| import pandas as pd | |
| from sklearn.model_selection import train_test_split | |
| # import my data into a dataframe (df) | |
| df = pd.read_csv("mydata.csv") | |
| # random split 60/40% solution / public dataframe | |
| solution, public_df = train_test_split(df,test_size=0.40,random_state=101) |
| greenlet == 0.4.17 | |
| flask_cors == 3.0.10 | |
| flask == 2.0.2 | |
| pandas == 1.3.4 | |
| scikit-learn == 1.0 | |
| flask_sqlalchemy == 2.5.1 | |
| cherrypy == 18.6.1 | |
| paste == 3.5.0 |
| from main import app | |
| if __name__ == "__main__": | |
| app.run() |
| version: "3" | |
| services: | |
| web: | |
| build: . | |
| ports: | |
| - "80:80" |
| # Get image from docker hub | |
| FROM tiangolo/meinheld-gunicorn-flask:python3.9 | |
| # If you need to install any apt package you can do it here e.g: | |
| # RUN apt-get update && apt-get install -y pandoc | |
| # Copy the requirements file into the container. | |
| # The requirements file is a list of all pip packages we need. | |
| COPY ./requirements.txt /app/requirements.txt |
| from flask import Flask | |
| import pandas as pd | |
| app = Flask(__name__) | |
| @app.route("/") | |
| def hello_world(): | |
| mydata = { | |
| "name":["John","Danny","Patricia","Rose"], | |
| "office":["HR","Sales","Sales","HR"], |
| from flask import Flask | |
| app = Flask(__name__) | |
| @app.route("/") | |
| def hello_world(): | |
| return "<p>Hello, World!</p>" |
The MIT License (MIT)
Copyright (c) 2016-2017 Emily M Klassen
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: