reflex_copy/reflex/vars.py

"""Define a state var."""

from __future__ import annotations

import contextlib
import dataclasses
import datetime
import dis
import functools
import inspect
import json
import random
import re
import string
import sys
from types import CodeType, FunctionType
from typing import (
    TYPE_CHECKING,
    Any,
    Callable,
    Dict,
    Iterable,
    List,
    Literal,
    Optional,
    Tuple,
    Type,
    Union,
    _GenericAlias,  # type: ignore
    cast,
    get_args,
    get_origin,
    get_type_hints,
)

from reflex import constants
from reflex.base import Base
from reflex.utils import console, imports, serializers, types
from reflex.utils.exceptions import VarAttributeError, VarTypeError, VarValueError

# This module used to export ImportVar itself, so we still import it for export here
from reflex.utils.imports import (
    ImportDict,
    ImportVar,
    ParsedImportDict,
    parse_imports,
)
from reflex.utils.types import override

if TYPE_CHECKING:
    from reflex.state import BaseState


# Set of unique variable names.
USED_VARIABLES = set()

# Supported operators for all types.
ALL_OPS = ["==", "!=", "!==", "===", "&&", "||"]
# Delimiters used between function args or operands.
DELIMITERS = [","]
# Mapping of valid operations for different type combinations.
OPERATION_MAPPING = {
    (int, int): {
        "+",
        "-",
        "/",
        "//",
        "*",
        "%",
        "**",
        ">",
        "<",
        "<=",
        ">=",
        "|",
        "&",
    },
    (int, str): {"*"},
    (int, list): {"*"},
    (str, str): {"+", ">", "<", "<=", ">="},
    (float, float): {"+", "-", "/", "//", "*", "%", "**", ">", "<", "<=", ">="},
    (float, int): {"+", "-", "/", "//", "*", "%", "**", ">", "<", "<=", ">="},
    (list, list): {"+", ">", "<", "<=", ">="},
}

# These names were changed in reflex 0.3.0
REPLACED_NAMES = {
    "full_name": "_var_full_name",
    "name": "_var_name",
    "state": "_var_data.state",
    "type_": "_var_type",
    "is_local": "_var_is_local",
    "is_string": "_var_is_string",
    "set_state": "_var_set_state",
    "deps": "_deps",
}

PYTHON_JS_TYPE_MAP = {
    (int, float): "number",
    (str,): "string",
    (bool,): "boolean",
    (list, tuple): "Array",
    (dict,): "Object",
    (None,): "null",
}


def get_unique_variable_name() -> str:
    """Get a unique variable name.

    Returns:
        The unique variable name.
    """
    name = "".join([random.choice(string.ascii_lowercase) for _ in range(8)])
    if name not in USED_VARIABLES:
        USED_VARIABLES.add(name)
        return name
    return get_unique_variable_name()


class VarData(Base):
    """Metadata associated with a Var."""

    # The name of the enclosing state.
    state: str = ""

    # Imports needed to render this var
    imports: ParsedImportDict = {}

    # Hooks that need to be present in the component to render this var
    hooks: Dict[str, None] = {}

    # Positions of interpolated strings. This is used by the decoder to figure
    # out where the interpolations are and only escape the non-interpolated
    # segments.
    interpolations: List[Tuple[int, int]] = []

    def __init__(
        self, imports: Union[ImportDict, ParsedImportDict] | None = None, **kwargs: Any
    ):
        """Initialize the var data.

        Args:
            imports: The imports needed to render this var.
            **kwargs: The var data fields.
        """
        if imports:
            kwargs["imports"] = parse_imports(imports)
        super().__init__(**kwargs)

    @classmethod
    def merge(cls, *others: VarData | None) -> VarData | None:
        """Merge multiple var data objects.

        Args:
            *others: The var data objects to merge.

        Returns:
            The merged var data object.
        """
        state = ""
        _imports = {}
        hooks = {}
        interpolations = []
        for var_data in others:
            if var_data is None:
                continue
            state = state or var_data.state
            _imports = imports.merge_imports(_imports, var_data.imports)
            hooks.update(var_data.hooks)
            interpolations += var_data.interpolations

        return (
            cls(
                state=state,
                imports=_imports,
                hooks=hooks,
                interpolations=interpolations,
            )
            or None
        )

    def __bool__(self) -> bool:
        """Check if the var data is non-empty.

        Returns:
            True if any field is set to a non-default value.
        """
        return bool(self.state or self.imports or self.hooks or self.interpolations)

    def __eq__(self, other: Any) -> bool:
        """Check if two var data objects are equal.

        Args:
            other: The other var data object to compare.

        Returns:
            True if all fields are equal and collapsed imports are equal.
        """
        if not isinstance(other, VarData):
            return False

        # Don't compare interpolations - that's added in by the decoder, and
        # not part of the vardata itself.
        return (
            self.state == other.state
            and self.hooks.keys() == other.hooks.keys()
            and imports.collapse_imports(self.imports)
            == imports.collapse_imports(other.imports)
        )

    def dict(self) -> dict:
        """Convert the var data to a dictionary.

        Returns:
            The var data dictionary.
        """
        return {
            "state": self.state,
            "interpolations": list(self.interpolations),
            "imports": {
                lib: [import_var.dict() for import_var in import_vars]
                for lib, import_vars in self.imports.items()
            },
            "hooks": self.hooks,
        }


def _encode_var(value: Var) -> str:
    """Encode the state name into a formatted var.

    Args:
        value: The value to encode the state name into.

    Returns:
        The encoded var.
    """
    if value._var_data:
        from reflex.utils.serializers import serialize

        final_value = str(value)
        data = value._var_data.dict()
        data["string_length"] = len(final_value)
        data_json = value._var_data.__config__.json_dumps(data, default=serialize)

        return (
            f"{constants.REFLEX_VAR_OPENING_TAG}{data_json}{constants.REFLEX_VAR_CLOSING_TAG}"
            + final_value
        )

    return str(value)


# Compile regex for finding reflex var tags.
_decode_var_pattern_re = (
    rf"{constants.REFLEX_VAR_OPENING_TAG}(.*?){constants.REFLEX_VAR_CLOSING_TAG}"
)
_decode_var_pattern = re.compile(_decode_var_pattern_re, flags=re.DOTALL)


def _decode_var(value: str) -> tuple[VarData | None, str]:
    """Decode the state name from a formatted var.

    Args:
        value: The value to extract the state name from.

    Returns:
        The extracted state name and the value without the state name.
    """
    var_datas = []
    if isinstance(value, str):
        # fast path if there is no encoded VarData
        if constants.REFLEX_VAR_OPENING_TAG not in value:
            return None, value

        offset = 0

        # Initialize some methods for reading json.
        var_data_config = VarData().__config__

        def json_loads(s):
            try:
                return var_data_config.json_loads(s)
            except json.decoder.JSONDecodeError:
                return var_data_config.json_loads(var_data_config.json_loads(f'"{s}"'))

        # Find all tags.
        while m := _decode_var_pattern.search(value):
            start, end = m.span()
            value = value[:start] + value[end:]

            # Read the JSON, pull out the string length, parse the rest as VarData.
            data = json_loads(m.group(1))
            string_length = data.pop("string_length", None)
            var_data = VarData.parse_obj(data)

            # Use string length to compute positions of interpolations.
            if string_length is not None:
                realstart = start + offset
                var_data.interpolations = [(realstart, realstart + string_length)]

            var_datas.append(var_data)
            offset += end - start

    return VarData.merge(*var_datas) if var_datas else None, value


def _extract_var_data(value: Iterable) -> list[VarData | None]:
    """Extract the var imports and hooks from an iterable containing a Var.

    Args:
        value: The iterable to extract the VarData from

    Returns:
        The extracted VarDatas.
    """
    from reflex.style import Style

    var_datas = []
    with contextlib.suppress(TypeError):
        for sub in value:
            if isinstance(sub, Var):
                var_datas.append(sub._var_data)
            elif not isinstance(sub, str):
                # Recurse into dict values.
                if hasattr(sub, "values") and callable(sub.values):
                    var_datas.extend(_extract_var_data(sub.values()))
                # Recurse into iterable values (or dict keys).
                var_datas.extend(_extract_var_data(sub))

    # Style objects should already have _var_data.
    if isinstance(value, Style):
        var_datas.append(value._var_data)
    else:
        # Recurse when value is a dict itself.
        values = getattr(value, "values", None)
        if callable(values):
            var_datas.extend(_extract_var_data(values()))
    return var_datas


class Var:
    """An abstract var."""

    # The name of the var.
    _var_name: str

    # The type of the var.
    _var_type: Type

    # Whether this is a local javascript variable.
    _var_is_local: bool

    # Whether the var is a string literal.
    _var_is_string: bool

    # _var_full_name should be prefixed with _var_state
    _var_full_name_needs_state_prefix: bool

    # Extra metadata associated with the Var
    _var_data: Optional[VarData]

    @classmethod
    def create(
        cls,
        value: Any,
        _var_is_local: bool = True,
        _var_is_string: bool | None = None,
        _var_data: Optional[VarData] = None,
    ) -> Var | None:
        """Create a var from a value.

        Args:
            value: The value to create the var from.
            _var_is_local: Whether the var is local.
            _var_is_string: Whether the var is a string literal.
            _var_data: Additional hooks and imports associated with the Var.

        Returns:
            The var.

        Raises:
            VarTypeError: If the value is JSON-unserializable.
        """
        from reflex.utils import format

        # Check for none values.
        if value is None:
            return None

        # If the value is already a var, do nothing.
        if isinstance(value, Var):
            return value

        # Try to pull the imports and hooks from contained values.
        if not isinstance(value, str):
            _var_data = VarData.merge(*_extract_var_data(value), _var_data)

        # Try to serialize the value.
        type_ = type(value)
        if type_ in types.JSONType:
            name = value
        else:
            name, serialized_type = serializers.serialize(value, get_type=True)
            if (
                serialized_type is not None
                and _var_is_string is None
                and issubclass(serialized_type, str)
            ):
                _var_is_string = True
        if name is None:
            raise VarTypeError(
                f"No JSON serializer found for var {value} of type {type_}."
            )
        name = name if isinstance(name, str) else format.json_dumps(name)

        if _var_is_string is None and type_ is str:
            console.deprecate(
                feature_name="Creating a Var from a string without specifying _var_is_string",
                reason=(
                    "Specify _var_is_string=False to create a Var that is not a string literal. "
                    "In the future, creating a Var from a string will be treated as a string literal "
                    "by default."
                ),
                deprecation_version="0.5.4",
                removal_version="0.6.0",
            )

        return BaseVar(
            _var_name=name,
            _var_type=type_,
            _var_is_local=_var_is_local,
            _var_is_string=_var_is_string if _var_is_string is not None else False,
            _var_data=_var_data,
        )

    @classmethod
    def create_safe(
        cls,
        value: Any,
        _var_is_local: bool = True,
        _var_is_string: bool | None = None,
        _var_data: Optional[VarData] = None,
    ) -> Var:
        """Create a var from a value, asserting that it is not None.

        Args:
            value: The value to create the var from.
            _var_is_local: Whether the var is local.
            _var_is_string: Whether the var is a string literal.
            _var_data: Additional hooks and imports associated with the Var.

        Returns:
            The var.
        """
        var = cls.create(
            value,
            _var_is_local=_var_is_local,
            _var_is_string=_var_is_string,
            _var_data=_var_data,
        )
        assert var is not None
        return var

    @classmethod
    def __class_getitem__(cls, type_: str) -> _GenericAlias:
        """Get a typed var.

        Args:
            type_: The type of the var.

        Returns:
            The var class item.
        """
        return _GenericAlias(cls, type_)

    def __post_init__(self) -> None:
        """Post-initialize the var."""
        # Decode any inline Var markup and apply it to the instance
        _var_data, _var_name = _decode_var(self._var_name)
        if _var_data:
            self._var_name = _var_name
            self._var_data = VarData.merge(self._var_data, _var_data)

    def _replace(self, merge_var_data=None, **kwargs: Any) -> BaseVar:
        """Make a copy of this Var with updated fields.

        Args:
            merge_var_data: VarData to merge into the existing VarData.
            **kwargs: Var fields to update.

        Returns:
            A new BaseVar with the updated fields overwriting the corresponding fields in this Var.
        """
        field_values = dict(
            _var_name=kwargs.pop("_var_name", self._var_name),
            _var_type=kwargs.pop("_var_type", self._var_type),
            _var_is_local=kwargs.pop("_var_is_local", self._var_is_local),
            _var_is_string=kwargs.pop("_var_is_string", self._var_is_string),
            _var_full_name_needs_state_prefix=kwargs.pop(
                "_var_full_name_needs_state_prefix",
                self._var_full_name_needs_state_prefix,
            ),
            _var_data=VarData.merge(
                kwargs.get("_var_data", self._var_data), merge_var_data
            ),
        )
        return BaseVar(**field_values)

    def _decode(self) -> Any:
        """Decode Var as a python value.

        Note that Var with state set cannot be decoded python-side and will be
        returned as full_name.

        Returns:
            The decoded value or the Var name.
        """
        if self._var_is_string:
            return self._var_name
        try:
            return json.loads(self._var_name)
        except ValueError:
            return self._var_name

    def equals(self, other: Var) -> bool:
        """Check if two vars are equal.

        Args:
            other: The other var to compare.

        Returns:
            Whether the vars are equal.
        """
        return (
            self._var_name == other._var_name
            and self._var_type == other._var_type
            and self._var_is_local == other._var_is_local
            and self._var_full_name_needs_state_prefix
            == other._var_full_name_needs_state_prefix
            and self._var_data == other._var_data
        )

    def _merge(self, other) -> Var:
        """Merge two or more dicts.

        Args:
            other: The other var to merge.

        Returns:
            The merged var.
        """
        if other is None:
            return self._replace()
        if not isinstance(other, Var):
            other = Var.create(other, _var_is_string=False)
        return self._replace(
            _var_name=f"{{...{self._var_name}, ...{other._var_name}}}"  # type: ignore
        )

    def to_string(self, json: bool = True) -> Var:
        """Convert a var to a string.

        Args:
            json: Whether to convert to a JSON string.

        Returns:
            The stringified var.
        """
        fn = "JSON.stringify" if json else "String"
        return self.operation(fn=fn, type_=str)

    def to_int(self) -> Var:
        """Convert a var to an int.

        Returns:
            The parseInt var.
        """
        return self.operation(fn="parseInt", type_=int)

    def __hash__(self) -> int:
        """Define a hash function for a var.

        Returns:
            The hash of the var.
        """
        return hash((self._var_name, str(self._var_type)))

    def __str__(self) -> str:
        """Wrap the var so it can be used in templates.

        Returns:
            The wrapped var, i.e. {state.var}.
        """
        from reflex.utils import format

        out = (
            self._var_full_name
            if self._var_is_local
            else format.wrap(self._var_full_name, "{")
        )
        if self._var_is_string:
            out = format.format_string(out)
        return out

    def __bool__(self) -> bool:
        """Raise exception if using Var in a boolean context.

        Raises:
            VarTypeError: when attempting to bool-ify the Var.
        """
        raise VarTypeError(
            f"Cannot convert Var {self._var_full_name!r} to bool for use with `if`, `and`, `or`, and `not`. "
            "Instead use `rx.cond` and bitwise operators `&` (and), `|` (or), `~` (invert)."
        )

    def __iter__(self) -> Any:
        """Raise exception if using Var in an iterable context.

        Raises:
            VarTypeError: when attempting to iterate over the Var.
        """
        raise VarTypeError(
            f"Cannot iterate over Var {self._var_full_name!r}. Instead use `rx.foreach`."
        )

    def __format__(self, format_spec: str) -> str:
        """Format the var into a Javascript equivalent to an f-string.

        Args:
            format_spec: The format specifier (Ignored for now).

        Returns:
            The formatted var.
        """
        # Encode the _var_data into the formatted output for tracking purposes.
        str_self = _encode_var(self)
        if self._var_is_local:
            return str_self
        return f"${str_self}"

    def __getitem__(self, i: Any) -> Var:
        """Index into a var.

        Args:
            i: The index to index into.

        Returns:
            The indexed var.

        Raises:
            VarTypeError: If the var is not indexable.
        """
        from reflex.utils import format

        # Indexing is only supported for strings, lists, tuples, dicts, and dataframes.
        if not (
            types._issubclass(self._var_type, Union[List, Dict, Tuple, str])
            or types.is_dataframe(self._var_type)
        ):
            if self._var_type == Any:
                raise VarTypeError(
                    "Could not index into var of type Any. (If you are trying to index into a state var, "
                    "add the correct type annotation to the var.)"
                )
            raise VarTypeError(
                f"Var {self._var_name} of type {self._var_type} does not support indexing."
            )

        # The type of the indexed var.
        type_ = Any

        # Convert any vars to local vars.
        if isinstance(i, Var):
            i = i._replace(_var_is_local=True)

        # Handle list/tuple/str indexing.
        if types._issubclass(self._var_type, Union[List, Tuple, str]):
            # List/Tuple/String indices must be ints, slices, or vars.
            if (
                not isinstance(i, types.get_args(Union[int, slice, Var]))
                or isinstance(i, Var)
                and not i._var_type == int
            ):
                raise VarTypeError("Index must be an integer or an integer var.")

            # Handle slices first.
            if isinstance(i, slice):
                # Get the start and stop indices.
                start = i.start or 0
                stop = i.stop or "undefined"

                # Use the slice function.
                return self._replace(
                    _var_name=f"{self._var_name}.slice({start}, {stop})",
                    _var_is_string=False,
                )

            # Get the type of the indexed var.
            if types.is_generic_alias(self._var_type):
                index = i if not isinstance(i, Var) else 0
                type_ = types.get_args(self._var_type)
                type_ = type_[index % len(type_)] if type_ else Any
            elif types._issubclass(self._var_type, str):
                type_ = str

            # Use `at` to support negative indices.
            return self._replace(
                _var_name=f"{self._var_name}.at({i})",
                _var_type=type_,
                _var_is_string=False,
            )

        # Dictionary / dataframe indexing.
        # Tuples are currently not supported as indexes.
        if (
            (
                types._issubclass(self._var_type, Dict)
                or types.is_dataframe(self._var_type)
            )
            and not isinstance(i, types.get_args(Union[int, str, float, Var]))
        ) or (
            isinstance(i, Var)
            and not types._issubclass(
                i._var_type, types.get_args(Union[int, str, float])
            )
        ):
            raise VarTypeError(
                "Index must be one of the following types: int, str, int or str Var"
            )
        # Get the type of the indexed var.
        if isinstance(i, str):
            i = format.wrap(i, '"')
        type_ = (
            types.get_args(self._var_type)[1]
            if types.is_generic_alias(self._var_type)
            else Any
        )

        # Use normal indexing here.
        return self._replace(
            _var_name=f"{self._var_name}[{i}]",
            _var_type=type_,
            _var_is_string=False,
        )

    def __getattribute__(self, name: str) -> Any:
        """Get a var attribute.

        Args:
            name: The name of the attribute.

        Returns:
            The var attribute.

        Raises:
            VarAttributeError: If the attribute cannot be found, or if __getattr__ fallback should be used.
        """
        try:
            var_attribute = super().__getattribute__(name)
            if (
                not name.startswith("_")
                and name not in Var.__dict__
                and name not in BaseVar.__dict__
            ):
                # Check if the attribute should be accessed through the Var instead of
                # accessing one of the Var operations
                type_ = types.get_attribute_access_type(
                    super().__getattribute__("_var_type"), name
                )
                if type_ is not None:
                    raise VarAttributeError(
                        f"{name} is being accessed through the Var."
                    )
            # Return the attribute as-is.
            return var_attribute
        except VarAttributeError:
            raise  # fall back to __getattr__ anyway

    def __getattr__(self, name: str) -> Var:
        """Get a var attribute.

        Args:
            name: The name of the attribute.

        Returns:
            The var attribute.

        Raises:
            VarAttributeError: If the var is wrongly annotated or can't find attribute.
            VarTypeError: If an annotation to the var isn't provided.
        """
        # Check if the attribute is one of the class fields.
        if not name.startswith("_"):
            if self._var_type == Any:
                raise VarTypeError(
                    f"You must provide an annotation for the state var `{self._var_full_name}`. Annotation cannot be `{self._var_type}`"
                ) from None
            is_optional = types.is_optional(self._var_type)
            type_ = types.get_attribute_access_type(self._var_type, name)

            if type_ is not None:
                return self._replace(
                    _var_name=f"{self._var_name}{'?' if is_optional else ''}.{name}",
                    _var_type=type_,
                    _var_is_string=False,
                )

            if name in REPLACED_NAMES:
                raise VarAttributeError(
                    f"Field {name!r} was renamed to {REPLACED_NAMES[name]!r}"
                )

            raise VarAttributeError(
                f"The State var `{self._var_full_name}` has no attribute '{name}' or may have been annotated "
                f"wrongly."
            )

        raise VarAttributeError(
            f"The State var has no attribute '{name}' or may have been annotated wrongly.",
        )

    def operation(
        self,
        op: str = "",
        other: Var | None = None,
        type_: Type | None = None,
        flip: bool = False,
        fn: str | None = None,
        invoke_fn: bool = False,
    ) -> Var:
        """Perform an operation on a var.

        Args:
            op: The operation to perform.
            other: The other var to perform the operation on.
            type_: The type of the operation result.
            flip: Whether to flip the order of the operation.
            fn: A function to apply to the operation.
            invoke_fn: Whether to invoke the function.

        Returns:
            The operation result.

        Raises:
            VarTypeError: If the operation between two operands is invalid.
            VarValueError: If flip is set to true and value of operand is not provided
        """
        from reflex.utils import format

        if isinstance(other, str):
            other = Var.create(json.dumps(other), _var_is_string=False)
        else:
            other = Var.create(other, _var_is_string=False)

        type_ = type_ or self._var_type

        if other is None and flip:
            raise VarValueError(
                "flip_operands cannot be set to True if the value of 'other' operand is not provided"
            )

        left_operand, right_operand = (other, self) if flip else (self, other)

        def get_operand_full_name(operand):
            # operand vars that are string literals need to be wrapped in back ticks.
            return (
                operand._var_name_unwrapped
                if operand._var_is_string
                and not operand._var_state
                and operand._var_is_local
                else operand._var_full_name
            )

        if other is not None:
            # check if the operation between operands is valid.
            if op and not self.is_valid_operation(
                types.get_base_class(left_operand._var_type),  # type: ignore
                types.get_base_class(right_operand._var_type),  # type: ignore
                op,
            ):
                raise VarTypeError(
                    f"Unsupported Operand type(s) for {op}: `{left_operand._var_full_name}` of type {left_operand._var_type.__name__} and `{right_operand._var_full_name}` of type {right_operand._var_type.__name__}"  # type: ignore
                )

            left_operand_full_name = get_operand_full_name(left_operand)
            right_operand_full_name = get_operand_full_name(right_operand)

            left_operand_full_name = format.wrap(left_operand_full_name, "(")
            right_operand_full_name = format.wrap(right_operand_full_name, "(")

            # apply function to operands
            if fn is not None:
                if invoke_fn:
                    # invoke the function on left operand.
                    operation_name = (
                        f"{left_operand_full_name}.{fn}({right_operand_full_name})"  # type: ignore
                    )
                else:
                    # pass the operands as arguments to the function.
                    operation_name = (
                        f"{left_operand_full_name} {op} {right_operand_full_name}"  # type: ignore
                    )
                    operation_name = f"{fn}({operation_name})"
            else:
                # apply operator to operands (left operand <operator> right_operand)
                operation_name = (
                    f"{left_operand_full_name} {op} {right_operand_full_name}"  # type: ignore
                )
                operation_name = format.wrap(operation_name, "(")
        else:
            # apply operator to left operand (<operator> left_operand)
            operation_name = f"{op}{get_operand_full_name(self)}"
            # apply function to operands
            if fn is not None:
                operation_name = (
                    f"{fn}({operation_name})"
                    if not invoke_fn
                    else f"{get_operand_full_name(self)}.{fn}()"
                )

        return self._replace(
            _var_name=operation_name,
            _var_type=type_,
            _var_is_string=False,
            _var_full_name_needs_state_prefix=False,
            merge_var_data=other._var_data if other is not None else None,
        )

    @staticmethod
    def is_valid_operation(
        operand1_type: Type, operand2_type: Type, operator: str
    ) -> bool:
        """Check if an operation between two operands is valid.

        Args:
            operand1_type: Type of the operand
            operand2_type: Type of the second operand
            operator: The operator.

        Returns:
            Whether operation is valid or not

        """
        if operator in ALL_OPS or operator in DELIMITERS:
            return True

        # bools are subclasses of ints
        pair = tuple(
            sorted(
                [
                    int if operand1_type == bool else operand1_type,
                    int if operand2_type == bool else operand2_type,
                ],
                key=lambda x: x.__name__,
            )
        )
        return pair in OPERATION_MAPPING and operator in OPERATION_MAPPING[pair]

    def compare(self, op: str, other: Var) -> Var:
        """Compare two vars with inequalities.

        Args:
            op: The comparison operator.
            other: The other var to compare with.

        Returns:
            The comparison result.
        """
        return self.operation(op, other, bool)

    def __invert__(self) -> Var:
        """Invert a var.

        Returns:
            The inverted var.
        """
        return self.operation("!", type_=bool)

    def __neg__(self) -> Var:
        """Negate a var.

        Returns:
            The negated var.
        """
        return self.operation(fn="-")

    def __abs__(self) -> Var:
        """Get the absolute value of a var.

        Returns:
            A var with the absolute value.
        """
        return self.operation(fn="Math.abs")

    def length(self) -> Var:
        """Get the length of a list var.

        Returns:
            A var with the absolute value.

        Raises:
            VarTypeError: If the var is not a list.
        """
        if not types._issubclass(self._var_type, List):
            raise VarTypeError(f"Cannot get length of non-list var {self}.")
        return self._replace(
            _var_name=f"{self._var_name}.length",
            _var_type=int,
            _var_is_string=False,
        )

    def _type(self) -> Var:
        """Get the type of the Var in Javascript.

        Returns:
            A var representing the type check.
        """
        return self._replace(
            _var_name=f"typeof {self._var_full_name}",
            _var_type=str,
            _var_is_string=False,
            _var_full_name_needs_state_prefix=False,
        )

    def __eq__(self, other: Union[Var, Type]) -> Var:
        """Perform an equality comparison.

        Args:
            other: The other var to compare with.

        Returns:
            A var representing the equality comparison.
        """
        for python_types, js_type in PYTHON_JS_TYPE_MAP.items():
            if not isinstance(other, Var) and other in python_types:
                return self.compare("===", Var.create(js_type, _var_is_string=True))  # type: ignore
        return self.compare("===", other)

    def __ne__(self, other: Union[Var, Type]) -> Var:
        """Perform an inequality comparison.

        Args:
            other: The other var to compare with.

        Returns:
            A var representing the inequality comparison.
        """
        for python_types, js_type in PYTHON_JS_TYPE_MAP.items():
            if not isinstance(other, Var) and other in python_types:
                return self.compare("!==", Var.create(js_type, _var_is_string=True))  # type: ignore
        return self.compare("!==", other)

    def __gt__(self, other: Var) -> Var:
        """Perform a greater than comparison.

        Args:
            other: The other var to compare with.

        Returns:
            A var representing the greater than comparison.
        """
        return self.compare(">", other)

    def __ge__(self, other: Var) -> Var:
        """Perform a greater than or equal to comparison.

        Args:
            other: The other var to compare with.

        Returns:
            A var representing the greater than or equal to comparison.
        """
        return self.compare(">=", other)

    def __lt__(self, other: Var) -> Var:
        """Perform a less than comparison.

        Args:
            other: The other var to compare with.

        Returns:
            A var representing the less than comparison.
        """
        return self.compare("<", other)

    def __le__(self, other: Var) -> Var:
        """Perform a less than or equal to comparison.

        Args:
            other: The other var to compare with.

        Returns:
            A var representing the less than or equal to comparison.
        """
        return self.compare("<=", other)

    def __add__(self, other: Var, flip=False) -> Var:
        """Add two vars.

        Args:
            other: The other var to add.
            flip: Whether to flip operands.

        Returns:
            A var representing the sum.
        """
        other_type = other._var_type if isinstance(other, Var) else type(other)
        # For list-list addition, javascript concatenates the content of the lists instead of
        # merging the list, and for that reason we use the spread operator available through spreadArraysOrObjects
        # utility function
        if (
            types.get_base_class(self._var_type) == list
            and types.get_base_class(other_type) == list
        ):
            return self.operation(
                ",", other, fn="spreadArraysOrObjects", flip=flip
            )._replace(
                merge_var_data=VarData(
                    imports={
                        f"/{constants.Dirs.STATE_PATH}": [
                            ImportVar(tag="spreadArraysOrObjects")
                        ]
                    },
                ),
            )
        return self.operation("+", other, flip=flip)

    def __radd__(self, other: Var) -> Var:
        """Add two vars.

        Args:
            other: The other var to add.

        Returns:
            A var representing the sum.
        """
        return self.__add__(other=other, flip=True)

    def __sub__(self, other: Var) -> Var:
        """Subtract two vars.

        Args:
            other: The other var to subtract.

        Returns:
            A var representing the difference.
        """
        return self.operation("-", other)

    def __rsub__(self, other: Var) -> Var:
        """Subtract two vars.

        Args:
            other: The other var to subtract.

        Returns:
            A var representing the difference.
        """
        return self.operation("-", other, flip=True)

    def __mul__(self, other: Var, flip=True) -> Var:
        """Multiply two vars.

        Args:
            other: The other var to multiply.
            flip: Whether to flip operands

        Returns:
            A var representing the product.
        """
        other_type = other._var_type if isinstance(other, Var) else type(other)
        # For str-int multiplication, we use the repeat function.
        # i.e "hello" * 2 is equivalent to "hello".repeat(2) in js.
        if (types.get_base_class(self._var_type), types.get_base_class(other_type)) in [
            (int, str),
            (str, int),
        ]:
            return self.operation(other=other, fn="repeat", invoke_fn=True)

        # For list-int multiplication, we use the Array function.
        # i.e ["hello"] * 2 is equivalent to Array(2).fill().map(() => ["hello"]).flat() in js.
        if (types.get_base_class(self._var_type), types.get_base_class(other_type)) in [
            (int, list),
            (list, int),
        ]:
            other_name = other._var_full_name if isinstance(other, Var) else other
            name = f"Array({other_name}).fill().map(() => {self._var_full_name}).flat()"
            return self._replace(
                _var_name=name,
                _var_type=str,
                _var_is_string=False,
                _var_full_name_needs_state_prefix=False,
            )

        return self.operation("*", other)

    def __rmul__(self, other: Var) -> Var:
        """Multiply two vars.

        Args:
            other: The other var to multiply.

        Returns:
            A var representing the product.
        """
        return self.__mul__(other=other, flip=True)

    def __pow__(self, other: Var) -> Var:
        """Raise a var to a power.

        Args:
            other: The power to raise to.

        Returns:
            A var representing the power.
        """
        return self.operation(",", other, fn="Math.pow")

    def __rpow__(self, other: Var) -> Var:
        """Raise a var to a power.

        Args:
            other: The power to raise to.

        Returns:
            A var representing the power.
        """
        return self.operation(",", other, flip=True, fn="Math.pow")

    def __truediv__(self, other: Var) -> Var:
        """Divide two vars.

        Args:
            other: The other var to divide.

        Returns:
            A var representing the quotient.
        """
        return self.operation("/", other)

    def __rtruediv__(self, other: Var) -> Var:
        """Divide two vars.

        Args:
            other: The other var to divide.

        Returns:
            A var representing the quotient.
        """
        return self.operation("/", other, flip=True)

    def __floordiv__(self, other: Var) -> Var:
        """Divide two vars.

        Args:
            other: The other var to divide.

        Returns:
            A var representing the quotient.
        """
        return self.operation("/", other, fn="Math.floor")

    def __mod__(self, other: Var) -> Var:
        """Get the remainder of two vars.

        Args:
            other: The other var to divide.

        Returns:
            A var representing the remainder.
        """
        return self.operation("%", other)

    def __rmod__(self, other: Var) -> Var:
        """Get the remainder of two vars.

        Args:
            other: The other var to divide.

        Returns:
            A var representing the remainder.
        """
        return self.operation("%", other, flip=True)

    def __and__(self, other: Var) -> Var:
        """Perform a logical and.

        Args:
            other: The other var to perform the logical AND with.

        Returns:
            A var representing the logical AND.

        Note:
            This method provides behavior specific to JavaScript, where it returns the JavaScript
            equivalent code (using the '&&' operator) of a logical AND operation.
            In JavaScript, the
            logical OR operator '&&' is used for Boolean logic, and this method emulates that behavior
            by returning the equivalent code as a Var instance.

            In Python, logical AND 'and' operates differently, evaluating expressions immediately, making
            it challenging to override the behavior entirely.
            Therefore, this method leverages the
            bitwise AND '__and__' operator for custom JavaScript-like behavior.

        Example:
        >>> var1 = Var.create(True)
        >>> var2 = Var.create(False)
        >>> js_code = var1 & var2
        >>> print(js_code._var_full_name)
        '(true && false)'
        """
        return self.operation("&&", other, type_=bool)

    def __rand__(self, other: Var) -> Var:
        """Perform a logical and.

        Args:
            other: The other var to perform the logical AND with.

        Returns:
            A var representing the logical AND.

        Note:
            This method provides behavior specific to JavaScript, where it returns the JavaScript
            equivalent code (using the '&&' operator) of a logical AND operation.
            In JavaScript, the
            logical OR operator '&&' is used for Boolean logic, and this method emulates that behavior
            by returning the equivalent code as a Var instance.

            In Python, logical AND 'and' operates differently, evaluating expressions immediately, making
            it challenging to override the behavior entirely.
            Therefore, this method leverages the
            bitwise AND '__rand__' operator for custom JavaScript-like behavior.

        Example:
        >>> var1 = Var.create(True)
        >>> var2 = Var.create(False)
        >>> js_code = var1 & var2
        >>> print(js_code._var_full_name)
        '(false && true)'
        """
        return self.operation("&&", other, type_=bool, flip=True)

    def __or__(self, other: Var) -> Var:
        """Perform a logical or.

        Args:
            other: The other var to perform the logical or with.

        Returns:
            A var representing the logical or.

        Note:
            This method provides behavior specific to JavaScript, where it returns the JavaScript
            equivalent code (using the '||' operator) of a logical OR operation. In JavaScript, the
            logical OR operator '||' is used for Boolean logic, and this method emulates that behavior
            by returning the equivalent code as a Var instance.

            In Python, logical OR 'or' operates differently, evaluating expressions immediately, making
            it challenging to override the behavior entirely. Therefore, this method leverages the
            bitwise OR '__or__' operator for custom JavaScript-like behavior.

        Example:
        >>> var1 = Var.create(True)
        >>> var2 = Var.create(False)
        >>> js_code = var1 | var2
        >>> print(js_code._var_full_name)
        '(true || false)'
        """
        return self.operation("||", other, type_=bool)

    def __ror__(self, other: Var) -> Var:
        """Perform a logical or.

        Args:
            other: The other var to perform the logical or with.

        Returns:
            A var representing the logical or.

        Note:
            This method provides behavior specific to JavaScript, where it returns the JavaScript
            equivalent code (using the '||' operator) of a logical OR operation. In JavaScript, the
            logical OR operator '||' is used for Boolean logic, and this method emulates that behavior
            by returning the equivalent code as a Var instance.

            In Python, logical OR 'or' operates differently, evaluating expressions immediately, making
            it challenging to override the behavior entirely. Therefore, this method leverages the
            bitwise OR '__or__' operator for custom JavaScript-like behavior.

        Example:
        >>> var1 = Var.create(True)
        >>> var2 = Var.create(False)
        >>> js_code = var1 | var2
        >>> print(js_code)
        'false || true'
        """
        return self.operation("||", other, type_=bool, flip=True)

    def __contains__(self, _: Any) -> Var:
        """Override the 'in' operator to alert the user that it is not supported.

        Raises:
            VarTypeError: the operation is not supported
        """
        raise VarTypeError(
            "'in' operator not supported for Var types, use Var.contains() instead."
        )

    def contains(self, other: Any, field: Union[Var, None] = None) -> Var:
        """Check if a var contains the object `other`.

        Args:
            other: The object to check.
            field: Optionally specify a field to check on both object and the other var.

        Raises:
            VarTypeError: If the var is not a valid type: dict, list, tuple or str.

        Returns:
            A var representing the contain check.
        """
        if not (types._issubclass(self._var_type, Union[dict, list, tuple, str, set])):
            raise VarTypeError(
                f"Var {self._var_full_name} of type {self._var_type} does not support contains check."
            )
        method = (
            "hasOwnProperty"
            if types.get_base_class(self._var_type) == dict
            else "includes"
        )
        if isinstance(other, str):
            other = Var.create(json.dumps(other), _var_is_string=True)
        elif not isinstance(other, Var):
            other = Var.create(other, _var_is_string=False)
        if types._issubclass(self._var_type, Dict):
            return self._replace(
                _var_name=f"{self._var_name}.{method}({other._var_full_name})",
                _var_type=bool,
                _var_is_string=False,
                merge_var_data=other._var_data,
            )
        else:  # str, list, tuple
            # For strings, the left operand must be a string.
            if types._issubclass(self._var_type, str) and not types._issubclass(
                other._var_type, str
            ):
                raise VarTypeError(
                    f"'in <string>' requires string as left operand, not {other._var_type}"
                )

            _var_name = None
            if field is None:
                _var_name = f"{self._var_name}.includes({other._var_full_name})"
            else:
                field = Var.create_safe(field, _var_is_string=isinstance(field, str))
                _var_name = f"{self._var_name}.some(e=>e[{field._var_name_unwrapped}]==={other._var_full_name})"

            return self._replace(
                _var_name=_var_name,
                _var_type=bool,
                _var_is_string=False,
                merge_var_data=other._var_data,
            )

    def reverse(self) -> Var:
        """Reverse a list var.

        Raises:
            VarTypeError: If the var is not a list.

        Returns:
            A var with the reversed list.
        """
        if not types._issubclass(self._var_type, list):
            raise VarTypeError(f"Cannot reverse non-list var {self._var_full_name}.")

        return self._replace(
            _var_name=f"[...{self._var_full_name}].reverse()",
            _var_is_string=False,
            _var_full_name_needs_state_prefix=False,
        )

    def lower(self) -> Var:
        """Convert a string var to lowercase.

        Returns:
            A var with the lowercase string.

        Raises:
            VarTypeError: If the var is not a string.
        """
        if not types._issubclass(self._var_type, str):
            raise VarTypeError(
                f"Cannot convert non-string var {self._var_full_name} to lowercase."
            )

        return self._replace(
            _var_name=f"{self._var_name}.toLowerCase()",
            _var_is_string=False,
            _var_type=str,
        )

    def upper(self) -> Var:
        """Convert a string var to uppercase.

        Returns:
            A var with the uppercase string.

        Raises:
            VarTypeError: If the var is not a string.
        """
        if not types._issubclass(self._var_type, str):
            raise VarTypeError(
                f"Cannot convert non-string var {self._var_full_name} to uppercase."
            )

        return self._replace(
            _var_name=f"{self._var_name}.toUpperCase()",
            _var_is_string=False,
            _var_type=str,
        )

    def strip(self, other: str | Var[str] = " ") -> Var:
        """Strip a string var.

        Args:
            other: The string to strip the var with.

        Returns:
            A var with the stripped string.

        Raises:
            VarTypeError: If the var is not a string.
        """
        if not types._issubclass(self._var_type, str):
            raise VarTypeError(f"Cannot strip non-string var {self._var_full_name}.")

        other = (
            Var.create_safe(json.dumps(other), _var_is_string=False)
            if isinstance(other, str)
            else other
        )

        return self._replace(
            _var_name=f"{self._var_name}.replace(/^${other._var_full_name}|${other._var_full_name}$/g, '')",
            _var_is_string=False,
            merge_var_data=other._var_data,
        )

    def split(self, other: str | Var[str] = " ") -> Var:
        """Split a string var into a list.

        Args:
            other: The string to split the var with.

        Returns:
            A var with the list.

        Raises:
            VarTypeError: If the var is not a string.
        """
        if not types._issubclass(self._var_type, str):
            raise VarTypeError(f"Cannot split non-string var {self._var_full_name}.")

        other = (
            Var.create_safe(json.dumps(other), _var_is_string=False)
            if isinstance(other, str)
            else other
        )

        return self._replace(
            _var_name=f"{self._var_name}.split({other._var_full_name})",
            _var_is_string=False,
            _var_type=List[str],
            merge_var_data=other._var_data,
        )

    def join(self, other: str | Var[str] | None = None) -> Var:
        """Join a list var into a string.

        Args:
            other: The string to join the list with.

        Returns:
            A var with the string.

        Raises:
            VarTypeError: If the var is not a list.
        """
        if not types._issubclass(self._var_type, list):
            raise VarTypeError(f"Cannot join non-list var {self._var_full_name}.")

        if other is None:
            other = Var.create_safe('""', _var_is_string=False)
        if isinstance(other, str):
            other = Var.create_safe(json.dumps(other), _var_is_string=False)
        else:
            other = Var.create_safe(other, _var_is_string=False)

        return self._replace(
            _var_name=f"{self._var_name}.join({other._var_full_name})",
            _var_is_string=False,
            _var_type=str,
            merge_var_data=other._var_data,
        )

    def foreach(self, fn: Callable) -> Var:
        """Return a list of components. after doing a foreach on this var.

        Args:
            fn: The function to call on each component.

        Returns:
            A var representing foreach operation.

        Raises:
            VarTypeError: If the var is not a list.
        """
        inner_types = get_args(self._var_type)
        if not inner_types:
            raise VarTypeError(
                f"Cannot foreach over non-sequence var {self._var_full_name} of type {self._var_type}."
            )
        arg = BaseVar(
            _var_name=get_unique_variable_name(),
            _var_type=inner_types[0],
        )
        index = BaseVar(
            _var_name=get_unique_variable_name(),
            _var_type=int,
        )
        fn_signature = inspect.signature(fn)
        fn_args = (arg, index)
        fn_ret = fn(*fn_args[: len(fn_signature.parameters)])
        return self._replace(
            _var_name=f"{self._var_full_name}.map(({arg._var_name}, {index._var_name}) => {fn_ret})",
            _var_is_string=False,
        )

    @classmethod
    def range(
        cls,
        v1: Var | int = 0,
        v2: Var | int | None = None,
        step: Var | int | None = None,
    ) -> Var:
        """Return an iterator over indices from v1 to v2 (or 0 to v1).

        Args:
            v1: The start of the range or end of range if v2 is not given.
            v2: The end of the range.
            step: The number of numbers between each item.

        Returns:
            A var representing range operation.

        Raises:
            VarTypeError: If the var is not an int.
        """
        if not isinstance(v1, Var):
            v1 = Var.create_safe(v1)
        if v1._var_type != int:
            raise VarTypeError(f"Cannot get range on non-int var {v1._var_full_name}.")
        if not isinstance(v2, Var):
            v2 = Var.create(v2)
        if v2 is None:
            v2 = Var.create_safe("undefined", _var_is_string=False)
        elif v2._var_type != int:
            raise VarTypeError(f"Cannot get range on non-int var {v2._var_full_name}.")

        if not isinstance(step, Var):
            step = Var.create(step)
        if step is None:
            step = Var.create_safe(1)
        elif step._var_type != int:
            raise VarTypeError(
                f"Cannot get range on non-int var {step._var_full_name}."
            )

        return BaseVar(
            _var_name=f"Array.from(range({v1._var_full_name}, {v2._var_full_name}, {step._var_name}))",
            _var_type=List[int],
            _var_is_local=False,
            _var_data=VarData.merge(
                v1._var_data,
                v2._var_data,
                step._var_data,
                VarData(
                    imports={
                        "/utils/helpers/range.js": [
                            ImportVar(tag="range", is_default=True),
                        ],
                    },
                ),
            ),
        )

    def to(self, type_: Type) -> Var:
        """Convert the type of the var.

        Args:
            type_: The type to convert to.

        Returns:
            The converted var.
        """
        return self._replace(_var_type=type_)

    def as_ref(self) -> Var:
        """Convert the var to a ref.

        Returns:
            The var as a ref.
        """
        return self._replace(
            _var_name=f"refs['{self._var_full_name}']",
            _var_is_local=True,
            _var_is_string=False,
            _var_full_name_needs_state_prefix=False,
            merge_var_data=VarData(
                imports={
                    f"/{constants.Dirs.STATE_PATH}": [imports.ImportVar(tag="refs")],
                },
            ),
        )

    @property
    def _var_full_name(self) -> str:
        """Get the full name of the var.

        Returns:
            The full name of the var.
        """
        from reflex.utils import format

        if not self._var_full_name_needs_state_prefix:
            return self._var_name
        return (
            self._var_name
            if self._var_data is None or self._var_data.state == ""
            else ".".join(
                [format.format_state_name(self._var_data.state), self._var_name]
            )
        )

    def _var_set_state(self, state: Type[BaseState] | str) -> Any:
        """Set the state of the var.

        Args:
            state: The state to set or the full name of the state.

        Returns:
            The var with the set state.
        """
        from reflex.utils import format

        state_name = state if isinstance(state, str) else state.get_full_name()
        new_var_data = VarData(
            state=state_name,
            hooks={
                "const {0} = useContext(StateContexts.{0})".format(
                    format.format_state_name(state_name)
                ): None
            },
            imports={
                f"/{constants.Dirs.CONTEXTS_PATH}": [ImportVar(tag="StateContexts")],
                "react": [ImportVar(tag="useContext")],
            },
        )
        self._var_data = VarData.merge(self._var_data, new_var_data)
        self._var_full_name_needs_state_prefix = True
        return self

    @property
    def _var_state(self) -> str:
        """Compat method for getting the state.

        Returns:
            The state name associated with the var.
        """
        return self._var_data.state if self._var_data else ""

    @property
    def _var_name_unwrapped(self) -> str:
        """Get the var str without wrapping in curly braces.

        Returns:
            The str var without the wrapped curly braces
        """
        from reflex.style import Style

        generic_alias = types.is_generic_alias(self._var_type)

        type_ = get_origin(self._var_type) if generic_alias else self._var_type
        wrapped_var = str(self)

        return (
            wrapped_var
            if not self._var_state
            and not generic_alias
            and (types._issubclass(type_, dict) or types._issubclass(type_, Style))
            else wrapped_var.strip("{}")
        )


# Allow automatic serialization of Var within JSON structures
serializers.serializer(_encode_var)


@dataclasses.dataclass(
    eq=False,
    **{"slots": True} if sys.version_info >= (3, 10) else {},
)
class BaseVar(Var):
    """A base (non-computed) var of the app state."""

    # The name of the var.
    _var_name: str = dataclasses.field()

    # The type of the var.
    _var_type: Type = dataclasses.field(default=Any)

    # Whether this is a local javascript variable.
    _var_is_local: bool = dataclasses.field(default=False)

    # Whether the var is a string literal.
    _var_is_string: bool = dataclasses.field(default=False)

    # _var_full_name should be prefixed with _var_state
    _var_full_name_needs_state_prefix: bool = dataclasses.field(default=False)

    # Extra metadata associated with the Var
    _var_data: Optional[VarData] = dataclasses.field(default=None)

    def __hash__(self) -> int:
        """Define a hash function for a var.

        Returns:
            The hash of the var.
        """
        return hash((self._var_name, str(self._var_type)))

    def get_default_value(self) -> Any:
        """Get the default value of the var.

        Returns:
            The default value of the var.

        Raises:
            ImportError: If the var is a dataframe and pandas is not installed.
        """
        if types.is_optional(self._var_type):
            return None

        type_ = (
            get_origin(self._var_type)
            if types.is_generic_alias(self._var_type)
            else self._var_type
        )
        if type_ is Literal:
            args = get_args(self._var_type)
            return args[0] if args else None
        if issubclass(type_, str):
            return ""
        if issubclass(type_, types.get_args(Union[int, float])):
            return 0
        if issubclass(type_, bool):
            return False
        if issubclass(type_, list):
            return []
        if issubclass(type_, dict):
            return {}
        if issubclass(type_, tuple):
            return ()
        if types.is_dataframe(type_):
            try:
                import pandas as pd

                return pd.DataFrame()
            except ImportError as e:
                raise ImportError(
                    "Please install pandas to use dataframes in your app."
                ) from e
        return set() if issubclass(type_, set) else None

    def get_setter_name(self, include_state: bool = True) -> str:
        """Get the name of the var's generated setter function.

        Args:
            include_state: Whether to include the state name in the setter name.

        Returns:
            The name of the setter function.
        """
        setter = constants.SETTER_PREFIX + self._var_name
        if self._var_data is None:
            return setter
        if not include_state or self._var_data.state == "":
            return setter
        return ".".join((self._var_data.state, setter))

    def get_setter(self) -> Callable[[BaseState, Any], None]:
        """Get the var's setter function.

        Returns:
            A function that that creates a setter for the var.
        """

        def setter(state: BaseState, value: Any):
            """Get the setter for the var.

            Args:
                state: The state within which we add the setter function.
                value: The value to set.
            """
            if self._var_type in [int, float]:
                try:
                    value = self._var_type(value)
                    setattr(state, self._var_name, value)
                except ValueError:
                    console.debug(
                        f"{type(state).__name__}.{self._var_name}: Failed conversion of {value} to '{self._var_type.__name__}'. Value not set.",
                    )
            else:
                setattr(state, self._var_name, value)

        setter.__qualname__ = self.get_setter_name()

        return setter


@dataclasses.dataclass(init=False, eq=False)
class ComputedVar(Var, property):
    """A field with computed getters."""

    # Whether to track dependencies and cache computed values
    _cache: bool = dataclasses.field(default=False)

    # The initial value of the computed var
    _initial_value: Any | types.Unset = dataclasses.field(default=types.Unset())

    # Explicit var dependencies to track
    _static_deps: set[str] = dataclasses.field(default_factory=set)

    # Whether var dependencies should be auto-determined
    _auto_deps: bool = dataclasses.field(default=True)

    # Interval at which the computed var should be updated
    _update_interval: Optional[datetime.timedelta] = dataclasses.field(default=None)

    def __init__(
        self,
        fget: Callable[[BaseState], Any],
        initial_value: Any | types.Unset = types.Unset(),
        cache: bool = False,
        deps: Optional[List[Union[str, Var]]] = None,
        auto_deps: bool = True,
        interval: Optional[Union[int, datetime.timedelta]] = None,
        **kwargs,
    ):
        """Initialize a ComputedVar.

        Args:
            fget: The getter function.
            initial_value: The initial value of the computed var.
            cache: Whether to cache the computed value.
            deps: Explicit var dependencies to track.
            auto_deps: Whether var dependencies should be auto-determined.
            interval: Interval at which the computed var should be updated.
            **kwargs: additional attributes to set on the instance

        Raises:
            TypeError: If the computed var dependencies are not Var instances or var names.
        """
        self._initial_value = initial_value
        self._cache = cache
        if isinstance(interval, int):
            interval = datetime.timedelta(seconds=interval)
        self._update_interval = interval
        if deps is None:
            deps = []
        else:
            for dep in deps:
                if isinstance(dep, Var):
                    continue
                if isinstance(dep, str) and dep != "":
                    continue
                raise TypeError(
                    "ComputedVar dependencies must be Var instances or var names (non-empty strings)."
                )
        self._static_deps = {
            dep._var_name if isinstance(dep, Var) else dep for dep in deps
        }
        self._auto_deps = auto_deps
        property.__init__(self, fget)
        kwargs["_var_name"] = kwargs.pop("_var_name", fget.__name__)
        kwargs["_var_type"] = kwargs.pop("_var_type", self._determine_var_type())
        BaseVar.__init__(self, **kwargs)  # type: ignore

    @override
    def _replace(self, merge_var_data=None, **kwargs: Any) -> ComputedVar:
        """Replace the attributes of the ComputedVar.

        Args:
            merge_var_data: VarData to merge into the existing VarData.
            **kwargs: Var fields to update.

        Returns:
            The new ComputedVar instance.
        """
        return ComputedVar(
            fget=kwargs.get("fget", self.fget),
            initial_value=kwargs.get("initial_value", self._initial_value),
            cache=kwargs.get("cache", self._cache),
            deps=kwargs.get("deps", self._static_deps),
            auto_deps=kwargs.get("auto_deps", self._auto_deps),
            interval=kwargs.get("interval", self._update_interval),
            _var_name=kwargs.get("_var_name", self._var_name),
            _var_type=kwargs.get("_var_type", self._var_type),
            _var_is_local=kwargs.get("_var_is_local", self._var_is_local),
            _var_is_string=kwargs.get("_var_is_string", self._var_is_string),
            _var_full_name_needs_state_prefix=kwargs.get(
                "_var_full_name_needs_state_prefix",
                self._var_full_name_needs_state_prefix,
            ),
            _var_data=VarData.merge(self._var_data, merge_var_data),
        )

    @property
    def _cache_attr(self) -> str:
        """Get the attribute used to cache the value on the instance.

        Returns:
            An attribute name.
        """
        return f"__cached_{self._var_name}"

    @property
    def _last_updated_attr(self) -> str:
        """Get the attribute used to store the last updated timestamp.

        Returns:
            An attribute name.
        """
        return f"__last_updated_{self._var_name}"

    def needs_update(self, instance: BaseState) -> bool:
        """Check if the computed var needs to be updated.

        Args:
            instance: The state instance that the computed var is attached to.

        Returns:
            True if the computed var needs to be updated, False otherwise.
        """
        if self._update_interval is None:
            return False
        last_updated = getattr(instance, self._last_updated_attr, None)
        if last_updated is None:
            return True
        return datetime.datetime.now() - last_updated > self._update_interval

    def __get__(self, instance: BaseState | None, owner):
        """Get the ComputedVar value.

        If the value is already cached on the instance, return the cached value.

        Args:
            instance: the instance of the class accessing this computed var.
            owner: the class that this descriptor is attached to.

        Returns:
            The value of the var for the given instance.
        """
        if instance is None or not self._cache:
            return super().__get__(instance, owner)

        # handle caching
        if not hasattr(instance, self._cache_attr) or self.needs_update(instance):
            # Set cache attr on state instance.
            setattr(instance, self._cache_attr, super().__get__(instance, owner))
            # Ensure the computed var gets serialized to redis.
            instance._was_touched = True
            # Set the last updated timestamp on the state instance.
            setattr(instance, self._last_updated_attr, datetime.datetime.now())
        return getattr(instance, self._cache_attr)

    def _deps(
        self,
        objclass: Type,
        obj: FunctionType | CodeType | None = None,
        self_name: Optional[str] = None,
    ) -> set[str]:
        """Determine var dependencies of this ComputedVar.

        Save references to attributes accessed on "self".  Recursively called
        when the function makes a method call on "self" or define comprehensions
        or nested functions that may reference "self".

        Args:
            objclass: the class obj this ComputedVar is attached to.
            obj: the object to disassemble (defaults to the fget function).
            self_name: if specified, look for this name in LOAD_FAST and LOAD_DEREF instructions.

        Returns:
            A set of variable names accessed by the given obj.

        Raises:
            VarValueError: if the function references the get_state, parent_state, or substates attributes
                (cannot track deps in a related state, only implicitly via parent state).
        """
        if not self._auto_deps:
            return self._static_deps
        d = self._static_deps.copy()
        if obj is None:
            fget = property.__getattribute__(self, "fget")
            if fget is not None:
                obj = cast(FunctionType, fget)
            else:
                return set()
        with contextlib.suppress(AttributeError):
            # unbox functools.partial
            obj = cast(FunctionType, obj.func)  # type: ignore
        with contextlib.suppress(AttributeError):
            # unbox EventHandler
            obj = cast(FunctionType, obj.fn)  # type: ignore

        if self_name is None and isinstance(obj, FunctionType):
            try:
                # the first argument to the function is the name of "self" arg
                self_name = obj.__code__.co_varnames[0]
            except (AttributeError, IndexError):
                self_name = None
        if self_name is None:
            # cannot reference attributes on self if method takes no args
            return set()

        invalid_names = ["get_state", "parent_state", "substates", "get_substate"]
        self_is_top_of_stack = False
        for instruction in dis.get_instructions(obj):
            if (
                instruction.opname in ("LOAD_FAST", "LOAD_DEREF")
                and instruction.argval == self_name
            ):
                # bytecode loaded the class instance to the top of stack, next load instruction
                # is referencing an attribute on self
                self_is_top_of_stack = True
                continue
            if self_is_top_of_stack and instruction.opname in (
                "LOAD_ATTR",
                "LOAD_METHOD",
            ):
                try:
                    ref_obj = getattr(objclass, instruction.argval)
                except Exception:
                    ref_obj = None
                if instruction.argval in invalid_names:
                    raise VarValueError(
                        f"Cached var {self._var_full_name} cannot access arbitrary state via `{instruction.argval}`."
                    )
                if callable(ref_obj):
                    # recurse into callable attributes
                    d.update(
                        self._deps(
                            objclass=objclass,
                            obj=ref_obj,
                        )
                    )
                else:
                    # normal attribute access
                    d.add(instruction.argval)
            elif instruction.opname == "LOAD_CONST" and isinstance(
                instruction.argval, CodeType
            ):
                # recurse into nested functions / comprehensions, which can reference
                # instance attributes from the outer scope
                d.update(
                    self._deps(
                        objclass=objclass,
                        obj=instruction.argval,
                        self_name=self_name,
                    )
                )
            self_is_top_of_stack = False
        return d

    def mark_dirty(self, instance) -> None:
        """Mark this ComputedVar as dirty.

        Args:
            instance: the state instance that needs to recompute the value.
        """
        with contextlib.suppress(AttributeError):
            delattr(instance, self._cache_attr)

    def _determine_var_type(self) -> Type:
        """Get the type of the var.

        Returns:
            The type of the var.
        """
        hints = get_type_hints(property.__getattribute__(self, "fget"))
        if "return" in hints:
            return hints["return"]
        return Any


def computed_var(
    fget: Callable[[BaseState], Any] | None = None,
    initial_value: Any | None = None,
    cache: bool = False,
    deps: Optional[List[Union[str, Var]]] = None,
    auto_deps: bool = True,
    interval: Optional[Union[datetime.timedelta, int]] = None,
    **kwargs,
) -> ComputedVar | Callable[[Callable[[BaseState], Any]], ComputedVar]:
    """A ComputedVar decorator with or without kwargs.

    Args:
        fget: The getter function.
        initial_value: The initial value of the computed var.
        cache: Whether to cache the computed value.
        deps: Explicit var dependencies to track.
        auto_deps: Whether var dependencies should be auto-determined.
        interval: Interval at which the computed var should be updated.
        **kwargs: additional attributes to set on the instance

    Returns:
        A ComputedVar instance.

    Raises:
        ValueError: If caching is disabled and an update interval is set.
    """
    if cache is False and interval is not None:
        raise ValueError("Cannot set update interval without caching.")

    if fget is not None:
        return ComputedVar(fget=fget, cache=cache)

    def wrapper(fget: Callable[[BaseState], Any]) -> ComputedVar:
        return ComputedVar(
            fget=fget,
            initial_value=initial_value,
            cache=cache,
            deps=deps,
            auto_deps=auto_deps,
            interval=interval,
            **kwargs,
        )

    return wrapper


# Partial function of computed_var with cache=True
cached_var = functools.partial(computed_var, cache=True)


class CallableVar(BaseVar):
    """Decorate a Var-returning function to act as both a Var and a function.

    This is used as a compatibility shim for replacing Var objects in the
    API with functions that return a family of Var.
    """

    def __init__(self, fn: Callable[..., BaseVar]):
        """Initialize a CallableVar.

        Args:
            fn: The function to decorate (must return Var)
        """
        self.fn = fn
        default_var = fn()
        super().__init__(**dataclasses.asdict(default_var))

    def __call__(self, *args, **kwargs) -> BaseVar:
        """Call the decorated function.

        Args:
            *args: The args to pass to the function.
            **kwargs: The kwargs to pass to the function.

        Returns:
            The Var returned from calling the function.
        """
        return self.fn(*args, **kwargs)


def get_uuid_string_var() -> Var:
    """Return a var that generates UUIDs via .web/utils/state.js.

    Returns:
        the var to generate UUIDs at runtime.
    """
    from reflex.utils.imports import ImportVar

    unique_uuid_var_data = VarData(
        imports={f"/{constants.Dirs.STATE_PATH}": {ImportVar(tag="generateUUID")}}  # type: ignore
    )

    return BaseVar(
        _var_name="generateUUID()", _var_type=str, _var_data=unique_uuid_var_data
    )