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Workflow Rules

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Jonathan edited this page May 22, 2022 · 1 revision

Standard Workflow 🗄

When working on this project here are steps and standards to follow when working on tickets and pull requests (PR's)

Ticket Workflow

When working on a ticket, create a new branch with the id of the ticket as the name of the branch. If the ticket has an id of 10 the command would be as follows:

git checkout -b 10

Move the ticket from todo to doing on the board. Proceed to make the changes specified in the ticket after you think your change meets the requirements. Make a descriptive commit and publish your branch. Make sure that at the end of your commit message that the format #000 corresponds to the ticket you are working on.

git commit -m "What I did #10"
git push -u origin 10

After your changes are pushed make a PR with your changes so that others on the team can see what you did and approve your work. Make sure that the pipeline passes, if not make updates to your ticket so that it does. Your ticket will be auto squashed.

Once your code is good, passes the pipeline, and approved by the team merge into main and move the ticket from doing to done.

Best Practices

The smaller the PR's the better if your code is very confusing on a PR split your work into multiple tickets.

Make sure that you are being descriptive in your comments and messages. The more context and images you can provide surrounding what you are doing the more everyone else will understand what you are doing and the more maintainable our work will be.

Environment

Our project consists of primarily node and python environments which are all deployed using docker containers to google cloud. To develop locally make sure that all of the following are installed on your device.

To work locally with our repo clone it with this command:

git clone https://git.ece.iastate.edu/sd/sdmay22-35.git

Front End

$ cd frontend
$ yarn
$ yarn dev

Back End

Our project is a monorepo containing various services meaning that there are multiple backend projects. cd into the desired project and run the following commands to run the code.

$ cd project  ie. ml/prediction
$ cd src
$ python3 -m flask run

Clone this wiki locally