runregistry 0.1.3

CMS Run Registry client

Run Registry Client

Python client to retrieve and query data from CMS Run Registry.

Installation

pip install runregistry

Authentication (Prerequisite)

You must provide a way for the client to access a Grid user certificate.

You can either do this in 3 possible ways:

1. Provide the certificate manually (explained below).
2. providing the user certificate in the conventional path (first ~\private\ and second ~\.globus\).
3. Setting your own path where you store the certificate in an environment variable: CERN_CERTIFICATE_PATH

Provide the certificate manually

1. Download a grid user certificate from here.
2. Convert it into public and private key (The certificates have to be passwordless. ):

mkdir -p ~/private
openssl pkcs12 -clcerts -nokeys -in myCertificate.p12 -out ~/private/usercert.pem
openssl pkcs12 -nocerts -in myCertificate.p12 -out ~/private/userkey.tmp.pem
openssl rsa -in ~/private/userkey.tmp.pem -out ~/private/userkey.pem

Usage

Get a single run (get_run):

import runregistry
runregistry.get_run(run_number=328762)

Query several runs (get_runs):

import runregistry
runregistry.get_runs(run_number={
    'or': [328762, 323555, 323444]
})

Apply a custom filter (run_numbers between 309000 and 310000 which had at least one GOOD dt lumisection):

import runregistry
runregistry.get_runs(
    filter={
        'run_number': {
            'and':[
                '>': 309000,
                '<': 310000
            ]
        },
        'dt': 'GOOD'
    }
)

Depending on the attribute you can use different operators:

Attribute	Supported operators
Integer/float	'=', '>', '<', '>=', '<=', '<>'
String	=, like, notlike
Boolean	= (true, false)

When using 'like' or 'notlike' operator, you must surround your query with percentage signs, see example below.

When filtering for triplet attributes (anything that is GOOD/BAD/STANDBY...) you must not use any String values, the only value allowed is strict equality '=' and is set by default.

You can combine the filters as well:

import runregistry
runregistry.get_runs(
    filter={
        'run_number': {
            'and':[
                '>': 309000,
                '<': 310000
            ]
        },
        'hlt_key': {
            'like': '%commissioning2018%'
        }
        'significant': {
            '=': True
        }
    }
)

If by observing the Network Requests in RR web application, you want to use the same filters observed by the network request. Just passs ignore_filter_transformation=True to any query.

Example (run_numbers between 309000 and 310000 which had at least one GOOD dt lumisection):

import runregistry
runregistry.get_runs(
    filter={
        'run_number': {
            '>': 309000, '<': 310000
        },
        'oms_attributes.hlt_key': {
            'like': '%commissioning2018%'
        },
        'triplet_summary.dt_triplet.GOOD': {
            '>': 0
        }
    },
    ignore_filter_transformation=True
)

Also, if by observing the Network Requests in RR web application, you want to obtain the data as it is seen in the network requests. Just compress_attributes=False, for example:

import runregistry
runregistry.get_runs(
    filter={
        'run_number': {
            'and':[
                '>': 309000,
                '<': 310000
            ]
        },
        'dt': 'GOOD'
    },
    compress_attributes=False
)

querying by comments and cause is not yet possible