hellerbarde

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

ronnix

from collections import defaultdict
from threading import Thread

import redis

import tornado.web


class SomeRequestHandler(tornado.web.RequestHandler):

bwhite

"""Information Retrieval metrics

Useful Resources:
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
http://www.nii.ac.jp/TechReports/05-014E.pdf
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
Learning to Rank for Information Retrieval (Tie-Yan Liu)
"""
import numpy as np

lbolla

Asynchronous programming with Tornado

Asynchronous programming can be tricky for beginners, therefore I think it's useful to iron some basic concepts to avoid common pitfalls.

For an explanation about generic asynchronous programming, I recommend you one of the [many][2] [resources][3] [online][4].

I will focus on solely on asynchronous programming in [Tornado][1]. From Tornado's homepage:

awidegreen

Introduction

• C-a == Ctrl-a
• M-a == Alt-a

General

:q        close
:w        write/saves
:wa[!]    write/save all windows [force]
:wq       write/save and close

brentp

from sklearn import linear_model
from scipy import stats
import numpy as np


class LinearRegression(linear_model.LinearRegression):
    """
    LinearRegression class after sklearn's, but calculate t-statistics
    and p-values for model coefficients (betas).
    Additional attributes available after .fit()

eskriett

#!/usr/bin/python
# GoogleMapDownloader.py 
# Created by Hayden Eskriett [http://eskriett.com]
#
# A script which when given a longitude, latitude and zoom level downloads a
# high resolution google map
# Find the associated blog post at: http://blog.eskriett.com/2013/07/19/downloading-google-maps/

import urllib
import Image

aflaxman

ivanacostarubio

# Ruby 1.9 using ruby-ni
#
# VERSION               0.0.1
#
FROM      base
MAINTAINER Ivan Acosta-Rubio "ivan@softwarecriollo.com"

ADD https://gist.github.com/ivanacostarubio/9309be8a79a94aafd02d/raw/8e84fac50a57a23f191eccf5e41bae4ecde80873/gistfile1.txt /etc/resolv.conf 

# Installing basic stuf: wget, git, ruby

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)