Multirust is a system for managing multiple installs of the Rust compiler and Cargo, the Rust package manager.
By default multirust installs into /usr/local, we will be installing into our home directory to avoid giving multirust any unneccesary privledges.
brew install gpggit clone https://github.com/brson/multirust.gitcd multirust
mkdir ~/rustbase
| # | |
| # read/write access to python's memory, using a custom bytearray. | |
| # some code taken from: http://tinyurl.com/q7duzxj | |
| # | |
| # tested on: | |
| # Python 2.7.10, ubuntu 32bit | |
| # Python 2.7.8, win32 | |
| # | |
| # example of correct output: | |
| # inspecting int=0x41424344, at 0x0228f898 |
Add Graal JIT Compilation to Your JVM Language in 5 Steps, A Tutorial http://stefan-marr.de/2015/11/add-graal-jit-compilation-to-your-jvm-language-in-5-easy-steps-step-1/
The SimpleLanguage, an example of using Truffle with great JavaDocs. It is the officle getting-started project: https://github.com/graalvm/simplelanguage
Truffle Tutorial, Christan Wimmer, PLDI 2016, 3h recording https://youtu.be/FJY96_6Y3a4 Slides
From a lecture by Professor John Ousterhout at Stanford.
Programmers tend to worry too much and too soon about performance. Many college-level Computer Science classes focus on fancy algorithms to improve performance, but in real life performance rarely matters. Most real-world programs run plenty fast enough on today's machines without any particular attention to performance. The real challenges are getting programs completed quickly, ensuring their quality, and managing the complexity of large applications. Thus the primary design criterion for software should be simplicity, not speed.
> Occasionally there will be parts of a program where performance matters, but you probably won't be able to predict where the performance issues will occur. If you try to optimize the performance of an application during the initial construction you will add complexity that will impact the timely delivery and quality o
| #define _GNU_SOURCE 1 | |
| #include <sched.h> // sched_setaffinity | |
| #include <stdint.h> | |
| #include <stdio.h> | |
| #include <limits.h> | |
| #include <stdlib.h> | |
| #include <stdint.h> | |
| #include <pthread.h> | |
| #include <assert.h> | |
| #include <sys/time.h> |
An example of using the Watson Speech to Text API to translate a podcast from ProPublica: How a Reporter Pierced the Hype Behind Theranos
This is just a simpler demo of the same technique I demonstrate to make automated video supercuts in this repo: https://github.com/dannguyen/watson-word-watcher
The transcription takes just a few minutes (less if you parallelize the requests to IBM) and is free...but it isn't perfect by any means. It doesn't fare super well on proper nouns:
Basic opinionated Python code technique guide. For lower level naming and structure, see https://github.com/amontalenti/elements-of-python-style
Install deps with pip managed by virtualenv, this decouples the VM from the runtime. Try not to target the latest VM release, this prevents your code from being trivially installable on existing Ubuntu and Centos systems. Use tox and py.test (see below) to confirm that decoupling.
Immutable, named lightweight composite containers for your data. Removes magic numbers from your code.
