airML 0.0.2

application will allow users to share and dereference ML models.

airML

Distributed Deployment of ML models at scale

This package is created to distribute KBox, which allow users to share and dereference ML models.

• Download the library here

• Install using pip

pip install airML

Use it in from your terminal

Once you install the airML package, you can directly execute the commands from the terminal. You don't need to open up a python environment to use the airML package.

Open a terminal and execute KBox commands in python with airML package as below,

airML list -o json

**Note: Here the -o json is an optional parameter. If you want to get the output as a json message, you should use this. Otherwise, use the command without -o json.

{
    "status_code": 200,
    "message": "visited all KNs.",
    "results": [
        {
            "name": "http://purl.org/pcp-on-web/dbpedia",
            "format": "kibe",
            "version": "c9a618a875c5d46add88de4f00b538962f9359ad"
        },
        {
            "name": "http://purl.org/pcp-on-web/ontology",
            "format": "kibe",
            "version": "c9a618a875c5d46add88de4f00b538962f9359ad"
        },
        {
            "name": "http://purl.org/pcp-on-web/dataset",
            "format": "kibe",
            "version": "dd240892384222f91255b0a94fd772c5d540f38b"
        }
    ]
}

Like the above command, you can use all other KBox commands with airML package. You can refer to the document here to get a good understanding of other KBox commands as well.

Use it in your python application.

execute(command)

Description: Execute the provided command in the KBox.jar
Args:
  command: 'string', KBox command which should be exectue in KBox.
Returns:
    string

If you want to use the airML inside your python application, you can follow these instructions,

1. Import the airML package (from airML import airML).

2. Execute any KBox command with execute() function as follows.

   airML.execute('KBox_Command')
   

**Note: execute() method will return a string output which contains the result of the executed command.

Other than the execute command you can use following methods directly,

list(kns=False)

Description: List all available models(kns=False) or list all KNS services(kns=True).
Args:
  kns:'boolean',defines whether to list only the KNS services or not
Returns:
        Results from the KBox as JSON String

install(modelID, format=None, version=None):

Description: Install the a model by given modelID
 Args:
     modelID: 'string', url of the model hosted in a public repository.
     format:  'string', format of the model.
     version: 'string' specific version to be installed of the the model.
 Returns:
     Results from the kbox as JSON String
 Example:
     install("http://nspm.org/art","NSPM","0")

getInfo(model):

Description: Gives the information about a specific model.
Args:
    model: url of the model.
Return:
    Results from the kbox as JSON String

locate(modelID, format, version=None):

Description: Returns the local address of the given model.
Args:
    modelID: 'string',url of the model to be located.
    format: 'string',format of the model.
    version: 'string',version of the model.
Returns:
    Results from the kbox as JSON String

search(pattern, format, version=None):

Description: Search for all model-ids containing a given pattern.
Args:
    pattern: 'string',pattern of the url of the models.
    format: 'string',format of the model.
    version: 'string',version of the model.
Returns:
    Search Result from the KBox as a JSON String

Source URLs

• See the source for this project here
• Find the KBox source code here