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To install Gradio from main, run the following command:
pip install https://gradio-builds.s3.amazonaws.com/4a3ee6fafe8ba9ecf1d5c103002766db14c569f4/gradio-4.31.4-py3-none-any.whl*Note: Setting share=True in
launch() will not work.
Job %20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
gradio.Job(future, ···)Description
A Job is a wrapper over the Future class that represents a prediction call that has been submitted by the Gradio client. This class is not meant to be instantiated directly, but rather is created by the Client.submit() method.
A Job object includes methods to get the status of the prediction call, as well to get the outputs of the prediction call. Job objects are also iterable, and can be used in a loop to get the outputs of prediction calls as they become available for generator endpoints.
Initialization
| Parameter | Description |
|---|---|
future Future required | The future object that represents the prediction call, created by the Client.submit() method |
communicator Communicator | None default: None | The communicator object that is used to communicate between the client and the background thread running the job |
verbose bool default: True | Whether to print any status-related messages to the console |
space_id str | None default: None | The space ID corresponding to the Client object that created this Job object |
Methods
result
gradio.Job.result(···)Description
Return the result of the call that the future represents. Raises CancelledError: If the future was cancelled, TimeoutError: If the future didn't finish executing before the given timeout, and Exception: If the call raised then that exception will be raised. <br>
Example Usage
from gradio_client import Client
calculator = Client(src="gradio/calculator")
job = calculator.submit("foo", "add", 4, fn_index=0)
job.result(timeout=5)
>> 9Agruments
| Parameter | Description |
|---|---|
timeout float | None default: None | The number of seconds to wait for the result if the future isn't done. If None, then there is no limit on the wait time. |
outputs
gradio.Job.outputs(···)Description
Returns a list containing the latest outputs from the Job. <br> If the endpoint has multiple output components, the list will contain a tuple of results. Otherwise, it will contain the results without storing them in tuples. <br> For endpoints that are queued, this list will contain the final job output even if that endpoint does not use a generator function. <br>
Example Usage
from gradio_client import Client
client = Client(src="gradio/count_generator")
job = client.submit(3, api_name="/count")
while not job.done():
time.sleep(0.1)
job.outputs()
>> ['0', '1', '2']status
gradio.Job.status(···)Description
Returns the latest status update from the Job in the form of a StatusUpdate object, which contains the following fields: code, rank, queue_size, success, time, eta, and progress_data. <br> progress_data is a list of updates emitted by the gr.Progress() tracker of the event handler. Each element of the list has the following fields: index, length, unit, progress, desc. If the event handler does not have a gr.Progress() tracker, the progress_data field will be None. <br>
Example Usage
from gradio_client import Client
client = Client(src="gradio/calculator")
job = client.submit(5, "add", 4, api_name="/predict")
job.status()
>> <Status.STARTING: 'STARTING'>
job.status().eta
>> 43.241 # seconds