Submission Group 02: rlyrics (R)

Submitting Author Name: Artan Zandian Submitting Author Github Handle: @artanzand Other Package Authors Github handles: @MacyChan, @manju-abhinandana, @abhiket Repository: https://github.com/UBC-MDS/rlyrics Version submitted: 1.0.0 Submission type: Standard Editor: @artanzand Language: en Reviewer 1: Cici Du @ciciecho-ds Reviewer 2: Sanchit Singh @ssingh90 Reviewer 3: Shi Yan Wang @sy25wang

Paste the full DESCRIPTION file inside a code block below:

Package: rlyrics
Title: Downloads, cleans and creates wordcloud of lyrics
Version: 0.0.0.9000
Authors@R: c(
    person("Abhiket","Gaurav", , "abhiketg@student.ubc.ca", role = c("aut")),
    person("Artan","Zandian", , "aazandian@student.ubc.ca", role = c("aut")),
    person("Macy","Chan", , "macychan@student.ubc.ca", role = c("aut", "cre")),
    person("Manju","Abhinandana Kumar", , "manju2na@student.ubc.ca", role = c("aut")))
Description: Downloads data from Kaggle, finds the lyrics of a certain artist and song, cleans the lyrics and creates wordcloud of lyrics.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2.9000
Suggests: 
    knitr,
    rmarkdown,
    covr,
    testthat (>= 3.0.0)
Config/testthat/edition: 3
Imports: 
    tm,
    textclean,
    readr,
    here,
    rvest,
    stringr,
    wordcloud2,
    kaggler (>= 0.0.0.9000),
    dplyr,
    tidyselect
Remotes: 
    ldurazo/kaggler
VignetteBuilder: knitr

Scope

Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):
- [x] data retrieval
- [x] data extraction
- [ ] data munging
- [ ] data deposition
- [ ] workflow automation
- [ ] version control
- [ ] citation management and bibliometrics
- [ ] scientific software wrappers
- [ ] field and lab reproducibility tools
- [ ] database software bindings
- [ ] geospatial data
- [x] text analysis
Explain how and why the package falls under these categories (briefly, 1-2 sentences):

The package rlyrics retrieves data from Kaggle, extracts lyrics, cleans the extracted lyrics, and performs text analysis to generate a word cloud with the highest frequent words in lyrics.
Who is the target audience and what are scientific applications of this package?

Lyricists and data scientists working in the entertainment industry
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

Yes. Of the many other packages that do pieces of the functions within this package, the one that comes closest is geniusr which scrapes the web to extract lyrics.
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Not applicable
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Explain reasons for any pkgcheck items which your package is unable to pass.

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This package:

[x] does not violate the Terms of Service of any service it interacts with.
[x] has a CRAN and OSI accepted license.
[x] contains a README with instructions for installing the development version.
[x] includes documentation with examples for all functions, created with roxygen2.
[x] contains a vignette with examples of its essential functions and uses.
[x] has a test suite.
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The package includes all the following forms of documentation:

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[x] Installation instructions: for the development version of package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
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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: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1

[x] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Great idea and I loved your presentation in 542!

test() runs fine but check() returns 1 error that says test failures: Error: '......tests/testthat/data/lyrics_22.txt' does not exist. You might want to address this issue.
Since to use this package, you have to use Kaggle API, I suggests adding more documentation and link to the Kaggle relevant documentation for users. https://www.kaggle.com/docs/api
I think it would make more logical sense if in your examples, you continue to use one song as your data source as it is a sequential process instead of extracting the lyrics from one song and cleaning another text.
The returned word cloud image is in portrait. I wonder if it's possible to generate it in landscape so it may look better.
Your README doesn't show the word cloud image. I think it would be more appealing if you included it in your README.

Cici, Thank you for the valuable review. We have addressed serval comments and the changes will be included in the upcoming release.

Fixed check() error
Added extra Kaggle API information on ReadMe and Vignette
Added cloud image on ReadMe
We will discuss the extra feature of word cloud image about cloud image size options.

Understood that it might be more helpful with lyrics example under clean_text(), however, we have tested that out and the result looks messy. Therefore, we decided to keep it as is. For a better explanation, feel free to visit this article

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

Briefly describe any working relationship you have (had) with the package authors.
[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 package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
[x] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

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: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1 hour

[x] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Overall I think this is a well structured package serving its purpose. Some of my suggestions and recommendations are:

Please review docstrings for your functions. Some function examples are in the following format that I am not sure if this is on purpose? `#' @examples
' \dontrun{`
Under the Functions section of your README, the input column and the description together can lead to some confusion. For example, for clean_text function, the input mentions text, but the description refers to the lyrics.
I am curious how some incorrect inputs are handled by your functions. For example, how the clean_text function handles the input that is a combination of words and digits (e.g., Se7en)
For your testing, would you consider adding more edge case testing? For example, what if the background_color input is of type character but not a real color word? I would recommend considering and adding more if cases to your functions and test cases.
The requirement of using Kaggle API may restrict the uses of this package. I believe the dataset is not limited to Kaggle but can be from other sources? You may want to add to your example paragraph that Kaggle here is only for example illustration.

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

Briefly describe any working relationship you have (had) with the package authors.
[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 package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
[x] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

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: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1

[x] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

It may be a good idea to include additional edge test cases in the clean_text function. Including tests for more foreign characters can improve the reliability of the function
Including functionality to check for songs with multiple artists and multiple versions of artists names (including capital letters) can improve the scope of the package to include a wider variety of songs
Adding a specific error output telling the user to fix their kaggle credentials in cases where there is difficulty authenticating kaggle credentials or finding the json file might be a useful addition to the download data function
I believe dding "\dontrun" is to avoid check() issues withing the docstrings, but it may be a good idea to enable these functions in the future to run with check() without issues since this will make the package more robust

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

Briefly describe any working relationship you have (had) with the package authors.
[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 package and any non-standard dependencies in README
[x] Vignette(s): demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all exported functions
[x] Examples: (that run successfully locally) for all exported functions
[x] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

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: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
[x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 1 hr

[x] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

Review Comments

Great work. Love the concept that you combine functionalities of many packages into one.

Docstring of extract_lyrics has "\dontrun{" as a typo
The r code styling can be kept constant such as using "<-" instead of "="
Similar to python package, keeping most of the info of the functions in the features section rather than example section makes more sense
These days, we have a number of songs with the same name. The package can include those kinds of cases in their package too, to differentiate between them
The package might not take numbers as ong names which can be a problem
The test cases are built very nicely, covering all possible scenarios

UBC-MDS / software-review-2022