How to identify numpy types in python

Question

How can one reliably determine if an object has a numpy type   I realize that this question goes against the philosophy of duck typing  but idea is to make sure a function  which uses scipy and numpy  never returns a numpy type unless it is called with a numpy type   This comes up in the solution to another question  but I think the general problem of determining if an object has a numpy type is far enough away from that original question that they should be separated

User · Answer

To get the type  use the builtin type function  With the in operator  you can test if the type is a numpy type by checking if it contains the string numpy   In  1   import numpy as np  In  2   a   np array  1  2  3    In  3   type a  Out 3    lt type  numpy ndarray  gt   In  4    numpy  in str type a   Out 4   True    This example was run in IPython  by the way  Very handy for interactive use and quick tests

User · Answer

Old question but I came up with a definitive answer with an example  Can t hurt to keep questions fresh as I had this same problem and didn t find a clear answer  The key is to make sure you have numpy imported  and then run the isinstance bool   While this may seem simple  if you are doing some computations across different data types  this small check can serve as a quick test before your start some numpy vectorized operation                           important part                      import numpy as np                         toy array for demo                       arr   np asarray range 1 100 2                               The instance check                            isinstance arr np ndarray

User · Answer

Use the builtin type function to get the type  then you can use the   module   property to find out where it was defined    gt  gt  gt  import numpy as np a   np array  1  2  3    gt  gt  gt  type a   lt type  numpy ndarray  gt   gt  gt  gt  type a    module    numpy   gt  gt  gt  type a    module      np   name   True

User · Answer

Note that the type numpy ndarray  is a type itself and watch out for boolean and scalar types   Don t be too discouraged if it s not intuitive or easy  it s a pain at first   See also  - https   docs scipy org doc numpy-1 15 1 reference arrays dtypes html - https   github com machinalis mypy-data tree master numpy-mypy   gt  gt  gt  import numpy as np  gt  gt  gt  np ndarray  lt class  numpy ndarray  gt   gt  gt  gt  type np ndarray   lt class  type  gt   gt  gt  gt  a   np linspace 1 25   gt  gt  gt  type a   lt class  numpy ndarray  gt   gt  gt  gt  type a     type np ndarray  False  gt  gt  gt  type a     np ndarray True  gt  gt  gt  isinstance a  np ndarray  True   Fun with booleans    gt  gt  gt  b   a astype  int32      11  gt  gt  gt  b 0  False  gt  gt  gt  isinstance b 0   bool  False  gt  gt  gt  isinstance b 0   np bool  False  gt  gt  gt  isinstance b 0   np bool   True  gt  gt  gt  isinstance b 0   np bool8  True  gt  gt  gt  b 0  dtype    np bool True  gt  gt  gt  b 0  dtype    bool    python equivalent True   More fun with scalar types  see  - https   docs scipy org doc numpy-1 15 1 reference arrays scalars html arrays-scalars-built-in   gt  gt  gt  x   np array  1    dtype np uint64   gt  gt  gt  x 0  dtype dtype  uint64    gt  gt  gt  isinstance x 0   np uint64  True  gt  gt  gt  isinstance x 0   np integer  True    generic integer  gt  gt  gt  isinstance x 0   int  False    but not a python int in this case    Try matching the  kind  strings  e g   gt  gt  gt  np dtype  bool   kind                                                                                             b   gt  gt  gt  np dtype  int64   kind                                                                                            i   gt  gt  gt  np dtype  float   kind                                                                                            f   gt  gt  gt  np dtype  half   kind                                                                                             f     But be weary of matching dtypes  gt  gt  gt  np integer  lt class  numpy integer  gt   gt  gt  gt  np dtype np integer  dtype  int64    gt  gt  gt  x 0  dtype    np dtype np integer  False    Down these paths there be dragons     the  dtype attribute returns a kind of dtype  not a specific dtype  gt  gt  gt  isinstance x 0  dtype  np dtype  True  gt  gt  gt  isinstance x 0  dtype  np uint64  False    gt  gt  gt  isinstance x 0  dtype  np dtype np uint64   Traceback  most recent call last     File   lt console gt    line 1  in  lt module gt  TypeError  isinstance   arg 2 must be a type or tuple of types   yea  don t go there  gt  gt  gt  isinstance x 0  dtype  np int   False    again  confusing the  dtype with a specific dtype     Inequalities can be tricky  although they might   work sometimes  try to avoid these idioms    gt  gt  gt  x 0  dtype  lt   np dtype np uint64  True  gt  gt  gt  x 0  dtype  lt   np dtype np float  True  gt  gt  gt  x 0  dtype  lt   np dtype np half  False    just when things were going well  gt  gt  gt  x 0  dtype  lt   np dtype np float16  False    oh boy  gt  gt  gt  x 0  dtype    np int False    ya  no luck here either  gt  gt  gt  x 0  dtype    np int  False    or here  gt  gt  gt  x 0  dtype    np uint64 True    have to end on a good note

User · Answer

That actually depends on what you re looking for    If you want to test whether a sequence is actually a ndarray  a isinstance      np ndarray  is probably the easiest  Make sure you don t reload numpy in the background as the module may be different  but otherwise  you should be OK  MaskedArrays  matrix  recarray are all subclasses of ndarray  so you should be set  If you want to test whether a scalar is a numpy scalar  things get a bit more complicated  You could check whether it has a shape and a dtype attribute  You can compare its dtype to the basic dtypes  whose list you can find in np core numerictypes genericTypeRank  Note that the elements of this list are strings  so you d have to do a tested dtype is np dtype an element of the list

User · Answer

The solution I ve come up with is   isinstance y   np ndarray  np generic      However  it s not 100  clear that all numpy types are guaranteed to be either np ndarray or np generic  and this probably isn t version robust

[python] How to identify numpy types in python?

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