VideoSink Class

Video sink allows for video and audio to be recorded to the Video Analyzer service. The recorded video can be played from anywhere and further managed from the cloud. Due to security reasons, a given Video Analyzer edge module instance can only record content to new video entries, or existing video entries previously recorded by the same module. Any attempt to record content to an existing video which has not been created by the same module instance will result in failure to record.

All required parameters must be populated in order to send to Azure.

Inheritance

azure.media.videoanalyzeredge._generated.models._models_py3.SinkNodeBase

VideoSink

Constructor

VideoSink(*, name: str, inputs: List[NodeInput], video_name: str, local_media_cache_path: str, local_media_cache_maximum_size_mi_b: str, video_creation_properties: VideoCreationProperties | None = None, video_publishing_options: VideoPublishingOptions | None = None, **kwargs)

Keyword-Only Parameters

Name	Description
name	str Required. Node name. Must be unique within the topology.
inputs	list[<xref:azure.media.videoanalyzer.edge.models.NodeInput>] Required. An array of upstream node references within the topology to be used as inputs for this node.
video_name	str Required. Name of a new or existing Video Analyzer video resource used for the media recording.
video_creation_properties	<xref:azure.media.videoanalyzer.edge.models.VideoCreationProperties> Optional video properties to be used in case a new video resource needs to be created on the service.
video_publishing_options	<xref:azure.media.videoanalyzer.edge.models.VideoPublishingOptions> Optional video publishing options to be used for changing publishing behavior of the output video.
local_media_cache_path	str Required. Path to a local file system directory for caching of temporary media files. This will also be used to store content which cannot be immediately uploaded to Azure due to Internet connectivity issues.
local_media_cache_maximum_size_mi_b	str Required. Maximum amount of disk space that can be used for caching of temporary media files. Once this limit is reached, the oldest segments of the media archive will be continuously deleted in order to make space for new media, thus leading to gaps in the cloud recorded content.

Variables

Name	Description
type	str Required. Type discriminator for the derived types.Constant filled by server.
name	str Required. Node name. Must be unique within the topology.
inputs	list[<xref:azure.media.videoanalyzer.edge.models.NodeInput>] Required. An array of upstream node references within the topology to be used as inputs for this node.
video_name	str Required. Name of a new or existing Video Analyzer video resource used for the media recording.
video_creation_properties	<xref:azure.media.videoanalyzer.edge.models.VideoCreationProperties> Optional video properties to be used in case a new video resource needs to be created on the service.
video_publishing_options	<xref:azure.media.videoanalyzer.edge.models.VideoPublishingOptions> Optional video publishing options to be used for changing publishing behavior of the output video.
local_media_cache_path	str Required. Path to a local file system directory for caching of temporary media files. This will also be used to store content which cannot be immediately uploaded to Azure due to Internet connectivity issues.
local_media_cache_maximum_size_mi_b	str Required. Maximum amount of disk space that can be used for caching of temporary media files. Once this limit is reached, the oldest segments of the media archive will be continuously deleted in order to make space for new media, thus leading to gaps in the cloud recorded content.

Methods

as_dict	Return a dict that can be JSONify using json.dump. Advanced usage might optionally use a callback as parameter: Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains 'type' with the msrest type and 'key' with the RestAPI encoded key. Value is the current value in this object. The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict. See the three examples in this file: attribute_transformer full_restapi_key_transformer last_restapi_key_transformer If you want XML serialization, you can pass the kwargs is_xml=True.
deserialize	Parse a str using the RestAPI syntax and return a model.
enable_additional_properties_sending
from_dict	Parse a dict using given key extractor return a model. By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)
is_xml_model
serialize	Return the JSON that would be sent to azure from this model. This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False). If you want XML serialization, you can pass the kwargs is_xml=True.
validate	Validate this model recursively and return a list of ValidationError.

as_dict

Return a dict that can be JSONify using json.dump.

Advanced usage might optionally use a callback as parameter:

Key is the attribute name used in Python. Attr_desc is a dict of metadata. Currently contains 'type' with the msrest type and 'key' with the RestAPI encoded key. Value is the current value in this object.

The string returned will be used to serialize the key. If the return type is a list, this is considered hierarchical result dict.

See the three examples in this file:

• attribute_transformer

• full_restapi_key_transformer

• last_restapi_key_transformer

If you want XML serialization, you can pass the kwargs is_xml=True.

as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>, **kwargs)

Parameters

Name	Description
key_transformer	<xref:function> A key transformer function.
keep_readonly	default value: True

Returns

Type	Description
dict	A dict JSON compatible object

deserialize

Parse a str using the RestAPI syntax and return a model.

deserialize(data, content_type=None)

Parameters

Name	Description
data Required	str A str using RestAPI structure. JSON by default.
content_type	str JSON by default, set application/xml if XML. default value: None

Returns

Type	Description
	An instance of this model

Exceptions

Type	Description
DeserializationError if something went wrong

enable_additional_properties_sending

enable_additional_properties_sending()

from_dict

Parse a dict using given key extractor return a model.

By default consider key extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor and last_rest_key_case_insensitive_extractor)

from_dict(data, key_extractors=None, content_type=None)

Parameters

Name	Description
data Required	dict A dict using RestAPI structure
content_type	str JSON by default, set application/xml if XML. default value: None
key_extractors	default value: None

Returns

Type	Description
	An instance of this model

Exceptions

Type	Description
DeserializationError if something went wrong

is_xml_model

is_xml_model()

serialize

Return the JSON that would be sent to azure from this model.

This is an alias to as_dict(full_restapi_key_transformer, keep_readonly=False).

If you want XML serialization, you can pass the kwargs is_xml=True.

serialize(keep_readonly=False, **kwargs)

Parameters

Name	Description
keep_readonly	bool If you want to serialize the readonly attributes default value: False

Returns

Type	Description
dict	A dict JSON compatible object

validate

Validate this model recursively and return a list of ValidationError.

validate()

Returns

Type	Description
list	A list of validation error