Raj rajrao

Mermaid

    F[👆 First Touch<br/>26.7%]:::green 
    L[📝 Lead Creation<br/>26.7%]:::orange 
    O[💼 Opportunity Creation<br/>26.7%]:::purple 
    
    M1[🔄 Middle Touches<br/>10%]:::red
    I1[📢 Impression<br/>10%]:::blue 
    M2[🔄 Middle Touches<br/>10%]:::red
 I2[📢 Impression10%]:::blue

The following query allows you to search for a requestid and get a link to the event (which is obtained by adding @log to the query)

fields @timestamp as Timestamp, @message, @logStream as LogStream, @log
| filter(@requestId = '09d10d9b-e8e0-46fa-ad9e-01a00c87d221')
| sort @timestamp desc
| limit 10

Get stats about a certain kind of message

	from requests_toolbelt.utils import dump

	headers = {'Content-Type': 'application/json'}
	response = requests.post(
	url,
	headers=headers,
	json=jdata,
	)
	print(dump.dump_all(response).decode("utf-8"))

	import timeit
	from pprint import pprint

	setup = '''
	from string import Template
	s = "the quick brown fox JUMPED OVER THE"
	t = "LAZY DOG'S BACK 1234567890"
	'''
	iter = 1
	baseline = timeit.timeit("f'{s} {t}'", setup, number=iter)

	def get_backoff_w_jitter(attempt: int, max_backoff: int = 20) -> int:
	"""returns the wait time for a backoff for attempt # attempt
	algorithm: truncated binary exponential backoff with jitter
	src: https://docs.aws.amazon.com/sdkref/latest/guide/feature-retry-behavior.html

	Arguments:
	attempt -- the attempt # for calculating the backoff. a number >= 0

	Returns:
	the backoff amount (usually used as seconds to sleep)

	# based on https://github.com/apache/airflow/blob/9ac742885ffb83c15f7e3dc910b0cf9df073407a/airflow/sensors/base.py#L251C13-L251C13
	import hashlib
	from datetime import datetime, timedelta
	from time import sleep

	poke_interval = 5 # Time in seconds that the job should wait in between each tries
	timeout = 60 # Time, in seconds before the task times out and fails.
	started_at = datetime.now()
	sleep(1)
	exponential_backoff = True

	# from https://twitter.com/clcoding/status/1708436006154785209?t=WNPxLM7Ox33QEVxUfRH-5w&s=19
	import random
	import turtle

	colors = ['red', 'cyan', 'pink', 'yellow', 'green', 'orange']
	t = turtle.Turtle()
	t.speed(10)
	turtle.bgcolor("black")
	length=100
	angle=50

	import os
	cur_working_dir = os.path.join(os.getcwd(), os.path.dirname(__file__))
	print(cur_working_dir)

	# https://geopy.readthedocs.io/en/stable/#nominatim
	# https://nominatim.org/release-docs/develop/api/Overview/
	from geopy.geocoders import Nominatim
	geolocator = Nominatim(user_agent="test")
	place = "New York"
	location = geolocator.geocode(place)
	print(location)

	import qrcode
	from PIL import Image

	data = "https://www.aggregatedIntelligence.com/"

	qr = qrcode.QRCode(version=1, box_size=10, border=5) qr.add_data(data)
	qr.make(fit=True)

	image = qr.make_image (fill="black", back_color="white")
	image.save("qr.png")