Add list_cat, list_concat, list_repeat

docs/source/user-guide/common-operations/expressions.rst

@@ -110,6 +110,35 @@ This function returns an integer indicating the total number of elements in the
 
 In this example, the `num_elements` column will contain `3` for both rows.
 
+To concatenate two arrays, you can use the function :py:func:`datafusion.functions.array_cat` or :py:func:`datafusion.functions.array_concat`.
+These functions return a new array that is the concatenation of the input arrays.
+
+.. ipython:: python
+
+    from datafusion import SessionContext, col
+    from datafusion.functions import array_cat, array_concat
+
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[4, 5, 6]]})
+    df.select(array_cat(col("a"), col("b")).alias("concatenated_array"))
+
+In this example, the `concatenated_array` column will contain `[1, 2, 3, 4, 5, 6]`.
+
+To repeat the elements of an array a specified number of times, you can use the function :py:func:`datafusion.functions.array_repeat`.
+This function returns a new array with the elements repeated.
+
+.. ipython:: python
+
+    from datafusion import SessionContext, col, literal
+    from datafusion.functions import array_repeat
+
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [[1, 2, 3]]})
+    df.select(array_repeat(col("a"), literal(2)).alias("repeated_array"))
+
+In this example, the `repeated_array` column will contain `[[1, 2, 3], [1, 2, 3]]`.
+
+
 Structs
 -------
 

python/datafusion/functions.py

@@ -147,6 +147,8 @@
     "length",
     "levenshtein",
     "list_append",
+    "list_cat",
+    "list_concat",
     "list_dims",
     "list_distinct",
     "list_element",
@@ -162,6 +164,7 @@
     "list_prepend",
     "list_push_back",
     "list_push_front",
+    "list_repeat",
     "list_remove",
     "list_remove_all",
     "list_remove_n",
@@ -1142,6 +1145,22 @@ def array_distinct(array: Expr) -> Expr:
     return Expr(f.array_distinct(array.expr))
 
 
+def list_cat(*args: Expr) -> Expr:
+    """Concatenates the input arrays.
+
+    This is an alias for :py:func:`array_concat`, :py:func:`array_cat`.
+    """
+    return array_concat(*args)
+
+
+def list_concat(*args: Expr) -> Expr:
+    """Concatenates the input arrays.
+
+    This is an alias for :py:func:`array_concat`, :py:func:`array_cat`.
+    """
+    return array_concat(*args)
+
+
 def list_distinct(array: Expr) -> Expr:
     """Returns distinct values from the array after removing duplicates.
 
@@ -1366,6 +1385,14 @@ def array_repeat(element: Expr, count: Expr) -> Expr:
     return Expr(f.array_repeat(element.expr, count.expr))
 
 
+def list_repeat(element: Expr, count: Expr) -> Expr:
+    """Returns an array containing ``element`` ``count`` times.
+
+    This is an alias for :py:func:`array_repeat`.
+    """
+    return array_repeat(element, count)
+
+
 def array_replace(array: Expr, from_val: Expr, to_val: Expr) -> Expr:
     """Replaces the first occurrence of ``from_val`` with ``to_val``."""
     return Expr(f.array_replace(array.expr, from_val.expr, to_val.expr))

python/tests/test_functions.py

@@ -289,6 +289,14 @@ def py_flatten(arr):
             lambda col: f.array_cat(col, col),
             lambda data: [np.concatenate([arr, arr]) for arr in data],
         ],
+        [
+            lambda col: f.list_cat(col, col),
+            lambda data: [np.concatenate([arr, arr]) for arr in data],
+        ],
+        [
+            lambda col: f.list_concat(col, col),
+            lambda data: [np.concatenate([arr, arr]) for arr in data],
+        ],
         [
             lambda col: f.array_dims(col),
             lambda data: [[len(r)] for r in data],
@@ -437,6 +445,10 @@ def py_flatten(arr):
             lambda col: f.array_repeat(col, literal(2)),
             lambda data: [[arr] * 2 for arr in data],
         ],
+        [
+            lambda col: f.list_repeat(col, literal(2)),
+            lambda data: [[arr] * 2 for arr in data],
+        ],
         [
             lambda col: f.array_replace(col, literal(3.0), literal(4.0)),
             lambda data: [py_arr_replace(arr, 3.0, 4.0, 1) for arr in data],