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Metadata Locks

If an InnoDB table is being accessed at all via SELECT or DML (INSERT, UPDATE, DELETE), you should rightly expect a metadata lock.

According to the MySQL Documentation on MetaData Locking (http://dev.mysql.com/doc/refman/5.6/en/metadata-locking.html):

To ensure transaction serializability, the server must not permit one session to perform a data definition language (DDL) statement on a table that is used in an uncompleted transaction in another session. The server achieves this by acquiring metadata locks on tables used within a transaction and deferring release of those locks until the transaction ends. A metadata lock on a table prevents changes to the table's structure. This locking approach has the implication that a table that is being used by a transaction within one session cannot be used in DDL statements by other sessions until the transaction ends.

SELECTs will obtain a shared metadata lock, while DML and DDL will obtain an exclusive metadata lock. So an uncommitted

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#!/usr/bin/env python
r"""
    Module to generate a stand-alone PDF of a tikz picture.

    Any lines in the TikZ fragment that begin with "%tikzpic " are preprocessor
    directives to this file.  Presently, only two preprocessor commands are
    supported. They are detailed through the examples below.

    1) To input code into the stand-alone LaTeX before compilation:

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from __future__ import division

import numpy as np

def multinomial_ci(counts, alpha):
    """
    Calculate a simultaneous (1-alpha) * 100 percent confidence interval.

    Parameters
    ----------

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"""
Example demonstrating how to modify the GraphMatcher class so that 
subgraph_is_isomorphic() will determine whether G2 is a subgraph (with
an identity isomorphism).

"""

import networkx as nx

G = nx.karate_club_graph()

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from __future__ import print_function

import datetime
import pytz

paris = pytz.timezone('Europe/Paris')
utc = pytz.utc

before_naive = datetime.datetime(2013, 3, 31, 1, 59)
before_paris = paris.localize(before_naive)

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"""
Categorical color palettes from Tableau.

For example: http://kb.tableausoftware.com/articles/knowledgebase/creating-custom-color-palettes

"""
palettes = [
    # Long name, short name
    ('Tableau 10', 'T 10'),
    ('Tableau 10 Light', 'T 10 L'),

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from collections import Callable
from cyordereddict import OrderedDict

class DefaultOrderedDict(OrderedDict):
    # Source: http://stackoverflow.com/a/6190500/562769
    def __init__(self, default_factory=None, *a, **kw):
        if (default_factory is not None and
           not isinstance(default_factory, Callable)):
            raise TypeError('first argument must be callable')
        OrderedDict.__init__(self, *a, **kw)

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/*
  I've wrapped Makoto Matsumoto and Takuji Nishimura's code in a namespace
  so it's better encapsulated. Now you can have multiple random number generators
  and they won't stomp all over eachother's state.
  
  If you want to use this as a substitute for Math.random(), use the random()
  method like so:
  
  var m = new MersenneTwister();

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# original XML at http://www.w3.org/Math/characters/unicode.xml
# XSL for conversion: https://gist.github.com/798546


unicode_to_latex = {
    u"\u0020": "\\space ",
    u"\u0023": "\\#",
    u"\u0024": "\\textdollar ",
    u"\u0025": "\\%",
    u"\u0026": "\\&",

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"""
Some functions related to Bayesian networks (DAGs).

Most of this was pulled from:
    http://www.mi.parisdescartes.fr/~nuel/bntworkshop2010/lecture3.pdf

"""

import networkx as nx