python-anti-patterns/examples/new_patterns.py at examples · quantifiedcode/python-anti-patterns

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Using an unpythonic loop:
Instead of counting over an index and retrieving the corresponding index element within the for
loop, you should use enumerate to retrieve the index and list element simultaneously.
l = [1,2,3]
for i in range(0,len(list)):
    le = l[i]
    print i,le
for i,le in enumerate(l):
    print i,le
Returning more than one variable type from function call
A function call should return only one type of variable. Example: If a function is supposed to
return a list, do not return None if an error occurs or some condition is unmet. Instead, raise
an exception.
Why this is bad:
If a function that is supposed to return a given type (e.g. list, tuple, dict) suddenly returns 
something else (e.g. None) the caller of that function will always need to check the type of the
return value before proceeding. This makes for confusing and complex code. If the function is unable
to produce the supposed return value it is better to raise an exception that can be caught by the caller instead.
def filter_for_foo(l):
    r = [e for e in l if e.find("foo") != -1]
    if not check_some_critical_condition(r):
        return None
    return r
res = filter_for_foo(["bar","foo","faz"])
if res is not None:
    #continue processing
def filter_for_foo(l):
    r = [e for e in l if e.find("foo") != -1]
    if not check_some_critical_condition(r):
        raise SomeException("critical condition unmet!")
    return r
    res = filter_for_foo(["bar","foo","faz"])
    #continue processing
except SomeException:
    #handle exception
The loop may never terminate
The given loop does not modify anything that impacts the loop condition and does not call 'break', 'return' or 'yield' explicitly
, which may lead to an infinite loop.
while i < 10:
    do_something()
    #we forget to increment i
Not using .items() to iterate over a list of key/value pairs of a dictionary.
d = {'foo' : 1,'bar' : 2}
for key in d:
    value = d[key]
    print "%s = %d" % (key,value)
for key,value in d.items():
    print "%s = %d" % (key,value)
Not using zip() to iterate over a pair of lists
l1 = [1,2,3]
l2 = [4,5,6]
for i in range(l1):
    l1v = l1[i]
    l2v = l2[i]
    print l1v,l2v
for l1v,l2v in zip(l1,l2):
    print l1v,l2v
Using "key in list" to check if a key is contained in a list.
This is not an error but inefficient, since the list search is O(n). If possible, a set or dictionary
should be used instead.
Note: Since the conversion of the list to a set is an O(n) operation, it should ideally be done only once when generating the list.
l = [1,2,3,4]
Not using 'else' where appropriate in a loop.
'else' can be used in a loop context to execute code in case the loop does not get terminated by a 'break' statement.
See here for more details:
https://docs.python.org/2/tutorial/controlflow.html#break-and-continue-statements-and-else-clauses-on-loops
found = False
l = [1,2,3]
for i in l:
    if i == 4:
        found = True
        break
if not found:
    #not found...
for i in l:
    if i == 4:
        break
    #not found...
Not using .setdefault() where appropriate.
setdefault can be used to initialize a dictionary value with a default.
https://docs.python.org/2/library/stdtypes.html#dict.setdefault
For usage examples see here:
http://stackoverflow.com/questions/3483520/use-cases-for-the-setdefault-dict-method
if not 'foo' in d:
    d['foo'] = []
d['foo'].append('bar')
foo = d.setdefault('foo',[])
foo.append(bar)
Not using .get() to return a default value from a dict
https://docs.python.org/2/library/stdtypes.html#dict.get
d = {'foo' : 'bar'}
foo = 'default'
if 'foo' in d:
    foo = d['foo']
foo = d.get('foo','default')
Using map/filter where a list comprehension would be possible
values = [1,2,3]
doubled_values = map(lambda x:x*2,values)
doubled_values = [x*2 for x in values]
filtered_values = filter(lambda x:True if x < 2 else False,values)
filtered_values = [x for x in values if x < 2]
Not using defaultdict where appropriate
if not 'count' in d:
    d['count'] = 0
d['count']+=1
from collections import defaultdict
d = defaultdict(lambda :0)
d['count']+=1
Not using a namedtuple when returning more than one value from a function
Named tuples can be used anywhere where normal tuples are acceptable, but their values can be accessed
through their name in addition to their index, which makes code more verbose and easier to read.
https://docs.python.org/2/library/collections.html#namedtuple-factory-function-for-tuples-with-named-fields
    return -1,"not found"
status_code,message = foo()
print status_code,message
from collections import namedtuple
    return_args = namedtuple('return_args',['status_code','message'])
    return return_args(-1,"not found")
print ra.status_code,ra.message
Not using explicit unpacking of sequencing
Python supports unpacking of lists, tuples and dicts.
l = [1,"foo","bar"]
l0,l1,l2 = l
Not using unpacking for updating multiple values at once
x,y = y+2,x-4
Not using 'with' to open files
f = open("file.txt","r")
content = f.read()
with open("file.txt","r") as input_file:
    content = f.read()
Asking for permission instead of forgiveness when working with files
if os.path.exists("file.txt"):
    os.unlink("file.txt")
    os.unlink("file.txt")
except OSError:
Not using a dict comprehension where appropriate
l = [1,2,3]
d = dict([(n,n*2) for n in l])
d = {n : n*2 for n in l}
Using string concatenation instead of formatting
n_errors = 10
s = "there were "+str(n_errors)+" errors."
s = "there were %d errors." % n_errors
Putting type information in the variable name (Hungarian notation)
strFoo = "bar"
foo = "bar"
Implementing Java-style getters and setters instead of using properties.
http://stackoverflow.com/questions/6618002/python-property-versus-getters-and-setters
class Foo(object):
    def __init__(a):
        self._a = a
    def get_a(self):
        return a
    def set_a(self,value):
        self._a = value
class Foo(object):
    def __init__(a):
        self._a = a
    @property
    def a(self):
        return self._a
    @a.setter
    def a(self,value):
        self._a = value
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