metadata for all authors in pyproject.toml.
• According to the checklist, README.md needs more badges.
• I would recommend adding a usage section in inREADME.md. It is currently lacking demonstration of usage of the functions or a link to the vignette.
• I am encountering errors when pip installing package (following the instruction on README.md):
  • ERROR: Could not find a version that satisfies the requirement ols_regressor (from versions: none)
  • ERROR: No matching distribution found for ols_regressor
  • I see that you have the installation instruction of using poetry in CONTRIBUTING.md. This instruction works, but should be reflected in the installation instructions in README.md as well since using pip to install does not seem to work at the moment.
• Please set up CI-CD. The ci-cd.yml file is missing.
• I would recommend test for code coverage if this has not been done already since I do not see pytest-cov in the pyproject.toml file.

[AlysenTownsley]

Package Review

**Note:

• Comment: refers to general comments / review feedback.

• Fix: refers to a concern for the team to fix (or consider fixing) for this milestone.**

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.

• Comment: Included in ReadMe.

• [x] Installation instructions: for the development version of the package and any non-standard dependencies in README.

• Comment: Included in ReadMe.

• [ ] Vignette(s) demonstrating major functionality that runs successfully locally.

• Comment: Your vignette is excellent – it’s very well written and informative. It’s clear that you put a lot of work into this. Great work!!

• Fix: Your latex equations for the R^2 at the end of your vignette did not render properly in ReadTheDocs.

• Fix: Cell 6 is quite a large code block for a beginner to understand. Recommend adding a comment before each step to link with the list of steps in the markdown cell above and improve readability.

(ex/ “# 1. Extract categorical features:

categorical_features = ['Brand', 'UsedOrNew', 'Transmission', 'DriveType', 'FuelType', 'BodyType', 'ExteriorColour']...”

• Fix: Several spelling errors (recommend passing through an editing tool).

• [ ] Function Documentation: for all user-facing functions.

• Comment: Excellent use of error statements for exception handling in cross_validate.py.

• Fix: cross_validate.py - The code is difficult to read (minimal spacing between lines or comments to explain what the code is doing in each step ex/ exception handling vs. scoring / timing the model).

• Fix: regressor.py - docstrings are required for all class methods including init() and fit().

• Comment: The comments are well done in the regressor.py script and it is easy to read.

• [ ] Examples for all user-facing functions.

• Fix: cross_validate.py does not have an example of the function inputs/ outputs in the docstring.

• [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.

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The package meets the readme requirements below:

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

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• [ ] Badges for:

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• Fix: Does not include code coverage – need to add the badge for this.

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• Fix: Does not include repo status – need to add the badge for this.

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• Fix: Does not include supported python versions – need to add the badge for this.

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• Fix: Does not include current package versions – need to add the badge for this.

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.)

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  • [ ] Brief demonstration of package usage (as it makes sense - links to vignettes could also suffice here if package description is clear)

• Fix: Include a usage section in the ReadMe.

• [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.

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• Comment: If any citations are required, make sure to include them.

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

• [ ] All functions have documentation and associated examples for use

• Comment: see above comments in the function documentation and example sections.

• [ ] The package is easy to install

• Fix: I was not able to install the package - more details below.

Functionality

• [ ] Installation: Installation succeeds as documented.

• Fix: Following your installation instructions on the ReadMe throws an error (i.e. pip install ols_regressor doesn’t work). I assume this is because the package is not yet on pypi? Also, there are no commands to install a virtual environment to run the code / install the dependencies.

• Fix: No instructions on how to run pytest.

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  • [ ] 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.

• Fix: I couldn’t run the tests, as I couldn’t install the package from the ReadMe instructions. Recommend to double check that your tests are working.

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• Comment: test scripts have good coverage.

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• Fix: CI workflow has not been set up in Github actions.

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  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)

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

Overall, the package is very well done, especially your vignette and test scripts! I have no major concerns, except that I was not able to install the package and run the tests/scripts locally. Let me know if you need help testing this as you work on this week’s milestone. 😊

All suggested fixes are available for your review in the relevant sections above (see Fix:). If you have any questions or concerns, please feel free to reach out!

[weiranzhao97]

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.
• [ ] 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
• [x] Badges for:
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  • [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.
• [ ] 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
• [ ] All functions have documentation and associated examples for use
• [x] The package is easy to install

Functionality

• [ ] 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.
• [ ] 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:

---

Review Comments

1. Could include example at the end of docstring of functions for clarity and guidance
2. There is lack of instructions over installation and testing in README
3. It is preferred to also include example of usage code in README
4. The example document is easy to understand and in detail. Personally It would be better to simplify the titles as name of the functions (e.g. Scoring() rather than 'Scoring the Fitted Model'; Predict() instead of 'Predicting with the Fitted Model'). So that I can get to the corresponding func that I have problem with instead of looking through the whole example.
5. It is preferred to include a one-line docstring for test functions.

[zgarciaj]

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.
• [ ] 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
• [x] Badges for: (The required badge was present)
  • [ ] 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.
• [ ] 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.
  • [ ] 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
• [ ] 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.
• [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.
• [ ] Continuous Integration: Has continuous integration setup (We suggest using Github actions but any CI platform is acceptable for review)
• [ ] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines. A few notable highlights to look at:
  • [ ] 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)

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 hour 45 minutes

---

Review Comments

The package is exceptionally well-made, with its functions, vignettes, and test scripts standing out. The effort put into developing the functions is evident. Additionally, the package's overall design is very well done. The vignette is particularly informative, offering comprehensive usage instructions and effectively highlighting the features' functionality with a focus on technical metrics. However, there are some areas that could benefit from further attention:

1. The file lacks an example for the cross_validate function. It would be helpful to include this for completeness. Also, the file is missing the docstring for the fit function.

2. The vignette is very well done, as it clearly demonstrates the functions' capabilities and their practical real-world applications. The definitions/explanations of different feature types are particularly helpful for beginners. However, the final section of the vignette needs revision since the LaTeX equations for R^2 are not displaying correctly on ReadTheDocs. Additionally, a thorough review of the text for any grammatical or spelling errors is advisable.

3. While I successfully installed the package, the installation instructions could be more beginner-friendly. It would be beneficial to start with guidance on cloning the repository using Git, followed by steps for installing Poetry, and ending with the pip install process. Further, adding a usage section in your README would enhance clarity and provide better guidance.

4. After installing the package and running Pytest, although all tests passed, a warning message appeared. This may be due to the lack of instructions for setting up a virtual environment and installing necessary dependencies. Including a section on dependencies in the README would be advantageous.

[charlesxch]

Hi @jy1909 . Thank you for your review. We made the several changes based on your suggestions.

• The docstring for the .fit() method is missing.

We added the docstring to the method. (https://github.com/UBC-MDS/OLS_regressor/issues/67)

• I recommend adding examples to the docstrings.

All docstrings now contain examples to illustrate. (https://github.com/UBC-MDS/OLS_regressor/issues/68)

• I would recommend including metadata for all authors in pyproject.toml.

All author names are included in the toml file right now. (https://github.com/UBC-MDS/OLS_regressor/issues/73)

• According to the checklist, README.md needs more badges.

We have more badges righe now in the README.md. (https://github.com/UBC-MDS/OLS_regressor/issues/70)

• I would recommend adding a usage section in inREADME.md. It is currently lacking demonstration of usage of the functions or a link to the vignette.

A usage section is added, with some simple illustration on the functions we defined. (https://github.com/UBC-MDS/OLS_regressor/issues/66)

• I am encountering errors when pip installing package (following the instruction on README.md):

  • ERROR: Could not find a version that satisfies the requirement ols_regressor (from versions: none)
  • ERROR: No matching distribution found for ols_regressor
  • I see that you have the installation instruction of using poetry in CONTRIBUTING.md. This instruction works, but should be reflected in the installation instructions in README.md as well since using pip to install does not seem to work at the moment.

The error is bucause we did not publish the package onto PyPI at the time you were tring do intall. It is now available.

• Please set up CI-CD. The ci-cd.yml file is missing.

Done with it. (https://github.com/UBC-MDS/OLS_regressor/issues/65)

• I would recommend test for code coverage if this has not been done already since I do not see pytest-cov in the pyproject.toml file.

It is now added to the toml file. (https://github.com/UBC-MDS/OLS_regressor/issues/74)

[charlesxch]

Hi @AlysenTownsley . Thank you for your review. We made the several changes based on your suggestions.

Fix: Your latex equations for the R^2 at the end of your vignette did not render properly in ReadTheDocs.

We removed the latex in the notebook. It seems that the Sphinx cannot read our latex.

Fix: Cell 6 is quite a large code block for a beginner to understand. Recommend adding a comment before each step to link with the list of steps in the markdown cell above and improve readability.

Some break-down comments are added. (https://github.com/UBC-MDS/OLS_regressor/issues/80)

Fix: Several spelling errors (recommend passing through an editing tool).

We passed all words to Grammarly and then fix the spelling errors. (https://github.com/UBC-MDS/OLS_regressor/issues/79)

Fix: cross_validate.py - The code is difficult to read (minimal spacing between lines or comments to explain what the code is doing in each step ex/ exception handling vs. scoring / timing the model).

More space and comments are added to the file. (https://github.com/UBC-MDS/OLS_regressor/issues/69)

Fix: regressor.py - docstrings are required for all class methods including init() and fit(). Fix: cross_validate.py does not have an example of the function inputs/ outputs in the docstring.

Docstrings and examples are added. (https://github.com/UBC-MDS/OLS_regressor/issues/67)

Fix: Does not include code coverage – need to add the badge for this. Fix: Does not include repo status – need to add the badge for this. Fix: Does not include supported python versions – need to add the badge for this. Fix: Does not include current package versions – need to add the badge for this.

Badges are added. (https://github.com/UBC-MDS/OLS_regressor/issues/70)

Fix: Include a usage section in the ReadMe.

A usage section is added, with some simple illustration on the functions we defined. (UBC-MDS/OLS_regressor#66)

Fix: I was not able to install the package - more details below. Fix: I couldn’t run the tests, as I couldn’t install the package from the ReadMe instructions. Recommend to double check that your tests are working.

The error is bucause we did not publish the package onto PyPI at the time you were tring do intall. It is now available.

Fix: No instructions on how to run pytest.

Done with it. (https://github.com/UBC-MDS/OLS_regressor/issues/81)

Fix: CI workflow has not been set up in Github actions.

Done with it. (UBC-MDS/OLS_regressor#65)

[charlesxch]

Hi @weiranzhao97 . Thank you for your review. We made the several changes based on your suggestions.

It is preferred to also include example of usage code in README

A usage section is added, with some simple illustration on the functions we defined. (https://github.com/UBC-MDS/OLS_regressor/issues/66)

The example document is easy to understand and in detail. Personally It would be better to simplify the titles as name of the functions (e.g. Scoring() rather than 'Scoring the Fitted Model'; Predict() instead of 'Predicting with the Fitted Model'). So that I can get to the corresponding func that I have problem with instead of looking through the whole example.

Thank you for your thoughtful suggestion on simplifying the titles in our example document. We've opted to retain the more descriptive titles to support a story-telling approach that enriches the learning experience, believing it provides clear and comprehensive guidance. However, we appreciate your input and will consider ways to enhance navigability in future updates to accommodate quicker reference needs.

It is preferred to include a one-line docstring for test functions.

The docstrings are added now. (https://github.com/UBC-MDS/OLS_regressor/issues/83)

[charlesxch]

Hi @zgarciaj . Thank you for your review. We made the several changes based on your suggestions.

The file lacks an example for the cross_validate function. It would be helpful to include this for completeness. Also, the file is missing the docstring for the fit function.

Docstrings and examples are added to the functions. (https://github.com/UBC-MDS/OLS_regressor/issues/67, https://github.com/UBC-MDS/OLS_regressor/issues/68)

The vignette is very well done, as it clearly demonstrates the functions' capabilities and their practical real-world applications. The definitions/explanations of different feature types are particularly helpful for beginners. However, the final section of the vignette needs revision since the LaTeX equations for R^2 are not displaying correctly on ReadTheDocs. Additionally, a thorough review of the text for any grammatical or spelling errors is advisable.

We removed the latex in the notebook. It seems that the Sphinx cannot read our latex. We passed all words to Grammarly and then fix the spelling errors. (https://github.com/UBC-MDS/OLS_regressor/issues/79)

While I successfully installed the package, the installation instructions could be more beginner-friendly. It would be beneficial to start with guidance on cloning the repository using Git, followed by steps for installing Poetry, and ending with the pip install process. Further, adding a usage section in your README would enhance clarity and provide better guidance.

We did not publish our package to PyPI at the time of review, making it a bit complicated to do the package installation. Right now the package is available through pip insall so we believe that the installation is much simpler. Besides, a usage section is added, with some simple illustration on the functions we defined. (https://github.com/UBC-MDS/OLS_regressor/issues/66)

After installing the package and running Pytest, although all tests passed, a warning message appeared. This may be due to the lack of instructions for setting up a virtual environment and installing necessary dependencies. Including a section on dependencies in the README would be advantageous.

We are still working on this issues. We will keep updating our progress with you.