Links

Smalldata_tools github: https://github.com/slac-lcls/smalldata_tools

S3DF: https://s3df.slac.stanford.edu/public/doc/#/

S3DF OnDemand: https://s3df.slac.stanford.edu/pun/sys/dashboard

PyTest: https://docs.pytest.org/en/6.2.x/contents.html

Example test from pcdsdevices: https://github.com/pcdshub/pcdsdevices/tree/master/pcdsdevices/tests

Pytest fixture: https://betterprogramming.pub/understand-5-scopes-of-pytest-fixtures-1b607b5c19ed

On-boarding

• LCLS Linux account
• S3DF account
• Setup bashrc and environment
• Clone smalldata_tools
• Read pytest docs

Implementation

• Two test suites:
  • LCLS-I
  • LCLS-II (TBD)
• Source env (subprocess.run? or have a bash script to source env and run tests)
• Tests:
  • Bash script to run the tests:
    • Source env
    • Run detector tests
  • One file per detector
  • Load / instantiate the different detectors
  • Test commonly used function: see 1.2.2 Details of the area detector analysis: DetObjectFunc to see how to implement functions
    
    • ROI
    • Projection
    • Azimuthal integration
    • Droplet
    • Photon
  • Cube

Run table

Git

Workflow

• Make a  branch: git checkout -b branch_name
• Develop code on the branch
• Commit at regular interval: git commit -m "a commit message"
• Keep track of master branch: if another pull request has been merged, you want to include these new changes in your code.
  • git checkout master
  • git pull
  • git checkout branch_name
  • git merge master
  • Resolve conflict if any
• When a milestone or an important step is reached make a pull request on github

Some useful commands

• git status
• git diff: show uncommitted changes
• git log: show commit history