A file containing a trained model.
| Name | Type | Description | Notes |
|---|---|---|---|
| controlled_access | bool | Boolean value, indicating the file being controlled access, if true. | [optional] |
| anvil_url | str | URL linking to the controlled access file that has been deposited at AnVIL workspace. | [optional] |
| release_timestamp | str | The date the object was released. | [optional] |
| documents | List[str] | Documents that provide additional information (not data file). | [optional] |
| lab | str | Lab associated with the submission. | [optional] |
| award | str | Grant associated with the submission. | [optional] |
| accession | str | A unique identifier to be used to reference the object prefixed with PKB. | [optional] |
| alternate_accessions | List[str] | Accessions previously assigned to objects that have been merged with this object. | [optional] |
| collections | List[str] | Some samples are part of particular data collections. | [optional] |
| status | str | The status of the metadata object. | [optional] |
| revoke_detail | str | Explanation of why an object was transitioned to the revoked status. | [optional] |
| schema_version | str | The version of the JSON schema that the server uses to validate the object. | [optional] |
| uuid | str | The unique identifier associated with every object. | [optional] |
| notes | str | DACC internal notes. | [optional] |
| aliases | List[str] | Lab specific identifiers to reference an object. | [optional] |
| creation_timestamp | str | The date the object was created. | [optional] |
| submitted_by | str | The user who submitted the object. | [optional] |
| submitter_comment | str | Additional information specified by the submitter to be displayed as a comment on the portal. | [optional] |
| description | str | A plain text description of the object. | [optional] |
| analysis_step_version | str | The analysis step version of the file. | [optional] |
| content_md5sum | str | The MD5sum of the uncompressed file. | [optional] |
| content_type | str | The type of content in the file. | [optional] |
| dbxrefs | List[str] | Identifiers from external resources that may have 1-to-1 or 1-to-many relationships with IGVF file objects. | [optional] |
| derived_from | List[str] | The files participating as inputs into software to produce this output file. | [optional] |
| file_format | str | The file format or extension of the file. | [optional] |
| file_format_specifications | List[str] | Document that further explains the file format. | [optional] |
| file_set | str | The file set that this file belongs to. | [optional] |
| file_size | int | File size specified in bytes. | [optional] |
| md5sum | str | The md5sum of the file being transferred. | [optional] |
| submitted_file_name | str | Original name of the file. | [optional] |
| upload_status | str | The upload/validation status of the file. | [optional] |
| validation_error_detail | str | Explanation of why the file failed the automated content checks. | [optional] |
| id | str | [optional] | |
| type | List[str] | [optional] | |
| summary | str | A summary of the model file. | [optional] |
| integrated_in | List[str] | Construct library set(s) that this file was used for in insert design. | [optional] |
| input_file_for | List[str] | The files which are derived from this file. | [optional] |
| gene_list_for | List[str] | File Set(s) that this file is a gene list for. | [optional] |
| loci_list_for | List[str] | File Set(s) that this file is a loci list for. | [optional] |
| href | str | The download path to obtain file. | [optional] |
| s3_uri | str | The S3 URI of public file object. | [optional] |
| upload_credentials | object | The upload credentials for S3 to submit the file content. | [optional] |
from igvf_client.models.model_file import ModelFile
# TODO update the JSON string below
json = "{}"
# create an instance of ModelFile from a JSON string
model_file_instance = ModelFile.from_json(json)
# print the JSON string representation of the object
print(ModelFile.to_json())
# convert the object into a dict
model_file_dict = model_file_instance.to_dict()
# create an instance of ModelFile from a dict
model_file_from_dict = ModelFile.from_dict(model_file_dict)