Excuse my poor wording in the title, but here's a longer explanation:
I have a function which as arguments takes some functions which are used to determine which data to retrieve from a database, as such:
def customer_data(customer_name, *args):
# initialize dictionary with ids
codata = dict([(data.__name__, []) for data in args])
codata['customer_observer_id'] = _customer_observer_ids(customer_name)
# add values to dictionary using function name as key
for data in args:
for coid in codata['customer_observer_id']:
codata[data.__name__].append(data(coid))
return codata
Which makes the call to the function looking something like this:
customer_data('customername', target_parts, source_group, ...)
One of these functions is defined with an extra parameter:
def polarization_value(customer_observer_id, timespan='day')
What I would like is a way to change the timespan variable in a clever way. One obvious way is to include a keyword argument in customer_observer and add an exception when the function name being called is 'polarization_value', but I have a feeling there is a better way to do this.
You can use functools.partial and pass polarization_value as :
functools.partial(polarization_value, timespan='day')
Example:
>>> import functools
def func(x, y=1):
print x, y
...
>>> new_func = functools.partial(func, y=20)
>>> new_func(100)
100 20
You may also find this helpful: Python: Why is functools.partial necessary?
Related
I am using a 3rd party library function which has a large number of positional and named arguments. The function is called from numerous points in my code with identical arguments/values.
For ease of maintenance I don't want to hard-code the dozens of identical arguments multiple times throughout my code. I was hoping there was a way of storing them once in a data structure so I just need to pass the data structure. Along the lines of the following:
Assume the signature of the function I'm calling looks like:
def lib_function(arg1, arg2, arg3=None, arg4=None):
Assume that throughout my code I want to call it with values of
a for arg1,
b for arg2
d for arg4
(and I'm not using arg3).
I've tried defining a data structure as follows:
arguments = ('a', 'b', {'arg4':'d'})
and using it like this:
res = lib_function(arguments)
but this is obviously not correct - the tuple and dict are not unpacked during the call but are handled as a single first argument.
Is there a way of doing this in Python?
The obvious alternative is to proxy lib_function in my code, with the arguments hard-coded in the proxy which is then called with no arguments. Something like:
def proxy_lib_function():
return lib_function('a', 'b', arg4='d')
res = proxy_lib_function()
However I wanted to check there isn't a more Pythonic way of doing this.
Separate positional and named arguments and use asterisk unpacking:
def lib_function(arg1, arg2, arg3=None, arg4=None):
print(locals())
args = ("a", "b")
kwargs = {"arg4": "d"}
res = lib_function(*args, **kwargs)
Your function is:
def lib_function(arg1, arg2, arg3=None, arg4=None):
Define another function:
def yourFunction(x):
return lib_function(x[0], x[1], x[2], x[3])
The "data structure" would be:
data = [yourData1, yourData2, yourData3, yourData4]
Then you can call your new function with this:
yourFunction(data)
I want to use partial from functools to partially apply a function's second argument, I know it is easy to do with lambda rather than partial as follows
>>> def func1(a,b):
... return a/b
...
>>> func2 = lambda x:func1(x,2)
>>> func2(4)
2
but I strictly want to use partial here (for the sake of learning) so i came up with this.
>>> def swap_binary_args(func):
... return lambda x,y: func(y,x)
...
>>> func3 = partial(swap_binary_args(func1),2)
>>> func3(4)
2
Is it possible to extend this strategy to a level where I can partial apply any arguments at any place like in the following pseudocode
>>>def indexed_partial(func, list_of_index, *args):
... ###do_something###
... return partially_applied_function
>>>func5=indexed_partial(func1, [1,4,3,5], 2,4,5,6)
in our case I can use this function as follows
>>>func6=indexed_partial(func1, [1], 2)
Is it possible to have an indexed partial like I want ? is there anything similar to this already which I am not aware of ? and more importantly is the idea of indexed partial generally a good or bad idea why ?
This question has been marked as possible duplicate of Can one partially apply the second argument of a function that takes no keyword arguments?
in that question the OP asked is it possible to partially apply second argument but here i am asking how to cook a function that can partially apply any arbitrary argument
I, too, think what you ask can't be done (easily?) with functools.partial. Probably the best (and most readable) solution is to use partial with keyword-arguments.
However, in case you want to use positional arguments (and hence indexed partial arguments), here is a possible definition of indexed_partial:
def indexed_partial(func, list_of_index, *args):
def partially_applied_function(*fargs, **fkwargs):
nargs = len(args) + len(fargs)
iargs = iter(args)
ifargs = iter(fargs)
posargs = ((ifargs, iargs)[i in list_of_index].next() for i in range(nargs))
return func(*posargs, **fkwargs)
return partially_applied_function
I've found various detailed explanations on how to pass long lists of arguments into a function, but I still kinda doubt if that's proper way to do it.
In other words, I suspect that I'm doing it wrong, but I can't see how to do it right.
The problem: I have (not very long) recurrent function, which uses quite a number of variables and needs to modify some content in at least some of them.
What I end up with is sth like this:
def myFunction(alpha, beta, gamma, zeta, alphaList, betaList, gammaList, zetaList):
<some operations>
myFunction(alpha, beta, modGamma, zeta, modAlphaList, betaList, gammaList, modZetaList)
...and I want to see the changes I did on original variables (in C I would just pass a reference, but I hear that in Python it's always a copy?).
Sorry if noob, I don't know how to phrase this question so I can find relevant answers.
You could wrap up all your parameters in a class, like this:
class FooParameters:
alpha = 1.0
beta = 1.0
gamma = 1.0
zeta = 1.0
alphaList = []
betaList = []
gammaList = []
zetaList = []
and then your function takes a single parameter instance:
def myFunction(params):
omega = params.alpha * params.beta + exp(params.gamma)
# more magic...
calling like:
testParams = FooParameters()
testParams.gamma = 2.3
myFunction(testParams)
print params.zetaList
Because the params instance is passed by reference, changes in the function are preserved.
This is commonly used in matplotlib, for example. They pass the long list of arguments using * or **, like:
def function(*args, **kwargs):
do something
Calling function:
function(1,2,3,4,5, a=1, b=2, b=3)
Here 1,2,3,4,5 will go to args and a=1, b=2, c=3 will go to kwargs, as a dictionary. So that they arrive at your function like:
args = [1,2,3,4,5]
kwargs = {a:1, b:2, c:3}
And you can treat them in the way you want.
I don't know where you got the idea that Python copies values when passing into a function. That is not at all true.
On the contrary: each parameter in a function is an additional name referring to the original object. If you change the value of that object in some way - for example, if it's a list and you change one of its members - then the original will also see that change. But if you rebind the name to something else - say by doing alpha = my_completely_new_value - then the original remains unchanged.
You may be tempted to something akin to this:
def myFunction(*args):
var_names = ['alpha','beta','gamma','zeta']
locals().update(zip(var_names,args))
myFunction(alpha,beta,gamma,zeta)
However, this 'often' won't work. I suggest introducing another namespace:
from collections import OrderedDict
def myFunction(*args):
var_names = ['alpha','beta','gamma','zeta']
vars = OrderedDict(zip(var_names,args))
#get them all via vars[var_name]
myFunction(*vars.values()) #since we used an orderedDict we can simply do *.values()
you can capture the non-modfied values in a closure:
def myFunction(alpha, beta, gamma, zeta, alphaList, betaList, gammaList, zetaList):
def myInner(g=gamma, al, zl):
<some operations>
myInner(modGamma, modAlphaList, modZetaList)
myInner(al=alphaList, zl=zetaList)
(BTW, this is about the only way to write a truly recursive function in Python.)
You could pass in a dictionary and return a new dictionary. Or put your method in a class and have alpha, beta etc. be attributes.
You should put myFunction in a class. Set up the class with the appropriate attributes and call the appropriate functions. The state is then well contained in the class.
I have created a class MyClassthat contains a lot of simulation data. The class groups simulation results for different simulations that have a similar structure. The results can be retreived with a MyClass.get(foo) method. It returns a dictionary with simulationID/array pairs, array being the value of foo for each simulation.
Now I want to implement a method in my class to apply any function to all the arrays for foo. It should return a dictionary with simulationID/function(foo) pairs.
For a function that does not need additional arguments, I found the following solution very satisfying (comments always welcome :-) ):
def apply(self, function, variable):
result={}
for k,v in self.get(variable).items():
result[k] = function(v)
return result
However, for a function requiring additional arguments I don't see how to do it in an elegant way. A typical operation would be the integration of foo with bar as x-values like np.trapz(foo, x=bar), where both foo and bar can be retreived with MyClass.get(...)
I was thinking in this direction:
def apply(self, function_call):
"""
function_call should be a string with the complete expression to evaluate
eg: MyClass.apply('np.trapz(QHeat, time)')
"""
result={}
for SID in self.simulations:
result[SID] = eval(function_call, locals=...)
return result
The problem is that I don't know how to pass the locals mapping object. Or maybe I'm looking in a wrong direction. Thanks on beforehand for your help.
Roel
You have two ways. The first is to use functools.partial:
foo = self.get('foo')
bar = self.get('bar')
callable = functools.partial(func, foo, x=bar)
self.apply(callable, variable)
while the second approach is to use the same technique used by partial, you can define a function that accept arbitrary argument list:
def apply(self, function, variable, *args, **kwds):
result={}
for k,v in self.get(variable).items():
result[k] = function(v, *args, **kwds)
return result
Note that in both case the function signature remains unchanged. I don't know which one I'll choose, maybe the first case but I don't know the context on you are working on.
I tried to recreate (the relevant part of) the class structure the way I am guessing it is set up on your side (it's always handy if you can provide a simplified code example for people to play/test).
What I think you are trying to do is translate variable names to variables that are obtained from within the class and then use those variables in a function that was passed in as well. In addition to that since each variable is actually a dictionary of values with a key (SID), you want the result to be a dictionary of results with the function applied to each of the arguments.
class test:
def get(self, name):
if name == "valA":
return {"1":"valA1", "2":"valA2", "3":"valA3"}
elif name == "valB":
return {"1":"valB1", "2":"valB2", "3":"valB3"}
def apply(self, function, **kwargs):
arg_dict = {fun_arg: self.get(sim_args) for fun_arg, sim_args in kwargs.items()}
result = {}
for SID in arg_dict[kwargs.keys()[0]]:
fun_kwargs = {fun_arg: sim_dict[SID] for fun_arg, sim_dict in arg_dict.items()}
result[SID] = function(**fun_kwargs)
return result
def joinstrings(string_a, string_b):
return string_a+string_b
my_test = test()
result = my_test.apply(joinstrings, string_a="valA", string_b="valB")
print result
So the apply method gets an argument dictionary, gets the class specific data for each of the arguments and creates a new argument dictionary with those (arg_dict).
The SID keys are obtained from this arg_dict and for each of those, a function result is calculated and added to the result dictionary.
The result is:
{'1': 'valA1valB1', '3': 'valA3valB3', '2': 'valA2valB2'}
The code can be altered in many ways, but I thought this would be the most readable. It is of course possible to join the dictionaries instead of using the SID's from the first element etc.
I have a function that has several outputs, all of which "native", i.e. integers and strings. For example, let's say I have a function that analyzes a string, and finds both the number of words and the average length of a word.
In C/C++ I would use # to pass 2 parameters to the function. In Python I'm not sure what's the right solution, because integers and strings are not passed by reference but by value (at least this is what I understand from trial-and-error), so the following code won't work:
def analyze(string, number_of_words, average_length):
... do some analysis ...
number_of_words = ...
average_length = ...
If i do the above, the values outside the scope of the function don't change. What I currently do is use a dictionary like so:
def analyze(string, result):
... do some analysis ...
result['number_of_words'] = ...
result['average_length'] = ...
And I use the function like this:
s = "hello goodbye"
result = {}
analyze(s, result)
However, that does not feel right. What's the correct Pythonian way to achieve this? Please note I'm referring only to cases where the function returns 2-3 results, not tens of results. Also, I'm a complete newbie to Python, so I know I may be missing something trivial here...
Thanks
python has a return statement, which allows you to do the follwing:
def func(input):
# do calculation on input
return result
s = "hello goodbye"
res = func(s) # res now a result dictionary
but you don't need to have result at all, you can return a few values like so:
def func(input):
# do work
return length, something_else # one might be an integer another string, etc.
s = "hello goodbye"
length, something = func(s)
If you return the variables in your function like this:
def analyze(s, num_words, avg_length):
# do something
return s, num_words, avg_length
Then you can call it like this to update the parameters that were passed:
s, num_words, avg_length = analyze(s, num_words, avg_length)
But, for your example function, this would be better:
def analyze(s):
# do something
return num_words, avg_length
In python you don't modify parameters in the C/C++ way (passing them by reference or through a pointer and doing modifications in situ).There are some reasons such as that the string objects are inmutable in python. The right thing to do is to return the modified parameters in a tuple (as SilentGhost suggested) and rebind the variables to the new values.
If you need to use method arguments in both directions, you can encapsulate the arguments to the class and pass object to the method and let the method use its properties.