import datetime
import re
import warnings
from functools import lru_cache
from typing import TYPE_CHECKING, Any, Literal

from pypika.enums import Arithmetic
from pypika.queries import QueryBuilder, Table
from pypika.terms import AggregateFunction, ArithmeticExpression, Star, Term, ValueWrapper

import frappe
from frappe import _
from frappe.boot import get_additional_filters_from_hooks
from frappe.database.operator_map import NESTED_SET_OPERATORS, OPERATOR_MAP
from frappe.database.utils import (
	DefaultOrderBy,
	FilterValue,
	convert_to_value,
	get_doctype_name,
	get_doctype_sort_info,
)
from frappe.model import CORE_DOCTYPES as PERMITTED_CORE_DOCTYPES
from frappe.model import OPTIONAL_FIELDS, get_permitted_fields
from frappe.model.base_document import DOCTYPES_FOR_DOCTYPE
from frappe.model.document import Document
from frappe.query_builder import Criterion, Field, Order, functions
from frappe.query_builder.custom import Month, MonthName, Quarter

CORE_DOCTYPES = DOCTYPES_FOR_DOCTYPE | frozenset(
	(
		"Custom Field",
		"Property Setter",
		"Module Def",
		"__Auth",
		"__global_search",
		"Singles",
		"Sessions",
		"Series",
	)
)


def _apply_date_field_filter_conversion(value, operator: str, doctype: str, field):
	"""Apply datetime to date conversion for Date fieldtype filters.

	This matches db_query behavior where datetime values are truncated to dates
	when filtering on Date fields, for all operators (not just 'between').

	Args:
		value: The filter value (can be datetime, tuple of datetimes, or other)
		operator: The operator being used (between, >, <, etc.)
		doctype: The doctype to get field metadata from
		field: The field name or pypika Field object

	Returns:
		The converted value with datetimes converted to dates if field is Date type
	"""
	try:
		# Extract field name
		if "." in str(field):
			field = field.split(".")[-1]

		# Skip querying meta for core doctypes to avoid recursion
		if doctype in CORE_DOCTYPES:
			meta = None
		else:
			meta = frappe.get_meta(doctype)

		if meta is None:
			return value

		df = meta.get_field(field)
		if df is None or df.fieldtype != "Date":
			return value

		# Convert datetime to date if the fieldtype is date
		if operator.lower() == "between" and isinstance(value, list | tuple) and len(value) == 2:
			from_val, to_val = value
			if isinstance(from_val, datetime.datetime):
				from_val = from_val.date()
			if isinstance(to_val, datetime.datetime):
				to_val = to_val.date()
			return (from_val, to_val)
		elif isinstance(value, datetime.datetime):
			return value.date()

	except (AttributeError, TypeError, KeyError):
		pass

	return value


def _apply_datetime_field_filter_conversion(between_values: tuple | list, doctype: str, field) -> tuple:
	"""Apply date to datetime conversion for Datetime fields with 'between' operator.

	Args:
		between_values: Tuple/list of two values [from, to] for between filter
		doctype: DocType name
		field: Field name or pypika Field object

	Returns:
		Tuple with dates expanded to datetime ranges for Datetime fields
	"""
	from frappe.model.db_query import _convert_type_for_between_filters

	# Extract field name
	field_name = field
	if "." in str(field):
		field_name = field.split(".")[-1]

	# Skip querying meta for core doctypes to avoid recursion
	if doctype in CORE_DOCTYPES:
		df = None
	else:
		meta = frappe.get_meta(doctype)
		df = meta.get_field(field_name) if meta else None

	# Standard datetime fields or Datetime fieldtype
	if not (field_name in ("creation", "modified") or (df and df.fieldtype == "Datetime")):
		return between_values

	from_val, to_val = between_values

	# Convert to datetime using db_query helper (handles strings, dates, datetimes)
	from_val = _convert_type_for_between_filters(from_val, set_time=datetime.time())
	to_val = _convert_type_for_between_filters(to_val, set_time=datetime.time(23, 59, 59, 999999))

	return (from_val, to_val)


if TYPE_CHECKING:
	from frappe.query_builder import DocType

TAB_PATTERN = re.compile("^tab")
WORDS_PATTERN = re.compile(r"\w+")
COMMA_PATTERN = re.compile(r",\s*(?![^()]*\))")

# Pattern for validating simple field names (alphanumeric + underscore)
SIMPLE_FIELD_PATTERN = re.compile(r"^\w+$")

# Pattern for detecting SQL function calls: identifier followed by opening parenthesis
FUNCTION_CALL_PATTERN = re.compile(r"^\s*[a-zA-Z_][a-zA-Z0-9_]*\s*\(", flags=re.ASCII)


# Pattern to validate field names in SELECT:
# Allows: name, `name`, name as alias, `name` as alias, table.name, table.name as alias
# Also allows backtick-qualified identifiers with spaces/hyphens:
#   - `tabTable`.`field`
#   - `tabTable Name`.`field` (spaces in table name)
#   - `tabTable-Field`.`field` (hyphens in table name)
#   - Any of above with aliases: ... as alias
#   - Single-quoted aliases with colons (used by reportview child fields):
#     - ... as 'Child:field'
ALLOWED_FIELD_PATTERN = re.compile(
	r"^(?:(`[\w\s-]+`|\w+)\.)?(`\w+`|\w+)(?:\s+as\s+(?:`[\w\s-]+`|'[\w\s:-]+'|\w+))?$",
	flags=re.IGNORECASE,
)

# Regex to parse field names:
# Group 1: Optional quote for table name
# Group 2: Optional table name (e.g., `tabDocType` or tabDocType or `tabNote Seen By`)
# Group 3: Optional quote for field name
# Group 4: Field name (e.g., `field` or field)
FIELD_PARSE_REGEX = re.compile(r"^(?:(`?)(tab[\w\s-]+)\1\.)?(`?)(\w+)\3$")

# Like FIELD_PARSE_REGEX but compulsary table name with backticks
BACKTICK_FIELD_PARSE_REGEX = re.compile(r"^`tab([\w\s-]+)`\.(`?)(\w+)\2$")

# Pattern to match child table field notation: tabChildDoc.field or `tabChild Doc`.field
# Group 1: Child doctype name (without 'tab' prefix)
# Group 2: Optional quote for fieldname
# Group 3: Fieldname
CHILD_TABLE_FIELD_PATTERN = re.compile(r'^[`"]?tab([\w\s]+)[`"]?\.([`"]?)(\w+)\2$')

# Maximum value of an unsigned 64-bit integer
MAX_LIMIT = 18446744073709551615

# Direct mapping from uppercase function names to pypika function classes
FUNCTION_MAPPING = {
	"COUNT": functions.Count,
	"SUM": functions.Sum,
	"AVG": functions.Avg,
	"MAX": functions.Max,
	"MIN": functions.Min,
	"ABS": functions.Abs,
	"EXTRACT": functions.Extract,
	"LOCATE": functions.Locate,
	"TIMESTAMP": functions.Timestamp,
	"IFNULL": functions.IfNull,
	"CONCAT": functions.Concat,
	"NOW": functions.Now,
	"NULLIF": functions.NullIf,
	"MONTHNAME": MonthName,
	"QUARTER": Quarter,
	"MONTH": Month,
}

# Functions that accept '*' as an argument (e.g., COUNT(*))
STAR_ALLOWED_FUNCTIONS = frozenset(("COUNT",))

# Mapping from operator names to pypika Arithmetic enum values
# Operators use dict format: {"ADD": [left, right], "as": "alias"}
# Supported: ADD (+), SUB (-), MUL (*), DIV (/)
# Can be nested with functions: {"DIV": [1, {"NULLIF": ["value", 0]}]}
OPERATOR_MAPPING = {
	"ADD": Arithmetic.add,
	"SUB": Arithmetic.sub,
	"MUL": Arithmetic.mul,
	"DIV": Arithmetic.div,
}


class Engine:
	def get_query(
		self,
		table: str | Table,
		fields: str | list | tuple | set | None = None,
		filters: dict[str, FilterValue] | FilterValue | list[list | FilterValue] | None = None,
		order_by: str | None = None,
		group_by: str | None = None,
		limit: int | None = None,
		offset: int | None = None,
		distinct: bool = False,
		for_update: bool = False,
		update: bool = False,
		into: bool = False,
		delete: bool = False,
		*,
		validate_filters: bool = False,
		skip_locked: bool = False,
		wait: bool = True,
		ignore_permissions: bool = True,
		ignore_user_permissions: bool = False,
		user: str | None = None,
		parent_doctype: str | None = None,
		reference_doctype: str | None = None,
		or_filters: dict[str, FilterValue] | FilterValue | list[list | FilterValue] | None = None,
		db_query_compat: bool = False,
	) -> QueryBuilder:
		"""Build a query with optional compatibility mode for legacy db_query behavior.

		Args:
			db_query_compat: When True, uses legacy db_query behavior for sorting and filtering.
			This is kept optional to not break existing code that relies on the original query builder behaviour.
			ignore_user_permissions: Ignore user permissions for the query.
				Useful for link search queries when the link field has `ignore_user_permissions` set.
			validate_filters: DEPRECATED. Will be removed in future versions.
		"""

		qb = frappe.local.qb
		db_type = frappe.local.db.db_type

		self.is_mariadb = db_type == "mariadb"
		self.is_postgres = db_type == "postgres"
		self.is_sqlite = db_type == "sqlite"
		self.user = user or frappe.session.user
		self.parent_doctype = parent_doctype
		self.reference_doctype = reference_doctype
		self.apply_permissions = not ignore_permissions
		self.ignore_user_permissions = ignore_user_permissions
		self.function_aliases = set()
		self.field_aliases = set()
		self.db_query_compat = db_query_compat
		self.permitted_fields_cache = {}  # Cache for get_permitted_fields results
		self.is_aggregate_query = False
		self._grouped_queries = set()

		if isinstance(table, Table):
			self.table = table
			self.doctype = get_doctype_name(table.get_sql())
		else:
			self.doctype = table
			self.table = qb.DocType(table)

		if self.apply_permissions:
			self.check_select_permission()
			self.permission_doctype = parent_doctype or self.doctype
			self.permission_table = (
				qb.DocType(self.permission_doctype) if self.permission_doctype != self.doctype else self.table
			)

		is_select = False
		if update:
			self.query = qb.update(self.table, immutable=False)
		elif into:
			self.query = qb.into(self.table, immutable=False)
		elif delete:
			self.query = qb.from_(self.table, immutable=False).delete()
		else:
			self.query = qb.from_(self.table, immutable=False)
			self.apply_fields(fields)
			is_select = True

		self.apply_filters(filters)
		self.apply_or_filters(or_filters)

		if limit:
			if not isinstance(limit, int) or limit < 0:
				frappe.throw(_("Limit must be a non-negative integer"), TypeError)
			self.query = self.query.limit(limit)

		if offset:
			if not isinstance(offset, int) or offset < 0:
				frappe.throw(_("Offset must be a non-negative integer"), TypeError)

			# In MariaDB and SQLite, offset requires limit
			if not self.is_postgres and not limit:
				self.query = self.query.limit(MAX_LIMIT)

			self.query = self.query.offset(offset)

		if distinct:
			self.query = self.query.distinct()

		if for_update:
			self.query = self.query.for_update(skip_locked=skip_locked, nowait=not wait)

		if any(isinstance(f, functions.AggregateFunction) for f in getattr(self, "fields", [])):
			# check if any field in select is aggregated (done to prevent breaking queries in postgres due to order by rule)
			self.is_aggregate_query = True

		if group_by:
			self.is_aggregate_query = True  # for postgres (group by used with order by)
			self.apply_group_by(group_by)

		if order_by:
			if not (
				self.is_postgres and is_select and distinct
			):  # ignore in Postgres since order by fields need to appear in select distinct
				self.apply_order_by(order_by)
			else:
				warnings.warn(
					(
						"ORDER BY fields have been ignored because PostgreSQL requires them to "
						"appear in the SELECT list when using with DISTINCT"
					),
					UserWarning,
					stacklevel=2,
				)

		self.add_permission_conditions()

		# Store metadata for masked field processing during execution
		self.query._doctype = self.doctype
		self.query._fields_list = getattr(self, "fields", [])

		self.query.immutable = True
		return self.query

	def apply_fields(self, fields):
		self.fields = self.parse_fields(fields)

		# Track field aliases for use in group_by/order_by
		for field in self.fields:
			if isinstance(field, Field | DynamicTableField | AggregateFunction) and field.alias:
				self.field_aliases.add(field.alias)

		if self.apply_permissions:
			self.fields = self.apply_field_permissions()

		if not self.fields:
			self.fields = [self.table.name]

		self.query._child_queries = []
		has_select_field = False
		for field in self.fields:
			if isinstance(field, DynamicTableField):
				self.query = field.apply_select(self.query, engine=self)
				has_select_field = True
			elif isinstance(field, ChildQuery):
				self.query._child_queries.append(field)
			else:
				self.query = self.query.select(field)
				has_select_field = True

		if not has_select_field:
			self.query = self.query.select(self.table.name)

	def apply_filters(
		self,
		filters: dict[str, FilterValue] | FilterValue | list[list | FilterValue] | None = None,
		collect: list | None = None,
	):
		if filters is None:
			return

		if isinstance(filters, FilterValue):
			filters = {"name": convert_to_value(filters)}

		if isinstance(filters, Criterion):
			self.query = self.query.where(filters)
			return

		if isinstance(filters, dict):
			self.apply_dict_filters(filters, collect=collect)
			return

		if isinstance(filters, list | tuple):
			if not filters:
				return

			# 1. Check for single simple filter [field, op, value] or [doctype, field, op, value]
			if len(filters) in (3, 4) and isinstance(filters[1], str):
				if (
					filters[1].lower() in OPERATOR_MAP
					or filters[1].lower() in get_additional_filters_from_hooks()
				):
					self.apply_list_filters(filters, collect=collect)
					return

			# 2. Handle special case: list of names -> name IN (...)
			if all(isinstance(d, FilterValue) for d in filters):
				self.apply_dict_filters(
					{"name": ("in", tuple(convert_to_value(f) for f in filters))}, collect=collect
				)
				return

			# 3. Check for nested logic format [cond, op, cond, ...] or [[cond, op, cond]]
			is_nested_structure = False
			potential_nested_list = filters
			is_single_group = False

			# Check for single grouped condition [[cond_a, op, cond_b]]
			if len(filters) == 1 and isinstance(filters[0], list | tuple):
				inner_list = filters[0]
				# Ensure inner list also looks like a nested structure
				# Check if the operator is a string, and specifically a logical operator
				if (
					len(inner_list) >= 3
					and isinstance(inner_list[1], str)
					and inner_list[1].lower() in ("and", "or")
				):
					is_nested_structure = True
					potential_nested_list = inner_list  # Use the inner list for validation and parsing
					is_single_group = True  # Flag that the original filters was wrapped

			# Check for standard nested structure [cond, op, cond, ...]
			# Check if it looks like it *might* be nested (even if malformed).
			# This allows lists starting with operators or containing invalid operators
			# to be passed to _parse_nested_filters for detailed validation.
			# Condition: Starts with a list/tuple and contains a string at an odd index OR starts with a string.
			elif (
				len(filters) >= 2
				and isinstance(filters[0], list | tuple)
				and any(isinstance(item, str) for i, item in enumerate(filters) if i % 2 != 0)
			) or (len(filters) > 0 and isinstance(filters[0], str)):
				is_nested_structure = True
				# potential_nested_list remains filters

			if is_nested_structure:
				# If validation passes, proceed with parsing the identified nested list
				try:
					# If it's a single group like [[cond]], parse the inner list as one condition.
					# Otherwise, parse the list as a sequence [cond1, op, cond2, ...].
					if is_single_group:
						combined_criterion = self._condition_to_criterion(potential_nested_list)
					else:
						# _parse_nested_filters MUST validate the structure, including the first element and operators.
						combined_criterion = self._parse_nested_filters(potential_nested_list)
					if combined_criterion:
						if collect is not None:
							collect.append(combined_criterion)
						else:
							self.query = self.query.where(combined_criterion)
				except Exception as e:
					# Log the original filters list for better debugging context
					frappe.throw(_("Error parsing nested filters: {0}. {1}").format(filters, str(e)), exc=e)

			else:  # Not a nested structure, assume it's a list of simple filters (implicitly ANDed)
				for filter_item in filters:
					if isinstance(filter_item, list | tuple):
						self.apply_list_filters(
							filter_item, collect=collect
						)  # Handles simple [field, op, value] lists
					elif isinstance(filter_item, dict | Criterion):
						self.apply_filters(filter_item, collect=collect)  # Recursive call for dict/criterion
					else:
						# Disallow single values (strings, numbers, etc.) directly in the list
						# unless it's the name IN (...) case handled above.
						raise ValueError(
							f"Invalid item type in filter list: {type(filter_item).__name__}. Expected list, tuple, dict, or Criterion."
						)
			return

		# If filters type is none of the above
		raise ValueError(f"Unsupported filters type: {type(filters).__name__}")

	def apply_or_filters(
		self,
		or_filters: dict[str, FilterValue] | FilterValue | list[list | FilterValue] | None = None,
	):
		"""Apply OR filters - all conditions are combined with OR operator.

		Example:
			or_filters={"name": "User", "module": "Core"}
			→ Collects: [Criterion(name='User'), Criterion(module='Core')]
			→ Combines: Criterion(name='User') | Criterion(module='Core')
			→ Result: WHERE name='User' OR module='Core'
		"""
		if or_filters is None:
			return

		# Collect criteria instead of applying immediately
		criteria = []
		self.apply_filters(or_filters, collect=criteria)

		# Combine all criteria with OR operator (|)
		if criteria:
			from functools import reduce

			# Reduce combines: [Criterion(name='User'), Criterion(module='Core')] → Criterion(name='User') | Criterion(module='Core')
			combined = reduce(lambda a, b: a | b, criteria)
			self.query = self.query.where(combined)

	def apply_list_filters(self, filter: list, collect: list | None = None):
		match filter:
			case [field, value]:
				self._apply_filter(field, value, collect=collect)
			case [field, operator, value]:
				self._apply_filter(field, value, operator, collect=collect)
			case [doctype, field, operator, value]:
				self._apply_filter(field, value, operator, doctype, collect=collect)
			case [doctype, field, operator, value, _]:
				self._apply_filter(field, value, operator, doctype, collect=collect)
			case _:
				raise ValueError(f"Unknown filter format: {filter}")

	def apply_dict_filters(self, filters: dict[str, FilterValue | list], collect: list | None = None):
		for field, value in filters.items():
			operator = "="
			if isinstance(value, list | tuple):
				operator, value = value

			self._apply_filter(field, value, operator, collect=collect)

	def _apply_filter(
		self,
		field: str | Field,
		value: FilterValue | list | set | None,
		operator: str = "=",
		doctype: str | None = None,
		collect: list | None = None,
	):
		"""Applies a simple filter condition to the query."""
		criterion = self._build_criterion_for_simple_filter(field, value, operator, doctype)
		if criterion:
			if collect is not None:
				collect.append(criterion)
			else:
				self.query = self.query.where(criterion)

	def _build_criterion_for_simple_filter(
		self,
		field: str | Field,
		value: FilterValue | Field | list | set | None,
		operator: str = "=",
		doctype: str | None = None,
	) -> "Criterion | None":
		"""Builds a pypika Criterion object for a simple filter condition."""
		import operator as builtin_operator

		"""Check hooks for custom_operator definitions"""
		additional_filters_config = get_additional_filters_from_hooks()
		if operator.lower() in additional_filters_config:
			f = frappe._dict(doctype=doctype or self.doctype, fieldname=field, operator=operator, value=value)
			from frappe.model.db_query import get_additional_filter_field

			resolved = get_additional_filter_field(additional_filters_config, f, value)
			operator = resolved.get("operator")
			value = resolved.get("value", value)

		_field = self._validate_and_prepare_filter_field(field, doctype)

		if isinstance(value, Field):
			_value = value
		else:
			# Regular value processing for literal comparisons like: table.field = 'value'
			_value = convert_to_value(value)

		if isinstance(value, Document):
			frappe.throw(_("Document cannot be used as a filter value"))
		_operator = operator

		if _operator.lower() in ("timespan", "previous", "next"):
			from frappe.model.db_query import get_date_range

			_value = get_date_range(_operator.lower(), _value)
			_operator = "between"

		# For Date fields with datetime values, convert to date to match db_query behavior
		if isinstance(_value, datetime.datetime) or (
			isinstance(_value, list | tuple) and any(isinstance(v, datetime.datetime) for v in _value)
		):
			_value = _apply_date_field_filter_conversion(_value, _operator, doctype or self.doctype, field)

		# For Datetime fields with date values and 'between' operator, convert to datetime range to match db_query
		if _operator.lower() == "between":
			if isinstance(_value, list | tuple) and len(_value) == 2:
				_value = _apply_datetime_field_filter_conversion(_value, doctype or self.doctype, field)
			elif isinstance(_value, str):
				from frappe.model.db_query import get_between_date_filter

				target_meta = frappe.get_meta(doctype or self.doctype)
				df = target_meta.get_field(field)
				_value = tuple(
					v.strip().strip("'") for v in get_between_date_filter(_value, df).split(" AND ")
				)

		# Handle empty lists for IN/NOT IN operators before conversion
		# IN with empty list should return 0 results (always False)
		# NOT IN with empty list should return all results (always True)
		if _operator.lower() in ("in", "not in"):
			if isinstance(_value, (list, tuple, set)) and len(_value) == 0:
				if _operator.lower() == "in":
					# Return a criterion that always evaluates to False (1=0)
					# This ensures IN with empty list returns 0 results
					return RawCriterion("1=0")
				else:  # not in
					# Return a criterion that always evaluates to True (1=1)
					# NOT IN with empty set matches all rows since nothing is excluded
					return RawCriterion("1=1")

		if not _value and isinstance(_value, list | tuple | set):
			_value = ("",)

		# db_query compatibility: handle None values for 'in' and 'not in' operators
		# In db_query, None values are converted to empty tuples for these operators
		if self.db_query_compat and _value is None and _operator.casefold() in ("in", "not in"):
			_value = ("",)

		if _operator in NESTED_SET_OPERATORS:
			hierarchy = _operator
			docname = _value

			# Use the original field name string for get_field if _field was converted
			# If _field is from a dynamic field, its name might be just the target fieldname.
			# We need the original string ('link.target') or the fieldname from the main doctype.
			original_field_name = field if isinstance(field, str) else _field.name
			# Check if the original field name exists in the *main* doctype meta
			main_meta = frappe.get_meta(self.doctype)
			if main_meta.has_field(original_field_name):
				_df = main_meta.get_field(original_field_name)
				ref_doctype = _df.options if _df else self.doctype
			else:
				# If not in main doctype, assume it's a standard field like 'name' or refers to the main doctype itself
				# This part might need refinement if nested set operators are used with dynamic fields.
				ref_doctype = self.doctype

			nodes = get_nested_set_hierarchy_result(ref_doctype, docname, hierarchy)
			operator_fn = (
				OPERATOR_MAP["not in"]
				if hierarchy in ("not ancestors of", "not descendants of")
				else OPERATOR_MAP["in"]
			)
			return operator_fn(_field, nodes or ("",))

		if (
			self.is_postgres and _operator.casefold() == "like"
		):  # use `ILIKE` to support case insensitive search in postgres
			operator_fn = OPERATOR_MAP["ilike"]
		else:
			operator_fn = OPERATOR_MAP[_operator.casefold()]
		if _value is None and isinstance(_field, Field):
			if operator_fn == builtin_operator.ne:
				filter_field_name = (
					field
					if isinstance(field, str)
					else (_field.name if hasattr(_field, "name") else str(_field))
				)
				if "." in filter_field_name:
					filter_field_name = filter_field_name.split(".")[-1]

				target_doctype = doctype or self.doctype
				fallback_sql = self._get_ifnull_fallback(target_doctype, filter_field_name)

				if fallback_sql == "''":
					fallback_value = ""
				elif fallback_sql.startswith("'") and fallback_sql.endswith("'"):
					fallback_value = fallback_sql[1:-1]
				else:
					try:
						fallback_value = int(fallback_sql)
					except (ValueError, TypeError):
						fallback_value = fallback_sql

				return operator_fn(_field, ValueWrapper(fallback_value))
			else:
				return _field.isnull()
		else:
			filter_field_name = (
				field if isinstance(field, str) else (_field.name if hasattr(_field, "name") else str(_field))
			)

			if "." in filter_field_name:
				filter_field_name = filter_field_name.split(".")[-1]

			target_doctype = doctype or self.doctype

			# Skip applying ifnull if field already has null-handling function
			if isinstance(_field, functions.IfNull | functions.Coalesce):
				return operator_fn(_field, _value)

			if self._should_apply_ifnull(target_doctype, filter_field_name, _operator, _value):
				fallback_sql = self._get_ifnull_fallback(target_doctype, filter_field_name)
				if fallback_sql == "''":
					fallback_value = ""
				elif fallback_sql.startswith("'") and fallback_sql.endswith("'"):
					fallback_value = fallback_sql[1:-1]
				else:
					try:
						fallback_value = int(fallback_sql)
					except (ValueError, TypeError):
						fallback_value = fallback_sql

				if fallback_value == _value:
					if _operator == "=":
						return _field.isnull() | _field.eq(_value)
					elif _operator == "!=":
						return operator_fn(_field, _value)

				_field = functions.IfNull(_field, ValueWrapper(fallback_value))

			return operator_fn(_field, _value)

	def _parse_nested_filters(self, nested_list: list | tuple) -> "Criterion | None":
		"""Parses a nested filter list like [cond1, 'and', cond2, 'or', cond3, ...] into a pypika Criterion."""
		if not isinstance(nested_list, list | tuple):
			frappe.throw(_("Nested filters must be provided as a list or tuple."))

		if not nested_list:
			return None

		# First item must be a condition (list/tuple)
		if not isinstance(nested_list[0], list | tuple):
			frappe.throw(
				_("Invalid start for filter condition: {0}. Expected a list or tuple.").format(nested_list[0])
			)

		current_criterion = self._condition_to_criterion(nested_list[0])

		idx = 1
		while idx < len(nested_list):
			# Expect an operator ('and' or 'or')
			operator_str = nested_list[idx]
			if not isinstance(operator_str, str) or operator_str.lower() not in ("and", "or"):
				frappe.throw(
					_("Expected 'and' or 'or' operator, found: {0}").format(operator_str),
					frappe.ValidationError,
				)

			idx += 1
			if idx >= len(nested_list):
				frappe.throw(_("Filter condition missing after operator: {0}").format(operator_str))

			# Expect a condition (list/tuple)
			next_condition = nested_list[idx]
			if not isinstance(next_condition, list | tuple):
				frappe.throw(
					_("Invalid filter condition: {0}. Expected a list or tuple.").format(next_condition)
				)

			next_criterion = self._condition_to_criterion(next_condition)

			if operator_str.lower() == "and":
				current_criterion = current_criterion & next_criterion
			elif operator_str.lower() == "or":
				current_criterion = current_criterion | next_criterion

			idx += 1

		return current_criterion

	def _condition_to_criterion(self, condition: list | tuple) -> "Criterion":
		"""Converts a single condition (simple filter list or nested list) into a pypika Criterion."""
		if not isinstance(condition, list | tuple):
			frappe.throw(_("Invalid condition type in nested filters: {0}").format(type(condition)))

		# Check if it's a nested condition list [cond1, op, cond2, ...]
		is_nested = False
		# Broaden check here as well: length >= 2 and second element is string
		if len(condition) >= 2 and isinstance(condition[1], str) and isinstance(condition[0], list | tuple):
			is_nested = True

		if is_nested:
			# It's a nested sub-expression like [["assignee", "=", "A"], "or", ["assignee", "=", "B"]]
			# _parse_nested_filters will handle operator validation ('and'/'or')
			return self._parse_nested_filters(condition)
		else:
			# Assume it's a simple filter [field, op, value] etc.
			field, value, operator, doctype = None, None, None, None
			additional_filters_config = get_additional_filters_from_hooks()
			# Determine structure based on length and types
			if (
				len(condition) == 3
				and isinstance(condition[1], str)
				and (
					condition[1].lower() in OPERATOR_MAP or condition[1].lower() in additional_filters_config
				)
			):
				# [field, operator, value]
				field, operator, value = condition
			elif (
				len(condition) == 4
				and isinstance(condition[2], str)
				and (
					condition[2].lower() in OPERATOR_MAP or condition[2].lower() in additional_filters_config
				)
			):
				# [doctype, field, operator, value]
				doctype, field, operator, value = condition
			elif len(condition) == 2:
				# [field, value] -> implies '=' operator
				field, value = condition
				operator = "="
			else:
				frappe.throw(_("Invalid simple filter format: {0}").format(condition))

			# Use the helper method to build the criterion for the simple filter
			return self._build_criterion_for_simple_filter(field, value, operator, doctype)

	def _validate_and_prepare_filter_field(self, field: str | Field, doctype: str | None = None) -> Field:
		"""Validate field name for filters and return a pypika Field object. Handles dynamic fields."""

		if isinstance(field, Term):
			# return if field is already a pypika Term
			return field

		# Parse backtick table.field notation: `tabDocType`.`fieldname`
		if "`" in field:
			if parsed := self._parse_backtick_field_notation(field):
				table_name, field_name = parsed

				self.check_filter_field_permission(table_name, field_name)

				# Return query builder field reference
				return frappe.qb.DocType(table_name)[field_name]

			# If parsing failed, fall through to error handling below
			frappe.throw(
				_("Filter fields have invalid backtick notation: {0}").format(field),
				frappe.ValidationError,
				title=_("Invalid Filter"),
			)

		# Handle dot notation (link_field.target_field or child_table_field.target_field)
		if "." in field:
			# Disallow tabDoc.field notation in filters.
			dynamic_field = DynamicTableField.parse(field, self.doctype, allow_tab_notation=False)
			if dynamic_field:
				# Parsed successfully as link/child field access
				target_doctype = dynamic_field.doctype
				target_fieldname = dynamic_field.fieldname
				parent_doctype_for_perm = (
					dynamic_field.parent_doctype if isinstance(dynamic_field, ChildTableField) else None
				)
				self.check_filter_field_permission(target_doctype, target_fieldname, parent_doctype_for_perm)

				self.query = dynamic_field.apply_join(self.query, engine=self)
				# Return the pypika Field object associated with the dynamic field
				return dynamic_field.field
			else:
				# Contains '.' but is not a valid link/child field access pattern
				# This rejects tabDoc.field and other invalid formats like a.b.c
				frappe.throw(
					_(
						"Invalid filter field format: {0}. Use 'fieldname' or 'link_fieldname.target_fieldname'."
					).format(field),
					frappe.ValidationError,
					title=_("Invalid Filter"),
				)
		else:
			# No '.' and no '`'. Check if it's a simple field name (alphanumeric + underscore).
			if not SIMPLE_FIELD_PATTERN.match(field):
				frappe.throw(
					_(
						"Invalid characters in fieldname: {0}. Only letters, numbers, and underscores are allowed."
					).format(field),
					frappe.ValidationError,
					title=_("Invalid Filter"),
				)
			# It's a simple, valid fieldname like 'name' or 'creation'
			target_doctype = doctype or self.doctype
			target_fieldname = field
			parent_doctype_for_perm = self.parent_doctype if doctype else None

			# If a specific doctype is provided and it's different from the main query doctype,
			# if it's a child table, add the join using ChildTableField logic
			if doctype and doctype != self.doctype:
				# Check if doctype is a valid child table of self.doctype
				parent_meta = frappe.get_meta(self.doctype)
				# Find the parent fieldname for this child doctype
				parent_fieldname = None
				for df in parent_meta.get_table_fields():
					if df.options == doctype:
						parent_fieldname = df.fieldname
						break

				# If it's not a child table, check permissions
				if not parent_fieldname:
					self.check_filter_field_permission(
						target_doctype, target_fieldname, parent_doctype_for_perm
					)
					return frappe.qb.DocType(target_doctype)[target_fieldname]

				# Create a ChildTableField instance to handle join and field access
				# Pass the identified parent_fieldname
				child_field_handler = ChildTableField(
					doctype=doctype,
					fieldname=target_fieldname,
					parent_doctype=self.doctype,
					parent_fieldname=parent_fieldname,
				)

				# For permission check, the parent is the main doctype
				parent_doctype_for_perm = self.doctype
				self.check_filter_field_permission(target_doctype, target_fieldname, parent_doctype_for_perm)

				# Delegate join logic
				self.query = child_field_handler.apply_join(self.query, engine=self)
				# Return the pypika Field object from the handler
				return child_field_handler.field
			else:
				# Field belongs to the main doctype or doctype wasn't specified differently
				# If doctype wasn't specified, and the field isn't a standard field and doesn't exist in main doctype, check child tables
				from frappe.model import child_table_fields, default_fields, optional_fields

				if self.doctype in CORE_DOCTYPES:
					meta = None
				else:
					try:
						meta = frappe.get_meta(self.doctype)
					except frappe.DoesNotExistError:
						meta = None

				if (
					meta
					and not doctype
					and target_fieldname not in default_fields + optional_fields + child_table_fields
					and not meta.has_field(target_fieldname)
				):
					for df in meta.get_table_fields(include_computed=True):
						try:
							child_meta = frappe.get_meta(df.options)
						except frappe.DoesNotExistError:
							continue

						if child_meta.has_field(target_fieldname):
							# Found in child table, create handler for it
							child_field_handler = ChildTableField(
								doctype=df.options,
								fieldname=target_fieldname,
								parent_doctype=self.doctype,
								parent_fieldname=df.fieldname,
							)
							parent_doctype_for_perm = self.doctype
							self.check_filter_field_permission(
								df.options, target_fieldname, parent_doctype_for_perm
							)
							self.query = child_field_handler.apply_join(self.query, engine=self)
							return child_field_handler.field

				self.check_filter_field_permission(target_doctype, target_fieldname, parent_doctype_for_perm)
				# Convert string field name to pypika Field object for the specified/current doctype
				return frappe.qb.DocType(target_doctype)[target_fieldname]

	def check_select_field_permission(self, doctype: str, fieldname: str, parent_doctype: str | None = None):
		"""Check if the user has permission to select the given field."""
		self._check_field_permission(doctype, fieldname, parent_doctype, for_filtering=False)

	def check_filter_field_permission(self, doctype: str, fieldname: str, parent_doctype: str | None = None):
		"""Check if the user has permission to filter/order/group by the given field.

		It allows all permlevel 0 fields for users with select permission,
		and all permitted fields for users with read permission.
		"""
		self._check_field_permission(doctype, fieldname, parent_doctype, for_filtering=True)

	def _check_field_permission(
		self, doctype: str, fieldname: str, parent_doctype: str | None = None, for_filtering: bool = False
	):
		"""Check if the user has permission to access the given field."""
		if not self.apply_permissions:
			return

		if fieldname in OPTIONAL_FIELDS:
			return

		# Skip field permission check if doctype has no permissions defined
		meta = frappe.get_meta(doctype)
		if not meta.get_permissions(parenttype=parent_doctype):
			return

		# Don't allow querying child table fields if user has only "select" permission
		permission_type = self.get_permission_type(doctype, parent_doctype)
		if parent_doctype and permission_type == "select":
			frappe.throw(
				_("You do not have permission to access child table field: {0}").format(
					frappe.bold(f"{doctype}.{fieldname}")
				),
				frappe.PermissionError,
			)

		permission_source = (
			self._get_filterable_fields if for_filtering else self._get_cached_permitted_fields
		)
		permitted_fields = permission_source(doctype, parent_doctype, permission_type)

		if fieldname not in permitted_fields:
			frappe.throw(
				_("You do not have permission to access field: {0}").format(
					frappe.bold(f"{doctype}.{fieldname}")
				),
				frappe.PermissionError,
				title=_("Permission Error"),
			)

	def _get_cached_permitted_fields(self, doctype: str, parenttype: str | None, permission_type: str) -> set:
		"""Get permitted fields with caching to avoid redundant lookups."""
		cache_key = (doctype, parenttype, permission_type)
		if cache_key not in self.permitted_fields_cache:
			self.permitted_fields_cache[cache_key] = set(
				get_permitted_fields(
					doctype=doctype,
					parenttype=parenttype,
					permission_type=permission_type,
					ignore_virtual=True,
					user=self.user,
				)
			)
		return self.permitted_fields_cache[cache_key]

	def _get_filterable_fields(
		self, doctype: str, parenttype: str | None = None, permission_type: str | None = None
	) -> set:
		"""Get fields that can be used in filters/order by/group by.

		For users with only select permission on parent doctypes, this returns
		all permlevel 0 fields (not just search fields which are used for selected fields).
		For users with read permission, returns standard permitted fields.
		"""
		if permission_type is None:
			permission_type = self.get_permission_type(doctype, parenttype)

		if permission_type == "select":
			meta = frappe.get_meta(doctype)

			# Only allow filtering by all permlevel 0 fields for parent doctypes.
			if meta.istable:
				return set()

			# for select permission on parent doctype, allow all permlevel 0 fields in filters
			cache_key = (doctype, None, "_filterable_select")
			if cache_key not in self.permitted_fields_cache:
				if doctype in PERMITTED_CORE_DOCTYPES:
					# no restrictions - return all valid columns
					self.permitted_fields_cache[cache_key] = set(meta.get_valid_columns())
				else:
					permlevel_0_fields = set(meta.default_fields) | OPTIONAL_FIELDS
					for df in meta.get_fieldnames_with_value(with_field_meta=True, with_virtual_fields=False):
						if df.permlevel == 0:
							permlevel_0_fields.add(df.fieldname)
					self.permitted_fields_cache[cache_key] = permlevel_0_fields
			return self.permitted_fields_cache[cache_key]
		else:
			# for read permission, use standard permitted fields
			return self._get_cached_permitted_fields(doctype, parenttype, permission_type)

	def parse_string_field(self, field: str):
		"""
		Parses a field string into a pypika Field object.

		Handles:
		- *
		- simple_field
		- `quoted_field`
		- tabDocType.simple_field
		- `tabDocType`.`quoted_field`
		- `tabTable Name`.`quoted_field`
		- Aliases for all above formats (e.g., field as alias)
		"""
		if field == "*":
			return self.table.star

		alias = None
		field_part = field
		if " as " in field.lower():  # Case-insensitive check for ' as '
			# Find the last occurrence of ' as ' to handle potential aliases named 'as'
			parts = re.split(r"\s+as\s+", field, flags=re.IGNORECASE)
			if len(parts) > 1:
				field_part = parts[0].strip()
				alias = parts[1].strip().strip("`\"'")  # Remove potential quotes from alias

		match = FIELD_PARSE_REGEX.match(field_part)

		if not match:
			frappe.throw(_("Could not parse field: {0}").format(field))

		# Groups: 1: table_quote, 2: table_name_with_tab, 3: field_quote, 4: field_name
		groups = match.groups()
		table_name = groups[1]  # This will be None if no table part (e.g., just 'field')
		field_name = groups[3]  # This will be the field name (e.g., 'field')

		if table_name:
			doctype_name = table_name[3:] if table_name.startswith("tab") else table_name
			table_obj = frappe.qb.DocType(doctype_name)
			pypika_field = table_obj[field_name]
		else:
			# Simple field name (e.g., `y` or y) - use the main table
			pypika_field = self.table[field_name]

		if alias:
			return pypika_field.as_(alias)
		else:
			return pypika_field

	def parse_fields(
		self, fields: str | list | tuple | set | Field | AggregateFunction | None
	) -> "list[Field | AggregateFunction | Criterion | DynamicTableField | ChildQuery]":
		if not fields:
			return []

		# return if fields is already a pypika Term
		if isinstance(fields, Term):
			return [fields]

		initial_field_list = []
		if isinstance(fields, str):
			# Split comma-separated fields passed as a single string
			initial_field_list.extend(f.strip() for f in COMMA_PATTERN.split(fields) if f.strip())
		elif isinstance(fields, list | tuple | set):
			for item in fields:
				if item is None:
					continue
				if isinstance(item, str) and "," in item:
					# Split comma-separated strings within the list
					initial_field_list.extend(f.strip() for f in COMMA_PATTERN.split(item) if f.strip())
				else:
					# Add non-comma-separated items directly
					initial_field_list.append(item)

		else:
			frappe.throw(_("Fields must be a string, list, tuple, pypika Field, or pypika Function"))

		_fields = []
		# Iterate through the list where each item could be a single field, criterion, or a comma-separated string
		for item in initial_field_list:
			if isinstance(item, str):
				# Sanitize and split potentially comma-separated strings within the list
				if sanitized_item := _validate_select_field(item.strip()):
					parsed = self._parse_single_field_item(sanitized_item)
					if isinstance(parsed, list):  # Result from parsing a child query dict
						_fields.extend(parsed)
					elif parsed:
						_fields.append(parsed)
			else:
				# Handle non-string items (like dict for child query, or pre-parsed Field/Function)
				parsed = self._parse_single_field_item(item)
				if isinstance(parsed, list):
					_fields.extend(parsed)
				elif parsed:
					_fields.append(parsed)

		return _fields

	def _parse_single_field_item(
		self, field: str | Criterion | dict | Field | Term
	) -> "list | Criterion | Field | DynamicTableField | ChildQuery | None":
		"""Parses a single item from the fields list/tuple. Assumes comma-separated strings have already been split."""
		if isinstance(field, Term):
			# Accept any pypika Term (Field, Criterion, ArithmeticExpression, AggregateFunction, etc.)
			return field
		elif isinstance(field, dict):
			# Check if it's a SQL function or operator dictionary
			function_parser = SQLFunctionParser(engine=self)
			if function_parser.is_function_dict(field):
				return function_parser.parse_function(field)
			elif function_parser.is_operator_dict(field):
				return function_parser.parse_operator(field)
			else:
				# Handle child queries defined as dicts {fieldname: [child_fields]}
				_parsed_fields = []
				for child_field, child_fields_list in field.items():
					# Skip uppercase keys as they might be unsupported SQL functions or operators
					if child_field.isupper():
						frappe.throw(
							_("Unsupported function or operator: {0}").format(child_field),
							frappe.ValidationError,
						)

					# Ensure child_fields_list is a list or tuple
					if not isinstance(child_fields_list, list | tuple | set):
						frappe.throw(
							_("Child query fields for '{0}' must be a list or tuple.").format(child_field)
						)
					_parsed_fields.append(ChildQuery(child_field, list(child_fields_list), self.doctype))
				# Return list as a dict entry might represent multiple child queries (though unlikely)
				return _parsed_fields

		# At this point, field must be a string (already validated and sanitized)
		if not isinstance(field, str):
			frappe.throw(_("Invalid field type: {0}").format(type(field)))

		# Try parsing as dynamic field (link/child table access)
		if parsed := DynamicTableField.parse(field, self.doctype):
			return parsed
		# Otherwise, parse as a standard field (simple, quoted, table-qualified, with/without alias)
		else:
			# Note: Comma handling is done in parse_fields before this method is called
			return self.parse_string_field(field)

	def _normalize_postgres_order_field(self, field):
		"""In PostgreSQL order_by fields need to either be in group_by or be aggregated
		when used with select and group_by"""
		current_sql = field.get_sql() if hasattr(field, "get_sql") else str(field)
		if current_sql in self._grouped_queries:
			return field
		clean_name = current_sql.strip('"')
		if clean_name in self.field_aliases:
			return field
		if not isinstance(field, functions.AggregateFunction):
			return functions.Max(field)
		return field

	def apply_group_by(self, group_by: str | None = None):
		parsed_group_by_fields = self._validate_group_by(group_by)
		self._grouped_queries = {
			f.get_sql() if hasattr(f, "get_sql") else str(f) for f in parsed_group_by_fields
		}
		self.query = self.query.groupby(*parsed_group_by_fields)

	def apply_order_by(self, order_by: str | None):
		if not order_by or order_by == DefaultOrderBy:
			self._apply_default_order_by()
			return

		parsed_order_fields = self._validate_order_by(order_by)
		for order_field, order_direction in parsed_order_fields:
			if self.is_postgres and self.is_aggregate_query:
				self.query = self.query.orderby(
					self._normalize_postgres_order_field(order_field), order=order_direction
				)
			else:
				self.query = self.query.orderby(order_field, order=order_direction)

	def _apply_default_order_by(self):
		"""Apply default ordering based on configured DocType metadata"""
		from pypika.enums import Order

		sort_field, sort_order = get_doctype_sort_info(self.doctype)

		# Handle multiple sort fields
		if "," in sort_field:
			for sort_spec in sort_field.split(","):
				if parts := sort_spec.strip().split(maxsplit=1):
					field_name = parts[0]
					spec_order = parts[1].lower() if len(parts) > 1 else sort_order.lower()
					field = self.table[field_name]
					if self.db_query_compat:
						order_direction = Order.desc if spec_order == "desc" else Order.asc
					else:
						order_direction = Order.asc if spec_order == "asc" else Order.desc
					if self.is_postgres and self.is_aggregate_query:
						self.query = self.query.orderby(
							self._normalize_postgres_order_field(field), order=order_direction
						)
					else:
						self.query = self.query.orderby(field, order=order_direction)
		else:
			field = self.table[sort_field]
			if self.db_query_compat:
				order_direction = Order.desc if sort_order.lower() == "desc" else Order.asc
			else:
				order_direction = Order.asc if sort_order.lower() == "asc" else Order.desc
			if self.is_postgres and self.is_aggregate_query:
				self.query = self.query.orderby(
					self._normalize_postgres_order_field(field), order=order_direction
				)
			else:
				self.query = self.query.orderby(field, order=order_direction)

	def _parse_backtick_field_notation(self, field_name: str) -> tuple[str, str] | None:
		"""
		Parse backtick field notation like `tabDocType`.`fieldname` or `tabDocType`.fieldname and return (doctype_name, field_name).
		Uses BACKTICK_FIELD_PARSE_REGEX for fast parsing.
		Returns None if the notation is invalid.
		"""
		match = BACKTICK_FIELD_PARSE_REGEX.match(field_name.strip())
		if not match:
			return None

		return (match.group(1), match.group(3))

	def _validate_and_parse_field_for_clause(self, field_name: str, clause_name: str) -> Field:
		"""
		Common helper to validate and parse field names for GROUP BY and ORDER BY clauses.

		Args:
			field_name: The field name to validate and parse
			clause_name: Name of the SQL clause (for error messages) - 'Group By' or 'Order By'

		Returns:
			Parsed Field object ready for use in pypika query
		"""
		if field_name.isdigit():
			# For numeric field references, return as-is (will be handled by caller)
			return field_name

		# Allow function aliases and field aliases - return as Field (no table prefix)
		if field_name in self.function_aliases or field_name in self.field_aliases:
			return Field(field_name)

		# Parse backtick table.field notation: `tabDocType`.`fieldname`
		if "`" in field_name:
			if parsed := self._parse_backtick_field_notation(field_name):
				table_name, field_name = parsed
				self.check_filter_field_permission(table_name, field_name)
				return frappe.qb.DocType(table_name)[field_name]

			# If parsing failed, fall through to error handling below
			frappe.throw(
				_("{0} has invalid backtick notation: {1}").format(clause_name, field_name),
				frappe.ValidationError,
			)

		# Try parsing as dynamic field (link_field.field or child_table.field)
		dynamic_field = DynamicTableField.parse(field_name, self.doctype, allow_tab_notation=False)
		if dynamic_field:
			# Check permissions for dynamic field
			if isinstance(dynamic_field, ChildTableField):
				self.check_filter_field_permission(
					dynamic_field.doctype, dynamic_field.fieldname, dynamic_field.parent_doctype
				)
			elif isinstance(dynamic_field, LinkTableField):
				# Check permission for the link field in parent doctype
				self.check_filter_field_permission(self.doctype, dynamic_field.link_fieldname)
				# Check permission for the target field in linked doctype
				self.check_filter_field_permission(dynamic_field.doctype, dynamic_field.fieldname)

			# Apply join for the dynamic field
			self.query = dynamic_field.apply_join(self.query, engine=self)
			return dynamic_field.field
		else:
			# Validate as simple field name (alphanumeric + underscore only)
			if not SIMPLE_FIELD_PATTERN.match(field_name):
				frappe.throw(
					_(
						"Invalid field format in {0}: {1}. Use 'field', 'link_field.field', or 'child_table.field'."
					).format(clause_name, field_name),
					frappe.ValidationError,
				)

			# Check permissions for simple field
			self.check_filter_field_permission(self.doctype, field_name)

			# Create Field object for simple field
			return self.table[field_name]

	def _validate_group_by(self, group_by: str) -> list[Field]:
		"""Validate the group_by string argument, apply joins for dynamic fields, and return parsed Field objects."""
		if not isinstance(group_by, str):
			frappe.throw(_("Group By must be a string"), TypeError)

		parsed_fields = []
		for part in group_by.split(","):
			field_name = part.strip()
			if not field_name:
				continue

			parsed_field = self._validate_and_parse_field_for_clause(field_name, "Group By")
			parsed_fields.append(parsed_field)

		return parsed_fields

	def _validate_order_by(self, order_by: str) -> list[tuple[Field | str, Order]]:
		"""Validate the order_by string argument, apply joins for dynamic fields, and return parsed Field objects with directions."""
		if not isinstance(order_by, str):
			frappe.throw(_("Order By must be a string"), TypeError)

		valid_directions = {"asc", "desc"}
		parsed_order_fields = []

		for declaration in order_by.split(","):
			if _order_by := declaration.strip():
				# Extract direction from end of declaration (handles backtick identifiers with spaces)
				# Check if the last word is a valid direction
				parts = _order_by.split()
				direction = None
				field_name = _order_by

				if len(parts) > 1 and parts[-1].lower() in valid_directions:
					# Last part is a direction, so field_name is everything before it
					direction = parts[-1].lower()
					field_name = " ".join(parts[:-1])

				if self.db_query_compat:
					order_direction = Order.desc if direction == "desc" else Order.asc
				else:
					order_direction = Order.asc if direction == "asc" else Order.desc

				parsed_field = self._validate_and_parse_field_for_clause(field_name, "Order By")
				parsed_order_fields.append((parsed_field, order_direction))

				if direction and direction not in valid_directions:
					frappe.throw(
						_("Invalid direction in Order By: {0}. Must be 'ASC' or 'DESC'.").format(direction),
						ValueError,
					)

		return parsed_order_fields

	def check_select_permission(self):
		"""Check if user has select (or read) permission on the doctype"""
		if not frappe.has_permission(
			self.doctype, "select", user=self.user, parent_doctype=self.parent_doctype
		):
			self._raise_permission_error()

	def _raise_permission_error(self, doctype=None):
		frappe.throw(
			_("Insufficient Permission for {0}").format(frappe.bold(doctype or self.doctype)),
			frappe.PermissionError,
		)

	def apply_field_permissions(self):
		"""Filter the list of fields based on permlevel."""
		allowed_fields = []
		parent_permission_type = self.get_permission_type(self.doctype)

		permitted_fields_set = self._get_cached_permitted_fields(
			self.doctype, self.parent_doctype, parent_permission_type
		)

		for field in self.fields:
			if isinstance(field, ChildTableField):
				if parent_permission_type == "select":
					# Skip child table fields if parent permission is only 'select'
					continue

				if field.parent_fieldname:
					parent_meta = frappe.get_meta(self.doctype)
					if parent_meta.get_field(
						field.parent_fieldname
					).permlevel not in parent_meta.get_permlevel_access(
						parent_permission_type, user=self.user
					):
						continue

				# Cache permitted fields for child doctypes if accessed multiple times
				permitted_child_fields_set = self._get_cached_permitted_fields(
					field.doctype,
					field.parent_doctype,
					self.get_permission_type(field.doctype, field.parent_doctype),
				)
				# Check permission for the specific field in the child table
				if field.fieldname in permitted_child_fields_set:
					allowed_fields.append(field)
			elif isinstance(field, LinkTableField):
				# Check permission for the link field *in the parent doctype*
				if field.link_fieldname in permitted_fields_set:
					# Also check if user has permission to read/select the target doctype
					target_doctype = field.doctype
					has_target_perm = frappe.has_permission(
						target_doctype, "select", user=self.user
					) or frappe.has_permission(target_doctype, "read", user=self.user)

					if has_target_perm:
						# Finally, check if the specific field *in the target doctype* is permitted
						permitted_target_fields_set = self._get_cached_permitted_fields(
							target_doctype, None, self.get_permission_type(target_doctype)
						)
						if field.fieldname in permitted_target_fields_set:
							allowed_fields.append(field)
			elif isinstance(field, ChildQuery):
				if parent_permission_type == "select":
					# Skip child queries if parent permission is only 'select'
					continue

				parent_meta = frappe.get_meta(self.doctype)
				if parent_meta.get_field(field.fieldname).permlevel not in parent_meta.get_permlevel_access(
					parent_permission_type, user=self.user
				):
					continue

				# Cache permitted fields for the child doctype of the query
				permitted_child_fields_set = self._get_cached_permitted_fields(
					field.doctype,
					field.parent_doctype,
					self.get_permission_type(field.doctype, field.parent_doctype),
				)
				# Filter the fields *within* the ChildQuery object based on permissions
				field.fields = [f for f in field.fields if f in permitted_child_fields_set]
				# Only add the child query if it still has fields after filtering
				if field.fields:
					allowed_fields.append(field)
			elif isinstance(field, Field):
				if field.name == "*":
					# Expand '*' to include all permitted fields
					# Avoid reparsing '*' recursively by passing the actual list
					allowed_fields.extend(self.parse_fields(list(permitted_fields_set)))
				# Check if the field name is an optional field (like _user_tags) or in permitted fields
				elif field.name in OPTIONAL_FIELDS or field.name in permitted_fields_set:
					allowed_fields.append(field)

			elif isinstance(field, Term):
				# Allow any Term subclass, like LiteralValue (raw SQL expressions), AggregateFunction, PseudoColumnMapper (functions or complex terms)
				allowed_fields.append(field)

		return allowed_fields

	def get_user_permission_conditions(
		self, doctype: str | None = None, table: Table | None = None
	) -> list[Criterion]:
		"""Build conditions for user permissions."""
		doctype = doctype or self.permission_doctype
		table = table or self.permission_table
		conditions = []

		if self.ignore_user_permissions:
			return conditions

		user_permissions = frappe.permissions.get_user_permissions(self.user)

		if not user_permissions:
			return conditions

		doctype_link_fields = self.get_doctype_link_fields(doctype)
		for df in doctype_link_fields:
			if df.get("ignore_user_permissions"):
				continue

			user_permission_values = user_permissions.get(df.get("options"), {})
			if user_permission_values:
				docs = []
				for permission in user_permission_values:
					if not permission.get("applicable_for"):
						docs.append(permission.get("doc"))
					# append docs based on user permission applicable on reference doctype
					# this is useful when getting list of docs from a link field
					# in this case parent doctype of the link
					# will be the reference doctype
					elif df.get("fieldname") == "name" and self.reference_doctype:
						if permission.get("applicable_for") == self.reference_doctype:
							docs.append(permission.get("doc"))
					elif permission.get("applicable_for") == doctype:
						docs.append(permission.get("doc"))

				if docs:
					field_name = df.get("fieldname")
					strict_user_permissions = frappe.get_system_settings("apply_strict_user_permissions")
					if strict_user_permissions:
						conditions.append(table[field_name].isin(docs))
					else:
						empty_value_condition = functions.IfNull(table[field_name], "") == ""
						value_condition = table[field_name].isin(docs)
						conditions.append(empty_value_condition | value_condition)

		return conditions

	def get_doctype_link_fields(self, doctype: str | None = None):
		doctype = doctype or self.permission_doctype
		meta = frappe.get_meta(doctype)
		# append current doctype with fieldname as 'name' as first link field
		doctype_link_fields = [{"options": doctype, "fieldname": "name"}]
		# append other link fields
		doctype_link_fields.extend(meta.get_link_fields())
		return doctype_link_fields

	def add_permission_conditions(self):
		"""
		Logic for adding permission conditions is as follows:

		If no role permissions with read/select exist:
			- apply only share permissions

		If role permissions with read/select exist:
			- apply (if_owner constraints OR user permissions), AND
			- apply permission query conditions

			If if_owner / user permission / permission query constraints are applied,
			final condition = (existing conditions) OR (share condtion)
			(rationale: shared documents trump all other restrictions)

			Else, all documents are accessible based on role permissions.

		For child tables (when parent_doctype is specified):
			- permissions are checked against the parent doctype
			- for non-single parent doctypes: a join to the parent table is added,
		                conditions reference parent fields
			- for single parent doctypes: all permissions are already checked by has_permission,
		                we exit early without adding any conditions
		"""

		if not self.apply_permissions:
			return

		if self.permission_doctype != self.doctype:
			parent_meta = frappe.get_meta(self.permission_doctype)
			if parent_meta.issingle:
				# Child table of single doctype
				# permissions are already checked by has_permission
				return

			self.query = self.query.inner_join(self.permission_table).on(
				self.table.parent == self.permission_table.name
			)

		if condition := self.get_permission_conditions(self.permission_doctype, self.permission_table):
			self.query = self.query.where(condition)

	def get_permission_conditions(self, doctype: str, table: Table) -> Criterion | None:
		role_permissions = frappe.permissions.get_role_permissions(doctype, user=self.user)
		has_role_permission = role_permissions.get("read") or role_permissions.get("select")

		if not has_role_permission:
			# no role permissions, apply only share permissions
			shared_docs = frappe.share.get_shared(doctype, self.user)
			if not shared_docs:
				# no permissions at all
				self._raise_permission_error(doctype=doctype)

			return table.name.isin(shared_docs)

		# build conditions from: if_owner constraint OR user permissions
		conditions = []

		if self.requires_owner_constraint(role_permissions):
			# skip user perm check if owner constraint is required
			conditions.append(table.owner == self.user)
		elif user_perm_conditions := self.get_user_permission_conditions(doctype, table):
			conditions.extend(user_perm_conditions)

		conditions.extend(self.get_permission_query_conditions(doctype))

		if not conditions:
			# no conditions to apply, all documents are accessible
			return

		where_condition = Criterion.all(conditions)

		# since some conditions apply, we need to consider shared docs as well
		shared_docs = frappe.share.get_shared(doctype, self.user)
		if shared_docs:
			# shared docs trump all other restrictions
			where_condition |= table.name.isin(shared_docs)

		return where_condition

	def get_queried_tables(self) -> list[str]:
		"""Extract all table names involved in the current query."""
		tables = []
		for table in self.query._from:
			tables.append(table.get_sql())

		for join in self.query._joins:
			tables.append(join.item.get_sql())
		return list(set(tables))

	def get_permission_query_conditions(self, doctype: str | None = None) -> list["RawCriterion"]:
		"""Add permission query conditions from hooks and server scripts"""
		from frappe.core.doctype.server_script.server_script_utils import get_server_script_map

		doctype = doctype or self.permission_doctype
		conditions = []
		hooks = frappe.get_hooks("permission_query_conditions", {})
		condition_methods = hooks.get(doctype, []) + hooks.get("*", [])

		for method in condition_methods:
			if c := frappe.call(frappe.get_attr(method), self.user, doctype=doctype):
				conditions.append(RawCriterion(f"({c})"))

		active_child_tables = []
		current_tables = self.get_queried_tables()
		if len(current_tables) > 1:
			main_table_name = f"tab{self.doctype}"
			for table_name in current_tables:
				if table_name != main_table_name:
					active_child_tables.append(table_name)

		# Get conditions from server scripts
		if permission_script_name := get_server_script_map().get("permission_query", {}).get(doctype):
			script = frappe.get_doc("Server Script", permission_script_name)
			if condition := script.get_permission_query_conditions(
				self.user, active_child_tables=active_child_tables
			):
				conditions.append(RawCriterion(f"({condition})"))
		return conditions

	def get_permission_type(
		self, doctype: str, parent_doctype: str | None = None
	) -> Literal["read", "select"]:
		"""Get permission type (select/read) based on user permissions.

		Args:
			doctype: The doctype to check permissions for.
			parent_doctype: The parent of the specified doctype. If passed, we assume that `doctype` is a child table,
							and fall back to checking permissions from this parent.

		Returns:
			The allowed permission type (read|select).
		"""
		if parent_doctype:
			return self.get_permission_type(parent_doctype)

		if frappe.only_has_select_perm(doctype, user=self.user):
			return "select"
		return "read"

	def requires_owner_constraint(self, role_permissions):
		"""Return True if "select" or "read" isn't available without being creator."""
		if not role_permissions.get("has_if_owner_enabled"):
			return

		if_owner_perms = role_permissions.get("if_owner")
		if not if_owner_perms:
			return

		# has select or read without if owner, no need for constraint
		for perm_type in ("select", "read"):
			if role_permissions.get(perm_type) and perm_type not in if_owner_perms:
				return

		# not checking if either select or read if present in if_owner_perms
		# because either of those is required to perform a query
		return True

	def build_match_conditions(self, as_condition: bool = True) -> str | list:
		"""Build permission-based conditions for the doctype."""
		if as_condition:
			condition = self.get_permission_conditions(self.doctype, self.table)
			if condition:
				quote_char = "`" if self.is_mariadb else '"'
				return condition.get_sql(with_namespace=True, quote_char=quote_char)
			return ""

		if not self.ignore_user_permissions:
			match_filters = []
			user_permissions = frappe.permissions.get_user_permissions(self.user)
			if not user_permissions:
				return match_filters

			for df in self.get_doctype_link_fields(self.doctype):
				if df.get("ignore_user_permissions"):
					continue

				options = df.get("options")

				if user_permission_values := user_permissions.get(options, {}):
					docs = []

					for permission in user_permission_values:
						applicable_for = permission.get("applicable_for")
						doc = permission.get("doc")
						if not applicable_for:
							docs.append(doc)

						elif df.get("fieldname") == "name" and self.reference_doctype:
							if applicable_for == self.reference_doctype:
								docs.append(doc)

						elif applicable_for == self.doctype:
							docs.append(doc)

					if docs:
						match_filters.append({options: docs})

			return match_filters

		return []

	def build_filter_conditions(
		self, filters, conditions: list, ignore_permissions: bool | None = None
	) -> None:
		if not filters:
			return

		original_apply_permissions = self.apply_permissions
		if ignore_permissions is not None:
			self.apply_permissions = not ignore_permissions

		try:
			criteria_list = []
			self.apply_filters(filters, collect=criteria_list)

			quote_char = "`" if self.is_mariadb else '"'
			for c in criteria_list:
				conditions.append(c.get_sql(with_namespace=True, quote_char=quote_char))
		finally:
			self.apply_permissions = original_apply_permissions

	def _is_field_nullable(self, doctype: str, fieldname: str) -> bool:
		"""Check if a field can contain NULL values."""
		# primary key is never nullable, modified is usually indexed by default and always present
		if fieldname in ("name", "modified", "creation"):
			return False

		try:
			# Use cached meta to avoid recursion when loading meta
			if (meta := frappe.client_cache.get_value(f"doctype_meta::{doctype}")) is None:
				return True

			if (df := meta.get_field(fieldname)) is None:
				return True

		except Exception:
			return True

		if df.fieldtype in ("Check", "Float", "Int", "Currency", "Percent"):
			return False

		if getattr(df, "not_nullable", False):
			return False

		return True

	def _get_ifnull_fallback(self, doctype: str, fieldname: str) -> str:
		"""Get type-appropriate fallback value for NULL comparisons."""
		try:
			meta = frappe.get_meta(doctype)
			df = meta.get_field(fieldname)
		except Exception:
			if frappe.db.db_type == "postgres":
				"""check type and accordingly choose fallback (to avoid postgres type cast errors)"""
				target_table = frappe.utils.get_table_name(doctype)
				info_schema = frappe.qb.Schema("information_schema")
				columns = info_schema.columns
				current_schema = frappe.conf.get("db_schema", "public")
				res = (
					frappe.qb.from_(columns)
					.select(columns.data_type)
					.where(
						(columns.table_name == target_table)
						& (columns.column_name == fieldname)
						& (columns.table_schema == current_schema)
					)
				).run(pluck=True)
				data_type = res[0] if res else None
				if data_type in ("smallint", "bigint", "int", "numeric"):  # can add as needed
					return "0"
			return "''"

		if df is None:
			# Try to get standard field definition
			from frappe.model.meta import get_default_df

			df = get_default_df(fieldname)
			if df is None:
				return "''"

		fieldtype = df.fieldtype

		if fieldtype in ("Link", "Data", "Dynamic Link"):
			return "''"

		if fieldtype in ("Date", "Datetime"):
			return "'0001-01-01'"

		if fieldtype == "Time":
			return "'00:00:00'"

		if fieldtype in ("Float", "Int", "Currency", "Percent", "Check"):
			return "0"

		try:
			db_type_info = frappe.db.type_map.get(fieldtype, ("varchar",))
			if db_type_info:
				db_type = db_type_info[0] if isinstance(db_type_info, tuple | list) else db_type_info
				if db_type in ("varchar", "text", "longtext", "smalltext", "json"):
					return "''"
		except Exception:
			pass

		return "''"

	def _should_apply_ifnull(self, doctype: str, fieldname: str, operator: str, value: Any) -> bool:
		"""Determine if IFNULL wrapping is needed for a filter condition."""
		# Skip this if we don't need db_query compatibility
		if not self.db_query_compat:
			return False

		if not self._is_field_nullable(doctype, fieldname):
			return False

		if value is None:
			return False

		if operator.lower() in ("like", "is"):
			return False

		# For "=" operator, only skip IFNULL if value is truthy (non-empty string, non-zero, etc)
		# When value is empty string "", we need to check for NULL values too
		if operator.lower() == "=" and value:
			return False

		try:
			meta = frappe.get_meta(doctype)
			df = meta.get_field(fieldname)
		except Exception:
			df = None

		is_datetime_field = df and df.fieldtype in ("Date", "Datetime") if df else False
		is_creation_or_modified = fieldname in ("creation", "modified")

		if operator.lower() in (">", ">="):
			# Null values can never be greater than any non-null value
			if is_datetime_field or is_creation_or_modified:
				return False

		if operator.lower() == "between":
			# Between operator never needs to check for null
			# Explanation: Consider SQL -> `COLUMN between X and Y`
			# Actual computation:
			#     for row in rows:
			#     if Y > row.COLUMN > X:
			#         yield row

			# Since Y and X can't be null, null value in column will never match filter, so
			# coalesce is extra cost that prevents index usage
			if is_datetime_field or is_creation_or_modified:
				return False

		if operator.lower() == "in":
			if isinstance(value, list | tuple):
				# if values contain '' or falsy values then only coalesce column
				# for `in` query this is only required if values contain '' or values are empty.
				has_null_or_empty = any(v is None or v == "" for v in value)
				return has_null_or_empty
			return False

		# for `not in` queries we can't be sure as column values might contain null.
		if operator.lower() == "not in":
			return True

		if operator.lower() == "<":
			if is_datetime_field or is_creation_or_modified:
				return True

		return True


class DynamicTableField:
	def __init__(
		self,
		doctype: str,
		fieldname: str,
		parent_doctype: str,
		alias: str | None = None,
	) -> None:
		self.doctype = doctype
		self.fieldname = fieldname
		self.alias = alias
		self.parent_doctype = parent_doctype

	def __str__(self) -> str:
		table_name = f"`tab{self.doctype}`"
		fieldname = f"`{self.fieldname}`"
		if frappe.db.db_type == "postgres":
			table_name = table_name.replace("`", '"')
			fieldname = fieldname.replace("`", '"')
		alias = f"AS {self.alias}" if self.alias else ""
		return f"{table_name}.{fieldname} {alias}".strip()

	@staticmethod
	def parse(field: str, doctype: str, allow_tab_notation: bool = True):
		if "." in field:
			alias = None
			# Handle 'as' alias, case-insensitive, taking the last occurrence
			if " as " in field.lower():
				parts = re.split(r"\s+as\s+", field, flags=re.IGNORECASE)
				if len(parts) > 1:
					field_part = parts[0].strip()
					alias = parts[-1].strip().strip("`\"'")  # Get last part as alias
					field = field_part  # Use the part before alias for further parsing

			child_match = None
			if allow_tab_notation:
				child_match = CHILD_TABLE_FIELD_PATTERN.match(field)

			if child_match:
				child_doctype_name = child_match.group(1)
				child_field = child_match.group(3)

				if child_doctype_name == doctype:
					# Referencing a field in the main doctype using `tabDoctype.field` notation.
					# This should be handled by the standard field parser, not as a DynamicTableField.
					return None
				# Found a child table reference like tabChildDoc.child_field
				# Note: parent_fieldname is None here as it's directly specified via tab notation
				return ChildTableField(child_doctype_name, child_field, doctype, alias=alias)
			else:
				# Try parsing as LinkTableField (link_field.target_field) or ChildTableField (child_field.target_field)
				# This handles patterns not starting with 'tab' prefix
				if "." not in field:  # Should not happen due to outer check, but safety
					return None

				parts = field.split(".", 1)
				if len(parts) != 2:  # Ensure it splits into exactly two parts
					return None
				potential_parent_fieldname, target_fieldname = parts

				# Basic validation for the parts to avoid unnecessary metadata lookups on invalid input
				# We expect simple identifiers here. Quoted/complex names are handled elsewhere or by child_match.
				if (
					not potential_parent_fieldname.replace("_", "").isalnum()
					or not target_fieldname.replace("_", "").isalnum()
				):
					return None

				try:
					meta = frappe.get_meta(doctype)  # Get meta of the *parent* doctype
					# Check if the first part is a valid fieldname in the parent doctype
					if not meta.has_field(potential_parent_fieldname):
						return None  # Not a field in the parent, so not link/child access pattern

					linked_field = meta.get_field(potential_parent_fieldname)
				except Exception:
					return None

				if linked_field:
					linked_doctype = linked_field.options
					if linked_field.fieldtype == "Link":
						# It's a Link field access: parent_doctype.link_fieldname.target_fieldname
						return LinkTableField(
							linked_doctype, target_fieldname, doctype, potential_parent_fieldname, alias=alias
						)
					elif linked_field.fieldtype in frappe.model.table_fields:
						# It's a Child Table field access: parent_doctype.child_table_fieldname.target_fieldname
						return ChildTableField(
							linked_doctype, target_fieldname, doctype, potential_parent_fieldname, alias=alias
						)

		return None

	def apply_select(self, query: QueryBuilder, engine: "Engine" = None) -> QueryBuilder:
		raise NotImplementedError

	def apply_join(self, query: QueryBuilder, engine: "Engine" = None) -> QueryBuilder:
		raise NotImplementedError


class ChildTableField(DynamicTableField):
	def __init__(
		self,
		doctype: str,
		fieldname: str,
		parent_doctype: str,
		parent_fieldname: str | None = None,
		alias: str | None = None,
	) -> None:
		self.doctype = doctype
		self.fieldname = fieldname
		self.alias = alias
		self.parent_doctype = parent_doctype
		self.parent_fieldname = parent_fieldname
		self.table = frappe.qb.DocType(self.doctype)
		self.field = self.table[self.fieldname]

	def apply_select(self, query: QueryBuilder, engine: "Engine" = None) -> QueryBuilder:
		table = frappe.qb.DocType(self.doctype)
		query = self.apply_join(query, engine=engine)
		return query.select(getattr(table, self.fieldname).as_(self.alias or None))

	def apply_join(self, query: QueryBuilder, engine: "Engine" = None) -> QueryBuilder:
		main_table = frappe.qb.DocType(self.parent_doctype)
		if not query.is_joined(self.table):
			join_conditions = (self.table.parent == main_table.name) & (
				self.table.parenttype == self.parent_doctype
			)
			if self.parent_fieldname:
				join_conditions &= self.table.parentfield == self.parent_fieldname
			query = query.left_join(self.table).on(join_conditions)
		return query


class LinkTableField(DynamicTableField):
	def __init__(
		self,
		doctype: str,
		fieldname: str,
		parent_doctype: str,
		link_fieldname: str,
		alias: str | None = None,
	) -> None:
		super().__init__(doctype, fieldname, parent_doctype, alias=alias)
		self.link_fieldname = link_fieldname
		self.table = frappe.qb.DocType(self.doctype)
		self.field = self.table[self.fieldname]

	def apply_select(self, query: QueryBuilder, engine: "Engine" = None) -> QueryBuilder:
		table = frappe.qb.DocType(self.doctype)
		query = self.apply_join(query, engine=engine)
		return query.select(getattr(table, self.fieldname).as_(self.alias or None))

	def apply_join(self, query: QueryBuilder, engine: "Engine" = None) -> QueryBuilder:
		table = frappe.qb.DocType(self.doctype)
		main_table = frappe.qb.DocType(self.parent_doctype)
		if not query.is_joined(table):
			query = query.left_join(table).on(table.name == getattr(main_table, self.link_fieldname))
			if engine and engine.apply_permissions:
				if condition := engine.get_permission_conditions(self.doctype, table):
					query = query.where(condition)

		return query


class ChildQuery:
	def __init__(
		self,
		fieldname: str,
		fields: list,
		parent_doctype: str,
	) -> None:
		field = frappe.get_meta(parent_doctype).get_field(fieldname)
		if field.fieldtype not in frappe.model.table_fields:
			return
		self.fieldname = fieldname
		self.fields = fields
		self.parent_doctype = parent_doctype
		self.doctype = field.options

	def get_query(self, parent_names=None) -> QueryBuilder:
		filters = {
			"parenttype": self.parent_doctype,
			"parentfield": self.fieldname,
			"parent": ["in", parent_names],
		}
		return frappe.qb.get_query(
			self.doctype,
			fields=[*self.fields, "parent", "parentfield"],
			filters=filters,
			order_by="idx asc",
		)


def get_nested_set_hierarchy_result(doctype: str, name: str, hierarchy: str) -> list[str]:
	"""Get matching nodes based on operator."""
	table = frappe.qb.DocType(doctype)
	try:
		lft, rgt = frappe.qb.from_(table).select("lft", "rgt").where(table.name == name).run()[0]
	except IndexError:
		lft, rgt = None, None

	if hierarchy in ("descendants of", "not descendants of", "descendants of (inclusive)"):
		result = (
			frappe.qb.from_(table)
			.select(table.name)
			.where(table.lft > lft)
			.where(table.rgt < rgt)
			.orderby(table.lft, order=Order.asc)
			.run(pluck=True)
		)
		if hierarchy == "descendants of (inclusive)":
			result += [name]
	else:
		# Get ancestor elements of a DocType with a tree structure
		result = (
			frappe.qb.from_(table)
			.select(table.name)
			.where(table.lft < lft)
			.where(table.rgt > rgt)
			.orderby(table.lft, order=Order.desc)
			.run(pluck=True)
		)
	return result


def _is_function_call(field_str: str) -> bool:
	"""Check if a string is a SQL function call."""
	return bool(FUNCTION_CALL_PATTERN.match(field_str))


@lru_cache(maxsize=1024)
def _validate_select_field(field: str):
	"""Validate a field string intended for use in a SELECT clause."""
	if field == "*":
		return field

	if field.isdigit():
		return field

	# Reject SQL functions in string format - use dict syntax instead
	if _is_function_call(field):
		frappe.throw(
			_(
				"SQL functions are not allowed as strings in SELECT: {0}. Use dict syntax like {{'COUNT': '*'}} instead."
			).format(field),
			frappe.ValidationError,
		)

	if ALLOWED_FIELD_PATTERN.match(field):
		return field

	frappe.throw(
		_(
			"Invalid field format for SELECT: {0}. Field names must be simple, backticked, table-qualified, aliased, or '*'."
		).format(field),
		frappe.PermissionError,
	)


class RawCriterion(Term):
	"""A class to represent raw SQL string as a criterion.

	Allows using raw SQL strings in pypika queries:
		frappe.qb.from_("DocType").where(RawCriterion("name like 'a%'"))
	"""

	def __init__(self, sql_string: str):
		self.sql_string = sql_string
		super().__init__()

	def get_sql(self, **kwargs: Any) -> str:
		return self.sql_string

	def __and__(self, other):
		return CombinedRawCriterion(self, other, "AND")

	def __or__(self, other):
		return CombinedRawCriterion(self, other, "OR")

	def __invert__(self):
		return RawCriterion(f"NOT ({self.sql_string})")


class CombinedRawCriterion(RawCriterion):
	def __init__(self, left, right, operator):
		self.left = left
		self.right = right
		self.operator = operator
		super(RawCriterion, self).__init__()

	def get_sql(self, **kwargs: Any) -> str:
		left_sql = self.left.get_sql(**kwargs) if hasattr(self.left, "get_sql") else str(self.left)
		right_sql = self.right.get_sql(**kwargs) if hasattr(self.right, "get_sql") else str(self.right)
		# Wrap entire expression in parentheses to ensure correct operator precedence
		return f"(({left_sql}) {self.operator} ({right_sql}))"


class SQLFunctionParser:
	"""Parser for SQL function dictionaries in query builder fields."""

	def __init__(self, engine):
		self.engine = engine

	def is_function_dict(self, field_dict: dict) -> bool:
		"""Check if a dictionary represents a SQL function definition."""
		function_keys = [k for k in field_dict.keys() if k.lower() != "as"]
		return len(function_keys) == 1 and function_keys[0] in FUNCTION_MAPPING

	def is_operator_dict(self, field_dict: dict) -> bool:
		"""Check if a dictionary represents an arithmetic operator expression.

		Example: {"ADD": [1, 2], "as": "sum"} or {"DIV": ["total", "count"]}
		"""
		operator_keys = [k for k in field_dict.keys() if k.lower() != "as"]
		return len(operator_keys) == 1 and operator_keys[0] in OPERATOR_MAPPING

	def _extract_dict_components(self, d: dict, valid_keys: dict, error_msg: str) -> tuple:
		"""Extract name, alias, and args from function/operator dict."""
		name = None
		alias = None
		args = None

		for key, value in d.items():
			if key.lower() == "as":
				alias = value
			else:
				name = key
				args = value

		if not name:
			frappe.throw(_("Invalid {0} dictionary format").format(error_msg), frappe.ValidationError)

		if name not in valid_keys:
			frappe.throw(_("Unsupported {0}: {1}").format(error_msg, name), frappe.ValidationError)

		if alias:
			self._validate_alias(alias)

		return name, alias, args

	def parse_function(self, function_dict: dict) -> Field:
		"""Parse a SQL function dictionary into a pypika function call."""
		function_name, alias, function_args = self._extract_dict_components(
			function_dict, FUNCTION_MAPPING, "function or invalid field name"
		)

		func_class = FUNCTION_MAPPING[function_name]

		if isinstance(function_args, str):
			parsed_arg = self._parse_and_validate_argument(function_args, function_name=function_name)
			function_call = func_class(parsed_arg)
		elif isinstance(function_args, list):
			parsed_args = []
			for arg in function_args:
				parsed_arg = self._parse_and_validate_argument(arg, function_name=function_name)
				parsed_args.append(parsed_arg)
			function_call = func_class(*parsed_args)
		elif isinstance(function_args, (int | float)):
			function_call = func_class(function_args)
		elif function_args is None:
			try:
				function_call = func_class()
			except TypeError:
				frappe.throw(
					_("Function {0} requires arguments but none were provided").format(function_name),
					frappe.ValidationError,
				)
		else:
			frappe.throw(
				_(
					"Invalid function argument type: {0}. Only strings, numbers, lists, and None are allowed."
				).format(type(function_args).__name__),
				frappe.ValidationError,
			)

		if alias:
			self.engine.function_aliases.add(alias)
			return function_call.as_(alias)
		else:
			return function_call

	def parse_operator(self, operator_dict: dict) -> ArithmeticExpression:
		"""Parse an arithmetic operator dictionary into a pypika ArithmeticExpression.

		Operators require exactly 2 arguments (left and right operands).
		Arguments can be: numbers, field names, nested functions, or nested operators.
		Example: {"DIV": [1, {"NULLIF": [{"LOCATE": ["'test'", "name"]}, 0]}]}
		"""
		operator_name, alias, operator_args = self._extract_dict_components(
			operator_dict, OPERATOR_MAPPING, "operator"
		)

		operator = OPERATOR_MAPPING[operator_name]

		# Operators require exactly 2 arguments (left and right operands)
		if not isinstance(operator_args, list) or len(operator_args) != 2:
			frappe.throw(
				_("Operator {0} requires exactly 2 arguments (left and right operands)").format(
					operator_name
				),
				frappe.ValidationError,
			)

		# Parse and validate both operands (supports nested functions/operators)
		left = self._parse_and_validate_argument(operator_args[0])
		right = self._parse_and_validate_argument(operator_args[1])

		# Wrap raw values (numbers, strings) in ValueWrapper so pypika can process them
		if not isinstance(left, Term):
			left = ValueWrapper(left)
		if not isinstance(right, Term):
			right = ValueWrapper(right)

		expression = ArithmeticExpression(operator=operator, left=left, right=right)

		if alias:
			self.engine.function_aliases.add(alias)
			return expression.as_(alias)
		else:
			return expression

	def _parse_and_validate_argument(self, arg, *, function_name: str | None = None):
		"""Parse and validate a single function/operator argument against SQL injection.

		Supports:
		- Numbers: 1, 2.5, etc.
		- Strings: field names or quoted literals
		- Nested dicts: functions {"COUNT": "name"} or operators {"ADD": [1, 2]}
		"""
		if isinstance(arg, (int | float)):
			return arg
		elif isinstance(arg, str):
			return self._validate_string_argument(arg, function_name=function_name)
		elif isinstance(arg, dict):
			# Recursively handle nested functions and operators
			if self.is_function_dict(arg):
				return self.parse_function(arg)
			elif self.is_operator_dict(arg):
				return self.parse_operator(arg)
			else:
				frappe.throw(
					_("Invalid nested expression: dictionary must represent a function or operator"),
					frappe.ValidationError,
				)
		elif arg is None:
			# None is allowed for some functions
			return arg
		else:
			frappe.throw(
				_("Invalid argument type: {0}. Only strings, numbers, dicts, and None are allowed.").format(
					type(arg).__name__
				),
				frappe.ValidationError,
			)

	def _validate_string_argument(self, arg: str, *, function_name: str | None = None):
		"""Validate string arguments to prevent SQL injection."""
		arg = arg.strip()

		if not arg:
			frappe.throw(_("Empty string arguments are not allowed"), frappe.ValidationError)

		# Special case: allow '*' only for specific functions like COUNT(*)
		if arg == "*":
			if function_name not in STAR_ALLOWED_FUNCTIONS:
				frappe.throw(
					_("'*' is only allowed in {0} SQL function(s)").format(", ".join(STAR_ALLOWED_FUNCTIONS)),
					frappe.ValidationError,
				)
			return Star()

		# Check for string literals (quoted strings)
		if len(arg) >= 2 and arg[0] in ("'", '"') and arg[-1] == arg[0]:
			# note: pypika handles proper escaping with wrap_constant
			return arg[1:-1]

		# Check for backtick notation: `tabDocType`.`fieldname`
		# Parse and return as Field object to preserve field reference in operators
		elif "`" in arg:
			if parsed := self.engine._parse_backtick_field_notation(arg):
				table_name, field_name = parsed
				self.engine.check_select_field_permission(table_name, field_name)
				return Table(f"tab{table_name}")[field_name]
			else:
				frappe.throw(
					_(
						"Invalid argument format: {0}. Only quoted string literals or simple field names are allowed."
					).format(arg),
					frappe.ValidationError,
				)

		# Check if it's a numeric string like "1" (for COUNT(1), etc.)
		elif arg.isdigit():
			return int(arg)

		elif self._is_valid_field_name(arg):
			self._check_function_field_permission(arg)
			return self.engine.table[arg]

		else:
			frappe.throw(
				_(
					"Invalid argument format: {0}. Only quoted string literals or simple field names are allowed."
				).format(arg),
				frappe.ValidationError,
			)

	def _is_valid_field_name(self, name: str) -> bool:
		"""Check if a string is a valid field name."""
		# Field names should only contain alphanumeric characters and underscores
		return SIMPLE_FIELD_PATTERN.match(name) is not None

	def _validate_alias(self, alias: str):
		"""Validate alias name for SQL injection."""
		if not isinstance(alias, str):
			frappe.throw(_("Alias must be a string"), frappe.ValidationError)

		alias = alias.strip()
		if not alias:
			frappe.throw(_("Empty alias is not allowed"), frappe.ValidationError)

		# Alias should be a simple identifier
		# Note: pypika wraps aliases in backticks, so anything without backticks is safe
		if not SIMPLE_FIELD_PATTERN.match(alias):
			frappe.throw(
				_("Invalid alias format: {0}. Alias must be a simple identifier.").format(alias),
				frappe.ValidationError,
			)

	def _check_function_field_permission(self, field_name: str):
		if self.engine.apply_permissions and self.engine.doctype:
			self.engine.check_select_field_permission(self.engine.doctype, field_name)
