diff --git a/2023-python/output/__init__.py b/2023-python/output/__init__.py
index 3a034d6..1ca7273 100644
--- a/2023-python/output/__init__.py
+++ b/2023-python/output/__init__.py
@@ -80,3 +80,59 @@ def vdbg(seen, h, w):
     """Print-debug visited positions of a matrix"""
     for r in range(h):
         print("".join(["#" if (r, c) in seen else "." for c in range(w)]))
+
+
+"""
+1. Create an array that holds the distance of each vertex from the starting
+   vertex. Initially, set this distance to infinity for all vertices except
+   the starting vertex which should be set to 0.
+2. Create a priority queue (heap) and insert the starting vertex with its
+   distance of 0.
+3. While there are still vertices left in the priority queue, select the vertex
+   with the smallest recorded distance from the starting vertex and visit its
+   neighboring vertices.
+4. For each neighboring vertex, check if it is visited already or not. If it
+   isn’t visited yet, calculate its tentative distance by adding its weight
+   to the smallest distance found so far for its parent/previous node
+   (starting vertex in case of first-level vertices).
+5. If this tentative distance is smaller than previously recorded value
+   (if any), update it in our ‘distances’ array.
+6. Finally, add this visited vertex with its updated distance to our priority
+   queue and repeat step-3 until we have reached our destination or exhausted
+   all nodes.
+"""
+
+
+# https://pieriantraining.com/understanding-dijkstras-algorithm-in-python/
+def dijkstra_algorithm(graph, start_node):
+    def min_distance(distances, visited):
+        min_val = float("inf")
+        min_index = -1
+
+        for i in range(len(distances)):
+            if distances[i] < min_val and i not in visited:
+                min_val = distances[i]
+                min_index = i
+
+        return min_index
+
+    num_nodes = len(graph)
+
+    distances = [float("inf")] * num_nodes
+    visited = []
+
+    distances[start_node] = 0
+
+    for i in range(num_nodes):
+        current_node = min_distance(distances, visited)
+
+        visited.append(current_node)
+
+        for j in range(num_nodes):
+            if graph[current_node][j] != 0:
+
+                new_distance = distances[current_node] + graph[current_node][j]
+
+                if new_distance < distances[j]:
+                    distances[j] = new_distance
+    return distances
diff --git a/2023-python/output/day_17.py b/2023-python/output/day_17.py
new file mode 100644
index 0000000..3c62d90
--- /dev/null
+++ b/2023-python/output/day_17.py
@@ -0,0 +1,100 @@
+from heapq import heappop, heappush
+
+from output import answer  # D, DD, ADJ, ints, mhd, mdbg, vdbg
+
+n = 17
+title = "Clumsy Crucible"
+
+
+@answer(1, "Using std crucible, least heat loss incured: {}")
+def part_1(presolved):
+    return presolved[0]
+
+
+@answer(2, "Using ultra crucible, least heat loss incured: {}")
+def part_2(presolved):
+    return presolved[1]
+
+
+def solve(data):
+    grid = {
+        (r, c): int(col)
+        for r, row in enumerate(data.split())
+        for c, col in enumerate(row)
+    }
+    p1 = least_heat_loss(grid, 1, 3)
+    p2 = least_heat_loss(grid, 4, 10)
+    return p1, p2
+
+
+def least_heat_loss(grid, minsteps, maxsteps):
+    target = max(grid)
+    seen = set()
+    queue = [(0, (0, 0), (0, 1), 0)]
+    while queue:
+        cost, pos, direction, steps = heappop(queue)
+        y, x = pos
+        dy, dx = direction
+
+        if pos == target:
+            return cost
+
+        if ((pos, direction, steps)) in seen:
+            continue
+
+        seen.add((pos, direction, steps))
+
+        if steps >= minsteps:
+            cwdy, cwdx = clockwise(*direction)
+            if (cw := (y + cwdy, x + cwdx)) in grid:
+                cwy, cwx = cw
+                heappush(queue, (cost + grid[cw], (cwy, cwx), (cwdy, cwdx), 1))
+
+            ccwdy, ccwdx = counterclockwise(*direction)
+            if (ccw := (y + ccwdy, x + ccwdx)) in grid:
+                ccwy, ccwx = ccw
+                heappush(queue, (cost + grid[ccw], (ccwy, ccwx), (ccwdy, ccwdx), 1))
+
+        if steps < maxsteps and (fwd := (y + dy, x + dx)) in grid:
+            fwdy, fwdx = fwd
+            heappush(queue, (cost + grid[fwd], (fwdy, fwdx), direction, steps + 1))
+
+    return -1
+
+
+def clockwise(y, x):
+    """
+    >>> clockwise(-1, 0)
+    (0, 1)
+    >>> clockwise(0, 1)
+    (1, 0)
+    >>> clockwise(1, 0)
+    (0, -1)
+    >>> clockwise(0, -1)
+    (-1, 0)
+    """
+    return (x, y) if y == 0 else (x, -y)
+
+
+def counterclockwise(y, x):
+    """
+    >>> counterclockwise(-1, 0)
+    (0, -1)
+    >>> counterclockwise(0, -1)
+    (1, 0)
+    >>> counterclockwise(1, 0)
+    (0, 1)
+    >>> counterclockwise(0, 1)
+    (-1, 0)
+    """
+    return (x, y) if x == 0 else (-x, y)
+
+
+if __name__ == "__main__":
+    with open("./input/17.txt", "r") as f:
+        inp = f.read().strip()
+
+    inp = solve(inp)
+
+    a = part_1(inp)
+    b = part_2(inp)