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EHOSTUNREACH

Mridul Singhai singhai0

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EHOSTUNREACH
  • San Francisco, CA
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@clayton
clayton / ffmpeg-install.sh
Created Aug 9, 2013
Install FFMPEG on OS X with HomeBrew to convert Mp4 to WebM
View ffmpeg-install.sh
# Installation
brew install ffmpeg --with-vpx --with-vorbis --with-libvorbis --with-vpx --with-vorbis --with-theora --with-libogg --with-libvorbis --with-gpl --with-version3 --with-nonfree --with-postproc --with-libaacplus --with-libass --with-libcelt --with-libfaac --with-libfdk-aac --with-libfreetype --with-libmp3lame --with-libopencore-amrnb --with-libopencore-amrwb --with-libopenjpeg --with-openssl --with-libopus --with-libschroedinger --with-libspeex --with-libtheora --with-libvo-aacenc --with-libvorbis --with-libvpx --with-libx264 --with-libxvid
# Easy Peasy
ffmpeg -i video.mp4 video.webm
@CMCDragonkai
CMCDragonkai / http_streaming.md
Last active May 6, 2021
HTTP Streaming (or Chunked vs Store & Forward)
View http_streaming.md

HTTP Streaming (or Chunked vs Store & Forward)

The standard way of understanding the HTTP protocol is via the request reply pattern. Each HTTP transaction consists of a finitely bounded HTTP request and a finitely bounded HTTP response.

However it's also possible for both parts of an HTTP 1.1 transaction to stream their possibly infinitely bounded data. The advantages is that the sender can send data that is beyond the sender's memory limit, and the receiver can act on

@gene1wood
gene1wood / 01_get_account_id_for_user_ec2instance_role_or_lambda.py
Last active May 9, 2021
Method to determine your AWS account ID using boto3 for either a user or an ec2 instance or lambda function
View 01_get_account_id_for_user_ec2instance_role_or_lambda.py
import boto3
print(boto3.client('sts').get_caller_identity()['Account'])
@rogerallen
rogerallen / us_state_abbrev.py
Last active May 12, 2021
A Python Dictionary to translate US States to Two letter codes
View us_state_abbrev.py
# United States of America Python Dictionary to translate States,
# Districts & Territories to Two-Letter codes and vice versa.
#
# https://gist.github.com/rogerallen/1583593
#
# Dedicated to the public domain. To the extent possible under law,
# Roger Allen has waived all copyright and related or neighboring
# rights to this code.
us_state_abbrev = {
@gaearon
gaearon / modern_js.md
Last active May 14, 2021
Modern JavaScript in React Documentation
View modern_js.md

If you haven’t worked with JavaScript in the last few years, these three points should give you enough knowledge to feel comfortable reading the React documentation:

  • We define variables with let and const statements. For the purposes of the React documentation, you can consider them equivalent to var.
  • We use the class keyword to define JavaScript classes. There are two things worth remembering about them. Firstly, unlike with objects, you don't need to put commas between class method definitions. Secondly, unlike many other languages with classes, in JavaScript the value of this in a method [depends on how it is called](https://developer.mozilla.org/en-US/docs/Web/Jav
View Effective_Engineer.md

FWIW: I'm not the author of the content presented here (which is an outline from Edmond Lau's book). I've just copy-pasted it from somewhere over the Internet, but I cannot remember what exactly the original source is. I was also not able to find the author's name, so I cannot give him/her the proper credits.


Effective Engineer - Notes

What's an Effective Engineer?

View 0-rate-limiters.md

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.