chicken_turtle_util.iterable¶

Utility functions for working with iterables. sliding_window, ...

See also¶

itertools more_itertools

`flatten`	Flatten shallowly zero or more times
`is_sorted`	Get whether iterable is sorted ascendingly
`partition`	Split iterable into partitions
`sliding_window`	Iterate using a sliding window

chicken_turtle_util.iterable.flatten(iterable, times=1)[source]¶

Flatten shallowly zero or more times

Does not flatten str and bytes. Order is stably maintained (i.e. no 2 items swap places, even if they’re equal).

Parameters:

iterable : iterable(any) except str or bytes

Iterable to flatten. May be any iterable other than str or bytes. May have irregular depth.

times : int, optional

The number of times to flatten shallowly or, equivalently, the number of levels of depth to remove. Should be 0 or more.

Yields:

any

Items of iterable flattened to depth depth(iterable) - times

Raises:

ValueError

If input is invalid.

Examples

>>> list(flatten([[2, 3], 1, [5, [7, 8]]]))
[2, 3, 1, 5, [7, 8]]

>>> list(flatten([[2, 3], 1, [5, [7, 8]]], times=2))
[2, 3, 1, 5, 7, 8]

>>> list(flatten([[2, 3], 1, [5, [7, 8]]], times=3))
[2, 3, 1, 5, 7, 8]

>>> flatten([iter([2, 3]), 1, [5, iter([7, 8])]])
iter([2, 3, 1, 5, iter([7, 8])])

>>> list(flatten([[2, 3], 1, [5, [7, 8]]], times=0))
[[2, 3], 1, [5, [7, 8]]]

chicken_turtle_util.iterable.is_sorted(iterable)[source]¶

Get whether iterable is sorted ascendingly

Parameters:

iterable : iterable(comparable)

Iterable whose ordering to check

Returns:

bool

Whether iterable is sorted

chicken_turtle_util.iterable.partition(iterable, key)[source]¶

Split iterable into partitions

Parameters:

iterable : iterable(item :: any)

Iterable to split into partitions

key : (item :: any) -> (partition_id :: any)

Function that assigns an item of the iterable to a partition

Returns:

partitioning : {(partition_id :: any)

Partitioning. Ordering of items is maintained within each partition. I.e. each partition is a subsequence of iterable.

chicken_turtle_util.iterable.sliding_window(iterable, size=2)[source]¶

Iterate using a sliding window

Parameters:

iterable : iterable(any)

Iterable to slide a window across

size : int, optional

Window size

Yields:

(any, ...)

Iterator slices of size size, taken from start to end through the iterator.

Raises:

ValueError

When ilen(iterable) < size or size < 1