theredpea

What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

• An active AWS account. First time sign-ups are eligible for the free tier for a year
• One Micro Tier EC2 Instance
• With AWS we will use the stock Ubuntu Server AMI and customize it.
• Anaconda for Python.
• Coffee/Beer/Time

gdamjan

import aiohttp
import asyncio

async def get_body(url):
    response = await aiohttp.request('GET', url)
    raw_html = await response.read()
    return raw_html

async def main():
    # run them sequentially (but the loop can do other stuff in the meanwhile)

0XDE57

ABOUT

about:config settings to harden the Firefox browser. Privacy and performance enhancements.
To change these settings type 'about:config' in the url bar. Then search the setting you would like to change and modify the value. Some settings may break certain websites from functioning and rendering normally. Some settings may also make firefox unstable. I am not liable for any damages/loss of data.

Not all these changes are necessary and will be dependent upon your usage and hardware. Do some research on settings if you don't understand what they do. These settings are best combined with your standard privacy extensions (HTTPS Everywhere No longer required: Enable HTTPS-Only Mode, NoScript/Request Policy, uBlock origin, agent spoofing, Privacy Badger etc), and all plugins set to "Ask To Activate".

ptarjan

Scaling your API with rate limiters

The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.

In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.

Request rate limiter

This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.