Gradio logo

New to Gradio? Start here: Getting Started

See the Release History

Timeseries

gradio.Timeseries(ยทยทยท)

Description

Creates a component that can be used to upload/preview timeseries csv files or display a dataframe consisting of a time series graphically.

Behavior

As input: passes the uploaded timeseries data as a pandas.DataFrame into the function

As output: expects a pandas.DataFrame or str path to a csv to be returned, which is then displayed as a timeseries graph

Initialization

Parameter Description
value

str | Callable | None

default: None

File path for the timeseries csv file. If callable, the function will be called whenever the app loads to set the initial value of the component.

x

str | None

default: None

Column name of x (time) series. None if csv has no headers, in which case first column is x series.

y

str | list[str] | None

default: None

Column name of y series, or list of column names if multiple series. None if csv has no headers, in which case every column after first is a y series.

colors

list[str] | None

default: None

an ordered list of colors to use for each line plot

label

str | None

default: None

component name in interface.

every

float | None

default: None

If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. Queue must be enabled. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.

show_label

bool | None

default: None

if True, will display label.

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.

interactive

bool | None

default: None

if True, will allow users to upload a timeseries csv; if False, can only be used to display timeseries data. If not provided, this is inferred based on whether the component is used as an input or output.

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.

Shortcuts

Class Interface String Shortcut Initialization

gradio.Timeseries

"timeseries"

Uses default values

Demos

import random
import os
import gradio as gr


def fraud_detector(card_activity, categories, sensitivity):
    activity_range = random.randint(0, 100)
    drop_columns = [
        column for column in ["retail", "food", "other"] if column not in categories
    ]
    if len(drop_columns):
        card_activity.drop(columns=drop_columns, inplace=True)
    return (
        card_activity,
        card_activity,
        {"fraud": activity_range / 100.0, "not fraud": 1 - activity_range / 100.0},
    )


demo = gr.Interface(
    fraud_detector,
    [
        gr.Timeseries(x="time", y=["retail", "food", "other"]),
        gr.CheckboxGroup(
            ["retail", "food", "other"], value=["retail", "food", "other"]
        ),
        gr.Slider(1, 3),
    ],
    [
        "dataframe",
        gr.Timeseries(x="time", y=["retail", "food", "other"]),
        gr.Label(label="Fraud Level"),
    ],
    examples=[
        [os.path.join(os.path.dirname(__file__), "fraud.csv"), ["retail", "food", "other"], 1.0],
    ],
)
if __name__ == "__main__":
    demo.launch()

Event Listeners

Description

Event listeners allow you to capture and respond to user interactions with the UI components you've defined in a Gradio Blocks app. When a user interacts with an element, such as changing a slider value or uploading an image, a function is called.

Supported Event Listeners

The Timeseries component supports the following event listeners. Each event listener takes the same parameters, which are listed in the Event Arguments table below.

Listener Description

gradio.Timeseries.change(fn, ยทยทยท)

This listener is triggered when the component's value changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.

Event Arguments

Parameter Description
fn

Callable | None | Literal['decorator']

default: "decorator"

the function to call when this event is triggered. 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

Deprecated and has no effect.

scroll_to_output

bool

default: False

If True, will scroll to output component on completion

show_progress

Literal[('full', 'minimal', 'hidden')] | None

default: None

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.