arkouda.apply¶

Element-wise function application for Arkouda arrays.

The arkouda.apply module provides functionality for applying user-defined Python functions to Arkouda pdarray objects in an element-wise fashion. This includes support for both lambda expressions passed as strings and pickled Python callables. The function is applied on the server side via embedded Python interpreters.

Functions¶

apply(arr, func, result_dtype=None): Apply a Python function to each element of a pdarray, returning a new pdarray.

Key Features¶

Supports passing functions as callables (pickled using cloudpickle) /

or as specially formatted strings. - Automatically initializes server-side Python interpreter support if needed. - Validates compatibility between client and server Python versions. - Supports specifying the output data type via result_dtype.

Limitations¶

Experimental: May not work in all environments or server builds.
Any Python modules used in the function must also be available on the server.
String functions must follow a strict format: e.g. “lambda x,: x+1” (note the comma).

Examples

>>> import arkouda as ak
>>> arr = ak.array([1, 2, 3])
>>> ak.apply(arr, lambda x: x + 1)
array([2 3 4])

>>> def square(x): return x ** 2
>>> ak.apply(arr, square)
array([1 4 9])

>>> ak.apply(arr, "lambda x,: x*2")
array([2 4 6])

Notes

If result_dtype is not specified, it defaults to the input array’s dtype.
If using a string-based function, result_dtype must match the input dtype.

Functions¶

apply(→ arkouda.numpy.pdarrayclass.pdarray)

Apply a python function to a pdarray.

Module Contents¶

arkouda.apply.apply(arr: arkouda.numpy.pdarrayclass.pdarray, func: Callable | str, result_dtype: numpy.dtype | str | None = None) → arkouda.numpy.pdarrayclass.pdarray[source]¶

Apply a python function to a pdarray.

The function should take one argument and return a new value. The function will then be called on each element in the pdarray.

Warning: This function is experimental and may not work as expected. Known limitations: - Any python modules used inside of the function must be installed on the server.

Parameters:

arr (pdarray) – The pdarray to which the function is applied
func (Union[Callable, str]) – The function to apply to the array. This can be a callable function or a string, but either way it should take a single argument and return a single value. If a string, it should be a lambda function that takes a single argument, e.g. “lambda x,: x+1”. Note the dangling comma after the argument, this is required for string functions.
result_dtype (Optional[Union[np.dtype, str]]) – The dtype of the resulting pdarray. If None, the dtype of the resulting pdarray will be the same as the input pdarray. If a string, it should be a valid numpy dtype string, e.g. “float64”. If a numpy dtype, it should be a valid numpy dtype object, e.g. np.float64. This is not supported for functions passed as strings.

Returns:

The pdarray resulting from applying the function to the input array

Return type:

pdarray

Examples

>>> import arkouda as ak
>>> arr = ak.apply(ak.array([1, 2, 3]), lambda x: x+1)
>>> arr
array([2 3 4])

Or, >>> import math >>> arr = ak.randint(0, 10, 4, seed=1) >>> def times_pi(x): … return x*math.pi >>> arr = ak.apply(arr, times_pi, “float64”) >>> arr array([21.991148575128552 28.274333882308138 15.707963267948966 3.1415926535897931])