Streamlit是一个开源库,可以帮助数据科学家和学者在短时间内开发机器学习 (ML) 可视化仪表板。只需几行代码,我们就可以构建并部署强大的数据应用程序。
为什么选择Streamlit?
目前,应用程序需求量巨大,开发人员需要一直开发新的库和框架,帮助构建并部署快速上手的仪表板。Streamlit 是一个库,可将仪表板的开发时间从几天缩短至几小时。以下是选择 Streamlit 的原因:
1. Streamlit是一个免费的开源库。
2. 和安装其他python 包一样, Streamlit的安装非常简单。
3. Streamlit学起来很容易,无需要任何 Web 开发经验,只需对 Python 有基本的了解,就足以构建数据应用程序。
4. Streamlit与大部分机器学习框架兼容,包括 Tensorflow 和 Pytorch、Scikit-learn 和可视化库,如 Seaborn、Altair、Plotly 等。
二、Install Pipenv
pip3 install pipenv
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三、Create a new environment with Streamlit
此处内容是重点!
- Navigate to your project folder:
cd myproject
- CopyCreate a new Pipenv environment in that folder and activate that environment:
pipenv shell
When you run the command above, a file called Pipfile
will appear in myprojects/
. This file is where your Pipenv environment and its dependencies are declared.
- Install Streamlit in your environment:
pip install streamlit
CopyOr if you want to create an easily-reproducible environment, replace pip
with pipenv
every time you install something:
pipenv install streamlit
这一步虽然安装的内容有点多,但是体积并不大,速度也非常快!
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- Test that the installation worked:
streamlit hello
- Streamlit's Hello app should appear in a new tab in your web browser!
四、Use your new environment
- Any time you want to use the new environment, you first need to go to your project folder (where the
Pipenv
file lives) and run:
pipenv shell
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- Now you can use Python and Streamlit as usual:
streamlit run myfile.py
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To stop the Streamlit server, press ctrl-C
.
- When you're done using this environment, just type
exit
or pressctrl-D
to return to your normal shell.
五、主要参考:
https://docs.streamlit.io/library/get-started/installation