iiLaurens

window.scrollTo(0, 0)
var bodyRect = document.body.getBoundingClientRect();

var items = Array.prototype.slice.call(
  document.querySelectorAll('*')
).map(function(element) {
  var rect=element.getBoundingClientRect();
  return {
    element: element,
    include: (element.tagName === "BUTTON" || element.tagName === "A" || (element.onclick != null) || window.getComputedStyle(element).cursor == "pointer"),

ruizb

The following section is not part of monet.js documentation, but I think it's worth showing how we can compose readers using fp-ts.

Reader composition

Let's say we have the following piece of code:

interface Dependencies {
  logger: { log: (message: string) => void }
 env: 'development' | 'production'

hkucuk

import webview
import base64

def open_file_dialog(window):
    file_types = ('Image Files (*.bmp;*.jpg;*.gif;*.png)', 
                  'All files (*.*)')
    
    path = window.create_file_dialog(webview.OPEN_DIALOG,
                                     allow_multiple=False,
                                     file_types=file_types)

PARC6502

Backend as a Service

Supabase - ~52K stars

• Designed explicitly as an open source firebase alternative
• Typescript based
• Docker support

Appwrite - ~32K stars

• Written in JavaScript and PHP
• Docker based
• Realtime support across all services

michaelchughes

Goal

Install working tensorflow or pytorch via standard conda environment workflow.

Basic Setup : Install pytorch in a fresh conda environment

The recommended conda-based install process works smoothly:

$ # Create a fresh environment

socool

// Enable component-scanning and auto-configuration with @SpringBootApplication Annotation
// It combines @Configuration + @ComponentScan + @EnableAutoConfiguration
@SpringBootApplication
public class FooApplication {
  public static void main(String[] args) {
    // Bootstrap the application
    SpringApplication.run(FooApplication.class, args);
  }
}

endolith

"""
Train a neural network to implement the discrete Fourier transform
"""
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
import numpy as np
import matplotlib.pyplot as plt

N = 32
batch = 10000

oifland

// Related to https://issues.jenkins-ci.org/browse/JENKINS-26481

abcs = ['a', 'b', 'c']

node('master') {
    stage('Test 1: loop of echo statements') {
        echo_all(abcs)
    }
    
    stage('Test 2: loop of sh commands') {

jonico

#!groovy
import groovy.json.JsonOutput
import groovy.json.JsonSlurper

def label = "mypod-${UUID.randomUUID().toString()}"
podTemplate(label: label, yaml: """
spec:
      containers:
      - name: mvn
        image: maven:3.3.9-jdk-8

Arinerron

#!/bin/bash

# Give the usual warning.
clear;
echo "[INFO] Automated Android root script started.\n\n[WARN] Exploit requires sdk module \"NDK\".\nFor more information, visit the installation guide @ https://goo.gl/E2nmLF\n[INFO] Press Ctrl+C to stop the script if you need to install the NDK module. Waiting 10 seconds...";
sleep 10;
clear;

# Download and extract exploit files.
echo "[INFO] Downloading exploit files from GitHub...";