Group 9 - spotify_assistant (Python)

Submitting Author: Julie Song (@YXIN15) All current maintainers: (@carolinetang77, @ChesterAiGo, @brabbit61) Package Name: spotify_assistant One-Line Description of Package: A Python package that explores Spotify users' listening trends, built upon Spotipy and implemented for Spotify developers. Repository Link: https://github.com/UBC-MDS/spotify_assistant Version submitted: v1.0.1 Editor: Caroline Tang @carolinetang77 Chester Wang @ChesterAiGo Jenit Jain @brabbit61 Reviewer 1: Luke Yang Reviewer 2: Ke Wang Reviewer 3: Arjun Radhakrishnan Reviewer 4: Waiel Tinwala Archive: TBD
Version accepted: TBD Date accepted (month/day/year): TBD

Description

A Python package that enriches Spotify users' music experience by allowing them to explore their listening trends via REST APIs implemented for Spotify developers.

There is one similar Python package, Spotipy that provides wrapper functions in Python for the Spotify API. This package contains a function for each possible API request, but does not combine any of these requests. Our aim is to create functions that combine multiple requests and provide additional insights for Spotify users.

Scope

Please indicate which category or categories this package falls under:
- [x] Data retrieval
- [x] Data extraction
- [ ] Data munging
- [x] 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.

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 is Spotify users who would like to extract data from music listening trends, both in general and from their own data. The package allows retrieval and extraction of the user's own listening data, as well as general Spotify releases data, and can allow users to create new playlists on Spotify based on recommended songs.
- Are there other Python packages that accomplish the same thing? If so, how does yours differ? There is a package called Spotipy that provides wrapper functions in Python for the Spotify API. This package furthers the functionality of that package by combining wrapper functions for new purposes and greater insights.
- 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.
[ ] has an OSI approved license.
[ ] contains a README with instructions for installing the development version.
[x] includes documentation with examples for all functions.
[ ] contains a vignette with examples of its essential functions and uses.
[x] has a test suite.
[x] has continuous integration, such as Travis CI, AppVeyor, CircleCI, and/or others.

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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: Do not submit your package separately to JOSS*

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[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.

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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:
- [x] Continuous integration and test coverage,
- [ ] 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)
[ ] 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.
[ ] 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:

[ ] 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: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[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)

Estimated hours spent reviewing: 1

Review Comments

Very interesting project. The package leverages an existing API of Spotify to achieve data acquisition and processing. Here are some suggestions for the project for future improvement:

The README.md could potentially be more specific about how one could get started using your package. For example. The usage could be further documented rather than demonstrating the function's descriptions and how they could be called.
The example.ipynb in docs could include more functions calls and printouts demonstrates the usage of the functions and what they produce.
I was trying to test out the project but got stuck on where I could find credentials = {clientId:'xxxxxxxxxxxx', clientSecret: 'xxxxxxxxxxxx'}. I believe a short introduction of what this means and how could we get these credentials would be helpful in your README.md.
Though the coverage is not required to be 100%, it is still recommended to test at least the major functions. For example, I noticed that one of the functions that was mentioned in your README.md get_users_top_genres was not tested in your tests, which leads to a series of helper functions missed in your ci testing workflow.
I noticed Pandas, NumPy and Spotipy were used and I saw it Pandas and Spotipy were declared in a yml file in the root. It might be a good idea to also add these to pyproject.toml.

Generally, the project's code was well written and the structure was clear. Hope that the comments were helpful and best of luck for future development.

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

[x] Short description of package goals.
[x] Package installation instructions
[ ] Any additional setup required to use the package (authentication tokens, etc.)
[ ] 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)
[ ] 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.
[ ] Citation information

Usability

[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: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[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: 1.5

Review Comments

I liked the application of Object Oriented Programming to develop this package. You've put in a lot of effort to conform to these principles and develop the package in a short span of time. Kudos!
The link to the ReadTheDocs page for the package is missing in the repository description as well as in the ReadMe. Adding this would allow users to get sufficient help regarding your package.
While you've used sufficient helper functions to make your code more modular and DRY, improving and adding comments to ensure other developers can quickly ramp up on your code base is also equally important. Inconsistencies in the function docstring such as having the function definition for def get_users_playlists_songs(self, playlists = None) but giving an example for Caroline.get_playlists_songs() in the docstring could be misleading.
The usage section could be improved by adding more details and linking references on how to get the client id and secret. Since users would be using private client secrets, it would also be better if there is a comment on the security practices followed to ensure that the secrets are not leaked and the package does not log the secrets in plain text.
With a sophisticated package like this, it is crucial to make sure that code is doing what it is expected to do. One way is through adding sufficient tests and improving the code coverage from the current ~40% to at least around 80%.

Overall, the package is really interesting and engaging, especially for all music enthusiasts! It offers some amazing functions as well which I really enjoyed looking into. Thank you!

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

[x] Short description of package goals.
[x] Package installation instructions
[x] Any additional setup required to use the package (authentication tokens, etc.)
[ ] 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)
[ ] 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.
[ ] Citation information

Usability

[ ] 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: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[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)

Estimated hours spent reviewing: 1

Review Comments

First of all, Congratulations to the team on creating such a high quality package. The README file introduces the package well and provides adequate information to get started with using the package.
in the User.py file, there is some inconsistency in the documentation. The name of the function and the example usage name are different.
It was very difficult finding the online hosted documentation. While the entire package is organized in a meaningful way, not having the full documentation link would discourage most users from using the package.
The initial setup requirement with the API keys is a little redundant every time a user needs to use the package. There should be a section explaining them in more detail (perhaps a section explaining how to permanently setup the keys as system/environment variables).
The README files Usage section can be elaborated and expanded upon. For example, showing the sample outputs along with the code.

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

[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

[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: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[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)

Estimated hours spent reviewing: 1 hour

Review Comments

I love the idea of this project and I also enjoy your presentation!
For some reason I wasn't able to run the example usage code. I guess there's something wrong with my account or developer's token. So the suggestions below are only based on looking at the code/repo.
I love the idea to create User object, but I think it would be better to seperate functions into different files, instead of putting everything into the single User.py file.
The given example usage code can be more robust. For example we should use 'client_id':'xxxxxxxxxxxx', instead of clientId:'xxxxxxxxxxxx', according to the init function here
I think it's a better practice to delete git branches that are already merged into master.
The test coverage is 40% and this can be improved.

UBC-MDS / software-review-2023