py2/h2o_ray.py
def model_builders(self, algo=None, timeoutSecs=10, **kwargs):
    '''
    Return a model builder or all of the model builders known to the
    h2o cluster.  The model builders are contained in a dictionary
    called "model_builders" at the top level of the result.  The
    dictionary maps algorithm names to parameters lists.  Each of the
    parameters contains all the metdata required by a client to
    present a model building interface to the user.

    if parameters = True, return the parameters?
    '''
    params_dict = {}
    h2o_methods.check_params_update_kwargs(params_dict, kwargs, 'model_builders', False)

    request = '3/ModelBuilders.json' 
    if algo:
        request += "/" + algo

    result = self.do_json_request(request, timeout=timeoutSecs, params=params_dict)
    # verboseprint(request, "result:", dump_json(result))
    h2o_sandbox.check_sandbox_for_errors()
    return result
def model_builders(self, algo=None, timeoutSecs=10, **kwargs):
    '''
    Return a model builder or all of the model builders known to the
    h2o cluster.  The model builders are contained in a dictionary
    called "model_builders" at the top level of the result.  The
    dictionary maps algorithm names to parameters lists.  Each of the
    parameters contains all the metdata required by a client to
    present a model building interface to the user.

    if parameters = True, return the parameters?
    '''
    params_dict = {}
    h2o_methods.check_params_update_kwargs(params_dict, kwargs, 'model_builders', False)

    request = '3/ModelBuilders.json' 
    if algo:
        request += "/" + algo

    result = self.do_json_request(request, timeout=timeoutSecs, params=params_dict)
    # verboseprint(request, "result:", dump_json(result))
    h2o_sandbox.check_sandbox_for_errors()
    return result
Return a model builder or all of the model builders known to the
    h2o cluster.  The model builders are contained in a dictionary
    called "model_builders" at the top level of the result.  The
    dictionary maps algorithm names to parameters lists.  Each of the
    parameters contains all the metdata required by a client to
    present a model building interface to the user.

    if parameters = True, return the parameters?