refactor(expr-ir): Generate dispatch methods (wip)

[dangotbanned]

What type of PR is this? (check all applicable)

• 💾 Refactor
• ✨ Feature
• 🐛 Bug Fix
• 🔧 Optimization
• 📝 Documentation
• ✅ Test
• 🐳 Other

Related issues

• See for idea refactor(expr-ir): Generate dispatch methods #3068 (comment)
• refactor(expr-ir): Shrinking ExprIR (main) #3066

Checklist

• Code follows style guide (ruff)
• Tests added
• Documented the changes

If you have comments or can explain your changes, please do so below

Will eventually be replacing most of this (so far only cast 😄):

narwhals/narwhals/_plan/protocols.py

Lines 149 to 200 in c72c3e4

	class ExprDispatch(StoresVersion, Protocol[FrameT_contra, R_co, NamespaceT_co]):
	_DISPATCH: ClassVar[Mapping[type[ExprIR], Callable[[Any, ExprIR, Any, str], Any]]] = {
	expr.Column: lambda self, node, frame, name: namespace(self).col(
	node, frame, name
	),
	expr.Literal: lambda self, node, frame, name: namespace(self).lit(
	node, frame, name
	),
	expr.Len: lambda self, node, frame, name: namespace(self).len(node, frame, name),
	# expr.Cast: lambda self, node, frame, name: self.cast(node, frame, name),
	expr.Sort: lambda self, node, frame, name: self.sort(node, frame, name),
	expr.SortBy: lambda self, node, frame, name: self.sort_by(node, frame, name),
	expr.Filter: lambda self, node, frame, name: self.filter(node, frame, name),
	agg.First: lambda self, node, frame, name: self.first(node, frame, name),
	agg.Last: lambda self, node, frame, name: self.last(node, frame, name),
	agg.ArgMin: lambda self, node, frame, name: self.arg_min(node, frame, name),
	agg.ArgMax: lambda self, node, frame, name: self.arg_max(node, frame, name),
	agg.Sum: lambda self, node, frame, name: self.sum(node, frame, name),
	agg.NUnique: lambda self, node, frame, name: self.n_unique(node, frame, name),
	agg.Std: lambda self, node, frame, name: self.std(node, frame, name),
	agg.Var: lambda self, node, frame, name: self.var(node, frame, name),
	agg.Quantile: lambda self, node, frame, name: self.quantile(node, frame, name),
	agg.Count: lambda self, node, frame, name: self.count(node, frame, name),
	agg.Max: lambda self, node, frame, name: self.max(node, frame, name),
	agg.Mean: lambda self, node, frame, name: self.mean(node, frame, name),
	agg.Median: lambda self, node, frame, name: self.median(node, frame, name),
	agg.Min: lambda self, node, frame, name: self.min(node, frame, name),
	expr.BinaryExpr: lambda self, node, frame, name: self.binary_expr(
	node, frame, name
	),
	expr.RollingExpr: lambda self, node, frame, name: self.rolling_expr(
	node, frame, name
	),
	expr.AnonymousExpr: lambda self, node, frame, name: self.map_batches(
	node, frame, name
	),
	expr.FunctionExpr: lambda self, node, frame, name: self._dispatch_function(
	node, frame, name
	),
	# NOTE: Keeping it simple for now
	# When adding other `*_range` functions, this should instead map to `range_expr`
	expr.RangeExpr: lambda self, node, frame, name: namespace(self).int_range(
	node, frame, name
	),
	expr.OrderedWindowExpr: lambda self, node, frame, name: self.over_ordered(
	node, frame, name
	),
	expr.WindowExpr: lambda self, node, frame, name: self.over(node, frame, name),
	expr.Ternary: lambda self, node, frame, name: self.ternary_expr(
	node, frame, name
	),
	}

And then something similar for this group as well:

narwhals/narwhals/_plan/protocols.py

Lines 201 to 222 in c72c3e4

	_DISPATCH_FUNCTION: ClassVar[
	Mapping[type[Function], Callable[[Any, FunctionExpr, Any, str], Any]]
	] = {
	boolean.AnyHorizontal: lambda self, node, frame, name: namespace(
	self
	).any_horizontal(node, frame, name),
	boolean.AllHorizontal: lambda self, node, frame, name: namespace(
	self
	).all_horizontal(node, frame, name),
	F.SumHorizontal: lambda self, node, frame, name: namespace(self).sum_horizontal(
	node, frame, name
	),
	F.MinHorizontal: lambda self, node, frame, name: namespace(self).min_horizontal(
	node, frame, name
	),
	F.MaxHorizontal: lambda self, node, frame, name: namespace(self).max_horizontal(
	node, frame, name
	),
	F.MeanHorizontal: lambda self, node, frame, name: namespace(self).mean_horizontal(
	node, frame, name
	),
	strings.ConcatHorizontal: lambda self, node, frame, name: namespace(