Submission: pytweet (Python)

[yuanxiongbear]

Submitting Author: Huanhuan Li (@huan-ds), Yuanzhe(Marco) Ma (@mmyz88), Jared Splinter (@JaredSplinter), Yuan Xiong (@yuanxiongbear) Package Name: pytweet One-Line Description of Package: A python package that gives a brief summary on a user's tweet. Repository Link: https://github.com/UBC-MDS/pytweet Version submitted: 0.1.8 Editor: Tiffany Timbers (@ttimbers) Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
Version accepted: TBD

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Description

• Tweeter is one of the most popular social medias. There are currently 192 million tweeter users around the world. An interesting topic is to learn your tweet behaviors such as when do you like to send tweets or sentiments in your tweets. Tweeter itself does not provide such function. However this can be easily done using pytweet. Pytweet provides a basic analysis on a user's tweets, including timeline analysis, hashtag analysis and sentiment analysis. And the result will be summarized in easily interpretable plots.

Scope

• Please indicate which category or categories this package falls under:
  • [ ] Data retrieval
  • [ ] Data extraction
  • [ ] 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):

  • Pytweet uses another package tweepy to extract information from tweeter for a given user. The extracted data in the format of dataframe is then used for various analysis that lead to generation of summary plots.

• Who is the target audience and what are scientific applications of this package ?

  • The audiences are tweeter users that are interested in their own tweet behaviors. Or audiences that are interested in studying particular user's tweet (like celebrity).

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?

  • There are more sophisticated tweet analysis apps. But no other simple package like pytweet that we are aware of.

• 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:

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[fatse]

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.
• [ ] 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
• [x] 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
• [x] Any additional setup required (authentication tokens, etc)
• [x] Brief demonstration usage
• [x] Direction to more detailed documentation (e.g. your documentation files or website).
• [x] If applicable, how the package compares to other similar packages and/or how it relates to other packages
• [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:

• [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

• [ ] Installation: Installation succeeds as documented.
• [ ] 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: 2h

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Review Comments

Hi team 👋

The pytweet package looks great and I am impressed by the work you have to done to build this package in such a short period of time. I enjoyed testing your package using my Twitter handle and thanks to this package I've got some interesting insights about my tweets.

Below are some comments that I think would make your package even greater and easier to use.

General comments:

Overall I enjoyed using/testing your pytweet package and I liked your rationale about the usefulness of this package and its place in the Python ecosystem as it seems like existing Python packages that perform tweets text analysis and sentiment analysis do not provide hashtag and/or timeline visualization. Good job and keep up the good work!!

Functionality:

1. I was unable to install your package using the command that you listed in the README file in the "Installation" section. However, I was able to install your package by using this command: pip install -i https://test.pypi.org/simple/ pytweet --extra-index-url https://pypi.org/simple/ so I think that you might want to update the installation command in your installation instructions.
2. Looks like your tests cover only 73% of your Python code so it would be great if you added more tests to increase your code coverage.
3. It would be easier for the users to use your package if you added an instruction section about the way they can add Twitter API keys in their .bash_profile.
4. I got errors when I tried to use pytweet.get_tweets('@BrunoMars', n_tweets=8) after I imported your package based on your instructions. I think that you need to update the import of your package into something like this: from pytweet import pytweet. I tested the get_tweets() function after importing your package properly and it worked fine.
5. You might need to update this line tweet_sentiment_analysis(tweet_data) in your instruction as it throws errors. I was able to use tweet_sentiment_analysis like this pytweet.tweet_sentiment_analysis(tweet_data).
6. When I tried to use plot_timeline() function I faced this error: TypeError: strptime() argument 1 must be str, not Timestamp. It would be great if you can handle this error gracefully by printing a more informative message about the type of argument the function is expecting.
7. When I tried to use visualize_sentiment() function I faced this error: KeyError: 'negative'. Also, the proper way to use this function is pytweet.visualize_sentiment() so you might want to update that line in your instructions in the README.

Documentation:

1. It would be great if you associated examples for use of the function in each docstring of your function. In that way, users can easily see what to expect as an output of your function when looking at the documentation of your package.
2. It would be great to list all the authors who contributed to building this package in pyproject.toml file. Right now I can see only "mmyz <yzmarco.ma@gmail.com>".
3. It would be helpful if you listed all the possible values for plot_type in the visualize_sentiment function, or at least include the plot_type argument in the example where you call this function, e.g. pytweet.visualize_sentiment(sentiment_df, plot_type="Standard"). Seems like Standard is the default one, and I realized this only after I looked at the code of this function, and as it appears there are two more options, i.e. Stacked and Separate.
4. It would be helpful to list the other arguments in the get_tweets() function, e.g. if the users want to include the replies then they can specify include_replies=True. This argument, include_replies, is an optional argument and defaults to False and I saw this only after I looked at the code of this function, so it would be more obvious if you called this function by including all the arguments, e.g. pytweet.get_tweets('@BrunoMars', n_tweets=8, include_replies=False, verbose=True).

I would like to hear your thoughts on this and let me know if you need more clarification.

Cheers, Fatime

[elina-linglin]

Peer 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
• [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 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
• [X] 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
• [X] Any additional setup required (authentication tokens, etc)
• [X] Brief demonstration usage
• [X] Direction to more detailed documentation (e.g. your documentation files or website).
• [X] If applicable, how the package compares to other similar packages and/or how it relates to other packages
• [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:

• [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

• [ ] 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: 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

• [X] 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:

• [X] A short summary describing the high-level functionality of the software
• [X] Authors: A list of authors with their affiliations
• [X] A statement of need clearly stating problems the software is designed to solve and its target audience.
• [X] 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

General Comments

Overall I think the project team has done a good job with this pytweet package. There are some minor issues with installation to be be addressed. One of the tests failed, so it might need some checking. Overall, this is a useful package. I especially like all the functions that produce interesting plots as they are very straightforward and informative. Thanks for making this fun package!

Specific Issues

Issue 1: Following the installation instruction from the README file, I wasn't able to successfully install the package into my local computer. The reason might have something to do with having it in only testPyPi but not in PyPi, as some of the package dependencies of testPyPi have not been updated to the latest version and thus unavailable.

Suggestion: You could consider publishing the package in PyPi so that all the packages needed are easily accessible upon installation.

You could also try using the following code:

pip install -i https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple pytweet

Issue 2: The following line of installation command on the readthedocs webpage needs to be updated to the same as the one on README file.

Issue 3: Change the following line of code:

import pytweet to from pytweet import pytweet

Issue 4: When I ran pytweet.plot_timeline(tweet_data, 'time'), I encountered a TypeError, which can be fixed after commenting out line 126 on pytweet.py.

Issue 5: For the following two functions, make sure the prefix pytweet. is added before function names.

Issue 6: When I ran the tests, one of the failed, so you might want to take a look at that.

Hope you will find the above suggestions helpful!

Cheers, Elina