Proposed new feature or change:

Mailing list post

Feature request: Add a uniform interface for accessing the minimum or maximum value of a given dtype.

Previously discussed here, here, and here. Currently, doing this requires branching on the type of dtype (boolean, integer, or floating point) and then (for the latter two) calling either iinfo or finfo, respectively. It would be more ergonomic to have a single, uniform interface for accessing this information that is dtype-independent.

Here are the possible interfaces suggested so far:

import numpy as np
dt = np.int32 # example

# As an attribute of the dtype itself:
dt.min
dt.min_value
dt.info().min
dt.info.min

# As a function in numpy.dtypes:
np.dtypes.info(dt).min
np.dtypes.min(dt)
np.dtypes.min_value(dt)

# As a top-level function:
np.min_dtype_value(dt)
np.dtype_info(dt).min
np.dtype_info(dt).min_value

Personally, my current favorite is simply dt.min.

Relevant comment by @mhvk on the mailing list thread:

It would also seem to make sense to consider how the dtype itself can hold/calculate this type of information, since that will be the only way a generic info() function can get information for a user-defined dtype. Indeed, taking that further, might a method or property on the dtype itself be the cleaner interface?