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contents/barnsley/code/coconut/barnsley.coco

@@ -8,7 +8,7 @@ data Point(x=0, y=0):
         return Point(x, y)
 
 
-def chaos_game(initial_location is Point, hutchinson_op, probabilities):
+def chaos_game(Point(initial_location), hutchinson_op, probabilities):
     point = initial_location
     while True:
         yield (point := choices(hutchinson_op, probabilities) @ point)

contents/euclidean_algorithm/code/coconut/euclidean.coco

@@ -1,18 +1,18 @@
-def euclid_sub(a is int, 0) = a
-addpattern def euclid_sub(0, b is int) = b
+def euclid_sub(int(a), 0) = a
+addpattern def euclid_sub(0, int(b)) = b
 
-addpattern def euclid_sub(a is int, b is int):
+addpattern def euclid_sub(int(a), int(b)):
     if a < b:
         return euclid_sub(a, b - a)
     elif b < a:
         return euclid_sub(a - b, b)
     return a
 
 
-def euclid_mod(a is int, 0) = a
-addpattern def euclid_mod(0, b is int) = b
+def euclid_mod(int(a), 0) = a
+addpattern def euclid_mod(0, int(b)) = b
 
-addpattern def euclid_mod(a is int, b is int) = euclid_mod(b, a % b)
+addpattern def euclid_mod(int(a), int(b)) = euclid_mod(b, a % b)
 
 if __name__ == '__main__':
     print('[#]\nModulus-based euclidean algorithm result:')

contents/flood_fill/code/coconut/flood_fill.coco

@@ -3,24 +3,24 @@ import numpy as np
 
 
 data Point(x, y):
-    def __add__(self, other is Point) = Point(self.x + other.x, self.y + other.y)
+    def __add__(self, Point(other)) = Point(self.x + other.x, self.y + other.y)
 
 
 # This function is necessary, because negative indices wrap around the
 # array in Coconut.
-def inbounds(canvas_shape, location is Point) =
+def inbounds(canvas_shape, Point(location)) =
     min(location) >= 0 and location.x < canvas_shape[0] and location.y < canvas_shape[1]
 
 
-def find_neighbours(canvas, location is Point, old_value):
+def find_neighbours(canvas, Point(location), old_value):
     possible_neighbours = ((Point(0, 1), Point(1, 0), Point(0, -1), Point(-1, 0))
                           |> map$(location.__add__))
 
     yield from possible_neighbours |> filter$(x -> (inbounds(canvas.shape, x)
                                                     and canvas[x] == old_value))
 
 
-def stack_fill(canvas, location is Point, old_value, new_value):
+def stack_fill(canvas,  Point(location), old_value, new_value):
     if new_value == old_value or not inbounds(canvas.shape, location):
         return
 
@@ -33,7 +33,7 @@ def stack_fill(canvas, location is Point, old_value, new_value):
             stack.extend(find_neighbours(canvas, current_location, old_value))
 
 
-def queue_fill(canvas, location is Point, old_value, new_value):
+def queue_fill(canvas, Point(location), old_value, new_value):
     if new_value == old_value or not inbounds(canvas.shape, location):
         return
 
@@ -49,7 +49,7 @@ def queue_fill(canvas, location is Point, old_value, new_value):
             queue.append(neighbour)
 
 
-def recursive_fill(canvas, location is Point, old_value, new_value):
+def recursive_fill(canvas, Point(location), old_value, new_value):
     if new_value == old_value or not inbounds(canvas.shape, location):
         return
 

contents/huffman_encoding/code/coconut/huffman.coco

@@ -4,13 +4,13 @@ from bisect import bisect
 class Tree
 
 data Empty() from Tree
-data Leaf(char, n is int) from Tree:
+data Leaf(char, int(n)) from Tree:
     def __str__(self):
         return f'Leaf({self.char}, {self.n})'
 
     __repr__ = __str__
 
-data Node(left is Tree, right is Tree) from Tree:
+data Node(Tree(left), Tree(right)) from Tree:
     def __str__(self):
         return f'Node({str(self.left)}, {str(self.right)})'
     __repr__ = __str__
@@ -52,7 +52,7 @@ def build_huffman_tree(message):
 
 def build_codebook(Empty(), code='') = []
 addpattern def build_codebook(Leaf(char, n), code='') = [(char, code)]
-addpattern def build_codebook(Node(left, right), code='') = 
+addpattern def build_codebook(Node(left, right), code='') =
     build_codebook(left, code+'0') + build_codebook(right, code+'1')
 
 def huffman_encode(codebook, message):

contents/jarvis_march/code/coconut/jarvis_march.coco

@@ -3,7 +3,7 @@ data point(x=0, y=0):
         return f'({self.x}, {self.y})'
 
 # Is the turn counter-clockwise?
-def counter_clockwise(p1 is point, p2 is point, p3 is point) =
+def counter_clockwise(point(p1), point(p2), point(p3)) =
     (p3.y - p1.y) * (p2.x - p1.x) >= (p2.y - p1.y) * (p3.x - p1.x)
 
 

contents/monte_carlo_integration/code/coconut/monte_carlo.coco

@@ -4,7 +4,7 @@ import random
 data point(x, y):
     def __abs__(self) = (self.x, self.y) |> map$(pow$(?, 2)) |> sum |> math.sqrt
 
-def in_circle(p is point, radius = 1):
+def in_circle(point(p), radius = 1):
     """Return True if the point is in the circle and False otherwise."""
     return abs(p) < radius
 

contents/tree_traversal/code/coconut/tree_traversal.coco

@@ -16,20 +16,20 @@ def dfs_recursive_postorder(Node(value, children)):
 
 def dfs_recursive_inorder_btree(Node(value, children)):
     """A depth first search approach for printing all values in a binary tree."""
-    case len(children):
-        match 2:
+    match len(children):
+        case 2:
             dfs_recursive_inorder_btree(children[0])
             print(value, end=' ')
             dfs_recursive_inorder_btree(children[1])
-        match 1:
+        case 1:
             dfs_recursive_inorder_btree(children[0])
             print(value, end=' ')
-        match 0:
+        case 0:
             print(value, end=' ')
     else:
         print('Invalid binary tree')
 
-def dfs_stack(node is Node):
+def dfs_stack(Node(node)):
     """A depth first approach for printing out all values in a tree using a stack."""
     stack = [node]
     while stack:
@@ -38,7 +38,7 @@ def dfs_stack(node is Node):
         for child in current_node.children:
             stack.append(child)
 
-def bfs_queue(node is Node):
+def bfs_queue(Node(node)):
     """A breadth first search approach for printing out all values in a tree."""
     queue = deque([node])
     while queue: