Something like h-index?

leetcode/stuff.py

@@ -381,3 +381,39 @@ def collect_min_jumps_from_board(board: list[int]) -> list[int]:
         range_end = range_begin + val + 1
 
     return jumps + [len(board) - 1]
+
+
+def collect_scored_citations(citations: list[int]) -> list[int]:
+    return [
+        i for i, v in enumerate(list(sorted(citations, reverse=True))) if v >= (i + 1)
+    ]
+
+
+def collect_h_index_qualified_citations(citations: list[int]) -> set[int]:
+    census: dict[int, int] = collect_h_index_census_from_citations(citations)
+    return {k for k, v in census.items() if v >= k}
+
+
+def collect_h_index_census_from_citations(citations: list[int]) -> dict[int, int]:
+    census: dict[int, int] = {}
+
+    for n in set(citations):
+        census.setdefault(n, 0)
+
+        for paper in citations:
+            if paper >= n:
+                census[n] += 1
+
+    return census
+
+
+def h_index(citations: list[int]) -> int:
+    last_qualified = None
+
+    for i, citation in enumerate(list(sorted(citations, reverse=True))):
+        if citation >= i + 1:
+            last_qualified = i + 1
+        else:
+            break
+
+    return last_qualified or 0

leetcode/test_stuff.py

@@ -310,3 +310,24 @@ def test_collect_complete_jump_paths_from_board(
 )
 def test_count_min_jumps_from_board(board: list[int], expected: int):
     assert stuff.count_min_jumps_from_board(board) == expected
+
+
+@pytest.mark.parametrize(
+    ("citations", "expected"),
+    [
+        (
+            [3, 0, 6, 1, 5],
+            3,
+        ),
+        (
+            [1, 3, 1],
+            1,
+        ),
+        (
+            [100],
+            1,
+        ),
+    ],
+)
+def test_h_index(citations: list[int], expected: int):
+    assert stuff.h_index(citations) == expected