kevin3/cool-python.py

## cool-python.py
The following tricks I find pretty useful in my daily Python work. I also added a few I stumbled upon lately.

1. Use collections

This really makes your code more elegant and less verbose, a few examples I absorbed this week:

Named tuples:

>>> Point = collections.namedtuple('Point', ['x', 'y'])
>>> p = Point(x=1.0, y=2.0)
>>> p
Point(x=1.0, y=2.0)
Now you can index by keyword, much nicer than offset into tuple by number (less readable)

>>> p.x
1.0
>>> p.y
Elegantly used when looping through a csv:

with open('stock.csv') as f:
    f_csv = csv.reader(f)
 headings = next(f_csv)
 Row = namedtuple('Row', headings)
 for r in f_csv:
 row = Row(*r) # note the star extraction
 # ... process row ...
I like the unpacking star feature to throw away useless fields:

line = 'nobody:*:-2:-2:Unprivileged User:/var/empty:/usr/bin/false'
>>> uname, *fields, homedir, sh = line.split(':')
>>> uname
'nobody'
>>> homedir
'/var/empty'
>>> sh
'/usr/bin/false'
Superconvenient: the defaultdict:

from collections import defaultdict
rows_by_date = defaultdict(list)
for row in rows:
    rows_by_date[row['date']].append(row)",
Before I would init the list each time which leads to needless code:

if row['date'] not in rows_by_date:

 rows_by_date[row['date']] = []
You can use OrderedDict to leave the order of inserted keys:

>>> import collections
>>> d = collections.OrderedDict()
>>> d['a'] = 'A'
>>> d['b'] = 'B'
>>> d['c'] = 'C'
>>> d['d'] = 'D'
>>> d['e'] = 'E'
>>> for k, v in d.items():
...     print k, v
...
a A
b B
c C
d D
e E
Another nice one is Counter:

from collections import Counter

words = [
  'look', 'into', 'my', 'eyes', 'look', 'into', 'my', 'eyes',
  'the', 'eyes', 'the', 'eyes', 'the', 'eyes', 'not', 'around', 'the',
  'eyes', ""don't"", 'look', 'around', 'the', 'eyes', 'look', 'into',
  'my', 'eyes', ""you're"", 'under'
]
word_counts = Counter(words)
top_three = word_counts.most_common(3)
print(top_three)
# Outputs [('eyes', 8), ('the', 5), ('look', 4)]",
Again, before I would write most_common manually. Not necessary, this is all done already somewhere in the stdlib :)

2. sorted() accepts a key arg which you can use to sort on something else

Here for example we sort on surname:

>>> sorted(names, key=lambda name: name.split()[-1].lower())
['Ned Batchelder', 'David Beazley', 'Raymond Hettinger', 'Brian Jones']
3. Create XMl from dict

Creating XML tags manually is usually a bad idea, I bookmarked this simple dict_to_xml helper:

from xml.etree.ElementTree import Element
def dict_to_xml(tag, d):
    '''
    Turn a simple dict of key/value pairs into XML
    '''
    elem = Element(tag)
    for key, val in d.items():
        child = Element(key)
        child.text = str(val)
        elem.append(child)
    return elem"
4. Oneliner to see if there are any python files in a particular directory

Sometimes ‘any’ is pretty useful:

import os
files = os.listdir('dirname')
if any(name.endswith('.py') for name in files):
5. Use set operations to match common items in lists
>>> a = [1, 2, 3, 'a']
>>> b = ['a', 'b', 'c', 3, 4, 5]
>>> set(a).intersection(b)
{3, 'a'}
6. Use re.compile

If you are going to check a regular expression in a loop, don’t do this:

for i in longlist:
  if re.match(r'^...', i)
yet define the regex once and use the pattern:
p = re.compile(r'^...')
for i in longlist:
  if p.match(i)
7. Printing files with potential bad (Unicode) characters

The book suggested to print filenames of unknown origin, use this convention to avoid errors:

def bad_filename(filename):
    return repr(filename)[1:-1]
try:
    print(filename)
except UnicodeEncodeError:
    print(bad_filename(filename))
Handling unicode chars in files can be nasty because they can blow up your script. However the logic behind it is not that hard to grasp. A good snippet to bookmark is the encoding / decoding of Unicode:

>>> a
'pýtĥöñ is awesome\n'
>>> b = unicodedata.normalize('NFD', a)
>>> b.encode('ascii', 'ignore').decode('ascii')
'python is awesome\n'
O’Reilly has a course on Working with Unicode in Python.

8. Print is pretty cool (Python 3)

I am probably not the only one writing this kind of join operations:

>>> row = ["1", "bob", "developer", "python"]
>>> print(','.join(str(x) for x in row))
1,bob,developer,python
Turns out you can just write it like this:

>>> print(*row, sep=',')
1,bob,developer,python
Note again the * unpacking.
9. Functions like sum() accept generators / use the right variable type

I wrote this at a conference to earn me a coffee mug ;)

sum = 0
for i in range(1300):
    if i % 3 == 0 or i % 5 == 0:
        sum += i
print(sum)
Returns 394118, while handing it in I realized this could be written much shorter and efficiently:

>>> sum(i for i in range(1300) if i % 3 == 0 or i % 5 == 0)
394118
A generator:

lines = (line.strip() for line in f)
is more memory efficient than:

lines = [line.strip() for line in f] # loads whole list into memory at once
And concatenating strings is inefficient:

s = "line1\n"
s += "line2\n"
s += "line3\n"
print(s)
Better build up a list and join when printing:

lines = []
lines.append("line1")
lines.append("line2")
lines.append("line3")
print("\n".join(lines))
Another one I liked from the cookbook:
portfolio = [
  {'name':'GOOG', 'shares': 50},
  {'name':'YHOO', 'shares': 75},
  {'name':'AOL', 'shares': 20},
  {'name':'SCOX', 'shares': 65}
]
min_shares = min(s['shares'] for s in portfolio)
One line to get the min of a numeric value in a nested data structure.

10. Enumerate lines in for loop

You can number lines (or whatever you are looping over) and start with 1 (2nd arg), this is a nice debugging technique

for lineno, line in enumerate(lines, 1): # start counting at 0
    fields = line.split()
    try:
        count = int(fields[1])
        ...
    except ValueError as e:
        print('Line {}: Parse error: {}'.format(lineno, e))
11. Pandas

Import pandas and numpy:

import pandas as pd
import numpy as np
12. Make random dataframe with three columns:

df = pd.DataFrame(np.random.rand(10,3), columns=list('ABC'))
Select:
# Boolean indexing (remember the parentheses)
df[(df.A < 0.5) & (df.B > 0.5)]
# Alternative, using query which depends on numexpr
df.query('A < 0.5 & B > 0.5')
Project:
# One columns
df.A
# Multiple columns
# there may be another shorter way, but I don't know it
df.loc[:,list('AB')]
Often used snippets
Dates
13. Difference (in days) between two dates:

from datetime import date

d1 = date(2013,1,1)
d2 = date(2013,9,13)
abs(d2-d1).days
directory-of-script snippet
os.path.dirname(os.path.realpath(__file__))
# combine with
os.path.join(os.path.dirname(os.path.realpath(__file__)), 'foo','bar','baz.txt')
14. PostgreSQL-connect-query snippet

import psycopg2
conn = psycopg2.connect("host='localhost' user='xxx'  password='yyy' dbname='zzz'")
cur = conn.cursor()
cur.execute("""SELECT * from foo;""")
rows = cur.fetchall()
for row in rows:
  print "   ", row[0]
conn.close()
Input parsing functions
15. Expand input-file args:

# input_data: e.g. 'file.txt' or '*.txt' or 'foo/file.txt' 'bar/file.txt'
filenames = [glob.glob(pathexpr) for pathexpr in input_data]
filenames = [item for sublist in filenames for item in sublist]
15. Parse key-value pair strings like ‘x=42.0,y=1’:

kvp = lambda elem,t,i: t(elem.split('=')[i])
parse_kvp_str = lambda args : dict([(kvp(elem,str,0), kvp(elem,float,1)) for elem in args.split(',')])
parse_kvp_str('x=42.0,y=1')
Postgres database functions

16. Upper case in Python (just for example):

-- create extension plpythonu;
CREATE OR REPLACE FUNCTION python_upper
(
  input text
) RETURNS text AS
$$
  return input.upper()
$$ LANGUAGE plpythonu STRICT;
17. Convert IP address from text to integer:

CREATE FUNCTION ip2int(input text) RETURNS integer
LANGUAGE plpythonu
AS $$
if 'struct' in SD:
    struct = SD['struct']
else:
    import struct
    SD['struct'] = struct
if 'socket' in SD:
    socket = SD['socket']
else:
    import socket
    SD['socket'] = socket
return struct.unpack("!I", socket.inet_aton(input))[0]
$$;
Convert IP address from integer to text:
CREATE FUNCTION int2ip(input integer) RETURNS text
LANGUAGE plpythonu
AS $$
if 'struct' in SD:
    struct = SD['struct']
else:
    import struct
    SD['struct'] = struct
if 'socket' in SD:
    socket = SD['socket']
else:
    import socket
    SD['socket'] = socket
return socket.inet_ntoa(struct.pack("!I", input))
$$;
18. Commandline options

optparse-commandline-options snippet
from optparse import OptionParser
usage = "usage: %prog [options] arg "
parser = OptionParser(usage=usage)
parser.add_option("-x", "--some-option-x", dest="x", default=42.0, type="float",
                  help="a floating point option")
(options, args) = parser.parse_args()
print options.x
print args[0]
19. print-in-place (progress bar) snippet

import time
import sys
for progress in range(100):
  time.sleep(0.1)
  sys.stdout.write("Download progress: %d%%   \r" % (progress) )
  sys.stdout.flush()
Packaging snippets

20. poor-mans-python-executable trick

Learned this trick from voidspace. The trick uses two files (__main__.py and hashbang.txt):

__main__.py:
print 'Hello world'
hashbang.txt (adding a newline after ‘python2.6’ is important):
#!/usr/bin/env python2.6
Build an “executable”:
zip main.zip __main__.py
cat hashbang.txt main.zip > hello
rm main.zip
chmod u+x hello
Run “executable”:
$ ./hello
Hello world
21. import-class-from-file trick

Import class MyClass from a module file (adapted from stackoverflow):

import imp
mod = imp.load_source('name.of.module', 'path/to/module.py')
obj = mod.MyClass()
22. Occusional-usage snippets

Extract words from string

words = lambda text: ''.join(c if c.isalnum() else ' ' for c in text).split()
words('Johnny.Appleseed!is:a*good&farmer')
# ['Johnny', 'Appleseed', 'is', 'a', 'good', 'farmer']
23. IP address to integer and back

import struct
import socket
def ip2int(addr):
    return struct.unpack("!I", socket.inet_aton(addr))[0]
def int2ip(addr):
    return socket.inet_ntoa(struct.pack("!I", addr))
24. Fluent Python Interface

Copied from riaanvddool.

# Fluent Interface Definition
class sql:
  class select:
    def __init__(self, dbcolumn, context=None):
      self.dbcolumn = dbcolumn
      self.context = context
    def select(self, dbcolumn):
      return self.__class__(dbcolumn,self)
# Demo
q = sql.select('foo').select('bar')
print q.dbcolumn  #bar
print q.context.dbcolumn  #foo
Flatten a nested lists
def flatten(elems):
	"""
	[['a'], ['b','c',['d'],'e',['f','g']]]
	"""
	stack = [elems]
	top = stack.pop()
	while top:
		head, tail = top[0], top[1:]
		if tail: stack.append(tail)
		if not isinstance(head, list): yield head
		else: stack.append(head)
		if stack: top = stack.pop()
		else: break
snap rounding
EPSILON = 0.000001
snap_ceil = lambda x: math.ceil(x) if abs(x - round(x)) > EPSILON else round(x)
snap_floor = lambda x: math.floor(x) if abs(x - round(x)) > EPSILON else round(x)
merge-two-dictionaries snippet
x = {'a': 42}
y = {'b': 127}
z = dict(x.items() + y.items())
# z = {'a': 42, 'b': 127}
25. anonymous-object snippet

Adapted from stackoverflow:

class Anon(object):
    def __new__(cls, **attrs):
        result = object.__new__(cls)
        result.__dict__ = attrs
        return result
26. Alternative:

class Anon(object):
    def __init__(self, **kwargs):
        self.__dict__.update(kwargs)
    def __repr__(self):
        return self.__str__()
    def __str__(self):
        return ", ".join(["%s=%s" % (key,value) for key,value in self.__dict__.items()])
27. generate-random-word snippet

Function that returns a random word (could also use random.choicewith this list of words):

import string, random
randword = lambda n: "".join([random.choice(string.letters) for i in range(n)])
setdefault tricks
Increment (and initialize) value:
d = {}
d[2] = d.setdefault(2,39) + 1
d[2] = d.setdefault(2,39) + 1
d[2] = d.setdefault(2,39) + 1
d[2] # value is 42
29. Append value to (possibly uninitialized) list stored under a key in dictionary:

d = {}
d.setdefault(2, []).append(42)
d.setdefault(2, []).append(127)
d[2] # value is [42, 127]
Binary tricks

30. add-integers-using-XOR snippet

Swap two integer variables using the XOR swap algorithm:

x = 42
y = 127
x = x ^ y
y = y ^ x
x = x ^ y
x # value is 127
y # value is 42
I know that most of it has been mentioned already But I think you should find some new tricks as well.
	The following tricks I find pretty useful in my daily Python work. I also added a few I stumbled upon lately.

	1. Use collections

	This really makes your code more elegant and less verbose, a few examples I absorbed this week:

	Named tuples:

	>>> Point = collections.namedtuple('Point', ['x', 'y'])
	>>> p = Point(x=1.0, y=2.0)
	>>> p
	Point(x=1.0, y=2.0)
	Now you can index by keyword, much nicer than offset into tuple by number (less readable)

	>>> p.x
	1.0
	>>> p.y
	Elegantly used when looping through a csv:

	with open('stock.csv') as f:
	f_csv = csv.reader(f)
	headings = next(f_csv)
	Row = namedtuple('Row', headings)
	for r in f_csv:
	row = Row(*r) # note the star extraction
	# ... process row ...
	I like the unpacking star feature to throw away useless fields:

	line = 'nobody:*:-2:-2:Unprivileged User:/var/empty:/usr/bin/false'
	>>> uname, *fields, homedir, sh = line.split(':')
	>>> uname
	'nobody'
	>>> homedir
	'/var/empty'
	>>> sh
	'/usr/bin/false'
	Superconvenient: the defaultdict:

	from collections import defaultdict
	rows_by_date = defaultdict(list)
	for row in rows:
	rows_by_date[row['date']].append(row)",
	Before I would init the list each time which leads to needless code:

	if row['date'] not in rows_by_date:

	rows_by_date[row['date']] = []
	You can use OrderedDict to leave the order of inserted keys:

	>>> import collections
	>>> d = collections.OrderedDict()
	>>> d['a'] = 'A'
	>>> d['b'] = 'B'
	>>> d['c'] = 'C'
	>>> d['d'] = 'D'
	>>> d['e'] = 'E'
	>>> for k, v in d.items():
	... print k, v
	...
	a A
	b B
	c C
	d D
	e E
	Another nice one is Counter:

	from collections import Counter

	words = [
	'look', 'into', 'my', 'eyes', 'look', 'into', 'my', 'eyes',
	'the', 'eyes', 'the', 'eyes', 'the', 'eyes', 'not', 'around', 'the',
	'eyes', ""don't"", 'look', 'around', 'the', 'eyes', 'look', 'into',
	'my', 'eyes', ""you're"", 'under'
	]
	word_counts = Counter(words)
	top_three = word_counts.most_common(3)
	print(top_three)
	# Outputs [('eyes', 8), ('the', 5), ('look', 4)]",
	Again, before I would write most_common manually. Not necessary, this is all done already somewhere in the stdlib :)

	2. sorted() accepts a key arg which you can use to sort on something else

	Here for example we sort on surname:

	>>> sorted(names, key=lambda name: name.split()[-1].lower())
	['Ned Batchelder', 'David Beazley', 'Raymond Hettinger', 'Brian Jones']
	3. Create XMl from dict

	Creating XML tags manually is usually a bad idea, I bookmarked this simple dict_to_xml helper:

	from xml.etree.ElementTree import Element
	def dict_to_xml(tag, d):
	'''
	Turn a simple dict of key/value pairs into XML
	'''
	elem = Element(tag)
	for key, val in d.items():
	child = Element(key)
	child.text = str(val)
	elem.append(child)
	return elem"
	4. Oneliner to see if there are any python files in a particular directory

	Sometimes ‘any’ is pretty useful:

	import os
	files = os.listdir('dirname')
	if any(name.endswith('.py') for name in files):
	5. Use set operations to match common items in lists
	>>> a = [1, 2, 3, 'a']
	>>> b = ['a', 'b', 'c', 3, 4, 5]
	>>> set(a).intersection(b)
	{3, 'a'}
	6. Use re.compile

	If you are going to check a regular expression in a loop, don’t do this:

	for i in longlist:
	if re.match(r'^...', i)
	yet define the regex once and use the pattern:
	p = re.compile(r'^...')
	for i in longlist:
	if p.match(i)
	7. Printing files with potential bad (Unicode) characters

	The book suggested to print filenames of unknown origin, use this convention to avoid errors:

	def bad_filename(filename):
	return repr(filename)[1:-1]
	try:
	print(filename)
	except UnicodeEncodeError:
	print(bad_filename(filename))
	Handling unicode chars in files can be nasty because they can blow up your script. However the logic behind it is not that hard to grasp. A good snippet to bookmark is the encoding / decoding of Unicode:

	>>> a
	'pýtĥöñ is awesome\n'
	>>> b = unicodedata.normalize('NFD', a)
	>>> b.encode('ascii', 'ignore').decode('ascii')
	'python is awesome\n'
	O’Reilly has a course on Working with Unicode in Python.

	8. Print is pretty cool (Python 3)

	I am probably not the only one writing this kind of join operations:

	>>> row = ["1", "bob", "developer", "python"]
	>>> print(','.join(str(x) for x in row))
	1,bob,developer,python
	Turns out you can just write it like this:

	>>> print(*row, sep=',')
	1,bob,developer,python
	Note again the * unpacking.
	9. Functions like sum() accept generators / use the right variable type

	I wrote this at a conference to earn me a coffee mug ;)

	sum = 0
	for i in range(1300):
	if i % 3 == 0 or i % 5 == 0:
	sum += i
	print(sum)
	Returns 394118, while handing it in I realized this could be written much shorter and efficiently:

	>>> sum(i for i in range(1300) if i % 3 == 0 or i % 5 == 0)
	394118
	A generator:

	lines = (line.strip() for line in f)
	is more memory efficient than:

	lines = [line.strip() for line in f] # loads whole list into memory at once
	And concatenating strings is inefficient:

	s = "line1\n"
	s += "line2\n"
	s += "line3\n"
	print(s)
	Better build up a list and join when printing:

	lines = []
	lines.append("line1")
	lines.append("line2")
	lines.append("line3")
	print("\n".join(lines))
	Another one I liked from the cookbook:
	portfolio = [
	{'name':'GOOG', 'shares': 50},
	{'name':'YHOO', 'shares': 75},
	{'name':'AOL', 'shares': 20},
	{'name':'SCOX', 'shares': 65}
	]
	min_shares = min(s['shares'] for s in portfolio)
	One line to get the min of a numeric value in a nested data structure.

	10. Enumerate lines in for loop

	You can number lines (or whatever you are looping over) and start with 1 (2nd arg), this is a nice debugging technique

	for lineno, line in enumerate(lines, 1): # start counting at 0
	fields = line.split()
	try:
	count = int(fields[1])
	...
	except ValueError as e:
	print('Line {}: Parse error: {}'.format(lineno, e))
	11. Pandas

	Import pandas and numpy:

	import pandas as pd
	import numpy as np
	12. Make random dataframe with three columns:

	df = pd.DataFrame(np.random.rand(10,3), columns=list('ABC'))
	Select:
	# Boolean indexing (remember the parentheses)
	df[(df.A < 0.5) & (df.B > 0.5)]
	# Alternative, using query which depends on numexpr
	df.query('A < 0.5 & B > 0.5')
	Project:
	# One columns
	df.A
	# Multiple columns
	# there may be another shorter way, but I don't know it
	df.loc[:,list('AB')]
	Often used snippets
	Dates
	13. Difference (in days) between two dates:

	from datetime import date

	d1 = date(2013,1,1)
	d2 = date(2013,9,13)
	abs(d2-d1).days
	directory-of-script snippet
	os.path.dirname(os.path.realpath(__file__))
	# combine with
	os.path.join(os.path.dirname(os.path.realpath(__file__)), 'foo','bar','baz.txt')
	14. PostgreSQL-connect-query snippet

	import psycopg2
	conn = psycopg2.connect("host='localhost' user='xxx' password='yyy' dbname='zzz'")
	cur = conn.cursor()
	cur.execute("""SELECT * from foo;""")
	rows = cur.fetchall()
	for row in rows:
	print " ", row[0]
	conn.close()
	Input parsing functions
	15. Expand input-file args:

	# input_data: e.g. 'file.txt' or '*.txt' or 'foo/file.txt' 'bar/file.txt'
	filenames = [glob.glob(pathexpr) for pathexpr in input_data]
	filenames = [item for sublist in filenames for item in sublist]
	15. Parse key-value pair strings like ‘x=42.0,y=1’:

	kvp = lambda elem,t,i: t(elem.split('=')[i])
	parse_kvp_str = lambda args : dict([(kvp(elem,str,0), kvp(elem,float,1)) for elem in args.split(',')])
	parse_kvp_str('x=42.0,y=1')
	Postgres database functions

	16. Upper case in Python (just for example):

	-- create extension plpythonu;
	CREATE OR REPLACE FUNCTION python_upper
	(
	input text
	) RETURNS text AS
	$$
	return input.upper()
	$$ LANGUAGE plpythonu STRICT;
	17. Convert IP address from text to integer:

	CREATE FUNCTION ip2int(input text) RETURNS integer
	LANGUAGE plpythonu
	AS $$
	if 'struct' in SD:
	struct = SD['struct']
	else:
	import struct
	SD['struct'] = struct
	if 'socket' in SD:
	socket = SD['socket']
	else:
	import socket
	SD['socket'] = socket
	return struct.unpack("!I", socket.inet_aton(input))[0]
	$$;
	Convert IP address from integer to text:
	CREATE FUNCTION int2ip(input integer) RETURNS text
	LANGUAGE plpythonu
	AS $$
	if 'struct' in SD:
	struct = SD['struct']
	else:
	import struct
	SD['struct'] = struct
	if 'socket' in SD:
	socket = SD['socket']
	else:
	import socket
	SD['socket'] = socket
	return socket.inet_ntoa(struct.pack("!I", input))
	$$;
	18. Commandline options

	optparse-commandline-options snippet
	from optparse import OptionParser
	usage = "usage: %prog [options] arg "
	parser = OptionParser(usage=usage)
	parser.add_option("-x", "--some-option-x", dest="x", default=42.0, type="float",
	help="a floating point option")
	(options, args) = parser.parse_args()
	print options.x
	print args[0]
	19. print-in-place (progress bar) snippet

	import time
	import sys
	for progress in range(100):
	time.sleep(0.1)
	sys.stdout.write("Download progress: %d%% \r" % (progress) )
	sys.stdout.flush()
	Packaging snippets

	20. poor-mans-python-executable trick

	Learned this trick from voidspace. The trick uses two files (__main__.py and hashbang.txt):

	__main__.py:
	print 'Hello world'
	hashbang.txt (adding a newline after ‘python2.6’ is important):
	#!/usr/bin/env python2.6
	Build an “executable”:
	zip main.zip __main__.py
	cat hashbang.txt main.zip > hello
	rm main.zip
	chmod u+x hello
	Run “executable”:
	$ ./hello
	Hello world
	21. import-class-from-file trick

	Import class MyClass from a module file (adapted from stackoverflow):

	import imp
	mod = imp.load_source('name.of.module', 'path/to/module.py')
	obj = mod.MyClass()
	22. Occusional-usage snippets

	Extract words from string

	words = lambda text: ''.join(c if c.isalnum() else ' ' for c in text).split()
	words('Johnny.Appleseed!is:a*good&farmer')
	# ['Johnny', 'Appleseed', 'is', 'a', 'good', 'farmer']
	23. IP address to integer and back

	import struct
	import socket
	def ip2int(addr):
	return struct.unpack("!I", socket.inet_aton(addr))[0]
	def int2ip(addr):
	return socket.inet_ntoa(struct.pack("!I", addr))
	24. Fluent Python Interface

	Copied from riaanvddool.

	# Fluent Interface Definition
	class sql:
	class select:
	def __init__(self, dbcolumn, context=None):
	self.dbcolumn = dbcolumn
	self.context = context
	def select(self, dbcolumn):
	return self.__class__(dbcolumn,self)
	# Demo
	q = sql.select('foo').select('bar')
	print q.dbcolumn #bar
	print q.context.dbcolumn #foo
	Flatten a nested lists
	def flatten(elems):
	"""
	[['a'], ['b','c',['d'],'e',['f','g']]]
	"""
	stack = [elems]
	top = stack.pop()
	while top:
	head, tail = top[0], top[1:]
	if tail: stack.append(tail)
	if not isinstance(head, list): yield head
	else: stack.append(head)
	if stack: top = stack.pop()
	else: break
	snap rounding
	EPSILON = 0.000001
	snap_ceil = lambda x: math.ceil(x) if abs(x - round(x)) > EPSILON else round(x)
	snap_floor = lambda x: math.floor(x) if abs(x - round(x)) > EPSILON else round(x)
	merge-two-dictionaries snippet
	x = {'a': 42}
	y = {'b': 127}
	z = dict(x.items() + y.items())
	# z = {'a': 42, 'b': 127}
	25. anonymous-object snippet

	Adapted from stackoverflow:

	class Anon(object):
	def __new__(cls, **attrs):
	result = object.__new__(cls)
	result.__dict__ = attrs
	return result
	26. Alternative:

	class Anon(object):
	def __init__(self, **kwargs):
	self.__dict__.update(kwargs)
	def __repr__(self):
	return self.__str__()
	def __str__(self):
	return ", ".join(["%s=%s" % (key,value) for key,value in self.__dict__.items()])
	27. generate-random-word snippet

	Function that returns a random word (could also use random.choicewith this list of words):

	import string, random
	randword = lambda n: "".join([random.choice(string.letters) for i in range(n)])
	setdefault tricks
	Increment (and initialize) value:
	d = {}
	d[2] = d.setdefault(2,39) + 1
	d[2] = d.setdefault(2,39) + 1
	d[2] = d.setdefault(2,39) + 1
	d[2] # value is 42
	29. Append value to (possibly uninitialized) list stored under a key in dictionary:

	d = {}
	d.setdefault(2, []).append(42)
	d.setdefault(2, []).append(127)
	d[2] # value is [42, 127]
	Binary tricks

	30. add-integers-using-XOR snippet

	Swap two integer variables using the XOR swap algorithm:

	x = 42
	y = 127
	x = x ^ y
	y = y ^ x
	x = x ^ y
	x # value is 127
	y # value is 42
	I know that most of it has been mentioned already But I think you should find some new tricks as well.