Metadata-Version: 2.1
Name: accern-xyme
Version: 0.1.0
Summary: AccernXYME is a library for easily accessing XYME via python.
Home-page: https://github.com/Accern/accern-xyme
Author: Accern Corp.
Author-email: josua.krause@accern.com
License: MIT
Description: Accern-XYME
        ===========
        
        *accern\_xyme* is a python library for accessing XYME functionality.
        
        |CircleCI|
        
        .. |CircleCI| image:: https://circleci.com/gh/Accern/accern-xyme.svg?style=svg
           :target: https://circleci.com/gh/Accern/accern-xyme
        
        Usage
        -----
        
        For XYME legacy information use the latest version before
        `v0.1.0 <https://github.com/Accern/accern-xyme/tree/legacy>`_
        
        You can install *accern\_xyme* with pip:
        
        .. code:: sh
        
            pip install --user accern-xyme
        
        Import it in python via:
        
        .. code:: python
        
            from accern_xyme import create_xyme_client
        
            client = create_xyme_client("https://xyme.accern.com/", "<USERNAME>", "<PASSWORD>")
            print(client.get_user_info())
        
        :code:`<USERNAME>` and :code:`<PASSWORD>` are the login credentials for XYME.
        The values can also be set to :code:`None` in which case the values must
        be set in the environment variables :code:`ACCERN_USER`
        and :code:`ACCERN_PASSWORD`. A login token can also be provided.
        
        You will need python3.6 or later.
        
        Exploring Workspaces
        --------------------
        
        The workspaces of the user can be retrieved via:
        
        .. code:: python
        
            for (workspace, count) in client.get_workspaces().items():
                print(f"{workspace} contains {count} jobs")
        
        And jobs in a given workspace can be retrieved via:
        
        .. code:: python
        
            for job in client.get_jobs(workspace):
                print(f"{job.get_job_id()}: {job.get_name()} - {job.get_status()}")
        
        Or directly by Job ID:
        
        .. code:: python
        
            job = client.get_job_id("username_example_com/job_id")
        
        Starting Jobs
        -------------
        
        A new job can be started via:
        
        .. code:: python
        
            # creating the job
            job = client.create_job(schema=schema_obj, name="my job")
        
            with job.update_schema() as cur:
                # updating the schema
                cur["M"]["params"]["hidden_layer_sizes"] = [100, 100, 100]
        
            # starting the job
            job.start()
        
            import time
            time.sleep(30)
        
            print(job.get_status())
        
        Computing Predictions
        ---------------------
        
        Predictions can be obtained for a finished or running job:
        
        .. code:: python
        
            # predict_proba is also available
            predictions, stdout = job.predict(df)
            print(stdout)
        
            print("prediction of first row: ", predictions.iloc[0])
        
Keywords: XYME AI machine learning client
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Provides-Extra: dev
Provides-Extra: test
