"""Plugin system for extending mypy."""

from abc import abstractmethod
from functools import partial
from typing import Callable, List, Tuple, Optional, NamedTuple, TypeVar, Dict
from mypy_extensions import trait

from mypy.nodes import (
    Expression, StrExpr, IntExpr, UnaryExpr, Context, DictExpr, ClassDef,
    TypeInfo, SymbolTableNode, MypyFile
)
from mypy.tvar_scope import TypeVarScope
from mypy.types import (
    Type, Instance, CallableType, TypedDictType, UnionType, NoneTyp, TypeVarType,
    AnyType, TypeList, UnboundType, TypeOfAny
)
from mypy.messages import MessageBuilder
from mypy.options import Options


@trait
class TypeAnalyzerPluginInterface:
    """Interface for accessing semantic analyzer functionality in plugins."""

    @abstractmethod
    def fail(self, msg: str, ctx: Context) -> None:
        raise NotImplementedError

    @abstractmethod
    def named_type(self, name: str, args: List[Type]) -> Instance:
        raise NotImplementedError

    @abstractmethod
    def analyze_type(self, typ: Type) -> Type:
        raise NotImplementedError

    @abstractmethod
    def analyze_callable_args(self, arglist: TypeList) -> Optional[Tuple[List[Type],
                                                                         List[int],
                                                                         List[Optional[str]]]]:
        raise NotImplementedError


# A context for a hook that semantically analyzes an unbound type.
AnalyzeTypeContext = NamedTuple(
    'AnalyzeTypeContext', [
        ('type', UnboundType),  # Type to analyze
        ('context', Context),
        ('api', TypeAnalyzerPluginInterface)])


@trait
class CheckerPluginInterface:
    """Interface for accessing type checker functionality in plugins."""

    msg = None  # type: MessageBuilder

    @abstractmethod
    def named_generic_type(self, name: str, args: List[Type]) -> Instance:
        raise NotImplementedError


@trait
class SemanticAnalyzerPluginInterface:
    """Interface for accessing semantic analyzer functionality in plugins."""

    modules = None  # type: Dict[str, MypyFile]
    options = None  # type: Options
    msg = None  # type: MessageBuilder

    @abstractmethod
    def named_type(self, qualified_name: str, args: Optional[List[Type]] = None) -> Instance:
        raise NotImplementedError

    @abstractmethod
    def parse_bool(self, expr: Expression) -> Optional[bool]:
        raise NotImplementedError

    @abstractmethod
    def fail(self, msg: str, ctx: Context, serious: bool = False, *,
             blocker: bool = False) -> None:
        raise NotImplementedError

    @abstractmethod
    def anal_type(self, t: Type, *,
                  tvar_scope: Optional[TypeVarScope] = None,
                  allow_tuple_literal: bool = False,
                  allow_unbound_tvars: bool = False,
                  third_pass: bool = False) -> Type:
        raise NotImplementedError

    @abstractmethod
    def class_type(self, info: TypeInfo) -> Type:
        raise NotImplementedError

    @abstractmethod
    def builtin_type(self, fully_qualified_name: str) -> Instance:
        raise NotImplementedError

    @abstractmethod
    def lookup_fully_qualified(self, name: str) -> SymbolTableNode:
        raise NotImplementedError

    @abstractmethod
    def lookup_fully_qualified_or_none(self, name: str) -> Optional[SymbolTableNode]:
        raise NotImplementedError

    @abstractmethod
    def lookup_qualified(self, name: str, ctx: Context,
                         suppress_errors: bool = False) -> Optional[SymbolTableNode]:
        raise NotImplementedError


# A context for a function hook that infers the return type of a function with
# a special signature.
#
# A no-op callback would just return the inferred return type, but a useful
# callback at least sometimes can infer a more precise type.
FunctionContext = NamedTuple(
    'FunctionContext', [
        ('arg_types', List[List[Type]]),   # List of actual caller types for each formal argument
        ('default_return_type', Type),     # Return type inferred from signature
        ('args', List[List[Expression]]),  # Actual expressions for each formal argument
        ('context', Context),
        ('api', CheckerPluginInterface)])

# A context for a method signature hook that infers a better signature for a
# method.  Note that argument types aren't available yet.  If you need them,
# you have to use a method hook instead.
MethodSigContext = NamedTuple(
    'MethodSigContext', [
        ('type', Type),                       # Base object type for method call
        ('args', List[List[Expression]]),     # Actual expressions for each formal argument
        ('default_signature', CallableType),  # Original signature of the method
        ('context', Context),
        ('api', CheckerPluginInterface)])

# A context for a method hook that infers the return type of a method with a
# special signature.
#
# This is very similar to FunctionContext (only differences are documented).
MethodContext = NamedTuple(
    'MethodContext', [
        ('type', Type),                    # Base object type for method call
        ('arg_types', List[List[Type]]),
        ('default_return_type', Type),
        ('args', List[List[Expression]]),
        ('context', Context),
        ('api', CheckerPluginInterface)])

# A context for an attribute type hook that infers the type of an attribute.
AttributeContext = NamedTuple(
    'AttributeContext', [
        ('type', Type),                # Type of object with attribute
        ('default_attr_type', Type),  # Original attribute type
        ('context', Context),
        ('api', CheckerPluginInterface)])

# A context for a class hook that modifies the class definition.
ClassDefContext = NamedTuple(
    'ClassDecoratorContext', [
        ('cls', ClassDef),       # The class definition
        ('reason', Expression),  # The expression being applied (decorator, metaclass, base class)
        ('api', SemanticAnalyzerPluginInterface)
    ])


class Plugin:
    """Base class of all type checker plugins.

    This defines a no-op plugin.  Subclasses can override some methods to
    provide some actual functionality.

    All get_ methods are treated as pure functions (you should assume that
    results might be cached).

    Look at the comments of various *Context objects for descriptions of
    various hooks.
    """

    def __init__(self, options: Options) -> None:
        self.options = options
        self.python_version = options.python_version

    def get_type_analyze_hook(self, fullname: str
                              ) -> Optional[Callable[[AnalyzeTypeContext], Type]]:
        return None

    def get_function_hook(self, fullname: str
                          ) -> Optional[Callable[[FunctionContext], Type]]:
        return None

    def get_method_signature_hook(self, fullname: str
                                  ) -> Optional[Callable[[MethodSigContext], CallableType]]:
        return None

    def get_method_hook(self, fullname: str
                        ) -> Optional[Callable[[MethodContext], Type]]:
        return None

    def get_attribute_hook(self, fullname: str
                           ) -> Optional[Callable[[AttributeContext], Type]]:
        return None

    def get_class_decorator_hook(self, fullname: str
                                 ) -> Optional[Callable[[ClassDefContext], None]]:
        return None

    def get_metaclass_hook(self, fullname: str
                           ) -> Optional[Callable[[ClassDefContext], None]]:
        return None

    def get_base_class_hook(self, fullname: str
                            ) -> Optional[Callable[[ClassDefContext], None]]:
        return None

    def get_customize_class_mro_hook(self, fullname: str
                                     ) -> Optional[Callable[[ClassDefContext], None]]:
        return None


T = TypeVar('T')


class ChainedPlugin(Plugin):
    """A plugin that represents a sequence of chained plugins.

    Each lookup method returns the hook for the first plugin that
    reports a match.

    This class should not be subclassed -- use Plugin as the base class
    for all plugins.
    """

    # TODO: Support caching of lookup results (through a LRU cache, for example).

    def __init__(self, options: Options, plugins: List[Plugin]) -> None:
        """Initialize chained plugin.

        Assume that the child plugins aren't mutated (results may be cached).
        """
        super().__init__(options)
        self._plugins = plugins

    def get_type_analyze_hook(self, fullname: str
                              ) -> Optional[Callable[[AnalyzeTypeContext], Type]]:
        return self._find_hook(lambda plugin: plugin.get_type_analyze_hook(fullname))

    def get_function_hook(self, fullname: str
                          ) -> Optional[Callable[[FunctionContext], Type]]:
        return self._find_hook(lambda plugin: plugin.get_function_hook(fullname))

    def get_method_signature_hook(self, fullname: str
                                  ) -> Optional[Callable[[MethodSigContext], CallableType]]:
        return self._find_hook(lambda plugin: plugin.get_method_signature_hook(fullname))

    def get_method_hook(self, fullname: str
                        ) -> Optional[Callable[[MethodContext], Type]]:
        return self._find_hook(lambda plugin: plugin.get_method_hook(fullname))

    def get_attribute_hook(self, fullname: str
                           ) -> Optional[Callable[[AttributeContext], Type]]:
        return self._find_hook(lambda plugin: plugin.get_attribute_hook(fullname))

    def get_class_decorator_hook(self, fullname: str
                                 ) -> Optional[Callable[[ClassDefContext], None]]:
        return self._find_hook(lambda plugin: plugin.get_class_decorator_hook(fullname))

    def get_metaclass_hook(self, fullname: str
                           ) -> Optional[Callable[[ClassDefContext], None]]:
        return self._find_hook(lambda plugin: plugin.get_metaclass_hook(fullname))

    def get_base_class_hook(self, fullname: str
                            ) -> Optional[Callable[[ClassDefContext], None]]:
        return self._find_hook(lambda plugin: plugin.get_base_class_hook(fullname))

    def get_customize_class_mro_hook(self, fullname: str
                                     ) -> Optional[Callable[[ClassDefContext], None]]:
        return self._find_hook(lambda plugin: plugin.get_customize_class_mro_hook(fullname))

    def _find_hook(self, lookup: Callable[[Plugin], T]) -> Optional[T]:
        for plugin in self._plugins:
            hook = lookup(plugin)
            if hook:
                return hook
        return None


class DefaultPlugin(Plugin):
    """Type checker plugin that is enabled by default."""

    def get_function_hook(self, fullname: str
                          ) -> Optional[Callable[[FunctionContext], Type]]:
        if fullname == 'contextlib.contextmanager':
            return contextmanager_callback
        elif fullname == 'builtins.open' and self.python_version[0] == 3:
            return open_callback
        return None

    def get_method_signature_hook(self, fullname: str
                                  ) -> Optional[Callable[[MethodSigContext], CallableType]]:
        if fullname == 'typing.Mapping.get':
            return typed_dict_get_signature_callback
        return None

    def get_method_hook(self, fullname: str
                        ) -> Optional[Callable[[MethodContext], Type]]:
        if fullname == 'typing.Mapping.get':
            return typed_dict_get_callback
        elif fullname == 'builtins.int.__pow__':
            return int_pow_callback
        return None

    def get_class_decorator_hook(self, fullname: str
                                 ) -> Optional[Callable[[ClassDefContext], None]]:
        from mypy.plugins import attrs
        from mypy.plugins import dataclasses

        if fullname in attrs.attr_class_makers:
            return attrs.attr_class_maker_callback
        elif fullname in attrs.attr_dataclass_makers:
            return partial(
                attrs.attr_class_maker_callback,
                auto_attribs_default=True
            )
        elif fullname in dataclasses.dataclass_makers:
            return dataclasses.dataclass_class_maker_callback
        return None


def open_callback(ctx: FunctionContext) -> Type:
    """Infer a better return type for 'open'.

    Infer TextIO or BinaryIO as the return value if the mode argument is not
    given or is a literal.
    """
    mode = None
    if not ctx.arg_types or len(ctx.arg_types[1]) != 1:
        mode = 'r'
    elif isinstance(ctx.args[1][0], StrExpr):
        mode = ctx.args[1][0].value
    if mode is not None:
        assert isinstance(ctx.default_return_type, Instance)
        if 'b' in mode:
            return ctx.api.named_generic_type('typing.BinaryIO', [])
        else:
            return ctx.api.named_generic_type('typing.TextIO', [])
    return ctx.default_return_type


def contextmanager_callback(ctx: FunctionContext) -> Type:
    """Infer a better return type for 'contextlib.contextmanager'."""
    # Be defensive, just in case.
    if ctx.arg_types and len(ctx.arg_types[0]) == 1:
        arg_type = ctx.arg_types[0][0]
        if (isinstance(arg_type, CallableType)
                and isinstance(ctx.default_return_type, CallableType)):
            # The stub signature doesn't preserve information about arguments so
            # add them back here.
            return ctx.default_return_type.copy_modified(
                arg_types=arg_type.arg_types,
                arg_kinds=arg_type.arg_kinds,
                arg_names=arg_type.arg_names,
                variables=arg_type.variables,
                is_ellipsis_args=arg_type.is_ellipsis_args)
    return ctx.default_return_type


def typed_dict_get_signature_callback(ctx: MethodSigContext) -> CallableType:
    """Try to infer a better signature type for TypedDict.get.

    This is used to get better type context for the second argument that
    depends on a TypedDict value type.
    """
    signature = ctx.default_signature
    if (isinstance(ctx.type, TypedDictType)
            and len(ctx.args) == 2
            and len(ctx.args[0]) == 1
            and isinstance(ctx.args[0][0], StrExpr)
            and len(signature.arg_types) == 2
            and len(signature.variables) == 1
            and len(ctx.args[1]) == 1):
        key = ctx.args[0][0].value
        value_type = ctx.type.items.get(key)
        ret_type = signature.ret_type
        if value_type:
            default_arg = ctx.args[1][0]
            if (isinstance(value_type, TypedDictType)
                    and isinstance(default_arg, DictExpr)
                    and len(default_arg.items) == 0):
                # Caller has empty dict {} as default for typed dict.
                value_type = value_type.copy_modified(required_keys=set())
            # Tweak the signature to include the value type as context. It's
            # only needed for type inference since there's a union with a type
            # variable that accepts everything.
            tv = TypeVarType(signature.variables[0])
            return signature.copy_modified(
                arg_types=[signature.arg_types[0],
                           UnionType.make_simplified_union([value_type, tv])],
                ret_type=ret_type)
    return signature


def typed_dict_get_callback(ctx: MethodContext) -> Type:
    """Infer a precise return type for TypedDict.get with literal first argument."""
    if (isinstance(ctx.type, TypedDictType)
            and len(ctx.arg_types) >= 1
            and len(ctx.arg_types[0]) == 1):
        if isinstance(ctx.args[0][0], StrExpr):
            key = ctx.args[0][0].value
            value_type = ctx.type.items.get(key)
            if value_type:
                if len(ctx.arg_types) == 1:
                    return UnionType.make_simplified_union([value_type, NoneTyp()])
                elif (len(ctx.arg_types) == 2 and len(ctx.arg_types[1]) == 1
                      and len(ctx.args[1]) == 1):
                    default_arg = ctx.args[1][0]
                    if (isinstance(default_arg, DictExpr) and len(default_arg.items) == 0
                            and isinstance(value_type, TypedDictType)):
                        # Special case '{}' as the default for a typed dict type.
                        return value_type.copy_modified(required_keys=set())
                    else:
                        return UnionType.make_simplified_union([value_type, ctx.arg_types[1][0]])
            else:
                ctx.api.msg.typeddict_key_not_found(ctx.type, key, ctx.context)
                return AnyType(TypeOfAny.from_error)
    return ctx.default_return_type


def int_pow_callback(ctx: MethodContext) -> Type:
    """Infer a more precise return type for int.__pow__."""
    if (len(ctx.arg_types) == 1
            and len(ctx.arg_types[0]) == 1):
        arg = ctx.args[0][0]
        if isinstance(arg, IntExpr):
            exponent = arg.value
        elif isinstance(arg, UnaryExpr) and arg.op == '-' and isinstance(arg.expr, IntExpr):
            exponent = -arg.expr.value
        else:
            # Right operand not an int literal or a negated literal -- give up.
            return ctx.default_return_type
        if exponent >= 0:
            return ctx.api.named_generic_type('builtins.int', [])
        else:
            return ctx.api.named_generic_type('builtins.float', [])
    return ctx.default_return_type
