Best way to check function arguments

Question

I m looking for an efficient way to check variables of a Python function  For example  I d like to check arguments type and value  Is there a module for this  Or should I use something like decorators  or any specific idiom   def my function a  b  c          An example function I d like to check the arguments of           check that a is an int       check that 0  lt  b  lt  10       check that c is not an empty string

User · Answer

def myFunction a b c    This is an example function I d like to check arguments of      if type  a      int          dostuff     if 0  lt  b  lt  10          dostuff     if type  C      str and c                dostuff

User · Answer

One way is to use assert   def myFunction a b c        This is an example function I d like to check arguments of      assert isinstance a  int    a should be an int        or if you want to allow whole number floats  assert int a     a     assert b  gt  0 and b  lt  10   b should be betwen 0 and 10      assert isinstance c  str  and c   c should be a non-empty string

User · Answer

You can use Type Enforcement accept returns decorators from PythonDecoratorLibrary It s very easy and readable    accepts int  int  float  def myfunc i1  i2  i3       pass

User · Answer

Edit  as of 2019 there is more support for using type annotations and static checking in Python  check out the typing module and mypy  The 2013 answer follows     Type checking is generally not Pythonic  In Python  it is more usual to use duck typing  Example   In you code  assume that the argument  in your example a  walks like an int and quacks like an int  For instance   def my function a       return a   7   This means that not only does your function work with integers  it also works with floats and any user defined class with the   add   method defined  so less  sometimes nothing  has to be done if you  or someone else  want to extend your function to work with something else  However  in some cases you might need an int  so then you could do something like this   def my function a       b   int a    7     c    5  6  3  123541  b      return c   and the function still works for any a that defines the   int   method   In answer to your other questions  I think it is best  as other answers have said to either do this   def my function a  b  c       assert 0  lt  b  lt  10     assert c          A non-empty string has the Boolean value True   or  def my function a  b  c       if 0  lt  b  lt  10            Do stuff with b     else          raise ValueError     if c            Do stuff with c     else          raise ValueError   Some type checking decorators I made   import inspect  def checkargs function       def  f  arguments           for index  argument in enumerate inspect getfullargspec function  0                if not isinstance arguments index   function   annotations   argument                    raise TypeError     is not of type     format arguments index   function   annotations   argument            return function  arguments       f   doc     function   doc       return  f  def coerceargs function       def  f  arguments           new arguments              for index  argument in enumerate inspect getfullargspec function  0                new arguments append function   annotations   argument  arguments index            return function  new arguments       f   doc     function   doc       return  f  if   name         main          checkargs     def f x  int  y  int                       A doc string                      return x  y       coerceargs     def g a  int  b  int                       Another doc string                      return a   b      print f 1  2       try          print f 3  4 0       except TypeError as e          print e       print g 1  2       print g 3  4 0

User · Answer

This is not the solution to you  but if you want to restrict the function calls to some specific parameter types then you must use the PROATOR   The Python Function prototype validator    you can refer the following link  https   github com mohit-thakur-721 proator

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The most Pythonic idiom is to clearly document what the function expects and then just try to use whatever gets passed to your function and either let exceptions propagate or just catch attribute errors and raise a TypeError instead  Type-checking should be avoided as much as possible as it goes against duck-typing  Value testing can be OK     depending on the context   The only place where validation really makes sense is at system or subsystem entry point  such as web forms  command line arguments  etc  Everywhere else  as long as your functions are properly documented  it s the caller s responsibility to pass appropriate arguments

User · Answer

This checks the type of input arguments upon calling the function   def func inp1 int 0 inp2 str            for item in func   annotations   keys            assert isinstance locals   item  func   annotations   item        return  something   first 7 second     print func first second     Also check with second 9  it must give assertion error

User · Answer

There are different ways to check what a variable is in Python  So  to list a few    isinstance obj  type  function takes your variable  obj and gives you True is it is the same type of the type you listed  issubclass obj  class  function that takes in a variable obj  and gives you True if obj is a subclass of class  So for example issubclass Rabbit  Animal  would give you a True value hasattr is another example  demonstrated by this function  super len      def super len o       if hasattr o     len              return len o       if hasattr o   len            return o len      if hasattr o   fileno            try              fileno   o fileno           except io UnsupportedOperation              pass         else              return os fstat fileno  st size      if hasattr o   getvalue              e g  BytesIO  cStringIO StringI         return len o getvalue        hasattr leans more towards duck-typing  and something that is usually more pythonic but that term is up opinionated   Just as a note  assert statements are usually used in testing  otherwise  just use if else statements

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def someFunc a  b  c       params   locals       for  item in params          print type params  item     item  params  item    Demo    gt  gt  someFunc 1   asd   1 0   gt  gt   lt type  int  gt  a 1  gt  gt   lt type  float  gt  c 1 0  gt  gt   lt type  str  gt  b asd   more about locals

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I did quite a bit of investigation on that topic recently since I was not satisfied with the many libraries I found out there   I ended up developing a library to address this  it is named valid8  As explained in the documentation  it is for value validation mostly  although it comes bundled with simple type validation functions too   and you might wish to associate it with a PEP484-based type checker such as enforce or pytypes   This is how you would perform validation with valid8 alone  and mini lambda actually  to define the validation logic - but it is not mandatory  in your case     for type validation from numbers import Integral from valid8 import instance of    for value validation from valid8 import validate arg from mini lambda import x  s  Len   validate arg  a   instance of Integral    validate arg  b    0  lt  x   amp   x  lt  10    validate arg  c   instance of str   Len s   gt  0  def my function a  Integral  b  c  str          an example function I d like to check the arguments of           check that a is an int       check that 0  lt  b  lt  10       check that c is not an empty string    check that it works my function 0 2  1   r      InputValidationError for  a  HasWrongType  Value should be an instance of  lt class  numbers Integral  gt   Wrong value   0 2   my function 0  0   r        InputValidationError for  b    x  gt  0   amp   x  lt  10   returned  False  my function 0  1  0         InputValidationError for  c  Successes       Failures    instance of  lt class  str  gt     HasWrongType  Value should be an instance of  lt class  str  gt   Wrong value   0     len s   gt  0    TypeError  object of type  int  has no len      my function 0  1            InputValidationError for  c  Successes    instance of  lt class  str  gt      Failures    len s   gt  0    False     And this is the same example leveraging PEP484 type hints and delegating type checking to enforce     for type validation from numbers import Integral from enforce import runtime validation  config config dict mode  covariant       type validation will accept subclasses too    for value validation from valid8 import validate arg from mini lambda import x  s  Len   runtime validation  validate arg  b    0  lt  x   amp   x  lt  10    validate arg  c   Len s   gt  0  def my function a  Integral  b  c  str          an example function I d like to check the arguments of           check that a is an int       check that 0  lt  b  lt  10       check that c is not an empty string    check that it works my function 0 2  1   r      RuntimeTypeError  a  was not of type  lt class  numbers Integral  gt  my function 0  0   r        InputValidationError for  b    x  gt  0   amp   x  lt  10   returned  False  my function 0  1  0         RuntimeTypeError  c  was not of type  lt class  str  gt  my function 0  1            InputValidationError for  c   len s   gt  0  returned  False

User · Answer

If you want to check   kwargs   args as well as normal arguments in one go  you can use the locals   function as the first statement in your function definition to get a dictionary of the arguments   Then use type   to examine the arguments  for example whilst iterating over the dict   def myfunc my  args  to  this  function    kwargs       d   locals       assert type d get  x       str      for x in d          if x     x               assert type d x      x     for x in   a   b   c            assert x in d       whatever more

User · Answer

If you want to do the validation for several functions you can add the logic inside a decorator like this   def deco func        def wrapper a b c            if not isinstance a  int               or not isinstance b  int               or not isinstance c  str                raise TypeError          if not 0  lt  b  lt  10               raise ValueError          if c                     raise ValueError          return func a b c       return wrapper   and use it    deco def foo a b c       print  ok     Hope this helps

User · Answer

Normally  you do something like this   def myFunction a b c      if not isinstance a  int         raise TypeError  Expected int  got  s     type a        if b  lt   0 or b  gt   10        raise ValueError  Value  d out of range     b       if not c        raise ValueError  String was empty         Rest of function

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In this elongated answer  we implement a Python 3 x-specific type checking decorator based on PEP 484-style type hints in less than 275 lines of pure-Python  most of which is explanatory docstrings and comments      heavily optimized for industrial-strength real-world use complete with a py test-driven test suite exercising all possible edge cases   Feast on the unexpected awesome of bear typing    gt  gt  gt   beartype     def spirit bear kermode  str  gitgaata   str  int   - gt  tuple          return  kermode  gitgaata   Moksgm ol    Ursus americanus kermodei    gt  gt  gt  spirit bear 0xdeadbeef   People of the Cane   AssertionError  parameter kermode 0xdeadbeef not of  lt class  str  gt    As this example suggests  bear typing explicitly supports type checking of parameters and return values annotated as either simple types or tuples of such types  Golly   O K   that s actually unimpressive   beartype resembles every other Python 3 x-specific type checking decorator based on PEP 484-style type hints in less than 275 lines of pure-Python  So what s the rub  bub   Pure Bruteforce Hardcore Efficiency  Bear typing is dramatically more efficient in both space and time than all existing implementations of type checking in Python to the best of my limited domain knowledge   More on that later    Efficiency usually doesn t matter in Python  however  If it did  you wouldn t be using Python  Does type checking actually deviate from the well-established norm of avoiding premature optimization in Python  Yes  Yes  it does   Consider profiling  which adds unavoidable overhead to each profiled metric of interest  e g   function calls  lines   To ensure accurate results  this overhead is mitigated by leveraging optimized C extensions  e g   the  lsprof C extension leveraged by the cProfile module  rather than unoptimized pure-Python  e g   the profile module   Efficiency really does matter when profiling   Type checking is no different  Type checking adds overhead to each function call type checked by your application     ideally  all of them  To prevent well-meaning  but sadly small-minded  coworkers from removing the type checking you silently added after last Friday s caffeine-addled allnighter to your geriatric legacy Django web app  type checking must be fast  So fast that no one notices it s there when you add it without telling anyone  I do this all the time  Stop reading this if you are a coworker   If even ludicrous speed isn t enough for your gluttonous application  however  bear typing may be globally disabled by enabling Python optimizations  e g   by passing the -O option to the Python interpreter      python3 -O   This succeeds only when type checking is optimized away  See above   gt  gt  gt  spirit bear 0xdeadbeef   People of the Cane    0xdeadbeef   People of the Cane    Moksgm ol    Ursus americanus kermodei     Just because  Welcome to bear typing   What The     Why  bear   You re a Neckbeard  Right   Bear typing is bare-metal type checking     that is  type checking as close to the manual approach of type checking in Python as feasible  Bear typing is intended to impose no performance penalties  compatibility constraints  or third-party dependencies  over and above that imposed by the manual approach  anyway   Bear typing may be seamlessly integrated into existing codebases and test suites without modification   Everyone s probably familiar with the manual approach  You manually assert each parameter passed to and or return value returned from every function in your codebase  What boilerplate could be simpler or more banal  We ve all seen it a hundred times a googleplex times  and vomited a little in our mouths everytime we did  Repetition gets old fast  DRY  yo   Get your vomit bags ready  For brevity  let s assume a simplified easy spirit bear   function accepting only a single str parameter  Here s what the manual approach looks like   def easy spirit bear kermode  str  - gt  str      assert isinstance kermode  str    easy spirit bear   parameter kermode    not of  lt class  str  gt   format kermode      return value    kermode   Moksgm ol    Ursus americanus kermodei       assert isinstance return value  str    easy spirit bear   return value    not of  lt class  str  gt   format return value      return return value   Python 101  right  Many of us passed that class   Bear typing extracts the type checking manually performed by the above approach into a dynamically defined wrapper function automatically performing the same checks     with the added benefit of raising granular TypeError rather than ambiguous AssertionError exceptions  Here s what the automated approach looks like   def easy spirit bear wrapper  args    beartype func easy spirit bear    kwargs       if not           isinstance args 0     beartype func   annotations    kermode            if 0  lt  len args  else         isinstance kwargs  kermode      beartype func   annotations    kermode            if  kermode  in kwargs else True               raise TypeError                   easy spirit bear   parameter kermode    not of   r   format                  args 0  if 0  lt  len args  else kwargs  kermode                      beartype func   annotations    kermode          return value     beartype func  args    kwargs       if not isinstance return value    beartype func   annotations    return             raise TypeError               easy spirit bear   return value    not of   r   format                  return value    beartype func   annotations    return          return return value   It s long-winded  But it s also basically  as fast as the manual approach    Squinting suggested   Note the complete lack of function inspection or iteration in the wrapper function  which contains a similar number of tests as the original function     albeit with the additional  maybe negligible  costs of testing whether and how the parameters to be type checked are passed to the current function call  You can t win every battle   Can such wrapper functions actually be reliably generated to type check arbitrary functions in less than 275 lines of pure Python  Snake Plisskin says   True story  Got a smoke    And  yes  I may have a neckbeard   No  Srsly  Why  bear    Bear beats duck  Duck may fly  but bear may throw salmon at duck  In Canada  nature can surprise you   Next question   What s So Hot about Bears  Anyway   Existing solutions do not perform bare-metal type checking     at least  none I ve grepped across  They all iteratively reinspect the signature of the type-checked function on each function call  While negligible for a single call  reinspection overhead is usually non-negligible when aggregated over all calls  Really  really non-negligible   It s not simply efficiency concerns  however  Existing solutions also often fail to account for common edge cases  This includes most if not all toy decorators provided as stackoverflow answers here and elsewhere  Classic failures include    Failing to type check keyword arguments and or return values  e g   sweeneyrod s  checkargs decorator   Failing to support tuples  i e   unions  of types accepted by the isinstance   builtin  Failing to propagate the name  docstring  and other identifying metadata from the original function onto the wrapper function  Failing to supply at least a semblance of unit tests   Kind of critical   Raising generic AssertionError exceptions rather than specific TypeError exceptions on failed type checks  For granularity and sanity  type checking should never raise generic exceptions    Bear typing succeeds where non-bears fail  All one  all bear   Bear Typing Unbared  Bear typing shifts the space and time costs of inspecting function signatures from function call time to function definition time     that is  from the wrapper function returned by the  beartype decorator into the decorator itself  Since the decorator is only called once per function definition  this optimization yields glee for all   Bear typing is an attempt to have your type checking cake and eat it  too  To do so   beartype    Inspects the signature and annotations of the original function  Dynamically constructs the body of the wrapper function type checking the original function  Thaaat s right  Python code generating Python code  Dynamically declares this wrapper function via the exec   builtin  Returns this wrapper function    Shall we  Let s dive into the deep end     If the active Python interpreter is  NOT  optimized  e g   option  -O  was    NOT  passed to this interpreter   enable type checking  if   debug        import inspect     from functools import wraps     from inspect import Parameter  Signature      def beartype func  callable  - gt  callable                      Decorate the passed   callable    e g   function  method  to validate         both all annotated parameters passed to this callable  and  the         annotated value returned by this callable if any           This decorator performs rudimentary type checking based on Python 3 x         function annotations  as officially documented by PEP 484   Type         Hints    While PEP 484 supports arbitrarily complex type composition          this decorator requires  all  parameter and return value annotations to         be either             Classes  e g    int    OrderedDict              Tuples of classes  e g     int  OrderedDict              If optimizations are enabled by the active Python interpreter  e g   due         to option  -O  passed to this interpreter   this decorator is a noop           Raises         ----------         NameError             If any parameter has the reserved name    beartype func           TypeError             If either                Any parameter or return value annotation is neither                  A type                  A tuple of types                The kind of any parameter is unrecognized  This should  never                happen  assuming no significant changes to Python semantics                         Raw string of Python statements comprising the body of this wrapper            including  in order                         A   wraps  decorator propagating the name  docstring  and other             identifying metadata of the original function to this wrapper              A private    beartype func  parameter initialized to this function              In theory  the  func  parameter passed to this decorator should be             accessible as a closure-style local in this wrapper  For unknown             reasons  presumably  a subtle bug in the exec   builtin   this is             not the case  Instead  a closure-style local must be simulated by             passing the  func  parameter to this function at function             definition time as the default value of an arbitrary parameter  To             ensure this default is  NOT  overwritten by a function accepting a             parameter of the same name  this edge case is tested for below              Assert statements type checking parameters passed to this callable              A call to this callable              An assert statement type checking the value returned by this             callable                      While there exist numerous alternatives  e g   appending to a list or           bytearray before joining the elements of that iterable into a string             these alternatives are either slower  as in the case of a list  due to           the high up-front cost of list construction  or substantially more           cumbersome  as in the case of a bytearray   Since string concatenation           is heavily optimized by the official CPython interpreter  the simplest           approach is  curiously  the most ideal          func body        wraps   beartype func  def func beartyped  args    beartype func   beartype func    kwargs                   inspect Signature  instance encapsulating this callable s signature          func sig   inspect signature func             Human-readable name of this function for use in exceptions          func name   func   name                     For the name of each parameter passed to this callable and the            inspect Parameter  instance encapsulating this parameter  in the           passed order             for func arg index  func arg in enumerate func sig parameters values                   If this callable redefines a parameter initialized to a default               value by this wrapper  raise an exception  Permitting this               unlikely edge case would permit unsuspecting users to                accidentally  override these defaults              if func arg name       beartype func                   raise NameError                       Parameter    reserved for use by  beartype   format                          func arg name                  If this parameter is both annotated and non-ignorable for purposes               of type checking  type check this parameter              if  func arg annotation is not Parameter empty and                 func arg kind not in  PARAMETER KIND IGNORED                     Validate this annotation                   check type annotation                      annotation func arg annotation                      label     parameter    type  format                          func name  func arg name                      String evaluating to this parameter s annotated type                  func arg type expr                            beartype func   annotations     r    format                          func arg name                      String evaluating to this parameter s current value when                   passed as a keyword                  func arg value key expr    kwargs   r    format func arg name                     If this parameter is keyword-only  type check this parameter                   only by lookup in the variadic    kwargs  dictionary                  if func arg kind is Parameter KEYWORD ONLY                      func body            if  arg name r  in kwargs and not isinstance           arg value key expr    arg type expr            raise TypeError                func name  keyword-only parameter                 arg name       not a    r    format                   arg value key expr    arg type expr        format                          func name func name                          arg name func arg name                          arg type expr func arg type expr                          arg value key expr func arg value key expr                                          Else  this parameter may be passed either positionally or as                   a keyword  Type check this parameter both by lookup in the                   variadic    kwargs  dictionary  AND  by index into the                   variadic   args  tuple                  else                        String evaluating to this parameter s current value when                       passed positionally                      func arg value pos expr    args   r    format                          func arg index                       func body            if not           isinstance  arg value pos expr    arg type expr           if  arg index   lt  len args  else         isinstance  arg value key expr    arg type expr           if  arg name r  in kwargs else True               raise TypeError                    func name  parameter  arg name       not of    r    format                   arg value pos expr  if  arg index   lt  len args  else  arg value key expr                    arg type expr        format                      func name func name                      arg name func arg name                      arg index func arg index                      arg type expr func arg type expr                      arg value key expr func arg value key expr                      arg value pos expr func arg value pos expr                               If this callable s return value is both annotated and non-ignorable           for purposes of type checking  type check this value          if func sig return annotation not in  RETURN ANNOTATION IGNORED                Validate this annotation               check type annotation                  annotation func sig return annotation                  label     return type  format func name                  Strings evaluating to this parameter s annotated type and               currently passed value  as above              func return type expr                        beartype func   annotations    return                    Call this callable  type check the returned value  and return this               value from this wrapper              func body            return value     beartype func  args    kwargs      if not isinstance return value   return type            raise TypeError                func name  return value      not of    r    format                  return value   return type        return return value     format func name func name  return type func return type expr            Else  call this callable and return this value from this wrapper          else              func body            return   beartype func  args    kwargs                 Dictionary mapping from local attribute name to value  For efficiency            only those local attributes explicitly required in the body of this           wrapper are copied from the current namespace   See below           local attrs       beartype func   func             Dynamically define this wrapper as a closure of this decorator  For           obscure and presumably uninteresting reasons  Python fails to locally           declare this closure when the locals   dictionary is passed  to           capture this closure  a local dictionary must be passed instead          exec func body  globals    local attrs             Return this wrapper          return local attrs  func beartyped         PARAMETER KIND IGNORED             Parameter POSITIONAL ONLY  Parameter VAR POSITIONAL  Parameter VAR KEYWORD                    Set of all  inspect Parameter kind  constants to be ignored during     annotation- based type checking in the   beartype  decorator       This includes         Constants specific to variadic parameters  e g     args      kwargs          Variadic parameters cannot be annotated and hence cannot be type checked        Constants specific to positional-only parameters  which apply to non-pure-       Python callables  e g   defined by C extensions   The   beartype        decorator applies  only  to pure-Python callables  which provide no       syntactic means of specifying positional-only parameters                RETURN ANNOTATION IGNORED    Signature empty  None              Set of all annotations for return values to be ignored during annotation-     based type checking in the   beartype  decorator       This includes          Signature empty   signifying a callable whose return value is  not        annotated         None   signifying a callable returning no value  By convention  callables       returning no value are typically annotated to return  None   Technically        callables whose return values are annotated as  None   could  be       explicitly checked to return  None  rather than a none- None  value  Since       return values are safely ignorable by callers  however  there appears to       be little real-world utility in enforcing this constraint               def  check type annotation annotation  object  label  str  - gt  None                      Validate the passed annotation to be a valid type supported by the           beartype  decorator           Parameters         ----------         annotation   object             Annotation to be validated          label   str             Human-readable label describing this annotation  interpolated into             exceptions raised by this function           Raises         ----------         TypeError             If this annotation is neither a new-style class nor a tuple of             new-style classes                         If this annotation is a tuple  raise an exception if any member of           this tuple is not a new-style class  Note that the    name              attribute tested below is not defined by old-style classes and hence           serves as a helpful means of identifying new-style classes          if isinstance annotation  tuple               for member in annotation                  if not                       isinstance member  type  and hasattr member     name                           raise TypeError                              tuple member    not a new-style class  format                              label  member             Else if this annotation is not a new-style class  raise an exception          elif not               isinstance annotation  type  and hasattr annotation     name                   raise TypeError                         neither a new-style class nor                    tuple of such classes  format label  annotation      Else  the active Python interpreter is optimized  In this case  disable type   checking by reducing this decorator to the identity decorator  else      def beartype func  callable  - gt  callable          return func   And leycec said  Let the   beartype bring forth type checking fastly  and it was so   Caveats  Curses  and Empty Promises  Nothing is perfect  Even bear typing   Caveat I  Default Values Unchecked  Bear typing does not type check unpassed parameters assigned default values  In theory  it could  But not in 275 lines or less and certainly not as a stackoverflow answer   The safe     probably totally unsafe  assumption is that function implementers claim they knew what they were doing when they defined default values  Since default values are typically constants     they d better be    rechecking the types of constants that never change on each function call assigned one or more default values would contravene the fundamental tenet of bear typing   Don t repeat yourself over and oooover and oooo-oooover again    Show me wrong and I will shower you with upvotes   Caveat II  No PEP 484  PEP 484   Type Hints   formalized the use of function annotations first introduced by PEP 3107   Function Annotations    Python 3 5 superficially supports this formalization with a new top-level typing module  a standard API for composing arbitrarily complex types from simpler types  e g   Callable  Arg1Type  Arg2Type   ReturnType   a type describing a function accepting two arguments of type Arg1Type and Arg2Type and returning a value of type ReturnType    Bear typing supports none of them  In theory  it could  But not in 275 lines or less and certainly not as a stackoverflow answer   Bear typing does  however  support unions of types in the same way that the isinstance   builtin supports unions of types  as tuples  This superficially corresponds to the typing Union type     with the obvious caveat that typing Union supports arbitrarily complex types  while tuples accepted by  beartype support only simple classes  In my defense  275 lines   Tests or It Didn t Happen  Here s the gist of it  Get it  gist  I ll stop now   As with the  beartype decorator itself  these py test tests may be seamlessly integrated into existing test suites without modification  Precious  isn t it   Now the mandatory neckbeard rant nobody asked for   A History of API Violence  Python 3 5 provides no actual support for using PEP 484 types  wat   It s true  no type checking  no type inference  no type nuthin   Instead  developers are expected to routinely run their entire codebases through heavyweight third-party CPython interpreter wrappers implementing a facsimile of such support  e g   mypy   Of course  these wrappers impose    A compatibility penalty  As the official mypy FAQ admits in response to the frequently asked question  Can I use mypy to type check my existing Python code     It depends  Compatibility is pretty good  but some Python features are not yet implemented or fully supported   A subsequent FAQ response clarifies this incompatibility by stating that        your code must make attributes explicit and use a explicit protocol representation   Grammar police see your  a explicit  and raise you an implicit frown   Mypy will support modular  efficient type checking  and this seems to rule out type checking some language features  such as arbitrary runtime addition of methods  However  it is likely that many of these features will be supported in a restricted form  for example  runtime modification is only supported for classes or methods registered as dynamic or    patchable       For a full list of syntactic incompatibilities  see  Dealing with common issues    It s not pretty  You just wanted type checking and now you refactored your entire codebase and broke everyone s build two days from the candidate release and the comely HR midget in casual business attire slips a pink slip through the crack in your cubicle-cum-mancave  Thanks alot  mypy   A performance penalty  despite interpreting statically typed code  Fourty years of hard-boiled computer science tells us that     all else being equal  interpreting statically typed code should be faster  not slower  than interpreting dynamically typed code  In Python  up is the new down  Additional non-trivial dependencies  increasing    The bug-laden fragility of project deployment  especially cross-platform  The maintenance burden of project development  Possible attack surface     I ask Guido   Why  Why bother inventing an abstract API if you weren t willing to pony up a concrete API actually doing something with that abstraction   Why leave the fate of a million Pythonistas to the arthritic hand of the free open-source marketplace  Why create yet another techno-problem that could have been trivially solved with a 275-line decorator in the official Python stdlib   I have no Python and I must scream

[python] Best way to check function arguments?

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