from __future__ import annotations

from typing import Callable, Sequence

import mypy.subtypes
from mypy.erasetype import erase_typevars
from mypy.expandtype import expand_type
from mypy.nodes import Context
from mypy.types import (
    AnyType,
    CallableType,
    ParamSpecType,
    PartialType,
    Type,
    TypeVarId,
    TypeVarLikeType,
    TypeVarTupleType,
    TypeVarType,
    UninhabitedType,
    UnpackType,
    get_proper_type,
)


def get_target_type(
    tvar: TypeVarLikeType,
    type: Type,
    callable: CallableType,
    report_incompatible_typevar_value: Callable[[CallableType, Type, str, Context], None],
    context: Context,
    skip_unsatisfied: bool,
) -> Type | None:
    p_type = get_proper_type(type)
    if isinstance(p_type, UninhabitedType) and tvar.has_default():
        return tvar.default
    if isinstance(tvar, ParamSpecType):
        return type
    if isinstance(tvar, TypeVarTupleType):
        return type
    assert isinstance(tvar, TypeVarType)
    values = tvar.values
    if values:
        if isinstance(p_type, AnyType):
            return type
        if isinstance(p_type, TypeVarType) and p_type.values:
            # Allow substituting T1 for T if every allowed value of T1
            # is also a legal value of T.
            if all(any(mypy.subtypes.is_same_type(v, v1) for v in values) for v1 in p_type.values):
                return type
        matching = []
        for value in values:
            if mypy.subtypes.is_subtype(type, value):
                matching.append(value)
        if matching:
            best = matching[0]
            # If there are more than one matching value, we select the narrowest
            for match in matching[1:]:
                if mypy.subtypes.is_subtype(match, best):
                    best = match
            return best
        if skip_unsatisfied:
            return None
        report_incompatible_typevar_value(callable, type, tvar.name, context)
    else:
        upper_bound = tvar.upper_bound
        if tvar.name == "Self":
            # Internally constructed Self-types contain class type variables in upper bound,
            # so we need to erase them to avoid false positives. This is safe because we do
            # not support type variables in upper bounds of user defined types.
            upper_bound = erase_typevars(upper_bound)
        if not mypy.subtypes.is_subtype(type, upper_bound):
            if skip_unsatisfied:
                return None
            report_incompatible_typevar_value(callable, type, tvar.name, context)
    return type


def apply_generic_arguments(
    callable: CallableType,
    orig_types: Sequence[Type | None],
    report_incompatible_typevar_value: Callable[[CallableType, Type, str, Context], None],
    context: Context,
    skip_unsatisfied: bool = False,
) -> CallableType:
    """Apply generic type arguments to a callable type.

    For example, applying [int] to 'def [T] (T) -> T' results in
    'def (int) -> int'.

    Note that each type can be None; in this case, it will not be applied.

    If `skip_unsatisfied` is True, then just skip the types that don't satisfy type variable
    bound or constraints, instead of giving an error.
    """
    tvars = callable.variables
    min_arg_count = sum(not tv.has_default() for tv in tvars)
    assert min_arg_count <= len(orig_types) <= len(tvars)
    # Check that inferred type variable values are compatible with allowed
    # values and bounds.  Also, promote subtype values to allowed values.
    # Create a map from type variable id to target type.
    id_to_type: dict[TypeVarId, Type] = {}

    for tvar, type in zip(tvars, orig_types):
        assert not isinstance(type, PartialType), "Internal error: must never apply partial type"
        if type is None:
            continue

        target_type = get_target_type(
            tvar, type, callable, report_incompatible_typevar_value, context, skip_unsatisfied
        )
        if target_type is not None:
            id_to_type[tvar.id] = target_type

    # TODO: validate arg_kinds/arg_names for ParamSpec and TypeVarTuple replacements,
    # not just type variable bounds above.
    param_spec = callable.param_spec()
    if param_spec is not None:
        nt = id_to_type.get(param_spec.id)
        if nt is not None:
            # ParamSpec expansion is special-cased, so we need to always expand callable
            # as a whole, not expanding arguments individually.
            callable = expand_type(callable, id_to_type)
            assert isinstance(callable, CallableType)
            return callable.copy_modified(
                variables=[tv for tv in tvars if tv.id not in id_to_type]
            )

    # Apply arguments to argument types.
    var_arg = callable.var_arg()
    if var_arg is not None and isinstance(var_arg.typ, UnpackType):
        # Same as for ParamSpec, callable with variadic types needs to be expanded as a whole.
        callable = expand_type(callable, id_to_type)
        assert isinstance(callable, CallableType)
        return callable.copy_modified(variables=[tv for tv in tvars if tv.id not in id_to_type])
    else:
        callable = callable.copy_modified(
            arg_types=[expand_type(at, id_to_type) for at in callable.arg_types]
        )

    # Apply arguments to TypeGuard if any.
    if callable.type_guard is not None:
        type_guard = expand_type(callable.type_guard, id_to_type)
    else:
        type_guard = None

    # The callable may retain some type vars if only some were applied.
    # TODO: move apply_poly() logic from checkexpr.py here when new inference
    # becomes universally used (i.e. in all passes + in unification).
    # With this new logic we can actually *add* some new free variables.
    remaining_tvars = [tv for tv in tvars if tv.id not in id_to_type]

    return callable.copy_modified(
        ret_type=expand_type(callable.ret_type, id_to_type),
        variables=remaining_tvars,
        type_guard=type_guard,
    )