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pyroRutils

The goal of pyroRutils is to support efficient, reproducible, and collaborative R workflows for Pyrologix Analysts. This package is a Work In Progress :)

Installation

You can install the development version of pyroRutils from GitHub with:

# Must have devtools installed: install.packages("devtools")
# If you have SSH credentials set up (?):
devtools::install_github("pyrologix/pyro-analysts/pyroRutils")

# If you get an error with the above approach, instead:
# with `pyrologix/pyro-analysts/` as your working directory, run:
devtools::install("pyroRutils")

Usage

WIP documentation and examples of usage…

# Replace storage path with a working network drive
pyroRutils::pull_variable_files(
  storage_path = file.path("", "Volumes", "_DATA", "Tyler_Transfer", "wx_scenario_monthly_relative_frequency"),
  variable = "trf"
)
#>   [1] "/Volumes/_DATA/Tyler_Transfer/wx_scenario_monthly_relative_frequency/trf_wx001_2011-2023.tif"
#>   [2] "/Volumes/_DATA/Tyler_Transfer/wx_scenario_monthly_relative_frequency/trf_wx002_2011-2023.tif"
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Contributing

Everybody is welcome to contribute to the package. Reach out to @tylerhoecker to discuss how.

Style

Please use the tidyverse style guide. The R package styler makes this easy to do. There are add-ins and shortcuts in both RStudio and VSCode that will style selected text, an entire file, or an entire package.

Dependencies

The more dependencies the package has, the more cumbersome it is to maintain, and the more vulnerable to outside code breaking. This doesn’t mean you shouldn’t use other packages (you definitely should!), but consider whether or not it makes sense to add a dependency to your function, or if it could be expressed just as well with existing dependencies or base R. When adding a dependency, consider the quality and source. Is it a highly used package that is known and used by many and well maintained (e.g. tidyverse packages, data.table, stars), or is it a package that somebody wrote a long time ago for their master’s thesis and has not seen any updates in many years? The former is a safe(r) dependency, whereas the latter is more risky.

Documentation

Please include Roxygen documentation that will allow other users to make use of your function. This includes documenting what the function does as well as its arguments. See roxygen2 or the book R Packages for best documentation practices.

Unit tests

EVENTUALLY - All contributions to this package should include unit tests created using the testthat.

Committing, git history, pull requests, and code review

Below is an example workflow to follow when making a contribution to vpr. This workflow is independent of the IDE you use to code (e.g. RStudio, VSCode, etc.).

1. Check out your development branch

From pyroRutils directory, execute:

git checkout -b 'my-branch'

2. Do your development

As you develop, you should be making small, logically chunked commits along the way and pushing to the remote. To make a commit and push it, execute:

git add your_changed_files
git commit -m "commit message describing changes"
git push

While you are developing you many want to use your new functions interactively to test their behavior, create examples, or develop new functions. The devtools package has a fucntion to make your changes available within an R session without installing pyroRutils each time you make a change:

devtools::load_all()

3. Make sure all unit tests pass and documentation is complete

See the above comments regarding testing and documentation. Once you’ve added the appropriate function documentation, to knit it together and run all the unit tests in the package, navigate to the pyroRutils directory, open an R terminal and call:

devtools::document() # re-knits all documentation
devtools::check() # runs R CMD CHECK on the package

This will give you a report on any failing tests, along with other possible style and package structure errors. Iterate until tests pass! If you need help debugging other issues, let @nerutenbeck know.

Also note that documentation, style, and tests are run automatically on GitHub actions upon opening pull requests.

4. Pull Request and Code Review

When you are ready for code review, open a pull request. At present, you should tag @tylerhoecker and one other Analyst.

Let’s face it, code review can be intimidating. We are exposing our work to the scrutiny and criticism of others, asking them to look for problems. In order to make code review easier for everybody, it helps to remember the following things:

  1. We are all on the same team
  2. We’re not in a coding competition
  3. People have different strengths and experience levels
  4. The fastest way to learn is through code review and others’ examples
  5. It’s better to find a bug in your code at review than at runtime

The reviewers will be looking for concise, clean, efficient, and readable code along with good documentation and unit tests that cover sufficient edge cases. As a review your job is not just to read and look for bugs. You should pull the branch, attempt to install pyroRutils, and run the code. A PR is one part making sure we are all aware of each other’s work, one part making sure you could take over the development/maintenance if the author had to work on something else and one part checking for functionality/bugs/documentation.

If you are tagged to review code

  1. Review files changed in a browser or locally
  2. Step through examples and tests, ask the author for data sources if you need them
  3. Leave comments and questions in the code where necessary using Github tooling
  4. Leave an overall comment and submit your review status on the PR page. This can be to aprove the PR or to request changes based on your comments or questions.
  5. Notify the author that you have completed your review.

General considerations for reviewing: 1. Try to be prompt in your review 2. Say something nice first 3. Execute the code you review where possible 4. Ask questions about why something is done a certain way and suggest the author add more comments if you are regularly asking “why?” 5. If you can, offer code that would address a bug or a potential change 6. Consider the deploy context - how fast does it need to be?

5. Squash and merge

Once your code has been through review and approved, you are ready to squash and merge to main. Congrats! You’re a pyroRutils contributor.

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Dynamic quantitative wildfire risk assessment in R

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