blackfox-restapi

• API version: v1
• Package version: 5.0.0
• Service version 5.0.0
• Build package: org.openapitools.codegen.languages.PythonClientCodegen

Requirements.

Python 2.7 and 3.4+

Installation & Usage

pip install

If the python package is hosted on a repository, you can install directly using:

pip install git+https://github.com/vodena/BlackFoxRestApiPython.git

(you may need to run pip with root permission: sudo pip install git+https://github.com/vodena/BlackFoxRestApiPython.git)

Then import the package:

import blackfox_restapi

Setuptools

Install via Setuptools.

python setup.py install --user

(or sudo python setup.py install to install the package for all users)

Then import the package:

import blackfox_restapi

Getting Started

Please follow the installation procedure and then run the following:

from __future__ import print_function
import time
import blackfox_restapi
from blackfox_restapi.rest import ApiException
from pprint import pprint


# Defining host is optional and default to http://localhost
configuration.host = "http://localhost"
# Enter a context with an instance of the API client
with blackfox_restapi.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = blackfox_restapi.AnnModelApi(api_client)
    id = 'id_example' # str | File hash(sha1)
integrate_scaler = False # bool | Integrate scaler in model (optional) (default to False)
model_type = blackfox_restapi.NeuralNetworkType() # NeuralNetworkType | h5, onnx, pb (optional)

    try:
        # Download model file
        api_response = api_instance.download(id, integrate_scaler=integrate_scaler, model_type=model_type)
        pprint(api_response)
    except ApiException as e:
        print("Exception when calling AnnModelApi->download: %s\n" % e)
    

Documentation for API Endpoints

All URIs are relative to http://localhost

Class	Method	HTTP request	Description
AnnModelApi	download	GET /api/ann/model/{id}	Download model file
AnnModelApi	exists	HEAD /api/ann/model/{id}	Check if model file exist
AnnModelApi	get_metadata	GET /api/ann/model/{id}/metadata	Get model metadata
AnnModelApi	upload	POST /api/ann/model	Upload model file
AnnOptimizationApi	delete	DELETE /api/ann/{id}
AnnOptimizationApi	get_model_id	GET /api/ann/{id}/model-id/{generation}	Get id of best model for given generation
AnnOptimizationApi	get_status	GET /api/ann/{id}/status	Get status of optimization
AnnOptimizationApi	start	POST /api/ann	Starts new optimization using ann
AnnOptimizationApi	start_series	POST /api/ann/series	Starts new series optimization using ann
AnnOptimizationApi	stop	POST /api/ann/{id}/action/stop	Stop running optimization
AnnPredictionApi	predict_from_array	POST /api/ann/prediction/array	Predict values from array
AnnPredictionApi	predict_from_file	POST /api/ann/prediction/file	Predict values from file
AnnTrainingApi	train	POST /api/ann/train
AnnTrainingApi	train_series	POST /api/ann/train/series
DataSetApi	download	GET /api/dataset/{id}	Download dataset file (*.csv)
DataSetApi	exists	HEAD /api/dataset/{id}	Check if dataset file exist
DataSetApi	upload	POST /api/dataset	Upload dataset file (*.csv)
InfoApi	get	GET /api/info
RandomForestModelApi	download	GET /api/random-forest/model/{id}	Download model file (*.h5)
RandomForestModelApi	exists	HEAD /api/random-forest/model/{id}	Check if h5 file exist
RandomForestModelApi	get_metadata	GET /api/random-forest/model/{id}/metadata	Get model metadata
RandomForestModelApi	upload	POST /api/random-forest/model	Upload model(binary file)
RandomForestOptimizationApi	delete	DELETE /api/random-forest/{id}
RandomForestOptimizationApi	get_model_id	GET /api/random-forest/{id}/model-id/{generation}	Get id of best model for given generation
RandomForestOptimizationApi	get_status	GET /api/random-forest/{id}/status	Get status of optimization
RandomForestOptimizationApi	start	POST /api/random-forest	Starts new optimization using random forest
RandomForestOptimizationApi	start_series	POST /api/random-forest/series	Starts new series optimization using random forest
RandomForestOptimizationApi	stop	POST /api/random-forest/{id}/action/stop	Stop running optimization
RnnModelApi	download	GET /api/rnn/model/{id}	Download model file
RnnModelApi	exists	HEAD /api/rnn/model/{id}	Check if model file exist
RnnModelApi	get_metadata	GET /api/rnn/model/{id}/metadata	Get model metadata
RnnModelApi	upload	POST /api/rnn/model	Upload model file
RnnOptimizationApi	delete	DELETE /api/rnn/{id}
RnnOptimizationApi	get_model_id	GET /api/rnn/{id}/model-id/{generation}	Get id of best model for given generation
RnnOptimizationApi	get_status	GET /api/rnn/{id}/status	Get status of optimization
RnnOptimizationApi	start	POST /api/rnn	Starts new reccurent neural network optimization
RnnOptimizationApi	stop	POST /api/rnn/{id}/action/stop	Stop running optimization
XGBoostModelApi	download	GET /api/xgboost/model/{id}	Download model file (*.bin)
XGBoostModelApi	exists	HEAD /api/xgboost/model/{id}	Check if h5 file exist
XGBoostModelApi	get_metadata	GET /api/xgboost/model/{id}/metadata	Get model metadata
XGBoostModelApi	upload	POST /api/xgboost/model	Upload model(binary file)
XGBoostOptimizationApi	delete	DELETE /api/xgboost/{id}	Delete optimization from optimization service
XGBoostOptimizationApi	get_model_id	GET /api/xgboost/{id}/model-id/{generation}	Get id of best model for given generation
XGBoostOptimizationApi	get_status	GET /api/xgboost/{id}/status	Get status of optimization
XGBoostOptimizationApi	start	POST /api/xgboost	Start XGBoost optimization
XGBoostOptimizationApi	start_series	POST /api/xgboost/series	Starts new series optimization using XGBoost model
XGBoostOptimizationApi	stop	POST /api/xgboost/{id}/action/stop	Stop running optimization

Documentation For Models

• AggregationType
• AnnHiddenLayerConfig
• AnnLayerConfig
• AnnModel
• AnnOptimizationConfig
• AnnOptimizationEngineConfig
• AnnOptimizationStatus
• AnnSeriesOptimizationConfig
• AnnSeriesTrainingConfig
• AnnTrainingConfig
• BinaryMetric
• ConvergencyCriterion
• Encoding
• InputConfig
• InputWindowConfig
• InputWindowRangeConfig
• NeuralNetworkActivationFunction
• NeuralNetworkTrainingAlgorithm
• NeuralNetworkType
• OptimizationAlgorithm
• OptimizationEngineConfig
• OptimizationState
• OutputConfig
• OutputWindowConfig
• PredictionArrayConfig
• PredictionFileConfig
• ProblemDetails
• ProblemType
• RandomForestModel
• RandomForestModelType
• RandomForestOptimizationConfig
• RandomForestOptimizationStatus
• RandomForestSeriesOptimizationConfig
• Range
• RangeInt
• RegressionMetric
• RnnHiddenLayerConfig
• RnnModel
• RnnOptimizationConfig
• RnnOptimizationStatus
• ServiceInfo
• TrainedNetwork
• XGBoostModel
• XGBoostOptimizationConfig
• XGBoostOptimizationStatus
• XGBoostSeriesOptimizationConfig

Documentation For Authorization

All endpoints do not require authorization.

Author