v0.2.1

doc/apidoc.md

@@ -309,6 +309,18 @@ Returns:
 
 
 
+### `map_dict`
+
+Map each item in the iterator using the given dictionary (supports defaultdict).
+
+Args:
+    mapper (dict[T], U]): The lookup to apply.
+
+Returns:
+    Itr[U]: An iterator of mapped items.
+
+
+
 ### `map_while`
 
 Map each item in the iterator using the given function, while the predicate remains True.
@@ -569,6 +581,53 @@ Returns:
 
 
 
+### `tee`
+
+
+Create multiple independent Itr wrappers that iterate over the same underlying iterator. NB Consuming any of the
+returned iterators will consume the original iterator
+
+This method calls itertools.tee on the wrapped iterator and returns a tuple of Itr
+objects, each wrapping one of the tee'd iterators. Each returned Itr yields the same
+sequence of items and can be consumed independently of the others.
+
+Parameters
+----------
+n : int, optional
+    Number of independent iterators to create (default: 2). Must be >= 1.
+
+Returns
+-------
+tuple[Itr[T], ...]
+    Tuple of length `n` containing the newly created Itr objects.
+
+Raises
+------
+ValueError
+    If `n` is less than 1.
+
+Notes
+-----
+- The implementation uses itertools.tee; the tee'd iterators share internal buffers
+  that store items produced by the original iterator until all tees have consumed them.
+  If one or more returned iterators lag behind the others, buffered items will be
+  retained and memory usage can grow.
+- After calling this method, avoid consuming the original wrapped iterator (`self._it`)
+  directly; use the returned Itr objects to prevent surprising interactions with the
+  shared buffer.
+- Creating the tees is inexpensive, but the memory characteristics depend on how the
+  resulting iterators are consumed relative to each other.
+
+Examples
+--------
+>>> i = Itr(range(3))
+>>> a, b = i.tee(2)
+>>> list(a)
+[0, 1, 2]
+>>> list(b)
+[0, 1, 2]
+
+
 ### `unzip`
 
 Splits the iterator of pairs into two separate iterators, each containing the elements from one position of