cimsparql 1.12.0

CIM query utilities

CIMSPARQL Query CIM data using sparql

This Python package provides functionality for reading/parsing cim data from either xml files or GraphDB into Python memory as pandas dataframes.

The package provides a set of predefined functions/queries to load CIM data such generator or branch data, though the user can easiliy extend or define their own queries.

Usage

Load data using predefined functions/queries

>>> from cimsparql.graphdb import GraphDBClient
>>> from cimsparql.url import service
>>> gdbc = GraphDBClient(service(repo='<repo>', server=127.0.0.1:7200))
>>> ac_lines = gdbc.ac_lines(limit=3)
>>> print(ac_lines[['name', 'x', 'r', 'bch']])
         name       x       r       bch
0  <branch 1>  1.9900  0.8800  0.000010
1  <branch 2>  1.9900  0.8800  0.000010
2  <branch 3>  0.3514  0.1733  0.000198

In the example above the client will query repo "" in the default server GraphDB for AC line values.

Inspect/view predefined queries

To see the actual sparql use the dry_run option:

>>> from cimsparql.queries import ac_line_query
>>> print(ac_line_query(limit=3, dry_run=True))

The resulting string contains all the prefix's available in the Graphdb repo making it easier to copy and past to graphdb. Note that the prefixes are not required in the user specified quires described below.

The dry_run option is available for all the predefined queries.

Load data using user specified queries

>>> query = 'SELECT ?mrid where { ?mrid rdf:type cim:ACLineSegment } limit 2'
>>> query_result = gdbc.get_table(query)
>>> print(query_result)

List of available repos at the server

>>> from cimsparql.url import GraphDbConfig
>>> print(GraphDbConfig().repos)

Prefix and namespace

Available namespace for current graphdb client (gdbc in the examples above), which can be used in queries (such as rdf and cim) can by found by

>>> print(gdbc.ns)
{'wgs': 'http://www.w3.org/2003/01/geo/wgs84_pos#',
 'rdf': 'http://www.w3.org/1999/02/22-rdf-syntax-ns#',
 'owl': 'http://www.w3.org/2002/07/owl#',
 'cim': 'http://iec.ch/TC57/2010/CIM-schema-cim15#',
 'gn': 'http://www.geonames.org/ontology#',
 'xsd': 'http://www.w3.org/2001/XMLSchema#',
 'rdfs': 'http://www.w3.org/2000/01/rdf-schema#',
 'SN': 'http://www.statnett.no/CIM-schema-cim15-extension#',
 'ALG': 'http://www.alstom.com/grid/CIM-schema-cim15-extension#'}

Running Tests Against Docker Databases

Tests can be run agains RDF4J and/or BlazeGraph databases if a container with the correct images are available.

docker pull eclipse/rdf4j-workbench
docker pull openkbs/blazegraph

Launch one or both containers and specify the following environment variables

RDF4J_URL = "localhost:8080/rdf4j-server"
BLAZEGRAPH_URL = "localhost:9999/blazegraph/namespace

Note 1: The port numbers may differ depending on your local Docker configurations. Note 2: You don't have to install RDF4J or BlazeGraph. Tests requiring these will be skipped in case they are not available. They will in any case be run in the CI pipeline on GitHub (where both always are available).

Data Assumptions

CimSPARQL makes certain assumptions about the data which is required to be present for the queries to work. The script modify_xml should be able to modify the XML files such that they are compliant with CimSPARQL.

1. There is a valid xml:base attribute in the top-level rdf:RDF element. This is required for uploading files (at least for RDF4J which is used in the CI pipeline)
2. All items cimsparql.constants.CIM_TYPES_WITH_MRID has cim:IdentifiedObject:mRID
3. cim:Terminal.endNumber is of type xsd:integer

poetry run python scripts/modify.xml -h

usage: Program that modifies XML files to be compatible with cimsparql [-h] [--baseURI BASEURI] [--suffix SUFFIX] file

positional arguments:
  file               File or glob pattern for files to modify

optional arguments:
  -h, --help         show this help message and exit
  --baseURI BASEURI  Base URI to insert in all XML files. For example: http://iec.ch/TC57/2013/CIM-schema-cim16
  --suffix SUFFIX    Suffix to the filename after modifying them. If given as an empty string the original files will be overwritten. Default 'mod'

In order to use the script to convert XML files into a format that can be used with cimsparql

poetry run scripts/modify_xml.py "path/to/model/*.xml"

Ontology (for developers)

Ontologies for the CIM model can be found at (ENTSOE's webpages)[https://www.entsoe.eu/digital/common-information-model/cim-for-grid-models-exchange/]. For convenience and testing purposes the ontology are located under tests/data/ontology. CIM models used for testing purposes in Cimsparql should be stored in N-quads format. In case you have a model in XML format it can be converted to N-quads by launching a DB (for example RDF4J) and upload all the XML files and the ontology.

Execute

PREFIX cims: <http://iec.ch/TC57/1999/rdf-schema-extensions-19990926#>

DELETE {?s ?p ?o}
INSERT {?s ?p ?o_cast} WHERE {
  ?s ?p ?o .
  ?p cims:dataType ?_dtype .
  ?_dtype cims:stereotype ?stereotype .
  BIND(IF(?stereotype = "Primitive",
    URI(concat("http://www.w3.org/2001/XMLSchema#", lcase(strafter(str(?_dtype), "#")))),
    ?_dtype) as ?dtype)
  BIND(STRDT(?o, ?dtype) as ?o_cast)
}

and export as N-quads.

Note: Make sure the base URI is either specified in the XML-files or when you upload. It should be set to

<rdf:RDF xml:base="http://iec.ch/TC57/2013/CIM-schema-cim16">

Test models

1. micro_t1_nl: MicroGrid/Type1_T1/CGMES_v2.4.15_MicroGridTestConfiguration_T1_NL_Complete_v2

Rest APIs

CimSparql mainly uses SparqlWrapper to communicate with the databases. However, there are certain operations which are performed directly via REST calls. Since there are small differences between different APIs you may have to specify which API you are using. This can be done when initializing the ServiceCfg class or by specifying the SPARQL_REST_API environment variable. Currently, RDF4J and blazegraph is supported (if not given RDF4J is default).

export SPARQL_REST_API=RDF4J  # To use RDF4J
export SPARQL_REST_API=BLAZEGRAPH  # To use BlazeGraph