TST/REF: split test_common into multiple files (#38897)

Author: arw2019

pandas/tests/io/parser/common/test_chunksize.py

@@ -0,0 +1,221 @@
+"""
+Tests that work on both the Python and C engines but do not have a
+specific classification into the other test modules.
+"""
+from io import StringIO
+
+import numpy as np
+import pytest
+
+from pandas.errors import DtypeWarning
+
+from pandas import DataFrame, concat
+import pandas._testing as tm
+
+
+@pytest.mark.parametrize("index_col", [0, "index"])
+def test_read_chunksize_with_index(all_parsers, index_col):
+    parser = all_parsers
+    data = """index,A,B,C,D
+foo,2,3,4,5
+bar,7,8,9,10
+baz,12,13,14,15
+qux,12,13,14,15
+foo2,12,13,14,15
+bar2,12,13,14,15
+"""
+
+    expected = DataFrame(
+        [
+            ["foo", 2, 3, 4, 5],
+            ["bar", 7, 8, 9, 10],
+            ["baz", 12, 13, 14, 15],
+            ["qux", 12, 13, 14, 15],
+            ["foo2", 12, 13, 14, 15],
+            ["bar2", 12, 13, 14, 15],
+        ],
+        columns=["index", "A", "B", "C", "D"],
+    )
+    expected = expected.set_index("index")
+
+    with parser.read_csv(StringIO(data), index_col=0, chunksize=2) as reader:
+        chunks = list(reader)
+    tm.assert_frame_equal(chunks[0], expected[:2])
+    tm.assert_frame_equal(chunks[1], expected[2:4])
+    tm.assert_frame_equal(chunks[2], expected[4:])
+
+
+@pytest.mark.parametrize("chunksize", [1.3, "foo", 0])
+def test_read_chunksize_bad(all_parsers, chunksize):
+    data = """index,A,B,C,D
+foo,2,3,4,5
+bar,7,8,9,10
+baz,12,13,14,15
+qux,12,13,14,15
+foo2,12,13,14,15
+bar2,12,13,14,15
+"""
+    parser = all_parsers
+    msg = r"'chunksize' must be an integer >=1"
+
+    with pytest.raises(ValueError, match=msg):
+        with parser.read_csv(StringIO(data), chunksize=chunksize) as _:
+            pass
+
+
+@pytest.mark.parametrize("chunksize", [2, 8])
+def test_read_chunksize_and_nrows(all_parsers, chunksize):
+    # see gh-15755
+    data = """index,A,B,C,D
+foo,2,3,4,5
+bar,7,8,9,10
+baz,12,13,14,15
+qux,12,13,14,15
+foo2,12,13,14,15
+bar2,12,13,14,15
+"""
+    parser = all_parsers
+    kwargs = {"index_col": 0, "nrows": 5}
+
+    expected = parser.read_csv(StringIO(data), **kwargs)
+    with parser.read_csv(StringIO(data), chunksize=chunksize, **kwargs) as reader:
+        tm.assert_frame_equal(concat(reader), expected)
+
+
+def test_read_chunksize_and_nrows_changing_size(all_parsers):
+    data = """index,A,B,C,D
+foo,2,3,4,5
+bar,7,8,9,10
+baz,12,13,14,15
+qux,12,13,14,15
+foo2,12,13,14,15
+bar2,12,13,14,15
+"""
+    parser = all_parsers
+    kwargs = {"index_col": 0, "nrows": 5}
+
+    expected = parser.read_csv(StringIO(data), **kwargs)
+    with parser.read_csv(StringIO(data), chunksize=8, **kwargs) as reader:
+        tm.assert_frame_equal(reader.get_chunk(size=2), expected.iloc[:2])
+        tm.assert_frame_equal(reader.get_chunk(size=4), expected.iloc[2:5])
+
+        with pytest.raises(StopIteration, match=""):
+            reader.get_chunk(size=3)
+
+
+def test_get_chunk_passed_chunksize(all_parsers):
+    parser = all_parsers
+    data = """A,B,C
+1,2,3
+4,5,6
+7,8,9
+1,2,3"""
+
+    with parser.read_csv(StringIO(data), chunksize=2) as reader:
+        result = reader.get_chunk()
+
+    expected = DataFrame([[1, 2, 3], [4, 5, 6]], columns=["A", "B", "C"])
+    tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize("kwargs", [{}, {"index_col": 0}])
+def test_read_chunksize_compat(all_parsers, kwargs):
+    # see gh-12185
+    data = """index,A,B,C,D
+foo,2,3,4,5
+bar,7,8,9,10
+baz,12,13,14,15
+qux,12,13,14,15
+foo2,12,13,14,15
+bar2,12,13,14,15
+"""
+    parser = all_parsers
+    result = parser.read_csv(StringIO(data), **kwargs)
+    with parser.read_csv(StringIO(data), chunksize=2, **kwargs) as reader:
+        tm.assert_frame_equal(concat(reader), result)
+
+
+def test_read_chunksize_jagged_names(all_parsers):
+    # see gh-23509
+    parser = all_parsers
+    data = "\n".join(["0"] * 7 + [",".join(["0"] * 10)])
+
+    expected = DataFrame([[0] + [np.nan] * 9] * 7 + [[0] * 10])
+    with parser.read_csv(StringIO(data), names=range(10), chunksize=4) as reader:
+        result = concat(reader)
+    tm.assert_frame_equal(result, expected)
+
+
+def test_chunk_begins_with_newline_whitespace(all_parsers):
+    # see gh-10022
+    parser = all_parsers
+    data = "\n hello\nworld\n"
+
+    result = parser.read_csv(StringIO(data), header=None)
+    expected = DataFrame([" hello", "world"])
+    tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.xfail(reason="GH38630, sometimes gives ResourceWarning", strict=False)
+def test_chunks_have_consistent_numerical_type(all_parsers):
+    parser = all_parsers
+    integers = [str(i) for i in range(499999)]
+    data = "a\n" + "\n".join(integers + ["1.0", "2.0"] + integers)
+
+    # Coercions should work without warnings.
+    with tm.assert_produces_warning(None):
+        result = parser.read_csv(StringIO(data))
+
+    assert type(result.a[0]) is np.float64
+    assert result.a.dtype == float
+
+
+def test_warn_if_chunks_have_mismatched_type(all_parsers):
+    warning_type = None
+    parser = all_parsers
+    integers = [str(i) for i in range(499999)]
+    data = "a\n" + "\n".join(integers + ["a", "b"] + integers)
+
+    # see gh-3866: if chunks are different types and can't
+    # be coerced using numerical types, then issue warning.
+    if parser.engine == "c" and parser.low_memory:
+        warning_type = DtypeWarning
+
+    with tm.assert_produces_warning(warning_type):
+        df = parser.read_csv(StringIO(data))
+    assert df.a.dtype == object
+
+
+@pytest.mark.parametrize("iterator", [True, False])
+def test_empty_with_nrows_chunksize(all_parsers, iterator):
+    # see gh-9535
+    parser = all_parsers
+    expected = DataFrame(columns=["foo", "bar"])
+
+    nrows = 10
+    data = StringIO("foo,bar\n")
+
+    if iterator:
+        with parser.read_csv(data, chunksize=nrows) as reader:
+            result = next(iter(reader))
+    else:
+        result = parser.read_csv(data, nrows=nrows)
+
+    tm.assert_frame_equal(result, expected)
+
+
+def test_read_csv_memory_growth_chunksize(all_parsers):
+    # see gh-24805
+    #
+    # Let's just make sure that we don't crash
+    # as we iteratively process all chunks.
+    parser = all_parsers
+
+    with tm.ensure_clean() as path:
+        with open(path, "w") as f:
+            for i in range(1000):
+                f.write(str(i) + "\n")
+
+        with parser.read_csv(path, chunksize=20) as result:
+            for _ in result:
+                pass