BUG: Convert tuple to list before _list_to_arrays when construct DataFrame.

doc/source/whatsnew/v0.25.0.rst

@@ -383,6 +383,7 @@ Reshaping
 - Bug in :func:`concat` where order of ``OrderedDict`` (and ``dict`` in Python 3.6+) is not respected, when passed in as  ``objs`` argument (:issue:`21510`)
 - Bug in :func:`concat` where the resulting ``freq`` of two :class:`DatetimeIndex` with the same ``freq`` would be dropped (:issue:`3232`).
 - Bug in :func:`merge` where merging with equivalent Categorical dtypes was raising an error (:issue:`22501`)
+- Bug in :class:`DataFrame` constructor when passing non-empty tuples would cause a segmentation fault (:issue:`25691`)
 
 Sparse
 ^^^^^^

pandas/_libs/lib.pyx

@@ -2267,7 +2267,7 @@ def to_object_array(rows: object, int min_width=0):
         list input_rows
         list row
 
-    input_rows = <list>rows
+    input_rows = list(rows)
     n = len(input_rows)
 
     k = min_width
@@ -2304,31 +2304,54 @@ def tuples_to_object_array(ndarray[object] tuples):
     return result
 
 
-def to_object_array_tuples(rows: list):
+def to_object_array_tuples(rows: object):
+    """
+    Convert a list of tuples into an object array. Any subclass of
+    tuple in `rows` will be casted to tuple.
+
+    Parameters
+    ----------
+    rows : 2-d array (N, K)
+        A list of tuples to be converted into an array
+    min_width : int
+        The minimum width of the object array. If a tuple
+        in `rows` contains fewer than `width` elements,
+        the remaining elements in the corresponding row
+        will all be `NaN`.
+
+    Returns
+    -------
+    obj_array : numpy array of the object dtype
+    """
     cdef:
         Py_ssize_t i, j, n, k, tmp
         ndarray[object, ndim=2] result
+        list input_rows
         tuple row
 
-    n = len(rows)
+    input_rows = list(rows)
+    n = len(input_rows)
 
     k = 0
     for i in range(n):
-        tmp = 1 if checknull(rows[i]) else len(rows[i])
+        tmp = 1 if checknull(input_rows[i]) else len(input_rows[i])
         if tmp > k:
             k = tmp
 
     result = np.empty((n, k), dtype=object)
 
     try:
         for i in range(n):
-            row = rows[i]
+            row = input_rows[i]
             for j in range(len(row)):
                 result[i, j] = row[j]
     except Exception:
         # upcast any subclasses to tuple
         for i in range(n):
-            row = (rows[i],) if checknull(rows[i]) else tuple(rows[i])
+            if (checknull(input_rows[i])):
+                row = (input_rows[i],)
+            else:
+                row = tuple(input_rows[i])
             for j in range(len(row)):
                 result[i, j] = row[j]
 

pandas/tests/frame/test_constructors.py

@@ -1209,12 +1209,26 @@ def test_constructor_mixed_type_rows(self):
         expected = DataFrame([[1, 2], [3, 4]])
         tm.assert_frame_equal(result, expected)
 
-    def test_constructor_tuples(self):
+    @pytest.mark.parametrize("tuples,lists", [
+        ((), []),
+        ((()), []),
+        (((), ()), [(), ()]),
+        (((), ()), [[], []]),
+        (([], []), [[], []]),
+        (([1, 2, 3], [4, 5, 6]), [[1, 2, 3], [4, 5, 6]])
+    ])
+    def test_constructor_tuple(self, tuples, lists):
+        # GH 25691
+        result = DataFrame(tuples)
+        expected = DataFrame(lists)
+        tm.assert_frame_equal(result, expected)
+
+    def test_constructor_list_of_tuples(self):
         result = DataFrame({'A': [(1, 2), (3, 4)]})
         expected = DataFrame({'A': Series([(1, 2), (3, 4)])})
         tm.assert_frame_equal(result, expected)
 
-    def test_constructor_namedtuples(self):
+    def test_constructor_list_of_namedtuples(self):
         # GH11181
         from collections import namedtuple
         named_tuple = namedtuple("Pandas", list('ab'))