harleyholt

import random
from imagination import count_soda, restock_soda

available_sodas = ['Sprite', 'Coke', 'Diet Coke', 'Dr. Pepper']

def take_soda(consumer):
    soda = random.choice(available_sodas)
    if count_soda(soda) < 2 and not consumer.is_dick():
        restock_soda(soda)
    else:

harleyholt

### BEGIN INIT INFO
# Provides:          gearman-job-server
# Required-Start:    $network $remote_fs $syslog mysql
# Required-Stop:     $network $remote_fs $syslog
# Default-Start:     2 3 4 5
# Default-Stop:      0 1 6
# Short-Description: Start daemon at boot time
# Description:       Enable gearman job server
### END INIT INFO

harleyholt

from gearman import GearmanClient

# create a client that will connect to the Gearman server running on
# localhost. The array allows you to specify a set of job servers.
client = GearmanClient(['127.0.0.1'])

# Submit a synchronous job request to the job server and store the
# result.
# This runs the "echo" job on the argument "foo"
result = client.submit_job('echo', 'foo')

harleyholt

from gearman import GearmanWorker

# The function that will do the work
def echoer(worker, job):
    print job.data
    return job.data

# Establish a connection with the job server on localhost--like the client,
# multiple job servers can be used.
worker = GearmanWorker(['127.0.0.1'])

harleyholt

/**
 * One way of specifying the analytic endpoint data. 
 * In this scheme, we can have multiple parallel time series returned.
 * Includes a summary object which allows us to return aggregated data for the series.
 * Includes a meta object which has information about the series (such as the units of measurement).
 *
 * The time series is specified as an array of values. This series can not be missing any values because it is in 
 * parallel to the generated time values. The API must take care of filling in any missing values of the time
 * series before returning it.
 *

harleyholt

/**
 * Example of a summary only data API return. The returned information contains the aggregate information.
 * The site value is the site that we are getting information for (it will not exist if the results are not filtered
 * to a specific site)
 * The time value contains the start and end of the sampling period while the resolution tells the client what the aggregate 
 * period is for the client
 */
{
    site: example.com,
    time: {

harleyholt

from django.db import connections

arguments = ('one', 'two', 'three', '...')

cursor = connections['example-db'].cursor()
try:
    cursor.callproc('proc_name', arguments)
    results = cursor.fetchall()
finally: 
    cursor.close()

harleyholt

mysqldump <database-name> [<table1> ... <tableN>] --routines > output.sql

harleyholt

<!-- Example one shows the most verbose way of specifying a template that is only rendered if someObject is defined in the current view model 

This information was culled from https://github.com/SteveSanderson/knockout/blob/1.3/src/binding/defaultBindings.js#L445
-->
<script type="text/html" id="sub-example-one">
  <h2 data-bind="text: title"></h2>
  <p data-bine="text: description"></p>
</script>

<script type="text/html" id="example-one">

harleyholt

select 
	row_type_cd,
    row_sub_type_cd,
	date_pst,
	publisher_id,
	site_id,
    case
        when user_type_cd = 'C' then 'control'
        when user_type_cd = 'T' then 'test'
        else 'other'