Data Models

fathomnet-py uses dataclasses as native Python descriptions of the FathomNet data models.

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class fathomnet.models.ABoundingBoxDTO(id: int | NoneType = None, uuid: str | NoneType = None, userDefinedKey: str | NoneType = None, concept: str | NoneType = None, altConcept: str | NoneType = None, image: fathomnet.models.AImageDTO | NoneType = None, groupOf: bool | NoneType = None, height: int | NoneType = None, occluded: bool | NoneType = None, observer: str | NoneType = None, truncated: bool | NoneType = None, width: int | NoneType = None, x: int | NoneType = None, y: int | NoneType = None, rejected: bool | NoneType = None, verified: bool | NoneType = None, verifier: str | NoneType = None, verificationTimestamp: str | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None)

altConcept: str | None = None

concept: str | None = None

createdTimestamp: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

groupOf: bool | None = None

height: int | None = None

id: int | None = None

image: AImageDTO | None = None

lastUpdatedTimestamp: str | None = None

observer: str | None = None

occluded: bool | None = None

rejected: bool | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

truncated: bool | None = None

userDefinedKey: str | None = None

uuid: str | None = None

verificationTimestamp: str | None = None

verified: bool | None = None

verifier: str | None = None

width: int | None = None

x: int | None = None

y: int | None = None

class fathomnet.models.AImageDTO(id: int | NoneType = None, uuid: str | NoneType = None, url: str | NoneType = None, valid: bool | NoneType = None, imagingType: str | NoneType = None, depthMeters: float | NoneType = None, height: int | NoneType = None, lastValidation: str | NoneType = None, latitude: float | NoneType = None, longitude: float | NoneType = None, altitude: float | NoneType = None, salinity: float | NoneType = None, temperatureCelsius: float | NoneType = None, oxygenMlL: float | NoneType = None, pressureDbar: float | NoneType = None, mediaType: str | NoneType = None, modified: str | NoneType = None, sha256: str | NoneType = None, contributorsEmail: str | NoneType = None, tags: Union[List[ForwardRef('ATagDTO')], NoneType] = None, timestamp: str | NoneType = None, width: int | NoneType = None, boundingBoxes: Union[List[ForwardRef('ABoundingBoxDTO')], NoneType] = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None)

altitude: float | None = None

boundingBoxes: List[ABoundingBoxDTO] | None = None

contributorsEmail: str | None = None

createdTimestamp: str | None = None

depthMeters: float | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

height: int | None = None

id: int | None = None

imagingType: str | None = None

lastUpdatedTimestamp: str | None = None

lastValidation: str | None = None

latitude: float | None = None

longitude: float | None = None

mediaType: str | None = None

modified: str | None = None

oxygenMlL: float | None = None

pressureDbar: float | None = None

salinity: float | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

sha256: str | None = None

tags: List[ATagDTO] | None = None

temperatureCelsius: float | None = None

timestamp: str | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

to_pascal_voc(path: str | None = None, pretty_print: bool = False) → str

Convert to a Pascal VOC.

Parameters:

• path (Optional[str], optional) – Path to the image file, defaults to using the image URL if available

• pretty_print (bool, optional) – Set true to add indentation and newlines in XML, defaults to False

Raises:

ValueError – Raised if both the path and image URL are unspecified

Returns:

Pascal VOC encoded string

Return type:

str

url: str | None = None

uuid: str | None = None

valid: bool | None = None

width: int | None = None

class fathomnet.models.ATagDTO(id: int | NoneType = None, uuid: str | NoneType = None, key: str | NoneType = None, mediaType: str | NoneType = None, value: str | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None, image: fathomnet.models.AImageDTO | NoneType = None)

createdTimestamp: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

id: int | None = None

image: AImageDTO | None = None

key: str | None = None

lastUpdatedTimestamp: str | None = None

mediaType: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

value: str | None = None

class fathomnet.models.ApiKey(uuid: str | NoneType = None, apiKey: str | NoneType = None)

apiKey: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

class fathomnet.models.AuthHeader(type: str | NoneType = None, token: str | NoneType = None)

property auth_dict

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

token: str | None = None

type: str | None = None

class fathomnet.models.Authentication(attributes: object | NoneType = None)

attributes: object | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.BDarwinCore(uuid: str | NoneType = None, recordType: str | NoneType = None, basisOfRecord: str | NoneType = None, datasetID: str | NoneType = None, recordLanguage: str | NoneType = None, license: str | NoneType = None, modified: str | NoneType = None, ownerInstitutionCode: str | NoneType = None, accessRights: str | NoneType = None, bibliographicCitation: str | NoneType = None, collectionCode: str | NoneType = None, collectionID: str | NoneType = None, dataGeneralizations: str | NoneType = None, datasetName: str | NoneType = None, dynamicProperties: str | NoneType = None, informationWithheld: str | NoneType = None, institutionCode: str | NoneType = None, institutionID: str | NoneType = None, recordReferences: str | NoneType = None, rightsHolder: str | NoneType = None)

accessRights: str | None = None

basisOfRecord: str | None = None

bibliographicCitation: str | None = None

collectionCode: str | None = None

collectionID: str | None = None

dataGeneralizations: str | None = None

datasetID: str | None = None

datasetName: str | None = None

dynamicProperties: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

informationWithheld: str | None = None

institutionCode: str | None = None

institutionID: str | None = None

license: str | None = None

modified: str | None = None

ownerInstitutionCode: str | None = None

recordLanguage: str | None = None

recordReferences: str | None = None

recordType: str | None = None

rightsHolder: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

class fathomnet.models.BImageSetUploadDTO(uuid: str | NoneType = None, localPath: str | NoneType = None, remoteUri: str | NoneType = None, sha256: str | NoneType = None, format: Union[ForwardRef('ImageSetUpload.UploadFormat'), NoneType] = None, contributorsEmail: str | NoneType = None, status: Union[ForwardRef('ImageSetUpload.Status'), NoneType] = None, statusUpdaterEmail: str | NoneType = None, statusUpdateTimestamp: str | NoneType = None, rejectionReason: str | NoneType = None, rejectionDetails: str | NoneType = None, darwinCore: fathomnet.models.BDarwinCore | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None)

contributorsEmail: str | None = None

createdTimestamp: str | None = None

darwinCore: BDarwinCore | None = None

format: UploadFormat | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

lastUpdatedTimestamp: str | None = None

localPath: str | None = None

rejectionDetails: str | None = None

rejectionReason: str | None = None

remoteUri: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

sha256: str | None = None

status: Status | None = None

statusUpdateTimestamp: str | None = None

statusUpdaterEmail: str | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

class fathomnet.models.BoundingBox(uuid: str | NoneType = None, id: int | NoneType = None, userDefinedKey: str | NoneType = None, concept: str | NoneType = None, altConcept: str | NoneType = None, image: Union[ForwardRef('Image'), NoneType] = None, groupOf: bool | NoneType = None, height: int | NoneType = None, occluded: bool | NoneType = None, observer: str | NoneType = None, truncated: bool | NoneType = None, width: int | NoneType = None, x: int | NoneType = None, y: int | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None, verified: bool | NoneType = None, verifier: str | NoneType = None, verificationTimestamp: str | NoneType = None)

altConcept: str | None = None

concept: str | None = None

createdTimestamp: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

groupOf: bool | None = None

height: int | None = None

id: int | None = None

image: Image | None = None

lastUpdatedTimestamp: str | None = None

observer: str | None = None

occluded: bool | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

truncated: bool | None = None

userDefinedKey: str | None = None

uuid: str | None = None

verificationTimestamp: str | None = None

verified: bool | None = None

verifier: str | None = None

width: int | None = None

x: int | None = None

y: int | None = None

class fathomnet.models.BoundingBoxDTO(id: int | NoneType = None, uuid: str | NoneType = None, userDefinedKey: str | NoneType = None, concept: str | NoneType = None, altConcept: str | NoneType = None, image: fathomnet.models.AImageDTO | NoneType = None, groupOf: bool | NoneType = None, height: int | NoneType = None, occluded: bool | NoneType = None, observer: str | NoneType = None, truncated: bool | NoneType = None, width: int | NoneType = None, x: int | NoneType = None, y: int | NoneType = None, rejected: bool | NoneType = None, verified: bool | NoneType = None, verifier: str | NoneType = None, verificationTimestamp: str | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None, imageUuid: str | NoneType = None)

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

imageUuid: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.ByConceptCount(concept: str | NoneType = None, count: int | NoneType = None)

concept: str | None = None

count: int | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.ByContributorCount(contributorsEmail: str | NoneType = None, count: int | NoneType = None)

contributorsEmail: str | None = None

count: int | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.Count(objectType: str | NoneType = None, count: int | NoneType = None)

count: int | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

objectType: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.DarwinCore(id: int | NoneType = None, uuid: str | NoneType = None, recordType: str | NoneType = None, basisOfRecord: str | NoneType = None, datasetID: str | NoneType = None, recordLanguage: str | NoneType = None, license: str | NoneType = None, modified: str | NoneType = None, ownerInstitutionCode: str | NoneType = None, accessRights: str | NoneType = None, bibliographicCitation: str | NoneType = None, collectionCode: str | NoneType = None, collectionID: str | NoneType = None, dataGeneralizations: str | NoneType = None, datasetName: str | NoneType = None, dynamicProperties: str | NoneType = None, informationWithheld: str | NoneType = None, institutionCode: str | NoneType = None, institutionID: str | NoneType = None, recordReferences: str | NoneType = None, rightsHolder: str | NoneType = None, imageSetUpload: Union[ForwardRef('ImageSetUpload'), NoneType] = None)

accessRights: str | None = None

basisOfRecord: str | None = None

bibliographicCitation: str | None = None

collectionCode: str | None = None

collectionID: str | None = None

dataGeneralizations: str | None = None

datasetID: str | None = None

datasetName: str | None = None

dynamicProperties: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

id: int | None = None

imageSetUpload: ImageSetUpload | None = None

informationWithheld: str | None = None

institutionCode: str | None = None

institutionID: str | None = None

license: str | None = None

modified: str | None = None

ownerInstitutionCode: str | None = None

recordLanguage: str | None = None

recordReferences: str | None = None

recordType: str | None = None

rightsHolder: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

class fathomnet.models.FathomnetIdAdminMutation(disabled: bool | NoneType = None, expertiseRank: str | NoneType = None, roleData: str | NoneType = None, organization: str | NoneType = None)

disabled: bool | None = None

expertiseRank: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

organization: str | None = None

roleData: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.FathomnetIdMutation(jobTitle: str | NoneType = None, organization: str | NoneType = None, profile: str | NoneType = None, displayName: str | NoneType = None)

displayName: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

jobTitle: str | None = None

organization: str | None = None

profile: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.FathomnetIdentity(id: int | NoneType = None, uuid: str | NoneType = None, email: str | NoneType = None, firebaseUid: str | NoneType = None, roleData: str | NoneType = None, organization: str | NoneType = None, jobTitle: str | NoneType = None, profile: str | NoneType = None, apiKey: str | NoneType = None, avatarUrl: str | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None, disabled: bool | NoneType = None, expertiseRank: str | NoneType = None, displayName: str | NoneType = None, roles: Union[List[ForwardRef('Roles')], NoneType] = None)

apiKey: str | None = None

avatarUrl: str | None = None

createdTimestamp: str | None = None

disabled: bool | None = None

displayName: str | None = None

email: str | None = None

expertiseRank: str | None = None

firebaseUid: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

id: int | None = None

jobTitle: str | None = None

lastUpdatedTimestamp: str | None = None

organization: str | None = None

profile: str | None = None

roleData: str | None = None

roles: List[Roles] | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

class fathomnet.models.GeoImage(uuid: str | NoneType = None, url: str | NoneType = None, latitude: float | NoneType = None, longitude: float | NoneType = None, depthMeters: float | NoneType = None, contributorsEmail: str | NoneType = None, timestamp: str | NoneType = None, valid: bool | NoneType = None, lastValidation: str | NoneType = None)

contributorsEmail: str | None = None

depthMeters: float | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

lastValidation: str | None = None

latitude: float | None = None

longitude: float | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

timestamp: str | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

url: str | None = None

uuid: str | None = None

valid: bool | None = None

class fathomnet.models.GeoImageConstraints(concept: str | NoneType = None, taxaProviderName: str | NoneType = None, contributorsEmail: str | NoneType = None, startTimestamp: str | NoneType = None, endTimestamp: str | NoneType = None, imagingTypes: List[str] | NoneType = None, includeUnverified: bool | NoneType = None, includeVerified: bool | NoneType = None, minLongitude: float | NoneType = None, maxLongitude: float | NoneType = None, minLatitude: float | NoneType = None, maxLatitude: float | NoneType = None, minDepth: float | NoneType = None, maxDepth: float | NoneType = None, ownerInstitutionCodes: List[str] | NoneType = None, limit: int | NoneType = None, offset: int | NoneType = None)

concept: str | None = None

contributorsEmail: str | None = None

endTimestamp: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

imagingTypes: List[str] | None = None

includeUnverified: bool | None = None

includeVerified: bool | None = None

limit: int | None = None

maxDepth: float | None = None

maxLatitude: float | None = None

maxLongitude: float | None = None

minDepth: float | None = None

minLatitude: float | None = None

minLongitude: float | None = None

offset: int | None = None

ownerInstitutionCodes: List[str] | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

startTimestamp: str | None = None

taxaProviderName: str | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.GeoImageConstraintsCount(constraints: fathomnet.models.GeoImageConstraints | NoneType = None, count: int | NoneType = None)

constraints: GeoImageConstraints | None = None

count: int | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.Image(id: int | NoneType = None, uuid: str | NoneType = None, url: str | NoneType = None, valid: bool | NoneType = None, imagingType: str | NoneType = None, depthMeters: float | NoneType = None, height: int | NoneType = None, lastValidation: str | NoneType = None, latitude: float | NoneType = None, longitude: float | NoneType = None, altitude: float | NoneType = None, salinity: float | NoneType = None, temperatureCelsius: float | NoneType = None, oxygenMlL: float | NoneType = None, pressureDbar: float | NoneType = None, mediaType: str | NoneType = None, modified: str | NoneType = None, sha256: str | NoneType = None, contributorsEmail: str | NoneType = None, timestamp: str | NoneType = None, width: int | NoneType = None, tags: Union[List[ForwardRef('Tag')], NoneType] = None, boundingBoxes: List[fathomnet.models.BoundingBox] | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None, imageSetUploads: Union[List[ForwardRef('ImageSetUpload')], NoneType] = None)

altitude: float | None = None

boundingBoxes: List[BoundingBox] | None = None

contributorsEmail: str | None = None

createdTimestamp: str | None = None

depthMeters: float | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

height: int | None = None

id: int | None = None

imageSetUploads: List[ImageSetUpload] | None = None

imagingType: str | None = None

lastUpdatedTimestamp: str | None = None

lastValidation: str | None = None

latitude: float | None = None

longitude: float | None = None

mediaType: str | None = None

modified: str | None = None

oxygenMlL: float | None = None

pressureDbar: float | None = None

salinity: float | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

sha256: str | None = None

tags: List[Tag] | None = None

temperatureCelsius: float | None = None

timestamp: str | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

url: str | None = None

uuid: str | None = None

valid: bool | None = None

width: int | None = None

class fathomnet.models.ImageSetUpload(id: int | NoneType = None, uuid: str | NoneType = None, localPath: str | NoneType = None, remoteUri: str | NoneType = None, sha256: str | NoneType = None, contributorsEmail: str | NoneType = None, status: fathomnet.models.ImageSetUpload.Status | NoneType = None, rejectionReason: str | NoneType = None, rejectionDetails: str | NoneType = None, statusUpdaterEmail: str | NoneType = None, statusUpdateTimestamp: str | NoneType = None, format: fathomnet.models.ImageSetUpload.UploadFormat | NoneType = None, darwinCore: fathomnet.models.DarwinCore | NoneType = None, images: List[fathomnet.models.Image] | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None)

class Status(value)

An enumeration.

ACCEPTED = 'ACCEPTED'

PENDING = 'PENDING'

REJECTED = 'REJECTED'

class UploadFormat(value)

An enumeration.

CSV = 'CSV'

UNSUPPORTED = 'UNSUPPORTED'

contributorsEmail: str | None = None

createdTimestamp: str | None = None

darwinCore: DarwinCore | None = None

format: UploadFormat | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

id: int | None = None

images: List[Image] | None = None

lastUpdatedTimestamp: str | None = None

localPath: str | None = None

rejectionDetails: str | None = None

rejectionReason: str | None = None

remoteUri: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

sha256: str | None = None

status: Status | None = None

statusUpdateTimestamp: str | None = None

statusUpdaterEmail: str | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

class fathomnet.models.ImageSetUploadStats(imageSetUploadUuid: str | NoneType = None, imageCount: int | NoneType = None, boundingBoxCount: int | NoneType = None, verifiedBoundingBoxCount: int | NoneType = None)

boundingBoxCount: int | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

imageCount: int | None = None

imageSetUploadUuid: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

verifiedBoundingBoxCount: int | None = None

class fathomnet.models.MarineRegion(id: int | NoneType = None, MRGID: int | NoneType = None, name: str | NoneType = None, minLatitude: float | NoneType = None, maxLatitude: float | NoneType = None, minLongitude: float | NoneType = None, maxLongitude: float | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None)

MRGID: int | None = None

createdTimestamp: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

id: int | None = None

lastUpdatedTimestamp: str | None = None

maxLatitude: float | None = None

maxLongitude: float | None = None

minLatitude: float | None = None

minLongitude: float | None = None

name: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.Message(message: str | NoneType = None)

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

message: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.Pageable(number: int | NoneType = None, size: int | NoneType = None, offset: int | NoneType = None, sort: fathomnet.models.Sort | NoneType = None, sorted: bool | NoneType = None)

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

classmethod from_params(size: int | None = None, page: int | None = None, sort_keys: List[str] | None = None)

Make a Pageable instance from paging parameters.

number: int | None = None

offset: int | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

size: int | None = None

sort: Sort | None = None

sorted: bool | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

to_params() → List[tuple]

Make a list of paging parameters to be passed into a request.

class fathomnet.models.Roles(value)

An enumeration.

ADMIN = 'ADMIN'

MODERATOR = 'MODERATOR'

READ = 'READ'

UNKNOWN = 'UNKNOWN'

UPDATE = 'UPDATE'

WRITE = 'WRITE'

class fathomnet.models.Sort(sorted: bool | NoneType = None, orderBy: List[fathomnet.models.Sort.Order] | NoneType = None)

class Order(ignoreCase: bool | NoneType = None, direction: fathomnet.models.Sort.Order.Direction | NoneType = None, property: str | NoneType = None, ascending: bool | NoneType = None)

class Direction(value)

An enumeration.

ASC = 'ASC'

DESC = 'DESC'

ascending: bool | None = None

direction: Direction | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

ignoreCase: bool | None = None

property: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

orderBy: List[Order] | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

sorted: bool | None = None

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.Tag(uuid: str | NoneType = None, id: int | NoneType = None, key: str | NoneType = None, mediaType: str | NoneType = None, value: str | NoneType = None, image: fathomnet.models.Image | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None)

createdTimestamp: str | None = None

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

id: int | None = None

image: Image | None = None

key: str | None = None

lastUpdatedTimestamp: str | None = None

mediaType: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

uuid: str | None = None

value: str | None = None

class fathomnet.models.TagDTO(id: int | NoneType = None, uuid: str | NoneType = None, key: str | NoneType = None, mediaType: str | NoneType = None, value: str | NoneType = None, createdTimestamp: str | NoneType = None, lastUpdatedTimestamp: str | NoneType = None, image: fathomnet.models.AImageDTO | NoneType = None, imageUuid: str | NoneType = None)

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

imageUuid: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str

class fathomnet.models.Taxa(name: str | NoneType = None, rank: str | NoneType = None)

classmethod from_dict(kvs: dict | list | str | int | float | bool | None, *, infer_missing=False) → A

classmethod from_json(s: str | bytes | bytearray, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) → A

name: str | None = None

rank: str | None = None

classmethod schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) → SchemaF[A]

to_dict(encode_json=False) → Dict[str, dict | list | str | int | float | bool | None]

to_json(*, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: int | str | None = None, separators: Tuple[str, str] | None = None, default: Callable | None = None, sort_keys: bool = False, **kw) → str