NSLS2 Beamlines simdb prototype implemented in MongoDB.

##Object Model 

##What database technology is simdb using? MongoDB.

##Where is this mongo database located? Run this code snippet:

import simdb
print(simdb.conf.connection_config)

And you will see this output.

{'database': 'mds',
 'host': 'localhost',
 'port': 27017,
 'timezone': 'US/Eastern'}

Note that the values for database, host, port, timezone may be different.

• database is the actual name of the mongo database
• host is the IP or DNS name of the server where the mongo database is actually located
• port is the port that mongoengine and pymongo use to connect to the database located at host
• timezone is the timezone of the database.

###Can I change where the mongo database is located at runtime? Yes. For example:

import simdb
new_database_name = 'one-database-to-rule-them-all'
new_host = '1.2.3.4'
simdb.conf.connection_config['database'] = new_database_name
simdb.conf.connection_config['host'] = new_host_name

After running this, simdb will be pointed at this new database for the duration of your python session. Note that this change is not persistent between python sessions!

##Description of the fields in each document ###BeamlineConfig [Source] (https://github .com/NSLS-II/simdb/blob/master/simdb/odm_templates.py#L17)

The beamline configuration is intentionally ambiguous and is generally left up to the user to decide. It is intended to be a bucket for any and all information that is constant across multiple runs/scans, but can also be used to store run-specific information, if the user so chooses.

The following fields are guaranteed to be in each BeamlineConfig document.

• uid: A string unique identifier that may be provided to simdb. If no uid is provided, simdb defaults to generating a uuid4.
  Note that this uid must be unique across all BeamlineConfig documents that are stored in the database that simdb is currently pointing to.
• time: The time that is provided to the insert_beamline_config function in simdb, not when the document is saved into mongo. In practice, this difference is a few ms.
• config_params: A dictionary field that is otherwise free-form. This is where all relevant information that you, the user, wish to store should go.

An example of the kind of information that might be good to store in the BeamlineConfig document would be the distance from the sample to the detector, various detector parameters (size of pixels in um), and perhaps a pointer to the most recent calibration scan. Such a BeamlineConfig might look like this:

BeamlineConfig
==============
calibration_scan_uid      : 6e78b971-30bb-4f48-8621-1ab95c2ccf94    
config_params             :
detector_dist             : 100                                     
detector_dist_units       : cm                                      
detector_pixel_size       : (100, 100)                              
detector_pixel_size_units : um                                      
time                      : 1433449177.4622374                      
time_as_datetime          : 2015-06-04 16:19:37.462237              
uid                       : 4c2d54a4-be2f-4b65-a520-695566fe4aa2    

###RunStart [Source] (https://github.com/NSLS-II/simdb/blob/master/simdb /odm_templates.py#L33)

The RunStart document