Assessment_fns

This is the core collection of functions used for the assessment of Offshore Scallop.

To install Git: https://git-scm.com/download/win

Some tips/best practices: https://guides.github.com/introduction/flow/

We have modified the typical GitHub workflow so that we can work from our network and users can access their scripts from a remote VPN connection. Our general idea for a workflow comes from here https://nvie.com/files/Git-branching-model.pdf, with some revisions to work from a network and minimize uncessary duplication.

The workflow is as follows

1: New users should be added as collaborators (talk to Dave or Freya)

2: FORK the Mar-scal MASTER to your personal github account

• This is your personal DEVELOPMENT version of the MASTER repo housed in Mar-scal.

3: On your computer you will clone your FORK repo to Y:\Github\Offshore\Assessment_fns\YOUR_NAME.

• This directory is where you will work on revisions.
• WE NEVER WORK in the directory where the MASTER resides (i.e. Y:\Offshore\Assessment\Assessment_fns)

4: All independent work is to be performed on a branch inside your personal FORK that resides in Y:\Github....

• Please name you branch something informative, e.g. Mapping update, survey bugfix, etc.

5: When you have completed your revisions COMMIT the revisions to your branch

6: Create a PULL REQUEST to merge the data into your FORK.

• Within your fork you can take care of your own pull requests.

7: Test your changes to ensure there are no bugs within your FORK

8: You can now submit a PULL REQUEST from your FORK to the Mar-scal MASTER

• For now DK/FK will review the PULL REQUEST to ensure it does not cause any issues. -DK/FK will also identify any ISSUES that need to be opened and/or closed, and integrated with pull requests too.
• If you are aware of ISSUES being resolved/opened feel free to integrate these into the PULL REQUEST yourself

Collaborators CAN merge their pull requests independently, but complicated edits MUST be discussed before being merged with the master on Mar-scal as these are now immediately implemented on our shared network.