gregyjames

public static void Main(String[] args)
{
    try {
        Curl.GlobalInit((int)CURLinitFlag.CURL_GLOBAL_ALL);

        Easy easy = new Easy();
        Easy.WriteFunction wf = new Easy.WriteFunction(OnWriteData);

        easy.SetOpt(CURLoption.CURLOPT_URL, args[0]);
        easy.SetOpt(CURLoption.CURLOPT_WRITEFUNCTION, wf);

gregyjames

#include <MIDI.h>
#include <SoftwareSerial.h>
#include <DFPlayer_Mini_Mp3.h>
#include <math.h>

SoftwareSerial mySerial(11, 10); // RX, TX

MIDI_CREATE_DEFAULT_INSTANCE();

bool isMp3Mode = false;

gregyjames

#include <MIDI.h>
#include <SoftwareSerial.h>
#include <DFPlayer_Mini_Mp3.h>
#include <math.h>

SoftwareSerial mySerial(11, 10); // RX, TX

MIDI_CREATE_DEFAULT_INSTANCE();

bool isMp3Mode = false;

gregyjames

#include <iostream>
using namespace std;
template <class etype>
class queue
{
    class qnode
    {
      public:

        etype element;

gregyjames

#include <algorithm>

//Array to sort
int arr = []

//Get length of array
const int length = sizeof(arr)/sizeof(arr[0]);
int count = length;
bool swapped = false;

gregyjames

Perceptron <- function(data, learningRate) {
  #Make the weights vector with 0s for each data coloumn
  w <- c(rep(0, ncol(data) -1))
  #The number of rows in the dataframe
  n <- nrow(data)
  #Get the labels from the dataframe
  label <- data[ , 1]
  #Get the data from from the dataframe
  obs <- data[ , 2:ncol(data)]
  #We start assuming that the data is misclassifies

gregyjames

#!/bin/bash

#Get all files in the directory
for file in *
do
	#Get the filenames and extensions
	filename=$(basename -- "$file")
	extension="${filename##*.}"
	
	#If the file isn't the cleaning script

gregyjames

"""Simple but robust implementation of generator/coroutine-based
pipelines in Python. The pipelines may be run either sequentially
(single-threaded) or in parallel (one thread per pipeline stage).

This implementation supports pipeline bubbles (indications that the
processing for a certain item should abort). To use them, yield the
BUBBLE constant from any stage coroutine except the last.

In the parallel case, the implementation transparently handles thread
shutdown when the processing is complete and when a stage raises an

gregyjames

import time

start = time.time()
# [OPERATION]
end = time.time()

exec_time = end-start

gregyjames

#include <iostream>
#include "Python.h"

int main()
{
	//Initialize the python instance
	Py_Initialize();
	
	//Run a simple string
	PyRun_SimpleString("from time import time,ctime\n"