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Module stac_fastapi.types.search

stac_fastapi.types.search module.

Variables

Limit
NumType

Functions

crop

def crop(
    v: typing.Annotated[int, Gt(gt=0)]
) -> typing.Annotated[int, Gt(gt=0)]

Crop value to 10,000.

str2bbox

def str2bbox(
    x: str
) -> Union[Tuple[Union[float, int], Union[float, int], Union[float, int], Union[float, int]], Tuple[Union[float, int], Union[float, int], Union[float, int], Union[float, int], Union[float, int], Union[float, int]], NoneType]

Convert string to BBox based on , delimiter.

str2list

def str2list(
    x: str
) -> Optional[List[str]]

Convert string to list base on , delimiter.

Classes

APIRequest

class APIRequest(

)

Generic API Request base class.

Descendants

  • stac_fastapi.types.search.BaseSearchGetRequest
  • stac_fastapi.api.models.CollectionUri
  • stac_fastapi.api.models.ItemUri
  • stac_fastapi.api.models.EmptyRequest
  • stac_fastapi.api.models.ItemCollectionUri
  • stac_fastapi.extensions.core.collection_search.request.BaseCollectionSearchGetRequest
  • stac_fastapi.extensions.core.fields.request.FieldsExtensionGetRequest
  • stac_fastapi.extensions.core.filter.request.FilterExtensionGetRequest
  • stac_fastapi.extensions.core.free_text.request.FreeTextExtensionGetRequest
  • stac_fastapi.extensions.core.free_text.request.FreeTextAdvancedExtensionGetRequest
  • stac_fastapi.extensions.core.pagination.request.GETTokenPagination
  • stac_fastapi.extensions.core.pagination.request.GETPagination
  • stac_fastapi.extensions.core.pagination.request.GETOffsetPagination
  • stac_fastapi.extensions.core.query.request.QueryExtensionGetRequest
  • stac_fastapi.extensions.core.sort.request.SortExtensionGetRequest

Methods

kwargs

def kwargs(
    self
) -> Dict

Transform api request params into format which matches the signature of the

endpoint.

BaseSearchGetRequest

class BaseSearchGetRequest(
    collections: Annotated[Optional[str], Query(PydanticUndefined)] = None,
    ids: Annotated[Optional[str], Query(PydanticUndefined)] = None,
    bbox: Annotated[Optional[str], Query(PydanticUndefined)] = None,
    intersects: Annotated[Optional[str], Query(PydanticUndefined)] = None,
    datetime: Annotated[Optional[str], Query(PydanticUndefined)] = None,
    limit: Annotated[Optional[Annotated[int, Gt(gt=0), AfterValidator(func=<function crop at 0x7ff2c816eac0>)]], Query(PydanticUndefined)] = 10
)

Base arguments for GET Request.

Ancestors (in MRO)

  • stac_fastapi.types.search.APIRequest

Descendants

  • stac_fastapi.extensions.core.aggregation.request.AggregationExtensionGetRequest

Methods

kwargs

def kwargs(
    self
) -> Dict

Transform api request params into format which matches the signature of the

endpoint.

BaseSearchPostRequest

class BaseSearchPostRequest(
    /,
    **data: 'Any'
)

Base arguments for POST Request.

Ancestors (in MRO)

  • stac_pydantic.api.search.Search
  • pydantic.main.BaseModel

Descendants

  • stac_fastapi.extensions.core.aggregation.request.AggregationExtensionPostRequest

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 values argument will be used.
None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class 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'
) -> '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
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with 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
Model with 2 type variables and a concrete model Model[str, int],
the value (str, int) would be passed to params.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as 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: 'dict[str, Any] | 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 None if the schema is already "complete" and rebuilding was not required.
If rebuilding was required, returns True if rebuilding was successful, otherwise False.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | 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
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. 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,
    context: 'Any | None' = None
) -> 'Self'

Usage docs: docs.pydantic.dev/2.9/concepts/json/#json-parsing

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
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValidationError If json_data is not a JSON string or the object could not be validated.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'Any | 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
context None Extra variables to pass to the validator. 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'

validate_bbox

def validate_bbox(
    v: Union[Tuple[Union[float, int], Union[float, int], Union[float, int], Union[float, int]], Tuple[Union[float, int], Union[float, int], Union[float, int], Union[float, int], Union[float, int], Union[float, int]]]
) -> Union[Tuple[Union[float, int], Union[float, int], Union[float, int], Union[float, int]], Tuple[Union[float, int], Union[float, int], Union[float, int], Union[float, int], Union[float, int], Union[float, int]]]

validate_datetime

def validate_datetime(
    value: str
) -> str

validate_spatial

def validate_spatial(
    values: Dict[str, Any]
) -> Dict[str, Any]

Instance variables

end_date
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.

spatial_filter

Return a geojson-pydantic object representing the spatial filter for the search request.

Check for both because the bbox and intersects parameters are mutually exclusive.

start_date

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: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage docs: docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

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 True to 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' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

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_python should 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
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
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,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

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
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
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
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: 'BaseModel',
    context: 'Any',
    /
) -> 'None'

We need to both initialize private attributes and call the user-defined model_post_init

method.