# Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License.
# This product includes software developed at Datadog (https://www.datadoghq.com/).
# Copyright 2019-Present Datadog, Inc.
from __future__ import annotations


from datadog_api_client.model_utils import (
    ModelComposed,
    cached_property,
)


class NotebookCellUpdateRequestAttributes(ModelComposed):
    def __init__(self, **kwargs):
        """
        The attributes of a notebook cell in update cell request. Valid cell types are ``markdown`` , ``timeseries`` , ``toplist`` , ``heatmap`` , ``distribution`` ,
        ``log_stream``. `More information on each graph visualization type. <https://docs.datadoghq.com/dashboards/widgets/>`_

        :param definition: Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
        :type definition: NotebookMarkdownCellDefinition

        :param graph_size: The size of the graph.
        :type graph_size: NotebookGraphSize, optional

        :param split_by: Object describing how to split the graph to display multiple visualizations per request.
        :type split_by: NotebookSplitBy, optional

        :param time: Timeframe for the notebook cell. When 'null', the notebook global time is used.
        :type time: NotebookCellTime, none_type, optional
        """
        super().__init__(kwargs)

    @cached_property
    def _composed_schemas(_):
        # we need this here to make our import statements work
        # we must store _composed_schemas in here so the code is only run
        # when we invoke this method. If we kept this at the class
        # level we would get an error because the class level
        # code would be run when this module is imported, and these composed
        # classes don't exist yet because their module has not finished
        # loading
        from datadog_api_client.v1.model.notebook_markdown_cell_attributes import NotebookMarkdownCellAttributes
        from datadog_api_client.v1.model.notebook_timeseries_cell_attributes import NotebookTimeseriesCellAttributes
        from datadog_api_client.v1.model.notebook_toplist_cell_attributes import NotebookToplistCellAttributes
        from datadog_api_client.v1.model.notebook_heat_map_cell_attributes import NotebookHeatMapCellAttributes
        from datadog_api_client.v1.model.notebook_distribution_cell_attributes import NotebookDistributionCellAttributes
        from datadog_api_client.v1.model.notebook_log_stream_cell_attributes import NotebookLogStreamCellAttributes

        return {
            "oneOf": [
                NotebookMarkdownCellAttributes,
                NotebookTimeseriesCellAttributes,
                NotebookToplistCellAttributes,
                NotebookHeatMapCellAttributes,
                NotebookDistributionCellAttributes,
                NotebookLogStreamCellAttributes,
            ],
        }

64184923130567cf736852b645bba7fbdaa59208
<mask token>


class NotebookCellUpdateRequestAttributes(ModelComposed):
    <mask token>
    <mask token>

<mask token>


class NotebookCellUpdateRequestAttributes(ModelComposed):

    def __init__(self, **kwargs):
        """
        The attributes of a notebook cell in update cell request. Valid cell types are ``markdown`` , ``timeseries`` , ``toplist`` , ``heatmap`` , ``distribution`` ,
        ``log_stream``. `More information on each graph visualization type. <https://docs.datadoghq.com/dashboards/widgets/>`_

        :param definition: Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
        :type definition: NotebookMarkdownCellDefinition

        :param graph_size: The size of the graph.
        :type graph_size: NotebookGraphSize, optional

        :param split_by: Object describing how to split the graph to display multiple visualizations per request.
        :type split_by: NotebookSplitBy, optional

        :param time: Timeframe for the notebook cell. When 'null', the notebook global time is used.
        :type time: NotebookCellTime, none_type, optional
        """
        super().__init__(kwargs)
    <mask token>

<mask token>


class NotebookCellUpdateRequestAttributes(ModelComposed):

    def __init__(self, **kwargs):
        """
        The attributes of a notebook cell in update cell request. Valid cell types are ``markdown`` , ``timeseries`` , ``toplist`` , ``heatmap`` , ``distribution`` ,
        ``log_stream``. `More information on each graph visualization type. <https://docs.datadoghq.com/dashboards/widgets/>`_

        :param definition: Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
        :type definition: NotebookMarkdownCellDefinition

        :param graph_size: The size of the graph.
        :type graph_size: NotebookGraphSize, optional

        :param split_by: Object describing how to split the graph to display multiple visualizations per request.
        :type split_by: NotebookSplitBy, optional

        :param time: Timeframe for the notebook cell. When 'null', the notebook global time is used.
        :type time: NotebookCellTime, none_type, optional
        """
        super().__init__(kwargs)

    @cached_property
    def _composed_schemas(_):
        from datadog_api_client.v1.model.notebook_markdown_cell_attributes import NotebookMarkdownCellAttributes
        from datadog_api_client.v1.model.notebook_timeseries_cell_attributes import NotebookTimeseriesCellAttributes
        from datadog_api_client.v1.model.notebook_toplist_cell_attributes import NotebookToplistCellAttributes
        from datadog_api_client.v1.model.notebook_heat_map_cell_attributes import NotebookHeatMapCellAttributes
        from datadog_api_client.v1.model.notebook_distribution_cell_attributes import NotebookDistributionCellAttributes
        from datadog_api_client.v1.model.notebook_log_stream_cell_attributes import NotebookLogStreamCellAttributes
        return {'oneOf': [NotebookMarkdownCellAttributes,
            NotebookTimeseriesCellAttributes, NotebookToplistCellAttributes,
            NotebookHeatMapCellAttributes,
            NotebookDistributionCellAttributes,
            NotebookLogStreamCellAttributes]}

from __future__ import annotations
from datadog_api_client.model_utils import ModelComposed, cached_property


class NotebookCellUpdateRequestAttributes(ModelComposed):

    def __init__(self, **kwargs):
        """
        The attributes of a notebook cell in update cell request. Valid cell types are ``markdown`` , ``timeseries`` , ``toplist`` , ``heatmap`` , ``distribution`` ,
        ``log_stream``. `More information on each graph visualization type. <https://docs.datadoghq.com/dashboards/widgets/>`_

        :param definition: Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
        :type definition: NotebookMarkdownCellDefinition

        :param graph_size: The size of the graph.
        :type graph_size: NotebookGraphSize, optional

        :param split_by: Object describing how to split the graph to display multiple visualizations per request.
        :type split_by: NotebookSplitBy, optional

        :param time: Timeframe for the notebook cell. When 'null', the notebook global time is used.
        :type time: NotebookCellTime, none_type, optional
        """
        super().__init__(kwargs)

    @cached_property
    def _composed_schemas(_):
        from datadog_api_client.v1.model.notebook_markdown_cell_attributes import NotebookMarkdownCellAttributes
        from datadog_api_client.v1.model.notebook_timeseries_cell_attributes import NotebookTimeseriesCellAttributes
        from datadog_api_client.v1.model.notebook_toplist_cell_attributes import NotebookToplistCellAttributes
        from datadog_api_client.v1.model.notebook_heat_map_cell_attributes import NotebookHeatMapCellAttributes
        from datadog_api_client.v1.model.notebook_distribution_cell_attributes import NotebookDistributionCellAttributes
        from datadog_api_client.v1.model.notebook_log_stream_cell_attributes import NotebookLogStreamCellAttributes
        return {'oneOf': [NotebookMarkdownCellAttributes,
            NotebookTimeseriesCellAttributes, NotebookToplistCellAttributes,
            NotebookHeatMapCellAttributes,
            NotebookDistributionCellAttributes,
            NotebookLogStreamCellAttributes]}

# Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License.
# This product includes software developed at Datadog (https://www.datadoghq.com/).
# Copyright 2019-Present Datadog, Inc.
from __future__ import annotations


from datadog_api_client.model_utils import (
    ModelComposed,
    cached_property,
)


class NotebookCellUpdateRequestAttributes(ModelComposed):
    def __init__(self, **kwargs):
        """
        The attributes of a notebook cell in update cell request. Valid cell types are ``markdown`` , ``timeseries`` , ``toplist`` , ``heatmap`` , ``distribution`` ,
        ``log_stream``. `More information on each graph visualization type. <https://docs.datadoghq.com/dashboards/widgets/>`_

        :param definition: Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
        :type definition: NotebookMarkdownCellDefinition

        :param graph_size: The size of the graph.
        :type graph_size: NotebookGraphSize, optional

        :param split_by: Object describing how to split the graph to display multiple visualizations per request.
        :type split_by: NotebookSplitBy, optional

        :param time: Timeframe for the notebook cell. When 'null', the notebook global time is used.
        :type time: NotebookCellTime, none_type, optional
        """
        super().__init__(kwargs)

    @cached_property
    def _composed_schemas(_):
        # we need this here to make our import statements work
        # we must store _composed_schemas in here so the code is only run
        # when we invoke this method. If we kept this at the class
        # level we would get an error because the class level
        # code would be run when this module is imported, and these composed
        # classes don't exist yet because their module has not finished
        # loading
        from datadog_api_client.v1.model.notebook_markdown_cell_attributes import NotebookMarkdownCellAttributes
        from datadog_api_client.v1.model.notebook_timeseries_cell_attributes import NotebookTimeseriesCellAttributes
        from datadog_api_client.v1.model.notebook_toplist_cell_attributes import NotebookToplistCellAttributes
        from datadog_api_client.v1.model.notebook_heat_map_cell_attributes import NotebookHeatMapCellAttributes
        from datadog_api_client.v1.model.notebook_distribution_cell_attributes import NotebookDistributionCellAttributes
        from datadog_api_client.v1.model.notebook_log_stream_cell_attributes import NotebookLogStreamCellAttributes

        return {
            "oneOf": [
                NotebookMarkdownCellAttributes,
                NotebookTimeseriesCellAttributes,
                NotebookToplistCellAttributes,
                NotebookHeatMapCellAttributes,
                NotebookDistributionCellAttributes,
                NotebookLogStreamCellAttributes,
            ],
        }
