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How to solve error 'numpy' has no attribute 'float' in Python?

Time:12-20

I am using numpy==1.24.0. On running this sample code line:

import numpy as np
num = np.float(3)

I am getting this error:

Traceback (most recent call last):   File "<stdin>", line 1, in <module>   File "/home/ubuntu/.local/lib/python3.8/site-packages/numpy/__init__.py", line 284, in __getattr__
    raise AttributeError("module {!r} has no attribute " AttributeError: module 'numpy' has no attribute 'float'

Please help me on this.

CodePudding user response:

I removed numpy.py then updated my numpy and it worked!
Note: numpy version=1.23.3

CodePudding user response:

The answer is already provided in the comments by @mattdmo and @tdelaney:

  • numpy 1.20 (release notes) deprecated numpy.float, numpy.int, and similar aliases, causing them to issue a deprecation warning

  • numpy 1.24 (release notes) removed these aliases altogether, causing an error when they are used

For guidelines on how to deal with various deprecated types, have a closer look at the table and guideline in the release notes for 1.20:

...

To give a clear guideline for the vast majority of cases, for the types bool, object, str (and unicode) using the plain version is shorter and clear, and generally a good replacement. For float and complex you can use float64 and complex128 if you wish to be more explicit about the precision.

For np.int a direct replacement with np.int_ or int is also good and will not change behavior, but the precision will continue to depend on the computer and operating system. If you want to be more explicit and review the current use, you have the following alternatives:

  • np.int64 or np.int32 to specify the precision exactly. This ensures that results cannot depend on the computer or operating system.
  • np.int_ or int (the default), but be aware that it depends on the computer and operating system.
  • The C types: np.cint (int), np.int_ (long), np.longlong.
  • np.intp which is 32bit on 32bit machines 64bit on 64bit machines. This can be the best type to use for indexing.

...

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