diff --git a/src/graphs/dijkstra.py b/src/graphs/dijkstra.py
new file mode 100644
index 0000000..dd6925b
--- /dev/null
+++ b/src/graphs/dijkstra.py
@@ -0,0 +1,76 @@
+"""
+Dijkstra's Shortest Path Algorithm
+
+Finds the shortest path from a source vertex to all other vertices
+in a weighted graph with non-negative edge weights.
+
+Time Complexity: O((V + E) log V) with a min-heap
+Space Complexity: O(V)
+"""
+
+import heapq
+from typing import Dict, List, Tuple
+
+
+def dijkstra(
+    graph: Dict[str, List[Tuple[str, float]]], source: str
+) -> Tuple[Dict[str, float], Dict[str, str | None]]:
+    """
+    Compute shortest distances from source to all reachable vertices.
+
+    Args:
+        graph: Adjacency list where graph[u] = [(v, weight), ...].
+               Every vertex that appears as a neighbour must also be a key
+               (even if its list is empty).
+        source: Starting vertex.
+
+    Returns:
+        distances: {vertex: shortest_distance} (unreachable → float('inf'))
+        previous:  {vertex: predecessor} for path reconstruction (source → None)
+    """
+    distances: Dict[str, float] = {v: float("inf") for v in graph}
+    previous: Dict[str, str | None] = {v: None for v in graph}
+    distances[source] = 0.0
+
+    # Min-heap: (distance, vertex)
+    heap: List[Tuple[float, str]] = [(0.0, source)]
+
+    while heap:
+        dist_u, u = heapq.heappop(heap)
+
+        # Skip stale entries
+        if dist_u > distances[u]:
+            continue
+
+        for v, weight in graph[u]:
+            alt = dist_u + weight
+            if alt < distances[v]:
+                distances[v] = alt
+                previous[v] = u
+                heapq.heappush(heap, (alt, v))
+
+    return distances, previous
+
+
+def shortest_path(
+    graph: Dict[str, List[Tuple[str, float]]], source: str, target: str
+) -> Tuple[float, List[str]]:
+    """
+    Return the shortest distance and path from source to target.
+
+    Returns:
+        (distance, path) where path is a list of vertices from source to target.
+        If unreachable, returns (float('inf'), []).
+    """
+    distances, previous = dijkstra(graph, source)
+
+    if distances[target] == float("inf"):
+        return float("inf"), []
+
+    path: List[str] = []
+    current: str | None = target
+    while current is not None:
+        path.append(current)
+        current = previous[current]
+
+    return distances[target], list(reversed(path))
diff --git a/tests/test_dijkstra.py b/tests/test_dijkstra.py
new file mode 100644
index 0000000..1aaeb53
--- /dev/null
+++ b/tests/test_dijkstra.py
@@ -0,0 +1,70 @@
+"""Tests for Dijkstra's shortest path algorithm."""
+
+import pytest
+from src.graphs.dijkstra import dijkstra, shortest_path
+
+
+@pytest.fixture
+def simple_graph():
+    """
+    A -> B (1) -> D (3)
+    A -> C (4)
+    B -> C (2)
+    C -> D (1)
+    """
+    return {
+        "A": [("B", 1), ("C", 4)],
+        "B": [("C", 2), ("D", 3)],
+        "C": [("D", 1)],
+        "D": [],
+    }
+
+
+class TestDijkstra:
+    def test_distances(self, simple_graph):
+        dist, _ = dijkstra(simple_graph, "A")
+        assert dist["A"] == 0
+        assert dist["B"] == 1
+        assert dist["C"] == 3  # A->B->C
+        assert dist["D"] == 4  # A->B->C->D
+
+    def test_previous_pointers(self, simple_graph):
+        _, prev = dijkstra(simple_graph, "A")
+        assert prev["A"] is None
+        assert prev["B"] == "A"
+        assert prev["C"] == "B"
+        assert prev["D"] in ("B", "C")  # both paths cost 4
+
+    def test_unreachable_vertex(self):
+        graph = {"A": [("B", 1)], "B": [], "C": []}
+        dist, _ = dijkstra(graph, "A")
+        assert dist["C"] == float("inf")
+
+    def test_single_vertex(self):
+        graph = {"X": []}
+        dist, prev = dijkstra(graph, "X")
+        assert dist["X"] == 0
+        assert prev["X"] is None
+
+
+class TestShortestPath:
+    def test_path_reconstruction(self, simple_graph):
+        cost, path = shortest_path(simple_graph, "A", "D")
+        assert cost == 4
+        assert path in (["A", "B", "C", "D"], ["A", "B", "D"])  # tie
+
+    def test_direct_neighbour(self, simple_graph):
+        cost, path = shortest_path(simple_graph, "A", "B")
+        assert cost == 1
+        assert path == ["A", "B"]
+
+    def test_same_source_target(self, simple_graph):
+        cost, path = shortest_path(simple_graph, "A", "A")
+        assert cost == 0
+        assert path == ["A"]
+
+    def test_unreachable_returns_empty(self):
+        graph = {"A": [], "B": []}
+        cost, path = shortest_path(graph, "A", "B")
+        assert cost == float("inf")
+        assert path == []