doron2402

1. https://ops.tips/blog/sending-files-via-grpc/
2. https://bbengfort.github.io/programmer/2017/03/03/secure-grpc.html
3. https://grpc.io/docs/tutorials/basic/node/

doron2402

package main

import (
	"errors"
	"fmt"
)

type Promise struct {
	successChannel chan interface{}
	failureChannel chan error

doron2402

package main

import (
	"crypto/rand"
	"encoding/binary"
	"log"
	"net/http"
)

// GenerateUint64 - generate a random uint64

doron2402

#!/usr/bin/env python3

import asyncio
import time
  
async def count():
    print("One")
    await asyncio.sleep(1)
    print("Two")

doron2402

import asyncio
from aiohttp import web
from asyncnsq import create_reader
from asyncnsq.utils import get_logger

# Handle request
async def handle_echo(reader, writer):
    data = await reader.read(100)
    message = data.decode()
    addr = writer.get_extra_info('peername')

doron2402

'use strict';
/**
For full repo go to: 
https://github.com/doron2402/simple-upload-files
**/
const http = require('http');

const uploaderRoute = require('./routes/uploader');
const formRoute = require('./routes/form');
const notFoundRoute = require('./routes/notFound');

doron2402

package main

import "fmt"

type person struct {
	firstName string
	lastName  string
	age       float32
	id        int
}

doron2402

# Polynomial Regression
# Number Of Vodka Shots Vs Tip
dataset = read.csv('./shots_tip.csv')


# Let's fit the data to a Linear Regression Model
linear_regressor = lm(formula = Tip ~ NumberOfShots,
                      data = dataset)

doron2402

doron2402

# Multiple Linear Regression

# Importing the dataset
dataset = read.csv('tip.csv')

# Encoding categorical data, in this case country 
dataset$Country = factor(dataset$Country,
                       levels = c('USA', 'England', 'France', 'Israel', 'Italy'),
                       labels = c(1, 2, 3, 4, 5))