Aaron Decker a-r-d

To parallelize job processing across multiple servers while ensuring each message is processed only once, we can use Redis' List data structure as a FIFO queue, along with its atomic operations. Here's how you can modify the approach:

Use Redis List as a FIFO queue Use Redis' BRPOPLPUSH command for reliable queue processing Implement a worker model that can run on multiple servers

Key points about this implementation:

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	# note: run the sql file in your database first.

	import os
	from supabase import create_client, Client
	from typing import List, Optional, Any, Union

	# Ensure the models directory exists
	os.makedirs("./models", exist_ok=True)

	url: str = os.environ.get("SUPABASE_URL")

	const Alpaca = require('@alpacahq/alpaca-trade-api')

	const getKeyId = () => process.env.APCA_API_KEY_ID
	const getSecretKey = () => process.env.APCA_API_SECRET_KEY

	export const alpaca = new Alpaca({
	keyId: getKeyId(),
	secretKey: getSecretKey(),
	paper: false,
	usePolygon: false,

	/*
	* Code for cross-fading 3 LEDs, red, green and blue (RGB)
	* To create fades, you need to do two things:
	* 1. Describe the colors you want to be displayed
	* 2. List the order you want them to fade in
	*
	* DESCRIBING A COLOR:
	* A color is just an array of three percentages, 0-100,
	* controlling the red, green and blue LEDs
	*

	library(rgdal)
	library(elevatr)

	# this is the prjection system given as example in the documentation
	ll_prj <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0"

	# Im using this projection system based on reading this document:
	# https://www.nceas.ucsb.edu/~frazier/RSpatialGuides/OverviewCoordinateReferenceSystems.pdf
	us_prj = "+init=epsg:4326 +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0"

	def featureScaling(arr):
	_max = 0
	_min = 10000000
	for a in arr:
	if a < _min:
	_min = a
	if a > _max:
	_max = a

	scaled = []

	[
	{"Country Code":"USA","Established Customers":"5009","Total Customers":"3900343","Pct Active Accounts":"90"},
	{"Country Code":"CAN","Established Customers":"3389","Total Customers":"300043","Pct Active Accounts":"80"},
	{"Country Code":"MEX","Established Customerz":"2890","Total Customers":"zzzz","Pct Active Accounts":"70"}
	]

	import numpy as np

	class BasicTemplateAlgorithm(QCAlgorithm):
	'''Basic template algorithm simply initializes the date range and cash'''

	def Initialize(self):
	'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
	self.SetStartDate(2004, 1, 1) #Set Start Date
	self.SetEndDate(2018, 2, 16) #Set End Date
	self.SetCash(100000) #Set Strategy Cash

	import numpy as np

	### <summary>
	### Basic template algorithm simply initializes the date range and cash. This is a skeleton
	### framework you can use for designing an algorithm.
	### </summary>
	class BasicTemplateAlgorithm(QCAlgorithm):
	'''Basic template algorithm simply initializes the date range and cash'''

	def Initialize(self):