https://github.com/soluto/python-flask-sklearn-docker-template

A simple example of python api for real time machine learning, using scikit-learn, Flask and Docker
https://github.com/soluto/python-flask-sklearn-docker-template

docker flask python scikit-learn sklearn soluto-open-source

Last synced: 13 days ago
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A simple example of python api for real time machine learning, using scikit-learn, Flask and Docker

• Host: GitHub
• URL: https://github.com/soluto/python-flask-sklearn-docker-template
• Owner: Soluto
• Archived: true
• Created: 2017-07-14T13:00:56.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2023-08-28T16:27:25.000Z (over 1 year ago)
• Last Synced: 2024-09-27T20:22:31.168Z (4 months ago)
• Topics: docker, flask, python, scikit-learn, sklearn, soluto-open-source
• Language: Python
• Homepage:
• Size: 13.7 KB
• Stars: 135
• Watchers: 23
• Forks: 41
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## DEPRECATED

This repository is no longer maintained and has been archived. Feel free to browse the code, but please migrate to other solutions.

## python-flask-docker-sklearn-template

A simple example of python api for real time machine learning.

On init, a simple linear regression model is created and saved on machine. On request arrival for prediction, the simple model is loaded and returning prediction.    

For more information read [this post](https://blog.solutotlv.com/deployed-scikit-learn-model-flask-docker/?utm_source=Github&utm_medium=python-flask-sklearn-docker-template)

# requirements  

docker installed

# Run on docker - local 

docker build . -t {some tag name}  -f ./Dockerfile_local  

detached : docker run -p 3000:5000 -d {some tag name}  

interactive (recommended for debug): docker run -p 3000:5000 -it {some tag name}  

# Run on docker - production 

Using uWSGI and nginx for production  

docker build . -t {some tag name}   

detached : docker run -p 3000:80 -d {some tag name}  

interactive (recommended for debug): docker run -p 3000:80 -it {some tag name}  

# Run on local computer

python -m venv env  

source env/bin/activate  

python -m pip install -r ./requirements.txt  

python main.py  

# Use sample api  

127.0.0.1:3000/isAlive  

127.0.0.1:3000/prediction/api/v1.0/some_prediction?f1=4&f2=4&f3=4