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Created November 28, 2015 16:58
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Transforming Code into Beautiful, Idiomatic Python
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python.py
# Transforming Code into Beautiful, Idiomatic Python
# Raymond Hettinger
# Looping over a range of numbers
for i in [0, 1, 2, 3, 4, 5]:
print i**2
# better:
for i in range(6):
print i**2
# best:
for i in xrange(6):
print i**2
# Looping over a collection
colors = ['red', 'green', 'blue', 'yellow']
# yuck:
for i in range(len(colors)):
print colors[i]
# iterate:
for color in colors:
print color
# Looping backwards
colors = ['red', 'green', 'blue', 'yellow']
# yuck:
for i in range(len(colors)-1, -1, -1):
print colors[i]
# pythonic:
for color in reversed(colors):
print color
# Looping over a collection and indicies
colors = ['red', 'green', 'blue', 'yellow']
for i in range(len(colors)):
print i, '-->', colors[i]
# when you need the index:
for i, color in enumerate(colors):
print i, '-->', color
# Looping over two collections
names = ['raymond', 'rachel', 'matthew']
colors = ['red', 'green', 'blue', 'yellow']
n = min(len(names), len(colors))
for i in range(n):
print names[i], '-->', colors[i]
for name, color in zip(names, colors):
print name, '-->', color
# iterator uses the least memory:
for name, color in izip(names, colors):
print name, '-->', color
# Looping in sorted order
colors = ['red', 'green', 'blue', 'yellow']
for color in sorted(colors):
print color
for color in sorted(colors, reverse=True):
print color
# Custom sort order
colors = ['red', 'green', 'blue', 'yellow']
def compare_length(c1, c2):
if len(c1) < len(c2): return -1
if len(c1) > len(c2): return 1
return 0
print sorted(colors, cmp=compare_length)
# no sort function needed! (think SQL)
print sorted(colors, key=len)
# Call a function until a sentinel value
# old:
blocks = []
while True:
block = f.read(32)
if block == '':
break
blocks.append(block)
# better: (iter takes a sentinel second arg)
blocks = []
for block in iter(partial(f.read, 32), ''):
blocks.append(block)
# Distinguishing multiple exit points in loops
def find(seq, target):
found = False
for i, value in enumerate(seq):
if value == tgt:
found = True
break
if not found:
return -1
return i
# for has an 'else' for finishing without breaks:
def find(seq, target):
for i, value in enumerate(seq):
if value == tgt:
break
else:
return -1
return i
# Looping over dictionary keys
d = {'matthew': 'blue', 'rachel': 'green', 'raymond': 'red'}
for k in d:
print k
# this lets you modify:
for k in d.keys():
if k.startswith('r'):
del d[k]
# best:
d = {k : d[k] for k in d if not k.startswith('r')}
# Looping over a dictionary keys and values
for k in d:
print k, '-->', d[k]
for k, v in d.items():
print k, '-->', v
# least memory:
for k, v in d.iteritems():
print k, '-->', v
# Construct a dictionary from pairs
names = ['raymond', 'rachel', 'matthew']
colors = ['red', 'green', 'blue']
# dict() takes an iterator:
d = dict(izip(names, colors))
#{'matthew': 'blue', 'rachel': 'green', 'raymond': 'red'}
d = dict(enumerate(names))
#{0: 'raymond', 1: 'rachel', 2: 'matthew'}
# Counting with dictionaries
colors = ['red', 'green', 'red', 'blue', 'green', 'red']
d = {}
for color in colors:
if color not in d:
d[color] = 0
d[color] += 1
#{'blue': 1, 'green': 2, 'red': 3}
# with default value:
d = {}
for color in colors:
d[color] = d.get(color, 0) + 1
# or with a defaultdict:
d = defaultdict(int)
for color in colors:
d[color] += 1
# Grouping with dictionaries -- Part I
names = ['raymond', 'rachel', 'matthew', 'roger',
'betty', 'melissa', 'judith', 'charlie']
d = {}
for name in names:
key = len(name)
if key not in d:
d[key] = []
d[key].append(name)
#{5: ['roger', 'betty'], 6: ['rachel', 'judith'],
# 7: ['raymond', 'matthew', 'melissa', 'charlie']}
# Grouping with dictionaries -- Part II
# ok, but setdefault is sort of inelegant:
d = {}
for name in names:
key = len(name)
d.setdefault(key, []).append(name)
# best:
d = defaultdict(list)
for name in names:
key = len(name)
d[key].append(name)
# Is a dictionary popitem() atomic?
d = {'matthew': 'blue', 'rachel': 'green', 'raymond':
'red'}
while d:
key, value = d.popitem()
print key, '-->', value
# yes, threadsafe
# Linking dictionaries
defaults = {'color': 'red', 'user': 'guest'}
parser = argparse.ArgumentParser()
parser.add_argument('-u', '--user')
parser.add_argument('-c', '--color')
namespace = parser.parse_args([])
command_line_args = {k:v for
k, v in vars(namespace).items() if v}
d = defaults.copy()
d.update(os.environ)
d.update(command_line_args)
# faster, more memory-efficient:
d = ChainMap(command_line_args, os.environ, defaults)
# Improving Clarity
# Clarify function calls with keyword arguments
# confusing:
twitter_search('@obama', False, 20, True)
# clear:
twitter_search('@obama', retweets=False, numtweets=20, popular=True)
# Clarify multiple return values with named tuples
doctest.testmod()
# (0, 4) # confusing
doctest.testmod()
# TestResults(failed=0, attempted=4) # clear
# create with:
TestResults = namedtuple('TestResults', ['failed', 'attempted'])
# is still tuple, interface works exactly the same
# Unpacking sequences
p = 'Raymond', 'Hettinger', 0x30, 'python@example.com'
# ugly:
fname = p[0]
lname = p[1]
age = p[2]
email = p[3]
# better:
fname, lname, age, email = p
# Updating multiple state variables
def fibonacci(n):
x = 0
y = 1
for i in range(n):
print x
t = y
y = x + y
x = t
def fibonacci(n):
x, y = 0, 1
for i in range(n):
print x
x, y = y, x+y
# Tuple packing and unpacking
# given influence():
# bad and easily bug-ridden:
tmp_x = x + dx * t
tmp_y = y + dy * t
tmp_dx = influence(m, x, y, dx, dy, partial='x')
tmp_dy = influence(m, x, y, dx, dy, partial='y')
x = tmp_x
y = tmp_y
dx = tmp_dx
dy = tmp_dy
# good:
x, y, dx, dy = (x + dx * t,
y + dy * t,
influence(m, x, y, dx, dy, partial='x'),
influence(m, x, y, dx, dy, partial='y'))
# Concatenating strings
names = ['raymond', 'rachel', 'matthew', 'roger',
'betty', 'melissa', 'judith', 'charlie']
s = names[0]
for name in names[1:]:
s += ', ' + name
print s
print ', '.join(names)
# Updating sequences
names = ['raymond', 'rachel', 'matthew', 'roger',
'betty', 'melissa', 'judith', 'charlie']
# slow slow slow:
del names[0]
names.pop(0)
names.insert(0, 'mark')
# double-ended queue:
names = deque(['raymond', 'rachel', 'matthew', 'roger',
'betty', 'melissa', 'judith', 'charlie'])
# much faster:
del names[0]
names.popleft()
names.appendleft('mark')
# Using decorators to factor-out administrative logic
def web_lookup(url, saved={}):
if url in saved:
return saved[url]
page = urllib.urlopen(url).read()
saved[url] = page
return page
@cache
def web_lookup(url):
return urllib.urlopen(url).read()
# Caching decorator
def cache(func):
saved = {}
@wraps(func)
def newfunc(*args):
if args in saved:
return newfunc(*args)
result = func(*args)
saved[args] = result
return result
return newfunc
# Factor-out temporary contexts
old_context = getcontext().copy()
getcontext().prec = 50
print Decimal(355) / Decimal(113)
setcontext(old_context)
# better:
with localcontext(Context(prec=50)):
print Decimal(355) / Decimal(113)
# How to open and close files
f = open('data.txt')
try:
data = f.read()
finally:
f.close()
with open('data.txt') as f:
data = f.read()
# How to use locks
# Make a lock
lock = threading.Lock()
# Old-way to use a lock
lock.acquire()
try:
print 'Critical section 1'
print 'Critical section 2'
finally:
lock.release()
# New-way to use a lock
with lock:
print 'Critical section 1'
print 'Critical section 2'
# Factor-out temporary contexts
try:
os.remove('somefile.tmp')
except OSError:
pass
# better:
with ignored(OSError):
os.remove('somefile.tmp')
# Context manager: ignored()
@contextmanager
def ignored(*exceptions):
try:
yield
except exceptions:
pass
# Factor-out temporary contexts
with open('help.txt', 'w') as f:
oldstdout = sys.stdout
sys.stdout = f
try:
help(pow)
finally:
sys.stdout = oldstdout
with open('help.txt', 'w') as f:
with redirect_stdout(f):
help(pow)
# Context manager: redirect_stdout()
@contextmanager
def redirect_stdout(fileobj):
oldstdout = sys.stdout
sys.stdout = fileobj
try:
yield fieldobj
finally:
sys.stdout = oldstdout
# List Comprehensions and Generator Expressions
# old:
result = []
for i in range(10):
s = i ** 2
result.append(s)
print sum(result)
# better:
print sum([i**2 for i in xrange(10)])
# best:
print sum(i**2 for i in xrange(10))
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