Submission group 8: tweetlytics

Submitting Author: Mahsa Sarafrazi (@mahsasarafrazi)
Package Name: tweetlytics One-Line Description of Package: This package would retrieve tweets on a required topic and time frame, stores them, performs data cleaning, data analysis, and plotting. Repository Link: https://github.com/UBC-MDS/tweetlytics Version submitted: 2.0.0 Editor: Amir Shojakhani: @Amirshoja, Shiva Shankar Jena: @shivajena, Mahmood Rahman: @mahm00d27
Reviewer 1: Xiaohan Chen Reviewer 2: James Kim Reviewer 3: Brandon Lam Reviewer 4: Zihan Zhou

Description

The package tweetytics is a package intended to give insight about a topic on Tweeter through some functions. The intention is that a user with little knowledge about data science can quickly call a function to analyze how the topics and trends are on Twitter. Internally, the package uses the official Twitter API, stores the data as a .json and .csv file, perform data cleaning, data analysis, and plotting.

Scope

Please indicate which category or categories this package falls under:
- [X ] Data retrieval
- [X ] Data extraction
- [X] Data munging
- [ ] Data deposition
- [ ] Reproducibility
- [ ] Geospatial
- [ ] Education
- [X] 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.

Explain how the and why the package falls under these categories (briefly, 1-2 sentences): The package tweetytics is a package intended to give insight about a topic on Tweeter through some functions. The intention is that a user with little knowledge about data science can quickly call a function to analyze how the topics and trends are on Twitter. Internally, the package uses the official Twitter API, stores the data as a .json and .csv file, perform data cleaning, data analysis, and plotting.
Who is the target audience and what are scientific applications of this package? Any data professionals at the entry-level would like to conduct a quick exploratory data analysis on Twitter.
Are there other Python packages that accomplish the same thing? If so, how does yours differ? from Twitter API and token to plotting, all the procedures that a person should accomplish to get the result, now combine in one package.
If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or another 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] has 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 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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[ ] 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: Do not submit your package separately to JOSS*

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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

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Documentation

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
[ ] Vignette(s) demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all user-facing functions
[x] Examples for all user-facing functions
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Readme 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, a repostatus.org badge, and any other badges. 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 badge for pyOpenSci peer-review will be provided upon acceptance.)
[x] Short description of goals of package, with descriptive links to all vignettes (rendered, i.e. readable, cf the documentation website section) unless the package is small and there’s only one vignette repeating the README.
[x] Installation instructions
[ ] Any additional setup required (authentication tokens, etc)
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[ ] If applicable, how the package compares to other similar packages and/or how it relates to other packages
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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:

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

Functionality

[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
[ ] 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.
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[ ] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.

For packages co-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

You may consider adding the ci /cd and codecov badges in the readme.
Images are not rendered well in Readthedoc.
Examples are missing for the docstring of plot_freq() function.
You may describe where your packages fit into the Python ecosystem (are there any other Python packages that have the same/similar functionality) in the readme.
To make it easier for users, you may also consider adding links / tutorials on how to generate the personal ‘bearer token’ for the get_store() function.
It would be great if you can provide a complete example instead of just the function name and output in the Usage of readme.

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 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
[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 setup.py file or elsewhere.

Readme 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, a repostatus.org badge, and any other badges. 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 badge for pyOpenSci peer-review will be provided upon acceptance.)
[x] Short description of goals of package, with descriptive links to all vignettes (rendered, i.e. readable, cf the documentation website section) unless the package is small and there’s only one vignette repeating the README.
[x] Installation instructions
[ ] Any additional setup required (authentication tokens, etc)
[x] Brief demonstration usage
[x] Direction to more detailed documentation (e.g. your documentation files or website).
[ ] If applicable, how the package compares to other similar packages and/or how it relates to other packages
[x] Citation information

Usability

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

Functionality

[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
[ ] 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, such as Travis CI, AppVeyor, CircleCI, and/or others.
[x] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.

For packages co-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: 1.5h

Review Comments

Firstly, I have to say the package is great! It is useful and needs a lot of hard work.
plot_tweets() didn't have the docstrings needed.
The return part in docstrings of the clean_tweets() function seems missing.
Is there any similar existing packages for python? What are your package's advantages compared to those ones? You can add some relevant explanations in README
A small issue: the list in dependency and usage seems not working, all the points are now in one line.
For the usage part in README, it can be better if you include a complete example instead of just the output, namely, clarifying the parameters you use or showing some part of your data as well.
A little confused and correct me if I am wrong: in your usage part, there is a plot_freq() function, is this the plot_tweets() one? Seems you forget to rename this function in the usage part.

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 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 setup.py file or elsewhere.

Readme 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, a repostatus.org badge, and any other badges. 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 badge for pyOpenSci peer-review will be provided upon acceptance.)
[x] Short description of goals of package, with descriptive links to all vignettes (rendered, i.e. readable, cf the documentation website section) unless the package is small and there’s only one vignette repeating the README.
[x] Installation instructions
[ ] Any additional setup required (authentication tokens, etc)
[x] Brief demonstration usage
[x] Direction to more detailed documentation (e.g. your documentation files or website).
[ ] If applicable, how the package compares to other similar packages and/or how it relates to other packages
[x] Citation information

Usability

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

Functionality

[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
[ ] 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, such as Travis CI, AppVeyor, CircleCI, and/or others.
[x] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.

For packages co-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: 1hr

Review Comments

Overall it is very interesting work! I saw your presentation again too and I can see that you guys put a lot of efforts into it and the results look great. I especially love all the resulting plots and the dashboard at the end. It would definitely help users who are looking to get insights from Tweeter data. Great job!
The only minor concern that I have is that your Documentation/ Readme do not contain examples that guide users on how to utilize the package. It would have been nicer if a detailed walk through of how to use the package with some sample data was shown in the 'Example usage' section of the Documentation. The examples shown in the Readme file has only the two function names without any parameters specified.

Additional small points include:

Looking at the script file, plot_tweets() function is missing docstrings.
In the Readme file (and also Documentation), the bullet points need to be better organized and structured under Note, Dependencies and Usage sections.
In the Documentation, images are not showing up properly under Sample outputs.
Under Sample Outputs section, the second function is named as plot_freq(), is this a typo?
I believe plot_tweets() should produce four plots as a result but only one is showcased under plot_freq().
Descriptions for Function 3: analytics is not complete with '...' at the end?
An instruction of how to obtain a bearer token for the official Twitter API V2 would have been nice too.

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 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
[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 setup.py file or elsewhere.

Readme 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, a repostatus.org badge, and any other badges. 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 badge for pyOpenSci peer-review will be provided upon acceptance.)
[x] Short description of goals of package, with descriptive links to all vignettes (rendered, i.e. readable, cf the documentation website section) unless the package is small and there’s only one vignette repeating the README.
[x] Installation instructions
[ ] Any additional setup required (authentication tokens, etc)
[x] Brief demonstration usage
[x] Direction to more detailed documentation (e.g. your documentation files or website).
[ ] If applicable, how the package compares to other similar packages and/or how it relates to other packages
[x] Citation information

Usability

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

Functionality

[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
[ ] 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, such as Travis CI, AppVeyor, CircleCI, and/or others.
[x] Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.

For packages co-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: 1.5h

Review Comments

Amazing work! The package works as expected and as described. I love how the name conveys the benefit of being able to generate plots quickly. The peer reviewers above me provided detailed feedback that I agree with. In addition, I noted some minor revisions, as follows.

Examples are missing for the docstring of plot_freq() function. Same for the return part in docstrings of the clean_tweets() function are missing.
Dependencies should have a better format, such as a simple introduction to these packages (Only in my opinion) Same for the Usage in the readme file, should be To use to get_store() function, users will require to obtain a bearer token for the official Twitter API V2. The bearer token can be requested on developers.twitter.com. and To test the package output, we have added sample files returned from the get_store() function and users can run clean_tweets(), analytics() and the plot_freq() functions. in the two lines, not in the same line. This may look messy.
In the README file include the link to the readthedocs documentation, which is really great. But the graph doesn't show on the documentation website.
For the usage section in the README, it is best to include a complete example rather than just output, i.e. clarify the parameters you are using or show some of the data. Maybe explain the output then the user can have a better understanding about this work.
In the docs , the example.ipynb file is not complete.

Aside from the minor issues mentioned above, the package has been so comprehensive and easy to use overall. I really appreciate that you can use this package to make data visualization easier for non-technical people. Thanks!

UBC-MDS / software-review-2022