PJ Hoberman pjhoberman

Signal Ledger — Contract

A recurring signal distillation workflow. You drop links, PDFs, or screenshots. The LLM filters for signal relevant to your specific work and returns distillations — not summaries. Each session ends with an updated ledger.

Format Contract

3–5 bullets max per item
Always include a "so what for you" framing tied to your actual projects and active work — not generic takeaways
Lead with the most actionable signal, not the most interesting
Be honest when a link can't be fetched — don't fake it or skip without noting it

Hi everyone

tl;dr Is this ETF project worthwhile, of interest, useful, or should I shelve it and move on with my life?

A while ago, I was looking at some ETFs I own and wondering why they moved up or down that day. I understand that market fluctuations will do that, but I also assumed the underlying assets likely moved in some significant manner. So, I started looking at the underlying stocks to find correlations and had trouble finding a programmatic way to find what an ETF holds. While the data is freely available on brokerage sites and the ETF fund itself (in excel format, normally), I didn't find any reasonable way to get this info via api, at least not that I could afford.

	inp = """199
	200
	208
	210
	200
	207
	240
	269
	260
	263"""

	def mask_val(mask, val):
	val = format(val, "#038b")[2:]
	new_val = ""
	for pair in zip(val, mask):
	if pair[1] != "X":
	new_val += pair[1]
	else:
	new_val += pair[0]
	return int(new_val, 2)

	with open('data.txt') as file:
	data = file.read().splitlines()

	# part 1

	DIRECTIONS = {
	0: 'N',
	90: 'E',
	180: 'S',
	270: 'W',

	from collections import Counter

	# part 1
	with open('scratch_28.txt') as file:
	data = file.read().splitlines()

	def get_adjacent_seats(row, col, _data):
	previous_row = None
	next_row = None
	previous_col = None

	from collections import Counter

	with open('data.txt') as file:
	data = file.read().splitlines()

	def get_adjacent_seats(row, col, _data):
	previous_row = None
	next_row = None
	previous_col = None
	next_col = None

	[
	{
	"url": "https://www.yogajournal.com/.image/MTQ2MTgwNjcyNDg2Mzg1MDg1/leah-cullis-in-garland-pose.jpg",
	"path": "2015/12/",
	"filename": "leah-cullis-in-garland-pose.jpg",
	"ref_ids": [
	"ci02075690900a25bd"
	]
	},
	{

	from itertools import permutations

	with open('scratch_23.txt') as file:
	nums = file.read().splitlines()
	nums = [int(nums) for nums in nums]

	def check_number(numbers, preamble=25, start=0):
	pre = numbers[start:preamble+start]
	test = numbers[preamble+start]
	perms = permutations(pre, 2)