physacco

Python 3 extension example

Build

python3 setup.py build

Output: build/lib.macosx-10.11-x86_64-3.5/hello.cpython-35m-darwin.so

Run

lanrat

[main]
plugins=ifupdown,keyfile

[ifupdown]
managed=false

[keyfile]
unmanaged-devices=interface-name:docker0;interface-name:vmnet1;interface-name:vmnet8;interface-name:vboxnet0

drmalex07

README

The example below creates a TCP server listening on a stream (i.e. SOCK_STREAM) socket. A similar approach can be followed to create a UDP server on a datagram (i.e. SOCK_DGRAM) socket. See man systemd.socket for details.

An example server

Create an simple echo server at /opt/foo/serve.py.

kingluo

$ erlc processes.erl
$ erl -noshell -s processes test -s init stop
the max processes is 262144 
the proecess time is 2.0:3.57
$ erl -noshell -s processes test2 100000 -s init stop
the max processes is 262144 
{"init terminating in do_boot",{system_limit,[{erlang,spawn,[erlang,apply,[#Fun<processes.2.26012808>,[]]],[]},{erlang,spawn,1,[]},{processes,for,3,[{file,"processes.erl"},{line,24}]},{processes,for,3,[{file,"processes.erl"},{line,24}]},{processes,max,1,[{file,"processes.erl"},{line,10}]},{init,start_it,1,[]},{init,start_em,1,[]}]}}

# program freeze here...
# Ctrl+C not work

CMCDragonkai

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

scottslowe

# Ubuntu Server automated installation
# by Scott Lowe ([email protected])

d-i debian-installer/locale string en_US
d-i console-setup/ask_detect boolean false
d-i keyboard-configuration/layoutcode string us
d-i netcfg/choose_interface select eth0
d-i netcfg/get_hostname string hostname
d-i netcfg/get_domain string domain.com 
d-i netcfg/wireless_wep string

mbaldessari

#include <stdio.h>
#include <stdint.h>
#include <string.h>
#include <sys/ioctl.h>
#include <sys/stat.h>
#include <net/if.h>
#include <ctype.h>

#define ETHTOOL_GSET    0x1
#define SIOCETHTOOL     0x8946

vishvananda

Overview

For those that are unfamiliar with the project, PyPy is an implementation of the Python language that features a JIT Compiler. I have noticed a huge performance benefit in some personal projects by switching to PyPy. I have always been curious how it would perform on a large and complex project like OpenStack, but my early experiments ran into massive roadblocks around broken dependencies.

It has been six months since I last looked, so I figured it was time to try it again. Support has come a long way and, now that lxml is working, we are close enough to get a Proof-of-Concept running. Read on for instructions on running nova with PyPy.

Preparation

Start out with a base ubuntu 12.04 (precise) install and run devstack. I won't go through the details of getting devstack running here, because there are already instructions on the devstack site.

Forst

#!/bin/bash

## FORSTWOOF UBUNTU PRESEED :: BUILD SCRIPT

# Quit on first error
set -e

# Temporary directory for the build
TMP="/var/tmp/ubuntu-build"

jongwook

========================================================================
   BYTE UNIX Benchmarks (Version 5.1.3)

   System: ip-172-31-43-143: GNU/Linux
   OS: GNU/Linux -- 3.14.35-28.38.amzn1.x86_64 -- #1 SMP Wed Mar 11 22:50:37 UTC 2015
   Machine: x86_64 (x86_64)
   Language: en_US.utf8 (charmap="UTF-8", collate="UTF-8")
   CPU 0: Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz (5000.1 bogomips)
          Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
   13:44:50 up 43 min,  2 users,  load average: 0.78, 0.62, 0.33; runlevel 3