all: replace generic <> with [] - part 2 (#16536)

examples/binary_search_tree.v

@@ -2,38 +2,38 @@
 
 struct Empty {}
 
-struct Node<T> {
+struct Node[T] {
 	value T
-	left  Tree<T>
-	right Tree<T>
+	left  Tree[T]
+	right Tree[T]
 }
 
-type Tree<T> = Empty | Node<T>
+type Tree[T] = Empty | Node[T]
 
 // return size(number of nodes) of BST
-fn (tree Tree<T>) size<T>() int {
+fn (tree Tree[T]) size[T]() int {
 	return match tree {
 		Empty { 0 }
-		Node<T> { 1 + tree.left.size() + tree.right.size() }
+		Node[T] { 1 + tree.left.size() + tree.right.size() }
 	}
 }
 
 // insert a value to BST
-fn (tree Tree<T>) insert<T>(x T) Tree<T> {
+fn (tree Tree[T]) insert[T](x T) Tree[T] {
 	return match tree {
 		Empty {
-			Node<T>{x, tree, tree}
+			Node[T]{x, tree, tree}
 		}
-		Node<T> {
+		Node[T] {
 			if x == tree.value {
 				tree
 			} else if x < tree.value {
-				Node<T>{
+				Node[T]{
 					...tree
 					left: tree.left.insert(x)
 				}
 			} else {
-				Node<T>{
+				Node[T]{
 					...tree
 					right: tree.right.insert(x)
 				}
@@ -43,12 +43,12 @@ fn (tree Tree<T>) insert<T>(x T) Tree<T> {
 }
 
 // whether able to find a value in BST
-fn (tree Tree<T>) search<T>(x T) bool {
+fn (tree Tree[T]) search[T](x T) bool {
 	return match tree {
 		Empty {
 			false
 		}
-		Node<T> {
+		Node[T] {
 			if x == tree.value {
 				true
 			} else if x < tree.value {
@@ -61,12 +61,12 @@ fn (tree Tree<T>) search<T>(x T) bool {
 }
 
 // find the minimal value of a BST
-fn (tree Tree<T>) min<T>() T {
+fn (tree Tree[T]) min[T]() T {
 	return match tree {
 		Empty {
 			T(1e9)
 		}
-		Node<T> {
+		Node[T] {
 			if tree.value < tree.left.min() {
 				tree.value
 			} else {
@@ -77,25 +77,25 @@ fn (tree Tree<T>) min<T>() T {
 }
 
 // delete a value in BST (if nonexistant do nothing)
-fn (tree Tree<T>) delete<T>(x T) Tree<T> {
+fn (tree Tree[T]) delete[T](x T) Tree[T] {
 	return match tree {
 		Empty {
 			tree
 		}
-		Node<T> {
+		Node[T] {
 			if tree.left !is Empty && tree.right !is Empty {
 				if x < tree.value {
-					Node<T>{
+					Node[T]{
 						...tree
 						left: tree.left.delete(x)
 					}
 				} else if x > tree.value {
-					Node<T>{
+					Node[T]{
 						...tree
 						right: tree.right.delete(x)
 					}
 				} else {
-					Node<T>{
+					Node[T]{
 						...tree
 						value: tree.right.min()
 						right: tree.right.delete(tree.right.min())
@@ -105,7 +105,7 @@ fn (tree Tree<T>) delete<T>(x T) Tree<T> {
 				if x == tree.value {
 					tree.left
 				} else {
-					Node<T>{
+					Node[T]{
 						...tree
 						left: tree.left.delete(x)
 					}
@@ -114,7 +114,7 @@ fn (tree Tree<T>) delete<T>(x T) Tree<T> {
 				if x == tree.value {
 					tree.right
 				} else {
-					Node<T>{
+					Node[T]{
 						...tree
 						right: tree.right.delete(x)
 					}
@@ -125,7 +125,7 @@ fn (tree Tree<T>) delete<T>(x T) Tree<T> {
 }
 
 fn main() {
-	mut tree := Tree<f64>(Empty{})
+	mut tree := Tree[f64](Empty{})
 	vals := [0.2, 0.0, 0.5, 0.3, 0.6, 0.8, 0.9, 1.0, 0.1, 0.4, 0.7]
 	for i in vals {
 		tree = tree.insert(i)

examples/bst_map.v

@@ -15,7 +15,7 @@ fn (a KeyVal) < (b KeyVal) bool {
 }
 
 fn main() {
-	mut bst := datatypes.BSTree<KeyVal>{}
+	mut bst := datatypes.BSTree[KeyVal]{}
 	bst.insert(KeyVal{ key: 1, val: 12 })
 	println(bst.in_order_traversal())
 

examples/compiletime/reflection.v

@@ -7,11 +7,11 @@ struct User {
 
 fn main() {
 	data := 'name=Alice\nage=18'
-	user := decode<User>(data)
+	user := decode[User](data)
 	println(user)
 }
 
-fn decode<T>(data string) T {
+fn decode[T](data string) T {
 	mut result := T{}
 	// compile-time `for` loop
 	// T.fields gives an array of a field metadata type

examples/graphs/bellman-ford.v

@@ -23,7 +23,7 @@ mut:
 
 // building a map of with all edges etc of a graph, represented from a matrix adjacency
 // Input: matrix adjacency --> Output: edges list of src, dest and weight
-fn build_map_edges_from_graph<T>(g [][]T) map[T]EDGE {
+fn build_map_edges_from_graph[T](g [][]T) map[T]EDGE {
 	n := g.len // TOTAL OF NODES for this graph -- its dimmension
 	mut edges_map := map[int]EDGE{} // a graph represented by map of edges
 
@@ -52,7 +52,7 @@ fn print_sol(dist []int) {
 // The main function that finds shortest distances from src
 // to all other vertices using Bellman-Ford algorithm.  The
 // function also detects negative weight cycle
-fn bellman_ford<T>(graph [][]T, src int) {
+fn bellman_ford[T](graph [][]T, src int) {
 	mut edges := build_map_edges_from_graph(graph)
 	// this function was done to adapt a graph representation
 	// by a adjacency matrix, to list of adjacency (using a MAP)

examples/graphs/dijkstra.v

@@ -36,7 +36,7 @@ mut:
 
 // Function to push according to priority ... the lower priority is goes ahead
 // The "push" always sorted in pq
-fn push_pq<T>(mut prior_queue []T, data int, priority int) {
+fn push_pq[T](mut prior_queue []T, data int, priority int) {
 	mut temp := []T{}
 	lenght_pq := prior_queue.len
 
@@ -57,7 +57,7 @@ fn push_pq<T>(mut prior_queue []T, data int, priority int) {
 }
 
 // Change the priority of a value/node ... exist a value, change its priority
-fn updating_priority<T>(mut prior_queue []T, search_data int, new_priority int) {
+fn updating_priority[T](mut prior_queue []T, search_data int, new_priority int) {
 	mut i := 0
 	mut lenght_pq := prior_queue.len
 
@@ -76,7 +76,7 @@ fn updating_priority<T>(mut prior_queue []T, search_data int, new_priority int)
 }
 
 // a single departure or remove from queue
-fn departure_priority<T>(mut prior_queue []T) int {
+fn departure_priority[T](mut prior_queue []T) int {
 	mut x := prior_queue[0].data
 	prior_queue.delete(0) // or .delete_many(0, 1 )
 	return x
@@ -84,7 +84,7 @@ fn departure_priority<T>(mut prior_queue []T) int {
 
 // give a NODE v, return a list with all adjacents
 // Take care, only positive EDGES
-fn all_adjacents<T>(g [][]T, v int) []int {
+fn all_adjacents[T](g [][]T, v int) []int {
 	mut temp := []int{}
 	for i in 0 .. (g.len) {
 		if g[v][i] > 0 {
@@ -95,7 +95,7 @@ fn all_adjacents<T>(g [][]T, v int) []int {
 }
 
 // print the costs from origin up to all nodes
-fn print_solution<T>(dist []T) {
+fn print_solution[T](dist []T) {
 	print('Vertex \tDistance from Source')
 	for node in 0 .. (dist.len) {
 		print('\n ${node} ==> \t ${dist[node]}')
@@ -103,7 +103,7 @@ fn print_solution<T>(dist []T) {
 }
 
 // print all  paths and their cost or weight
-fn print_paths_dist<T>(path []T, dist []T) {
+fn print_paths_dist[T](path []T, dist []T) {
 	print('\n Read the nodes from right to left (a path): \n')
 
 	for node in 1 .. (path.len) {

examples/graphs/minimal_spann_tree_prim.v

@@ -30,7 +30,7 @@ mut:
 
 // Function to push according to priority ... the lower priority is goes ahead
 // The "push" always sorted in pq
-fn push_pq<T>(mut prior_queue []T, data int, priority int) {
+fn push_pq[T](mut prior_queue []T, data int, priority int) {
 	mut temp := []T{}
 	lenght_pq := prior_queue.len
 
@@ -50,7 +50,7 @@ fn push_pq<T>(mut prior_queue []T, data int, priority int) {
 }
 
 // Change the priority of a value/node ... exist a value, change its priority
-fn updating_priority<T>(mut prior_queue []T, search_data int, new_priority int) {
+fn updating_priority[T](mut prior_queue []T, search_data int, new_priority int) {
 	mut i := 0
 	mut lenght_pq := prior_queue.len
 
@@ -72,7 +72,7 @@ fn updating_priority<T>(mut prior_queue []T, search_data int, new_priority int)
 }
 
 // a single departure or remove from queue
-fn departure_priority<T>(mut prior_queue []T) int {
+fn departure_priority[T](mut prior_queue []T) int {
 	mut x := prior_queue[0].data
 	prior_queue.delete(0) // or .delete_many(0, 1 )
 	return x
@@ -80,7 +80,7 @@ fn departure_priority<T>(mut prior_queue []T) int {
 
 // give a NODE v, return a list with all adjacents
 // Take care, only positive EDGES
-fn all_adjacents<T>(g [][]T, v int) []int {
+fn all_adjacents[T](g [][]T, v int) []int {
 	mut temp := []int{}
 	for i in 0 .. (g.len) {
 		if g[v][i] > 0 {

examples/news_fetcher.v

@@ -11,7 +11,7 @@ struct Story {
 }
 
 fn worker_fetch(mut p pool.PoolProcessor, cursor int, worker_id int) voidptr {
-	id := p.get_item<int>(cursor)
+	id := p.get_item[int](cursor)
 	resp := http.get('https://hacker-news.firebaseio.com/v0/item/${id}.json') or {
 		println('failed to fetch data from /v0/item/${id}.json')
 		return pool.no_result

examples/quick_sort.v

@@ -11,12 +11,12 @@ fn main() {
 		arr << rand.intn(gen_max) or { 0 }
 	}
 	println('length of random array is ${arr.len}')
-	println('before quick sort whether array is sorted: ${is_sorted<int>(arr)}')
-	quick_sort<int>(mut arr, 0, arr.len - 1)
-	println('after quick sort whether array is sorted: ${is_sorted<int>(arr)}')
+	println('before quick sort whether array is sorted: ${is_sorted[int](arr)}')
+	quick_sort[int](mut arr, 0, arr.len - 1)
+	println('after quick sort whether array is sorted: ${is_sorted[int](arr)}')
 }
 
-fn quick_sort<T>(mut arr []T, l int, r int) {
+fn quick_sort[T](mut arr []T, l int, r int) {
 	if l >= r {
 		return
 	}
@@ -28,11 +28,11 @@ fn quick_sort<T>(mut arr []T, l int, r int) {
 		}
 	}
 	arr[l], arr[sep] = arr[sep], arr[l]
-	quick_sort<T>(mut arr, l, sep - 1)
-	quick_sort<T>(mut arr, sep + 1, r)
+	quick_sort[T](mut arr, l, sep - 1)
+	quick_sort[T](mut arr, sep + 1, r)
 }
 
-fn is_sorted<T>(arr []T) bool {
+fn is_sorted[T](arr []T) bool {
 	for i in 0 .. arr.len - 1 {
 		if arr[i] > arr[i + 1] {
 			return false