NubeIO / common-py-libs

Rubix Python

Development setup

• Use poetry to manage dependencies

• Install poetry tool

  ./setup.sh

• Setup dependencies in existing project

  poetry install

• Add new dependencies in existing project

  poetry add flask panda

• Join venv

  poetry shell

• Run after join venv

  $ python run.py -h
  Usage: run.py [OPTIONS]
  
  Options:
    -p, --port INTEGER              Port  [default: 1717]
    -d, --data-dir PATH             Application data dir
    --prod                          Production mode
    -s, --setting-file TEXT         Rubix BACnet: setting ini file
    -l, --logging-conf TEXT         Rubix BACnet: logging config file
    --workers INTEGER               Gunicorn: The number of worker processes for handling requests.
    -c, --gunicorn-config TEXT      Gunicorn: config file(gunicorn.conf.py)
    --log-level [FATAL|ERROR|WARN|INFO|DEBUG]
                                    Logging level
    -h, --help                      Show this message and exit.

• Build local binary

  poetry run pyinstaller run.py -n <project_name> --clean --onefile --add-data VERSION:VERSION

The output is: dist/<project_name>. Project name should be in pyproject.toml

Integrate with IDE

PyCharm or Intellij Ultimate

• Right click in each run.py

  

• Modify name, parameter, Environment variables in popup

  • Parameters: -s config.json --workers 2 (other parameters will be depended on each specific project)
  • Environment variables: GEVENT_SUPPORT=True

  

• In project directory, make a copy ./config/config.example.json to ./out/config.json

• Then run or debug as image

  

  

Development note

Python module:

• Expose only needed function, class for another file in module level.
• For using in module level, use intra-package references.

Reference:

• import python docs
• intra package docs

Example here:

from .app import create_app, db 
from .background import FlaskThread 
from .event_dispatcher import EventDispatcher 
from .server import GunicornFlaskApplication 
from .setting import AppSetting, ServiceSetting, DriverSetting, MqttSetting, InfluxSetting, GenericListenerSetting

Use Singleton pattern

class Singleton(type):
  _instances = {}


def __call__(cls, *args, **kwargs):
  if cls not in cls._instances:
    cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs)
  return cls._instances[cls]


class DeviceRegistry(metaclass=Singleton):
  pass

Class attribute

Don't use class attributes and class method level in order to avoid unexpected behaviors.

• An instance attribute is a Python variable belonging to one, and only one, object. This variable is only accessible in the scope of this object and it is defined inside the constructor function, __init__(self,..) of the class.
• A class attribute is a Python variable that belongs to a class rather than a particular object. It is shared between all the objects of this class and it is defined outside the constructor function, __init__(self,...), of the class.

Example: https://github.com/NubeIO/rubix-point-server/compare/dev#diff-b352f9e685d68e2028ada02b2190f5cb3c9c6ae12b351f9b318c002317af7facR46-R50

Use logger format from gunicorn

• To maintain consistency and readability.
• Don't init logger too early in file level.

Instead

import logging

logger = logging.getLogger(__name__)

Should use

from logging import Logger
from flask import current_app
from werkzeug.local import LocalProxy


class Object:
  def __init__(self):
    self.logger = LocalProxy(lambda: current_app.logger) or Logger(__name__)

Use FlaskThread

class FlaskThread(Thread):
    """
    To make every new thread behinds Flask app context.
    Maybe using another lightweight solution but richer: APScheduler <https://github.com/agronholm/apscheduler>
    """

    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.app = current_app._get_current_object()

    def run(self):
        with self.app.app_context():
            super().run()