Metadata

pydantic model openff.qcsubmit.common_structures.Metadata[source]

A general metadata class which is required to be filled in before submitting a dataset to the qcarchive.

Show JSON schema
{
   "title": "Metadata",
   "description": "A general metadata class which is required to be filled in before submitting a dataset to the qcarchive.",
   "type": "object",
   "properties": {
      "submitter": {
         "title": "Submitter",
         "description": "The name of the submitter/creator of the dataset, this is automatically generated but can be changed.",
         "default": "docs",
         "type": "string"
      },
      "creation_date": {
         "title": "Creation Date",
         "description": "The date the dataset was created on, this is automatically generated.",
         "default": "2021-11-25",
         "type": "string",
         "format": "date"
      },
      "collection_type": {
         "title": "Collection Type",
         "description": "The type of collection that will be created in QCArchive this is automatically updated when attached to a dataset.",
         "type": "string"
      },
      "dataset_name": {
         "title": "Dataset Name",
         "description": "The name that will be given to the collection once it is put into QCArchive, this is updated when attached to a dataset.",
         "type": "string"
      },
      "short_description": {
         "title": "Short Description",
         "description": "A short informative description of the dataset.",
         "minLength": 8,
         "pattern": "[a-zA-Z]",
         "type": "string"
      },
      "long_description_url": {
         "title": "Long Description Url",
         "description": "The url which links to more information about the submission normally a github repo with scripts showing how the dataset was created.",
         "minLength": 1,
         "maxLength": 2083,
         "format": "uri",
         "type": "string"
      },
      "long_description": {
         "title": "Long Description",
         "description": "A long description of the purpose of the dataset and the molecules within.",
         "minLength": 8,
         "pattern": "[a-zA-Z]",
         "type": "string"
      },
      "elements": {
         "title": "Elements",
         "description": "The unique set of elements present in the dataset",
         "default": "set()",
         "type": "array",
         "items": {
            "type": "string"
         },
         "uniqueItems": true
      }
   }
}

Config
  • allow_mutation: bool = True

  • arbitrary_types_allowed: bool = True

  • json_encoders: dict = {<class ‘numpy.ndarray’>: <function DatasetConfig.Config.<lambda> at 0x7f536e5e08b0>, <enum ‘Enum’>: <function DatasetConfig.Config.<lambda> at 0x7f536e5e0940>}

  • validate_assignment: bool = True

Fields
field submitter: str = 'docs'

The name of the submitter/creator of the dataset, this is automatically generated but can be changed.

field creation_date: datetime.date = datetime.date(2021, 11, 25)

The date the dataset was created on, this is automatically generated.

field collection_type: Optional[str] = None

The type of collection that will be created in QCArchive this is automatically updated when attached to a dataset.

field dataset_name: Optional[str] = None

The name that will be given to the collection once it is put into QCArchive, this is updated when attached to a dataset.

field short_description: Optional[openff.qcsubmit.common_structures.ConstrainedStrValue] = None

A short informative description of the dataset.

Constraints
  • minLength = 8

  • pattern = [a-zA-Z]

field long_description_url: Optional[pydantic.networks.HttpUrl] = None

The url which links to more information about the submission normally a github repo with scripts showing how the dataset was created.

Constraints
  • minLength = 1

  • maxLength = 2083

  • format = uri

field long_description: Optional[openff.qcsubmit.common_structures.ConstrainedStrValue] = None

A long description of the purpose of the dataset and the molecules within.

Constraints
  • minLength = 8

  • pattern = [a-zA-Z]

field elements: Set[str] = {}

The unique set of elements present in the dataset

validate_metadata(raise_errors=False)[source]

Before submitting this function should be called to highlight any incomplete fields.

Parameters

raise_errors (bool) –

Return type

Optional[List[str]]