Skip to content

Instantly share code, notes, and snippets.

View podviaznikov's full-sized avatar
🗽
NYC, hacking, thinking, observing, feeling

anton podviaznikov

🗽
NYC, hacking, thinking, observing, feeling
View GitHub Profile
@staltz
staltz / introrx.md
Last active March 29, 2024 06:13
The introduction to Reactive Programming you've been missing
@dergachev
dergachev / GIF-Screencast-OSX.md
Last active March 29, 2024 03:45
OS X Screencast to animated GIF

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Screencapture GIF

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

@jboner
jboner / latency.txt
Last active March 29, 2024 01:48
Latency Numbers Every Programmer Should Know
Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns 3 us
Send 1K bytes over 1 Gbps network 10,000 ns 10 us
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD

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.

@leonardofed
leonardofed / README.md
Last active March 28, 2024 17:32
A curated list of AWS resources to prepare for the AWS Certifications


A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.


@hellerbarde
hellerbarde / latency.markdown
Created May 31, 2012 13:16 — forked from jboner/latency.txt
Latency numbers every programmer should know

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

@enricofoltran
enricofoltran / main.go
Last active March 23, 2024 16:41
A simple golang web server with basic logging, tracing, health check, graceful shutdown and zero dependencies
package main
import (
"context"
"flag"
"fmt"
"log"
"net/http"
"os"
"os/signal"
@kconner
kconner / macOS Internals.md
Last active March 22, 2024 22:58
macOS Internals

macOS Internals

Understand your Mac and iPhone more deeply by tracing the evolution of Mac OS X from prelease to Swift. John Siracusa delivers the details.

Starting Points

How to use this gist

You've got two main options:

@debasishg
debasishg / gist:8172796
Last active March 15, 2024 15:05
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
@john2x
john2x / 00_destructuring.md
Last active March 15, 2024 14:24
Clojure Destructuring Tutorial and Cheat Sheet

Clojure Destructuring Tutorial and Cheat Sheet

(Related blog post)

Simply put, destructuring in Clojure is a way extract values from a datastructure and bind them to symbols, without having to explicitly traverse the datstructure. It allows for elegant and concise Clojure code.

Vectors and Sequences