Sean Aubin Seanny123

## dactyl.json
{
  "name": "Dactyl Manuform (5x6+6)",
  "vendorId": "0xFDDD",
  "productId": "0x06AD",
  "lighting": "none",
  "matrix": { "rows": 12, "cols": 6 },
  "layouts": {
    "keymap": [
      [{ "x": 3 }, "0,3", { "x": 8.5 }, "6,2"],
      [

## README.md

      
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                Seanny123
                / README.md
            
            
              Created
              July 6, 2023 14:33
            
              
                Pandas example using `explode()`
              
          
    Created using the following ChatGPT conversation:
https://chat.openai.com/share/9cac1fad-851d-4f43-87da-17d64b3f4e02

  
## fanout.py
"""
An example of nested fanout using Ray Workflows.

The full workflow creates several batches given a single input, then each of those batches is fanned-out and evaluated.
"""

import time

import ray
from ray import workflow

## ray_futures.py
import concurrent.futures
import random
import time

import ray

@ray.remote
def append_a(in_str):
    print(in_str)
    time.sleep(random.uniform(0, 1.5))

## better_formatting.py
def hello(name):
    return "Hello" + name


name = input("Enter your name: ")
print(hello(name))

## pyproject.toml
[tool.pylint.messages_control]
disable = [
    "arguments-differ",
    "attribute-defined-outside-init",
    "bad-continuation",
    "blacklisted-name",
    "duplicate-code",
    "fixme",
    "import-error",
    "no-member",

## better_code.py
def append_number(num, numbers=None):
    if numbers is None:
        numbers = []
    numbers.append(num)
    return numbers

## bad_code.py
def append_number(num, numbers=[]):
    numbers.append(num)
    return numbers

## bad_formatting.py
def hello (name):
    return"Hello"+name
name = input("Enter your name: ")
print(hello(name ))

## argo-params.sh
# requires yq and jq to be installed
kubectl get pods $1 -o yaml | yq .metadata.annotations.\"workflows.argoproj.io/template\" | jq -r | jq
	{
	"name": "Dactyl Manuform (5x6+6)",
	"vendorId": "0xFDDD",
	"productId": "0x06AD",
	"lighting": "none",
	"matrix": { "rows": 12, "cols": 6 },
	"layouts": {
	"keymap": [
	[{ "x": 3 }, "0,3", { "x": 8.5 }, "6,2"],
	[
	"""
	An example of nested fanout using Ray Workflows.

	The full workflow creates several batches given a single input, then each of those batches is fanned-out and evaluated.
	"""

	import time

	import ray
	from ray import workflow
	import concurrent.futures
	import random
	import time

	import ray

	@ray.remote
	def append_a(in_str):
	print(in_str)
	time.sleep(random.uniform(0, 1.5))
	def hello(name):
	return "Hello" + name


	name = input("Enter your name: ")
	print(hello(name))
	[tool.pylint.messages_control]
	disable = [
	"arguments-differ",
	"attribute-defined-outside-init",
	"bad-continuation",
	"blacklisted-name",
	"duplicate-code",
	"fixme",
	"import-error",
	"no-member",
	def append_number(num, numbers=None):
	if numbers is None:
	numbers = []
	numbers.append(num)
	return numbers
	def append_number(num, numbers=[]):
	numbers.append(num)
	return numbers
	def hello (name):
	return"Hello"+name
	name = input("Enter your name: ")
	print(hello(name ))
	# requires yq and jq to be installed
	kubectl get pods $1 -o yaml \| yq .metadata.annotations.\"workflows.argoproj.io/template\" \| jq -r \| jq