840 lines
35 KiB
Python
840 lines
35 KiB
Python
# functions to transform a c class into a dataclass
|
|
|
|
from collections import OrderedDict
|
|
from textwrap import dedent
|
|
import operator
|
|
|
|
from . import ExprNodes
|
|
from . import Nodes
|
|
from . import PyrexTypes
|
|
from . import Builtin
|
|
from . import Naming
|
|
from .Errors import error, warning
|
|
from .Code import UtilityCode, TempitaUtilityCode, PyxCodeWriter
|
|
from .Visitor import VisitorTransform
|
|
from .StringEncoding import EncodedString
|
|
from .TreeFragment import TreeFragment
|
|
from .ParseTreeTransforms import NormalizeTree, SkipDeclarations
|
|
from .Options import copy_inherited_directives
|
|
|
|
_dataclass_loader_utilitycode = None
|
|
|
|
def make_dataclasses_module_callnode(pos):
|
|
global _dataclass_loader_utilitycode
|
|
if not _dataclass_loader_utilitycode:
|
|
python_utility_code = UtilityCode.load_cached("Dataclasses_fallback", "Dataclasses.py")
|
|
python_utility_code = EncodedString(python_utility_code.impl)
|
|
_dataclass_loader_utilitycode = TempitaUtilityCode.load(
|
|
"SpecificModuleLoader", "Dataclasses.c",
|
|
context={'cname': "dataclasses", 'py_code': python_utility_code.as_c_string_literal()})
|
|
return ExprNodes.PythonCapiCallNode(
|
|
pos, "__Pyx_Load_dataclasses_Module",
|
|
PyrexTypes.CFuncType(PyrexTypes.py_object_type, []),
|
|
utility_code=_dataclass_loader_utilitycode,
|
|
args=[],
|
|
)
|
|
|
|
def make_dataclass_call_helper(pos, callable, kwds):
|
|
utility_code = UtilityCode.load_cached("DataclassesCallHelper", "Dataclasses.c")
|
|
func_type = PyrexTypes.CFuncType(
|
|
PyrexTypes.py_object_type, [
|
|
PyrexTypes.CFuncTypeArg("callable", PyrexTypes.py_object_type, None),
|
|
PyrexTypes.CFuncTypeArg("kwds", PyrexTypes.py_object_type, None)
|
|
],
|
|
)
|
|
return ExprNodes.PythonCapiCallNode(
|
|
pos,
|
|
function_name="__Pyx_DataclassesCallHelper",
|
|
func_type=func_type,
|
|
utility_code=utility_code,
|
|
args=[callable, kwds],
|
|
)
|
|
|
|
|
|
class RemoveAssignmentsToNames(VisitorTransform, SkipDeclarations):
|
|
"""
|
|
Cython (and Python) normally treats
|
|
|
|
class A:
|
|
x = 1
|
|
|
|
as generating a class attribute. However for dataclasses the `= 1` should be interpreted as
|
|
a default value to initialize an instance attribute with.
|
|
This transform therefore removes the `x=1` assignment so that the class attribute isn't
|
|
generated, while recording what it has removed so that it can be used in the initialization.
|
|
"""
|
|
def __init__(self, names):
|
|
super(RemoveAssignmentsToNames, self).__init__()
|
|
self.names = names
|
|
self.removed_assignments = {}
|
|
|
|
def visit_CClassNode(self, node):
|
|
self.visitchildren(node)
|
|
return node
|
|
|
|
def visit_PyClassNode(self, node):
|
|
return node # go no further
|
|
|
|
def visit_FuncDefNode(self, node):
|
|
return node # go no further
|
|
|
|
def visit_SingleAssignmentNode(self, node):
|
|
if node.lhs.is_name and node.lhs.name in self.names:
|
|
if node.lhs.name in self.removed_assignments:
|
|
warning(node.pos, ("Multiple assignments for '%s' in dataclass; "
|
|
"using most recent") % node.lhs.name, 1)
|
|
self.removed_assignments[node.lhs.name] = node.rhs
|
|
return []
|
|
return node
|
|
|
|
# I believe cascaded assignment is always a syntax error with annotations
|
|
# so there's no need to define visit_CascadedAssignmentNode
|
|
|
|
def visit_Node(self, node):
|
|
self.visitchildren(node)
|
|
return node
|
|
|
|
|
|
class TemplateCode(object):
|
|
"""
|
|
Adds the ability to keep track of placeholder argument names to PyxCodeWriter.
|
|
|
|
Also adds extra_stats which are nodes bundled at the end when this
|
|
is converted to a tree.
|
|
"""
|
|
_placeholder_count = 0
|
|
|
|
def __init__(self, writer=None, placeholders=None, extra_stats=None):
|
|
self.writer = PyxCodeWriter() if writer is None else writer
|
|
self.placeholders = {} if placeholders is None else placeholders
|
|
self.extra_stats = [] if extra_stats is None else extra_stats
|
|
|
|
def add_code_line(self, code_line):
|
|
self.writer.putln(code_line)
|
|
|
|
def add_code_lines(self, code_lines):
|
|
for line in code_lines:
|
|
self.writer.putln(line)
|
|
|
|
def reset(self):
|
|
# don't attempt to reset placeholders - it really doesn't matter if
|
|
# we have unused placeholders
|
|
self.writer.reset()
|
|
|
|
def empty(self):
|
|
return self.writer.empty()
|
|
|
|
def indenter(self):
|
|
return self.writer.indenter()
|
|
|
|
def new_placeholder(self, field_names, value):
|
|
name = self._new_placeholder_name(field_names)
|
|
self.placeholders[name] = value
|
|
return name
|
|
|
|
def add_extra_statements(self, statements):
|
|
if self.extra_stats is None:
|
|
assert False, "Can only use add_extra_statements on top-level writer"
|
|
self.extra_stats.extend(statements)
|
|
|
|
def _new_placeholder_name(self, field_names):
|
|
while True:
|
|
name = "DATACLASS_PLACEHOLDER_%d" % self._placeholder_count
|
|
if (name not in self.placeholders
|
|
and name not in field_names):
|
|
# make sure name isn't already used and doesn't
|
|
# conflict with a variable name (which is unlikely but possible)
|
|
break
|
|
self._placeholder_count += 1
|
|
return name
|
|
|
|
def generate_tree(self, level='c_class'):
|
|
stat_list_node = TreeFragment(
|
|
self.writer.getvalue(),
|
|
level=level,
|
|
pipeline=[NormalizeTree(None)],
|
|
).substitute(self.placeholders)
|
|
|
|
stat_list_node.stats += self.extra_stats
|
|
return stat_list_node
|
|
|
|
def insertion_point(self):
|
|
new_writer = self.writer.insertion_point()
|
|
return TemplateCode(
|
|
writer=new_writer,
|
|
placeholders=self.placeholders,
|
|
extra_stats=self.extra_stats
|
|
)
|
|
|
|
|
|
class _MISSING_TYPE(object):
|
|
pass
|
|
MISSING = _MISSING_TYPE()
|
|
|
|
|
|
class Field(object):
|
|
"""
|
|
Field is based on the dataclasses.field class from the standard library module.
|
|
It is used internally during the generation of Cython dataclasses to keep track
|
|
of the settings for individual attributes.
|
|
|
|
Attributes of this class are stored as nodes so they can be used in code construction
|
|
more readily (i.e. we store BoolNode rather than bool)
|
|
"""
|
|
default = MISSING
|
|
default_factory = MISSING
|
|
private = False
|
|
|
|
literal_keys = ("repr", "hash", "init", "compare", "metadata")
|
|
|
|
# default values are defined by the CPython dataclasses.field
|
|
def __init__(self, pos, default=MISSING, default_factory=MISSING,
|
|
repr=None, hash=None, init=None,
|
|
compare=None, metadata=None,
|
|
is_initvar=False, is_classvar=False,
|
|
**additional_kwds):
|
|
if default is not MISSING:
|
|
self.default = default
|
|
if default_factory is not MISSING:
|
|
self.default_factory = default_factory
|
|
self.repr = repr or ExprNodes.BoolNode(pos, value=True)
|
|
self.hash = hash or ExprNodes.NoneNode(pos)
|
|
self.init = init or ExprNodes.BoolNode(pos, value=True)
|
|
self.compare = compare or ExprNodes.BoolNode(pos, value=True)
|
|
self.metadata = metadata or ExprNodes.NoneNode(pos)
|
|
self.is_initvar = is_initvar
|
|
self.is_classvar = is_classvar
|
|
|
|
for k, v in additional_kwds.items():
|
|
# There should not be any additional keywords!
|
|
error(v.pos, "cython.dataclasses.field() got an unexpected keyword argument '%s'" % k)
|
|
|
|
for field_name in self.literal_keys:
|
|
field_value = getattr(self, field_name)
|
|
if not field_value.is_literal:
|
|
error(field_value.pos,
|
|
"cython.dataclasses.field parameter '%s' must be a literal value" % field_name)
|
|
|
|
def iterate_record_node_arguments(self):
|
|
for key in (self.literal_keys + ('default', 'default_factory')):
|
|
value = getattr(self, key)
|
|
if value is not MISSING:
|
|
yield key, value
|
|
|
|
|
|
def process_class_get_fields(node):
|
|
var_entries = node.scope.var_entries
|
|
# order of definition is used in the dataclass
|
|
var_entries = sorted(var_entries, key=operator.attrgetter('pos'))
|
|
var_names = [entry.name for entry in var_entries]
|
|
|
|
# don't treat `x = 1` as an assignment of a class attribute within the dataclass
|
|
transform = RemoveAssignmentsToNames(var_names)
|
|
transform(node)
|
|
default_value_assignments = transform.removed_assignments
|
|
|
|
base_type = node.base_type
|
|
fields = OrderedDict()
|
|
while base_type:
|
|
if base_type.is_external or not base_type.scope.implemented:
|
|
warning(node.pos, "Cannot reliably handle Cython dataclasses with base types "
|
|
"in external modules since it is not possible to tell what fields they have", 2)
|
|
if base_type.dataclass_fields:
|
|
fields = base_type.dataclass_fields.copy()
|
|
break
|
|
base_type = base_type.base_type
|
|
|
|
for entry in var_entries:
|
|
name = entry.name
|
|
is_initvar = entry.declared_with_pytyping_modifier("dataclasses.InitVar")
|
|
# TODO - classvars aren't included in "var_entries" so are missed here
|
|
# and thus this code is never triggered
|
|
is_classvar = entry.declared_with_pytyping_modifier("typing.ClassVar")
|
|
if name in default_value_assignments:
|
|
assignment = default_value_assignments[name]
|
|
if (isinstance(assignment, ExprNodes.CallNode) and (
|
|
assignment.function.as_cython_attribute() == "dataclasses.field" or
|
|
Builtin.exprnode_to_known_standard_library_name(
|
|
assignment.function, node.scope) == "dataclasses.field")):
|
|
# I believe most of this is well-enforced when it's treated as a directive
|
|
# but it doesn't hurt to make sure
|
|
valid_general_call = (isinstance(assignment, ExprNodes.GeneralCallNode)
|
|
and isinstance(assignment.positional_args, ExprNodes.TupleNode)
|
|
and not assignment.positional_args.args
|
|
and (assignment.keyword_args is None or isinstance(assignment.keyword_args, ExprNodes.DictNode)))
|
|
valid_simple_call = (isinstance(assignment, ExprNodes.SimpleCallNode) and not assignment.args)
|
|
if not (valid_general_call or valid_simple_call):
|
|
error(assignment.pos, "Call to 'cython.dataclasses.field' must only consist "
|
|
"of compile-time keyword arguments")
|
|
continue
|
|
keyword_args = assignment.keyword_args.as_python_dict() if valid_general_call and assignment.keyword_args else {}
|
|
if 'default' in keyword_args and 'default_factory' in keyword_args:
|
|
error(assignment.pos, "cannot specify both default and default_factory")
|
|
continue
|
|
field = Field(node.pos, **keyword_args)
|
|
else:
|
|
if assignment.type in [Builtin.list_type, Builtin.dict_type, Builtin.set_type]:
|
|
# The standard library module generates a TypeError at runtime
|
|
# in this situation.
|
|
# Error message is copied from CPython
|
|
error(assignment.pos, "mutable default <class '{0}'> for field {1} is not allowed: "
|
|
"use default_factory".format(assignment.type.name, name))
|
|
|
|
field = Field(node.pos, default=assignment)
|
|
else:
|
|
field = Field(node.pos)
|
|
field.is_initvar = is_initvar
|
|
field.is_classvar = is_classvar
|
|
if entry.visibility == "private":
|
|
field.private = True
|
|
fields[name] = field
|
|
node.entry.type.dataclass_fields = fields
|
|
return fields
|
|
|
|
|
|
def handle_cclass_dataclass(node, dataclass_args, analyse_decs_transform):
|
|
# default argument values from https://docs.python.org/3/library/dataclasses.html
|
|
kwargs = dict(init=True, repr=True, eq=True,
|
|
order=False, unsafe_hash=False,
|
|
frozen=False, kw_only=False)
|
|
if dataclass_args is not None:
|
|
if dataclass_args[0]:
|
|
error(node.pos, "cython.dataclasses.dataclass takes no positional arguments")
|
|
for k, v in dataclass_args[1].items():
|
|
if k not in kwargs:
|
|
error(node.pos,
|
|
"cython.dataclasses.dataclass() got an unexpected keyword argument '%s'" % k)
|
|
if not isinstance(v, ExprNodes.BoolNode):
|
|
error(node.pos,
|
|
"Arguments passed to cython.dataclasses.dataclass must be True or False")
|
|
kwargs[k] = v.value
|
|
|
|
kw_only = kwargs['kw_only']
|
|
|
|
fields = process_class_get_fields(node)
|
|
|
|
dataclass_module = make_dataclasses_module_callnode(node.pos)
|
|
|
|
# create __dataclass_params__ attribute. I try to use the exact
|
|
# `_DataclassParams` class defined in the standard library module if at all possible
|
|
# for maximum duck-typing compatibility.
|
|
dataclass_params_func = ExprNodes.AttributeNode(node.pos, obj=dataclass_module,
|
|
attribute=EncodedString("_DataclassParams"))
|
|
dataclass_params_keywords = ExprNodes.DictNode.from_pairs(
|
|
node.pos,
|
|
[ (ExprNodes.IdentifierStringNode(node.pos, value=EncodedString(k)),
|
|
ExprNodes.BoolNode(node.pos, value=v))
|
|
for k, v in kwargs.items() ] +
|
|
[ (ExprNodes.IdentifierStringNode(node.pos, value=EncodedString(k)),
|
|
ExprNodes.BoolNode(node.pos, value=v))
|
|
for k, v in [('kw_only', kw_only), ('match_args', False),
|
|
('slots', False), ('weakref_slot', False)]
|
|
])
|
|
dataclass_params = make_dataclass_call_helper(
|
|
node.pos, dataclass_params_func, dataclass_params_keywords)
|
|
dataclass_params_assignment = Nodes.SingleAssignmentNode(
|
|
node.pos,
|
|
lhs = ExprNodes.NameNode(node.pos, name=EncodedString("__dataclass_params__")),
|
|
rhs = dataclass_params)
|
|
|
|
dataclass_fields_stats = _set_up_dataclass_fields(node, fields, dataclass_module)
|
|
|
|
stats = Nodes.StatListNode(node.pos,
|
|
stats=[dataclass_params_assignment] + dataclass_fields_stats)
|
|
|
|
code = TemplateCode()
|
|
generate_init_code(code, kwargs['init'], node, fields, kw_only)
|
|
generate_repr_code(code, kwargs['repr'], node, fields)
|
|
generate_eq_code(code, kwargs['eq'], node, fields)
|
|
generate_order_code(code, kwargs['order'], node, fields)
|
|
generate_hash_code(code, kwargs['unsafe_hash'], kwargs['eq'], kwargs['frozen'], node, fields)
|
|
|
|
stats.stats += code.generate_tree().stats
|
|
|
|
# turn off annotation typing, so all arguments to __init__ are accepted as
|
|
# generic objects and thus can accept _HAS_DEFAULT_FACTORY.
|
|
# Type conversion comes later
|
|
comp_directives = Nodes.CompilerDirectivesNode(node.pos,
|
|
directives=copy_inherited_directives(node.scope.directives, annotation_typing=False),
|
|
body=stats)
|
|
|
|
comp_directives.analyse_declarations(node.scope)
|
|
# probably already in this scope, but it doesn't hurt to make sure
|
|
analyse_decs_transform.enter_scope(node, node.scope)
|
|
analyse_decs_transform.visit(comp_directives)
|
|
analyse_decs_transform.exit_scope()
|
|
|
|
node.body.stats.append(comp_directives)
|
|
|
|
|
|
def generate_init_code(code, init, node, fields, kw_only):
|
|
"""
|
|
Notes on CPython generated "__init__":
|
|
* Implemented in `_init_fn`.
|
|
* The use of the `dataclasses._HAS_DEFAULT_FACTORY` sentinel value as
|
|
the default argument for fields that need constructing with a factory
|
|
function is copied from the CPython implementation. (`None` isn't
|
|
suitable because it could also be a value for the user to pass.)
|
|
There's no real reason why it needs importing from the dataclasses module
|
|
though - it could equally be a value generated by Cython when the module loads.
|
|
* seen_default and the associated error message are copied directly from Python
|
|
* Call to user-defined __post_init__ function (if it exists) is copied from
|
|
CPython.
|
|
|
|
Cython behaviour deviates a little here (to be decided if this is right...)
|
|
Because the class variable from the assignment does not exist Cython fields will
|
|
return None (or whatever their type default is) if not initialized while Python
|
|
dataclasses will fall back to looking up the class variable.
|
|
"""
|
|
if not init or node.scope.lookup_here("__init__"):
|
|
return
|
|
|
|
# selfname behaviour copied from the cpython module
|
|
selfname = "__dataclass_self__" if "self" in fields else "self"
|
|
args = [selfname]
|
|
|
|
if kw_only:
|
|
args.append("*")
|
|
|
|
function_start_point = code.insertion_point()
|
|
code = code.insertion_point()
|
|
|
|
# create a temp to get _HAS_DEFAULT_FACTORY
|
|
dataclass_module = make_dataclasses_module_callnode(node.pos)
|
|
has_default_factory = ExprNodes.AttributeNode(
|
|
node.pos,
|
|
obj=dataclass_module,
|
|
attribute=EncodedString("_HAS_DEFAULT_FACTORY")
|
|
)
|
|
|
|
default_factory_placeholder = code.new_placeholder(fields, has_default_factory)
|
|
|
|
seen_default = False
|
|
for name, field in fields.items():
|
|
entry = node.scope.lookup(name)
|
|
if entry.annotation:
|
|
annotation = u": %s" % entry.annotation.string.value
|
|
else:
|
|
annotation = u""
|
|
assignment = u''
|
|
if field.default is not MISSING or field.default_factory is not MISSING:
|
|
seen_default = True
|
|
if field.default_factory is not MISSING:
|
|
ph_name = default_factory_placeholder
|
|
else:
|
|
ph_name = code.new_placeholder(fields, field.default) # 'default' should be a node
|
|
assignment = u" = %s" % ph_name
|
|
elif seen_default and not kw_only and field.init.value:
|
|
error(entry.pos, ("non-default argument '%s' follows default argument "
|
|
"in dataclass __init__") % name)
|
|
code.reset()
|
|
return
|
|
|
|
if field.init.value:
|
|
args.append(u"%s%s%s" % (name, annotation, assignment))
|
|
|
|
if field.is_initvar:
|
|
continue
|
|
elif field.default_factory is MISSING:
|
|
if field.init.value:
|
|
code.add_code_line(u" %s.%s = %s" % (selfname, name, name))
|
|
elif assignment:
|
|
# not an argument to the function, but is still initialized
|
|
code.add_code_line(u" %s.%s%s" % (selfname, name, assignment))
|
|
else:
|
|
ph_name = code.new_placeholder(fields, field.default_factory)
|
|
if field.init.value:
|
|
# close to:
|
|
# def __init__(self, name=_PLACEHOLDER_VALUE):
|
|
# self.name = name_default_factory() if name is _PLACEHOLDER_VALUE else name
|
|
code.add_code_line(u" %s.%s = %s() if %s is %s else %s" % (
|
|
selfname, name, ph_name, name, default_factory_placeholder, name))
|
|
else:
|
|
# still need to use the default factory to initialize
|
|
code.add_code_line(u" %s.%s = %s()" % (
|
|
selfname, name, ph_name))
|
|
|
|
if node.scope.lookup("__post_init__"):
|
|
post_init_vars = ", ".join(name for name, field in fields.items()
|
|
if field.is_initvar)
|
|
code.add_code_line(" %s.__post_init__(%s)" % (selfname, post_init_vars))
|
|
|
|
if code.empty():
|
|
code.add_code_line(" pass")
|
|
|
|
args = u", ".join(args)
|
|
function_start_point.add_code_line(u"def __init__(%s):" % args)
|
|
|
|
|
|
def generate_repr_code(code, repr, node, fields):
|
|
"""
|
|
The core of the CPython implementation is just:
|
|
['return self.__class__.__qualname__ + f"(' +
|
|
', '.join([f"{f.name}={{self.{f.name}!r}}"
|
|
for f in fields]) +
|
|
')"'],
|
|
|
|
The only notable difference here is self.__class__.__qualname__ -> type(self).__name__
|
|
which is because Cython currently supports Python 2.
|
|
|
|
However, it also has some guards for recursive repr invocations. In the standard
|
|
library implementation they're done with a wrapper decorator that captures a set
|
|
(with the set keyed by id and thread). Here we create a set as a thread local
|
|
variable and key only by id.
|
|
"""
|
|
if not repr or node.scope.lookup("__repr__"):
|
|
return
|
|
|
|
# The recursive guard is likely a little costly, so skip it if possible.
|
|
# is_gc_simple defines where it can contain recursive objects
|
|
needs_recursive_guard = False
|
|
for name in fields.keys():
|
|
entry = node.scope.lookup(name)
|
|
type_ = entry.type
|
|
if type_.is_memoryviewslice:
|
|
type_ = type_.dtype
|
|
if not type_.is_pyobject:
|
|
continue # no GC
|
|
if not type_.is_gc_simple:
|
|
needs_recursive_guard = True
|
|
break
|
|
|
|
if needs_recursive_guard:
|
|
code.add_code_line("__pyx_recursive_repr_guard = __import__('threading').local()")
|
|
code.add_code_line("__pyx_recursive_repr_guard.running = set()")
|
|
code.add_code_line("def __repr__(self):")
|
|
if needs_recursive_guard:
|
|
code.add_code_line(" key = id(self)")
|
|
code.add_code_line(" guard_set = self.__pyx_recursive_repr_guard.running")
|
|
code.add_code_line(" if key in guard_set: return '...'")
|
|
code.add_code_line(" guard_set.add(key)")
|
|
code.add_code_line(" try:")
|
|
strs = [u"%s={self.%s!r}" % (name, name)
|
|
for name, field in fields.items()
|
|
if field.repr.value and not field.is_initvar]
|
|
format_string = u", ".join(strs)
|
|
|
|
code.add_code_line(u' name = getattr(type(self), "__qualname__", type(self).__name__)')
|
|
code.add_code_line(u" return f'{name}(%s)'" % format_string)
|
|
if needs_recursive_guard:
|
|
code.add_code_line(" finally:")
|
|
code.add_code_line(" guard_set.remove(key)")
|
|
|
|
|
|
def generate_cmp_code(code, op, funcname, node, fields):
|
|
if node.scope.lookup_here(funcname):
|
|
return
|
|
|
|
names = [name for name, field in fields.items() if (field.compare.value and not field.is_initvar)]
|
|
|
|
code.add_code_lines([
|
|
"def %s(self, other):" % funcname,
|
|
" if other.__class__ is not self.__class__:"
|
|
" return NotImplemented",
|
|
#
|
|
" cdef %s other_cast" % node.class_name,
|
|
" other_cast = <%s>other" % node.class_name,
|
|
])
|
|
|
|
# The Python implementation of dataclasses.py does a tuple comparison
|
|
# (roughly):
|
|
# return self._attributes_to_tuple() {op} other._attributes_to_tuple()
|
|
#
|
|
# For the Cython implementation a tuple comparison isn't an option because
|
|
# not all attributes can be converted to Python objects and stored in a tuple
|
|
#
|
|
# TODO - better diagnostics of whether the types support comparison before
|
|
# generating the code. Plus, do we want to convert C structs to dicts and
|
|
# compare them that way (I think not, but it might be in demand)?
|
|
checks = []
|
|
op_without_equals = op.replace('=', '')
|
|
|
|
for name in names:
|
|
if op != '==':
|
|
# tuple comparison rules - early elements take precedence
|
|
code.add_code_line(" if self.%s %s other_cast.%s: return True" % (
|
|
name, op_without_equals, name))
|
|
code.add_code_line(" if self.%s != other_cast.%s: return False" % (
|
|
name, name))
|
|
if "=" in op:
|
|
code.add_code_line(" return True") # "() == ()" is True
|
|
else:
|
|
code.add_code_line(" return False")
|
|
|
|
|
|
def generate_eq_code(code, eq, node, fields):
|
|
if not eq:
|
|
return
|
|
generate_cmp_code(code, "==", "__eq__", node, fields)
|
|
|
|
|
|
def generate_order_code(code, order, node, fields):
|
|
if not order:
|
|
return
|
|
|
|
for op, name in [("<", "__lt__"),
|
|
("<=", "__le__"),
|
|
(">", "__gt__"),
|
|
(">=", "__ge__")]:
|
|
generate_cmp_code(code, op, name, node, fields)
|
|
|
|
|
|
def generate_hash_code(code, unsafe_hash, eq, frozen, node, fields):
|
|
"""
|
|
Copied from CPython implementation - the intention is to follow this as far as
|
|
is possible:
|
|
# +------------------- unsafe_hash= parameter
|
|
# | +----------- eq= parameter
|
|
# | | +--- frozen= parameter
|
|
# | | |
|
|
# v v v | | |
|
|
# | no | yes | <--- class has explicitly defined __hash__
|
|
# +=======+=======+=======+========+========+
|
|
# | False | False | False | | | No __eq__, use the base class __hash__
|
|
# +-------+-------+-------+--------+--------+
|
|
# | False | False | True | | | No __eq__, use the base class __hash__
|
|
# +-------+-------+-------+--------+--------+
|
|
# | False | True | False | None | | <-- the default, not hashable
|
|
# +-------+-------+-------+--------+--------+
|
|
# | False | True | True | add | | Frozen, so hashable, allows override
|
|
# +-------+-------+-------+--------+--------+
|
|
# | True | False | False | add | raise | Has no __eq__, but hashable
|
|
# +-------+-------+-------+--------+--------+
|
|
# | True | False | True | add | raise | Has no __eq__, but hashable
|
|
# +-------+-------+-------+--------+--------+
|
|
# | True | True | False | add | raise | Not frozen, but hashable
|
|
# +-------+-------+-------+--------+--------+
|
|
# | True | True | True | add | raise | Frozen, so hashable
|
|
# +=======+=======+=======+========+========+
|
|
# For boxes that are blank, __hash__ is untouched and therefore
|
|
# inherited from the base class. If the base is object, then
|
|
# id-based hashing is used.
|
|
|
|
The Python implementation creates a tuple of all the fields, then hashes them.
|
|
This implementation creates a tuple of all the hashes of all the fields and hashes that.
|
|
The reason for this slight difference is to avoid to-Python conversions for anything
|
|
that Cython knows how to hash directly (It doesn't look like this currently applies to
|
|
anything though...).
|
|
"""
|
|
|
|
hash_entry = node.scope.lookup_here("__hash__")
|
|
if hash_entry:
|
|
# TODO ideally assignment of __hash__ to None shouldn't trigger this
|
|
# but difficult to get the right information here
|
|
if unsafe_hash:
|
|
# error message taken from CPython dataclasses module
|
|
error(node.pos, "Cannot overwrite attribute __hash__ in class %s" % node.class_name)
|
|
return
|
|
|
|
if not unsafe_hash:
|
|
if not eq:
|
|
return
|
|
if not frozen:
|
|
code.add_extra_statements([
|
|
Nodes.SingleAssignmentNode(
|
|
node.pos,
|
|
lhs=ExprNodes.NameNode(node.pos, name=EncodedString("__hash__")),
|
|
rhs=ExprNodes.NoneNode(node.pos),
|
|
)
|
|
])
|
|
return
|
|
|
|
names = [
|
|
name for name, field in fields.items()
|
|
if not field.is_initvar and (
|
|
field.compare.value if field.hash.value is None else field.hash.value)
|
|
]
|
|
|
|
# make a tuple of the hashes
|
|
hash_tuple_items = u", ".join(u"self.%s" % name for name in names)
|
|
if hash_tuple_items:
|
|
hash_tuple_items += u"," # ensure that one arg form is a tuple
|
|
|
|
# if we're here we want to generate a hash
|
|
code.add_code_lines([
|
|
"def __hash__(self):",
|
|
" return hash((%s))" % hash_tuple_items,
|
|
])
|
|
|
|
|
|
def get_field_type(pos, entry):
|
|
"""
|
|
sets the .type attribute for a field
|
|
|
|
Returns the annotation if possible (since this is what the dataclasses
|
|
module does). If not (for example, attributes defined with cdef) then
|
|
it creates a string fallback.
|
|
"""
|
|
if entry.annotation:
|
|
# Right now it doesn't look like cdef classes generate an
|
|
# __annotations__ dict, therefore it's safe to just return
|
|
# entry.annotation
|
|
# (TODO: remove .string if we ditch PEP563)
|
|
return entry.annotation.string
|
|
# If they do in future then we may need to look up into that
|
|
# to duplicating the node. The code below should do this:
|
|
#class_name_node = ExprNodes.NameNode(pos, name=entry.scope.name)
|
|
#annotations = ExprNodes.AttributeNode(
|
|
# pos, obj=class_name_node,
|
|
# attribute=EncodedString("__annotations__")
|
|
#)
|
|
#return ExprNodes.IndexNode(
|
|
# pos, base=annotations,
|
|
# index=ExprNodes.StringNode(pos, value=entry.name)
|
|
#)
|
|
else:
|
|
# it's slightly unclear what the best option is here - we could
|
|
# try to return PyType_Type. This case should only happen with
|
|
# attributes defined with cdef so Cython is free to make it's own
|
|
# decision
|
|
s = EncodedString(entry.type.declaration_code("", for_display=1))
|
|
return ExprNodes.StringNode(pos, value=s)
|
|
|
|
|
|
class FieldRecordNode(ExprNodes.ExprNode):
|
|
"""
|
|
__dataclass_fields__ contains a bunch of field objects recording how each field
|
|
of the dataclass was initialized (mainly corresponding to the arguments passed to
|
|
the "field" function). This node is used for the attributes of these field objects.
|
|
|
|
If possible, coerces `arg` to a Python object.
|
|
Otherwise, generates a sensible backup string.
|
|
"""
|
|
subexprs = ['arg']
|
|
|
|
def __init__(self, pos, arg):
|
|
super(FieldRecordNode, self).__init__(pos, arg=arg)
|
|
|
|
def analyse_types(self, env):
|
|
self.arg.analyse_types(env)
|
|
self.type = self.arg.type
|
|
return self
|
|
|
|
def coerce_to_pyobject(self, env):
|
|
if self.arg.type.can_coerce_to_pyobject(env):
|
|
return self.arg.coerce_to_pyobject(env)
|
|
else:
|
|
# A string representation of the code that gave the field seems like a reasonable
|
|
# fallback. This'll mostly happen for "default" and "default_factory" where the
|
|
# type may be a C-type that can't be converted to Python.
|
|
return self._make_string()
|
|
|
|
def _make_string(self):
|
|
from .AutoDocTransforms import AnnotationWriter
|
|
writer = AnnotationWriter(description="Dataclass field")
|
|
string = writer.write(self.arg)
|
|
return ExprNodes.StringNode(self.pos, value=EncodedString(string))
|
|
|
|
def generate_evaluation_code(self, code):
|
|
return self.arg.generate_evaluation_code(code)
|
|
|
|
|
|
def _set_up_dataclass_fields(node, fields, dataclass_module):
|
|
# For defaults and default_factories containing things like lambda,
|
|
# they're already declared in the class scope, and it creates a big
|
|
# problem if multiple copies are floating around in both the __init__
|
|
# function, and in the __dataclass_fields__ structure.
|
|
# Therefore, create module-level constants holding these values and
|
|
# pass those around instead
|
|
#
|
|
# If possible we use the `Field` class defined in the standard library
|
|
# module so that the information stored here is as close to a regular
|
|
# dataclass as is possible.
|
|
variables_assignment_stats = []
|
|
for name, field in fields.items():
|
|
if field.private:
|
|
continue # doesn't appear in the public interface
|
|
for attrname in [ "default", "default_factory" ]:
|
|
field_default = getattr(field, attrname)
|
|
if field_default is MISSING or field_default.is_literal or field_default.is_name:
|
|
# some simple cases where we don't need to set up
|
|
# the variable as a module-level constant
|
|
continue
|
|
global_scope = node.scope.global_scope()
|
|
module_field_name = global_scope.mangle(
|
|
global_scope.mangle(Naming.dataclass_field_default_cname, node.class_name),
|
|
name)
|
|
# create an entry in the global scope for this variable to live
|
|
field_node = ExprNodes.NameNode(field_default.pos, name=EncodedString(module_field_name))
|
|
field_node.entry = global_scope.declare_var(
|
|
field_node.name, type=field_default.type or PyrexTypes.unspecified_type,
|
|
pos=field_default.pos, cname=field_node.name, is_cdef=True,
|
|
# TODO: do we need to set 'pytyping_modifiers' here?
|
|
)
|
|
# replace the field so that future users just receive the namenode
|
|
setattr(field, attrname, field_node)
|
|
|
|
variables_assignment_stats.append(
|
|
Nodes.SingleAssignmentNode(field_default.pos, lhs=field_node, rhs=field_default))
|
|
|
|
placeholders = {}
|
|
field_func = ExprNodes.AttributeNode(node.pos, obj=dataclass_module,
|
|
attribute=EncodedString("field"))
|
|
dc_fields = ExprNodes.DictNode(node.pos, key_value_pairs=[])
|
|
dc_fields_namevalue_assignments = []
|
|
|
|
for name, field in fields.items():
|
|
if field.private:
|
|
continue # doesn't appear in the public interface
|
|
type_placeholder_name = "PLACEHOLDER_%s" % name
|
|
placeholders[type_placeholder_name] = get_field_type(
|
|
node.pos, node.scope.entries[name]
|
|
)
|
|
|
|
# defining these make the fields introspect more like a Python dataclass
|
|
field_type_placeholder_name = "PLACEHOLDER_FIELD_TYPE_%s" % name
|
|
if field.is_initvar:
|
|
placeholders[field_type_placeholder_name] = ExprNodes.AttributeNode(
|
|
node.pos, obj=dataclass_module,
|
|
attribute=EncodedString("_FIELD_INITVAR")
|
|
)
|
|
elif field.is_classvar:
|
|
# TODO - currently this isn't triggered
|
|
placeholders[field_type_placeholder_name] = ExprNodes.AttributeNode(
|
|
node.pos, obj=dataclass_module,
|
|
attribute=EncodedString("_FIELD_CLASSVAR")
|
|
)
|
|
else:
|
|
placeholders[field_type_placeholder_name] = ExprNodes.AttributeNode(
|
|
node.pos, obj=dataclass_module,
|
|
attribute=EncodedString("_FIELD")
|
|
)
|
|
|
|
dc_field_keywords = ExprNodes.DictNode.from_pairs(
|
|
node.pos,
|
|
[(ExprNodes.IdentifierStringNode(node.pos, value=EncodedString(k)),
|
|
FieldRecordNode(node.pos, arg=v))
|
|
for k, v in field.iterate_record_node_arguments()]
|
|
|
|
)
|
|
dc_field_call = make_dataclass_call_helper(
|
|
node.pos, field_func, dc_field_keywords
|
|
)
|
|
dc_fields.key_value_pairs.append(
|
|
ExprNodes.DictItemNode(
|
|
node.pos,
|
|
key=ExprNodes.IdentifierStringNode(node.pos, value=EncodedString(name)),
|
|
value=dc_field_call))
|
|
dc_fields_namevalue_assignments.append(
|
|
dedent(u"""\
|
|
__dataclass_fields__[{0!r}].name = {0!r}
|
|
__dataclass_fields__[{0!r}].type = {1}
|
|
__dataclass_fields__[{0!r}]._field_type = {2}
|
|
""").format(name, type_placeholder_name, field_type_placeholder_name))
|
|
|
|
dataclass_fields_assignment = \
|
|
Nodes.SingleAssignmentNode(node.pos,
|
|
lhs = ExprNodes.NameNode(node.pos,
|
|
name=EncodedString("__dataclass_fields__")),
|
|
rhs = dc_fields)
|
|
|
|
dc_fields_namevalue_assignments = u"\n".join(dc_fields_namevalue_assignments)
|
|
dc_fields_namevalue_assignments = TreeFragment(dc_fields_namevalue_assignments,
|
|
level="c_class",
|
|
pipeline=[NormalizeTree(None)])
|
|
dc_fields_namevalue_assignments = dc_fields_namevalue_assignments.substitute(placeholders)
|
|
|
|
return (variables_assignment_stats
|
|
+ [dataclass_fields_assignment]
|
|
+ dc_fields_namevalue_assignments.stats)
|