Module transpiler_mate.ogc_record
Variables
SCIENCE_KEYWORDS_TERM_SET
Classes
OgcRecordsTranspiler
class OgcRecordsTranspiler(
)
Abstract base class for generic types.
On Python 3.12 and newer, generic classes implicitly inherit from Generic when they declare a parameter list after the class's name::
class Mapping[KT, VT]:
    def __getitem__(self, key: KT) -> VT:
        ...
    # Etc.
On older versions of Python, however, generic classes have to explicitly inherit from Generic.
After a class has been declared to be generic, it can then be used as follows::
def lookup_name[KT, VT](mapping: Mapping[KT, VT], key: KT, default: VT) -> VT:
    try:
        return mapping[key]
    except KeyError:
        return default
Ancestors (in MRO)
- transpiler_mate.metadata.Transpiler
- typing.Generic
Methods
transpile
def transpile(
    self,
    metadata_source: transpiler_mate.metadata.software_application_models.SoftwareApplication
) -> Mapping[str, Any]
ScienceKeywordRecord
class ScienceKeywordRecord(
    /,
    **data: 'Any'
)
Usage Documentation
A base class for creating Pydantic models.
Attributes
| Name | Type | Description | Default | 
|---|---|---|---|
| class_vars | None | The names of the class variables defined on the model. | None | 
| private_attributes | None | Metadata about the private attributes of the model. | None | 
| signature | None | The synthesized __init__[Signature][inspect.Signature] of the model. | None | 
| pydantic_complete | None | Whether model building is completed, or if there are still undefined fields. | None | 
| pydantic_core_schema | None | The core schema of the model. | None | 
| pydantic_custom_init | None | Whether the model has a custom __init__function. | None | 
| pydantic_decorators | None | Metadata containing the decorators defined on the model. This replaces Model.__validators__andModel.__root_validators__from Pydantic V1. | None | 
| pydantic_generic_metadata | None | Metadata for generic models; contains data used for a similar purpose to args, origin, parameters in typing-module generics. May eventually be replaced by these. | None | 
| pydantic_parent_namespace | None | Parent namespace of the model, used for automatic rebuilding of models. | None | 
| pydantic_post_init | None | The name of the post-init method for the model, if defined. | None | 
| pydantic_root_model | None | Whether the model is a [ RootModel][pydantic.root_model.RootModel]. | None | 
| pydantic_serializer | None | The pydantic-coreSchemaSerializerused to dump instances of the model. | None | 
| pydantic_validator | None | The pydantic-coreSchemaValidatorused to validate instances of the model. | None | 
| pydantic_fields | None | A dictionary of field names and their corresponding [ FieldInfo][pydantic.fields.FieldInfo] objects. | None | 
| pydantic_computed_fields | None | A dictionary of computed field names and their corresponding [ ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects. | None | 
| pydantic_extra | None | A dictionary containing extra values, if [ extra][pydantic.config.ConfigDict.extra]is set to 'allow'. | None | 
| pydantic_fields_set | None | The names of fields explicitly set during instantiation. | None | 
| pydantic_private | None | Values of private attributes set on the model instance. | None | 
Ancestors (in MRO)
- pydantic.main.BaseModel
Class variables
model_computed_fields
model_config
model_fields
Static methods
construct
def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'
from_orm
def from_orm(
    obj: 'Any'
) -> 'Self'
model_construct
def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'
Creates a new instance of the Model class with validated data.
Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Note
model_construct() generally respects the model_config.extra setting on the provided model.
That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance's __dict__
and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored.
Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in
an error if extra values are passed, but they will be ignored.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| _fields_set | None | A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [ model_fields_set][pydantic.BaseModel.model_fields_set] attribute.Otherwise, the field names from the valuesargument will be used. | None | 
| values | None | Trusted or pre-validated data dictionary. | None | 
Returns:
| Type | Description | 
|---|---|
| None | A new instance of the Modelclass with validated data. | 
model_json_schema
def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'
Generates a JSON schema for a model class.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| by_alias | None | Whether to use attribute aliases or not. | None | 
| ref_template | None | The reference template. | None | 
| union_format | None | The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use theanyOfkeyword to combine schemas (the default). - 'primitive_type_array': Use thetypekeyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type ( string,boolean,null,integerornumber) or contains constraints/metadata, falls back toany_of. | None | 
| schema_generator | None | To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchemawith your desired modifications | None | 
| mode | None | The mode in which to generate the schema. | None | 
Returns:
| Type | Description | 
|---|---|
| None | The JSON schema for the given model class. | 
model_parametrized_name
def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'
Compute the class name for parametrizations of generic classes.
This method can be overridden to achieve a custom naming scheme for generic BaseModels.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| params | None | Tuple of types of the class. Given a generic class Modelwith 2 type variables and a concrete modelModel[str, int],the value (str, int)would be passed toparams. | None | 
Returns:
| Type | Description | 
|---|---|
| None | String representing the new class where paramsare passed toclsas type variables. | 
Raises:
| Type | Description | 
|---|---|
| TypeError | Raised when trying to generate concrete names for non-generic models. | 
model_rebuild
def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | None'
Try to rebuild the pydantic-core schema for the model.
This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| force | None | Whether to force the rebuilding of the model schema, defaults to False. | None | 
| raise_errors | None | Whether to raise errors, defaults to True. | None | 
| _parent_namespace_depth | None | The depth level of the parent namespace, defaults to 2. | None | 
| _types_namespace | None | The types namespace, defaults to None. | None | 
Returns:
| Type | Description | 
|---|---|
| None | Returns Noneif the schema is already "complete" and rebuilding was not required.If rebuilding was required, returns Trueif rebuilding was successful, otherwiseFalse. | 
model_validate
def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'
Validate a pydantic model instance.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| obj | None | The object to validate. | None | 
| strict | None | Whether to enforce types strictly. | None | 
| extra | None | Whether to ignore, allow, or forbid extra data during model validation. See the [ extraconfiguration value][pydantic.ConfigDict.extra] for details. | None | 
| from_attributes | None | Whether to extract data from object attributes. | None | 
| context | None | Additional context to pass to the validator. | None | 
| by_alias | None | Whether to use the field's alias when validating against the provided input data. | None | 
| by_name | None | Whether to use the field's name when validating against the provided input data. | None | 
Returns:
| Type | Description | 
|---|---|
| None | The validated model instance. | 
Raises:
| Type | Description | 
|---|---|
| ValidationError | If the object could not be validated. | 
model_validate_json
def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'
Usage Documentation
Validate the given JSON data against the Pydantic model.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| json_data | None | The JSON data to validate. | None | 
| strict | None | Whether to enforce types strictly. | None | 
| extra | None | Whether to ignore, allow, or forbid extra data during model validation. See the [ extraconfiguration value][pydantic.ConfigDict.extra] for details. | None | 
| context | None | Extra variables to pass to the validator. | None | 
| by_alias | None | Whether to use the field's alias when validating against the provided input data. | None | 
| by_name | None | Whether to use the field's name when validating against the provided input data. | None | 
Returns:
| Type | Description | 
|---|---|
| None | The validated Pydantic model. | 
Raises:
| Type | Description | 
|---|---|
| ValidationError | If json_datais not a JSON string or the object could not be validated. | 
model_validate_strings
def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'
Validate the given object with string data against the Pydantic model.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| obj | None | The object containing string data to validate. | None | 
| strict | None | Whether to enforce types strictly. | None | 
| extra | None | Whether to ignore, allow, or forbid extra data during model validation. See the [ extraconfiguration value][pydantic.ConfigDict.extra] for details. | None | 
| context | None | Extra variables to pass to the validator. | None | 
| by_alias | None | Whether to use the field's alias when validating against the provided input data. | None | 
| by_name | None | Whether to use the field's name when validating against the provided input data. | None | 
Returns:
| Type | Description | 
|---|---|
| None | The validated Pydantic model. | 
parse_file
def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'
parse_obj
def parse_obj(
    obj: 'Any'
) -> 'Self'
parse_raw
def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'
schema
def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'
schema_json
def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'
update_forward_refs
def update_forward_refs(
    **localns: 'Any'
) -> 'None'
validate
def validate(
    value: 'Any'
) -> 'Self'
Instance variables
hierarchy_list
model_extra
Get extra fields set during validation.
model_fields_set
Returns the set of fields that have been explicitly set on this model instance.
scheme
uri
Methods
copy
def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'
Returns a copy of the model.
Deprecated
This method is now deprecated; use model_copy instead.
If you need include or exclude, use:
data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| include | None | Optional set or mapping specifying which fields to include in the copied model. | None | 
| exclude | None | Optional set or mapping specifying which fields to exclude in the copied model. | None | 
| update | None | Optional dictionary of field-value pairs to override field values in the copied model. | None | 
| deep | None | If True, the values of fields that are Pydantic models will be deep-copied. | None | 
Returns:
| Type | Description | 
|---|---|
| None | A copy of the model with included, excluded and updated fields as specified. | 
dict
def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'
json
def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'
model_copy
def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'
Usage Documentation
Returns a copy of the model.
Note
The underlying instance's [__dict__][object.dict] attribute is copied. This
might have unexpected side effects if you store anything in it, on top of the model
fields (e.g. the value of [cached properties][functools.cached_property]).
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| update | None | Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data. | None | 
| deep | None | Set to Trueto make a deep copy of the model. | None | 
Returns:
| Type | Description | 
|---|---|
| None | New model instance. | 
model_dump
def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'
Usage Documentation
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| mode | None | The mode in which to_pythonshould run.If mode is 'json', the output will only contain JSON serializable types. If mode is 'python', the output may contain non-JSON-serializable Python objects. | None | 
| include | None | A set of fields to include in the output. | None | 
| exclude | None | A set of fields to exclude from the output. | None | 
| context | None | Additional context to pass to the serializer. | None | 
| by_alias | None | Whether to use the field's alias in the dictionary key if defined. | None | 
| exclude_unset | None | Whether to exclude fields that have not been explicitly set. | None | 
| exclude_defaults | None | Whether to exclude fields that are set to their default value. | None | 
| exclude_none | None | Whether to exclude fields that have a value of None. | None | 
| exclude_computed_fields | None | Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_tripparameter instead. | None | 
| round_trip | None | If True, dumped values should be valid as input for non-idempotent types such as Json[T]. | None | 
| warnings | None | How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [ PydanticSerializationError][pydantic_core.PydanticSerializationError]. | None | 
| fallback | None | A function to call when an unknown value is encountered. If not provided, a [ PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised. | None | 
| serialize_as_any | None | Whether to serialize fields with duck-typing serialization behavior. | None | 
Returns:
| Type | Description | 
|---|---|
| None | A dictionary representation of the model. | 
model_dump_json
def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'
Usage Documentation
Generates a JSON representation of the model using Pydantic's to_json method.
Parameters:
| Name | Type | Description | Default | 
|---|---|---|---|
| indent | None | Indentation to use in the JSON output. If None is passed, the output will be compact. | None | 
| ensure_ascii | None | If True, the output is guaranteed to have all incoming non-ASCII characters escaped.If False(the default), these characters will be output as-is. | None | 
| include | None | Field(s) to include in the JSON output. | None | 
| exclude | None | Field(s) to exclude from the JSON output. | None | 
| context | None | Additional context to pass to the serializer. | None | 
| by_alias | None | Whether to serialize using field aliases. | None | 
| exclude_unset | None | Whether to exclude fields that have not been explicitly set. | None | 
| exclude_defaults | None | Whether to exclude fields that are set to their default value. | None | 
| exclude_none | None | Whether to exclude fields that have a value of None. | None | 
| exclude_computed_fields | None | Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_tripparameter instead. | None | 
| round_trip | None | If True, dumped values should be valid as input for non-idempotent types such as Json[T]. | None | 
| warnings | None | How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [ PydanticSerializationError][pydantic_core.PydanticSerializationError]. | None | 
| fallback | None | A function to call when an unknown value is encountered. If not provided, a [ PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised. | None | 
| serialize_as_any | None | Whether to serialize fields with duck-typing serialization behavior. | None | 
Returns:
| Type | Description | 
|---|---|
| None | A JSON string representation of the model. | 
model_post_init
def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'
Override this method to perform additional initialization after __init__ and model_construct.
This is useful if you want to do some validation that requires the entire model to be initialized.