karmi

# ========================================
# Testing n-gram analysis in ElasticSearch
# ========================================

curl -X DELETE localhost:9200/ngram_test
curl -X PUT    localhost:9200/ngram_test -d '
{
  "settings" : {
    "index" : {
      "analysis" : {

lxneng

(env)~/env pip install pycurl
Downloading/unpacking pycurl
  Downloading pycurl-7.19.0.tar.gz (71Kb): 71Kb downloaded
  Running setup.py egg_info for package pycurl
    sh: curl-config: not found
    Traceback (most recent call last):
      File "<string>", line 14, in <module>
      File "/home/eric/env/build/pycurl/setup.py", line 90, in <module>
        raise Exception, ("`%s' not found -- please install the libcurl development files" % CURL_CONFIG)
    Exception: `curl-config' not found -- please install the libcurl development files

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

maccman

import os
from flask import Flask, render_template, request
import stripe

stripe_keys = {
  'secret_key': os.environ['SECRET_KEY'],
  'publishable_key': os.environ['PUBLISHABLE_KEY']
}

stripe.api_key = stripe_keys['secret_key']

sgergely

----- Esc -----
Quick change directory: Esc + c
Quick change directory history: Esc + c and then Esc + h
Quick change directory previous entry: Esc + c and then Esc + p
Command line history: Esc + h
Command line previous command: Esc + p
View change: Esc + t (each time you do this shortcut a new directory view will appear)
Print current working directory in command line: Esc + a
Switch between background command line and MC: Ctrl + o
Search/Go to directory in active panel: Esc + s / Ctrl + s then start typing directory name

KartikTalwar

The fastest remote directory rsync over ssh archival I can muster (40MB/s over 1gb NICs)

This creates an archive that does the following:

rsync (Everyone seems to like -z, but it is much slower for me)

• a: archive mode - rescursive, preserves owner, preserves permissions, preserves modification times, preserves group, copies symlinks as symlinks, preserves device files.
• H: preserves hard-links
• A: preserves ACLs

mystix

VERSION=0.20.6

sudo apt-get update
sudo apt-get install openjdk-6-jdk

wget https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-$VERSION.deb
sudo dpkg -i elasticsearch-$VERSION.deb

# be sure you add "action.disable_delete_all_indices" : true to the config!!

samklr

#! /bin/sh

### Must have Gcloud sdk installed and configured

###Create a micro instance as ansible master
gcloud compute --project $PROJECT_NAME instances create "ansible" --zone "us-central1-b" --machine-type "f1-micro" --network "default" --maintenance-policy "MIGRATE" --scopes "https://www.googleapis.com/auth/userinfo.email" "https://www.googleapis.com/auth/compute" "https://www.googleapis.com/auth/devstorage.full_control" --tags "http-server" "https-server" --no-boot-disk-auto-delete

###or a centos like in the tutorial
gcloud compute --project $PROJECT_NAME instances create "ansible-master" --zone "us-central1-b" --machine-type "g1-small" --network "default" --maintenance-policy "MIGRATE" --scopes "https://www.googleapis.com/auth/userinfo.email" "https://www.googleapis.com/auth/compute" "https://www.googleapis.com/auth/devstorage.full_control" --tags "http-server" "https-server" --image "https://www.googleapis.com/compute/v1/projects/centos-cloud/global/images/centos-7-v20140926" --no-boot-disk-auto-de

valyala

Optimizing postgresql table for more than 100K inserts per second

• Create UNLOGGED table. This reduces the amount of data written to persistent storage by up to 2x.
• Set WITH (autovacuum_enabled=false) on the table. This saves CPU time and IO bandwidth on useless vacuuming of the table (since we never DELETE or UPDATE the table).
• Insert rows with COPY FROM STDIN. This is the fastest possible approach to insert rows into table.
• Minimize the number of indexes in the table, since they slow down inserts. Usually an index on time timestamp with time zone is enough.
• Add synchronous_commit = off to postgresql.conf.
• Use table inheritance for fast removal of old data:

judotens

from __future__ import absolute_import
import os
from subprocess import Popen, PIPE
import datetime
import time 
from celery import Celery
from celery import states

from os.path import dirname, join