Will Ware wware

An example of Python logging over a network, starting with an example from https://docs.python.org/2/howto/logging-cookbook.html.

This is very handy if you have a rack of servers and you want to aggregate logging statements from one or several of them to in some convenient place. This is especially handy if you're using an inversion-of-control framework (my own work these days is with Buildbot, which relies upon Twisted), because a lot of what's happening may be obscured, for instance by Deferreds but also possibly by

Output from this thing currently looks like this, but I'm interested in the possibility of throwing log records in an SQL database for purposes of sorting/filtering/searching, and presenting them with something like http://datatables.net.

Git Merge Lore

I'm working at a place where people prefer merges over rebases. In the past I've been influenced by the pro-rebase school of thought, but if there are relatively few pull requests being merged, you can use --no-ff to maintain pretty good clarity, and merge points become the decision point where a pull request has been included or excluded. With that in mind, I want to look at a few relevant use cases.

	#!/usr/bin/env python

	import logging
	from Queue import Empty
	from multiprocessing import Queue, Pool, Process

	logging.getLogger('').setLevel(logging.DEBUG)

	"""
	We can send instances thru Queues, and because the Queue is not a list,

	import time
	import multiprocessing

	POOLSIZE = 4
	N = 10
	mgr = multiprocessing.Manager()
	done = mgr.dict() # they don't implement sets. Thread-safe counter???

	# this MUST be a globally defined funcion
	def f(x):

	#!/usr/bin/env python

	from Crypto.Cipher import AES
	from Crypto import Random
	from struct import pack
	import argparse
	import base64
	import getpass
	import math
	import random

	import logging
	import pprint
	import traceback

	_sql = False
	try:
	import sqlalchemy
	import sqlparse
	_sql = True
	except ImportError:

	void print_double(double val)
	{
	char buf[10];
	int neg = (val < 0);
	int exponent = 0;
	if (val == 0.0) {
	Serial.print("0.0");
	return;
	}
	if (neg)

	import aifc
	import math
	import sys

	filename = sys.argv[1]

	F_SAMPLE = 40000
	DT = 1. / F_SAMPLE

	class Aiff:

	import doctest
	import numpy
	import sys


	def is_vector(x):
	return isinstance(x, numpy.ndarray) and x.shape == (3,)


	def normalize(vec):

	import pprint
	import logging


	def about(thang):
	def shorty(x):
	if len(x) > 200:
	x = x[:200] + "..."
	return x
	if isinstance(thang, dict):