astuyve

{
"Version": "2012-10-17",
"Statement": [
    {
        "Effect": "Deny",
        "Action": [
            "logs:CreateLogGroup",
            "logs:CreateLogStream",
            "logs:PutLogEvents"
        ],

giautm

const { withDangerousMod, withPlugins } = require("@expo/config-plugins");
const {
  mergeContents,
} = require("@expo/config-plugins/build/utils/generateCode");
const fs = require("fs");
const path = require("path");

async function readFileAsync(path) {
  return fs.promises.readFile(path, "utf8");
}

TheRealFlyingCoder

So Github workflow for deploying a docker image to GCR, and subsequently pushing that to a cloud run instance is pretty easy

First just add your github tokens:

GCP_SERVICE_ID
GCP_PROJECT_ID
GCP_REGION <-- your services deploy region
GCP_SA_KEY <-- Follow the method in here (http://acaird.github.io/computers/2020/02/11/github-google-container-cloud-run)

Take note that my Dockerfile is specifically for an Express.js remix app, where Remix builds to `/server/build`.

romaninsh

# Add the following to your existing VPC CF stack

  # create 2 subnets, lambdas like to be in multiple subnets
  Private1:
    Type: AWS::EC2::Subnet
    Properties:
      VpcId: !Ref VPC
      AvailabilityZone: !Select [ 0, !GetAZs ]
      CidrBlock: !Ref Private1CIDR

tj

package main

import (
	"fmt"
	"net/http"

	"github.com/apex/go-apex"
	"github.com/apex/go-apex/proxy"
)

reggi

How to setup AWS lambda function to talk to the internet and VPC

I'm going to walk you through the steps for setting up a AWS Lambda to talk to the internet and a VPC. Let's dive in.

So it might be really unintuitive at first but lambda functions have three states.

1. No VPC, where it can talk openly to the web, but can't talk to any of your AWS services.
2. VPC, the default setting where the lambda function can talk to your AWS services but can't talk to the web.
3. VPC with NAT, The best of both worlds, AWS services and web.

seanbehan

create temporary table temp (symbol varchar(255), open decimal, high decimal, low decimal, close decimal, volume varchar(255), date date );

create table if not exists stocks (id serial primary key, symbol varchar(255), open decimal, high decimal, low decimal, close decimal, volume varchar(255), date date, created_at timestamp, updated_at timestamp);

copy temp (symbol, date, open, high, low, close, volume) from '/path/to/file.csv' with delimiter ',' csv header;

delete from stocks using temp where stocks.date = temp.date and stocks.symbol = temp.symbol;

insert into stocks (symbol, open, high, low, close, volume, date) select symbol, open, high, low, close, volume, date from temp;

jlafon

An introduction to DynamoDB

DynamoDB is a powerful, fully managed, low latency, NoSQL database service provided by Amazon. DynamoDB allows you to pay for dedicated throughput, with predictable performance for "any level of request traffic". Scalability is handled for you, and data is replicated across multiple availability zones automatically. Amazon handles all of the pain points associated with managing a distributed datastore for you, including replication, load balancing, provisioning, and backups. All that is left is for you to take your data, and its access patterns, and make it work in the denormalized world of NoSQL.

Modeling your data

The single most important part of using DynamoDB begins before you ever put data into it: designing the table(s) and keys. Keys (Amazon calls them primary keys) can be composed of one attribute, called a hash key, or a compound key called the hash and range key. The key is used to uniquely identify an item in a table. The choice of the primary key is particularl

Kartones

PSQL

Magic words:

psql -U postgres

Some interesting flags (to see all, use -h or --help depending on your psql version):

• -E: will describe the underlaying queries of the \ commands (cool for learning!)
• -l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)

vunb

ffmpeg -i input.mp3 -acodec pcm_s16le -ac 1 -ar 16000 output.wav

# To convert all mp3 files in a directory in Linux:

for f in *.mp3; do ffmpeg -i "$f" -acodec pcm_s16le -ac 1 -ar 16000 "${f%.mp3}.wav"; done

# Or Windows:

for /r %i in (*) do ffmpeg -i %i -acodec pcm_s16le -ac 1 -ar 16000 %i.wav