# streamlit **Repository Path**: fudy81/streamlit ## Basic Information - **Project Name**: streamlit - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2020-08-04 - **Last Updated**: 2021-05-26 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Welcome to Streamlit :wave: [![Documentation Status](https://readthedocs.com/projects/streamlit-streamlit/badge/?version=latest)](https://docs.streamlit.io/en/latest/?badge=latest) **The fastest way to build data apps.** Streamlit lets you create apps for your machine learning projects with deceptively simple Python scripts. It supports hot-reloading, so your app updates live as you edit and save your file. No need to mess with HTTP requests, HTML, JavaScript, etc. All you need is your favorite editor and a browser. Take a look at Streamlit in action: ![Example of live coding a dashboard in Streamlit|635x380](https://aws1.discourse-cdn.com/standard10/uploads/streamlit/original/1X/292e985f7f75ef7bef8c27b5899f71f76cd577e0.gif) **Check out our [launch blog post](https://towardsdatascience.com/coding-ml-tools-like-you-code-ml-models-ddba3357eace)!!** ## Installation ```bash pip install streamlit streamlit hello ``` We also have suggestions for installing Streamlit in a virtual environment in [Windows](https://github.com/streamlit/streamlit/wiki/Installing-in-a-virtual-environment#on-windows), [Mac](https://github.com/streamlit/streamlit/wiki/Installing-in-a-virtual-environment#on-mac--linux), and [Linux](https://github.com/streamlit/streamlit/wiki/Installing-in-a-virtual-environment#on-mac--linux). ## Example Streamlit lets you build interactive apps ridiculously easily: ```python import streamlit as st x = st.slider('Select a value') st.write(x, 'squared is', x * x) ``` ## A Bigger Example Despite its simplicity Streamlit lets you build incredibly rich and powerful tools. [This demo project](https://github.com/streamlit/demo-self-driving) lets you browse the entire [Udacity self-driving-car dataset](https://github.com/udacity/self-driving-car) and run inference in real time using the [YOLO object detection net](https://pjreddie.com/darknet/yolo). ![Making-of Animation](https://raw.githubusercontent.com/streamlit/demo-self-driving/master/av_final_optimized.gif "Making-of Animation") The complete demo is implemented in less than 300 lines of Python. In fact, the app contains [only 23 Streamlit calls](https://github.com/streamlit/demo-self-driving/blob/master/app.py) which illustrates all the major building blocks of Streamlit. You can try it right now with: ```bash pip install --upgrade streamlit opencv-python streamlit run https://raw.githubusercontent.com/streamlit/demo-self-driving/master/app.py ``` ## More Information - Our [launch post](https://towardsdatascience.com/coding-ml-tools-like-you-code-ml-models-ddba3357eace) - Our lovely [community](https://discuss.streamlit.io/) - Streamlit [documentation](https://docs.streamlit.io/) - More [demo projects](https://github.com/streamlit/) - If you would like to contribute, see [instructions here](https://github.com/streamlit/streamlit/wiki/Contributing) ## Streamlit for Teams [Streamlit for Teams](https://streamlit.io/for-teams/) is our enterprise edition, with single-click deploy, authentication, web editing, versioning, and more. Please contact us if you would like to learn more. ## License Streamlit is completely free and open source and licensed under the [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0) license.