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feat: Implement item() for Series and Index (#1792)
* feat: Implement item() for Series and Index This commit introduces the `item()` method to both `Series` and `Index` classes. The `item()` method allows you to extract the single value from a Series or Index. It calls `peek(2)` internally and raises a `ValueError` if the Series or Index does not contain exactly one element. This behavior is consistent with pandas. Unit tests have been added to verify the functionality for: - Single-item Series/Index - Multi-item Series/Index (ValueError expected) - Empty Series/Index (ValueError expected) * refactor: Move item() docstrings to third_party This commit moves the docstrings for the `item()` method in `Series` and `Index` to their respective files in the `third_party/bigframes_vendored/pandas/core/` directory. The docstrings have been updated to match the pandas docstrings as closely as possible, while adhering to the existing style in the BigQuery DataFrames repository. This ensures that the BigQuery DataFrames API documentation remains consistent with pandas where applicable. * Apply suggestions from code review * Here's the test I've prepared: **Test: Update item() tests to match pandas behavior** This commit updates the tests for `Series.item()` and `Index.item()` to align more closely with pandas. The changes include: - Comparing the return value of `bigframes_series.item()` and `bigframes_index.item()` with their pandas counterparts. - Asserting that the ValueError messages for multi-item and empty Series/Index cases are identical to those raised by pandas. The expected message is "can only convert an array of size 1 to a Python scalar". * 🦉 Updates from OwlBot post-processor See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md * fix: Ensure item() matches pandas error messages exactly This commit modifies the implementation of `Series.item()` and `Index.item()` to delegate the single-item check and ValueError raising to pandas. Previously, `item()` used `peek(2)` and manually checked the length. The new implementation changes: - `Series.item()` to `self.peek(1).item()` - `Index.item()` to `self.to_series().peek(1).item()` This ensures that the ValueError message ("can only convert an array of size 1 to a Python scalar") is identical to the one produced by pandas when the Series/Index does not contain exactly one element. Existing tests were verified to still pass and accurately cover these conditions by comparing against `pandas.Series.item()` and `pandas.Index.item()`. * 🦉 Updates from OwlBot post-processor See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md * fix: Address feedback for Series.item() and Index.item() This commit incorporates several fixes and improvements based on feedback: 1. **Docstring Style**: * "Examples:" headings in `Series.item()` and `Index.item()` docstrings (in `third_party/`) are now bold (`**Examples:**`). 2. **Implementation of `item()`**: * `Series.item()` now uses `self.peek(2)` and then calls `.item()` on the peeked pandas Series if length is 1, otherwise raises `ValueError("can only convert an array of size 1 to a Python scalar")`. * `Index.item()` now uses `self.to_series().peek(2)` and then calls `.item()` on the peeked pandas Series if length is 1, otherwise raises the same ValueError. This change was made to allow tests to fail correctly when there is more than 1 item, rather than relying on pandas' `peek(1).item()` which would fetch only one item and not detect the multi-item error. 3. **Test Updates**: * Tests for `Series.item()` and `Index.item()` now capture the precise error message from the corresponding pandas method when testing error conditions (multiple items, empty). * The tests now assert that the BigQuery DataFrames methods raise a `ValueError` with a message identical to the one from pandas. 4. **Doctest Fix**: * The doctest for `Series.item()` in `third_party/bigframes_vendored/pandas/core/series.py` has been updated to expect `np.int64(1)` to match pandas behavior. `import numpy as np` was added to the doctest. 5. **Mypy Fix**: * A type annotation (`pd_idx_empty: pd.Index = ...`) was added in `tests/system/small/test_index.py` to resolve a `var-annotated` mypy error. * 🦉 Updates from OwlBot post-processor See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md * split tests into multiple test cases --------- Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com> Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>
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‎bigframes/core/indexes/base.py

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@@ -618,6 +618,10 @@ def to_numpy(self, dtype=None, *, allow_large_results=None, **kwargs) -> np.ndar
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def __len__(self):
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return self.shape[0]
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def item(self):
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# Docstring is in third_party/bigframes_vendored/pandas/core/indexes/base.py
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return self.to_series().peek(2).item()
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def _should_create_datetime_index(block: blocks.Block) -> bool:
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if len(block.index.dtypes) != 1:

‎bigframes/series.py

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@@ -960,6 +960,10 @@ def peek(
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as_series.name = self.name
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return as_series
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def item(self):
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# Docstring is in third_party/bigframes_vendored/pandas/core/series.py
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return self.peek(2).item()
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def nlargest(self, n: int = 5, keep: str = "first") -> Series:
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if keep not in ("first", "last", "all"):
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raise ValueError("'keep must be one of 'first', 'last', or 'all'")

‎tests/system/small/test_index.py

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@@ -12,6 +12,8 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import re
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import numpy
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import pandas as pd
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import pytest
@@ -458,3 +460,42 @@ def test_multiindex_repr_includes_all_names(session):
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)
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index = session.read_pandas(df).set_index(["A", "B"]).index
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assert "names=['A', 'B']" in repr(index)
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def test_index_item(session):
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# Test with a single item
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bf_idx_single = bpd.Index([42], session=session)
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pd_idx_single = pd.Index([42])
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assert bf_idx_single.item() == pd_idx_single.item()
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def test_index_item_with_multiple(session):
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# Test with multiple items
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bf_idx_multiple = bpd.Index([1, 2, 3], session=session)
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pd_idx_multiple = pd.Index([1, 2, 3])
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try:
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pd_idx_multiple.item()
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except ValueError as e:
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expected_message = str(e)
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else:
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raise AssertionError("Expected ValueError from pandas, but didn't get one")
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with pytest.raises(ValueError, match=re.escape(expected_message)):
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bf_idx_multiple.item()
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def test_index_item_with_empty(session):
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# Test with an empty Index
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bf_idx_empty = bpd.Index([], dtype="Int64", session=session)
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pd_idx_empty: pd.Index = pd.Index([], dtype="Int64")
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try:
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pd_idx_empty.item()
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except ValueError as e:
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expected_message = str(e)
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else:
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raise AssertionError("Expected ValueError from pandas, but didn't get one")
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with pytest.raises(ValueError, match=re.escape(expected_message)):
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bf_idx_empty.item()

‎tests/system/small/test_series.py

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@@ -4642,3 +4642,42 @@ def test_series_to_pandas_dry_run(scalars_df_index):
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assert isinstance(result, pd.Series)
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assert len(result) > 0
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def test_series_item(session):
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# Test with a single item
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bf_s_single = bigframes.pandas.Series([42], session=session)
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pd_s_single = pd.Series([42])
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assert bf_s_single.item() == pd_s_single.item()
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def test_series_item_with_multiple(session):
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# Test with multiple items
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bf_s_multiple = bigframes.pandas.Series([1, 2, 3], session=session)
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pd_s_multiple = pd.Series([1, 2, 3])
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try:
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pd_s_multiple.item()
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except ValueError as e:
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expected_message = str(e)
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else:
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raise AssertionError("Expected ValueError from pandas, but didn't get one")
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with pytest.raises(ValueError, match=re.escape(expected_message)):
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bf_s_multiple.item()
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def test_series_item_with_empty(session):
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# Test with an empty Series
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bf_s_empty = bigframes.pandas.Series([], dtype="Int64", session=session)
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pd_s_empty = pd.Series([], dtype="Int64")
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try:
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pd_s_empty.item()
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except ValueError as e:
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expected_message = str(e)
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else:
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raise AssertionError("Expected ValueError from pandas, but didn't get one")
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with pytest.raises(ValueError, match=re.escape(expected_message)):
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bf_s_empty.item()

‎third_party/bigframes_vendored/pandas/core/indexes/base.py

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@@ -1087,6 +1087,25 @@ def unique(self, level: Hashable | int | None = None):
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"""
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raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
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def item(self, *args, **kwargs):
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"""Return the first element of the underlying data as a Python scalar.
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**Examples:**
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>>> import bigframes.pandas as bpd
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>>> bpd.options.display.progress_bar = None
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>>> s = bpd.Series([1], index=['a'])
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>>> s.index.item()
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'a'
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Returns:
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scalar: The first element of Index.
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Raises:
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ValueError: If the data is not length = 1.
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"""
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raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
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def to_numpy(self, dtype, *, allow_large_results=None):
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"""
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A NumPy ndarray representing the values in this Series or Index.

‎third_party/bigframes_vendored/pandas/core/series.py

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@@ -4933,6 +4933,26 @@ def kurt(self):
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"""
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raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
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def item(self: Series, *args, **kwargs):
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"""Return the first element of the underlying data as a Python scalar.
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**Examples:**
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>>> import bigframes.pandas as bpd
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>>> import numpy as np
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>>> bpd.options.display.progress_bar = None
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>>> s = bpd.Series([1])
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>>> s.item()
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np.int64(1)
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Returns:
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scalar: The first element of Series.
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Raises:
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ValueError: If the data is not length = 1.
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"""
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raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
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def items(self):
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"""
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Lazily iterate over (index, value) tuples.

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