abacusai.upload =============== .. py:module:: abacusai.upload Classes ------- .. autoapisummary:: abacusai.upload.Upload Module Contents --------------- .. py:class:: Upload(client, uploadId=None, datasetUploadId=None, status=None, datasetId=None, datasetVersion=None, modelId=None, modelVersion=None, batchPredictionId=None, parts=None, createdAt=None) Bases: :py:obj:`abacusai.return_class.AbstractApiClass` A Upload Reference for uploading file parts :param client: An authenticated API Client instance :type client: ApiClient :param uploadId: The unique ID generated when the upload process of the full large file in smaller parts is initiated. :type uploadId: str :param datasetUploadId: Same as upload_id. It is kept for backwards compatibility purposes. :type datasetUploadId: str :param status: The current status of the upload. :type status: str :param datasetId: A reference to the dataset this upload is adding data to. :type datasetId: str :param datasetVersion: A reference to the dataset version the upload is adding data to. :type datasetVersion: str :param modelId: A reference the model the upload is creating a version for :type modelId: str :param modelVersion: A reference to the model version the upload is creating. :type modelVersion: str :param batchPredictionId: A reference to the batch prediction the upload is creating. :type batchPredictionId: str :param parts: A list containing the order of the file parts that have been uploaded. :type parts: list[dict] :param createdAt: The timestamp at which the upload was created. :type createdAt: str .. py:attribute:: upload_id :value: None .. py:attribute:: dataset_upload_id :value: None .. py:attribute:: status :value: None .. py:attribute:: dataset_id :value: None .. py:attribute:: dataset_version :value: None .. py:attribute:: model_id :value: None .. py:attribute:: model_version :value: None .. py:attribute:: batch_prediction_id :value: None .. py:attribute:: parts :value: None .. py:attribute:: created_at :value: None .. py:attribute:: deprecated_keys .. py:method:: __repr__() .. py:method:: to_dict() Get a dict representation of the parameters in this class :returns: The dict value representation of the class parameters :rtype: dict .. py:method:: cancel() Cancels an upload. :param upload_id: A unique string identifier for the upload. :type upload_id: str .. py:method:: part(part_number, part_data) Uploads part of a large dataset file from your bucket to our system. Our system currently supports parts of up to 5GB and full files of up to 5TB. Note that each part must be at least 5MB in size, unless it is the last part in the sequence of parts for the full file. :param part_number: The 1-indexed number denoting the position of the file part in the sequence of parts for the full file. :type part_number: int :param part_data: The multipart/form-data for the current part of the full file. :type part_data: io.TextIOBase :returns: The object 'UploadPart' which encapsulates the hash and the etag for the part that got uploaded. :rtype: UploadPart .. py:method:: mark_complete() Marks an upload process as complete. :param upload_id: A unique string identifier for the upload process. :type upload_id: str :returns: The upload object associated with the process, containing details of the file. :rtype: Upload .. py:method:: refresh() Calls describe and refreshes the current object's fields :returns: The current object :rtype: Upload .. py:method:: describe() Retrieves the current upload status (complete or inspecting) and the list of file parts uploaded for a specified dataset upload. :param upload_id: The unique ID associated with the file uploaded or being uploaded in parts. :type upload_id: str :returns: Details associated with the large dataset file uploaded in parts. :rtype: Upload .. py:method:: upload_part(upload_args) Uploads a file part. :returns: The object 'UploadPart' that encapsulates the hash and the etag for the part that got uploaded. :rtype: UploadPart .. py:method:: upload_file(file, threads=10, chunksize=1024 * 1024 * 10, wait_timeout=600) Uploads the file in the specified chunk size using the specified number of workers. :param file: A bytesIO or StringIO object to upload to Abacus.AI :type file: IOBase :param threads: The max number of workers to use while uploading the file :type threads: int :param chunksize: The number of bytes to use for each chunk while uploading the file. Defaults to 10 MB :type chunksize: int :param wait_timeout: The max number of seconds to wait for the file parts to be joined on Abacus.AI. Defaults to 600. :type wait_timeout: int :returns: The upload file object. :rtype: Upload .. py:method:: _yield_upload_part(file, chunksize) .. py:method:: wait_for_join(timeout=600) A waiting call until the upload parts are joined. :param timeout: The waiting time given to the call to finish, if it doesn't finish by the allocated time, the call is said to have timed out. Defaults to 600. :type timeout: int .. py:method:: get_status() Gets the status of the upload. :returns: A string describing the status of the upload (pending, complete, etc.). :rtype: str