Example of an ML web app using Streamlit 🌱

This repository contains code to build a Streamlit web app that serves an Iris classifier.

Prerequisities

Before you begin, ensure you have met the following requirements:

• You have a Windows/Linux/Mac machine running Python 3.6+.
• You have installed the latest versions of pip and virtualenv or conda (Anaconda).

Setup

To install the dependencies, you can simply follow this steps.

Clone the project repository:

git clone https://github.com/RodolfoFerro/streamlit-example.git
cd streamlit-example

To create and activate the virtual environment, follow these steps:

Using conda

$ conda create -n streamlit python=3.7

# Activate the virtual environment:
$ conda activate streamlit

# To deactivate (when you're done):
(streamlit)$ conda deactivate

Using virtualenv

# In this case I'm supposing that your latest python3 version is 3.7
$ virtualenv streamlit --python=python3

# Activate the virtual environment:
$ source streamlit/bin/activate

# To deactivate (when you're done):
(streamlit)$ deactivate

To install the requirements using pip, once the virtual environment is active:

(streamlit)$ pip install -r requirements.txt

Running the script

Finally, if you want to run the main script:

(streamlit)$ streamlit run app.py

Extend code!

Please feel free to use this repo as a template to extend code!