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import numpy as np
import panel as pn


The Audio pane displays an audio player given a local or remote audio file, NumPy ndarray or a Torch Tensor.

The pane also allows access and control over the player state including toggling of playing/paused and loop state, the current time, and the volume.

The audio player supports ogg, mp3, and wav file formats

If SciPy is installed, 1-dim Numpy ndarrys and 1-dim Torch Tensors are also supported. The dtype must be one of the following

  • numpy: np.int16, np.uint16, np.float32, np.float64

  • torch: torch.short, torch.int16, torch.half, torch.float16, torch.float, torch.float32, torch.double, torch.float64

The array or tensor input will be downsampled to 16bit and converted to a wav file by SciPy.


For details on other options for customizing the component see the layout and styling how-to guides.

  • autoplay (boolean): When True, it specifies that the output will play automatically. In Chromium browsers this requires the user to click play once

  • loop (boolean): Whether to loop when reaching the end of playback

  • muted (boolean): When True, it specifies that the output should be muted

  • name (str): The title of the pane

  • object (string): Local file path, remote URL pointing to audio file, 1-dim numpy array or 1-dim torch tensor

  • paused (boolean): Whether the player is paused

  • sample_rate (int): The sample_rate of the audio when given a NumPy array or Torch Tensor. Default is 44100.

  • throttle (int): How frequently to sample the current playback in milliseconds

  • time (float): Current playback time in seconds

  • volume (int): Volume in the range 0-100

The Audio pane can be constructed with a URL pointing to a remote audio file or a local audio file (in which case the data is embedded).

audio = pn.pane.Audio('', name='Audio')


The player can be controlled using its own widgets, as well as by using Python code as follows. To pause or unpause it in code, use the paused property:

#audio.paused = False

The current player time can be read and set with the time variable (in seconds):


The volume may also be read and set:

audio.volume = 50

When providing a NumPy Array or Torch Tensor, you should specify the sample_rate.

In this example we plot a frequency modulated signal:

sps = 44100 # Samples per second
duration = 10 # Duration in seconds

modulator_frequency = 2.0
carrier_frequency = 120.0
modulation_index = 2.0

time = np.arange(sps*duration) / sps
modulator = np.sin(2.0 * np.pi * modulator_frequency * time) * modulation_index
carrier = np.sin(2.0 * np.pi * carrier_frequency * time)
waveform = np.sin(2. * np.pi * (carrier_frequency * time + modulator))
waveform_quiet = waveform * 0.3

pn.pane.Audio(waveform_quiet, sample_rate=sps)