Update to Data Classes.

The major changes from the previous version are:

- Add InitVar to specify initialize-only fields.
- Renamed __dataclass_post_init__() to __post_init().
- Rename cmp to compare.
- Added eq, separate from compare, so you can test
  unorderable items for equality.
- Flushed out asdict() and astuple().
- Changed replace() to just call __init__(), and dropped
  complex post-create logic.

pep-0557.rst

@@ -6,7 +6,7 @@ Type: Standards Track
 Content-Type: text/x-rst
 Created: 02-Jun-2017
 Python-Version: 3.7
-Post-History: 08-Sep-2017
+Post-History: 08-Sep-2017, 25-Nov-2017
 
 Notice for Reviewers
 ====================
@@ -21,21 +21,27 @@ Abstract
 
 This PEP describes an addition to the standard library called Data
 Classes.  Although they use a very different mechanism, Data Classes
-can be thought of as "mutable namedtuples with defaults".
+can be thought of as "mutable namedtuples with defaults".  Because
+Data Classes use normal class definition syntax, you are free to use
+inheritance, metaclasses, docstrings, user-defined methods, class
+factories, and other Python class features.
 
 A class decorator is provided which inspects a class definition for
 variables with type annotations as defined in PEP 526, "Syntax for
 Variable Annotations".  In this document, such variables are called
 fields.  Using these fields, the decorator adds generated method
 definitions to the class to support instance initialization, a repr,
-and comparisons methods.  Such a class is called a Data Class, but
+comparisons methods, and optionally other methods as described in the
-there's really nothing special about the class: it is the same class
+Specification_ section.  Such a class is called a Data Class, but
-but with the generated methods added.
+there's really nothing special about the class: the decorator adds
+generated methods to the class and returns the same class it was
+given.
 
 As an example::
 
   @dataclass
   class InventoryItem:
+      '''Class for keeping track of an item in inventory.'''
       name: str
       unit_price: float
       quantity_on_hand: int = 0
@@ -100,7 +106,7 @@ So, why is this PEP needed?
 
 With the addition of PEP 526, Python has a concise way to specify the
 type of class members.  This PEP leverages that syntax to provide a
-simple, unobtrusive way to describe Data Classes.  With one exception,
+simple, unobtrusive way to describe Data Classes.  With two exceptions,
 the specified attribute type annotation is completely ignored by Data
 Classes.
 
@@ -110,6 +116,12 @@ interference from Data Classes.  The decorated classes are truly
 "normal" Python classes.  The Data Class decorator should not
 interfere with any usage of the class.
 
+One main design goal of Data Classes is to support static type
+checkers.  The use of PEP 526 syntax is one example of this, but so is
+the design of the ``fields()`` function and the ``@dataclass``
+decorator.  Due to their very dynamic nature, some of the libraries
+mentioned above are difficult to use with static type checkers.
+
 Data Classes are not, and are not intended to be, a replacement
 mechanism for all of the above libraries.  But being in the standard
 library will allow many of the simpler use cases to instead leverage
@@ -118,14 +130,12 @@ sets, and will of course continue to exist and prosper.
 
 Where is it not appropriate to use Data Classes?
 
-- Compatibility with tuples is required.
+- API compatibility with tuples or dicts is required.
-
-- True immutability is required.
 
 - Type validation beyond that provided by PEPs 484 and 526 is
-  required, or value validation is required.
+  required, or value validation or conversion is required.
 
-XXX Motivation for each dataclass() and field() parameter
+.. _Specification:
 
 Specification
 =============
@@ -134,14 +144,14 @@ All of the functions described in this PEP will live in a module named
 ``dataclasses``.
 
 A function ``dataclass`` which is typically used as a class decorator
-is provided to post-process classes and add generated member
+is provided to post-process classes and add generated methods,
-functions, described below.
+described below.
 
 The ``dataclass`` decorator examines the class to find ``field``'s.  A
 ``field`` is defined as any variable identified in
-``__annotations__``.  That is, a variable that is decorated with a
+``__annotations__``.  That is, a variable that has a type annotation.
-type annotation.  With a single exception described below, none of the
+With two exceptions described below, none of the Data Class machinery
-Data Class machinery examines the type specified in the annotation.
+examines the type specified in the annotation.
 
 Note that ``__annotations__`` is guaranteed to be an ordered mapping,
 in class declaration order.  The order of the fields in all of the
@@ -151,7 +161,7 @@ The ``dataclass`` decorator is typically used with no parameters and
 no parentheses.  However, it also supports the following logical
 signature::
 
-  def dataclass(*, init=True, repr=True, hash=None, cmp=True, frozen=False)
+  def dataclass(*, init=True, repr=True, eq=True, compare=True, hash=None, frozen=False)
 
 If ``dataclass`` is used just as a simple decorator with no
 parameters, it acts as if it has the default values documented in this
@@ -165,37 +175,45 @@ signature.  That is, these three uses of ``@dataclass`` are equivalent::
   class C:
       ...
 
-  @dataclass(init=True, repr=True, hash=None, cmp=True, frozen=False)
+  @dataclass(init=True, repr=True, eq=True, compare=True, hash=None, frozen=False)
   class C:
       ...
 
 The parameters to ``dataclass`` are:
 
-- ``init``: If true, a ``__init__`` method will be generated.
+- ``init``: If true (the default), a ``__init__`` method will be
+  generated.
 
-- ``repr``: If true, a ``__repr__`` function will be generated.  The
+- ``repr``: If true (the default), a ``__repr__`` function will be
-  generated repr string will have the class name and the name and repr
+  generated.  The generated repr string will have the class name and
-  of each field, in the order they are defined in the class.  Fields
+  the name and repr of each field, in the order they are defined in
-  that are marked as being excluded from the repr are not included.
+  the class.  Fields that are marked as being excluded from the repr
-  For example:
+  are not included.  For example:
   ``InventoryItem(name='widget',unit_price=3.0,quantity_on_hand=10)``.
 
-- ``cmp``: If true, ``__eq__``, ``__ne__``, ``__lt__``, ``__le__``,
+- ``eq``: If true (the default), ``__eq__`` and ``__ne__`` methods
+  will be generated.  These compare the class as if it were a tuple of
+  its fields, in order.  Both instances in the comparison must be of
+  the identical type.
+
+- ``compare``: If true (the default), ``__lt__``, ``__le__``,
   ``__gt__``, and ``__ge__`` methods will be generated.  These compare
   the class as if it were a tuple of its fields, in order.  Both
-  instances in the comparison must be of the identical type.
+  instances in the comparison must be of the identical type.  If
+  ``compare`` is True, then ``eq`` is ignored, and ``__eq__`` and
+  ``__ne__`` will be automatically generated.
 
 - ``hash``: Either a bool or ``None``.  If ``None`` (the default), the
-  ``__hash__`` method is generated according to how cmp and frozen are
+  ``__hash__`` method is generated according to how ``eq`` and
-  set.
+  ``frozen`` are set.
 
-  If ``cmp`` and ``frozen`` are both true, Data Classes will generate
+  If ``eq`` and ``frozen`` are both true, Data Classes will generate a
-  a ``__hash__`` for you.  If ``cmp`` is true and ``frozen`` is false,
+  ``__hash__`` method for you.  If ``eq`` is true and ``frozen`` is
-  ``__hash__`` will be set to ``None``, marking it unhashable (which
+  false, ``__hash__`` will be set to ``None``, marking it unhashable
-  it is).  If cmp is false, ``__hash__`` will be left untouched
+  (which it is).  If ``eq`` is false, ``__hash__`` will be left
-  meaning the ``__hash__`` method of the superclass will be used (if
+  untouched meaning the ``__hash__`` method of the superclass will be
-  superclass is ``object``, this means it will fall back to id-based
+  used (if the superclass is ``object``, this means it will fall back
-  hashing).
+  to id-based hashing).
 
   Although not recommended, you can force Data Classes to create a
   ``__hash__`` method with ``hash=True``. This might be the case if your
@@ -204,10 +222,11 @@ The parameters to ``dataclass`` are:
 
   See the Python documentation [#]_ for more information.
 
-- ``frozen``: If True, assigning to fields will generate an exception.
+- ``frozen``: If true (the default is False), assigning to fields will
-  This emulates read-only frozen instances.  See the discussion below.
+  generate an exception.  This emulates read-only frozen instances.
+  See the discussion below.
 
-``field``'s may optionally specify a default value, using normal
+``field``s may optionally specify a default value, using normal
 Python syntax::
 
   @dataclass
@@ -215,6 +234,11 @@ Python syntax::
       a: int       # 'a' has no default value
       b: int = 0   # assign a default value for 'b'
 
+In this example, both ``a`` and ``b`` will be included in the added
+``__init__`` function, which will be defined as::
+
+  def __init__(self, a: int, b: int = 0):
+
 For common and simple use cases, no other functionality is required.
 There are, however, some Data Class features that require additional
 per-field information.  To satisfy this need for additional
@@ -222,7 +246,7 @@ information, you can replace the default field value with a call to
 the provided ``field()`` function.  The signature of ``field()`` is::
 
   def field(*, default=_MISSING, default_factory=_MISSING, repr=True,
-            hash=None, init=True, cmp=True)
+            hash=None, init=True, compare=True, metadata=None)
 
 The ``_MISSING`` value is a sentinel object used to detect if the
 ``default`` and ``default_factory`` parameters are provided.  Users
@@ -241,57 +265,133 @@ The parameters to ``field()`` are:
   with mutable default values, as discussed below.  It is an error to
   specify both ``default`` and ``default_factory``.
 
-- ``init``: If True, this field is included as a parameter to the
+- ``init``: If true (the default), this field is included as a
-  generated ``__init__`` function.
+  parameter to the generated ``__init__`` function.
 
-- ``repr``: If True, this field is included in the string returned by
+- ``repr``: If true (the default), this field is included in the
-  the generated ``__repr__`` function.
+  string returned by the generated ``__repr__`` function.
 
-- ``cmp``: If True, this field is included in the generated comparison
+- ``compare``: If True (the default), this field is included in the
-  methods (``__eq__`` et al).
+  generated equality and comparison methods (``__eq__``, ``__gt__``,
+  et al.).
 
 - ``hash``: This can be a bool or ``None``.  If True, this field is
   included in the generated ``__hash__`` method.  If ``None`` (the
-  default), use the value of ``cmp``: this would normally be the
+  default), use the value of ``compare``: this would normally be the
   expected behavior.  A field needs to be considered in the hash if
   it's used for comparisons.  Setting this value to anything other
   than ``None`` is discouraged.
 
+- ``metadata``: This can be a mapping or None. None is treated as an
+  empty dict.  This value is wrapped in ``types.MappingProxyType`` to
+  make it read-only, and exposed on the Field object. It is not used
+  at all by Data Classes, and is provided as a third-party extension
+  mechanism.  Multiple third-parties can each have their own key, to
+  use as a namespace in the metadata.
+
+If the default value of a field is specified by a call to ``field()``,
+then the class attribute for this field will be replaced by the
+specified ``default`` value, if one is provided in the call to
+``field()``.  If no ``default`` is provided, then the class attribute
+will be deleted.  The intent is that after the ``dataclass`` decorator
+runs, the class attributes will all contain the default values for the
+fields, just as if the default value itself were specified.  For
+example, after::
+
+  @dataclass
+  class C:
+      x: int
+      y: int = field(repr=False)
+      z: int = field(repr=False, default=10)
+      t: int = 20
+
+The class attribute ``C.z`` will be ``10``, the class attribute
+``C.t`` will be ``20``, and the class attributes ``C.x`` and ``C.y``
+will not be set.
+
 ``Field`` objects
 -----------------
 
 ``Field`` objects describe each defined field. These objects are
 created internally, and are returned by the ``fields()`` module-level
 method (see below).  Users should never instantiate a ``Field``
-object directly.  Its attributes are:
+object directly.  Its documented attributes are:
 
  - ``name``: The name of the field.
 
  - ``type``: The type of the field.
 
- - ``default``, ``default_factory``, ``init``, ``repr``, ``hash``, and
+ - ``default``, ``default_factory``, ``init``, ``repr``, ``hash``,
-   ``cmp`` have the identical meaning as they do in the ``field()``
+   ``compare``, and ``metadata`` have the identical meaning as they do
-   declaration.
+   in the ``field()`` declaration.
+
+Other attributes may exist, but they are private.
 
 post-init processing
 --------------------
 
 The generated ``__init__`` code will call a method named
-``__dataclass_post_init__``, if it is defined on the class.  It will
+``__post_init__``, if it is defined on the class.  It will
-be called as ``self.__dataclass_post_init__()``.
+be called as ``self.__post_init__()``.
 
 Among other uses, this allows for initializing field values that
-depend on one or more other fields.
+depend on one or more other fields.  For example::
+
+    @dataclass
+    class C:
+        a: float
+        b: float
+        c: float = field(init=False)
+
+        def __post_init__(self):
+            self.c = self.a + self.b
+
+See the section below on init-only variables for ways to pass
+parameters to ``__post_init__()``.  Also see the warning about how
+``replace()`` handles ``init=False`` fields.
 
 Class variables
 ---------------
 
-The one place where ``dataclass`` actually inspects the type of a
+One place where ``dataclass`` actually inspects the type of a field is
-field is to determine if a field is a class variable.  It does this by
+to determine if a field is a class variable as defined in PEP 526.  It
-seeing if the type of the field is given as of type
+does this by checking if the type of the field is of type
 ``typing.ClassVar``.  If a field is a ``ClassVar``, it is excluded
 from consideration as a field and is ignored by the Data Class
-mechanisms.
+mechanisms. For more discussion, see [#]_.  Such ``ClassVar``
+pseudo-fields are not returned by the module-level ``fields()``
+function.
+
+Init-only variables
+-------------------
+
+The other place where ``dataclass`` inspects a type annotation is to
+determine if a field is an init-only variable.  It does this by seeing
+if the type of a field is of type ``dataclasses.InitVar``.  If a field
+is an ``InitVar``, it is considered a pseudo-field called an init-only
+field.  As it is not a true field, it is not returned by the
+module-level ``fields()`` function.  Init-only fields are added as
+parameters to the generated ``__init__`` method, and are passed to
+the optional ``__post_init__`` method.  They are not otherwise used
+by Data Classes.
+
+For example, suppose a field will be initialzed from a database, if a
+value is not provided when creating the class::
+
+  @dataclass
+  class C:
+      i: int
+      j: int = None
+      database: InitVar[DatabaseType] = None
+
+      def __post_init__(self, database):
+          if self.j is None and database is not None:
+              self.j = database.lookup('j')
+
+  c = C(10, database=my_database)
+
+In this case, ``fields()`` will return ``Field`` objects for ``i`` and
+``j``, but not for ``database``.
 
 Frozen instances
 ----------------
@@ -299,46 +399,13 @@ Frozen instances
 It is not possible to create truly immutable Python objects.  However,
 by passing ``frozen=True`` to the ``@dataclass`` decorator you can
 emulate immutability.  In that case, Data Classes will add
-``__setattr__`` and ``__delattr__`` member functions to the class.
+``__setattr__`` and ``__delattr__`` methods to the class.  These
-These functions will raise a ``FrozenInstanceError`` when invoked.
+methods will raise a ``FrozenInstanceError`` when invoked.
 
 There is a tiny performance penalty when using ``frozen=True``:
 ``__init__`` cannot use simple assignment to initialize fields, and
 must use ``object.__setattr__``.
 
-Mutable default values
-----------------------
-
-Python stores the default field values in class attributes.
-Consider this example, not using Data Classes::
-
-  class C:
-      x = []
-      def __init__(self, x=x):
-          self.x = x
-
-  assert C().x is C().x
-  assert C().x is not C([]).x
-
-That is, two instances of class ``C`` that do not not specify a value
-for ``x`` when creating a class instance will share the same copy of
-the list.  Because Data Classes just use normal Python class creation,
-they also share this problem.  There is no general way for Data
-Classes to detect this condition.  Instead, Data Classes will raise a
-``TypeError`` if it detects a default parameter of type ``list``,
-``dict``, or ``set``.  This is a partial solution, but it does protect
-against many common errors.  See `How to support mutable default
-values`_ in the Discussion section for more details.
-
-Using default factory functions is a way to create new instances of
-mutable types as default values for fields::
-
-  @dataclass
-  class C:
-      x: list = field(default_factory=list)
-
-  assert C().x is not C().x
-
 Inheritance
 -----------
 
@@ -346,13 +413,15 @@ When the Data Class is being created by the ``@dataclass`` decorator,
 it looks through all of the class's base classes in reverse MRO (that
 is, starting at ``object``) and, for each Data Class that it finds,
 adds the fields from that base class to an ordered mapping of fields.
-After all of the base classes, it adds its own fields to the ordered
+After all of the base class fields are added, it adds its own fields
-mapping.  Because the fields are in insertion order, derived classes
+to the ordered mapping.  All of the generated methods will use this
-override base classes.  An example::
+combined, calculated ordered mapping of fields.  Because the fields
+are in insertion order, derived classes override base classes.  An
+example::
 
   @dataclass
   class Base:
-      x: float = 15.0
+      x: Any = 15.0
       y: int = 0
 
   @dataclass
@@ -363,6 +432,10 @@ override base classes.  An example::
 The final list of fields is, in order, ``x``, ``y``, ``z``.  The final
 type of ``x`` is ``int``, as specified in class ``C``.
 
+The generated ``__init__`` method for ``C`` will look like::
+
+  def __init__(self, x: int = 15, y: int = 0, z: int = 10):
+
 Default factory functions
 -------------------------
 
@@ -376,18 +449,165 @@ If a field is excluded from ``__init__`` (using ``init=False``) and
 the field also specifies ``default_factory``, then the default factory
 function will always be called from the generated ``__init__``
 function.  This happens because there is no other way to give the
-field a default value.
+field an initial value.
+
+Mutable default values
+----------------------
+
+Python stores default member variable values in class attributes.
+Consider this example, not using Data Classes::
+
+  class C:
+      x = []
+      def add(self, element):
+          self.x += element
+
+  o1 = C()
+  o2 = C()
+  o1.add(1)
+  o2.add(2)
+  assert o1.x == [1, 2]
+  assert o1.x is o2.x
+
+Note that the two instances of class ``C`` share the same class
+variable ``x``, as expected.
+
+Using Data Classes, *if* this code was valid::
+
+  @dataclass
+  class D:
+      x: List = []
+      def add(self, element):
+          self.x += element
+
+it would generate code similar to::
+
+  class D:
+      x = []
+      def __init__(self, x=x):
+          self.x = x
+      def add(self, element):
+          self.x += element
+
+  assert D().x is D().x
+
+This has the same issue as the original example using class ``C``.
+That is, two instances of class ``D`` that do not specify a value for
+``x`` when creating a class instance will share the same copy of
+``x``.  Because Data Classes just use normal Python class creation
+they also share this problem.  There is no general way for Data
+Classes to detect this condition.  Instead, Data Classes will raise a
+``TypeError`` if it detects a default parameter of type ``list``,
+``dict``, or ``set``.  This is a partial solution, but it does protect
+against many common errors.  See `Automatically support mutable
+default values`_ in the Rejected Ideas section for more details.
+
+Using default factory functions is a way to create new instances of
+mutable types as default values for fields::
+
+  @dataclass
+  class D:
+      x: list = field(default_factory=list)
+
+  assert D().x is not D().x
 
 Module level helper functions
 -----------------------------
 
 - ``fields(class_or_instance)``: Returns a list of ``Field`` objects
   that define the fields for this Data Class.  Accepts either a Data
-  Class, or an instance of a Data Class.
+  Class, or an instance of a Data Class.  Raises `ValueError` if not
+  passed a Data Class or instance of one.  Does not return
+  pseudo-fields which are ``ClassVar`` or ``InitVar``.
 
-- ``asdict(instance)``: todo: recursion, class factories, etc.
+- ``asdict(instance, *, dict_factory=dict)``: Converts the Data Class
+  ``instance`` to a dict (by using the factory function
+  ``dict_factory``).  Each Data Class is converted to a dict of its
+  fields, as name:value pairs.  Data Classes, dicts, lists, and tuples
+  are recursed into.  For example::
 
-- ``astuple(instance)``: todo: recursion, class factories, etc.
+    @dataclass
+    class Point:
+         x: int
+         y: int
+
+    @dataclass
+    class C:
+         l: List[Point]
+
+    p = Point(10, 20)
+    assert asdict(p) == {'x': 10, 'y': 20}
+
+    c = C([Point(0, 0), Point(10, 4)])
+    assert asdict(c) == {'l': [{'x': 0, 'y': 0}, {'x': 10, 'y': 4}]}
+
+  Raises ``TypeError`` if ``instance`` is not a Data Class instance.
+
+- ``astuple(*, tuple_factory=tuple)``: Converts the Data Class
+  ``instance`` to a tuple (by using the factory function
+  ``tuple_factory``).  Each Data Class is converted to a tuple of its
+  field values.  Data Classes, dicts, lists, and tuples are recursed
+  into.
+
+  Continuing from the previous example::
+
+    assert astuple(p) == (10, 20)
+    assert astuple(c) == ([(0, 0), (10, 4)],)
+
+  Raises ``TypeError`` if ``instance`` is not a Data Class instance.
+
+- ``isdataclass(instance)``: Returns ``True`` if ``instance`` is an
+  instance of a Data Class, otherwise returns ``False``.
+
+- ``make_dataclass(cls_name, fields, *, bases=(), namespace=None)``:
+  Creates a new Data Class with name ``cls_name``, fields as defined
+  in ``fields``, base classes as given in ``bases``, and initialized
+  with a namespace as given in ``namespace``.  This function is not
+  strictly required, because any Python mechanism for creating a new
+  class with ``__annotations__`` can then apply the ``dataclass``
+  function to convert that class to a Data Class.  This function is
+  provided as a convenience.  For example::
+
+    C = make_dataclass('C',
+                       [('x', int),
+                        ('y', int, field(default=5))],
+                       namespace={'add_one': lambda self: self.x + 1})
+
+  Is equivalent to::
+
+    @dataclass
+    class C:
+        x: int
+        y: int = 5
+
+        def add_one(self):
+            return self.x + 1
+
+- ``replace(instance, **changes)``: Creates a new object of the same
+  type of ``instance``, replacing fields with values from ``changes``.
+  If ``instance`` is not a Data Class, raises ``TypeError``.  If
+  values in ``changes`` do not specify fields, raises ``TypeError``.
+
+  The newly returned object is created by calling the ``__init__``
+  method of the Data Class.  This ensures that
+  ``__post_init__``, if present, is also called.
+
+  Init-only variables without default values, if any exist, must be
+  specified on the call to ``replace`` so that they can be passed to
+  ``__init__`` and ``__post_init__``.
+
+  It is an error for ``changes`` to contain any fields that are
+  defined as having ``init=False``.  A ``ValueError`` will be raised
+  in this case.
+
+  Be forewarned about how ``init=False`` fields work during a call to
+  ``replace()``.  They are not copied from the source object, but
+  rather are initialized in ``__post_init__()``, if they're
+  initialized at all.  It is expected that ``init=False`` fields will
+  be rarely and judiciously used.  If they are used, it might be wise
+  to have alternate class constructors, or perhaps a custom
+  ``replace()`` (or similarly named) method which handles instance
+  copying.
 
 .. _discussion:
 
@@ -421,24 +641,16 @@ workarounds:
 
 For more discussion, see [#]_.
 
-Should post-init take params?
+Why not just use namedtuple?
------------------------------
+----------------------------
 
-The post-init function ``__dataclass_post_init__`` takes no
+- Any namedtuple can be accidentally compared to any other with the
-parameters.  This was deemed to be simpler than trying to find a
+  same number of fields. For example: ``Point3D(2017, 6, 2) ==
-mechanism to optionally pass a parameter to the
+  Date(2017, 6, 2)``.  With Data Classes, this would return False.
-``__dataclass_post_init__`` function.
 
-
+- A namedtuple can be accidentally compared to a tuple.  For example
-Why not just use namedtuple
+  ``Point2D(1, 10) == (1, 10)``.  With Data Classes, this would return
----------------------------
+  False.
-
-- Any namedtuple can be compared to any other with the same number of
-  fields. For example: ``Point3D(2017, 6, 2) == Date(2017, 6, 2)``.
-  With Data Classes, this would return False.
-
-- A namedtuple can be compared to a tuple.  For example ``Point2D(1,
-  10) == (1, 10)``.  With Data Classes, this would return False.
 
 - Instances are always iterable, which can make it difficult to add
   fields.  If a library defines::
@@ -461,16 +673,19 @@ Why not just use namedtuple
 - Cannot control which fields are used for ``__init__``, ``__repr__``,
   etc.
 
-Why not just use typing.NamedTuple
+- Cannot support combining fields by inheritance.
-----------------------------------
+
+Why not just use typing.NamedTuple?
+-----------------------------------
 
 For classes with statically defined fields, it does support similar
 syntax to Data Classes, using type annotations.  This produces a
 namedtuple, so it shares ``namedtuple``'s benefits and some of its
-downsides.
+downsides.  Data Classes, unlike ``typing.NamedTuple``, support
+combining fields via inheritance.
 
-Why not just use attrs
+Why not just use attrs?
-----------------------
+-----------------------
 
 - attrs moves faster than could be accommodated if it were moved in to
   the standard library.
@@ -482,30 +697,81 @@ Why not just use attrs
 
 For more discussion, see [#]_.
 
-Dynamic creation of classes
+post-init parameters
----------------------------
+--------------------
 
-An earlier version of this PEP and the sample implementation provided
+In an earlier version of this PEP before ``InitVar`` was added, the
-a ``make_class`` function that dynamically created Data Classes.  This
+post-init function ``__post_init__`` never took any parameters.
-functionality was later dropped, although it might be added at a later
+
-time as a helper function.  The ``@dataclass`` decorator does not care
+The normal way of doing parameterized initialization (and not just
-how classes are created, so they could be either statically defined or
+with Data Classes) is to provide an alternate classmethod constructor.
-dynamically defined.  For this Data Class::
+For example::
 
   @dataclass
   class C:
       x: int
-      y: int = field(init=False, default=0)
 
-Here is one way of dynamically creating the same Data Class::
+      @classmethod
+      def from_file(cls, filename):
+          with open(filename) as fl:
+              file_value = int(fl.read())
+          return C(file_value)
 
-  cls_dict = {'__annotations__': OrderedDict(x=int, y=int),
+  c = C.from_file('file.txt')
-              'y': field(init=False, default=0),
-              }
-  C = dataclass(type('C', (object,), cls_dict))
 
-How to support mutable default values
+Because the ``__post_init__`` function is the last thing called in the
--------------------------------------
+generated ``__init__``, having a classmethod constructor (which can
+also execute code immmediately after constructing the object) is
+functionally equivalent to being able to pass parameters to a
+``__post_init__`` function.
+
+With ``InitVar``'s, ``__post_init__`` functions can now take
+parameters.  They are passed first to ``__init__`` which passes them
+to ``__post_init__`` where user code can use them as needed.
+
+The only real difference between alternate classmethod constructors
+and ``InitVar`` pseudo-fields is in object creation.  With
+``InitVar``s, using ``__init__`` and the module-level ``replace()``
+function ``InitVar``'s must always be specified.  With alternate
+classmethod constructors the additional initialization parameters are
+always optional.  Which approach is more appropriate will be
+application-specific, but both approaches are supported.
+
+Rejected ideas
+==============
+
+Copying ``init=False`` fields after new object creation in replace()
+--------------------------------------------------------------------
+
+Fields that are ``init=False`` are by definition not passed to
+``__init__``, but instead are initialized with a default value, or by
+calling a default factory function in ``__init__``, or by code in
+``__post_init__``.
+
+A previous version of this PEP specified that ``init=False`` fields
+would be copied from the source object to the newly created object
+after ``__init__`` returned, but that was deemed to be inconsistent
+with using ``__init__`` and ``__post_init__`` to initialize the new
+object.  For example, consider this case::
+
+  @dataclass
+  class Square:
+      length: float
+      area: float = field(init=False, default=0.0)
+
+      def __post_init__(self):
+          self.area = self.length * self.length
+
+  s1 = Square(1.0)
+  s2 = replace(s1, length=2.0)
+
+If ``init=False`` fields were copied from the source to the
+destination object after ``__post_init__`` is run, then s2 would end
+up begin ``Square(length=2.0, area=1.0)``, instead of the correct
+``Square(length=2.0, area=4.0)``.
+
+Automatically support mutable default values
+--------------------------------------------
 
 One proposal was to automatically copy defaults, so that if a literal
 list ``[]`` was a default value, each instance would get a new list.
@@ -517,6 +783,9 @@ see [#]_.
 Examples
 ========
 
+A complicated example
+---------------------
+
 This code exists in a closed source project::
 
   class Application:
@@ -536,10 +805,10 @@ This can be replaced by::
 
   @dataclass
   class Application:
-      name: Str
+      name: str
-      requirements: List
+      requirements: List[Requirement]
-      constraints: List[str] = field(default_factory=list)
+      constraints: Dict[str, str] = field(default_factory=dict)
-      path: Str = ''
+      path: str = ''
       executable_links: List[str] = field(default_factory=list)
       executable_dir: Tuple[str] = ()
       additional_items: List[str] = field(init=False, default_factory=list)
@@ -555,8 +824,8 @@ of this PEP and code: Ivan Levkivskyi, Guido van Rossum, Hynek
 Schlawack, Raymond Hettinger, and Lisa Roach.  I thank them for their
 time and expertise.
 
-A special mention must be made about the attrs project.  It was a true
+A special mention must be made about the ``attrs`` project.  It was a
-inspiration for this PEP, and I respect the design decisions they
+true inspiration for this PEP, and I respect the design decisions they
 made.
 
 References
@@ -580,6 +849,9 @@ References
 .. [#] Python documentation for __hash__
        (https://docs.python.org/3/reference/datamodel.html#object.__hash__)
 
+.. [#] ClassVar discussion in PEP 526
+       (https://www.python.org/dev/peps/pep-0526/#class-and-instance-variable-annotations)
+
 .. [#] Start of python-ideas discussion
        (https://mail.python.org/pipermail/python-ideas/2017-May/045618.html)
 
@@ -595,6 +867,7 @@ References
 .. [#] Copying mutable defaults
        (https://github.com/ericvsmith/dataclasses/issues/3)
 
+
 Copyright
 =========