Preserve formatting and precision of NumPy unsigned integers

README.md

@@ -766,7 +766,8 @@ column, in which case every column may have different number formatting:
 
 ```
 
-`intfmt` works similarly for integers
+`intfmt` works similarly for integers, including signed and unsigned NumPy
+integer scalars:
 
     >>> print(tabulate([["a",1000],["b",90000]], intfmt=","))
     -  ------

tabulate/__init__.py

@@ -11,6 +11,7 @@
 import io
 from itertools import chain, zip_longest as izip_longest
 import math
+from numbers import Integral
 import re
 import textwrap
 import warnings
@@ -935,9 +936,10 @@ def _isint(string, inttype=int):
     return (
         type(string) is inttype
         or (
-            (hasattr(string, "is_integer") or hasattr(string, "__array__"))
-            and str(type(string)).startswith("<class 'numpy.int")
-        )  # numpy.int64 and similar
+            type(string).__module__ == "numpy"
+            and isinstance(string, Integral)
+            and string.dtype.kind in ("i", "u")
+        )  # NumPy integer scalars, excluding timedelta64
         or (
             isinstance(string, (bytes, str)) and _isconvertible(inttype, string)
         )  # integer as string

test/test_numpy_integers.py

@@ -0,0 +1,46 @@
+"""NumPy integer values retain their precision and integer formatting."""
+
+import pytest
+
+from tabulate import tabulate
+
+
+@pytest.mark.parametrize("input_type", ["list", "numpy", "dataframe"])
+@pytest.mark.parametrize("intfmt", [",", "x"])
+@pytest.mark.parametrize(
+    "dtype",
+    [
+        "int8",
+        "int16",
+        "int32",
+        "int64",
+        "uint8",
+        "uint16",
+        "uint32",
+        "uint64",
+        "longlong",
+        "ulonglong",
+    ],
+)
+def test_numpy_integer_formats(input_type, intfmt, dtype):
+    numpy = pytest.importorskip("numpy")
+    integer_type = getattr(numpy, dtype)
+    value = integer_type(numpy.iinfo(integer_type).max)
+    rows = [[value]]
+    if input_type == "numpy":
+        table = numpy.array(rows, dtype=integer_type)
+    elif input_type == "dataframe":
+        pandas = pytest.importorskip("pandas")
+        table = pandas.DataFrame(rows, dtype=integer_type)
+    else:
+        table = rows
+
+    options = {"tablefmt": "plain", "showindex": False, "intfmt": intfmt, "floatfmt": ".0f"}
+    assert tabulate(table, **options) == tabulate([[int(value)]], **options)
+
+
+def test_numpy_duration_is_not_formatted_as_integer():
+    numpy = pytest.importorskip("numpy")
+    value = numpy.timedelta64(1, "D")
+
+    assert tabulate([[value]], tablefmt="plain", intfmt="x") == str(value)