ehurheap

/* 
  Now that the initial version is done, it’s time to start extending it.
  Product has determined that that our customers want to be able to bucket events together by time.  
  After filtering the events, we would like you to aggregate events that occur in the same timespan. 
  For the purposes of this interview our timestamps will be at day granularity and we will always bucket by day.
  Types:
  type Alert struct {
		alertType  string
		date       string
		totalValue int64

rileyhilliard

# This module demonstrates that it's possible to leverage WebAI to host an LLM chatbot,
# interacting with it via APIs. The code sends a prompt to the LLM and streams back its response.
# In theory, this approach can be extended to programmatically interact with the LLM,
# while using WebAI to orchestrate running the LLM across a cluster of local hardware.
# Demo: https://i.ibb.co/jkNF488Z/Feb-11-2025-12-17-22.gif
import json
import requests
import time

def get_endpoints():

Evert87

import io.micrometer.core.instrument.MeterRegistry
import io.micrometer.core.instrument.Timer
import org.aspectj.lang.ProceedingJoinPoint
import org.aspectj.lang.annotation.Around
import org.aspectj.lang.annotation.Aspect
import org.springframework.stereotype.Component
import kotlin.coroutines.Continuation
import kotlin.coroutines.intrinsics.startCoroutineUninterceptedOrReturn
import kotlin.coroutines.intrinsics.suspendCoroutineUninterceptedOrReturn

Julians42

using Random
using CairoMakie
using QuadGK
using Distributions

function CI(x, p, ci_size)
    """Computes the minimum length confidence interval for a single-peaked posterior distribution"""
    dx = x[2] - x[1]
    median_loc = argmax(p)
    median = x[median_loc] # compute the mode of the distribution - this point will be in the confidence interval

alekszahariev

{
    "url": "https://google.com",
    "name": "ReferrToEarn",
    "iconUrl": "https://files.softicons.com/download/animal-icons/cat-force-icons-by-iconka/ico/cat_upsidedown.ico"
}

CelsoTJr

if ('speechSynthesis' in window) {
        let utterance = new SpeechSynthesisUtterance(texto);
        utterance.lang = 'pt-BR'; 
        utterance.rate = 1.2; 
        window.speechSynthesis.speak(utterance); 
    } else {
        console.log("Web Speech API não suportada neste navegador.");
    }

HugsLibRecordKeeper

Log uploaded on Wednesday, February 12, 2025, 2:25:09 AM
Loaded mods:
Harmony(brrainz.harmony)[mv:2.3.1.0]: 0Harmony(2.3.3), HarmonyMod(2.3.1)
Core(Ludeon.RimWorld): (no assemblies)
Royalty(Ludeon.RimWorld.Royalty): (no assemblies)
Ideology(Ludeon.RimWorld.Ideology): (no assemblies)
Biotech(Ludeon.RimWorld.Biotech): (no assemblies)
Anomaly(Ludeon.RimWorld.Anomaly): (no assemblies)
HugsLib(UnlimitedHugs.HugsLib)[ov:11.0.4]: 0Harmony(av:2.3.3,fv:1.2.0.1), HugsLib(av:1.0.0,fv:11.0.4)
AAAA(Allowed Area Automatic Adapter)(seekiworksmod.no17): AAAA(3.1.0)

Zaryob

pts1 = np.float32([[56,65],[368,52],[28,387],[389,390]])
pts2 = np.float32([[0,0],[300,0],[0,300],[300,300]])
M = cv2.getPerspectiveTransform(pts1, pts2)
perspective_transformed = cv2.warpPerspective(image, M, (300, 300))

AlfaBlok

‎‎​

xzuyn

import logging
import time
from contextlib import contextmanager
from collections import defaultdict

import numpy as np
import torch
import matplotlib.pyplot as plt

# --- External libraries ---