snowflake.core.table.Table¶

class snowflake.core.table.Table(*, name: Annotated[str, Strict(strict=True)], kind: Annotated[str, Strict(strict=True)] | None = 'PERMANENT', cluster_by: List[Annotated[str, Strict(strict=True)]] | None = None, enable_schema_evolution: Annotated[bool, Strict(strict=True)] | None = None, change_tracking: Annotated[bool, Strict(strict=True)] | None = None, data_retention_time_in_days: Annotated[int, Strict(strict=True)] | None = None, max_data_extension_time_in_days: Annotated[int, Strict(strict=True)] | None = None, default_ddl_collation: Annotated[str, Strict(strict=True)] | None = None, columns: List[TableColumn] | None = None, constraints: List[Constraint] | None = None, comment: Annotated[str, Strict(strict=True)] | None = None, created_on: datetime | None = None, database_name: Annotated[str, Strict(strict=True)] | None = None, schema_name: Annotated[str, Strict(strict=True)] | None = None, rows: Annotated[int, Strict(strict=True)] | None = None, bytes: Annotated[int, Strict(strict=True)] | None = None, owner: Annotated[str, Strict(strict=True)] | None = None, dropped_on: datetime | None = None, automatic_clustering: Annotated[bool, Strict(strict=True)] | None = None, search_optimization: Annotated[bool, Strict(strict=True)] | None = None, search_optimization_progress: Annotated[int, Strict(strict=True)] | None = None, search_optimization_bytes: Annotated[int, Strict(strict=True)] | None = None, owner_role_type: Annotated[str, Strict(strict=True)] | None = None, budget: Annotated[str, Strict(strict=True)] | None = None)¶

Bases: BaseModel

Attributes

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'validate_assignment': True}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_extra¶

Get extra fields set during validation.

Returns:: A dictionary of extra fields, or None if config.extra is not set to “allow”.

model_fields: ClassVar[dict[str, FieldInfo]] = {'automatic_clustering': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, default=None), 'budget': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None), 'bytes': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, default=None), 'change_tracking': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, default=None), 'cluster_by': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, default=None), 'columns': FieldInfo(annotation=Union[List[TableColumn], NoneType], required=False, default=None), 'comment': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None), 'constraints': FieldInfo(annotation=Union[List[Constraint], NoneType], required=False, default=None), 'created_on': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None), 'data_retention_time_in_days': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, default=None), 'database_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None), 'default_ddl_collation': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None), 'dropped_on': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None), 'enable_schema_evolution': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, default=None), 'kind': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default='PERMANENT'), 'max_data_extension_time_in_days': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, default=None), 'name': FieldInfo(annotation=str, required=True, metadata=[Strict(strict=True)]), 'owner': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None), 'owner_role_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None), 'rows': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, default=None), 'schema_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None), 'search_optimization': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, default=None), 'search_optimization_bytes': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, default=None), 'search_optimization_progress': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, default=None)}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

model_fields_set¶

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,: i.e. that were not filled from defaults.

name: StrictStr¶

kind: StrictStr | None¶

cluster_by: List[StrictStr] | None¶

enable_schema_evolution: StrictBool | None¶

change_tracking: StrictBool | None¶

data_retention_time_in_days: StrictInt | None¶

max_data_extension_time_in_days: StrictInt | None¶

default_ddl_collation: StrictStr | None¶

columns: List[TableColumn] | None¶

constraints: List[Constraint] | None¶

comment: StrictStr | None¶

created_on: datetime | None¶

database_name: StrictStr | None¶

schema_name: StrictStr | None¶

rows: StrictInt | None¶

bytes: StrictInt | None¶

owner: StrictStr | None¶

dropped_on: datetime | None¶

automatic_clustering: StrictBool | None¶

search_optimization: StrictBool | None¶

search_optimization_progress: StrictInt | None¶

search_optimization_bytes: StrictInt | None¶

owner_role_type: StrictStr | None¶

budget: StrictStr | None¶

Methods

__init__(**data: Any) → None¶

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

classmethod construct(_fields_set: set[str] | None = None, **values: Any) → Self¶

Returns a copy of the model.

!!! warning “Deprecated”: This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

include – Optional set or mapping specifying which fields to include in the copied model.
exclude – Optional set or mapping specifying which fields to exclude in the copied model.
update – Optional dictionary of field-value pairs to override field values in the copied model.
deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include: Set[int] | Set[str] | Dict[int, Any] | Dict[str, Any] | None = None, exclude: Set[int] | Set[str] | Dict[int, Any] | Dict[str, Any] | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → Dict[str, Any]¶

classmethod from_dict(obj: dict) → Table¶: Create an instance of Table from a dict

classmethod from_json(json_str: str) → Table¶: Create an instance of Table from a JSON string

classmethod from_orm(obj: Any) → Self¶

json(*, include: Set[int] | Set[str] | Dict[int, Any] | Dict[str, Any] | None = None, exclude: Set[int] | Set[str] | Dict[int, Any] | Dict[str, Any] | 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¶

classmethod kind_validate_enum(v)¶

classmethod 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:

_fields_set – The set of field names accepted for the Model instance.
values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

model_copy(*, update: dict[str, Any] | None = None, deep: bool = False) → Self¶

Usage docs: https://docs.pydantic.dev/2.8/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

update – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.
deep – Set to True to make a deep copy of the model.

Returns:

New model instance.

Usage docs: https://docs.pydantic.dev/2.8/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

mode – 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.
include – A set of fields to include in the output.
exclude – A set of fields to exclude from the output.
context – Additional context to pass to the serializer.
by_alias – Whether to use the field’s alias in the dictionary key if defined.
exclude_unset – Whether to exclude fields that have not been explicitly set.
exclude_defaults – Whether to exclude fields that are set to their default value.
exclude_none – Whether to exclude fields that have a value of None.
round_trip – If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
serialize_as_any – Whether to serialize fields with duck-typing serialization behavior.

Returns:

A dictionary representation of the model.

Usage docs: https://docs.pydantic.dev/2.8/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

indent – Indentation to use in the JSON output. If None is passed, the output will be compact.
include – Field(s) to include in the JSON output.
exclude – Field(s) to exclude from the JSON output.
context – Additional context to pass to the serializer.
by_alias – Whether to serialize using field aliases.
exclude_unset – Whether to exclude fields that have not been explicitly set.
exclude_defaults – Whether to exclude fields that are set to their default value.
exclude_none – Whether to exclude fields that have a value of None.
round_trip – If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
serialize_as_any – Whether to serialize fields with duck-typing serialization behavior.

Returns:

A JSON string representation of the model.

classmethod model_json_schema(by_alias: bool = True, ref_template: str = '#/$defs/{model}', schema_generator: type[~pydantic.json_schema.GenerateJsonSchema] = <class 'pydantic.json_schema.GenerateJsonSchema'>, mode: ~typing.Literal['validation', 'serialization'] = 'validation') → dict[str, Any]¶

Generates a JSON schema for a model class.

Parameters:

by_alias – Whether to use attribute aliases or not.
ref_template – The reference template.
schema_generator – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications
mode – The mode in which to generate the schema.

Returns:

The JSON schema for the given model class.

classmethod 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:: params – 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.
Returns:: String representing the new class where params are passed to cls as type variables.
Raises:: TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(context: Any, /) → None¶

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

self – The BaseModel instance.
context – The context.

classmethod 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:

force – Whether to force the rebuilding of the model schema, defaults to False.
raise_errors – Whether to raise errors, defaults to True.
_parent_namespace_depth – The depth level of the parent namespace, defaults to 2.
_types_namespace – The types namespace, defaults to None.

Returns:

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.

classmethod model_validate(obj: Any, *, strict: bool | None = None, from_attributes: bool | None = None, context: Any | None = None) → Self¶

Validate a pydantic model instance.

Parameters:

obj – The object to validate.
strict – Whether to enforce types strictly.
from_attributes – Whether to extract data from object attributes.
context – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Returns:

The validated model instance.

classmethod model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, context: Any | None = None) → Self¶

Usage docs: https://docs.pydantic.dev/2.8/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

json_data – The JSON data to validate.
strict – Whether to enforce types strictly.
context – Extra variables to pass to the validator.

Returns:

The validated Pydantic model.

Raises:

ValueError – If json_data is not a JSON string.

classmethod 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:

obj – The object containing string data to validate.
strict – Whether to enforce types strictly.
context – Extra variables to pass to the validator.

Returns:

The validated Pydantic model.

classmethod parse_file(path: str | Path, *, content_type: str | None = None, encoding: str = 'utf8', proto: DeprecatedParseProtocol | None = None, allow_pickle: bool = False) → Self¶

classmethod parse_obj(obj: Any) → Self¶

classmethod parse_raw(b: str | bytes, *, content_type: str | None = None, encoding: str = 'utf8', proto: DeprecatedParseProtocol | None = None, allow_pickle: bool = False) → Self¶

classmethod schema(by_alias: bool = True, ref_template: str = '#/$defs/{model}') → Dict[str, Any]¶

classmethod schema_json(*, by_alias: bool = True, ref_template: str = '#/$defs/{model}', **dumps_kwargs: Any) → str¶

to_dict()¶: Returns the dictionary representation of the model using alias

to_json() → str¶: Returns the JSON representation of the model using alias

to_str() → str¶: Returns the string representation of the model using alias

classmethod update_forward_refs(**localns: Any) → None¶

classmethod validate(value: Any) → Self¶