Initial commit: 首次建仓，建立目录结构

dashboard/venv/lib/python3.12/site-packages/pandas/tests/internals/test_api.py

@@ -0,0 +1,178 @@
+"""
+Tests for the pseudo-public API implemented in internals/api.py and exposed
+in core.internals
+"""
+
+import datetime
+
+import numpy as np
+import pytest
+
+from pandas.errors import Pandas4Warning
+
+import pandas as pd
+import pandas._testing as tm
+from pandas.api.internals import create_dataframe_from_blocks
+from pandas.core import internals
+from pandas.core.internals import api
+
+
+def test_internals_api():
+    assert internals.make_block is api.make_block
+
+
+def test_namespace():
+    # SUBJECT TO CHANGE
+
+    modules = [
+        "blocks",
+        "concat",
+        "managers",
+        "construction",
+        "api",
+        "ops",
+    ]
+    expected = [
+        "make_block",
+        "BlockManager",
+        "SingleBlockManager",
+        "concatenate_managers",
+    ]
+
+    result = [x for x in dir(internals) if not x.startswith("__")]
+    assert set(result) == set(expected + modules), set(result) ^ set(expected + modules)
+
+
+@pytest.mark.parametrize(
+    "name",
+    [
+        "Block",
+        "ExtensionBlock",
+    ],
+)
+def test_deprecations(name):
+    # GH#55139
+    msg = f"{name} is deprecated.* Use public APIs instead"
+    with tm.assert_produces_warning(Pandas4Warning, match=msg):
+        getattr(internals, name)
+
+
+def test_make_block_2d_with_dti():
+    # GH#41168
+    dti = pd.date_range("2012", periods=3, tz="UTC")
+
+    msg = "make_block is deprecated"
+    with tm.assert_produces_warning(Pandas4Warning, match=msg):
+        blk = api.make_block(dti, placement=[0])
+
+    assert blk.shape == (1, 3)
+    assert blk.values.shape == (1, 3)
+
+
+def test_create_block_manager_from_blocks_deprecated():
+    # GH#33892
+    # If they must, downstream packages should get this from internals.api,
+    #  not internals.
+    msg = (
+        "create_block_manager_from_blocks is deprecated and will be "
+        "removed in a future version. Use public APIs instead"
+    )
+    with tm.assert_produces_warning(Pandas4Warning, match=msg):
+        internals.create_block_manager_from_blocks
+
+
+def test_maybe_infer_ndim_deprecated():
+    # GH#40226
+    msg = "maybe_infer_ndim is deprecated and will be removed in a future version."
+    arr = np.arange(5)
+    bp = pd._libs.internals.BlockPlacement([1])
+    with tm.assert_produces_warning(DeprecationWarning, match=msg):
+        internals.api.maybe_infer_ndim(arr, bp, 1)
+
+
+def test_create_dataframe_from_blocks(float_frame):
+    block = float_frame._mgr.blocks[0]
+    index = float_frame.index.copy()
+    columns = float_frame.columns.copy()
+
+    result = create_dataframe_from_blocks(
+        [(block.values, block.mgr_locs.as_array)], index=index, columns=columns
+    )
+    tm.assert_frame_equal(result, float_frame)
+
+
+def test_create_dataframe_from_blocks_types():
+    df = pd.DataFrame(
+        {
+            "int": list(range(1, 4)),
+            "uint": np.arange(3, 6).astype("uint8"),
+            "float": [2.0, np.nan, 3.0],
+            "bool": np.array([True, False, True]),
+            "boolean": pd.array([True, False, None], dtype="boolean"),
+            "string": list("abc"),
+            "datetime": pd.date_range("20130101", periods=3),
+            "datetimetz": pd.date_range("20130101", periods=3).tz_localize(
+                "Europe/Brussels"
+            ),
+            "timedelta": pd.timedelta_range("1 day", periods=3),
+            "period": pd.period_range("2012-01-01", periods=3, freq="D"),
+            "categorical": pd.Categorical(["a", "b", "a"]),
+            "interval": pd.IntervalIndex.from_tuples([(0, 1), (1, 2), (3, 4)]),
+        }
+    )
+
+    result = create_dataframe_from_blocks(
+        [(block.values, block.mgr_locs.as_array) for block in df._mgr.blocks],
+        index=df.index,
+        columns=df.columns,
+    )
+    tm.assert_frame_equal(result, df)
+
+
+def test_create_dataframe_from_blocks_datetimelike():
+    # extension dtypes that have an exact matching numpy dtype can also be
+    # be passed as a numpy array
+    index, columns = pd.RangeIndex(3), pd.Index(["a", "b", "c", "d"])
+
+    block_array1 = np.arange(
+        datetime.datetime(2020, 1, 1),
+        datetime.datetime(2020, 1, 7),
+        step=datetime.timedelta(1),
+    ).reshape((2, 3))
+    block_array2 = np.arange(
+        datetime.timedelta(1), datetime.timedelta(7), step=datetime.timedelta(1)
+    ).reshape((2, 3))
+    result = create_dataframe_from_blocks(
+        [(block_array1, np.array([0, 2])), (block_array2, np.array([1, 3]))],
+        index=index,
+        columns=columns,
+    )
+    expected = pd.DataFrame(
+        {
+            "a": pd.date_range("2020-01-01", periods=3, unit="us"),
+            "b": pd.timedelta_range("1 days", periods=3, unit="us"),
+            "c": pd.date_range("2020-01-04", periods=3, unit="us"),
+            "d": pd.timedelta_range("4 days", periods=3, unit="us"),
+        }
+    )
+    tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "array",
+    [
+        pd.date_range("2020-01-01", periods=3),
+        pd.date_range("2020-01-01", periods=3, tz="UTC"),
+        pd.period_range("2012-01-01", periods=3, freq="D"),
+        pd.timedelta_range("1 day", periods=3),
+    ],
+)
+def test_create_dataframe_from_blocks_1dEA(array):
+    # ExtensionArrays can be passed as 1D even if stored under the hood as 2D
+    df = pd.DataFrame({"a": array})
+
+    block = df._mgr.blocks[0]
+    result = create_dataframe_from_blocks(
+        [(block.values[0], block.mgr_locs.as_array)], index=df.index, columns=df.columns
+    )
+    tm.assert_frame_equal(result, df)