Least Astonishment and the Mutable Default Argument

Question

Anyone tinkering with Python long enough has been bitten  or torn to pieces  by the following issue   def foo a          a append 5      return a   Python novices would expect this function to always return a list with only one element   5   The result is instead very different  and very astonishing  for a novice     gt  gt  gt  foo    5   gt  gt  gt  foo    5  5   gt  gt  gt  foo    5  5  5   gt  gt  gt  foo    5  5  5  5   gt  gt  gt  foo     A manager of mine once had his first encounter with this feature  and called it  a dramatic design flaw  of the language  I replied that the behavior had an underlying explanation  and it is indeed very puzzling and unexpected if you don t understand the internals  However  I was not able to answer  to myself  the following question  what is the reason for binding the default argument at function definition  and not at function execution  I doubt the experienced behavior has a practical use  who really used static variables in C  without breeding bugs    Edit    Baczek made an interesting example  Together with most of your comments and Utaal s in particular  I elaborated further    gt  gt  gt  def a            print  a executed           return          gt  gt  gt               gt  gt  gt  def b x a             x append 5          print x       a executed  gt  gt  gt  b    5   gt  gt  gt  b    5  5    To me  it seems that the design decision was relative to where to put the scope of parameters  inside the function or  together  with it   Doing the binding inside the function would mean that x is effectively bound to the specified default when the function is called  not defined  something that would present a deep flaw  the def line would be  hybrid  in the sense that part of the binding  of the function object  would happen at definition  and part  assignment of default parameters  at function invocation time   The actual behavior is more consistent  everything of that line gets evaluated when that line is executed  meaning at function definition

User · Answer

This actually has nothing to do with default values, other than that it often comes up as an unexpected behaviour when you write functions with mutable default values.

>>> def foo(a):
    a.append(5)
    print a

>>> a  = [5]
>>> foo(a)
[5, 5]
>>> foo(a)
[5, 5, 5]
>>> foo(a)
[5, 5, 5, 5]
>>> foo(a)
[5, 5, 5, 5, 5]

No default values in sight in this code, but you get exactly the same problem.

The problem is that foo is modifying a mutable variable passed in from the caller, when the caller doesn't expect this. Code like this would be fine if the function was called something like append_5; then the caller would be calling the function in order to modify the value they pass in, and the behaviour would be expected. But such a function would be very unlikely to take a default argument, and probably wouldn't return the list (since the caller already has a reference to that list; the one it just passed in).

Your original foo, with a default argument, shouldn't be modifying a whether it was explicitly passed in or got the default value. Your code should leave mutable arguments alone unless it is clear from the context/name/documentation that the arguments are supposed to be modified. Using mutable values passed in as arguments as local temporaries is an extremely bad idea, whether we're in Python or not and whether there are default arguments involved or not.

If you need to destructively manipulate a local temporary in the course of computing something, and you need to start your manipulation from an argument value, you need to make a copy.

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This  bug  gave me a lot of overtime work hours  But I m beginning to see a potential use of it  but I would have liked it to be at the execution time  still   I m gonna give you what I see as a useful example   def example errors            statements       Something went wrong     mistake   True     if mistake          tryToFixIt errors            Didn t work   let s try again         tryToFixItAnotherway errors            This time it worked     return errors  def tryToFixIt err       err append  Attempt to fix it    def tryToFixItAnotherway err       err append  Attempt to fix it by another way    def main        for item in range 2           errors   example       print   n  join errors   main     prints the following  Attempt to fix it Attempt to fix it by another way Attempt to fix it Attempt to fix it by another way

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I know nothing about the Python interpreter inner workings  and I m not an expert in compilers and interpreters either  so don t blame me if I propose anything unsensible or impossible   Provided that python objects are mutable I think that this should be taken into account when designing the default arguments stuff  When you instantiate a list   a        you expect to get a new list referenced by a   Why should the a    in  def x a        instantiate a new list on function definition and not on invocation  It s just like you re asking  if the user doesn t provide the argument then instantiate a new list and use it as if it was produced by the caller   I think this is ambiguous instead   def x a datetime datetime now       user  do you want a to default to the datetime corresponding to when you re defining or executing x  In this case  as in the previous one  I ll keep the same behaviour as if the default argument  assignment  was the first instruction of the function  datetime now   called on function invocation   On the other hand  if the user wanted the definition-time mapping he could write   b   datetime datetime now   def x a b     I know  I know  that s a closure  Alternatively Python might provide a keyword to force definition-time binding   def x static a b

User · Answer

Just change the function to be   def notastonishinganymore a                The name is just a joke           a   a        a append 5      return a

User · Answer

Actually  this is not a design flaw  and it is not because of internals  or performance  It comes simply from the fact that functions in Python are first-class objects  and not only a piece of code  As soon as you get to think into this way  then it completely makes sense  a function is an object being evaluated on its definition  default parameters are kind of  quot member data quot  and therefore their state may change from one call to the other - exactly as in any other object  In any case  Effbot has a very nice explanation of the reasons for this behavior in Default Parameter Values in Python  I found it very clear  and I really suggest reading it for a better knowledge of how function objects work

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Why don t you introspect   I m really surprised no one has performed the insightful introspection offered by Python  2 and 3 apply  on callables    Given a simple little function func defined as    gt  gt  gt  def func a               a append 5    When Python encounters it  the first thing it will do is compile it in order to create a code object for this function  While this compilation step is done  Python evaluates  and then stores the default arguments  an empty list    here  in the function object itself  As the top answer mentioned  the list a can now be considered a member of the function func   So  let s do some introspection  a before and after to examine how the list gets expanded inside the function object  I m using Python 3 x for this  for Python 2 the same applies  use   defaults   or func defaults in Python 2  yes  two names for the same thing    Function Before Execution    gt  gt  gt  def func a                a append 5             After Python executes this definition it will take any default parameters specified  a      here  and cram them in the   defaults   attribute for the function object  relevant section  Callables          gt  gt  gt  func   defaults           O k  so an empty list as the single entry in   defaults    just as expected    Function After Execution   Let s now execute this function    gt  gt  gt  func     Now  let s see those   defaults   again     gt  gt  gt  func   defaults     5      Astonished  The value inside the object changes  Consecutive calls to the function will now simply append to that embedded list object    gt  gt  gt  func    func    func    gt  gt  gt  func   defaults     5  5  5  5      So  there you have it  the reason why this  flaw  happens  is because default arguments are part of the function object  There s nothing weird going on here  it s all just a bit surprising   The common solution to combat this is to use None as the default and then initialize in the function body   def func a   None         or  a      if a is None else a     if a is None          a        Since the function body is executed anew each time  you always get a fresh new empty list if no argument was passed for a     To further verify that the list in   defaults   is the same as that used in the function func you can just change your function to return the id of the list a used inside the function body  Then  compare it to the list in   defaults    position  0  in   defaults    and you ll see how these are indeed refering to the same list instance    gt  gt  gt  def func a                 a append 5          return id a   gt  gt  gt   gt  gt  gt  id func   defaults   0      func   True   All with the power of introspection        To verify that Python evaluates the default arguments during compilation of the function  try executing the following   def bar a input  Did you just see me without calling the function           pass    use raw input in Py2   as you ll notice  input   is called before the process of building the function and binding it to the name bar is made

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1   The so-called problem of  Mutable Default Argument  is in general a special example demonstrating that   All functions with this problem suffer also from similar side effect problem on the actual parameter   That is against the rules of functional programming  usually undesiderable and should be fixed both together   Example   def foo a                        the same problematic function     a append 5      return a   gt  gt  gt  somevar    1  2              an example without a default parameter  gt  gt  gt  foo somevar   1  2  5   gt  gt  gt  somevar  1  2  5                         usually expected  1  2    Solution   a copy An absolutely safe solution is to copy or deepcopy the input object first and then to do whatever with the copy   def foo a          a   a          a copy     a append 5      return a       or everything safe by one line   return a    5     Many builtin mutable types have a copy method like some dict copy   or some set copy   or can be copied easy like somelist    or list some list   Every object can be also copied by copy copy any object  or more thorough by copy deepcopy    the latter useful if the mutable object is composed from mutable objects   Some objects are fundamentally based on side effects like  file  object and can not be meaningfully reproduced by copy  copying  Example problem for a similar SO question  class Test object                the original problematic class   def   init   self  var1          self  var1   var1  somevar    1  2                  an example without a default parameter t1   Test somevar  t2   Test somevar  t1  var1 append  1   print somevar                     1  2   1   but usually expected  1  2  print t2  var1                    1  2   1   but usually expected  1  2    It shouldn t be neither saved in any public attribute of an instance returned by this function   Assuming that private attributes of instance should not be modified from outside of this class or subclasses by convention  i e   var1 is a private attribute    Conclusion  Input parameters objects shouldn t be modified in place  mutated  nor they should not be binded into an object returned by the function   If we prefere programming without side effects which is strongly recommended  see Wiki about  side effect   The first two paragraphs are relevent in this context       2  Only if the side effect on the actual parameter is required but unwanted on the default parameter then the useful solution is def     var1 None   if var1 is None  var1      More    3  In some cases is the mutable behavior of default parameters useful

User · Answer

You can get round this by replacing the object  and therefore the tie with the scope    def foo a          a   list a      a append 5      return a   Ugly  but it works

User · Answer

What you re asking is why this   def func a     b   2       pass   isn t internally equivalent to this   def func a None  b   None       a default   lambda         b default   lambda  2     def actual func a None  b None           if a is None  a   a default           if b is None  b   b default       return actual func func   func     except for the case of explicitly calling func None  None   which we ll ignore   In other words  instead of evaluating default parameters  why not store each of them  and evaluate them when the function is called   One answer is probably right there--it would effectively turn every function with default parameters into a closure   Even if it s all hidden away in the interpreter and not a full-blown closure  the data s got to be stored somewhere   It d be slower and use more memory

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When we do this   def foo a                    we assign the argument a to an unnamed list  if the caller does not pass the value of a   To make things simpler for this discussion  let s temporarily give the unnamed list a name  How about pavlo    def foo a pavlo            At any time  if the caller doesn t tell us what a is  we reuse pavlo   If pavlo is mutable  modifiable   and foo ends up modifying it  an effect we notice the next time foo is called without specifying a   So this is what you see  Remember  pavlo is initialized to         gt  gt  gt  foo     5    Now  pavlo is  5    Calling foo   again modifies pavlo again    gt  gt  gt  foo    5  5    Specifying a when calling foo   ensures pavlo is not touched    gt  gt  gt  ivan    1  2  3  4   gt  gt  gt  foo a ivan   1  2  3  4  5   gt  gt  gt  ivan  1  2  3  4  5    So  pavlo is still  5  5     gt  gt  gt  foo    5  5  5

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Suppose you have the following code  fruits     apples    bananas    loganberries    def eat food fruits             When I see the declaration of eat  the least astonishing thing is to think that if the first parameter is not given  that it will be equal to the tuple   apples    bananas    loganberries    However  supposed later on in the code  I do something like  def some random function        global fruits     fruits     blueberries    mangos     then if default parameters were bound at function execution rather than function declaration then I would be astonished  in a very bad way  to discover that fruits had been changed   This would be more astonishing IMO than discovering that your foo function above was mutating the list   The real problem lies with mutable variables  and all languages have this problem to some extent  Here s a question  suppose in Java I have the following code   StringBuffer s   new StringBuffer  Hello World     Map lt StringBuffer Integer gt  counts   new HashMap lt StringBuffer Integer gt     counts put s  5   s append          System out println  counts get s         does this work    Now  does my map use the value of the StringBuffer key when it was placed into the map  or does it store the key by reference   Either way  someone is astonished  either the person who tried to get the object out of the Map using a value identical to the one they put it in with  or the person who can t seem to retrieve their object even though the key they re using is literally the same object that was used to put it into the map  this is actually why Python doesn t allow its mutable built-in data types to be used as dictionary keys    Your example is a good one of a case where Python newcomers will be surprised and bitten   But I d argue that if we  fixed  this  then that would only create a different situation where they d be bitten instead  and that one would be even less intuitive  Moreover  this is always the case when dealing with mutable variables  you always run into cases where someone could intuitively expect one or the opposite behavior depending on what code they re writing   I personally like Python s current approach  default function arguments are evaluated when the function is defined and that object is always the default  I suppose they could special-case using an empty list  but that kind of special casing would cause even more astonishment  not to mention be backwards incompatible

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I used to think that creating the objects at runtime would be the better approach   I m less certain now  since you do lose some useful features  though it may be worth it regardless simply to prevent newbie confusion   The disadvantages of doing so are   1  Performance  def foo arg something expensive to compute                If call-time evaluation is used  then the expensive function is called every time your function is used without an argument   You d either pay an expensive price on each call  or need to manually cache the value externally  polluting your namespace and adding verbosity   2  Forcing bound parameters  A useful trick is to bind parameters of a lambda to the current binding of a variable when the lambda is created   For example   funcs     lambda i i  i for i in range 10     This returns a list of functions that return 0 1 2 3    respectively   If the behaviour is changed  they will instead bind i to the call-time value of i  so you would get a list of functions that all returned 9   The only way to implement this otherwise would be to create a further closure with the i bound  ie   def make func i   return lambda  i funcs    make func i  for i in range 10     3  Introspection  Consider the code   def foo a  test   b 100  c         print a b c   We can get information about the arguments and defaults using the inspect module  which    gt  gt  gt  inspect getargspec foo     a    b    c    None  None    test   100         This information is very useful for things like document generation  metaprogramming  decorators etc   Now  suppose the behaviour of defaults could be changed so that this is the equivalent of    undefined   object      sentinel value  def foo a  undefined  b  undefined  c  undefined      if a is  undefined  a  test      if b is  undefined  b 100     if c is  undefined  c      However  we ve lost the ability to introspect  and see what the default arguments are   Because the objects haven t been constructed  we can t ever get hold of them without actually calling the function   The best we could do is to store off the source code and return that as a string

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The solutions here are    Use None as your default value  or a nonce object   and switch on that to create your values at runtime  or Use a lambda as your default parameter  and call it within a try block to get the default value  this is the sort of thing that lambda abstraction is for     The second option is nice because users of the function can pass in a callable  which may be already existing  such as a type

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It may be true that    Someone is using every language library feature  and Switching the behavior here would be ill-advised  but   it is entirely consistent to hold to both of the features above and still make another point    It is a confusing feature and it is unfortunate in Python    The other answers  or at least some of them either make points 1 and 2 but not 3  or make point 3 and downplay points 1 and 2  But all three are true   It may be true that switching horses in midstream here would be asking for significant breakage  and that there could be more problems created by changing Python to intuitively handle Stefano s opening snippet  And it may be true that someone who knew Python internals well could explain a minefield of consequences  However   The existing behavior is not Pythonic  and Python is successful because very little about the language violates the principle of least astonishment anywhere near this badly  It is a real problem  whether or not it would be wise to uproot it  It is a design flaw  If you understand the language much better by trying to trace out the behavior  I can say that C   does all of this and more  you learn a lot by navigating  for instance  subtle pointer errors  But this is not Pythonic  people who care about Python enough to persevere in the face of this behavior are people who are drawn to the language because Python has far fewer surprises than other language  Dabblers and the curious become Pythonistas when they are astonished at how little time it takes to get something working--not because of a design fl--I mean  hidden logic puzzle--that cuts against the intuitions of programmers who are drawn to Python because it Just Works

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A simple workaround using None   gt  gt  gt  def bar b  data None           data   data or            data append b          return data       gt  gt  gt  bar 3   3   gt  gt  gt  bar 3   3   gt  gt  gt  bar 3   3   gt  gt  gt  bar 3   34    34  3   gt  gt  gt  bar 3   34    34  3

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This behavior is easy explained by    function  class etc   declaration is executed only once  creating all default value objects everything is passed by reference   So   def x a 0  b     c     d 0       a   a   1     b   b    1      c append 1      print a  b  c    a doesn t change - every assignment call creates new int object - new object is printed b doesn t change - new array is build from default value and printed c changes - operation is performed on same object - and it is printed

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Well  the reason is quite simply that bindings are done when code is executed  and the function definition is executed  well    when the functions is defined   Compare this   class BananaBunch      bananas           def addBanana self  banana           self bananas append banana    This code suffers from the exact same unexpected happenstance  bananas is a class attribute  and hence  when you add things to it  it s added to all instances of that class  The reason is exactly the same   It s just  How It Works   and making it work differently in the function case would probably be complicated  and in the class case likely impossible  or at least slow down object instantiation a lot  as you would have to keep the class code around and execute it when objects are created   Yes  it is unexpected  But once the penny drops  it fits in perfectly with how Python works in general  In fact  it s a good teaching aid  and once you understand why this happens  you ll grok python much better   That said it should feature prominently in any good Python tutorial  Because as you mention  everyone runs into this problem sooner or later

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This is not a design flaw  Anyone who trips over this is doing something wrong   There are 3 cases I see where you might run into this problem    You intend to modify the argument as a side effect of the function  In this case it never makes sense to have a default argument  The only exception is when you re abusing the argument list to have function attributes  e g  cache     and you wouldn t be expected to call the function with an actual argument at all  You intend to leave the argument unmodified  but you accidentally did modify it  That s a bug  fix it  You intend to modify the argument for use inside the function  but didn t expect the modification to be viewable outside of the function  In that case you need to make a copy of the argument  whether it was the default or not  Python is not a call-by-value language so it doesn t make the copy for you  you need to be explicit about it    The example in the question could fall into category 1 or 3  It s odd that it both modifies the passed list and returns it  you should pick one or the other

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I sometimes exploit this behavior as an alternative to the following pattern   singleton   None  def use singleton        global singleton      if singleton is None          singleton    make singleton        return singleton use me     If singleton is only used by use singleton  I like the following pattern as a replacement      make singleton   is called only once when the def is executed def use singleton singleton  make singleton         return singleton use me     I ve used this for instantiating client classes that access external resources  and also for creating dicts or lists for memoization   Since I don t think this pattern is well known  I do put a short comment in to guard against future misunderstandings

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Python  The Mutable Default Argument  Default arguments get evaluated at the time the function is compiled into a function object  When used by the function  multiple times by that function  they are and remain the same object    When they are mutable  when mutated  for example  by adding an element to it  they remain mutated on consecutive calls   They stay mutated because they are the same object each time   Equivalent code   Since the list is bound to the function when the function object is compiled and instantiated  this   def foo mutable default argument        make a list the default argument        function that uses a list      is almost exactly equivalent to this    a list        create a list in the globals  def foo mutable default argument  a list     make it the default argument        function that uses a list     del  a list   remove globals name binding   Demonstration  Here s a demonstration - you can verify that they are the same object each time they are referenced by    seeing that the list is created before the function has finished compiling to a function object  observing that the id is the same each time the list is referenced  observing that the list stays changed when the function that uses it is called a second time  observing the order in which the output is printed from the source  which I conveniently numbered for you     example py  print  1  Global scope being evaluated    def create list           noisily create a list for usage as a kwarg        l          print  3  list being created and returned  id      str id l        return l  print  2  example function about to be compiled to an object    def example function default kwarg1 create list         print  appending  a  in default default kwarg1       default kwarg1 append  a       print  list with id      str id default kwarg1                  - is now      repr default kwarg1    print  4  example function compiled      repr example function     if   name         main         print  5  calling example function twice         example function       example function     and running it with python example py   1  Global scope being evaluated 2  example function about to be compiled to an object 3  list being created and returned  id  140502758808032 4  example function compiled   lt function example function at 0x7fc9590905f0 gt  5  calling example function twice   appending  a  in default default kwarg1 list with id  140502758808032 - is now    a   appending  a  in default default kwarg1 list with id  140502758808032 - is now    a    a     Does this violate the principle of  Least Astonishment    This order of execution is frequently confusing to new users of Python  If you understand the Python execution model  then it becomes quite expected    The usual instruction to new Python users   But this is why the usual instruction to new users is to create their default arguments like this instead   def example function 2 default kwarg None       if default kwarg is None          default kwarg        This uses the None singleton as a sentinel object to tell the function whether or not we ve gotten an argument other than the default  If we get no argument  then we actually want to use a new empty list      as the default   As the tutorial section on control flow says      If you don   t want the default to be shared between subsequent calls    you can write the function like this instead   def f a  L None       if L is None          L          L append a      return L

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It s a performance optimization   As a result of this functionality  which of these two function calls do you think is faster   def print tuple some tuple  1 2 3        print some tuple  print tuple           1 print tuple  1 2 3    2   I ll give you a hint   Here s the disassembly  see http   docs python org library dis html     1  0 LOAD GLOBAL              0  print tuple  3 CALL FUNCTION            0 6 POP TOP 7 LOAD CONST               0  None  10 RETURN VALUE    2   0 LOAD GLOBAL              0  print tuple   3 LOAD CONST               4   1  2  3    6 CALL FUNCTION            1  9 POP TOP 10 LOAD CONST               0  None  13 RETURN VALUE      I doubt the experienced behavior has a practical use  who really used static variables in C  without breeding bugs      As you can see  there is a performance benefit when using immutable default arguments   This can make a difference if it s a frequently called function or the default argument takes a long time to construct   Also  bear in mind that Python isn t C   In C you have constants that are pretty much free   In Python you don t have this benefit

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The relevant part of the documentation      Default parameter values are evaluated from left to right when the function definition is executed  This means that the expression is evaluated once  when the function is defined  and that the same    pre-computed    value is used for each call  This is especially important to understand when a default parameter is a mutable object  such as a list or a dictionary  if the function modifies the object  e g  by appending an item to a list   the default value is in effect modified  This is generally not what was intended  A way around this is to use None as the default  and explicitly test for it in the body of the function  e g    def whats on the telly penguin None       if penguin is None          penguin          penguin append  property of the zoo       return penguin

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TLDR  Define-time defaults are consistent and strictly more expressive     Defining a function affects two scopes  the defining scope containing the function  and the execution  scope contained by the function  While it is pretty clear how blocks map to scopes  the question is where def  lt name gt   lt args defaults gt    belongs to                                   defining scope def name parameter default                                          execution scope   The def name part must evaluate in the defining scope - we want name to be available there  after all  Evaluating the function only inside itself would make it inaccessible   Since parameter is a constant name  we can  evaluate  it at the same time as def name  This also has the advantage it produces the function with a known signature as name parameter        instead of a bare name         Now  when to evaluate default   Consistency already says  at definition   everything else of def  lt name gt   lt args defaults gt    is best evaluated at definition as well  Delaying parts of it would be the astonishing choice   The two choices are not equivalent  either  If default is evaluated at definition time  it can still affect execution time  If default is evaluated at execution time  it cannot affect definition time  Choosing  at definition  allows expressing both cases  while choosing  at execution  can express only one   def name parameter defined      set default at definition time          def name parameter default         delay default until execution time     parameter   default if parameter is None else parameter

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There is a simple way to understand why this happens   Python executes code  from top to bottom  in a namespace   The  internals  just embody of this rule      The reason for this choice is to  let the language fit in your head    All the odd corner cases tend to simplify to executing code in a namespace   default immutables  nested functions  classes  with a little patch-up when done compiling   the self argument  etc   Similarly  complex syntax could be written in simple syntax   a foo      is just a lookup  foo     call   a        This works with list comprehensions  decorators  metaclasses  and more   This gives you a near perfect  view of the strange corners   The language fits in your head   You should keep at it   Learning Python has a period of railing at the language  but it gets comfortable   It s the only language I ve worked in that gets simpler the more you look at corner cases    Keep Hacking   Keep notes   For your specific code  in too much detail   def foo a          a append 5      return a  foo     is one statement  equivalent to    Start making a code object  Interpreting  a     right now  as we go   The    is the default value of argument a   It is of type list  as    always is  Compile all the code after the   into Python bytecode and stick it in another list  Create the callable dictionary  with the arguments and code in the  code  field Add the callable to the current namespace in the  foo  field    Then  it goes to the next line  foo      It s not a reserved word  so look it up in the namespace    Call the function  which will use the list as the default argument  Start executing its bytecode in its namespace   append does not create a new list  so the old one is modified

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I am going to demonstrate an alternative structure to pass a default list value to a function  it works equally well with dictionaries      As others have extensively commented  the list parameter is bound to the function when it is defined as opposed to when it is executed   Because lists and dictionaries are mutable  any alteration to this parameter will affect other calls to this function   As a result  subsequent calls to the function will receive this shared list which may have been altered by any other calls to the function   Worse yet  two parameters are using this function s shared parameter at the same time oblivious to the changes made by the other   Wrong Method  probably       def foo list arg  5        return list arg  a   foo   a append 6   gt  gt  gt  a  5  6   b   foo   b append 7    The value of 6 appended to variable  a  is now part of the list held by  b    gt  gt  gt  b  5  6  7       Although  a  is expecting to receive 6  the last element it appended to the list     it actually receives the last element appended to the shared list    It thus receives the value 7 previously appended by  b    gt  gt  gt  a pop                7   You can verify that they are one and the same object by using id    gt  gt  gt  id a  5347866528   gt  gt  gt  id b  5347866528   Per Brett Slatkin s  Effective Python  59 Specific Ways to Write Better Python   Item 20  Use None and Docstrings to specify dynamic default arguments  p  48      The convention for achieving the desired result in Python is to   provide a default value of None and to document the actual behaviour   in the docstring    This implementation ensures that each call to the function either receives the default list or else the list passed to the function   Preferred Method   def foo list arg None              param list arg   A list of input values                        If none provided  used a list with a default value of 5            if not list arg         list arg    5     return list arg  a   foo   a append 6   gt  gt  gt  a  5  6   b   foo   b append 7   gt  gt  gt  b  5  7   c   foo  10   c append 11   gt  gt  gt  c  10  11    There may be legitimate use cases for the  Wrong Method  whereby the programmer intended the default list parameter to be shared  but this is more likely the exception than the rule

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5 points in defense of Python  Simplicity  The behavior is simple in the following sense  Most people fall into this trap only once  not several times   Consistency  Python always passes objects  not names  The default parameter is  obviously  part of the function heading  not the function body   It therefore ought to be evaluated at module load time  and only at module load time  unless nested   not at function call time   Usefulness  As Frederik Lundh points out in his explanation of  quot Default Parameter Values in Python quot   the current behavior can be quite useful for advanced programming   Use sparingly    Sufficient documentation  In the most basic Python documentation  the tutorial  the issue is loudly announced as an  quot Important warning quot  in the first subsection of Section  quot More on Defining Functions quot   The warning even uses boldface  which is rarely applied outside of headings  RTFM  Read the fine manual   Meta-learning  Falling into the trap is actually a very helpful moment  at least if you are a reflective learner   because you will subsequently better understand the point  quot Consistency quot  above and that will teach you a great deal about Python

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The shortest answer would probably be  definition is execution   therefore the whole argument makes no strict sense  As a more contrived example  you may cite this   def a    return     def b x a         print x   Hopefully it s enough to show that not executing the default argument expressions at the execution time of the def statement isn t easy or doesn t make sense  or both   I agree it s a gotcha when you try to use default constructors  though

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Already busy topic  but from what I read here  the following helped me realizing how it s working internally   def bar a           print id a       a   a    1       print id a       return a   gt  gt  gt  bar   4484370232 4484524224  1   gt  gt  gt  bar   4484370232 4484524152  1   gt  gt  gt  bar   4484370232   Never change  this is  class property  of the function 4484523720   Always a new object   1   gt  gt  gt  id bar func defaults 0   4484370232

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the discussion has yet to mention the difference in scope of mutable and immutable default arguments  when they are previously declared vars  the default arguments  values  which are previously declared vars  becomes accessible as if they were stated as global  however  if the function tries to mutate them  even later in the function  they are no longer global  as already mentioned  you can freely change them as long as you don t mutate them  it is based on the same logic as the regular least astonishment  however it also affects scope and it is important to familiarize with it  a function that does not change the default arguments value can access them freely  global list    1  global int   1 def foo2 a global list b global int       print  global list        print global list    implicity global     print  global int        print global int    implicity global    gt  gt  gt  foo2   global list   1  global int  1  gt  gt  gt  global list    2   gt  gt  gt  global int   2  gt  gt  gt  foo2   global list   2  global int  2  however the function cannot change them from within and the error message might be confusing  as it acts as if it doesn t know this var at all  def foo3 a global list b global int       print  global list        print global list    implicity global     global list remove 2    yes  i m  quot cheating quot      global list append 3       print global list    implicity global     print  global int        print global int    local     print  the error is in the previous line is because this next line assignment makes global int a local var       global int   3     print global int     gt  gt  gt  foo3   global list   1  global int  Traceback  most recent call last     UnboundLocalError  local variable  global int  referenced before assignment  code example  https   onlinegdb com BkB1Unb1u

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This behavior is not surprising if you take the following into consideration   The behavior of read-only class attributes upon assignment attempts  and that Functions are objects  explained well in the accepted answer    The role of  2  has been covered extensively in this thread   1  is likely the astonishment causing factor  as this behavior is not  quot intuitive quot  when coming from other languages   1  is described in the Python tutorial on classes  In an attempt to assign a value to a read-only class attribute      all variables found outside of the innermost scope are read-only  an attempt to write to such a variable will simply create a new local variable in the innermost scope  leaving the identically named outer variable unchanged    Look back to the original example and consider the above points  def foo a          a append 5      return a  Here foo is an object and a is an attribute of foo  available at foo func defs 0    Since a is a list  a is mutable and is thus a read-write attribute of foo  It is initialized to the empty list as specified by the signature when the function is instantiated  and is available for reading and writing as long as the function object exists  Calling foo without overriding a default uses that default s value from foo func defs  In this case  foo func defs 0  is used for a within function object s code scope  Changes to a change foo func defs 0   which is part of the foo object and persists between execution of the code in foo  Now  compare this to the example from the documentation on emulating the default argument behavior of other languages  such that the function signature defaults are used every time the function is executed  def foo a  L None       if L is None          L          L append a      return L  Taking  1  and  2  into account  one can see why this accomplishes the desired behavior   When the foo function object is instantiated  foo func defs 0  is set to None  an immutable object  When the function is executed with defaults  with no parameter specified for L in the function call   foo func defs 0   None  is available in the local scope as L  Upon L       the assignment cannot succeed at foo func defs 0   because that attribute is read-only  Per  1   a new local variable also named L is created in the local scope and used for the remainder of the function call  foo func defs 0  thus remains unchanged for future invocations of foo

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Every other answer explains why this is actually a nice and desired behavior  or why you shouldn t be needing this anyway  Mine is for those stubborn ones who want to exercise their right to bend the language to their will  not the other way around   We will  fix  this behavior with a decorator that will copy the default value instead of reusing the same instance for each positional argument left at its default value     import inspect from copy import copy  def sanify function       def wrapper  a    kw             store the default values         defaults   inspect getargspec function  defaults   for python2           construct a new argument list         new args              for i  arg in enumerate defaults                 allow passing positional arguments             if i in range len a                    new args append a i               else                    copy the value                 new args append copy arg           return function  new args    kw      return wrapper   Now let s redefine our function using this decorator    sanify def foo a          a append 5      return a  foo       5   foo       5   -- as desired   This is particularly neat for functions that take multiple arguments  Compare     the  correct  approach def bar a None  b None  c None       if a is None          a          if b is None          b          if c is None          c            finally do the actual work   with    the nasty decorator hack  sanify def bar a     b     c            wow  works right out of the box    It s important to note that the above solution breaks if you try to use keyword args  like so   foo a  4     The decorator could be adjusted to allow for that  but we leave this as an exercise for the reader

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I think the answer to this question lies in how python pass data to parameter  pass by value or by reference   not mutability or how python handle the  def  statement   A brief introduction  First  there are two type of data types in python  one is simple elementary data type  like numbers  and another data type is objects  Second  when passing data to parameters  python pass elementary data type by value  i e   make a local copy of the value to a local variable  but pass object by reference  i e   pointers to the object   Admitting the above two points  let s explain what happened to the python code  It s only because of passing by reference for objects  but has nothing to do with mutable immutable  or arguably the fact that  def  statement is executed only once when it is defined      is an object  so python pass the reference of    to a  i e   a is only a pointer to    which lies in memory as an object  There is only one copy of    with  however  many references to it  For the first foo    the list    is changed to 1 by append method  But Note that there is only one copy of the list object and this object now becomes 1  When running the second foo    what effbot webpage says  items is not evaluated any more  is wrong  a is evaluated to be the list object  although now the content of the object is 1  This is the effect of passing by reference  The result of foo 3  can be easily derived in the same way   To further validate my answer  let s take a look at two additional codes          No  2           def foo x  items None       if items is None          items          items append x      return items  foo 1    return  1  foo 2    return  2  foo 3    return  3       is an object  so is None  the former is mutable while the latter is immutable  But the mutability has nothing to do with the question   None is somewhere in the space but we know it s there and there is only one copy of None there  So every time foo is invoked  items is evaluated  as opposed to some answer that it is only evaluated once  to be None  to be clear  the reference  or the address  of None  Then in the foo  item is changed to     i e   points to another object which has a different address           No  3          def foo x  items          items append x      return items  foo 1       returns  1  foo 2       returns  2  foo 3       returns  1 3    The invocation of foo 1  make items point to a list object    with an address  say  11111111  the content of the list is changed to 1 in the foo function in the sequel  but the address is not changed  still 11111111  Then foo 2     is coming  Although the    in foo 2     has the same content as the default parameter    when calling foo 1   their address are different  Since we provide the parameter explicitly  items has to take the address of this new     say 2222222  and return it after making some change  Now foo 3  is executed  since only x is provided  items has to take its default value again  What s the default value  It is set when defining the foo function  the list object located in 11111111  So the items is evaluated to be the address 11111111 having an element 1  The list located at 2222222 also contains one element 2  but it is not pointed by items any more  Consequently  An append of 3 will make items  1 3     From the above explanations  we can see that the effbot webpage recommended in the accepted answer failed to give a relevant answer to this question  What is more  I think a point in the effbot webpage is wrong  I think the code regarding the UI Button is correct   for i in range 10       def callback            print  clicked button   i     UI Button  button  s    i  callback    Each button can hold a distinct callback function which will display different value of i  I can provide an example to show this   x    for i in range 10       def callback            print i      x append callback     If we execute x 7    we ll get 7 as expected  and x 9    will gives 9  another value of i

[python] "Least Astonishment" and the Mutable Default Argument

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