(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.
The script is here:
#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"
2015-01-29 Unofficial Relay FAQ
Compilation of questions and answers about Relay from React.js Conf.
Disclaimer: I work on Relay at Facebook. Relay is a complex system on which we're iterating aggressively. I'll do my best here to provide accurate, useful answers, but the details are subject to change. I may also be wrong. Feedback and additional questions are welcome.
Relay is a new framework from Facebook that provides data-fetching functionality for React applications. It was announced at React.js Conf (January 2015).
This benchmark has been misleading for a while. It was originally made to demonstrate how JIT compilers can do all sorts of crazy stuff to your code - especially LuaJIT - and was meant to be a starting point of discussion about what exactly LuaJIT does and how.
As a result, its not indicative of what its performance may be on more realistic data. Differences can be expected because
Basic unit type:
λ> replTy "()"
() :: ()
Basic functions:
... or Why Pipelining Is Not That Easy
Golang Concurrency Patterns for brave and smart.
By @kachayev
webserver: webserver.c libuv/uv.a http-parser/http_parser.o | |
gcc -I libuv/include \ | |
-lrt -lm -lpthread -o \ | |
webserver webserver.c \ | |
libuv/uv.a http-parser/http_parser.o | |
libuv/uv.a: | |
$(MAKE) -C libuv | |
http-parser/http_parser.o: |
# Thee will be more information here when I share the entire problem space I'm working on, but | |
# in short, this is preview material for my second talk in a series called "What Computer Scientists Know". | |
# The first talk is on recursion, and goes through several examples., leading up to a problem based | |
# on a simple puzzle that initial estimates based on performance of a previous puzzle would take years | |
# to solve on modern computers with the techniques shown in Ruby. That sets the stage for improving the | |
# performance of that problem with threading, concurrency, and related tuning. | |
# | |
# The second talk is on threading and concurrency, touching on algorithmic performance as well. | |
# Using some knowledge of the problem (board symmetry, illegal moves, etc), we reduce the problem space | |
# to about .5% of what we initially thought it was. Still, the initial single threaded solution took more |