""" Tests for all of the components defined in components.py. Tests are divided into two types: 1. test_component_functions() are unit tests that check essential functions of a component, the functions that are checked are documented in the docstring. 2. test_in_interface() are functional tests that check a component's functionalities inside an Interface. Please do not use Interface.launch() in this file, as it slow downs the tests. """ import filecmp import json import os import shutil import tempfile from copy import deepcopy from difflib import SequenceMatcher from pathlib import Path from unittest.mock import MagicMock, patch import numpy as np import pandas as pd import PIL import pytest import vega_datasets from gradio_client import media_data from gradio_client import utils as client_utils from scipy.io import wavfile try: from typing import cast except ImportError: from typing import cast import gradio as gr from gradio import processing_utils, utils from gradio.components.dataframe import DataframeData from gradio.components.file_explorer import FileExplorerData from gradio.components.image_editor import EditorData from gradio.components.video import VideoData from gradio.data_classes import FileData, ListFiles os.environ["GRADIO_ANALYTICS_ENABLED"] = "False" class TestGettingComponents: def test_component_function(self): assert isinstance( gr.components.component("textarea", render=False), gr.templates.TextArea ) @pytest.mark.parametrize( "component, render, unrender, should_be_rendered", [ (gr.Textbox(render=True), False, True, False), (gr.Textbox(render=False), False, False, False), (gr.Textbox(render=False), True, False, True), ("textbox", False, False, False), ("textbox", True, False, True), ], ) def test_get_component_instance_rendering( self, component, render, unrender, should_be_rendered ): with gr.Blocks(): textbox = gr.components.get_component_instance( component, render=render, unrender=unrender ) assert textbox.is_rendered == should_be_rendered class TestTextbox: def test_component_functions(self): """ Preprocess, postprocess, serialize, tokenize, get_config """ text_input = gr.Textbox() assert text_input.preprocess("Hello World!") == "Hello World!" assert text_input.postprocess("Hello World!") == "Hello World!" assert text_input.postprocess(None) is None assert text_input.postprocess("Ali") == "Ali" assert text_input.postprocess(2) == "2" assert text_input.postprocess(2.14) == "2.14" assert text_input.get_config() == { "lines": 1, "max_lines": 20, "placeholder": None, "value": "", "name": "textbox", "show_copy_button": False, "show_label": True, "type": "text", "label": None, "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "rtl": False, "text_align": None, "autofocus": False, "_selectable": False, "info": None, "autoscroll": True, } @pytest.mark.asyncio async def test_in_interface_as_input(self): """ Interface, process """ iface = gr.Interface(lambda x: x[::-1], "textbox", "textbox") assert iface("Hello") == "olleH" def test_in_interface_as_output(self): """ Interface, process """ iface = gr.Interface(lambda x: x[-1], "textbox", gr.Textbox()) assert iface("Hello") == "o" iface = gr.Interface(lambda x: x / 2, "number", gr.Textbox()) assert iface(10) == "5.0" def test_static(self): """ postprocess """ component = gr.Textbox("abc") assert component.get_config().get("value") == "abc" def test_override_template(self): """ override template """ component = gr.TextArea(value="abc") assert component.get_config().get("value") == "abc" assert component.get_config().get("lines") == 7 component = gr.TextArea(value="abc", lines=4) assert component.get_config().get("value") == "abc" assert component.get_config().get("lines") == 4 def test_faulty_type(self): with pytest.raises( ValueError, match='`type` must be one of "text", "password", or "email".' ): gr.Textbox(type="boo") def test_max_lines(self): assert gr.Textbox(type="password").get_config().get("max_lines") == 1 assert gr.Textbox(type="email").get_config().get("max_lines") == 1 assert gr.Textbox(type="text").get_config().get("max_lines") == 20 assert gr.Textbox().get_config().get("max_lines") == 20 class TestNumber: def test_component_functions(self): """ Preprocess, postprocess, serialize, get_config """ numeric_input = gr.Number(elem_id="num", elem_classes="first") assert numeric_input.preprocess(3) == 3.0 assert numeric_input.preprocess(None) is None assert numeric_input.postprocess(3) == 3 assert numeric_input.postprocess(3) == 3.0 assert numeric_input.postprocess(2.14) == 2.14 assert numeric_input.postprocess(None) is None assert numeric_input.get_config() == { "value": None, "name": "number", "show_label": True, "step": 1, "label": None, "minimum": None, "maximum": None, "container": True, "min_width": 160, "scale": None, "elem_id": "num", "elem_classes": ["first"], "visible": True, "interactive": None, "proxy_url": None, "info": None, "precision": None, "_selectable": False, } def test_component_functions_integer(self): """ Preprocess, postprocess, serialize, get_template_context """ numeric_input = gr.Number(precision=0, value=42) assert numeric_input.preprocess(3) == 3 assert numeric_input.preprocess(None) is None assert numeric_input.postprocess(3) == 3 assert numeric_input.postprocess(3) == 3 assert numeric_input.postprocess(2.85) == 3 assert numeric_input.postprocess(None) is None assert numeric_input.get_config() == { "value": 42, "name": "number", "show_label": True, "step": 1, "label": None, "minimum": None, "maximum": None, "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "info": None, "precision": 0, "_selectable": False, } def test_component_functions_precision(self): """ Preprocess, postprocess, serialize, get_template_context """ numeric_input = gr.Number(precision=2, value=42.3428) assert numeric_input.preprocess(3.231241) == 3.23 assert numeric_input.preprocess(None) is None assert numeric_input.postprocess(-42.1241) == -42.12 assert numeric_input.postprocess(5.6784) == 5.68 assert numeric_input.postprocess(2.1421) == 2.14 assert numeric_input.postprocess(None) is None def test_precision_none_with_integer(self): """ Preprocess, postprocess """ numeric_input = gr.Number(precision=None) assert numeric_input.preprocess(5) == 5 assert isinstance(numeric_input.preprocess(5), int) assert numeric_input.postprocess(5) == 5 assert isinstance(numeric_input.postprocess(5), int) def test_precision_none_with_float(self): """ Preprocess, postprocess """ numeric_input = gr.Number(value=5.5, precision=None) assert numeric_input.preprocess(5.5) == 5.5 assert isinstance(numeric_input.preprocess(5.5), float) assert numeric_input.postprocess(5.5) == 5.5 assert isinstance(numeric_input.postprocess(5.5), float) def test_in_interface_as_input(self): """ Interface, process """ iface = gr.Interface(lambda x: x**2, "number", "textbox") assert iface(2) == "4" def test_precision_0_in_interface(self): """ Interface, process """ iface = gr.Interface(lambda x: x**2, gr.Number(precision=0), "textbox") assert iface(2) == "4" def test_in_interface_as_output(self): """ Interface, process """ iface = gr.Interface(lambda x: int(x) ** 2, "textbox", "number") assert iface(2) == 4.0 def test_static(self): """ postprocess """ component = gr.Number() assert component.get_config().get("value") is None component = gr.Number(3) assert component.get_config().get("value") == 3.0 class TestSlider: def test_component_functions(self): """ Preprocess, postprocess, serialize, get_config """ slider_input = gr.Slider() assert slider_input.preprocess(3.0) == 3.0 assert slider_input.postprocess(3) == 3 assert slider_input.postprocess(3) == 3 assert slider_input.postprocess(None) == 0 slider_input = gr.Slider(10, 20, value=15, step=1, label="Slide Your Input") assert slider_input.get_config() == { "minimum": 10, "maximum": 20, "step": 1, "value": 15, "name": "slider", "show_label": True, "label": "Slide Your Input", "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "info": None, "_selectable": False, } def test_in_interface(self): """ " Interface, process """ iface = gr.Interface(lambda x: x**2, "slider", "textbox") assert iface(2) == "4" def test_static(self): """ postprocess """ component = gr.Slider(0, 100, 5) assert component.get_config().get("value") == 5 component = gr.Slider(0, 100, None) assert component.get_config().get("value") == 0 @patch("gradio.Slider.get_random_value", return_value=7) def test_slider_get_random_value_on_load(self, mock_get_random_value): slider = gr.Slider(minimum=-5, maximum=10, randomize=True) assert slider.value == 7 assert slider.load_event_to_attach[0]() == 7 assert slider.load_event_to_attach[1] is None @patch("random.randint", return_value=3) def test_slider_rounds_when_using_default_randomizer(self, mock_randint): slider = gr.Slider(minimum=0, maximum=1, randomize=True, step=0.1) # If get_random_value didn't round, this test would fail # because 0.30000000000000004 != 0.3 assert slider.get_random_value() == 0.3 mock_randint.assert_called() class TestCheckbox: def test_component_functions(self): """ Preprocess, postprocess, serialize, get_config """ bool_input = gr.Checkbox() assert bool_input.preprocess(True) assert bool_input.postprocess(True) assert bool_input.postprocess(True) bool_input = gr.Checkbox(value=True, label="Check Your Input") assert bool_input.get_config() == { "value": True, "name": "checkbox", "show_label": True, "label": "Check Your Input", "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "_selectable": False, "info": None, } def test_in_interface(self): """ Interface, process """ iface = gr.Interface(lambda x: 1 if x else 0, "checkbox", "number") assert iface(True) == 1 class TestCheckboxGroup: def test_component_functions(self): """ Preprocess, postprocess, serialize, get_config """ checkboxes_input = gr.CheckboxGroup(["a", "b", "c"]) assert checkboxes_input.preprocess(["a", "c"]) == ["a", "c"] assert checkboxes_input.postprocess(["a", "c"]) == ["a", "c"] checkboxes_input = gr.CheckboxGroup(["a", "b"], type="index") assert checkboxes_input.preprocess(["a"]) == [0] assert checkboxes_input.preprocess(["a", "b"]) == [0, 1] assert checkboxes_input.preprocess(["a", "b", "c"]) == [0, 1, None] # When a Gradio app is loaded with gr.load, the tuples are converted to lists, # so we need to test that case as well checkboxgroup = gr.CheckboxGroup(["a", "b", ["c", "c full"]]) # type: ignore assert checkboxgroup.choices == [("a", "a"), ("b", "b"), ("c", "c full")] checkboxes_input = gr.CheckboxGroup( value=["a", "c"], choices=["a", "b", "c"], label="Check Your Inputs", ) assert checkboxes_input.get_config() == { "choices": [("a", "a"), ("b", "b"), ("c", "c")], "value": ["a", "c"], "name": "checkboxgroup", "show_label": True, "label": "Check Your Inputs", "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "_selectable": False, "type": "value", "info": None, } with pytest.raises(ValueError): gr.CheckboxGroup(["a"], type="unknown") cbox = gr.CheckboxGroup(choices=["a", "b"], value="c") assert cbox.get_config()["value"] == ["c"] assert cbox.postprocess("a") == ["a"] with pytest.raises(ValueError): gr.CheckboxGroup().as_example("a") def test_in_interface(self): """ Interface, process """ checkboxes_input = gr.CheckboxGroup(["a", "b", "c"]) iface = gr.Interface(lambda x: "|".join(x), checkboxes_input, "textbox") assert iface(["a", "c"]) == "a|c" assert iface([]) == "" _ = gr.CheckboxGroup(["a", "b", "c"], type="index") class TestRadio: def test_component_functions(self): """ Preprocess, postprocess, serialize, get_config """ radio_input = gr.Radio(["a", "b", "c"]) assert radio_input.preprocess("c") == "c" assert radio_input.postprocess("a") == "a" radio_input = gr.Radio( choices=["a", "b", "c"], value="a", label="Pick Your One Input" ) assert radio_input.get_config() == { "choices": [("a", "a"), ("b", "b"), ("c", "c")], "value": "a", "name": "radio", "show_label": True, "label": "Pick Your One Input", "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "_selectable": False, "type": "value", "info": None, } radio = gr.Radio(choices=["a", "b"], type="index") assert radio.preprocess("a") == 0 assert radio.preprocess("b") == 1 assert radio.preprocess("c") is None # When a Gradio app is loaded with gr.load, the tuples are converted to lists, # so we need to test that case as well radio = gr.Radio(["a", "b", ["c", "c full"]]) # type: ignore assert radio.choices == [("a", "a"), ("b", "b"), ("c", "c full")] with pytest.raises(ValueError): gr.Radio(["a", "b"], type="unknown") def test_in_interface(self): """ Interface, process """ radio_input = gr.Radio(["a", "b", "c"]) iface = gr.Interface(lambda x: 2 * x, radio_input, "textbox") assert iface("c") == "cc" class TestDropdown: def test_component_functions(self): """ Preprocess, postprocess, serialize, get_config """ dropdown_input = gr.Dropdown(["a", "b", ("c", "c full")], multiselect=True) assert dropdown_input.preprocess("a") == "a" assert dropdown_input.postprocess("a") == ["a"] assert dropdown_input.preprocess("c full") == "c full" assert dropdown_input.postprocess("c full") == ["c full"] # When a Gradio app is loaded with gr.load, the tuples are converted to lists, # so we need to test that case as well dropdown_input = gr.Dropdown(["a", "b", ["c", "c full"]]) # type: ignore assert dropdown_input.choices == [("a", "a"), ("b", "b"), ("c", "c full")] dropdown = gr.Dropdown(choices=["a", "b"], type="index") assert dropdown.preprocess("a") == 0 assert dropdown.preprocess("b") == 1 assert dropdown.preprocess("c") is None dropdown = gr.Dropdown(choices=["a", "b"], type="index", multiselect=True) assert dropdown.preprocess(["a"]) == [0] assert dropdown.preprocess(["a", "b"]) == [0, 1] assert dropdown.preprocess(["a", "b", "c"]) == [0, 1, None] dropdown_input_multiselect = gr.Dropdown(["a", "b", ("c", "c full")]) assert dropdown_input_multiselect.preprocess(["a", "c full"]) == ["a", "c full"] assert dropdown_input_multiselect.postprocess(["a", "c full"]) == [ "a", "c full", ] dropdown_input_multiselect = gr.Dropdown( value=["a", "c"], choices=["a", "b", ("c", "c full")], label="Select Your Inputs", multiselect=True, max_choices=2, ) assert dropdown_input_multiselect.get_config() == { "allow_custom_value": False, "choices": [("a", "a"), ("b", "b"), ("c", "c full")], "value": ["a", "c"], "name": "dropdown", "show_label": True, "label": "Select Your Inputs", "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "multiselect": True, "filterable": True, "max_choices": 2, "_selectable": False, "type": "value", "info": None, } with pytest.raises(ValueError): gr.Dropdown(["a"], type="unknown") dropdown = gr.Dropdown(choices=["a", "b"], value="c") assert dropdown.get_config()["value"] == "c" assert dropdown.postprocess("a") == "a" def test_in_interface(self): """ Interface, process """ dropdown_input = gr.Dropdown(["a", "b", "c"]) iface = gr.Interface(lambda x: "|".join(x), dropdown_input, "textbox") assert iface(["a", "c"]) == "a|c" assert iface([]) == "" class TestImageEditor: def test_component_functions(self): test_image_path = "test/test_files/bus.png" image_data = FileData(path=test_image_path) image_editor_data = EditorData( background=image_data, layers=[image_data, image_data], composite=image_data ) payload = { "background": test_image_path, "layers": [test_image_path, test_image_path], "composite": test_image_path, } image_editor_component = gr.ImageEditor() assert isinstance(image_editor_component.preprocess(image_editor_data), dict) assert image_editor_component.postprocess(payload) == image_editor_data # Test that ImageEditor can accept just a filepath as well simpler_data = EditorData( background=image_data, layers=[], composite=image_data ) assert image_editor_component.postprocess(test_image_path) == simpler_data assert image_editor_component.get_config() == { "value": None, "height": None, "width": None, "image_mode": "RGBA", "sources": ("upload", "webcam", "clipboard"), "type": "numpy", "label": None, "show_label": True, "show_download_button": True, "container": True, "scale": None, "min_width": 160, "interactive": None, "visible": True, "elem_id": None, "elem_classes": [], "mirror_webcam": True, "show_share_button": False, "_selectable": False, "crop_size": None, "transforms": ("crop",), "eraser": {"default_size": "auto"}, "brush": { "default_size": "auto", "colors": [ "rgb(204, 50, 50)", "rgb(173, 204, 50)", "rgb(50, 204, 112)", "rgb(50, 112, 204)", "rgb(173, 50, 204)", ], "default_color": "auto", "color_mode": "defaults", }, "proxy_url": None, "name": "imageeditor", } class TestImage: def test_component_functions(self, gradio_temp_dir): """ Preprocess, postprocess, serialize, get_config, _segment_by_slic type: pil, file, filepath, numpy """ img = FileData(path="test/test_files/bus.png") image_input = gr.Image() image_input = gr.Image(type="filepath") image_temp_filepath = image_input.preprocess(img) assert image_temp_filepath in [ str(f) for f in gradio_temp_dir.glob("**/*") if f.is_file() ] image_input = gr.Image(type="pil", label="Upload Your Image") assert image_input.get_config() == { "image_mode": "RGB", "sources": ["upload", "webcam", "clipboard"], "name": "image", "show_share_button": False, "show_download_button": True, "streaming": False, "show_label": True, "label": "Upload Your Image", "container": True, "min_width": 160, "scale": None, "height": None, "width": None, "elem_id": None, "elem_classes": [], "visible": True, "value": None, "interactive": None, "proxy_url": None, "mirror_webcam": True, "_selectable": False, "streamable": False, "type": "pil", } assert image_input.preprocess(None) is None image_input = gr.Image() assert image_input.preprocess(img) is not None image_input.preprocess(img) file_image = gr.Image(type="filepath") assert isinstance(file_image.preprocess(img), str) with pytest.raises(ValueError): gr.Image(type="unknown") string_source = gr.Image(sources="upload") assert string_source.sources == ["upload"] # Output functionalities image_output = gr.Image(type="pil") processed_image = image_output.postprocess( PIL.Image.open(img.path) ).model_dump() assert processed_image is not None if processed_image is not None: processed = PIL.Image.open(cast(dict, processed_image).get("path", "")) source = PIL.Image.open(img.path) assert processed.size == source.size def test_in_interface_as_output(self): """ Interface, process """ def generate_noise(height, width): return np.random.randint(0, 256, (height, width, 3)) iface = gr.Interface(generate_noise, ["slider", "slider"], "image") assert iface(10, 20).endswith(".png") def test_static(self): """ postprocess """ component = gr.Image("test/test_files/bus.png") value = component.get_config().get("value") base64 = client_utils.encode_file_to_base64(value["path"]) assert base64 == media_data.BASE64_IMAGE component = gr.Image(None) assert component.get_config().get("value") is None def test_images_upright_after_preprocess(self): component = gr.Image(type="pil") file_path = "test/test_files/rotated_image.jpeg" im = PIL.Image.open(file_path) assert im.getexif().get(274) != 1 image = component.preprocess(FileData(path=file_path)) assert image == PIL.ImageOps.exif_transpose(im) class TestPlot: @pytest.mark.asyncio async def test_in_interface_as_output(self): """ Interface, process """ def plot(num): import matplotlib.pyplot as plt fig = plt.figure() plt.plot(range(num), range(num)) return fig iface = gr.Interface(plot, "slider", "plot") with utils.MatplotlibBackendMananger(): output = await iface.process_api(fn_index=0, inputs=[10], state={}) assert output["data"][0]["type"] == "matplotlib" assert output["data"][0]["plot"].startswith("data:image/png;base64") def test_static(self): """ postprocess """ with utils.MatplotlibBackendMananger(): import matplotlib.pyplot as plt fig = plt.figure() plt.plot([1, 2, 3], [1, 2, 3]) component = gr.Plot(fig) assert component.get_config().get("value") is not None component = gr.Plot(None) assert component.get_config().get("value") is None def test_postprocess_altair(self): import altair as alt from vega_datasets import data cars = data.cars() chart = ( alt.Chart(cars) .mark_point() .encode( x="Horsepower", y="Miles_per_Gallon", color="Origin", ) ) out = gr.Plot().postprocess(chart).model_dump() assert isinstance(out["plot"], str) assert out["plot"] == chart.to_json() class TestAudio: 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 output1[0] == 8000 assert output1[1].shape == (8046,) x_wav = processing_utils.move_files_to_cache([x_wav], audio_input)[0] audio_input = gr.Audio(type="filepath") output1 = audio_input.preprocess(x_wav) 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": True, "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": "wav", "streamable": False, "max_length": None, "min_length": None, "waveform_options": None, "_selectable": 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") # Confirm Audio can be instantiated with a numpy array gr.Audio((100, np.random.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"] ) assert audio_output.get_config() == { "autoplay": False, "name": "audio", "show_download_button": True, "show_share_button": False, "streaming": False, "show_label": True, "label": None, "max_length": None, "min_length": None, "container": True, "editable": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "value": None, "interactive": None, "proxy_url": None, "type": "filepath", "format": "wav", "streamable": False, "sources": ["upload", "microphone"], "waveform_options": None, "_selectable": False, } output1 = audio_output.postprocess(y_audio.name).model_dump() output2 = audio_output.postprocess(Path(y_audio.name)).model_dump() 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_audio_preprocess_can_be_read_by_scipy(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") output = audio_input.preprocess(x_wav) wavfile.read(output) 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 output.endswith("mp3") output = audio_input.postprocess( (48000, np.random.randint(-256, 256, (5, 3)).astype(np.int16)) ).model_dump() assert output["path"].endswith("mp3") class TestFile: def test_component_functions(self): """ Preprocess, serialize, get_config, value """ x_file = FileData(path=media_data.BASE64_FILE["path"]) file_input = gr.File() output = file_input.preprocess(x_file) assert isinstance(output, str) input1 = file_input.preprocess(x_file) input2 = file_input.preprocess(x_file) assert input1 == input1.name # Testing backwards compatibility assert input1 == input2 assert Path(input1).name == "sample_file.pdf" file_input = gr.File(label="Upload Your File") assert file_input.get_config() == { "file_count": "single", "file_types": None, "name": "file", "show_label": True, "label": "Upload Your File", "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "value": None, "interactive": None, "proxy_url": None, "_selectable": False, "height": None, "type": "filepath", } assert file_input.preprocess(None) is None assert file_input.preprocess(x_file) is not None zero_size_file = FileData(path="document.txt", size=0) temp_file = file_input.preprocess(zero_size_file) assert not Path(temp_file.name).exists() file_input = gr.File(type="binary") output = file_input.preprocess(x_file) assert isinstance(output, bytes) output1 = file_input.postprocess("test/test_files/sample_file.pdf") output2 = file_input.postprocess("test/test_files/sample_file.pdf") assert output1 == output2 def test_preprocess_with_multiple_files(self): file_data = FileData(path=media_data.BASE64_FILE["path"]) list_file_data = ListFiles(root=[file_data, file_data]) file_input = gr.File(file_count="directory") output = file_input.preprocess(list_file_data) assert isinstance(output, list) assert isinstance(output[0], str) def test_file_type_must_be_list(self): with pytest.raises( ValueError, match="Parameter file_types must be a list. Received str" ): gr.File(file_types=".json") def test_in_interface_as_input(self): """ Interface, process """ x_file = media_data.BASE64_FILE["path"] def get_size_of_file(file_obj): return os.path.getsize(file_obj.name) iface = gr.Interface(get_size_of_file, "file", "number") assert iface(x_file) == 10558 def test_as_component_as_output(self): """ Interface, process """ def write_file(content): with open("test.txt", "w") as f: f.write(content) return "test.txt" iface = gr.Interface(write_file, "text", "file") assert iface("hello world").endswith(".txt") class TestUploadButton: def test_component_functions(self): """ preprocess """ x_file = FileData(path=media_data.BASE64_FILE["path"]) upload_input = gr.UploadButton() input = upload_input.preprocess(x_file) assert isinstance(input, str) input1 = upload_input.preprocess(x_file) input2 = upload_input.preprocess(x_file) assert input1 == input1.name # Testing backwards compatibility assert input1 == input2 def test_raises_if_file_types_is_not_list(self): with pytest.raises( ValueError, match="Parameter file_types must be a list. Received int" ): gr.UploadButton(file_types=2) def test_preprocess_with_multiple_files(self): file_data = FileData(path=media_data.BASE64_FILE["path"]) list_file_data = ListFiles(root=[file_data, file_data]) upload_input = gr.UploadButton(file_count="directory") output = upload_input.preprocess(list_file_data) assert isinstance(output, list) assert isinstance(output[0], str) class TestDataframe: def test_component_functions(self): """ Preprocess, serialize, get_config """ x_data = { "data": [["Tim", 12, False], ["Jan", 24, True]], "headers": ["Name", "Age", "Member"], "metadata": None, } dataframe_input = gr.Dataframe(headers=["Name", "Age", "Member"]) output = dataframe_input.preprocess(DataframeData(**x_data)) assert output["Age"][1] == 24 assert not output["Member"][0] assert dataframe_input.postprocess(x_data) == x_data dataframe_input = gr.Dataframe( headers=["Name", "Age", "Member"], label="Dataframe Input" ) assert dataframe_input.get_config() == { "value": { "headers": ["Name", "Age", "Member"], "data": [["", "", ""]], "metadata": None, }, "_selectable": False, "headers": ["Name", "Age", "Member"], "row_count": (1, "dynamic"), "col_count": (3, "dynamic"), "datatype": ["str", "str", "str"], "type": "pandas", "label": "Dataframe Input", "show_label": True, "scale": None, "min_width": 160, "interactive": None, "visible": True, "elem_id": None, "elem_classes": [], "wrap": False, "proxy_url": None, "name": "dataframe", "height": 500, "latex_delimiters": [{"display": True, "left": "$$", "right": "$$"}], "line_breaks": True, "column_widths": [], } dataframe_input = gr.Dataframe() output = dataframe_input.preprocess(DataframeData(**x_data)) assert output["Age"][1] == 24 x_data = { "data": [["Tim", 12, False], ["Jan", 24, True]], "headers": ["Name", "Age", "Member"], "metadata": {"display_value": None, "styling": None}, } dataframe_input.preprocess(DataframeData(**x_data)) with pytest.raises(ValueError): gr.Dataframe(type="unknown") dataframe_output = gr.Dataframe() assert dataframe_output.get_config() == { "value": { "headers": ["1", "2", "3"], "data": [["", "", ""]], "metadata": None, }, "_selectable": False, "headers": ["1", "2", "3"], "row_count": (1, "dynamic"), "col_count": (3, "dynamic"), "datatype": ["str", "str", "str"], "type": "pandas", "label": None, "show_label": True, "scale": None, "min_width": 160, "interactive": None, "visible": True, "elem_id": None, "elem_classes": [], "wrap": False, "proxy_url": None, "name": "dataframe", "height": 500, "latex_delimiters": [{"display": True, "left": "$$", "right": "$$"}], "line_breaks": True, "column_widths": [], } dataframe_input = gr.Dataframe(column_widths=["100px", 200, "50%"]) assert dataframe_input.get_config()["column_widths"] == [ "100px", "200px", "50%", ] def test_postprocess(self): """ postprocess """ dataframe_output = gr.Dataframe() output = dataframe_output.postprocess([]).model_dump() assert output == {"data": [[]], "headers": [], "metadata": None} output = dataframe_output.postprocess(np.zeros((2, 2))).model_dump() assert output == { "data": [[0, 0], [0, 0]], "headers": ["1", "2"], "metadata": None, } output = dataframe_output.postprocess([[1, 3, 5]]).model_dump() assert output == { "data": [[1, 3, 5]], "headers": ["1", "2", "3"], "metadata": None, } output = dataframe_output.postprocess( pd.DataFrame([[2, True], [3, True], [4, False]], columns=["num", "prime"]) ).model_dump() assert output == { "headers": ["num", "prime"], "data": [[2, True], [3, True], [4, False]], "metadata": None, } with pytest.raises(ValueError): gr.Dataframe(type="unknown") # When the headers don't match the data dataframe_output = gr.Dataframe(headers=["one", "two", "three"]) output = dataframe_output.postprocess([[2, True], [3, True]]).model_dump() assert output == { "headers": ["one", "two"], "data": [[2, True], [3, True]], "metadata": None, } dataframe_output = gr.Dataframe(headers=["one", "two", "three"]) output = dataframe_output.postprocess( [[2, True, "ab", 4], [3, True, "cd", 5]] ).model_dump() assert output == { "headers": ["one", "two", "three", "4"], "data": [[2, True, "ab", 4], [3, True, "cd", 5]], "metadata": None, } def test_dataframe_postprocess_all_types(self): df = pd.DataFrame( { "date_1": pd.date_range("2021-01-01", periods=2), "date_2": pd.date_range("2022-02-15", periods=2).strftime( "%B %d, %Y, %r" ), "number": np.array([0.2233, 0.57281]), "number_2": np.array([84, 23]).astype(np.int64), "bool": [True, False], "markdown": ["# Hello", "# Goodbye"], } ) component = gr.Dataframe( datatype=["date", "date", "number", "number", "bool", "markdown"] ) output = component.postprocess(df).model_dump() assert output == { "headers": list(df.columns), "data": [ [ pd.Timestamp("2021-01-01 00:00:00"), "February 15, 2022, 12:00:00 AM", 0.2233, 84, True, "# Hello", ], [ pd.Timestamp("2021-01-02 00:00:00"), "February 16, 2022, 12:00:00 AM", 0.57281, 23, False, "# Goodbye", ], ], "metadata": None, } def test_dataframe_postprocess_only_dates(self): df = pd.DataFrame( { "date_1": pd.date_range("2021-01-01", periods=2), "date_2": pd.date_range("2022-02-15", periods=2), } ) component = gr.Dataframe(datatype=["date", "date"]) output = component.postprocess(df).model_dump() assert output == { "headers": list(df.columns), "data": [ [ pd.Timestamp("2021-01-01 00:00:00"), pd.Timestamp("2022-02-15 00:00:00"), ], [ pd.Timestamp("2021-01-02 00:00:00"), pd.Timestamp("2022-02-16 00:00:00"), ], ], "metadata": None, } def test_dataframe_postprocess_styler(self): component = gr.Dataframe() df = pd.DataFrame( { "name": ["Adam", "Mike"] * 4, "gpa": [1.1, 1.12] * 4, "sat": [800, 800] * 4, } ) s = df.style.format(precision=1, decimal=",") output = component.postprocess(s).model_dump() assert output == { "data": [ ["Adam", 1.1, 800], ["Mike", 1.12, 800], ["Adam", 1.1, 800], ["Mike", 1.12, 800], ["Adam", 1.1, 800], ["Mike", 1.12, 800], ["Adam", 1.1, 800], ["Mike", 1.12, 800], ], "headers": ["name", "gpa", "sat"], "metadata": { "display_value": [ ["Adam", "1,1", "800"], ["Mike", "1,1", "800"], ["Adam", "1,1", "800"], ["Mike", "1,1", "800"], ["Adam", "1,1", "800"], ["Mike", "1,1", "800"], ["Adam", "1,1", "800"], ["Mike", "1,1", "800"], ], "styling": [ ["", "", ""], ["", "", ""], ["", "", ""], ["", "", ""], ["", "", ""], ["", "", ""], ["", "", ""], ["", "", ""], ], }, } df = pd.DataFrame( { "A": [14, 4, 5, 4, 1], "B": [5, 2, 54, 3, 2], "C": [20, 20, 7, 3, 8], "D": [14, 3, 6, 2, 6], "E": [23, 45, 64, 32, 23], } ) t = df.style.highlight_max(color="lightgreen", axis=0) output = component.postprocess(t).model_dump() assert output == { "data": [ [14, 5, 20, 14, 23], [4, 2, 20, 3, 45], [5, 54, 7, 6, 64], [4, 3, 3, 2, 32], [1, 2, 8, 6, 23], ], "headers": ["A", "B", "C", "D", "E"], "metadata": { "display_value": [ ["14", "5", "20", "14", "23"], ["4", "2", "20", "3", "45"], ["5", "54", "7", "6", "64"], ["4", "3", "3", "2", "32"], ["1", "2", "8", "6", "23"], ], "styling": [ [ "background-color: lightgreen", "", "background-color: lightgreen", "background-color: lightgreen", "", ], ["", "", "background-color: lightgreen", "", ""], [ "", "background-color: lightgreen", "", "", "background-color: lightgreen", ], ["", "", "", "", ""], ["", "", "", "", ""], ], }, } class TestDataset: def test_preprocessing(self): test_file_dir = Path(__file__).parent / "test_files" bus = str(Path(test_file_dir, "bus.png").resolve()) dataset = gr.Dataset( components=["number", "textbox", "image", "html", "markdown"], samples=[ [5, "hello", bus, "Bold", "**Bold**"], [15, "hi", bus, "Italics", "*Italics*"], ], ) row = dataset.preprocess(1) assert row[0] == 15 assert row[1] == "hi" assert row[2].endswith("bus.png") assert row[3] == "Italics" assert row[4] == "*Italics*" dataset = gr.Dataset( components=["number", "textbox", "image", "html", "markdown"], samples=[ [5, "hello", bus, "Bold", "**Bold**"], [15, "hi", bus, "Italics", "*Italics*"], ], type="index", ) assert dataset.preprocess(1) == 1 radio = gr.Radio(choices=[("name 1", "value 1"), ("name 2", "value 2")]) dataset = gr.Dataset(samples=[["value 1"], ["value 2"]], components=[radio]) assert dataset.samples == [["name 1"], ["name 2"]] def test_postprocessing(self): test_file_dir = Path(Path(__file__).parent, "test_files") bus = Path(test_file_dir, "bus.png") dataset = gr.Dataset( components=["number", "textbox", "image", "html", "markdown"], type="index" ) output = dataset.postprocess( samples=[ [5, "hello", bus, "Bold", "**Bold**"], [15, "hi", bus, "Italics", "*Italics*"], ], ) assert output == { "samples": [ [5, "hello", bus, "Bold", "**Bold**"], [15, "hi", bus, "Italics", "*Italics*"], ], "__type__": "update", } class TestVideo: def test_component_functions(self): """ Preprocess, serialize, deserialize, get_config """ x_video = VideoData( video=FileData(path=deepcopy(media_data.BASE64_VIDEO)["path"]) ) video_input = gr.Video() x_video = processing_utils.move_files_to_cache([x_video], video_input)[0] output1 = video_input.preprocess(x_video) assert isinstance(output1, str) output2 = video_input.preprocess(x_video) assert output1 == output2 video_input = gr.Video(include_audio=False) output1 = video_input.preprocess(x_video) output2 = video_input.preprocess(x_video) assert output1 == output2 video_input = gr.Video(label="Upload Your Video") assert video_input.get_config() == { "autoplay": False, "sources": ["webcam", "upload"], "name": "video", "show_share_button": False, "show_label": True, "label": "Upload Your Video", "container": True, "min_width": 160, "scale": None, "height": None, "width": None, "elem_id": None, "elem_classes": [], "visible": True, "value": None, "interactive": None, "proxy_url": None, "mirror_webcam": True, "include_audio": True, "format": None, "min_length": None, "max_length": None, "_selectable": False, } assert video_input.preprocess(None) is None video_input = gr.Video(format="avi") output_video = video_input.preprocess(x_video) assert output_video[-3:] == "avi" assert "flip" not in output_video # Output functionalities y_vid_path = "test/test_files/video_sample.mp4" subtitles_path = "test/test_files/s1.srt" video_output = gr.Video() output1 = video_output.postprocess(y_vid_path).model_dump()["video"]["path"] assert output1.endswith("mp4") output2 = video_output.postprocess(y_vid_path).model_dump()["video"]["path"] assert output1 == output2 assert ( video_output.postprocess(y_vid_path).model_dump()["video"]["orig_name"] == "video_sample.mp4" ) output_with_subtitles = video_output.postprocess( (y_vid_path, subtitles_path) ).model_dump() assert output_with_subtitles["subtitles"]["path"].endswith(".vtt") p_video = gr.Video() video_with_subtitle = gr.Video() postprocessed_video = p_video.postprocess(Path(y_vid_path)).model_dump() postprocessed_video_with_subtitle = video_with_subtitle.postprocess( (Path(y_vid_path), Path(subtitles_path)) ).model_dump() processed_video = { "video": { "path": "video_sample.mp4", "orig_name": "video_sample.mp4", "mime_type": None, "size": None, "url": None, }, "subtitles": None, } processed_video_with_subtitle = { "video": { "path": "video_sample.mp4", "orig_name": "video_sample.mp4", "mime_type": None, "size": None, "url": None, }, "subtitles": { "path": "s1.srt", "mime_type": None, "orig_name": None, "size": None, "url": None, }, } postprocessed_video["video"]["path"] = os.path.basename( postprocessed_video["video"]["path"] ) assert processed_video == postprocessed_video postprocessed_video_with_subtitle["video"]["path"] = os.path.basename( postprocessed_video_with_subtitle["video"]["path"] ) if postprocessed_video_with_subtitle["subtitles"]["path"]: postprocessed_video_with_subtitle["subtitles"]["path"] = "s1.srt" assert processed_video_with_subtitle == postprocessed_video_with_subtitle def test_in_interface(self): """ Interface, process """ x_video = media_data.BASE64_VIDEO["path"] iface = gr.Interface(lambda x: x, "video", "playable_video") assert iface({"video": x_video})["video"].endswith(".mp4") def test_with_waveform(self): """ Interface, process """ x_audio = media_data.BASE64_AUDIO["path"] iface = gr.Interface(lambda x: gr.make_waveform(x), "audio", "video") assert iface(x_audio)["video"].endswith(".mp4") def test_video_postprocess_converts_to_playable_format(self): test_file_dir = Path(Path(__file__).parent, "test_files") # This file has a playable container but not playable codec with tempfile.NamedTemporaryFile( suffix="bad_video.mp4", delete=False ) as tmp_not_playable_vid: bad_vid = str(test_file_dir / "bad_video_sample.mp4") assert not processing_utils.video_is_playable(bad_vid) shutil.copy(bad_vid, tmp_not_playable_vid.name) output = gr.Video().postprocess(tmp_not_playable_vid.name).model_dump() assert processing_utils.video_is_playable(output["video"]["path"]) # This file has a playable codec but not a playable container with tempfile.NamedTemporaryFile( suffix="playable_but_bad_container.mkv", delete=False ) as tmp_not_playable_vid: bad_vid = str(test_file_dir / "playable_but_bad_container.mkv") assert not processing_utils.video_is_playable(bad_vid) shutil.copy(bad_vid, tmp_not_playable_vid.name) output = gr.Video().postprocess(tmp_not_playable_vid.name).model_dump() assert processing_utils.video_is_playable(output["video"]["path"]) @patch("pathlib.Path.exists", MagicMock(return_value=False)) @patch("gradio.components.video.FFmpeg") def test_video_preprocessing_flips_video_for_webcam(self, mock_ffmpeg): # Ensures that the cached temp video file is not used so that ffmpeg is called for each test x_video = VideoData(video=FileData(path=media_data.BASE64_VIDEO["path"])) video_input = gr.Video(sources=["webcam"]) _ = video_input.preprocess(x_video) # Dict mapping filename to FFmpeg options output_params = mock_ffmpeg.call_args_list[0][1]["outputs"] assert "hflip" in list(output_params.values())[0] assert "flip" in list(output_params.keys())[0] mock_ffmpeg.reset_mock() _ = gr.Video( sources=["webcam"], mirror_webcam=False, include_audio=True ).preprocess(x_video) mock_ffmpeg.assert_not_called() mock_ffmpeg.reset_mock() _ = gr.Video(sources=["upload"], format="mp4", include_audio=True).preprocess( x_video ) mock_ffmpeg.assert_not_called() mock_ffmpeg.reset_mock() output_file = gr.Video( sources=["webcam"], mirror_webcam=True, format="avi" ).preprocess(x_video) output_params = mock_ffmpeg.call_args_list[0][1]["outputs"] assert "hflip" in list(output_params.values())[0] assert "flip" in list(output_params.keys())[0] assert ".avi" in list(output_params.keys())[0] assert ".avi" in output_file mock_ffmpeg.reset_mock() output_file = gr.Video( sources=["webcam"], mirror_webcam=False, format="avi", include_audio=False ).preprocess(x_video) output_params = mock_ffmpeg.call_args_list[0][1]["outputs"] assert list(output_params.values())[0] == ["-an"] assert "flip" not in Path(list(output_params.keys())[0]).name assert ".avi" in list(output_params.keys())[0] assert ".avi" in output_file class TestNames: # This test ensures that `components.get_component_instance()` works correctly when instantiating from components def test_no_duplicate_uncased_names(self, io_components): unique_subclasses_uncased = {s.__name__.lower() for s in io_components} assert len(io_components) == len(unique_subclasses_uncased) class TestLabel: def test_component_functions(self): """ Process, postprocess, deserialize """ y = "happy" label_output = gr.Label() label = label_output.postprocess(y).model_dump() assert label == {"label": "happy", "confidences": None} y = {3: 0.7, 1: 0.2, 0: 0.1} label = label_output.postprocess(y).model_dump() assert label == { "label": 3, "confidences": [ {"label": 3, "confidence": 0.7}, {"label": 1, "confidence": 0.2}, {"label": 0, "confidence": 0.1}, ], } label_output = gr.Label(num_top_classes=2) label = label_output.postprocess(y).model_dump() assert label == { "label": 3, "confidences": [ {"label": 3, "confidence": 0.7}, {"label": 1, "confidence": 0.2}, ], } with pytest.raises(ValueError): label_output.postprocess([1, 2, 3]).model_dump() test_file_dir = Path(Path(__file__).parent, "test_files") path = str(Path(test_file_dir, "test_label_json.json")) label_dict = label_output.postprocess(path).model_dump() assert label_dict["label"] == "web site" assert label_output.get_config() == { "name": "label", "show_label": True, "num_top_classes": 2, "value": {}, "label": None, "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "proxy_url": None, "color": None, "_selectable": False, } def test_color_argument(self): label = gr.Label(value=-10, color="red") assert label.get_config()["color"] == "red" def test_in_interface(self): """ Interface, process """ x_img = "test/test_files/bus.png" def rgb_distribution(img): rgb_dist = np.mean(img, axis=(0, 1)) rgb_dist /= np.sum(rgb_dist) rgb_dist = np.round(rgb_dist, decimals=2) return { "red": rgb_dist[0], "green": rgb_dist[1], "blue": rgb_dist[2], } iface = gr.Interface(rgb_distribution, "image", "label") output = iface(x_img) assert output == { "label": "red", "confidences": [ {"label": "red", "confidence": 0.44}, {"label": "green", "confidence": 0.28}, {"label": "blue", "confidence": 0.28}, ], } class TestHighlightedText: def test_postprocess(self): """ postprocess """ component = gr.HighlightedText() value = [ ("", None), ("Wolfgang", "PER"), (" lives in ", None), ("Berlin", "LOC"), ("", None), ] result = [ {"token": "", "class_or_confidence": None}, {"token": "Wolfgang", "class_or_confidence": "PER"}, {"token": " lives in ", "class_or_confidence": None}, {"token": "Berlin", "class_or_confidence": "LOC"}, {"token": "", "class_or_confidence": None}, ] result_ = component.postprocess(value).model_dump() assert result == result_ text = "Wolfgang lives in Berlin" entities = [ {"entity": "PER", "start": 0, "end": 8}, {"entity": "LOC", "start": 18, "end": 24}, ] result_ = component.postprocess( {"text": text, "entities": entities} ).model_dump() assert result == result_ text = "Wolfgang lives in Berlin" entities = [ {"entity_group": "PER", "start": 0, "end": 8}, {"entity": "LOC", "start": 18, "end": 24}, ] result_ = component.postprocess( {"text": text, "entities": entities} ).model_dump() assert result == result_ # Test split entity is merged when combine adjacent is set text = "Wolfgang lives in Berlin" entities = [ {"entity": "PER", "start": 0, "end": 4}, {"entity": "PER", "start": 4, "end": 8}, {"entity": "LOC", "start": 18, "end": 24}, ] # After a merge empty entries are stripped except the leading one result_after_merge = [ {"token": "", "class_or_confidence": None}, {"token": "Wolfgang", "class_or_confidence": "PER"}, {"token": " lives in ", "class_or_confidence": None}, {"token": "Berlin", "class_or_confidence": "LOC"}, ] result_ = component.postprocess( {"text": text, "entities": entities} ).model_dump() assert result != result_ assert result_after_merge != result_ component = gr.HighlightedText(combine_adjacent=True) result_ = component.postprocess( {"text": text, "entities": entities} ).model_dump() assert result_after_merge == result_ component = gr.HighlightedText() text = "Wolfgang lives in Berlin" entities = [ {"entity": "LOC", "start": 18, "end": 24}, {"entity": "PER", "start": 0, "end": 8}, ] result_ = component.postprocess( {"text": text, "entities": entities} ).model_dump() assert result == result_ text = "I live there" entities = [] result_ = component.postprocess( {"text": text, "entities": entities} ).model_dump() assert [{"token": text, "class_or_confidence": None}] == result_ text = "Wolfgang" entities = [ {"entity": "PER", "start": 0, "end": 8}, ] result_ = component.postprocess( {"text": text, "entities": entities} ).model_dump() assert [ {"token": "", "class_or_confidence": None}, {"token": text, "class_or_confidence": "PER"}, {"token": "", "class_or_confidence": None}, ] == result_ def test_component_functions(self): """ get_config """ ht_output = gr.HighlightedText(color_map={"pos": "green", "neg": "red"}) assert ht_output.get_config() == { "color_map": {"pos": "green", "neg": "red"}, "name": "highlightedtext", "show_label": True, "label": None, "show_legend": False, "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "value": None, "proxy_url": None, "_selectable": False, "combine_adjacent": False, "adjacent_separator": "", "interactive": None, } def test_in_interface(self): """ Interface, process """ def highlight_vowels(sentence): phrases, cur_phrase = [], "" vowels, mode = "aeiou", None for letter in sentence: letter_mode = "vowel" if letter in vowels else "non" if mode is None: mode = letter_mode elif mode != letter_mode: phrases.append((cur_phrase, mode)) cur_phrase = "" mode = letter_mode cur_phrase += letter phrases.append((cur_phrase, mode)) return phrases iface = gr.Interface(highlight_vowels, "text", "highlight") output = iface("Helloooo") assert output == [ {"token": "H", "class_or_confidence": "non"}, {"token": "e", "class_or_confidence": "vowel"}, {"token": "ll", "class_or_confidence": "non"}, {"token": "oooo", "class_or_confidence": "vowel"}, ] class TestAnnotatedImage: def test_postprocess(self): """ postprocess """ component = gr.AnnotatedImage() img = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8) mask1 = [40, 40, 50, 50] mask2 = np.zeros((100, 100), dtype=np.uint8) mask2[10:20, 10:20] = 1 input = (img, [(mask1, "mask1"), (mask2, "mask2")]) result = component.postprocess(input).model_dump() base_img_out = PIL.Image.open(result["image"]["path"]) assert result["annotations"][0]["label"] == "mask1" mask1_img_out = PIL.Image.open(result["annotations"][0]["image"]["path"]) assert mask1_img_out.size == base_img_out.size mask1_array_out = np.array(mask1_img_out) assert np.max(mask1_array_out[40:50, 40:50]) == 255 assert np.max(mask1_array_out[50:60, 50:60]) == 0 def test_component_functions(self): ht_output = gr.AnnotatedImage(label="sections", show_legend=False) assert ht_output.get_config() == { "name": "annotatedimage", "show_label": True, "label": "sections", "show_legend": False, "container": True, "min_width": 160, "scale": None, "color_map": None, "height": None, "width": None, "elem_id": None, "elem_classes": [], "visible": True, "value": None, "proxy_url": None, "_selectable": False, } def test_in_interface(self): def mask(img): top_left_corner = [0, 0, 20, 20] random_mask = np.random.randint(0, 2, img.shape[:2]) return (img, [(top_left_corner, "left corner"), (random_mask, "random")]) iface = gr.Interface(mask, "image", gr.AnnotatedImage()) output = iface("test/test_files/bus.png") output_img, (mask1, _) = output["image"], output["annotations"] input_img = PIL.Image.open("test/test_files/bus.png") output_img = PIL.Image.open(output_img) mask1_img = PIL.Image.open(mask1["image"]) assert output_img.size == input_img.size assert mask1_img.size == input_img.size class TestChatbot: def test_component_functions(self): """ Postprocess, get_config """ chatbot = gr.Chatbot() assert chatbot.postprocess( [["You are **cool**\nand fun", "so are *you*"]] ).model_dump() == [("You are **cool**\nand fun", "so are *you*")] multimodal_msg = [ [("test/test_files/video_sample.mp4",), "cool video"], [("test/test_files/audio_sample.wav",), "cool audio"], [("test/test_files/bus.png", "A bus"), "cool pic"], [(Path("test/test_files/video_sample.mp4"),), "cool video"], [(Path("test/test_files/audio_sample.wav"),), "cool audio"], [(Path("test/test_files/bus.png"), "A bus"), "cool pic"], ] postprocessed_multimodal_msg = chatbot.postprocess(multimodal_msg).model_dump() for msg in postprocessed_multimodal_msg: assert "file" in msg[0] assert msg[1] in {"cool video", "cool audio", "cool pic"} assert msg[0]["file"]["path"].split(".")[-1] in {"mp4", "wav", "png"} if msg[0]["alt_text"]: assert msg[0]["alt_text"] == "A bus" assert chatbot.get_config() == { "value": [], "label": None, "show_label": True, "name": "chatbot", "show_share_button": False, "visible": True, "elem_id": None, "elem_classes": [], "container": True, "min_width": 160, "scale": None, "height": None, "proxy_url": None, "_selectable": False, "latex_delimiters": [{"display": True, "left": "$$", "right": "$$"}], "likeable": False, "rtl": False, "show_copy_button": False, "avatar_images": [None, None], "sanitize_html": True, "render_markdown": True, "bubble_full_width": True, "line_breaks": True, "layout": None, } def test_avatar_images_are_moved_to_cache(self): chatbot = gr.Chatbot(avatar_images=("test/test_files/bus.png", None)) assert chatbot.avatar_images[0] assert utils.is_in_or_equal(chatbot.avatar_images[0], chatbot.GRADIO_CACHE) assert chatbot.avatar_images[1] is None class TestJSON: def test_component_functions(self): """ Postprocess """ js_output = gr.JSON() assert js_output.postprocess('{"a":1, "b": 2}'), '"{\\"a\\":1, \\"b\\": 2}"' assert js_output.get_config() == { "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "value": None, "show_label": True, "label": None, "name": "json", "proxy_url": None, "_selectable": False, } def test_chatbot_selectable_in_config(self): with gr.Blocks() as demo: cb = gr.Chatbot(label="Chatbot") cb.like(lambda: print("foo")) gr.Chatbot(label="Chatbot2") assertion_count = 0 for component in demo.config["components"]: if component["props"]["label"] == "Chatbot": assertion_count += 1 assert component["props"]["likeable"] elif component["props"]["label"] == "Chatbot2": assertion_count += 1 assert not component["props"]["likeable"] assert assertion_count == 2 @pytest.mark.asyncio async def test_in_interface(self): """ Interface, process """ def get_avg_age_per_gender(data): return { "M": int(data[data["gender"] == "M"]["age"].mean()), "F": int(data[data["gender"] == "F"]["age"].mean()), "O": int(data[data["gender"] == "O"]["age"].mean()), } iface = gr.Interface( get_avg_age_per_gender, gr.Dataframe(headers=["gender", "age"]), "json", ) y_data = [ ["M", 30], ["F", 20], ["M", 40], ["O", 20], ["F", 30], ] assert ( await iface.process_api( 0, [{"data": y_data, "headers": ["gender", "age"]}], state={} ) )["data"][0] == { "M": 35, "F": 25, "O": 20, } class TestHTML: def test_component_functions(self): """ get_config """ html_component = gr.components.HTML("#Welcome onboard", label="HTML Input") assert html_component.get_config() == { "value": "#Welcome onboard", "label": "HTML Input", "show_label": True, "visible": True, "elem_id": None, "elem_classes": [], "proxy_url": None, "name": "html", "_selectable": False, } def test_in_interface(self): """ Interface, process """ def bold_text(text): return f"{text}" iface = gr.Interface(bold_text, "text", "html") assert iface("test") == "test" class TestMarkdown: def test_component_functions(self): markdown_component = gr.Markdown("# Let's learn about $x$", label="Markdown") assert markdown_component.get_config()["value"] == "# Let's learn about $x$" def test_in_interface(self): """ Interface, process """ iface = gr.Interface(lambda x: x, "text", "markdown") input_data = " Here's an [image](https://gradio.app/images/gradio_logo.png)" output_data = iface(input_data) assert output_data == input_data.strip() class TestModel3D: def test_component_functions(self): """ get_config """ model_component = gr.components.Model3D(None, label="Model") assert model_component.get_config() == { "value": None, "clear_color": [0, 0, 0, 0], "label": "Model", "show_label": True, "container": True, "scale": None, "min_width": 160, "visible": True, "elem_id": None, "elem_classes": [], "proxy_url": None, "interactive": None, "name": "model3d", "camera_position": (None, None, None), "height": None, "zoom_speed": 1, "pan_speed": 1, "_selectable": False, } file = "test/test_files/Box.gltf" output1 = model_component.postprocess(file) output2 = model_component.postprocess(Path(file)) assert output1 assert output2 assert Path(output1.path).name == Path(output2.path).name def test_in_interface(self): """ Interface, process """ iface = gr.Interface(lambda x: x, "model3d", "model3d") input_data = "test/test_files/Box.gltf" output_data = iface(input_data) assert output_data.endswith(".gltf") class TestColorPicker: def test_component_functions(self): """ Preprocess, postprocess, serialize, tokenize, get_config """ color_picker_input = gr.ColorPicker() assert color_picker_input.preprocess("#000000") == "#000000" assert color_picker_input.postprocess("#000000") == "#000000" assert color_picker_input.postprocess(None) is None assert color_picker_input.postprocess("#FFFFFF") == "#FFFFFF" assert color_picker_input.get_config() == { "value": None, "show_label": True, "label": None, "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "name": "colorpicker", "info": None, "_selectable": False, } def test_in_interface_as_input(self): """ Interface, process """ iface = gr.Interface(lambda x: x, "colorpicker", "colorpicker") assert iface("#000000") == "#000000" def test_in_interface_as_output(self): """ Interface, process """ iface = gr.Interface(lambda x: x, "colorpicker", gr.ColorPicker()) assert iface("#000000") == "#000000" def test_static(self): """ postprocess """ component = gr.ColorPicker("#000000") assert component.get_config().get("value") == "#000000" class TestGallery: def test_postprocess(self): url = "https://huggingface.co/Norod78/SDXL-VintageMagStyle-Lora/resolve/main/Examples/00015-20230906102032-7778-Wonderwoman VintageMagStyle _lora_SDXL-VintageMagStyle-Lora_1_, Very detailed, clean, high quality, sharp image.jpg" gallery = gr.Gallery([url]) assert gallery.get_config()["value"] == [ { "image": { "path": url, "orig_name": "00015-20230906102032-7778-Wonderwoman VintageMagStyle _lora_SDXL-VintageMagStyle-Lora_1_, Very detailed, clean, high quality, sharp image.jpg", "mime_type": None, "size": None, "url": url, }, "caption": None, } ] def test_gallery(self): gallery = gr.Gallery() Path(Path(__file__).parent, "test_files") postprocessed_gallery = gallery.postprocess( [ (str(Path("test/test_files/foo.png")), "foo_caption"), (Path("test/test_files/bar.png"), "bar_caption"), str(Path("test/test_files/baz.png")), Path("test/test_files/qux.png"), ] ).model_dump() # Using str(Path(...)) to ensure that the test passes on all platforms assert postprocessed_gallery == [ { "image": { "path": str(Path("test") / "test_files" / "foo.png"), "orig_name": "foo.png", "mime_type": None, "size": None, "url": None, }, "caption": "foo_caption", }, { "image": { "path": str(Path("test") / "test_files" / "bar.png"), "orig_name": "bar.png", "mime_type": None, "size": None, "url": None, }, "caption": "bar_caption", }, { "image": { "path": str(Path("test") / "test_files" / "baz.png"), "orig_name": "baz.png", "mime_type": None, "size": None, "url": None, }, "caption": None, }, { "image": { "path": str(Path("test") / "test_files" / "qux.png"), "orig_name": "qux.png", "mime_type": None, "size": None, "url": None, }, "caption": None, }, ] class TestState: def test_as_component(self): state = gr.State(value=5) assert state.preprocess(10) == 10 assert state.preprocess("abc") == "abc" assert state.stateful def test_initial_value_deepcopy(self): with pytest.raises(TypeError): gr.State(value=gr) # modules are not deepcopyable @pytest.mark.asyncio async def test_in_interface(self): def test(x, y=" def"): return (x + y, x + y) io = gr.Interface(test, ["text", "state"], ["text", "state"]) result = await io.call_function(0, ["abc"]) assert result["prediction"][0] == "abc def" result = await io.call_function(0, ["abc", result["prediction"][0]]) assert result["prediction"][0] == "abcabc def" @pytest.mark.asyncio async def test_in_blocks(self): with gr.Blocks() as demo: score = gr.State() btn = gr.Button() btn.click(lambda x: x + 1, score, score) result = await demo.call_function(0, [0]) assert result["prediction"] == 1 result = await demo.call_function(0, [result["prediction"]]) assert result["prediction"] == 2 def test_dataframe_as_example_converts_dataframes(): df_comp = gr.Dataframe() assert df_comp.as_example(pd.DataFrame({"a": [1, 2, 3, 4], "b": [5, 6, 7, 8]})) == [ [1, 5], [2, 6], [3, 7], [4, 8], ] assert df_comp.as_example(np.array([[1, 2], [3, 4.0]])) == [[1.0, 2.0], [3.0, 4.0]] @pytest.mark.parametrize("component", [gr.Model3D, gr.File, gr.Audio]) def test_as_example_returns_file_basename(component): component = component() assert component.as_example("/home/freddy/sources/example.ext") == "example.ext" assert component.as_example(None) == "" @patch( "gradio.components.Component.as_example", spec=gr.components.Component.as_example ) @patch("gradio.components.Image.as_example", spec=gr.Image.as_example) @patch("gradio.components.File.as_example", spec=gr.File.as_example) @patch("gradio.components.Dataframe.as_example", spec=gr.DataFrame.as_example) @patch("gradio.components.Model3D.as_example", spec=gr.Model3D.as_example) def test_dataset_calls_as_example(*mocks): gr.Dataset( components=[gr.Dataframe(), gr.File(), gr.Image(), gr.Model3D(), gr.Textbox()], samples=[ [ pd.DataFrame({"a": np.array([1, 2, 3])}), "foo.png", "bar.jpeg", "duck.obj", "hello", ] ], ) assert all(m.called for m in mocks) cars = vega_datasets.data.cars() stocks = vega_datasets.data.stocks() barley = vega_datasets.data.barley() simple = pd.DataFrame( { "a": ["A", "B", "C", "D", "E", "F", "G", "H", "I"], "b": [28, 55, 43, 91, 81, 53, 19, 87, 52], } ) class TestScatterPlot: @patch.dict("sys.modules", {"bokeh": MagicMock(__version__="3.0.3")}) def test_get_config(self): print(gr.ScatterPlot().get_config()) assert gr.ScatterPlot().get_config() == { "caption": None, "elem_id": None, "elem_classes": [], "interactive": None, "label": None, "name": "plot", "bokeh_version": "3.0.3", "show_actions_button": False, "proxy_url": None, "show_label": True, "container": True, "min_width": 160, "scale": None, "value": None, "visible": True, "x": None, "y": None, "color": None, "size": None, "shape": None, "title": None, "tooltip": None, "x_title": None, "y_title": None, "color_legend_title": None, "size_legend_title": None, "shape_legend_title": None, "color_legend_position": None, "size_legend_position": None, "shape_legend_position": None, "height": None, "width": None, "x_lim": None, "y_lim": None, "x_label_angle": None, "y_label_angle": None, "_selectable": False, } def test_no_color(self): plot = gr.ScatterPlot( x="Horsepower", y="Miles_per_Gallon", tooltip="Name", title="Car Data", x_title="Horse", ) output = plot.postprocess(cars).model_dump() assert sorted(output.keys()) == ["chart", "plot", "type"] config = json.loads(output["plot"]) assert config["encoding"]["x"]["field"] == "Horsepower" assert config["encoding"]["x"]["title"] == "Horse" assert config["encoding"]["y"]["field"] == "Miles_per_Gallon" assert config["title"] == "Car Data" assert "height" not in config assert "width" not in config def test_no_interactive(self): plot = gr.ScatterPlot( x="Horsepower", y="Miles_per_Gallon", tooltip="Name", interactive=False ) output = plot.postprocess(cars).model_dump() assert sorted(output.keys()) == ["chart", "plot", "type"] config = json.loads(output["plot"]) assert "selection" not in config def test_height_width(self): plot = gr.ScatterPlot( x="Horsepower", y="Miles_per_Gallon", height=100, width=200 ) output = plot.postprocess(cars).model_dump() assert sorted(output.keys()) == ["chart", "plot", "type"] config = json.loads(output["plot"]) assert config["height"] == 100 assert config["width"] == 200 def test_xlim_ylim(self): plot = gr.ScatterPlot( x="Horsepower", y="Miles_per_Gallon", x_lim=[200, 400], y_lim=[300, 500] ) output = plot.postprocess(cars).model_dump() config = json.loads(output["plot"]) assert config["encoding"]["x"]["scale"] == {"domain": [200, 400]} assert config["encoding"]["y"]["scale"] == {"domain": [300, 500]} def test_color_encoding(self): plot = gr.ScatterPlot( x="Horsepower", y="Miles_per_Gallon", tooltip="Name", title="Car Data", color="Origin", ) output = plot.postprocess(cars).model_dump() config = json.loads(output["plot"]) assert config["encoding"]["color"]["field"] == "Origin" assert config["encoding"]["color"]["scale"] == { "domain": ["USA", "Europe", "Japan"], "range": [0, 1, 2], } assert config["encoding"]["color"]["type"] == "nominal" def test_two_encodings(self): plot = gr.ScatterPlot( show_label=False, title="Two encodings", x="Horsepower", y="Miles_per_Gallon", color="Acceleration", shape="Origin", ) output = plot.postprocess(cars).model_dump() config = json.loads(output["plot"]) assert config["encoding"]["color"]["field"] == "Acceleration" assert config["encoding"]["color"]["scale"] == { "domain": [cars.Acceleration.min(), cars.Acceleration.max()], "range": [0, 1], } assert config["encoding"]["color"]["type"] == "quantitative" assert config["encoding"]["shape"]["field"] == "Origin" assert config["encoding"]["shape"]["type"] == "nominal" def test_legend_position(self): plot = gr.ScatterPlot( show_label=False, title="Two encodings", x="Horsepower", y="Miles_per_Gallon", color="Acceleration", color_legend_position="none", color_legend_title="Foo", shape="Origin", shape_legend_position="none", shape_legend_title="Bar", size="Acceleration", size_legend_title="Accel", size_legend_position="none", ) output = plot.postprocess(cars).model_dump() config = json.loads(output["plot"]) assert config["encoding"]["color"]["legend"] is None assert config["encoding"]["shape"]["legend"] is None assert config["encoding"]["size"]["legend"] is None def test_scatterplot_accepts_fn_as_value(self): plot = gr.ScatterPlot( value=lambda: cars.sample(frac=0.1, replace=False), x="Horsepower", y="Miles_per_Gallon", color="Origin", ) assert isinstance(plot.value, dict) assert isinstance(plot.value["plot"], str) class TestLinePlot: @patch.dict("sys.modules", {"bokeh": MagicMock(__version__="3.0.3")}) def test_get_config(self): assert gr.LinePlot().get_config() == { "caption": None, "elem_id": None, "elem_classes": [], "interactive": None, "label": None, "name": "plot", "bokeh_version": "3.0.3", "show_actions_button": False, "proxy_url": None, "show_label": True, "container": True, "min_width": 160, "scale": None, "value": None, "visible": True, "x": None, "y": None, "color": None, "stroke_dash": None, "overlay_point": None, "title": None, "tooltip": None, "x_title": None, "y_title": None, "color_legend_title": None, "stroke_dash_legend_title": None, "color_legend_position": None, "stroke_dash_legend_position": None, "height": None, "width": None, "x_lim": None, "y_lim": None, "x_label_angle": None, "y_label_angle": None, "_selectable": False, } def test_no_color(self): plot = gr.LinePlot( x="date", y="price", tooltip=["symbol", "price"], title="Stock Performance", x_title="Trading Day", ) output = plot.postprocess(stocks).model_dump() assert sorted(output.keys()) == ["chart", "plot", "type"] config = json.loads(output["plot"]) for layer in config["layer"]: assert layer["mark"]["type"] in ["line", "point"] assert layer["encoding"]["x"]["field"] == "date" assert layer["encoding"]["x"]["title"] == "Trading Day" assert layer["encoding"]["y"]["field"] == "price" assert config["title"] == "Stock Performance" assert "height" not in config assert "width" not in config def test_height_width(self): plot = gr.LinePlot(x="date", y="price", height=100, width=200) output = plot.postprocess(stocks).model_dump() assert sorted(output.keys()) == ["chart", "plot", "type"] config = json.loads(output["plot"]) assert config["height"] == 100 assert config["width"] == 200 def test_xlim_ylim(self): plot = gr.LinePlot(x="date", y="price", x_lim=[200, 400], y_lim=[300, 500]) output = plot.postprocess(stocks).model_dump() config = json.loads(output["plot"]) for layer in config["layer"]: assert layer["encoding"]["x"]["scale"] == {"domain": [200, 400]} assert layer["encoding"]["y"]["scale"] == {"domain": [300, 500]} def test_color_encoding(self): plot = gr.LinePlot( x="date", y="price", tooltip="symbol", color="symbol", overlay_point=True ) output = plot.postprocess(stocks).model_dump() config = json.loads(output["plot"]) for layer in config["layer"]: assert layer["encoding"]["color"]["field"] == "symbol" assert layer["encoding"]["color"]["scale"] == { "domain": ["MSFT", "AMZN", "IBM", "GOOG", "AAPL"], "range": [0, 1, 2, 3, 4], } assert layer["encoding"]["color"]["type"] == "nominal" if layer["mark"]["type"] == "point": assert layer["encoding"]["opacity"] == {} def test_lineplot_accepts_fn_as_value(self): plot = gr.LinePlot( value=lambda: stocks.sample(frac=0.1, replace=False), x="date", y="price", color="symbol", ) assert isinstance(plot.value, dict) assert isinstance(plot.value["plot"], str) class TestBarPlot: @patch.dict("sys.modules", {"bokeh": MagicMock(__version__="3.0.3")}) def test_get_config(self): assert gr.BarPlot().get_config() == { "caption": None, "elem_id": None, "elem_classes": [], "interactive": None, "label": None, "name": "plot", "bokeh_version": "3.0.3", "show_actions_button": False, "proxy_url": None, "show_label": True, "container": True, "min_width": 160, "scale": None, "value": None, "visible": True, "x": None, "y": None, "color": None, "vertical": True, "group": None, "title": None, "tooltip": None, "x_title": None, "y_title": None, "color_legend_title": None, "group_title": None, "color_legend_position": None, "height": None, "width": None, "y_lim": None, "x_label_angle": None, "y_label_angle": None, "sort": None, "_selectable": False, } def test_no_color(self): plot = gr.BarPlot( x="a", y="b", tooltip=["a", "b"], title="Made Up Bar Plot", x_title="Variable A", sort="x", ) output = plot.postprocess(simple).model_dump() assert sorted(output.keys()) == ["chart", "plot", "type"] assert output["chart"] == "bar" config = json.loads(output["plot"]) assert config["encoding"]["x"]["sort"] == "x" assert config["encoding"]["x"]["field"] == "a" assert config["encoding"]["x"]["title"] == "Variable A" assert config["encoding"]["y"]["field"] == "b" assert config["encoding"]["y"]["title"] == "b" assert config["title"] == "Made Up Bar Plot" assert "height" not in config assert "width" not in config def test_height_width(self): plot = gr.BarPlot(x="a", y="b", height=100, width=200) output = plot.postprocess(simple).model_dump() assert sorted(output.keys()) == ["chart", "plot", "type"] config = json.loads(output["plot"]) assert config["height"] == 100 assert config["width"] == 200 def test_ylim(self): plot = gr.BarPlot(x="a", y="b", y_lim=[15, 100]) output = plot.postprocess(simple).model_dump() config = json.loads(output["plot"]) assert config["encoding"]["y"]["scale"] == {"domain": [15, 100]} def test_horizontal(self): output = gr.BarPlot( simple, x="a", y="b", x_title="Variable A", y_title="Variable B", title="Simple Bar Plot with made up data", tooltip=["a", "b"], vertical=False, y_lim=[20, 100], ).get_config() assert output["value"]["chart"] == "bar" config = json.loads(output["value"]["plot"]) assert config["encoding"]["x"]["field"] == "b" assert config["encoding"]["x"]["scale"] == {"domain": [20, 100]} assert config["encoding"]["x"]["title"] == "Variable B" assert config["encoding"]["y"]["field"] == "a" assert config["encoding"]["y"]["title"] == "Variable A" def test_barplot_accepts_fn_as_value(self): plot = gr.BarPlot( value=lambda: barley.sample(frac=0.1, replace=False), x="year", y="yield", ) assert isinstance(plot.value, dict) assert isinstance(plot.value["plot"], str) class TestCode: def test_component_functions(self): """ Preprocess, postprocess, serialize, get_config """ code = gr.Code() assert code.preprocess("# hello friends") == "# hello friends" assert code.preprocess("def fn(a):\n return a") == "def fn(a):\n return a" assert ( code.postprocess( """ def fn(a): return a """ ) == """def fn(a): return a""" ) test_file_dir = Path(Path(__file__).parent, "test_files") path = str(Path(test_file_dir, "test_label_json.json")) with open(path) as f: assert code.postprocess(path) == path assert code.postprocess((path,)) == f.read() assert code.get_config() == { "value": None, "language": None, "lines": 5, "name": "code", "show_label": True, "label": None, "container": True, "min_width": 160, "scale": None, "elem_id": None, "elem_classes": [], "visible": True, "interactive": None, "proxy_url": None, "_selectable": False, } class TestFileExplorer: def test_component_functions(self): """ Preprocess, get_config """ file_explorer = gr.FileExplorer(file_count="single") config = file_explorer.get_config() assert config["glob"] == "**/*.*" assert config["value"] is None assert config["file_count"] == "single" assert config["server_fns"] == ["ls"] input_data = FileExplorerData(root=[["test/test_files/bus.png"]]) preprocessed_data = file_explorer.preprocess(input_data) assert isinstance(preprocessed_data, str) assert Path(preprocessed_data).name == "bus.png" input_data = FileExplorerData(root=[]) preprocessed_data = file_explorer.preprocess(input_data) assert preprocessed_data is None file_explorer = gr.FileExplorer(file_count="multiple") config = file_explorer.get_config() assert config["glob"] == "**/*.*" assert config["value"] is None assert config["file_count"] == "multiple" assert config["server_fns"] == ["ls"] input_data = FileExplorerData(root=[["test/test_files/bus.png"]]) preprocessed_data = file_explorer.preprocess(input_data) assert isinstance(preprocessed_data, list) assert Path(preprocessed_data[0]).name == "bus.png" input_data = FileExplorerData(root=[]) preprocessed_data = file_explorer.preprocess(input_data) assert preprocessed_data == [] def test_file_explorer_dir_only_glob(self, tmpdir): tmpdir.mkdir("foo") tmpdir.mkdir("bar") tmpdir.mkdir("baz") (Path(tmpdir) / "baz" / "qux").mkdir() (Path(tmpdir) / "foo" / "abc").mkdir() (Path(tmpdir) / "foo" / "abc" / "def").mkdir() (Path(tmpdir) / "foo" / "abc" / "def" / "file.txt").touch() file_explorer = gr.FileExplorer(glob="**/", root=Path(tmpdir)) tree = file_explorer.ls() def sort_answer(answer): answer = sorted(answer, key=lambda x: x["path"]) for item in answer: if item["children"]: item["children"] = sort_answer(item["children"]) return answer answer = [ { "path": "bar", "type": "folder", "children": [{"path": "", "type": "file", "children": None}], }, { "path": "baz", "type": "folder", "children": [ {"path": "", "type": "file", "children": None}, { "path": "qux", "type": "folder", "children": [{"path": "", "type": "file", "children": None}], }, ], }, { "path": "foo", "type": "folder", "children": [ {"path": "", "type": "file", "children": None}, { "path": "abc", "type": "folder", "children": [ {"path": "", "type": "file", "children": None}, { "path": "def", "type": "folder", "children": [ {"path": "", "type": "file", "children": None} ], }, ], }, ], }, ] assert sort_answer(tree) == sort_answer(answer) def test_component_class_ids(): button_id = gr.Button().component_class_id textbox_id = gr.Textbox().component_class_id json_id = gr.JSON().component_class_id mic_id = gr.Mic().component_class_id microphone_id = gr.Microphone().component_class_id audio_id = gr.Audio().component_class_id assert button_id == gr.Button().component_class_id assert textbox_id == gr.Textbox().component_class_id assert json_id == gr.JSON().component_class_id assert mic_id == gr.Mic().component_class_id assert microphone_id == gr.Microphone().component_class_id assert audio_id == gr.Audio().component_class_id assert mic_id == microphone_id # Make sure that the ids are unique assert len({button_id, textbox_id, json_id, microphone_id, audio_id}) == 5 def test_constructor_args(): assert gr.Textbox(max_lines=314).constructor_args == {"max_lines": 314} assert gr.LoginButton(visible=False, value="Log in please").constructor_args == { "visible": False, "value": "Log in please", }