Metadata-Version: 2.1
Name: airML
Version: 0.0.2
Summary: application will allow users to share and dereference ML models.
Home-page: https://github.com/AKSW/airML
Author-email: oshara.16@cse.mrt.ac.lk
License: Apache
Description: # 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](https://test.pypi.org/project/airML/)
        
        * 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](https://github.com/AKSW/KBox#how-can-i-execute-kbox-in-command-line) 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](https://github.com/AKSW/airML)
        * Find the KBox source code [here](https://github.com/AKSW/KBox)
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
