Submission Group 11: cryptocurrencyeda(Python)

Submitting Authors:

Berkay Bulut (@berkaybulut)
Cici Du (@ciciecho-ds)
Alex Yinan Guo (@alexYinanGu0)
Nobby Nguyen (@nobbynguyen)

Package Name: cryptocurrencyeda One-Line Description of Package: A Python package for simple exploratory data analysis of historical cryptocurrency prices and performance. Repository Link: cryptocurrencyeda Version submitted: 1.0.1 Editor: Florencia D'Andrea (@flor14)

Reviewers:

Navya Dahiya
Dongxiao Li
Kyle Maj
Michelle Wang

Description

This is a Python package to analyze historical cryptocurrency prices and performance through simple exploratory data analysis including calculations and plotting. Data is sourced from the KuCoin API. There are four functions that are included in this python package which are described in more detail below. Cryptocurrency investors and enthusiasts can use this package to analyze cryptocurrencies of interest. There are four functions in our packages:

retrieve_data: downloads historical data from a cryptocurrency exchange using an an http request from a cryptocurrency exchange.
plot_price: generates and visualizes a plot of the price of the cryptocurrenty inputted over a period of time.
daily_growth_rate: performs calculation of daily growth rate of the cryptocurrenty inputted over a period of time.
avg_daily_return: performs calculation of the average daily return of the inputted cryptocurrency price.

Scope
Please indicate which category or categories this package falls under:
- [x] 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):
The cryptocurrencyeda package retrieves data and provides visualization and simple calculations for cryptocurrency data.
- Who is the target audience and what are scientific applications of this package?
Cryptocurrency investors and enthusiasts can use this package to analyze cryptocurrencies of interest.
- Are there other Python packages that accomplish the same thing? If so, how does yours differ?
There are existing Python libraries to access information of cryptocurrency such as cryptocompare and cryptofeed. There are also existing Python libraries to visualize financial data such as mplfinance. However, there is no integrated Python library for accessing, analyzing, and visualizing cryptocurrency data altogether. Therefore, we want to build a simple tool that can facilitate simple cryptocurrency data analysis all at once.
- 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.
[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.
[ ] 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.

Publication options
[ ] 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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[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 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
[ ] 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
[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 hour

Review Comments

What an interesting package this is, especially on the wave of crypto hype this could prove to be quite a popular package in time to come! Good job with creating this innovative package! Some thoughts for further improvements:

The background provided on source of data can be further elaborated. Especially for newbies in the realm of crypto, this will be useful. It was mentioned that KuCoin API was used, but you can also write a couple sentences on what this dataset is about and what kind of variables there are, what period of data does this take in. So that the users can identify whether this package pulls the right data they want.
retrieve_data documentation can also include some more details like the actual time for 'maximum time' that can be pulled from data. The parameters for input says 'name' but 'symbol' was actually used instead in function call. Perhaps more explanation for name input would be useful (what standard for symbol are we looking at)
plot_price plot date axis gives months but not years so it is not very clear which year range this plot is plotting. Consider adding the year as well.
daily_growth_rate seems like a good feature. Further improvement can be thinking of how to handle different types of frequency data and yet still calculate the daily growth, for example if the data is in minutes or hours (aggregate by day).
avg_daily_return is also useful, and can be expanded to give users option to calculate avg weekly or monthly returns. So provide another argument in the function for 'period' and users can type in what granularity they want.

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
[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
[ ] 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
[ ] 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

[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:

[ ] 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 hour

Review Comments

In the README.md under the Import all functions: section, it would be better to remove the <<< for easier copy as a whole. I first copied the whole chunk into Python and it will throw message like SyntaxError: invalid syntax. Should be an easy update!
For function retrieve_data(symbol="BTC-USDT", time_period="1day", start_date="2018-01-01", end_date="2022-01-10", ), could be better to explain a little bit what symbol is. I am still a little bit confused about it even after reading the documents.
The x-axis of the plot output does not show a clear time range like from which year to which year as there is only a monthly interval. Could also include year information in the x-axis of the plot for easier understanding.
In your example usage website link(https://cryptocurrencyeda.readthedocs.io/en/latest/example.html#imports), there is ab error message ModuleNotFoundError: No module named 'cryptocurrencyeda' under the Import section. Should be an easy fix.
You can also plot the daily growth rate for users (can be a new function in the future). Overall, it is a good function. Nice job! By the way, you did not included the codecov badge in README. Could have a simple update!

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
[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
[ ] 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).
[x] If applicable, how the package compares to other similar packages and/or how it relates to other packages
[ ] 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: 45 minutes

Review Comments

A very interesting package, with great ease of use for all types of users. Great work team !!
In ReadTheDocs, there is a ModuleNotFoundError under the Imports section, which should be fixed as it is the official documentation
It would be better if you could include the badges for CodeCov and docs(for showing that the docs are rendered properly whenever a change is pushed to main branch as part of release)
It would be helpful if >>> can be removed from the README file under Import all functions and use the functions so that it is easy for the user to copy and directly try out your code
It would be good if the value returned by avg_daily_return can be rounded off to nearest 2 or 3 decimal places for better readability and interpretability.
In API Reference section in ReadTheDocs, daily_growth_rate function, the parameters are not being rendered as bullet points like in other functions
In function plot_price, the Examples heading is missing under which >>>plot_price(df) should be written

Both 6 and 7 points above can be rectified by tweaking your python function docstrings

A future implementation for daily_growth function could be to plot the graph for easy visualisation for better interpretability

UBC-MDS / software-review-2022