| terraform/ | |
| ├── backend.tf | |
| └── components | |
| ├── component_a | |
| │ ├── exports.tf | |
| │ └── main.tf | |
| ├── component_b | |
| │ ├── exports.tf | |
| │ └── main.tf | |
| └── shared |
| # backend.tf | |
| bucket = "studio.voltron.project.tfstate" | |
| region = "ap-southeast-2" | |
| key = "terraform.tf" | |
| dynamodb_table = "terraform-state-locks" | |
| profile = "voltronstudio-master" | |
| # Backends must be baked in during the initialization step: | |
| # | |
| # terraform init --backend-config=backend.tf |
| data "terraform_remote_state" "vpc" { | |
| backend = "s3" | |
| config { | |
| bucket = "networking-terraform-state-files" | |
| key = "vpc-prod.terraform.tfstate" | |
| region = "us-east-1" | |
| } | |
| } | |
| data.terraform_remote_state.vpc.private_subnet_ids |
| resource "aws_ssm_parameter" "sqs_http_proxy_id" { | |
| name = "/voltron/shared/sqs/http-proxy/id" | |
| type = "String" | |
| value = module.sqs_http_proxy.id | |
| overwrite = true | |
| } | |
| data "aws_ssm_parameter" "sqs_http_proxy_queue_url" { | |
| name = "/voltron/shared/sqs/http-proxy/id" | |
| } |
| terraform { | |
| required_version = ">= 0.13" | |
| } | |
| provider "aws" { | |
| version = "~> 3.0" | |
| region = "ap-southeast-2" | |
| } | |
| resource "aws_s3_bucket" "b" { |
| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| import json | |
| import base64 | |
| import urllib.request | |
| url_request = urllib.request.Request('http://demo.networkoptix.com:7001/ec2/getCamerasEx') | |
| url_request.add_header('Authorization', f'Basic {base64.b64encode(b"demo:nxwitness").decode("utf-8")}') | |
| response = urllib.request.urlopen(url_request) |
Your task is to build an image processing service. A client may send one or many images to your service in the form of JSON. Your service makes an API call to a deep learning platform to detect classes in a set of images. Once the detection is complete, the client gets back a JSON object containing the classes and confidence values of each image sent. For example:
Request:
{
"images": [
"http://example.com/image1",
You're lonely and bored. Your doritos are stale and no one is online, this loneliness you feel has a cure...A TAMAGOTCHI!
For those of you who have never heard of a Tamagotchi, here's a quick summary:
A tamagotchi is a virtual pet whose life you must sustain through various activities including eating, playing, making it sleep etc. Tamagotchi's go through several life cycles, most notably, egg/infant, teen, adult, elderly. Tamagotchi's can die from lack of attention (in the classic ones, half a day of neglect would kill it) and also from age. For more information check the wiki http://en.wikipedia.org/wiki/Tamagotchi
Your job is to create a tamagotchi via the command line. The goal is to see how you handle open ended design requirements.
This gist describes my commit message structure. Its primarily based off AngularJS's commit message guidelines with a few alterations. You can check out their guidelines for more information here.
type(scope): [<id>] <message>
<new_line>
[<body>]