In a class method I have a set of possible options for a single keyword argument, each with a different algorithm to calculate something. To check which option has been added to the keyword I made a chain of if, elif, else too find the keyword option provided.
class MyClass:
def my_method(self, my_parameter, my_keyword='spacial'):
if my_keyword == 'spacial':
print('Cool stuf')
elif my_keyword == 'discoidal':
print('OTHER cool stuff')
elif my_keyword == 'temporal':
print('You get the gist')
else:
print('not in options list')
In my opinion this is not a very elegant way to code this. Especially if the options list keeps growing. Is there a way to omit the list of if, elif, elif, else statements?
Use a dictionary:
def cool_stuff(param):
...
def other_cool_stuff(param):
...
def you_get_the_gist(param):
....
dispatch_mapping = {
'spacial': cool_stuff,
'discoidal': other_cool_stuff,
'temporal': you_get_the_gist
}
Somewhere else:
def my_method(self, param, keyword='spacial'):
handler = dispatch_mapping.get(keyword)
if handler is None:
raise Exception("No handler for %s" % keyword)
return handler(param)
There exists always at least one place where you have to divide the cases.
In your case you set a string and then compare it again.
A "way" around that would be replace setting your string by different function/method calls directly instead of routing it inside a function. Or use a dictionary to map strings to a function call.
Using dictionary is a good idea. However, another option is reflection which function be called by string.
class MyClass:
def handle_spacial(self):
print('Cool stuf')
def handle_discoidal(self):
print('OTHER cool stuff')
def handle_temporal(self):
print('You get the gist')
def default(self):
print('not in options list')
def my_method(self, my_parameter, my_keyword='spacial'):
function_name = "handle_"+my_keyword
if hasattr(self, function_name):
getattr(self, function_name)()
else:
self.default()
The best way to to create a dictionary of keywords and options to be displayed and use in the following way:
>>> class MyClass:
... global mykey_option
... mykey_option={'spacial':'Cool stuf','discoidal':'OTHER cool stuff','temporal':'You get the gist'}
... def my_method(self, my_parameter, my_keyword='spacial'):
... try:
... print(mykey_option[my_keyword])
... except:
... print('not in options list')
...
>>> x = MyClass()
>>> x.my_method(1,'discoidal')
OTHER cool stuff
>>> x.my_method(1,'spacial')
Cool stuf
>>> x.my_method(1,'temporal')
You get the gist
>>> x.my_method(1,'newstring')
not in options list
Related
I have a class with code that fits into the following template:
class aClass:
def __init__(self, switch = False):
self.switch = switch
def f(self):
done = False
while not done:
# a dozen lines of code
if self.switch:
# a single line of code
# another dozen lines of code
So the single line of code in the if statement will either never be executed, or it will be executed in all iterations. And this is actually known as soon as the object is initialized.
When self.switch is True, I would like the single line of code to be executed without having to check for self.switch at every single iteration. And when self.switch is False, I would like the single line of code to be ignored, again without having to repeatedly check for self.switch.
I have of course considered writing two versions of f and selecting the appropriate one in __init__ according to the value of the switch, but duplicating all this code except for a single line doesn't feel right.
Can anyone suggest an elegant way to solve this problem? Perhaps a way to generate the appropriate version of the f method at initialization?
That's a completely valid ask. If not for performance then for readability.
Extract the three pieces of logic (before, inside, and after your condition) in three separate methods and in f() just write two implementations of the big loop:
def first(self):
pass
def second(self):
pass
def third(self):
pass
def f(self):
if self.switch:
while ...:
self.first()
self.third()
else:
while ...:
self.first()
self.second()
self.third()
If you want it more elegant (although it depends on taste), you express the two branches of my f() into two methods first_loop and second_loop and then in __init__ assign self.f = self.first_loop or self.f = self.second_loop depending on the switch:
class SuperUnderperformingAccordingToManyYetReadable(object):
def __init__(self, switch):
if self.switch:
self.f = self._first_loop
else:
self.f = self._second_loop
def _first(self):
pass
def _second(self):
pass
def _third(self):
pass
def _first_loop(self):
while ...:
self.first()
self.third()
def _second_loop(self):
while ...:
self.first()
self.second()
self.third()
You may need to do some extra work to manage breaking out of the while loop.
If the .switch attribute is not supposed to change, try to select the loop body dynamicly in the __init__() method:
def __init__(self, switch=False):
self.switch = switch
self.__fBody = self.__fSwitchTrue if switch else self.__fSwitchFalse
def f(self):
self.__done = False
while not self.__done:
self.__fBody()
def __fSwitchTrue(self):
self.__fBodyStart()
... # a single line of code
self.__fBodyEnd()
def __fSwitchFalse(self):
self.__fBodyStart()
self.__fBodyEnd()
def __fBodyStart(self):
... # a dozen lines of code
def __fBodyEnd(self):
... # another dozen lines of code
Remember to change values used by more than one of the defined methods to attributes (like done is changed to .__done).
In a comment to my original question, JohnColeman suggested using exec and provided a link to another relevant question.
That was an excellent suggestion and the solution I was lead to is:
_template_pre = """\
def f(self):
for i in range(5):
print("Executing code before the optional segment.")
"""
_template_opt = """\
print("Executing the optional segment")
"""
_template_post = """\
print("Executing code after the optional segment.")
"""
class aClass:
def __init__(self, switch = False):
if switch:
fdef = _template_pre + _template_opt + _template_post
else:
fdef = _template_pre + _template_post
exec(fdef, globals(), self.__dict__)
# bind the function
self.f = self.f.__get__(self)
You can verify this actually works:
aClass(switch = False).f()
aClass(switch = True).f()
Before jumping to conclusions as to how "pythonic" this is, let me point out that such an approach is employed in a couple of metaclass recipes I have encountered and even in the Python Standard Library (check the implementation of namedtuple, to name one example).
I am making up a handler to handle different types of data. Here is my current solution:
def get_handler_by_type(type):
def handler_for_type_A:
...
#code for processing data type A
def handler_for_type_B:
...
#code for processing data type B
def handler_for_type_C:
...
#code for processing data type C
handler_map = {type_A: handler_for_type_A,
type_B: handler_for_type_B,
type_C: handler_for_type_C,
}
return handler_map(type)
However, this seems quite inefficient as I will call get_handler_by_type frequently and every time it gets called, the dictionary will be constructed again.
I know I could do this instead:
def handler_for_type_A:
...
#code for processing data type A
def handler_for_type_B:
...
#code for processing data type B
def handler_for_type_C:
...
#code for processing data type C
handler_map = {type_A: handler_for_type_A,
type_B: handler_for_type_B,
type_C: handler_for_type_C,
}
def get_handler_by_type(type, handler_map = handler_map):
return handler_map(type)
But this is pretty ugly in my opinion. Because I have handler_for_type_Xs and handler_map that are polluting the global space. Is there a way of doing this both efficiently and elegantly?
Thanks for any inputs.
One way is to look the handler up dynamically (if you have a consistent naming convention)
return vars()['handler_for_'+type]
Another way is to store the map as an attribute of the function
def get_handler_by_type(type):
def handler_for_type_A:
...
#code for processing data type A
def handler_for_type_B:
...
#code for processing data type B
def handler_for_type_C:
...
#code for processing data type C
if not hasattr(get_handler_by_type, 'handler_map'):
get_handler_by_type.handler_map = {'type_A': handler_for_type_A,
'type_B': handler_for_type_B,
'type_C': handler_for_type_C,
}
return get_handler_by_type.handler_map[type]
This way will encapsulate it:
def _handler_helper():
def fna():
print "a"
pass
def fnb():
print "b"
pass
m = {"a":fna,"b":fnb}
return lambda x:m[x]
get_handler_by_type = _handler_helper()
You may want to use def if you want to have a docstring, but this works.
Another option might be to have a more OOP approach:
class _HandlerHelper:
def fna(self):
print 'a'
def fnb(self):
print 'b'
# __call__ is a magic method which lets you treat the object as a function
def __call__(self, fn):
return getattr(self, 'fn' + fn)
get_handler_by_type = _HandlerHelper()
Consider the following:
def funcA():
some process = dynamicVar
if dynamicVar == 1:
return dynamicVar
else:
print "no dynamicVar"
def main():
outcome = funcA()
If the 'some process' part results in a 1, the var dynamicVar is passed back as outcome to the main func. If dynamicVar is anything but 1, the routine fails as no arguments are being return.
I could wrap the outcome as a list:
def funcA():
outcomeList = []
some process = dynamicVar
if dynamicVar == 1:
outcomeList.append(dynamicVar)
return outcomeList
else:
print "no dynamicVar"
return outcomeList
def main():
outcome = funcA()
if outcome != []:
do something using dynamicVar
else:
do something else!
or maybe as a dictionary item. Each of the 2 solutions I can think of involve another set of processing in the main / requesting func.
Is this the 'correct' way to handle this eventuality? or is there a better way?
What is the proper way of dealing with this. I was particularly thinking about trying to catch try: / except: errors, so in that example the uses are reversed, so something along the lines of:
def funcA():
some process = dynamicVar
if dynamicVar == 1:
return
else:
outcome = "no dynamicVar"
return outcome
def main():
try:
funcA()
except:
outcome = funcA.dynamicVar
In Python, all function that do not return a value will implicitly return None. So you can just check if outcome is not None in main().
I believe when you write a function, it's return value should be clear and expected. You should return what you say you will return. That being said, you can use None as a meaningful return value to indicate that the operation failed or produced no results:
def doSomething():
"""
doSomething will return a string value
If there is no value available, None will be returned
"""
if check_something():
return "a string"
# this is being explicit. If you did not do this,
# None would still be returned. But it is nice
# to be verbose so it reads properly with intent.
return None
Or you can make sure to always return a default of the same type:
def doSomething():
"""
doSomething will return a string value
If there is no value available, and empty string
will be returned
"""
if check_something():
return "a string"
return ""
This handles the case with a bunch of complex conditional tests that eventually just fall through:
def doSomething():
if foo:
if bar:
if biz:
return "value"
return ""
I have a five or six resources that have nice 'with' handlers, and normally I'd do this:
with res1, res2, res3, res4, res5, res6:
do1
do2
However, sometimes one or more of these resources should not be activated. Which leads to very ugly repetitive code:
with res1, res3, res4, res6: # these always acquired
if res2_enabled:
with res2:
if res5_enabled:
with res5:
do1
do2
else:
do1
do2
else if res5_enabled:
with res5:
...
There must be clean easy ways to do this surely?
You could create a wrapper object that supports the with statement, and do the checking in there. Something like:
with wrapper(res1), wrapper(res2), wrapper(res3):
...
or a wrapper than handles all of them:
with wrapper(res1, res2, res3):
...
The definition for you wrapper would be:
class wrapper(object):
def __init__(self, *objs):
...
def __enter__(self):
initialize objs here
def __exit__(self):
release objects here
If I understand you correctly you can do this:
from contextlib import contextmanager, nested
def enabled_resources(*resources):
return nested(*(res for res,enabled in resources if enabled))
# just for testing
#contextmanager
def test(n):
print n, "entered"
yield
resources = [(test(n), n%2) for n in range(10)]
# you want
# resources = [(res1, res1_enabled), ... ]
with enabled_resources(*resources):
# do1, do2
pass
Original Poster here; here is my approach refined so far:
I can add (or monkey-patch) the bool operator __nonzero__ onto the with objects, returning whether they are enabled. Then, when objects are mutually exclusive, I can have:
with res1 or res2 or res3 or res4:
...
When an resource is togglable, I can create an empty withable that is a nop; wither seems a nice name for it:
class sither:
#classmethod
def __enter__(cls): pass
#classmethod
def __exit__(cls,*args): pass
...
with res1 or wither, res2 or wither:
...
I can also use this keeping the toggling out of the withable objects:
with res1 if res1enabled else wither, res2 if res2enabled else wither:
..
Finally, those I have most control over, I can integrate the enabled checking into the class itself such that when used and not enabled, they are nop:
with res1, res2, res3:
...
The with statement is absolutely adorable, it just seems a bit unentrenched yet. It will be interesting to see what finesse others come up with in this regard...
I asked previously how the nested functions work, but unfortunately I still don't quite get it. To understand it better, can someone please show some real-wold, practical usage examples of nested functions?
Many thanks
Your question made me curious, so I looked in some real-world code: the Python standard library. I found 67 examples of nested functions. Here are a few, with explanations.
One very simple reason to use a nested function is simply that the function you're defining doesn't need to be global, because only the enclosing function uses it. A typical example from Python's quopri.py standard library module:
def encode(input, output, quotetabs, header = 0):
...
def write(s, output=output, lineEnd='\n'):
# RFC 1521 requires that the line ending in a space or tab must have
# that trailing character encoded.
if s and s[-1:] in ' \t':
output.write(s[:-1] + quote(s[-1]) + lineEnd)
elif s == '.':
output.write(quote(s) + lineEnd)
else:
output.write(s + lineEnd)
... # 35 more lines of code that call write in several places
Here there was some common code within the encode function, so the author simply factored it out into a write function.
Another common use for nested functions is re.sub. Here's some code from the json/encode.py standard library module:
def encode_basestring(s):
"""Return a JSON representation of a Python string
"""
def replace(match):
return ESCAPE_DCT[match.group(0)]
return '"' + ESCAPE.sub(replace, s) + '"'
Here ESCAPE is a regular expression, and ESCAPE.sub(replace, s) finds all matches of ESCAPE in s and replaces each one with replace(match).
In fact, any API, like re.sub, that accepts a function as a parameter can lead to situations where nested functions are convenient. For example, in turtle.py there's some silly demo code that does this:
def baba(xdummy, ydummy):
clearscreen()
bye()
...
tri.write(" Click me!", font = ("Courier", 12, "bold") )
tri.onclick(baba, 1)
onclick expects you to pass an event-handler function, so we define one and pass it in.
Decorators are a very popular use for nested functions. Here's an example of a decorator that prints a statement before and after any call to the decorated function.
def entry_exit(f):
def new_f(*args, **kwargs):
print "Entering", f.__name__
f(*args, **kwargs)
print "Exited", f.__name__
return new_f
#entry_exit
def func1():
print "inside func1()"
#entry_exit
def func2():
print "inside func2()"
func1()
func2()
print func1.__name__
Nested functions avoid cluttering other parts of the program with other functions and variables that only make sense locally.
A function that return Fibonacci numbers could be defined as follows:
>>> def fib(n):
def rec():
return fib(n-1) + fib(n-2)
if n == 0:
return 0
elif n == 1:
return 1
else:
return rec()
>>> map(fib, range(10))
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
EDIT: In practice, generators would be a better solution for this, but the example shows how to take advantage of nested functions.
They are useful when using functions that take other functions as input. Say you're in a function, and want to sort a list of items based on the items' value in a dict:
def f(items):
vals = {}
for i in items: vals[i] = random.randint(0,100)
def key(i): return vals[i]
items.sort(key=key)
You can just define key right there and have it use vals, a local variable.
Another use-case is callbacks.
I have only had to use nested functions when creating decorators. A nested function is basically a way of adding some behavior to a function without knowing what the function is that you are adding behavior to.
from functools import wraps
from types import InstanceType
def printCall(func):
def getArgKwargStrings(*args, **kwargs):
argsString = "".join(["%s, " % (arg) for arg in args])
kwargsString = "".join(["%s=%s, " % (key, value) for key, value in kwargs.items()])
if not len(kwargs):
if len(argsString):
argsString = argsString[:-2]
else:
kwargsString = kwargsString[:-2]
return argsString, kwargsString
#wraps(func)
def wrapper(*args, **kwargs):
ret = None
if args and isinstance(args[0], InstanceType) and getattr(args[0], func.__name__, None):
instance, args = args[0], args[1:]
argsString, kwargsString = getArgKwargStrings(*args, **kwargs)
ret = func(instance, *args, **kwargs)
print "Called %s.%s(%s%s)" % (instance.__class__.__name__, func.__name__, argsString, kwargsString)
print "Returned %s" % str(ret)
else:
argsString, kwargsString = getArgKwargStrings(*args, **kwargs)
ret = func(*args, **kwargs)
print "Called %s(%s%s)" % (func.__name__, argsString, kwargsString)
print "Returned %s" % str(ret)
return ret
return wrapper
def sayHello(name):
print "Hello, my name is %s" % (name)
if __name__ == "__main__":
sayHelloAndPrintDebug = printCall(sayHello)
name = "Nimbuz"
sayHelloAndPrintDebug(name)
Ignore all the mumbo jumbo in the "printCall" function for right now and focus only the "sayHello" function and below. What we're doing here is we want to print out how the "sayHello" function was called everytime it is called without knowing or altering what the "sayHello" function does. So we redefine the "sayHello" function by passing it to "printCall", which returns a NEW function that does what the "sayHello" function does AND prints how the "sayHello" function was called. This is the concept of decorators.
Putting "#printCall" above the sayHello definition accomplishes the same thing:
#printCall
def sayHello(name):
print "Hello, my name is %s" % (name)
if __name__ == "__main__":
name = "Nimbuz"
sayHello(name)
Yet another (very simple) example. A function that returns another function. Note how the inner function (that is returned) can use variables from the outer function's scope.
def create_adder(x):
def _adder(y):
return x + y
return _adder
add2 = create_adder(2)
add100 = create_adder(100)
>>> add2(50)
52
>>> add100(50)
150
Python Decorators
This is actually another topic to learn, but if you look at the stuff on 'Using Functions as Decorators', you'll see some examples of nested functions.
OK, besides decorators: Say you had an application where you needed to sort a list of strings based on substrings which varied from time to time. Now the sorted functions takes a key= argument which is a function of one argument: the items (strings in this case) to be sorted. So how to tell this function which substrings to sort on? A closure or nested function, is perfect for this:
def sort_key_factory(start, stop):
def sort_key(string):
return string[start: stop]
return sort_key
Simple eh? You can expand on this by encapsulating start and stop in a tuple or a slice object and then passing a sequence or iterable of these to the sort_key_factory.