mlop_flask

Create a flask application for ML Ops

Dependencies

PyCaret

to instal pycaret 
Install
PyCaret is tested and supported on the following 64-bit systems:
    Python 3.6 – 3.8
    Python 3.9 for Ubuntu only
    Ubuntu 16.04 or later
#   Windows 7 or later
Install PyCaret with Python's pip package manager.
    pip install pycaret
To install the full version (see dependencies below):
    pip install pycaret[full]
If you want to try our nightly build (unstable) you can install pycaret-nightly from pip.
    pip install pycaret-nightly
Environment
In order to avoid potential conflicts with other packages, it is strongly recommended to use a virtual environment, e.g. python3 virtualenv (see python3 virtualenv documentation) or conda environments. Using an isolated environment makes it possible to install a specific version of pycaret and its dependencies independently of any previously installed Python packages. 
# create a conda environment
conda create --name yourenvname python=3.8

# activate conda environment
conda activate yourenvname

# install pycaret
pip install pycaret

# create notebook kernel
python -m ipykernel install --user --name yourenvname --display-name "display-name"
PyCaret is not yet compatible with sklearn>=0.23.2.

#   For MAC OS

MAC users will have to install LightGBM separately using Homebrew, or it can be built using CMake and Apple Clang (or gcc). See the instructions below:

Install CMake (3.16 or higher):

    >> brew install cmake
    Install OpenMP
    >> brew install libomp
    Run the following commands in terminal:

    git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM
    mkdir build ; cd build
    cmake ..
    make -j4

Flask

Prerequisite
Python 2.6 or higher is usually required for installation of Flask. Although Flask and its dependencies work well with Python 3 (Python 3.3 onwards), many Flask extensions do not support it properly. Hence, it is recommended that Flask should be installed on Python 2.7.

Install virtualenv for development environment
virtualenv is a virtual Python environment builder. It helps a user to create multiple Python environments side-by-side. Thereby, it can avoid compatibility issues between the different versions of the libraries.

The following command installs virtualenv

pip install virtualenv
This command needs administrator privileges. Add sudo before pip on Linux/Mac OS. If you are on Windows, log in as Administrator. On Ubuntu virtualenv may be installed using its package manager.

Sudo apt-get install virtualenv
Once installed, new virtual environment is created in a folder.

mkdir newproj
cd newproj
virtualenv venv
To activate corresponding environment, on Linux/OS X, use the following −

venv/bin/activate
On Windows, following can be used

venv\scripts\activate
We are now ready to install Flask in this environment.

pip install Flask
The above command can be run directly, without virtual environment for system-wide installation.

Docker

install the docker extension in vs studio code and install the docker desktop application on the local machine.
connect to your docker hub account and create a repository.
then; 
    docker build -t follysage/pycaret:latest . # to build the the docker image
    docker run -d -p 5000:5000 follysage/pycaret  # to run the container