cmempy - Python API¤

Introduction¤

cmempy is a Python API wrapper around the eccenca Corporate Memory HTTP APIs which can be used to rapidly script processes which interact with Corporate Memory. cmempy is also the underlying Python module which powers the cmemc - Command Line Interface.

Installation¤

cmempy is published as an Apache 2 licensed open source python package at pypi.org, hence you are able to install it with a simple pip command:

$ pip install cmem-cmempy

Configure a Connection¤

The used Corporate Memory connection is configured by providing environment variables similar to cmemc (Environment based Configuration).

These environment variables can be created and changed in your code or used from the process which executes your python code (e.g. your shell). If you have a working cmemc file based configuration setup already you can export the environment to your shell using cmemc config eval.

The following table lists all processed environment variables:

Variable	Description	Default Value
CMEM_BASE_URI	Base URL of your Corporate Memory	http://docker.localhost
DI_API_ENDPOINT	Data Integration API endpoint	CMEM_BASE_URI/dataintegration
DP_API_ENDPOINT	Data Platform API endpoint	CMEM_BASE_URI/dataplatform
OAUTH_TOKEN_URI	OAuth 2.0 Token endpoint	CMEM_BASE_URI/auth/realms/cmem/protocol/openid-connect/token
OAUTH_GRANT_TYPE	OAuth 2.0 grant type (password or client_credentials)	client_credentials
OAUTH_USER	Username to retrieve the token	admin
OAUTH_PASSWORD	Password to retrieve the token	secret
OAUTH_CLIENT_ID	OAuth 2.0 client id	cmem-service-account
OAUTH_CLIENT_SECRET	OAuth 2.0 client secret	secret
SSL_VERIFY	Verify SSL certs for API requestsv	True
REQUESTS_CA_BUNDLE	Path to the CA Bundle file (.pem)	Internal path to included CA bundle

Commented Example¤

Here is a commented code example how to configure and use cmempy.

The example demonstrates, how to execute SPARQL queries on DataPlatform, as well as how to work with the DataIntegration workspace and retrieve workflow status information:

example_usage.py

"""Basic example, how to use cmempy"""

from os import environ

from cmem.cmempy.workspace.projects.project import get_projects
from cmem.cmempy.workflow import get_workflows
from cmem.cmempy.workspace.activities.taskactivity import get_activity_status
from cmem.cmempy.queries import SparqlQuery

# setup the environment for the connection to Corporate Memory
environ["CMEM_BASE_URI"] = "http://docker.local"
environ["OAUTH_GRANT_TYPE"] = "client_credentials"
environ["OAUTH_CLIENT_ID"] = "cmem-service-account"
environ["OAUTH_CLIENT_SECRET"] = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"

# this query simply lists 5 resource subjects from the triple store
QUERY_TEXT = "SELECT DISTINCT ?s WHERE {?s ?p ?o} LIMIT 5"

# the default result is a JSON structure according to the W3C standard
# seeAlso: https://www.w3.org/TR/sparql11-results-json/
results = SparqlQuery(QUERY_TEXT).get_results()
print(results)

# loop over project descriptions
for project in get_projects():
    project_id = project["name"]
    print("Project: {}:".format(project_id))

    # loop over workflow ids for a project
    for workflow_id in get_workflows(project_id):
        # get the status object of a specific workflow
        status = get_activity_status(project_id, workflow_id)
        message = status["message"]
        print("- Workflow: {} ({}):".format(workflow_id, message))

Starting this script should result in an output similar to this:

$ python example_usage.py
{
  "head": {
    "vars": [ "s" ]
  } ,
  "results": {
    "bindings": [
      {
        "s": { "type": "uri" , "value": "https://vocab.eccenca.com/dsm/" }
      } ,
      {
        "s": { "type": "uri" , "value": "https://vocab.eccenca.com/dsm/ThesaurusProject" }
      } ,
      {
        "s": { "type": "uri" , "value": "http://www.w3.org/1999/02/22-rdf-syntax-ns#" }
      } ,
      {
        "s": { "type": "uri" , "value": "http://www.w3.org/2002/07/owl#" }
      } ,
      {
        "s": { "type": "uri" , "value": "http://www.w3.org/2000/01/rdf-schema#" }
      }
    ]
  }
}

Project: cmem:
- Workflow: my-workflow (Idle):