Testing Audio Component Processing and Streaming in gradio-app/gradio
This test suite validates the Audio component functionality in the Gradio library, covering core audio processing operations, file handling, and format conversions. The tests ensure reliable audio manipulation and streaming capabilities across different input/output scenarios.
Test Coverage Overview
Implementation Analysis
Technical Details
Best Practices Demonstrated
gradio-app/gradio
test/components/test_audio.py
import filecmp
from copy import deepcopy
from difflib import SequenceMatcher
from pathlib import Path
import numpy as np
import pytest
from gradio_client import media_data
from gradio_client import utils as client_utils
import gradio as gr
from gradio import processing_utils, utils
from gradio.data_classes import FileData
class TestAudio:
@pytest.mark.asyncio
async def test_component_functions(self, gradio_temp_dir):
"""
Preprocess, postprocess serialize, get_config, deserialize
type: filepath, numpy, file
"""
x_wav = FileData(path=media_data.BASE64_AUDIO["path"])
audio_input = gr.Audio()
output1 = audio_input.preprocess(x_wav)
assert isinstance(output1, tuple)
assert output1[0] == 8000
assert output1[1].shape == (8046,)
x_wav = await processing_utils.async_move_files_to_cache([x_wav], audio_input)
x_wav = x_wav[0]
audio_input = gr.Audio(type="filepath")
output1 = audio_input.preprocess(x_wav)
assert isinstance(output1, str)
assert Path(output1).name.endswith("audio_sample.wav")
audio_input = gr.Audio(label="Upload Your Audio")
assert audio_input.get_config() == {
"autoplay": False,
"sources": ["upload", "microphone"],
"name": "audio",
"show_download_button": None,
"show_share_button": False,
"streaming": False,
"show_label": True,
"label": "Upload Your Audio",
"container": True,
"editable": True,
"min_width": 160,
"scale": None,
"elem_id": None,
"elem_classes": [],
"visible": True,
"value": None,
"interactive": None,
"proxy_url": None,
"type": "numpy",
"format": None,
"recording": False,
"streamable": False,
"max_length": None,
"min_length": None,
"waveform_options": {
"sample_rate": 44100,
"show_controls": False,
"show_recording_waveform": True,
"skip_length": 5,
"waveform_color": None,
"waveform_progress_color": None,
"trim_region_color": None,
},
"_selectable": False,
"key": None,
"loop": False,
}
assert audio_input.preprocess(None) is None
audio_input = gr.Audio(type="filepath")
assert isinstance(audio_input.preprocess(x_wav), str)
with pytest.raises(ValueError):
gr.Audio(type="unknown") # type: ignore
rng = np.random.default_rng()
# Confirm Audio can be instantiated with a numpy array
gr.Audio((100, rng.random(size=(1000, 2))), label="Play your audio")
# Output functionalities
y_audio = client_utils.decode_base64_to_file(
deepcopy(media_data.BASE64_AUDIO)["data"]
)
audio_output = gr.Audio(type="filepath")
assert filecmp.cmp(
y_audio.name,
audio_output.postprocess(y_audio.name).model_dump()["path"], # type: ignore
)
assert audio_output.get_config() == {
"autoplay": False,
"name": "audio",
"show_download_button": None,
"show_share_button": False,
"streaming": False,
"show_label": True,
"label": None,
"max_length": None,
"min_length": None,
"container": True,
"editable": True,
"min_width": 160,
"recording": False,
"scale": None,
"elem_id": None,
"elem_classes": [],
"visible": True,
"value": None,
"interactive": None,
"proxy_url": None,
"type": "filepath",
"format": None,
"streamable": False,
"sources": ["upload", "microphone"],
"waveform_options": {
"sample_rate": 44100,
"show_controls": False,
"show_recording_waveform": True,
"skip_length": 5,
"waveform_color": None,
"waveform_progress_color": None,
"trim_region_color": None,
},
"_selectable": False,
"key": None,
"loop": False,
}
output1 = audio_output.postprocess(y_audio.name).model_dump() # type: ignore
output2 = audio_output.postprocess(Path(y_audio.name)).model_dump() # type: ignore
assert output1 == output2
def test_default_value_postprocess(self):
x_wav = deepcopy(media_data.BASE64_AUDIO)
audio = gr.Audio(value=x_wav["path"])
assert utils.is_in_or_equal(audio.value["path"], audio.GRADIO_CACHE)
def test_in_interface(self):
def reverse_audio(audio):
sr, data = audio
return (sr, np.flipud(data))
iface = gr.Interface(reverse_audio, "audio", "audio")
reversed_file = iface("test/test_files/audio_sample.wav")
reversed_reversed_file = iface(reversed_file)
reversed_reversed_data = client_utils.encode_url_or_file_to_base64(
reversed_reversed_file
)
similarity = SequenceMatcher(
a=reversed_reversed_data, b=media_data.BASE64_AUDIO["data"]
).ratio()
assert similarity > 0.99
def test_in_interface_as_output(self):
"""
Interface, process
"""
def generate_noise(duration):
return 48000, np.random.randint(-256, 256, (duration, 3)).astype(np.int16)
iface = gr.Interface(generate_noise, "slider", "audio")
assert iface(100).endswith(".wav")
def test_prepost_process_to_mp3(self, gradio_temp_dir):
x_wav = FileData(
path=processing_utils.save_base64_to_cache(
media_data.BASE64_MICROPHONE["data"], cache_dir=gradio_temp_dir
)
)
audio_input = gr.Audio(type="filepath", format="mp3")
output = audio_input.preprocess(x_wav)
assert isinstance(output, str)
assert output.endswith("mp3")
output = audio_input.postprocess(
(48000, np.random.randint(-256, 256, (5, 3)).astype(np.int16))
).model_dump() # type: ignore
assert output["path"].endswith("mp3")
@pytest.mark.asyncio
async def test_combine_stream_audio(self, gradio_temp_dir):
x_wav = FileData(
path=processing_utils.save_base64_to_cache(
media_data.BASE64_MICROPHONE["data"], cache_dir=gradio_temp_dir
)
)
bytes_output = [Path(x_wav.path).read_bytes()] * 2
output = await gr.Audio().combine_stream(
bytes_output, desired_output_format="wav"
)
assert str(output.path).endswith("wav")
output = await gr.Audio().combine_stream(
bytes_output, desired_output_format=None
)
assert str(output.path).endswith("mp3")