`tlc.core.schema`¶

Defines Schema, which is a class for describing atomic or (possibly nested) composite structures

Module Contents¶

Classes¶

Class	Description
`BoolValue`	Describes a scalar boolean value
`BytesStringValue`	Describes a binary value utf-8 encoded as a string
`DatetimeStringValue`	Describes a date-time string value
`DictValue`	Describes a value which consists of an anonymous, free-form dictionary
`DimensionNumericValue`	Describes a scalar numeric value which is a dimension size within a property
`Float32Value`	A numeric value with type ‘float32’
`Float64Value`	A numeric value with type ‘float64’
`FolderUrlStringValue`	Describes a generic URL string value
`ImageUrlStringValue`	Describes a Image URL string value
`InstanceSegmentationRLEBytesStringValue`	Describes a binary value encoded as a run-length encoding
`Int16Value`	A numeric value with type ‘int16’
`Int32Value`	A numeric value with type ‘int32’
`Int64Value`	A numeric value with type ‘int64’
`Int8Value`	A numeric value with type ‘int8’
`MapElement`	Defines a single item in a value map.
`NoneSchema`	A schema that encodes a None value
`NumericValue`	Describes a scalar numeric value
`ObjectTypeStringValue`	A string containing an object type
`ScalarValue`	Describes a scalar value in a schema
`Schema`	A schema is a recursive structure which defines the layout of an object. It defines what elements the object consists of, which must be either
`SegmentationMaskUrlStringValue`	Describes a Segmentation Mask URL string value
`SegmentationUrlStringValue`	Describes a Segmentation URL string value
`StringValue`	Describes a string value
`TensorUrlStringValue`	Describes a URL string value pointing to a tensor
`TimestampValue`	A timestamp value counting the number of ‘unit’s since epoch
`Uint16Value`	A numeric value with type ‘uint16’
`Uint32Value`	A numeric value with type ‘uint32’
`Uint64Value`	A numeric value with type ‘uint64’
`Uint8Value`	A numeric value with type ‘uint8’
`UrlStringValue`	Describes a generic URL string value

API¶

class BoolValue( default_value: bool | None = None, )¶

Bases: tlc.core.schema.ScalarValue

Describes a scalar boolean value

static from_any( any_value: Any, ) → BoolValue¶: Create and populate a BoolValue object given an anonymous, potentially sparse object

class BytesStringValue( default_value: str | None = None, )¶

Bases: tlc.core.schema.StringValue

Describes a binary value utf-8 encoded as a string

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶

class DatetimeStringValue( default_value: str | None = None, )¶

Bases: tlc.core.schema.StringValue

Describes a date-time string value

class DictValue( default_value: dict | None = None, )¶

Bases: tlc.core.schema.ScalarValue

Describes a value which consists of an anonymous, free-form dictionary

property default_value: dict¶

static from_any( _: Any, ) → DictValue¶

class DimensionNumericValue( value_min: int = 0, value_max: int | None = None, enforce_min: bool = True, enforce_max: bool = False, display_name: str = '', description: str = '', number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, sample_type: str = '', default_value: int | None = None, )¶

Bases: tlc.core.schema.Int32Value

Describes a scalar numeric value which is a dimension size within a property

static dimension_numeric_value_from_any( this_property: Any, ) → DimensionNumericValue | None¶: Creates a DimensionNumericValue object and populates it from an anonymous, possibly sparse object

classmethod fixed_size( size: int, ) → DimensionNumericValue¶: Create a fixed size dimension value

is_fixed_size() → bool¶

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶: Add a minimal representation of this object to a dictionary for subsequent serialization to JSON

class Float32Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: float | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘float32’

class Float64Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: float | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘float64’

class FolderUrlStringValue( default_value: str | None = None, )¶

Bases: tlc.core.schema.StringValue

Describes a generic URL string value

class ImageUrlStringValue( default_value: str | None = None, )¶

Bases: tlc.core.schema.UrlStringValue

Describes a Image URL string value

class InstanceSegmentationRLEBytesStringValue( polygons_are_relative: bool = False, default_value: str | None = None, )¶

Bases: tlc.core.schema.BytesStringValue

Describes a binary value encoded as a run-length encoding

static from_any( any_value: Any, ) → InstanceSegmentationRLEBytesStringValue¶

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶

class Int16Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘int16’

class Int32Value( value_min: int | None = None, value_max: int | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘int32’

class Int64Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘int64’

class Int8Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘int8’

class MapElement( internal_name: str = '', display_name: str = '', description: str = '', display_color: str = '', url: str = '', )¶

Bases: dict

Defines a single item in a value map.

Initialize self. See help(type(self)) for accurate signature.

property description: str¶

property display_color: str¶

property display_name: str¶

static from_any( any_map_element: Any, ) → MapElement¶: Creates a MapElement object and populates it from an anonymous, possibly sparse object

property internal_name: str¶

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶: Add a minimal representation of this object to a dictionary for subsequent serialization to JSON

property url: str¶

class NoneSchema¶

Bases: tlc.core.schema.Schema

A schema that encodes a None value

It is not a valid Schema as it has neither value nor values. It is used to encode override schemas that remove sub schemas.

Example:

override_schema = { "values": { "column_to_remove": None }}
# or equivalently
override_schema = { "values": { "column_to_remove": NoneSchema()}}

to_json() → str¶

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶

class NumericValue( value_type: str = _DEFAULT_SCALAR_VALUE_TYPE, value_min: float | int | None = None, value_max: float | int | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | float | None = None, )¶

Bases: tlc.core.schema.ScalarValue

Describes a scalar numeric value

static from_any( any_value: Any, ) → NumericValue¶: Create and populate a NumericValue object given an anonymous, potentially sparse object

static from_value( value: Any, ) → NumericValue¶

Create a numeric value from a Python value.

Parameters:: value – The value to create a NumericValue from
Returns:: A NumericValue (or one it the derived classes) representing the value

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶: Add a minimal representation of this object to a dictionary for subsequent serialization to JSON

class ObjectTypeStringValue( default_value: str | None = None, )¶

Bases: tlc.core.schema.StringValue

A string containing an object type

class ScalarValue( value_type: str = _DEFAULT_SCALAR_VALUE_TYPE, default_value: Any = None, )¶

Describes a scalar value in a schema

property default_value: Any¶

static from_any( any_value: Any, ) → ScalarValue¶: Create and populate a ScalarValue (or one of the derived classes) given an anonymous, potentially sparse object

static from_value( value: Any, ) → ScalarValue¶

Create a scalar value from a Python value.

Parameters:: value – The value to create a ScalarValue from
Returns:: A ScalarValue (or one it the derived classes) representing the value

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶: Add a minimal representation of this object to a dictionary for subsequent serialization to JSON

class Schema( display_name: str = '', description: str = '', writable: bool = True, display_importance: float = 0, value: ScalarValue | None = None, values: dict[str, Schema] | None = None, composite_role: str = '', display_color: str = '', swap_group: str = '', computable: bool = True, sample_type: str | None = None, transient: bool = False, default_visible: bool = True, size0: DimensionNumericValue | None = None, size1: DimensionNumericValue | None = None, size2: DimensionNumericValue | None = None, size3: DimensionNumericValue | None = None, size4: DimensionNumericValue | None = None, size5: DimensionNumericValue | None = None, metadata: dict[str, Any] | None = None, default_value: Any | None = None, array_signature_group: str | None = None, )¶

A schema is a recursive structure which defines the layout of an object. It defines what elements the object consists of, which must be either

Atomic type (with optional metadata, e.g. value range, unit, etc.) OR
Composite contents (a list of schemas describing the sub-object)

In addition, it defines HOW MANY of these scalar or composite elements exist, in the form of up to six-dimensions which can each be described separately and be of fixed or variable lengths. The default size of dimensions is 1, describing a scalar value.

Schemas are used for

Defining the layout of Objects (as reported by e.g. “MyObject.schema”)
In the case of Tables: defining the common layout of all table rows (as reported by e.g “MyTableObject.schema.values[“rows”])

In the case where a schema defines a “top-level” object, it will always have a ‘values’ attribute (since it is always a composite object, and does not comprise only a single atomic value).

add_outer_dimension() → Schema¶: Like push_dim, but adds an outer dimension (if possible).

add_sample_weight( hidden: bool = True, default_value: float = 1.0, ) → None¶

Adds a sample weight column to the schema.

Parameters:: hidden – Whether the column should be hidden

add_sub_schema( name: str, schema: Schema, ) → None¶: Adds a Schema as a sub-property within this Schema (i.e. into the ‘values’ collection)

add_sub_value( name: str, value: ScalarValue, writable: bool = True, computable: bool = True, ) → None¶: Adds a scalar value as a sub-property within this Schema (i.e. into the ‘values’ collection)

consider_override_from( override_schema: Schema | Mapping[str, object] | None, ) → Schema¶: Selectively overwrites columns within this Schema according to the columns defined in another Schema.

does_object_match( _object: Any, ) → bool¶

Checks whether a schema matches an example object.

This requires exact 1:1 mapping between attributes in the object and the schema (including recursively). This means no attributes can be missing, nor can there be any additional attributes only present in the object.

static from_any( any_object: Any, ) → Schema¶: Returns a Schema object which has been populated from a serialized (possibly sparse) object

static from_json( json_string: str, ) → Schema¶: Returns a Schema object which has been populated from a JSON string

classmethod from_sample( sample: Any, ) → Schema¶

Creates a schema describing the provided sample.

Parameters:: sample – The sample to create a schema from
Returns:: The schema

classmethod from_structure( structure: tlc.client.sample_type._SampleTypeStructure, ) → Schema¶

Creates a schema from a structure.

Parameters:: structure – The structure to create a schema from
Returns:: The schema

is_atomic() → bool¶

Return whether the schema is atomic, i.e. has a single value.

The opposite of is_composite.

Returns:: Whether the schema is atomic

is_composite() → bool¶

Return whether the schema is composite, i.e. has multiple values.

The opposite of is_atomic.

Returns:: Whether the schema is composite

is_empty() → bool¶

is_fixed_size() → bool¶

Return whether the schema has fixed size.

This requires all dimensions to be fixed size.

is_scalar() → bool¶

Return whether the schema is a scalar value

Sizes are required to be set in increasing dimensions without gaps and no size is treated like a scalar.

last_dimension() → DimensionNumericValue | None¶: Return the last (outermost) dimension of the Schema

pop_dim() → DimensionNumericValue | None¶

Sets size5 to None and shifts all other dimensions left. (size5 becomes size4, size4 becomes size3, etc.).

Returns:: The old size0

push_dim( dim: DimensionNumericValue | None = None, ) → DimensionNumericValue | None¶

Inserts dim as size0 and shifts all other dimensions right. (size1 becomes size0, size2 becomes size1).

Parameters:: dim – The dimension to insert as size0
Returns:: The old size5

row_from_sample( sample: Any, ) → Any¶

sample_from_row( row: Any, ) → Any¶

property sample_type_object: SampleType¶

set_writable_flag_recursively( writable: bool, ) → None¶

Sets the writable flag recursively.

Parameters:: writable – Whether the schema is writable

to_json() → str¶

Writes the contents of this schema to a JSON string. Note that

Defaults values are omitted for brevity
Schemas might be recursive

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶: Add a minimal representation of this object to a dictionary for subsequent serialization to JSON

class SegmentationMaskUrlStringValue( default_value: str | None = None, map: dict[float, MapElement] | dict[float, str] | None = None, )¶

Bases: tlc.core.schema.SegmentationUrlStringValue

Describes a Segmentation Mask URL string value

static from_any( any_value: Any, ) → SegmentationMaskUrlStringValue¶: Create and populate a SegmentationMaskUrlStringValue object given an anonymous, potentially sparse object

class SegmentationUrlStringValue( default_value: str | None = None, map: dict[float, MapElement] | dict[float, str] | None = None, )¶

Bases: tlc.core.schema.UrlStringValue

Describes a Segmentation URL string value

static from_any( any_value: Any, ) → SegmentationUrlStringValue¶: Create and populate a SegmentationUrlStringValue object given an anonymous, potentially sparse object

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶

class StringValue( string_role: str = '', default_value: str | None = None, )¶

Bases: tlc.core.schema.ScalarValue

Describes a string value

static from_any( any_value: Any, ) → StringValue¶: Create and populate a StringValue object given an anonymous, potentially sparse object

to_minimal_dict( include_all: bool, ) → dict[str, Any]¶: Add a minimal representation of this object to a dictionary for subsequent serialization to JSON

class TensorUrlStringValue( default_value: str | None = None, )¶

Bases: tlc.core.schema.UrlStringValue

Describes a URL string value pointing to a tensor

class TimestampValue( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = NUMBER_ROLE_TIMESTAMP, unit: str = 'ms', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.Int64Value

A timestamp value counting the number of ‘unit’s since epoch

Stores the value as an ‘int64’

Defaults to milliseconds resolution

class Uint16Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘uint16’

class Uint32Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘uint32’

class Uint64Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘uint64’

class Uint8Value( value_min: float | None = None, value_max: float | None = None, enforce_min: bool = False, enforce_max: bool = False, value_step: float = 0, number_role: str = '', unit: str = '', value_map: dict[float, MapElement] | None = None, default_value: int | None = None, )¶

Bases: tlc.core.schema.NumericValue

A numeric value with type ‘uint8’

class UrlStringValue( url_string_icon: str = '', default_value: str | None = None, )¶

Bases: tlc.core.schema.StringValue

Describes a generic URL string value

tlc.core.schema¶

Module Contents¶

Classes¶

API¶

`tlc.core.schema`¶