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Dataset

gr.Dataset(components, samples)

Description

Used to create an output widget for showing datasets. Used to render the examples box.

Behavior

As input: passes the selected sample either as a list of data (if type="value") or as an int index (if type="index")

As output: expects a list of lists corresponding to the dataset data.

Initialization

Parameter Description
label

str | None

default: None

components

list[IOComponent] | list[str]

required

Which component types to show in this dataset widget, can be passed in as a list of string names or Components instances. The following components are supported in a Dataset: Audio, Checkbox, CheckboxGroup, ColorPicker, Dataframe, Dropdown, File, HTML, Image, Markdown, Model3D, Number, Radio, Slider, Textbox, TimeSeries, Video

samples

list[list[Any]] | None

default: None

a nested list of samples. Each sublist within the outer list represents a data sample, and each element within the sublist represents an value for each component

headers

list[str] | None

default: None

Column headers in the Dataset widget, should be the same len as components. If not provided, inferred from component labels

type

Literal['values', 'index']

default: "values"

'values' if clicking on a sample should pass the value of the sample, or "index" if it should pass the index of the sample

samples_per_page

int

default: 10

how many examples to show per page.

visible

bool

default: True

If False, component will be hidden.

elem_id

str | None

default: None

An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.

elem_classes

list[str] | str | None

default: None

An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.

container

bool

default: True

If True, will place the component in a container - providing some extra padding around the border.

scale

int | None

default: None

relative width compared to adjacent Components in a Row. For example, if Component A has scale=2, and Component B has scale=1, A will be twice as wide as B. Should be an integer.

min_width

int

default: 160

minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.

Shortcuts

Class Interface String Shortcut Initialization

gradio.Dataset

"dataset"

Uses default values

Methods

click

gradio.Dataset.click(fn, ···)

Description

This listener is triggered when the component (e.g. a button) is clicked. This method can be used when this component is in a Gradio Blocks.

Agruments

Parameter Description
fn

Callable | None

required

the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.

inputs

Component | Sequence[Component] | set[Component] | None

default: None

List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list.

outputs

Component | Sequence[Component] | None

default: None

List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list.

api_name

str | None | Literal[False]

default: None

Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name.

status_tracker

None

default: None

scroll_to_output

bool

default: False

If True, will scroll to output component on completion

show_progress

Literal['full', 'minimal', 'hidden']

default: "full"

If True, will show progress animation while pending

queue

bool | None

default: None

If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app.

batch

bool

default: False

If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component.

max_batch_size

int

default: 4

Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True)

preprocess

bool

default: True

If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component).

postprocess

bool

default: True

If False, will not run postprocessing of component data before returning 'fn' output to the browser.

cancels

dict[str, Any] | list[dict[str, Any]] | None

default: None

A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish.

every

float | None

default: None

Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled.

select

gradio.Dataset.select(fn, ···)

Description

This listener is triggered when the user selects from within the Component. This event has EventData of type gradio.SelectData that carries information, accessible through SelectData.index and SelectData.value. See EventData documentation on how to use this event data.

Agruments

Parameter Description
fn

Callable | None

required

the function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.

inputs

Component | Sequence[Component] | set[Component] | None

default: None

List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list.

outputs

Component | Sequence[Component] | None

default: None

List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list.

api_name

str | None | Literal[False]

default: None

Defines how the endpoint appears in the API docs. Can be a string, None, or False. If False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name.

status_tracker

None

default: None

scroll_to_output

bool

default: False

If True, will scroll to output component on completion

show_progress

Literal['full', 'minimal', 'hidden']

default: "full"

If True, will show progress animation while pending

queue

bool | None

default: None

If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app.

batch

bool

default: False

If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component.

max_batch_size

int

default: 4

Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True)

preprocess

bool

default: True

If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component).

postprocess

bool

default: True

If False, will not run postprocessing of component data before returning 'fn' output to the browser.

cancels

dict[str, Any] | list[dict[str, Any]] | None

default: None

A list of other events to cancel when This listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish.

every

float | None

default: None

Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. Queue must be enabled.