Group 5 - stocksignals(Python)

[pengzh313]

Submitting Author: Ruslan Dimitrov (@RussDim), Robin Dhillon (@robindhillon1), Peng Zhang (@pengzh313), Chenyang Wang (@wakesyracuse7) All current maintainers: (@RussDim, @robindhillon1, @pengzh313, @wakesyracuse7) Package Name: stocksignals One-Line Description of Package: Calculate and plot buy/sell signal indicators for a stock, including 200-day price moving average, 10 vs 20-day price moving average, and 20-day Bollinger bands. Repository Link: https://github.com/UBC-MDS/StockSignals Version submitted: v0.0.7 Editor: TBD Reviewer 1: Renzo Wijngaarden (@Hawknum) Reviewer 2: Wilfred Hass (@WilfHass) Reviewer 3: Lisa Sequeira (@LisaSeq) Reviewer 4: Daniel Merigo Silos (@merigo) Archive: TBD
Version accepted: TBD Date accepted (month/day/year): TBD

---

Description

• Include a brief paragraph describing what your package does: The stocksignals package is to calculate and plot buy/sell signal indicators for a stock, including 200-day price moving average, 10 vs 20-day price moving average, and 20-day Bollinger bands.

Scope

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

• 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?
    A stock market investor who are interested in identifying stock buy/sell signals with 200-day price moving average, 10 vs 20-day price moving average, and 20-day Bollinger bands can use this package to calculate and plot a selected stock for given signals.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ? There are multiple packages related to utilizing stock price data. For example, past projects in UBC MDS DSCI524 have explored various transformations to help analyzing stocks like this one: https://github.com/UBC-MDS/stockAnalyzer. Other packages like this one https://github.com/UBC-MDS/Stock-Price-Trend-Volatility-Analysis have explored volatility analysis. The aim of this package is to explore specific technical analysis indicators and streamline the process by providing a hands-on package which can be used in daily stock analysis. Furthermore, this package will help streamline the process in order to help automation of the basics of stock screening.

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[WilfHass]

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.
• [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).

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)
• [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
• [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)

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 1/2

Review Comments

1. Package looks good! I would recommend adding more badges to easily show the code coverage and other important information at a quick glance.
2. I would recommend adding an example in the vignette of using the functions and showing the user what would be output, such as the plots (in notebook functionality) that then appears on the ReadTheDocs.
3. I would also like to recommend making it more clear on where to find the ReadTheDocs link as the hyperlink on "here" is very small and hard to see.
4. The plotting looks hard to test but if you have time, adding a few more tests for edge cases like erroneous data could help!
5. Finally, I would suggest pooling some functions together in the file directory! Each file having a different function when some are helpers to others might get complicated in the future and it might be easier to start pooling functions early.

Overall, great package! Very fun and interesting to use.

[RenzoWijn]

Package Review

• [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.
• [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).

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
• [] 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
• [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.
• [ ] 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)

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

The package overall looks great! Concise and does what it says on the label. A few potential improvements:

1. Add all applicable badges to your GitHub repository. This will help anyone looking to use your package see more quickly that it is reliable and well-tested. (Also mentioned by @WilfHass )
2. Improve the visual appeal of your plots: the units on the y-axis are dollar signs so add $ to the numbers, the x-axis shows the wrong date format in some of your plots.
3. Make your package more accessible by using appropriate colour schemes or discernible line styles that are easily legible for those who are colourblind! Two of your plots feature lines that are red and green dotted, and therefore indistinguishable to those who suffer from red-green colourblindness.
4. I would also suggest to making your directory structure more concise to not lose track of the greater scope of your file structures. (Mentioned by @WilfHass)
5. Perhaps to try and tie all your functions together, you could add a parameter to your functions like docs=True that when set to True prints the explanation of the table/plot so people don't have to switch between the README.md and their implementation of your package when they're not familiar with it, or when they use your package in an educational setting.

[LisaSeq]

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.
• [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).

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.)
• [] 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.
• [ ] 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
• [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)

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

As mentioned in the R package equivalent, very interesting package and great work overall! My comments are as follows:

1. For the plotting functions, it would be a good idea to indicate in the docstring that the user must first run get_data to download the data of the stock sticker prior to running the other functions. Otherwise the user is left with a long error message to decipher. I noticed you have mentioned something like this in the details about the moving_average function, but not for the other functions, alternatively you could build this into the function to have an error message that is more clear to the user.
2. Also, while playing around with the get_data function, I noticed that running the get_data function a second time, after already loaded the a csv for a given stock sticker, this function overwrites this file if I use it again to request data for a new stock sticker. What if a user wanted to review the stock information for more than one stock sticker at the same time? If this was the intent, perhaps a warning could be added into the documentation for this.
3. For the moving_average function, can more detailed description be provided for the argument size? Current it says: "size : int: The size of the period that we're interested in", is this period size in days, months or years?
4. I too agree with previous users regarding the addition of more badges if available to show how robust and how user friendly your package is.
5. Lastly, with regards to the documentation, it would be nice to do what you did with R package and display the expected plots in your documentation, so the user has some idea or expectation on what they should see. Furthermore, finding ways of making these plots more interactive would add really make the graphs stand out.

[DMerigo]

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.
• [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:

• [ ] 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.)
• [ ] 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
• [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)

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

1. Some badges are missing, specially the test coverage and documentation ones would be nice (specially since your documentation is well rendered and complete in sphinx format and hosted on Read the Docs)

2. Interactivity would be incredible in this package, the plots could use it to explore the specific prices at specific times.

3. I agree with @LisaSeq a more specific size indication in calc_moving_avg.py would be great for specificity.

4. After installing and when I pasted your examples (in the Usage portion of the README) and running it threw an error with DATE, it cleared after I ran a second time and functioned correctly but wanted to mention it (For reference I am on a Mac M2, using VSCode and the 573 environment)

5. The vignette is missed, it would have helped understand how to use your function and how it can be used in the context of stock analysis (and even maybe show how a Bollinger band is useful!)

6. While doing several tests with different I noticed it was hard to visualize the differences between plots (maybe adding a grid behind the data would help visualize the actual x and y values for the datapoints)

7. I agree with @RenzoWijn the axis labels show the wrong date formats in the moving average plots

Well done! The package is well constructed and includes good documentation in each of the functions. It is easy to use (experimented with a few stocks and it performed nicely). The only suggestions I have are the ones mentioned in the comments (specially the interactivity).