Yiftach

Redis Cloud is a fully-managed cloud service for hosting and running your Redis dataset in a highly-available and scalable manner, with predictable and stable top performance. You can quickly and easily get your apps up and running with Redis Cloud through its add-on for Heroku, just tell us how much memory you need and get started instantly with your first Redis database. You can then add more Redis databases (each running in a dedicated process, in a non-blocking manner) and increase or decrease the memory size of your plan without affecting your existing data.

Redis Cloud offers true high-availability with its in-memory dataset replication and instant auto-failover mechanism, combined with its fast storage engine. You can easily import an existing dataset to any of your Redis Cloud databases, from your S3 account or from any other Redis server. Daily backups are performed automatically and in addition, you can backup your dataset manually at any given time. The service

paulallies

#add 'node_modules' to .gitignore file

git rm -r --cached node_modules
git commit -m 'Remove the now ignored directory node_modules'
git push origin <branch-name>

pierrejoubert73

How to add a collapsible section in markdown

1. Example

Click me

Heading

1. Foo
2. Bar
   • Baz

• Qux

sanjeevshrestha

telegraf:
  image: telegraf
  restart: always
  environment:
    HOST_PROC: /rootfs/proc
    HOST_SYS: /rootfs/sys
    HOST_ETC: /rootfs/etc
  hostname: localhost
  volumes:
   - ./telegraf/telegraf.conf:/etc/telegraf/telegraf.conf:ro

simonw

Datasette for Polar Bears

I found an interesting looking dataset about Polar Bear ear tag tracking on a USGS website: https://alaska.usgs.gov/products/data.php?dataid=130

I deployed it as a datasette website and API here: https://polar-bears.now.sh/

Here's how I did it:

0. Install datasette and csvs-to-sqlite:

korakot

import re
import pandas as pd
from google.cloud import bigquery
from google.colab import auth

PROJECT_ID = 'sql-hunt'  # change to your own project

class BqTable:
  
  def __init__(self, table, dataset='samples', active_project='bigquery-public-data', client=None):

corinneling

Node JS Web Scraper

I this is part of the first node web scraper I created with axios and cheerio. I took out all of the logic, since I only wanted to showcase how a basic setup for a nodejs web scraper would look.

const cheerio = require('cheerio'),
      axios = require('axios'),
      url = `<url goes here>`;
 

Tynael

A brief example on how to use npx to run gist based scripts.

Read the article here https://neutrondev.com/npm-vs-npx-whats-the-difference/ or watch it on YouTube https://www.youtube.com/watch?v=fSHWc8RTJug

kenmoini

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: admin-user
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: cluster-admin
subjects:
- kind: ServiceAccount

alexellis

from flask import Flask
app = Flask(__name__)
import unicornhat as UH
import time
import os
import signal
import sys

def clear_uh():
    UH.clear()