Gabriel Cardona cgcardona

Generating a new keypair

TODO

When you have a type which is an array of objects you can access the object's properties by using the dot notation. For example:

let foo = {
  arrKey: [{key: "value"}]
}

foo.arrKey[0].key // "value"

Exposing a port to the Web and port forwarding on EC2

By default a new AWS EC2 instance only exposes port 22 to the Web to enable accessing the new EC2 instance via ssh. Often it's helpful to open other ports to the Web so that you can access them via a browser. This tutorial shows 2 different ways of exposing ports on AWS EC2 instances.

Additionally if you're not interested in exposing a port to the Web but would still like to access it via your browser you can use port forwarding in VS Code which is covered in the final section below.

Exposing a port to the Web on an AWS instance

When launching a new EC2 instance, fill out the following items

Query the trader joe v2 subgraph

List the symbol of all tokens

GraqhQL

Request

$RUN

Slides

https://docs.google.com/presentation/d/1az-hY7Zas2lEQm0jS6laDcoxnJz__FxM0uNd7Gqy5ec/edit?usp=sharing

Introduction

Let's go ahead and get started. My name is Gabriel Cardona and I am a Developer Evangelist from Ava Labs. I'm on the Developer Relations Squad. We are led by the amazing Luigi Demeo and the team now consists of Usman, Martin, Meaghan, Andrea and myself. Our goal is to accelerate the adoption of Avalanche by developers by providing resources needed for devs to go from idea to application and from hobbyist to professional. We are always hiring so check out https://www.avalabs.org/careers to see which opening we have on the DevRel Squad and across all of Ava Labs.

	import { Avalanche, BN, Buffer } from "avalanche/dist"
	import {
	AVMAPI,
	KeyChain,
	UTXOSet,
	UnsignedTx,
	Tx,
	KeyPair,
	SelectCredentialClass
	} from "avalanche/dist/apis/avm"

	import { Avalanche, BN, Buffer } from "avalanche/dist"
	import {
	AVMAPI,
	KeyChain,
	UTXOSet,
	UnsignedTx,
	Tx
	} from "avalanche/dist/apis/avm"
	import {
	GetBalanceResponse,

	# all the imports
	import io, torch, time, math, os

	# import specified modules
	from flask import Flask, request, send_file
	from torch import autocast
	from diffusers import StableDiffusionPipeline

	# create a new flask app
	app = Flask(__name__)

	# all the imports
	import torch, time, math, os

	# import specified modules
	from torch import autocast
	from diffusers import StableDiffusionPipeline

	# confirm GPU supports the NVIDIA machine learning toolkit
	assert torch.cuda.is_available()
	# Stable Diffusion v1.4: CompVis/stable-diffusion-v1-4

	import { task } from "hardhat/config"
	import { SignerWithAddress } from "@nomiclabs/hardhat-ethers/signers"
	import { BigNumber } from "ethers"
	import "@nomiclabs/hardhat-waffle"

	// When using the hardhat network, you may choose to fork Fuji or Avalanche Mainnet
	// This will allow you to debug contracts using the hardhat network while keeping the current network state
	// To enable forking, turn one of these booleans on, and then run your tasks/scripts using ``--network hardhat``
	// For more information go to the hardhat guide
	// https://hardhat.org/hardhat-network/