ipmb

upstream myapp {
    server 127.0.0.1:8081;
}

limit_req_zone $binary_remote_addr zone=login:10m rate=1r/s;

server {
    listen 443 ssl spdy;
    server_name _;
  

aidoom

#! /bin/sh

### BEGIN INIT INFO
# Provides:          IBController
# Short-Description: starts instance of IBController
# Description:       starts instance of IBController using start-stop-daemon
### END INIT INFO

############### EDIT ME ##################
# ini file

kyledrake

# The blog post that started it all: https://neocities.org/blog/the-fcc-is-now-rate-limited
#
# Current known FCC address ranges:
# https://news.ycombinator.com/item?id=7716915
#
# Confirm/locate FCC IP ranges with this: http://whois.arin.net/rest/net/NET-165-135-0-0-1/pft
#
# In your nginx.conf:

location / {

gustavla

# Author: Nelle Varoquaux, Andrew Tulloch

# Uses the pool adjacent violators algorithm (PAVA), with the
# enhancement of searching for the longest decreasing subsequence to
# pool at each step.

import numpy as np
cimport numpy as np
cimport cython

madjar

import asyncio
import aiohttp
import bs4
import tqdm


@asyncio.coroutine
def get(*args, **kwargs):
    response = yield from aiohttp.request('GET', *args, **kwargs)
    return (yield from response.read_and_close(decode=True))

revskill10

 /** @jsx React.DOM */

 var LopMonHoc = React.createClass({
 	getInitialState: function(){
 		return {data: []}
 	},
 	loadData: function(){
 		$.ajax({
 			url: '/daotao/lops',
 			success: function(data){

insin

/*

gulpfile from one of my React applications which has a gulp --production build
set up.

Assumptions:

  1. All your own .js/.jsx modules are somewhere under ./src, have unique
     filenames and use Node.js-style requires WITHOUT any path information, just
     the name of another module somewhere under ./src

mblondel

"""Kernel K-means"""

# Author: Mathieu Blondel <[email protected]>
# License: BSD 3 clause

import numpy as np

from sklearn.base import BaseEstimator, ClusterMixin
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils import check_random_state

andreif

Performance of Flask, Tornado, GEvent, and their combinations

Wensheng Wang, 10/1/11

Source: http://blog.wensheng.org/2011/10/performance-of-flask-tornado-gevent-and.html

When choosing a web framework, I pretty much have eyes set on Tornado. But I heard good things about Flask and Gevent. So I tested the performance of each and combinations of the three. I chose something just a little more advanced than a "Hello World" program to write - one that use templates. Here are the codes:

1, Pure Flask (pure_flask.py)

frankrowe

 import shapefile
   # read the shapefile
   reader = shapefile.Reader("my.shp")
   fields = reader.fields[1:]
   field_names = [field[0] for field in fields]
   buffer = []
   for sr in reader.shapeRecords():
       atr = dict(zip(field_names, sr.record))
       geom = sr.shape.__geo_interface__
       buffer.append(dict(type="Feature", \