dhanush

package main

func main() {
	conn := comms.NewConnection("my-producer", "my-exchange", []string{"queue-1", "queue-2"})
	if err := conn.Connect(); err != nil {
		panic(err)
	}
	if err := conn.BindQueue(); err != nil {
		panic(err)
	}

dhanush

package main 

import (
	"comms"
	"github.com/streadway/amqp"
	"log"
)

func main() {
	forever := make(chan bool)

dhanush

package comms

//Publish publishes a request to the amqp queue
func (c *Connection) Publish(m Message) error {
	select { //non blocking channel - if there is no error will go to default where we do nothing
	case err := <-c.err:
		if err != nil {
			c.Reconnect()
		}
	default:

dhanush

package comms
//Consume consumes the messages from the queues and passes it as map of chan of amqp.Delivery
func (c *Connection) Consume() (map[string]<-chan amqp.Delivery, error) {
	m := make(map[string]<-chan amqp.Delivery)
	for _, q := range c.queues {
		deliveries, err := c.channel.Consume(q, "", false, false, false, false, nil)
		if err != nil {
			return nil ,err
		}
		m[q] = deliveries

dhanush

package comms

import (
	"errors"
	"fmt"
	"github.com/streadway/amqp"
)

//MessageBody is the struct for the body passed in the AMQP message. The type will be set on the Request header
type MessageBody struct {

dhanush

func BuildImage(dockerBuildCtxDir, tagName string) error {
	ctx, cancel := context.WithTimeout(context.Background(), time.Duration(300)*time.Second)
	defer cancel()
	dockerFileTarReader, err := tarDirectory(dockerBuildCtxDir) 
        //this above method will create a tar file from the directory passed in. The return has to be of type io.Reader
	if err != nil {
		log.Printf("Error in taring the docker root folder - %s", err.Error())
		return err
	}
	buildArgs := make(map[string]*string)

dhanush

FROM alpine:3.8
RUN apk update

RUN mkdir -p /tmp/dhanush
WORKDIR /tmp/dhanush

COPY ./test.exe ./
COPY ./test.env ./

ENTRYPOINT [ "/tmp/dhanush/test.exe" ]

dhanush

func downloadMultipleFiles(urls []string) ([][]byte, error) {
	done := make(chan []byte, len(urls))
	errch := make(chan error, len(urls))
	for _, URL := range urls {
		go func(URL string) {
			b, err := downloadFile(URL)
			if err != nil {
				errch <- err
				done <- nil
				return

dhanush

func downloadFile(URL string) ([]byte, error) {
	response, err := http.Get(URL)
	if err != nil {
		return nil, err
	}
        defer response.Body.Close()
	if response.StatusCode != http.StatusOK {
		return nil, errors.New(response.Status)
	}
	var data bytes.Buffer

dhanush

import pandas
import math
from numpy.random import permutation
from sklearn import svm

x_cols = [] #array of all the features (column names in the file) we use to predict
y_cols = ['role'] #to be predicted item

#Create Pandas dataframe
training_data_frame = pandas.read_csv('train.csv')