ENH: Add support for dataclasses in the DataFrame constructor (pandas…

…-dev#27999)

doc/source/user_guide/dsintro.rst

@@ -397,6 +397,28 @@ The result will be a DataFrame with the same index as the input Series, and
 with one column whose name is the original name of the Series (only if no other
 column name provided).
 
+.. _basics.dataframe.from_list_dataclasses:
+
+From a list of dataclasses
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. versionadded:: 1.1.0
+
+Data Classes as introduced in `PEP557 <https://www.python.org/dev/peps/pep-0557>`__,
+can be passed into the DataFrame constructor.
+Passing a list of dataclasses is equivilent to passing a list of dictionaries.
+
+Please be aware, that that all values in the list should be dataclasses, mixing
+types in the list would result in a TypeError.
+
+.. ipython:: python
+
+    from dataclasses import make_dataclass
+
+    Point = make_dataclass("Point", [("x", int), ("y", int)])
+
+    pd.DataFrame([Point(0, 0), Point(0, 3), Point(2, 3)])
+
 **Missing data**
 
 Much more will be said on this topic in the :ref:`Missing data <missing_data>`

pandas/core/dtypes/common.py

@@ -24,6 +24,7 @@
     is_array_like,
     is_bool,
     is_complex,
+    is_dataclass,
     is_decimal,
     is_dict_like,
     is_file_like,

pandas/core/dtypes/inference.py

@@ -386,3 +386,39 @@ def is_sequence(obj) -> bool:
         return not isinstance(obj, (str, bytes))
     except (TypeError, AttributeError):
         return False
+
+
+def is_dataclass(item):
+    """
+    Checks if the object is a data-class instance
+
+    Parameters
+    ----------
+    item : object
+
+    Returns
+    --------
+    is_dataclass : bool
+        True if the item is an instance of a data-class,
+        will return false if you pass the data class itself
+
+    Examples
+    --------
+    >>> from dataclasses import dataclass
+    >>> @dataclass
+    ... class Point:
+    ...     x: int
+    ...     y: int
+
+    >>> is_dataclass(Point)
+    False
+    >>> is_dataclass(Point(0,2))
+    True
+
+    """
+    try:
+        from dataclasses import is_dataclass
+
+        return is_dataclass(item) and not isinstance(item, type)
+    except ImportError:
+        return False

pandas/core/frame.py

@@ -77,6 +77,7 @@
     ensure_platform_int,
     infer_dtype_from_object,
     is_bool_dtype,
+    is_dataclass,
     is_datetime64_any_dtype,
     is_dict_like,
     is_dtype_equal,
@@ -117,6 +118,7 @@
 from pandas.core.internals import BlockManager
 from pandas.core.internals.construction import (
     arrays_to_mgr,
+    dataclasses_to_dicts,
     get_names_from_index,
     init_dict,
     init_ndarray,
@@ -474,6 +476,8 @@ def __init__(
             if not isinstance(data, (abc.Sequence, ExtensionArray)):
                 data = list(data)
             if len(data) > 0:
+                if is_dataclass(data[0]):
+                    data = dataclasses_to_dicts(data)
                 if is_list_like(data[0]) and getattr(data[0], "ndim", 1) == 1:
                     if is_named_tuple(data[0]) and columns is None:
                         columns = data[0]._fields

pandas/core/internals/construction.py

@@ -429,6 +429,33 @@ def _get_axes(N, K, index, columns):
     return index, columns
 
 
+def dataclasses_to_dicts(data):
+    """    Converts a list of dataclass instances to a list of dictionaries
+
+    Parameters
+    ----------
+    data : List[Type[dataclass]]
+
+    Returns
+    --------
+    list_dict : List[dict]
+
+    Examples
+    --------
+    >>> @dataclass
+    >>> class Point:
+    ...     x: int
+    ...     y: int
+
+    >>> dataclasses_to_dicts([Point(1,2), Point(2,3)])
+    [{"x":1,"y":2},{"x":2,"y":3}]
+
+    """
+    from dataclasses import asdict
+
+    return list(map(asdict, data))
+
+
 # ---------------------------------------------------------------------
 # Conversion of Inputs to Arrays
 

pandas/tests/frame/test_constructors.py

@@ -9,7 +9,7 @@
 import pytest
 import pytz
 
-from pandas.compat import is_platform_little_endian
+from pandas.compat import PY37, is_platform_little_endian
 from pandas.compat.numpy import _is_numpy_dev
 
 from pandas.core.dtypes.common import is_integer_dtype
@@ -1364,6 +1364,46 @@ def test_constructor_list_of_namedtuples(self):
         result = DataFrame(tuples, columns=["y", "z"])
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.skipif(not PY37, reason="Requires Python >= 3.7")
+    def test_constructor_list_of_dataclasses(self):
+        # GH21910
+        from dataclasses import make_dataclass
+
+        Point = make_dataclass("Point", [("x", int), ("y", int)])
+
+        datas = [Point(0, 3), Point(1, 3)]
+        expected = DataFrame({"x": [0, 1], "y": [3, 3]})
+        result = DataFrame(datas)
+        tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.skipif(not PY37, reason="Requires Python >= 3.7")
+    def test_constructor_list_of_dataclasses_with_varying_types(self):
+        # GH21910
+        from dataclasses import make_dataclass
+
+        # varying types
+        Point = make_dataclass("Point", [("x", int), ("y", int)])
+        HLine = make_dataclass("HLine", [("x0", int), ("x1", int), ("y", int)])
+
+        datas = [Point(0, 3), HLine(1, 3, 3)]
+
+        expected = DataFrame(
+            {"x": [0, np.nan], "y": [3, 3], "x0": [np.nan, 1], "x1": [np.nan, 3]}
+        )
+        result = DataFrame(datas)
+        tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.skipif(not PY37, reason="Requires Python >= 3.7")
+    def test_constructor_list_of_dataclasses_error_thrown(self):
+        # GH21910
+        from dataclasses import make_dataclass
+
+        Point = make_dataclass("Point", [("x", int), ("y", int)])
+
+        # expect TypeError
+        with pytest.raises(TypeError):
+            DataFrame([Point(0, 0), {"x": 1, "y": 0}])
+
     def test_constructor_list_of_dict_order(self):
         # GH10056
         data = [