module cli.make_ml_store

Short summary

module lightmlrestapi.cli.make_ml_store

Creates and runs an Falcon application.

source on GitHub

Functions

function

truncated documentation

start_mlreststor

Creates an falcon application and runs it through a wsgi server. The appplication stores machine …

Documentation

Creates and runs an Falcon application.

source on GitHub

lightmlrestapi.cli.make_ml_store.start_mlreststor(location='.', host='127.0.0.1', port=8081, name='ml', nostart=False, wsgi='waitress', secret='', users='', algo='sha224', fLOG=<built-in function print>)

Creates an falcon application and runs it through a wsgi server. The appplication stores machine learned models and runs predictions assuming all the necessary packages were installed.

Parameters:

  • name – only one option is implemented ‘ml’

  • location – location of the storage

  • host – host

  • port – port

  • nostart – do not start the wsgi server (for debug purpose)

  • wsgi – wsgi framework which runs the falcon application

  • secret – secret used to encrypt the logging, default is empty which disables the encryption

  • users – list of authorized users stored in a text file with two columns: login and encrypted password

  • algo – algorithm used to encrypt the passwords

  • fLOG – logging function

Only waitress is implemented right now. Other alternative such as mod_wsgi with Apache. uwsgi are not implemented. Parameter users can be empty to disable authentification.

Creates an falcon application to store machine learned models

Creates an falcon application and starts it through a wsgi server. The appplication stores machine learned models and runs predictions assuming all the necessary packages were installed.

<<<

python -m lightmlrestapi start_mlreststor --help

>>>

usage: start_mlreststor [-h] [-l LOCATION] [-ho HOST] [-p PORT] [-n NAME]
                        [-no NOSTART] [-w WSGI] [-s SECRET] [-u USERS]
                        [-a ALGO]

Creates an `falcon` application and runs it through a `wsgi` server. The
appplication stores machine learned models and runs predictions assuming all
the necessary packages were installed.

optional arguments:
  -h, --help            show this help message and exit
  -l LOCATION, --location LOCATION
                        location of the storage (default: .)
  -ho HOST, --host HOST
                        host (default: 127.0.0.1)
  -p PORT, --port PORT  port (default: 8081)
  -n NAME, --name NAME  only one option is implemented 'ml' (default: ml)
  -no NOSTART, --nostart NOSTART
                        do not start the wsgi server (for debug purpose)
                        (default: False)
  -w WSGI, --wsgi WSGI  `wsgi` framework which runs the falcon application
                        (default: waitress)
  -s SECRET, --secret SECRET
                        secret used to encrypt the logging, default is empty
                        which disables the encryption (default: )
  -u USERS, --users USERS
                        list of authorized users stored in a text file with
                        two columns: login and encrypted password (default: )
  -a ALGO, --algo ALGO  algorithm used to encrypt the passwords (default:
                        sha224)

source on GitHub