Starting to move towards python3.9

[python_utils.git] / list_utils.py

diff --git a/list_utils.py b/list_utils.py
index 9a5d4fde0dcad7936a16ffc6f53a7a50ba0b67fa..182e2bc5c104908f39a15e4675021e6ed8a7c338 100644 (file)
--- a/list_utils.py
+++ b/list_utils.py
@@ -1,20 +1,32 @@
 #!/usr/bin/env python3
 
+from collections import Counter
 from itertools import islice
-from typing import Any, Iterator, List
+from typing import Any, Iterator, List, Mapping, Sequence
 
 
 def shard(lst: List[Any], size: int) -> Iterator[Any]:
-    """Yield successive size-sized shards from lst."""
+    """
+    Yield successive size-sized shards from lst.
+
+    >>> for sublist in shard([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], 3):
+    ...     [_ for _ in sublist]
+    [1, 2, 3]
+    [4, 5, 6]
+    [7, 8, 9]
+    [10, 11, 12]
+
+    """
     for x in range(0, len(lst), size):
         yield islice(lst, x, x + size)
 
 
 def flatten(lst: List[Any]) -> List[Any]:
-    """Flatten out a list:
+    """
+    Flatten out a list:
 
-        >>> flatten([ 1, [2, 3, 4, [5], 6], 7, [8, [9]]])
-        [1, 2, 3, 4, 5, 6, 7, 8, 9]
+    >>> flatten([ 1, [2, 3, 4, [5], 6], 7, [8, [9]]])
+    [1, 2, 3, 4, 5, 6, 7, 8, 9]
 
     """
     if len(lst) == 0:
@@ -22,3 +34,82 @@ def flatten(lst: List[Any]) -> List[Any]:
     if isinstance(lst[0], list):
         return flatten(lst[0]) + flatten(lst[1:])
     return lst[:1] + flatten(lst[1:])
+
+
+def prepend(item: Any, lst: List[Any]) -> List[Any]:
+    """
+    Prepend an item to a list.
+
+    >>> prepend('foo', ['bar', 'baz'])
+    ['foo', 'bar', 'baz']
+
+    """
+    lst.insert(0, item)
+    return lst
+
+
+def population_counts(lst: List[Any]) -> Mapping[Any, int]:
+    """
+    Return a population count mapping for the list (i.e. the keys are
+    list items and the values are the number of occurrances of that
+    list item in the original list.
+
+    >>> population_counts([1, 1, 1, 2, 2, 3, 3, 3, 4])
+    Counter({1: 3, 3: 3, 2: 2, 4: 1})
+
+    """
+    return Counter(lst)
+
+
+def most_common_item(lst: List[Any]) -> Any:
+
+    """
+    Return the most common item in the list.  In the case of ties,
+    which most common item is returned will be random.
+
+    >>> most_common_item([1, 1, 1, 2, 2, 3, 3, 3, 3, 4, 4])
+    3
+
+    """
+    return population_counts(lst).most_common(1)[0][0]
+
+
+def least_common_item(lst: List[Any]) -> Any:
+    """
+    Return the least common item in the list.  In the case of
+    ties, which least common item is returned will be random.
+
+    >>> least_common_item([1, 1, 1, 2, 2, 3, 3, 3, 4])
+    4
+
+    """
+    return population_counts(lst).most_common()[-1][0]
+
+
+def dedup_list(lst: List[Any]) -> List[Any]:
+    """
+    Remove duplicates from the list performantly.
+
+    >>> dedup_list([1, 2, 1, 3, 3, 4, 2, 3, 4, 5, 1])
+    [1, 2, 3, 4, 5]
+
+    """
+    return list(set(lst))
+
+
+def uniq(lst: List[Any]) -> List[Any]:
+    """
+    Alias for dedup_list.
+
+    """
+    return dedup_list(lst)
+
+
+def ngrams(lst: Sequence[Any], n):
+    for i in range(len(lst) - n + 1):
+        yield lst[i:i + n]
+
+
+if __name__ == '__main__':
+    import doctest
+    doctest.testmod()