munro

// Similar to json.dumps(obj, *, ensure_ascii=True) in Python

function encodeJsonUnicode(obj) {
    return JSON.stringify(obj).replace(/[^\0-\x7F]/g, (c) => {
        return '\\u' + ('0000' + c.charCodeAt(0).toString(16)).slice(-4);
    });
}

// decoding is simply JSON.parse(...);

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munro

# @TODO this runs, but isn't fitting!

from dataclasses import dataclass

import torch
from torch import nn


@dataclass(frozen=True)
class ForecastPrediction:

munro

import re
from functools import lru_cache
from typing import Sequence, TypeVar

from fuzzywuzzy import fuzz
from unidecode import unidecode

T = TypeVar("T")

munro

-- Does a depth of 10
CREATE OR REPLACE PROCEDURE `mydataset`.connected_components_by_edge(
    table_name STRING,
    left_column STRING,
    right_column STRING,
    output_temp_table_name STRING
)
OPTIONS(
    description="Connected components algorithm, clusters nodes by unidirected edges by the smallest node ID."
)

munro

// also checkout selenium wire https://pypi.org/project/selenium-wire/
function interceptHttp(onComplete) {
    // this will get rid of any previous interceptors, feel free to change
    // this if you want to layer them.
    window._old_send_ = window._old_send_ || window.XMLHttpRequest.prototype.send;
    window._old_open_ = window._old_open_ || window.XMLHttpRequest.prototype.open;
    window._old_setRequestHeader_ = window._old_setRequestHeader_ || window.XMLHttpRequest.prototype.setRequestHeader;

    window.XMLHttpRequest.prototype.open = function () {
        this._openArgs = [...arguments];

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// Rand fill buffer: 3.894 GiB/s | Instant { tv_sec: 554538, tv_nsec: 411678934 } | Rand buffer beginning: [131, 217, 107, 91, 100, 45, 141, 113, 182, 115]
// Write speed: 7.058 GiB/s | 1.416909244s | Write buffer beginning: [131, 217, 107, 91, 100, 45, 141, 113, 182, 115]
// Read speed: 10.746 GiB/s | 930.555263ms | File beginning: [131, 217, 107, 91, 100, 45, 141, 113, 182, 115]
// Verified 0 bytes look incorrect | 28.545 GiB/s | 350.32772ms

// Hardware: raid-1 two SAMSUNG MZQL23T8HCLS-00A07
// Capacity: 3.84 Tb
// Form Factor: U.2
// Seq. Read: 6.333 GiB/s
// Ran. Read: 1000k Iops

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wget https://cdn.geekbench.com/Geekbench-5.4.1-Linux.tar.gz
tar xvfz Geekbench-5.4.1-Linux.tar.gz
./Geekbench-5.4.1-Linux/geekbench_x86_64

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export async function* createAsyncGenerator<T>(
    createResource: (opts: { send: (value: T) => void, close: () => void }) => void,
    reconnect?: () => Promise<void>
): AsyncGenerator<T, void, undefined> {
    while (true) {
        let closed = false;
        let buffer: T[] = [];
        let bufferHasData = createEvent();

        createResource({

munro

import contextvars

import asyncio
from contextlib import asynccontextmanager
from typing import TypeVar

T = TypeVar("T")


@asynccontextmanager