xotl.tools.future.itertools - Functions creating iterators for efficient looping

Several util functions for iterators.

Changed in version 1.8.4: Renamed to xotl.tools.future.iterator. The xotl.tools.iterators is now a deprecated alias.

xotl.tools.future.itertools.dict_update_new(target, source, fail=False)

Update values in source that are new (not present) in target.

If fail is True and a value is already set, an error is raised.

xotl.tools.future.itertools.first_non_null(iterable, default=None)

Returns the first value from iterable which is non-null.

This is roughly the same as:

next((x for x in iter(iterable) if x), default)

New in version 1.4.0.

xotl.tools.future.itertools.slides(iterable: Iterable[T], width: int = 2, fill: X = None) → Iterator[Tuple[Union[T, X, None], ...]]

Creates a sliding window of a given width over an iterable:

>>> list(slides(range(1, 11)))
[(1, 2), (3, 4), (5, 6), (7, 8), (9, 10)]

If the iterator does not yield a width-aligned number of items, the last slice returned is filled with fill (by default None) unless fill is NO_FILL:

>>> list(slides(range(1, 11), width=3))
[(1, 2, 3), (4, 5, 6), (7, 8, 9), (10, None, None)]

>>> list(slides(range(1, 11), width=3, fill=NO_FILL))
[(1, 2, 3), (4, 5, 6), (7, 8, 9), (10,)]

Changed in version 1.4.0: If the fill argument is a collection is cycled over to get the filling, just like in first_n().

Changed in version 1.4.2: The fill argument now defaults to None, instead of Unset.

Changed in version 2.2.2: The fill argument can now take the contant NO_FILL

xotl.tools.future.itertools.continuously_slides(iterable: Iterable[T], width: int = 2, fill: X = None) → Iterator[Tuple[Union[T, X, None], ...]]

Similar to slides() but moves one item at the time (i.e continuously).

fill is only used to fill the fist chunk if the iterable has less items than the width of the window.

Example (generate a texts tri-grams):

>>> slider = continuously_slides(str('maupassant'), 3)
>>> list(str('').join(chunk) for chunk in slider)
['mau', 'aup', 'upa', 'pas', 'ass', 'ssa', 'san', 'ant']

xotl.tools.future.itertools.ungroup(iterator: Iterable[Tuple[X, Iterable[T]]]) → Iterator[T]

Reverses the operation of itertools.groupby() (or similar).

The iterator should produce pairs of (_, xs); where xs is another iterator (or iterable).

It’s guaranteed that the iterator will be consumed at the boundaries of each pair, i.e. before taking another pair (_, ys) from iterator the first xs will be fully yielded.

Demonstration:

>>> def groups():
...    def chunk(s):
...       for x in range(s, s+3):
...           print('Yielding x:', x)
...           yield x
...
...    for g in range(2):
...       print('Yielding group', g)
...       yield g, chunk(g)

>>> list(ungroup(groups()))
Yielding group 0
Yielding x: 0
Yielding x: 1
Yielding x: 2
Yielding group 1
Yielding x: 1
Yielding x: 2
Yielding x: 3
[0, 1, 2, 1, 2, 3]

This is not the same as:

>>> import itertools
>>> xs = itertools.chain(*(xs for _, xs in groups()))
Yielding group 0
Yielding group 1

Notice that the iterator was fully consumed just to create the arguments to chain().

New in version 1.7.3.

xotl.tools.future.itertools.merge(*iterables, key=None)

Merge the iterables in order.

Return an iterator that yields all items from iterables following the order given by key. If key is not given we compare the items.

If the iterables yield their items in increasing order (w.r.t key), the result is also ordered (like a merge sort).

merge() returns the empty iterator.

New in version 1.8.4.

Changed in version 2.1.0: Based on heapq.merge(). In Python 3.5+, this is just an alias of it.

Deprecated since version 2.1.0: Use heapq.merge() directly. This function will be removed when we support for Python 3.4.

xotl.tools.future.itertools.delete_duplicates(seq[, key=lambda x: x])

Remove all duplicate elements from seq.

Two items x and y are considered equal (duplicates) if key(x) == key(y). By default key is the identity function.

Works with any sequence that supports len(), __getitem__(), and addition.

Note

seq.__getitem__ should work properly with slices.

The return type will be the same as that of the original sequence.

New in version 1.5.5.

Changed in version 1.7.4: Added the key argument. Clarified the documentation: seq should also implement the __add__ method and that its __getitem__ method should deal with slices.

xotl.tools.future.itertools.iter_delete_duplicates(iter[, key=lambda x: x])

Yields non-repeating (and consecutive) items from iter.

key has the same meaning as in delete_duplicates().

Examples:

>>> list(iter_delete_duplicates('AAAaBBBA'))
['A', 'a', 'B', 'A']

>>> list(iter_delete_duplicates('AAAaBBBA', key=lambda x: x.lower()))
['A', 'B', 'A']

New in version 1.7.4.

xotl.tools.future.itertools.iter_without_duplicates(iter[, key=lambda x: x])

Yields non-repeating items from iter.

key has the same meaning as in delete_duplicates().

The difference between this function and iter_delete_duplicates() is that we ensure the same item (as per key) is produced only once; while iter_delete_duplicates() only remove consecutive repeating items.

Example:

>>> list(iter_without_duplicates('AAAaBBBA', key=lambda x: x.lower()))
['A', 'B']

xotl.tools.future.itertools.flatten(sequence, is_scalar=xotl.tools.types.is_scalar, depth=None)

Flatten-out a sequence.

It takes care of everything deemed a collection (i.e, not a scalar according to the callable passed in is_scalar argument; if None, iterables -but strings- will be considered as scalars.

For example:

>>> range_ = lambda *a: list(range(*a))
>>> tuple(flatten((1, range_(2, 5), range(5, 10))))
(1, 2, 3, 4, 5, 6, 7, 8, 9)

If depth is None the collection is flattened recursively until the “bottom” is reached. If depth is an integer then the collection is flattened up to that level. depth=0 means not to flatten. Nested iterators are not “exploded” if under the stated depth:

# In the following doctest we use ``...range(...X)`` because the
# string repr of range differs in Py2 and Py3k.

>>> tuple(flatten((range_(2), range(2, 4)), depth=0))  # doctest: +ELLIPSIS  # noqa
([0, 1], ...range(2, 4))

>>> tuple(flatten((range(2), range_(2, 4)), depth=0))  # doctest: +ELLIPSIS  # noqa
(...range(...2), [2, 3])

Note

Compatibility issue

In Python 2 bytes is the standard string but in Python 3 is a binary buffer, so flatten([b'abc', [1, 2, 3]]) will deliver different results.

xotl.tools.iterators.zip([iter1[, iter2[, ...]]])

Return a zip-like object whose next() method returns a tuple where the i-th element comes from the i-th iterable argument. The next() method continues until the shortest iterable in the argument sequence is exhausted and then it raises StopIteration.

Deprecated since version 2.1.0: Use the builtin zip(). This function will be removed in xotl.tools 3.

xotl.tools.iterators.map(func, *iterables)

Make an iterator that computes the function using arguments from each of the iterables. It stops when the shortest iterable is exhausted instead of filling in None for shorter iterables.

Deprecated since version 2.1.0: Use the builtin map(). This function will be removed in xotl.tools 3.

xotl.tools.iterators.zip_longest(*iterables, fillvalue=None)

Make an iterator that aggregates elements from each of the iterables. If the iterables are of uneven length, missing values are filled-in with fillvalue. Iteration continues until the longest iterable is exhausted.

If one of the iterables is potentially infinite, then the zip_longest() function should be wrapped with something that limits the number of calls (for example islice() or takewhile()). If not specified, fillvalue defaults to None.

This function is actually an alias to itertools.izip_longest() in Python 2.7, and an alias to itertools.zip_longest() in Python 3.3.

xotl.tools.future.itertools.zip_map(funcs: Iterable[Callable[[A], B]], args: Iterable[A]) → Iterable[B]

Apply each function in funcs to its corresponding arguments.

If the iterables are not of the same length, stop as soon as the shortest is exhausted.

New in version 2.1.9.

xotl.tools.future.itertools.NO_FILL

A sentinel value to make slides() not to fill the last chunk.