python 可视化包streamlit学习

streamlit是一个快速开发基于python应用的数据app包，开发比较方便,同时官方也提供了
一个方便云服务

安装

 
python -m venv venv

source venv/bin/activate

pip install -i https://mirrors.aliyun.com/pypi/simple/ streamlit

简单应用

命令

streamlit

Usage: streamlit [OPTIONS] COMMAND [ARGS]...

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  Try out a demo with:

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      $ streamlit hello

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  Or use the line below to run your own script:

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      $ streamlit run your_script.py

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Options:

  --log_level [error|warning|info|debug]

  --version                       Show the version and exit.

  --help                          Show this message and exit.

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Commands:

  activate  Activate Streamlit by entering your email.

  cache     Manage the Streamlit cache.

  config    Manage Streamlit's config settings.

  docs      Show help in browser.

  hello     Runs the Hello World script.

  help      Print this help message.

  run       Run a Python script, piping stderr to Streamlit.

  version   Print Streamlit's version number.

创建应用

streamlit hello

运行效果

参考代码

import streamlit as st

import numpy as np

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# Interactive Streamlit elements, like these sliders, return their value.

# This gives you an extremely simple interaction model.

iterations = st.sidebar.slider("Level of detail", 2, 20, 10, 1)

separation = st.sidebar.slider("Separation", 0.7, 2.0, 0.7885)

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# Non-interactive elements return a placeholder to their location

# in the app. Here we're storing progress_bar to update it later.

progress_bar = st.sidebar.progress(0)

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# These two elements will be filled in later, so we create a placeholder

# for them using st.empty()

frame_text = st.sidebar.empty()

image = st.empty()

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m, n, s = 960, 640, 400

x = np.linspace(-m / s, m / s, num=m).reshape((1, m))

y = np.linspace(-n / s, n / s, num=n).reshape((n, 1))

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for frame_num, a in enumerate(np.linspace(0.0, 4 * np.pi, 100)):

    # Here were setting value for these two elements.

    progress_bar.progress(frame_num)

    frame_text.text("Frame %i/100" % (frame_num + 1))

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    # Performing some fractal wizardry.

    c = separation * np.exp(1j * a)

    Z = np.tile(x, (n, 1)) + 1j * np.tile(y, (1, m))

    C = np.full((n, m), c)

    M = np.full((n, m), True, dtype=bool)

    N = np.zeros((n, m))

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    for i in range(iterations):

        Z[M] = Z[M] * Z[M] + C[M]

        M[np.abs(Z) > 2] = False

        N[M] = i

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    # Update the image placeholder by calling the image() function on it.

    image.image(1.0 - (N / N.max()), use_column_width=True)

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# We clear elements by calling empty on them.

progress_bar.empty()

frame_text.empty()

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# Streamlit widgets automatically run the script from top to bottom. Since

# this button is not connected to any other logic, it just causes a plain

# rerun.

st.button("Re-run")