删除了一些调试文件

data.py

@@ -1,25 +0,0 @@
-import gradio as gr
-import pandas as pd
-import numpy as np
-import random
-from gradio_datetimerange import DateTimeRange
-from datetime import datetime, timedelta
-now = datetime.now()
-
-df = pd.DataFrame({
-    'time': [now - timedelta(minutes=5*i) for i in range(25)],
-    'price': np.random.randint(100, 1000, 25),
-    'origin': [random.choice(["DFW", "DAL", "HOU"]) for _ in range(25)],
-    'destination': [random.choice(["JFK", "LGA", "EWR"]) for _ in range(25)],
-})
-
-if __name__ == "__main__":
-    with gr.Blocks() as demo:
-        daterange = DateTimeRange(["now - 24h", "now"])
-        plot1 = gr.LinePlot(df, x="time", y="price")
-        plot2 = gr.LinePlot(df, x="time", y="price", color="origin")
-        daterange.bind([plot1, plot2])
-
-    demo.launch(share=True)
-    print(type(DateTimeRange))
-    print(type(gr.LinePlot))

flatten_ndarray.py

@@ -1,30 +0,0 @@
-import pandas as pd
-import numpy as np
-
-def flatten_ndarray_column(df, column_name):
-    def flatten_ndarray(ndarray):
-        if isinstance(ndarray, np.ndarray) and ndarray.dtype == 'O':
-            return np.concatenate([flatten_ndarray(subarray) for subarray in ndarray])
-        elif isinstance(ndarray, np.ndarray) and ndarray.ndim == 1:
-            return np.expand_dims(ndarray, axis=0)
-        return ndarray
-
-    flattened_data = df[column_name].apply(flatten_ndarray)
-    max_length = max(flattened_data.apply(len))
-
-    for i in range(max_length):
-        df[f'{column_name}_{i}'] = flattened_data.apply(lambda x: x[i] if i < len(x) else np.nan)
-
-    return df
-
-# 示例用法
-if __name__ == "__main__":
-    # 创建示例 DataFrame
-    data = {
-        'target': [np.array([np.array([1, 2]), np.array([3, 4])]), np.array([5, 6, 7])]
-    }
-    df = pd.DataFrame(data)
-
-    # 拆分 target 列中的嵌套 ndarray
-    df = flatten_ndarray_column(df, 'target')
-    print(df)

line_plot.py

@@ -1,44 +0,0 @@
-import pandas as pd
-from fastapi import FastAPI
-import plotly.graph_objects as go
-import gradio as gr
-import uvicorn
-
-def create_plot(df):
-    fig = go.Figure()
-    for column in df.columns[1:]:
-        fig.add_trace(go.Scatter(x=df[df.columns[0]], y=df[column], mode='lines', name=column))
-    
-    # 配置图例
-    fig.update_layout(
-        legend=dict(
-            title="Variables",
-            orientation="h",
-            yanchor="bottom",
-            y=1.02,
-            xanchor="right",
-            x=1
-        ),
-        xaxis_title='Time',
-        yaxis_title='Values'
-    )
-    return fig
-
-# 创建Gradio界面
-demo = gr.Blocks()
-with demo:
-    # 示例数据
-    data = {
-        'time': pd.date_range(start='2023-01-01', periods=6, freq='D'),
-        'y1': [0, 1, 4, 9, 16, 25],
-        'y2': [0, 1, 2, 3, 4, 5]
-    }
-    df = pd.DataFrame(data)
-    plot = create_plot(df)
-    gr.Plot(plot)
-
-# 运行Gradio界面
-if __name__ == "__main__":
-    app = FastAPI()
-    app = gr.mount_gradio_app(app, demo, path="/")
-    uvicorn.run(app, host="127.0.0.1", port=7860)

tempCodeRunnerFile.py

@@ -1,4 +0,0 @@
-if __name__ == "__main__":
-#     app = FastAPI()
-#     app = gr.mount_gradio_app(app, demo, path="/")
-#     uvicorn.run(app, host="127.0.0.1", port=7860)

your_script.py

@@ -1,47 +0,0 @@
-import altair as alt
-from fastapi import FastAPI
-import gradio as gr
-import numpy as np
-import pandas as pd
-import uvicorn
-from vega_datasets import data
-
-
-def plot(v, a):
-    g = 9.81
-    theta = a / 180 * 3.14
-    tmax = ((2 * v) * np.sin(theta)) / g
-    timemat = tmax * np.linspace(0, 1, 40)
-
-    x = (v * timemat) * np.cos(theta)
-    y = ((v * timemat) * np.sin(theta)) - ((0.5 * g) * (timemat**2))
-    df = pd.DataFrame({"x": x, "y": y})
-    return df
-
-demo = gr.Blocks()
-
-with demo:
-    gr.Markdown(
-        r"Let's do some kinematics! Choose the speed and angle to see the trajectory. Remember that the range $R = v_0^2 \cdot \frac{\sin(2\theta)}{g}$"
-    )
-
-    with gr.Row():
-        speed = gr.Slider(1, 30, 25, label="Speed")
-        angle = gr.Slider(0, 90, 45, label="Angle")
-    output = gr.LinePlot(
-        x="x",
-        y="y",
-        overlay_point=True,
-        tooltip=["x", "y"],
-        x_lim=[0, 100],
-        y_lim=[0, 60],
-        width=350,
-        height=300,
-    )
-    btn = gr.Button(value="Run")
-    btn.click(plot, [speed, angle], output)
-
-if __name__ == "__main__":
-    app = FastAPI()
-    app = gr.mount_gradio_app(app, demo, path="/")
-    uvicorn.run(app, host="127.0.0.1", port=7860)