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Function iterable

numpy/lib/function_base.py:349–390  ·  view source on GitHub ↗

Check whether or not an object can be iterated over. Parameters ---------- y : object Input object. Returns ------- b : bool Return ``True`` if the object has an iterator method or is a sequence and ``False`` otherwise. Examples --------

(y)

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347
348@set_module('numpy')
349def iterable(y):
350 """
351 Check whether or not an object can be iterated over.
352
353 Parameters
354 ----------
355 y : object
356 Input object.
357
358 Returns
359 -------
360 b : bool
361 Return ``True`` if the object has an iterator method or is a
362 sequence and ``False`` otherwise.
363
364
365 Examples
366 --------
367 >>> np.iterable([1, 2, 3])
368 True
369 >>> np.iterable(2)
370 False
371
372 Notes
373 -----
374 In most cases, the results of ``np.iterable(obj)`` are consistent with
375 ``isinstance(obj, collections.abc.Iterable)``. One notable exception is
376 the treatment of 0-dimensional arrays::
377
378 >>> from collections.abc import Iterable
379 >>> a = np.array(1.0) # 0-dimensional numpy array
380 >>> isinstance(a, Iterable)
381 True
382 >>> np.iterable(a)
383 False
384
385 """
386 try:
387 iter(y)
388 except TypeError:
389 return False
390 return True
391
392
393def _average_dispatcher(a, axis=None, weights=None, returned=None, *,

Callers 1

__init__Method · 0.85

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