Пример #1
0
    def __init__(self, username=None, api_key=None, dev_mode=False,
                 debug=False, set_locale=False, storage=None, domain=None):
        """Initializes the BigML API.

        If left unspecified, `username` and `api_key` will default to the
        values of the `BIGML_USERNAME` and `BIGML_API_KEY` environment
        variables respectively.

        If `dev_mode` is set to `True`, the API will be used in development
        mode where the size of your datasets are limited but you are not
        charged any credits.

        If storage is set to a directory name, the resources obtained in
        CRU operations will be stored in the given directory.

        If domain is set, the api will point to the specified domain. Default
        will be the one in the environment variable `BIGML_DOMAIN` or
        `bigml.io` if missing. The expected domain argument is a string or a
        Domain object. See Domain class for details.

        """

        BigMLConnection.__init__(self, username=username, api_key=api_key,
                                 dev_mode=dev_mode, debug=debug,
                                 set_locale=set_locale, storage=storage,
                                 domain=domain)
        ResourceHandler.__init__(self)
        SourceHandler.__init__(self)
        DatasetHandler.__init__(self)
        ModelHandler.__init__(self)
        EnsembleHandler.__init__(self)
        PredictionHandler.__init__(self)
        ClusterHandler.__init__(self)
        CentroidHandler.__init__(self)
        AnomalyHandler.__init__(self)
        AnomalyScoreHandler.__init__(self)
        EvaluationHandler.__init__(self)
        BatchPredictionHandler.__init__(self)
        BatchCentroidHandler.__init__(self)
        BatchAnomalyScoreHandler.__init__(self)
        ProjectHandler.__init__(self)
        SampleHandler.__init__(self)

        self.getters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.getters[resource_type] = getattr(self, "get_%s" % method_name)
        self.creaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.creaters[resource_type] = getattr(self,
                                                   "create_%s" % method_name)
        self.updaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.updaters[resource_type] = getattr(self,
                                                   "update_%s" % method_name)
        self.deleters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.deleters[resource_type] = getattr(self,
                                                   "delete_%s" % method_name)
Пример #2
0
    def __init__(self,
                 username=None,
                 api_key=None,
                 dev_mode=False,
                 debug=False,
                 set_locale=False,
                 storage=None,
                 domain=None):
        """Initializes the BigML API.

        If left unspecified, `username` and `api_key` will default to the
        values of the `BIGML_USERNAME` and `BIGML_API_KEY` environment
        variables respectively.

        If `dev_mode` is set to `True`, the API will be used in development
        mode where the size of your datasets are limited but you are not
        charged any credits.

        If storage is set to a directory name, the resources obtained in
        CRU operations will be stored in the given directory.

        If domain is set, the api will point to the specified domain. Default
        will be the one in the environment variable `BIGML_DOMAIN` or
        `bigml.io` if missing. The expected domain argument is a string or a
        Domain object. See Domain class for details.

        """

        BigMLConnection.__init__(self,
                                 username=username,
                                 api_key=api_key,
                                 dev_mode=dev_mode,
                                 debug=debug,
                                 set_locale=set_locale,
                                 storage=storage,
                                 domain=domain)
        ResourceHandler.__init__(self)
        SourceHandler.__init__(self)
        DatasetHandler.__init__(self)
        ModelHandler.__init__(self)
        EnsembleHandler.__init__(self)
        PredictionHandler.__init__(self)
        ClusterHandler.__init__(self)
        CentroidHandler.__init__(self)
        AnomalyHandler.__init__(self)
        AnomalyScoreHandler.__init__(self)
        EvaluationHandler.__init__(self)
        BatchPredictionHandler.__init__(self)
        BatchCentroidHandler.__init__(self)
        BatchAnomalyScoreHandler.__init__(self)
        ProjectHandler.__init__(self)
        SampleHandler.__init__(self)
        CorrelationHandler.__init__(self)
        StatisticalTestHandler.__init__(self)
        LogisticRegressionHandler.__init__(self)
        AssociationHandler.__init__(self)
        AssociationSetHandler.__init__(self)
        ScriptHandler.__init__(self)
        ExecutionHandler.__init__(self)
        LibraryHandler.__init__(self)

        self.getters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.getters[resource_type] = getattr(self, "get_%s" % method_name)
        self.creaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.creaters[resource_type] = getattr(self,
                                                   "create_%s" % method_name)
        self.updaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.updaters[resource_type] = getattr(self,
                                                   "update_%s" % method_name)
        self.deleters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.deleters[resource_type] = getattr(self,
                                                   "delete_%s" % method_name)
Пример #3
0
    def __init__(self, username=None, api_key=None, dev_mode=False,
                 debug=False, set_locale=False, storage=None, domain=None,
                 project=None, organization=None):
        """Initializes the BigML API.

        If left unspecified, `username` and `api_key` will default to the
        values of the `BIGML_USERNAME` and `BIGML_API_KEY` environment
        variables respectively.

        If `dev_mode` is set to `True`, the API will be used in development
        mode where the size of your datasets are limited but you are not
        charged any credits.

        If storage is set to a directory name, the resources obtained in
        CRU operations will be stored in the given directory.

        If domain is set, the api will point to the specified domain. Default
        will be the one in the environment variable `BIGML_DOMAIN` or
        `bigml.io` if missing. The expected domain argument is a string or a
        Domain object. See Domain class for details.

        When project is set to a project ID,
        the user is considered to be working in an
        organization project. The scope of the API requests will be limited
        to this project and permissions should be previously given by the
        organization administrator.

        When organization is set to an organization ID,
        the user is considered to be working for an
        organization. The scope of the API requests will be limited to the
        projects of the organization and permissions need to be previously
        given by the organization administrator.

        """

        BigMLConnection.__init__(self, username=username, api_key=api_key,
                                 dev_mode=dev_mode, debug=debug,
                                 set_locale=set_locale, storage=storage,
                                 domain=domain, project=project,
                                 organization=organization)
        ResourceHandler.__init__(self)
        SourceHandler.__init__(self)
        DatasetHandler.__init__(self)
        ModelHandler.__init__(self)
        EnsembleHandler.__init__(self)
        PredictionHandler.__init__(self)
        ClusterHandler.__init__(self)
        CentroidHandler.__init__(self)
        AnomalyHandler.__init__(self)
        AnomalyScoreHandler.__init__(self)
        EvaluationHandler.__init__(self)
        BatchPredictionHandler.__init__(self)
        BatchCentroidHandler.__init__(self)
        BatchAnomalyScoreHandler.__init__(self)
        ProjectHandler.__init__(self)
        SampleHandler.__init__(self)
        CorrelationHandler.__init__(self)
        StatisticalTestHandler.__init__(self)
        LogisticRegressionHandler.__init__(self)
        AssociationHandler.__init__(self)
        AssociationSetHandler.__init__(self)
        ScriptHandler.__init__(self)
        ExecutionHandler.__init__(self)
        LibraryHandler.__init__(self)
        TopicModelHandler.__init__(self)
        TopicDistributionHandler.__init__(self)
        BatchTopicDistributionHandler.__init__(self)
        TimeSeriesHandler.__init__(self)
        ForecastHandler.__init__(self)
        DeepnetHandler.__init__(self)
        OptimlHandler.__init__(self)
        FusionHandler.__init__(self)
        ConfigurationHandler.__init__(self)
        PCAHandler.__init__(self)
        ProjectionHandler.__init__(self)
        BatchProjectionHandler.__init__(self)
        LinearRegressionHandler.__init__(self)
        self.status_url = "%s%s" % (self.url, STATUS_PATH)


        self.getters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.getters[resource_type] = getattr(self, "get_%s" % method_name)
        self.creaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.creaters[resource_type] = getattr(self,
                                                   "create_%s" % method_name)
        self.updaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.updaters[resource_type] = getattr(self,
                                                   "update_%s" % method_name)
        self.deleters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.deleters[resource_type] = getattr(self,
                                                   "delete_%s" % method_name)
        self.listers = {}
        for resource_type in RESOURCE_RE:
            method_name = IRREGULAR_PLURALS.get( \
                resource_type, "%ss" % RENAMED_RESOURCES.get( \
                resource_type, resource_type))
            self.listers[resource_type] = getattr(self,
                                                  "list_%s" % method_name)
Пример #4
0
    def __init__(self, username=None, api_key=None, dev_mode=False,
                 debug=False, set_locale=False, storage=None, domain=None,
                 project=None, organization=None):
        """Initializes the BigML API.

        If left unspecified, `username` and `api_key` will default to the
        values of the `BIGML_USERNAME` and `BIGML_API_KEY` environment
        variables respectively.

        If `dev_mode` is set to `True`, the API will be used in development
        mode where the size of your datasets are limited but you are not
        charged any credits.

        If storage is set to a directory name, the resources obtained in
        CRU operations will be stored in the given directory.

        If domain is set, the api will point to the specified domain. Default
        will be the one in the environment variable `BIGML_DOMAIN` or
        `bigml.io` if missing. The expected domain argument is a string or a
        Domain object. See Domain class for details.

        When project is set to a project ID,
        the user is considered to be working in an
        organization project. The scope of the API requests will be limited
        to this project and permissions should be previously given by the
        organization administrator.

        When organization is set to an organization ID,
        the user is considered to be working for an
        organization. The scope of the API requests will be limited to the
        projects of the organization and permissions need to be previously
        given by the organization administrator.

        """

        BigMLConnection.__init__(self, username=username, api_key=api_key,
                                 dev_mode=dev_mode, debug=debug,
                                 set_locale=set_locale, storage=storage,
                                 domain=domain, project=project,
                                 organization=organization)
        ResourceHandler.__init__(self)
        SourceHandler.__init__(self)
        DatasetHandler.__init__(self)
        ModelHandler.__init__(self)
        EnsembleHandler.__init__(self)
        PredictionHandler.__init__(self)
        ClusterHandler.__init__(self)
        CentroidHandler.__init__(self)
        AnomalyHandler.__init__(self)
        AnomalyScoreHandler.__init__(self)
        EvaluationHandler.__init__(self)
        BatchPredictionHandler.__init__(self)
        BatchCentroidHandler.__init__(self)
        BatchAnomalyScoreHandler.__init__(self)
        ProjectHandler.__init__(self)
        SampleHandler.__init__(self)
        CorrelationHandler.__init__(self)
        StatisticalTestHandler.__init__(self)
        LogisticRegressionHandler.__init__(self)
        AssociationHandler.__init__(self)
        AssociationSetHandler.__init__(self)
        ScriptHandler.__init__(self)
        ExecutionHandler.__init__(self)
        LibraryHandler.__init__(self)
        TopicModelHandler.__init__(self)
        TopicDistributionHandler.__init__(self)
        BatchTopicDistributionHandler.__init__(self)
        TimeSeriesHandler.__init__(self)
        ForecastHandler.__init__(self)
        DeepnetHandler.__init__(self)
        OptimlHandler.__init__(self)
        FusionHandler.__init__(self)
        ConfigurationHandler.__init__(self)
        PCAHandler.__init__(self)
        ProjectionHandler.__init__(self)
        BatchProjectionHandler.__init__(self)


        self.getters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.getters[resource_type] = getattr(self, "get_%s" % method_name)
        self.creaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.creaters[resource_type] = getattr(self,
                                                   "create_%s" % method_name)
        self.updaters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.updaters[resource_type] = getattr(self,
                                                   "update_%s" % method_name)
        self.deleters = {}
        for resource_type in RESOURCE_RE:
            method_name = RENAMED_RESOURCES.get(resource_type, resource_type)
            self.deleters[resource_type] = getattr(self,
                                                   "delete_%s" % method_name)
        self.listers = {}
        for resource_type in RESOURCE_RE:
            method_name = IRREGULAR_PLURALS.get( \
                resource_type, "%ss" % RENAMED_RESOURCES.get( \
                resource_type, resource_type))
            self.listers[resource_type] = getattr(self,
                                                  "list_%s" % method_name)