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1. Make a GitHub account and record your username (personal or work email is fine)
2. Add your ssh key to your GitHub account
3. Navigate to the #comp-general Slack channel 
4. Create a SLAC GitHub access workflow (the + with the lightning bolt at the bottomWorkflow button at the top near the channel name). An admin will review and grant you access
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1. Run conda install --update-all --force-reinstall -y -c conda-forge bmad
2. Run git clone git@github.com:slaclab/lcls-lattice.git
   1. This repo can live wherever, just remember where it lives
   2. You may need to request access
3. Set the LCLS_LATTICE environment variable to wherever the repo in step 2 lives
4. Run git clone git@github.com:slaclab/simulacrum.git and remember where it lives
5. Navigate to the newly cloned simulacrum repo and run pip install . 
6. Run python <service directory>/<service>.py for any service you want running

   1. This will eat a terminal tab. I strongly advise against backgrounding because you'll need to kill the process eventually, and if you background it you'll either need to remember the process ID or find it later

   2. For SRF work specifically, we typically only need the sc_rf_service so the command would be python sc_rf_service/sc_rf_service.py
      1. All other services typically need the model service running with the appropriate beam line flag (python model_service/model_service.py [lcls classic | cu_hxr | cu_spec | cu_sxr | sc_hxr | sc_sxr])

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