tensorbay.label.attributes

Items and AttributeInfo.

AttributeInfo represents the information of an attribute. It refers to the Json schema method to describe an attribute.

Items is the base class of AttributeInfo, representing the items of an attribute.

class tensorbay.label.attributes.Items(*, type_='', enum=None, minimum=None, maximum=None, items=None)[source]

Bases: tensorbay.utility.repr.ReprMixin, tensorbay.utility.common.EqMixin

The base class of AttributeInfo, representing the items of an attribute.

When the value type of an attribute is array, the AttributeInfo would contain an ‘items’ field.

Todo

The format of argument type_ on the generated web page is incorrect.

Parameters

type –
The type of the attribute value, could be a single type or multi-types. The type must be within the followings:
- array
- boolean
- integer
- number
- string
- null
- instance
enum (Optional[Iterable[Optional[Union[str, float, bool]]]]) – All the possible values of an enumeration attribute.
minimum (Optional[float]) – The minimum value of number type attribute.
maximum (Optional[float]) – The maximum value of number type attribute.
items (Optional[Items]) – The items inside array type attributes.
type_ (Union[str, None, Type[Optional[Union[list, bool, int, float, str]]], Iterable[Union[str, None, Type[Optional[Union[list, bool, int, float, str]]]]]]) –

type: The type of the attribute value, could be a single type or multi-types.

enum: All the possible values of an enumeration attribute.

minimum: The minimum value of number type attribute.

maximum: The maximum value of number type attribute.

items: The items inside array type attributes.

Raises

TypeError – When both enum and type_ are absent or when type_ is array and items is absent.

Parameters

type_ (Union[str, None, Type[Optional[Union[list, bool, int, float, str]]], Iterable[Union[str, None, Type[Optional[Union[list, bool, int, float, str]]]]]]) –
enum (Optional[Iterable[Optional[Union[str, float, bool]]]]) –
minimum (Optional[float]) –
maximum (Optional[float]) –
items (Optional[Items]) –

Examples

>>> Items(type_="integer", enum=[1, 2, 3, 4, 5], minimum=1, maximum=5)
Items(
  (type): 'integer',
  (enum): [...],
  (minimum): 1,
  (maximum): 5
)

classmethod loads(contents)[source]

Load an Items from a dict containing the items information.

Parameters: contents (Dict[str, Any]) – A dict containing the information of the items.
Returns: The loaded Items object.
Return type: tensorbay.label.attributes._T

Examples

>>> contents = {
...     "type": "array",
...     "enum": [1, 2, 3, 4, 5],
...     "minimum": 1,
...     "maximum": 5,
...     "items": {
...         "enum": [None],
...         "type": "null",
...     },
... }
>>> Items.loads(contents)
Items(
  (type): 'array',
  (enum): [...],
  (minimum): 1,
  (maximum): 5,
  (items): Items(...)
)

dumps()[source]

Dumps the information of the items into a dict.

Returns: A dict containing all the information of the items.
Return type: Dict[str, Any]

Examples

>>> items = Items(type_="integer", enum=[1, 2, 3, 4, 5], minimum=1, maximum=5)
>>> items.dumps()
{'type': 'integer', 'enum': [1, 2, 3, 4, 5], 'minimum': 1, 'maximum': 5}

class tensorbay.label.attributes.AttributeInfo(name, *, type_='', enum=None, minimum=None, maximum=None, items=None, parent_categories=None, description='')[source]

Bases: tensorbay.utility.name.NameMixin, tensorbay.label.attributes.Items

This class represents the information of an attribute.

It refers to the Json schema method to describe an attribute.

Todo

The format of argument type_ on the generated web page is incorrect.

Parameters

name (str) – The name of the attribute.
type –
The type of the attribute value, could be a single type or multi-types. The type must be within the followings:
- array
- boolean
- integer
- number
- string
- null
- instance
enum (Optional[Iterable[Optional[Union[str, float, bool]]]]) – All the possible values of an enumeration attribute.
minimum (Optional[float]) – The minimum value of number type attribute.
maximum (Optional[float]) – The maximum value of number type attribute.
items (Optional[tensorbay.label.attributes.Items]) – The items inside array type attributes.
parent_categories (List[str]) – The parent categories of the attribute.
description (str) – The description of the attribute.
type_ (Union[str, None, Type[Optional[Union[list, bool, int, float, str]]], Iterable[Union[str, None, Type[Optional[Union[list, bool, int, float, str]]]]]]) –

type: The type of the attribute value, could be a single type or multi-types.

enum: All the possible values of an enumeration attribute.

minimum: The minimum value of number type attribute.

maximum: The maximum value of number type attribute.

items: The items inside array type attributes.

parent_categories

The parent categories of the attribute.

Type: List[str]

description

The description of the attribute.

Type: str

Examples

>>> from tensorbay.label import Items
>>> items = Items(type_="integer", enum=[1, 2, 3, 4, 5], minimum=1, maximum=5)
>>> AttributeInfo(
...     name="example",
...     type_="array",
...     enum=[1, 2, 3, 4, 5],
...     items=items,
...     minimum=1,
...     maximum=5,
...     parent_categories=["parent_category_of_example"],
...     description="This is an example",
... )
AttributeInfo("example")(
  (type): 'array',
  (enum): [
    1,
    2,
    3,
    4,
    5
  ],
  (minimum): 1,
  (maximum): 5,
  (items): Items(
    (type): 'integer',
    (enum): [...],
    (minimum): 1,
    (maximum): 5
  ),
  (parent_categories): [
    'parent_category_of_example'
  ]
)

classmethod loads(contents)[source]

Load an AttributeInfo from a dict containing the attribute information.

Parameters: contents (Dict[str, Any]) – A dict containing the information of the attribute.
Returns: The loaded AttributeInfo object.
Return type: tensorbay.label.attributes._T

Examples

>>> contents = {
...     "name": "example",
...     "type": "array",
...     "items": {"type": "boolean"},
...     "description": "This is an example",
...     "parentCategories": ["parent_category_of_example"],
... }
>>> AttributeInfo.loads(contents)
AttributeInfo("example")(
  (type): 'array',
  (items): Items(
    (type): 'boolean',
  ),
  (parent_categories): [
    'parent_category_of_example'
  ]
)

dumps()[source]

Dumps the information of this attribute into a dict.

Returns: A dict containing all the information of this attribute.
Return type: Dict[str, Any]

Examples

>>> from tensorbay.label import Items
>>> items = Items(type_="integer", minimum=1, maximum=5)
>>> attributeinfo = AttributeInfo(
...     name="example",
...     type_="array",
...     items=items,
...     parent_categories=["parent_category_of_example"],
...     description="This is an example",
... )
>>> attributeinfo.dumps()
{
    'name': 'example',
    'description': 'This is an example',
    'type': 'array',
    'items': {'type': 'integer', 'minimum': 1, 'maximum': 5},
    'parentCategories': ['parent_category_of_example'],
}