thehappycheese

Automates reloading a website during development; served using vanilla Deno server using a websocket.

	// place in ./.devcontainer folder
	{
	"name": "Python 3",
	"dockerFile": "dockerfile",
	"features": {
	"ghcr.io/raucha/devcontainer-features/pytorch:1": {},// not sure if these are needed?
	"ghcr.io/devcontainers/features/nvidia-cuda:2": {} // not sure if these are needed?
	},
	"runArgs": ["--gpus","all"], // apparently this is the magic that makes cuda work in docker desktop for windows


	/**
	* Hash a file without loading the whole thing into memory
	* @param {File} file
	* @param {"SHA-256"\|"SHA-1"} algo
	*/
	export async function hash_file_in_chunks(file, algo = "SHA-256") {
	const chunk_size = 1000 * 1024 * 1024; // 100MB
	const count_chunks = Math.ceil(file.size / chunk_size);
	const output = new ArrayBuffer(32*count_chunks);

	#! ./python
	import json
	import sys
	from pathlib import Path
	import subprocess

	def get_staged_files():
	"""Get list of files that are staged for commit."""
	try:
	result = subprocess.run(

	from __future__ import annotations

	import subprocess
	from pathlib import Path
	from typing import Optional
	import os
	from dataclasses import dataclass
	from deprecated import deprecated
	from pandas import Timestamp

	# This works... but cant read the output array in the final step! :(

	# Experimental!
	UserLib ← &ffi ⊂□"User32.dll"
	GdiLib ← &ffi ⊂□"Gdi32.dll"
	KernelLib ← &ffi ⊂□"Kernel32.dll"
	MessageBoxA ← UserLib {"int" "MessageBoxA" "long" "const char" "const char" "unsigned int"}
	# MessageBoxA {0 "Yes Please" "About to Take A Screenshot" 0}
	GetSystemMetrics ← UserLib {"int" "GetSystemMetrics" "int"}
	GetDeviceContext ← UserLib {"long long" "GetDC" "long"}

	import pandas as pd
	import asyncio
	from aiohttp import ClientSession, TCPConnector

	@pd.api.extensions.register_series_accessor("aiohttp")
	class AiohttpAccessor:
	def __init__(self, pandas_obj):
	self._obj = pandas_obj

	async def _fetch_text(self, url: str, session):

	# pairwise coefficient of interpolation
	Interp ← ÷:⊃(-≡⊢\|≡/-)◫2

	MarchingSquares ← (
	:
	⊃(
	≡(◫2)Interp
	\| ◫2⍜⍉Interp
	\| ≡≡(°⋯♭)◫2_2> # types
	\| ≡°⍉⍉⊞⊟∩(⇡-1)⊃(⊢⇌\|⊢)△

	import pandas as pd

	def split_dataframe_by_weighted_sequence(
	df:pd.DataFrame,
	split_column:str,
	weight_column:str,
	skew:float=0.5
	):
	"""
	Split a dataframe into two parts by a sequence of values and a sequence of weights.

	from pathlib import Path
	import keyring
	import pandas as pd
	import os
	import sys
	# You need access to the compiled .NET AdomdClient .dll
	# You can get it using nuget
	# ```powershell
	# nuget.exe install Microsoft.AnalysisServices.AdomdClient.retail.amd64
	# nuget.exe install Microsoft.AnalysisServices.Tabular