Repository: narwhals-dev/narwhals (python)

Issue:
docs: get `str.to_datetime` to appear in the search bar in docs
Currently, you search "str.to_datetime" in the Narwhals docs, you get "No matching documents"

You need to search "to_datetime" for it to show up

Is there anything we can do to improve this?

Pull request:
docs: improve search in docs
<!--
# Thanks for contributing a pull request! 
## Please make sure you see our contribution guidelines: https://github.com/narwhals-dev/narwhals/blob/main/CONTRIBUTING.md
-->

## What type of PR is this? (check all applicable)

- [ ] 💾 Refactor
- [ ] ✨ Feature
- [ ] 🐛 Bug Fix
- [ ] 🔧 Optimization
- [ ] 📝 Documentation
- [ ] ✅ Test
- [x] 🐳 Other

## Related issues

- Related issue #\<issue number\>
- Closes #1900 

## Checklist

- [ ] Code follows style guide (ruff)
- [ ] Tests added
- [ ] Documented the changes

## If you have comments or can explain your changes, please do so below
Explanation from https://squidfunk.github.io/mkdocs-material/plugins/search/#configuration

Regular expression (taken from the link):
```
[\s\-,:!=\[\]()"/]+    # Matches one or more special characters and whitespace
|                       # OR
(?!\b)(?=[A-Z][a-z])   # Positive lookahead for camelCase word boundaries
|                       # OR
\.(?!\d)               # Period not followed by a number
|                       # OR
&[lg]t;                # HTML entities &lt; and &gt;
```

Patch:
diff --git a/mkdocs.yml b/mkdocs.yml
index e0930ee6..e31b98ab 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -98,7 +98,10 @@ theme:
 
 
 plugins:
-- search
+- search: 
+    # See https://squidfunk.github.io/mkdocs-material/plugins/search/#configuration
+    enabled: true
+    separator: '[\s\-,:!=\[\]()"/]+|(?!\b)(?=[A-Z][a-z])|\.(?!\d)|&[lg]t;'
 - mkdocstrings:
     handlers:
       python:
diff --git a/narwhals/_arrow/dataframe.py b/narwhals/_arrow/dataframe.py
index 0d4206fa..eb72fa3f 100644
--- a/narwhals/_arrow/dataframe.py
+++ b/narwhals/_arrow/dataframe.py
@@ -19,6 +19,7 @@ from narwhals._arrow.utils import select_rows
 from narwhals._expression_parsing import evaluate_into_exprs
 from narwhals.dependencies import is_numpy_array
 from narwhals.utils import Implementation
+from narwhals.utils import Version
 from narwhals.utils import check_column_exists
 from narwhals.utils import generate_temporary_column_name
 from narwhals.utils import is_sequence_but_not_str
@@ -519,8 +520,44 @@ class ArrowDataFrame(CompliantDataFrame, CompliantLazyFrame):
         else:
             return self._from_native_frame(df.slice(abs(n)))
 
-    def lazy(self: Self) -> Self:
-        return self
+    def lazy(self: Self, *, backend: Implementation | None = None) -> CompliantLazyFrame:
+        from narwhals.utils import parse_version
+
+        if backend is None:
+            return self
+        elif backend is Implementation.DUCKDB:
+            import duckdb  # ignore-banned-import
+
+            from narwhals._duckdb.dataframe import DuckDBLazyFrame
+
+            df = self._native_frame  # noqa: F841
+            return DuckDBLazyFrame(
+                df=duckdb.table("df"),
+                backend_version=parse_version(duckdb.__version__),
+                version=self._version,
+            )
+        elif backend is Implementation.POLARS:
+            import polars as pl  # ignore-banned-import
+
+            from narwhals._polars.dataframe import PolarsLazyFrame
+
+            return PolarsLazyFrame(
+                df=pl.from_arrow(self._native_frame).lazy(),  # type: ignore[union-attr]
+                backend_version=parse_version(pl.__version__),
+                version=self._version,
+            )
+        elif backend is Implementation.DASK:
+            import dask  # ignore-banned-import
+            import dask.dataframe as dd  # ignore-banned-import
+
+            from narwhals._dask.dataframe import DaskLazyFrame
+
+            return DaskLazyFrame(
+                native_dataframe=dd.from_pandas(self._native_frame.to_pandas()),
+                backend_version=parse_version(dask.__version__),
+                version=self._version,
+            )
+        raise AssertionError  # pragma: no cover
 
     def collect(self: Self) -> ArrowDataFrame:
         return ArrowDataFrame(
diff --git a/narwhals/_duckdb/dataframe.py b/narwhals/_duckdb/dataframe.py
index f17c8073..6e3699b0 100644
--- a/narwhals/_duckdb/dataframe.py
+++ b/narwhals/_duckdb/dataframe.py
@@ -142,7 +142,14 @@ class DuckDBLazyFrame(CompliantLazyFrame):
         selection = (col for col in self.columns if col not in columns_to_drop)
         return self._from_native_frame(self._native_frame.select(*selection))
 
-    def lazy(self: Self) -> Self:
+    def lazy(self: Self, *, backend: Implementation | None = None) -> Self:
+        # The `backend`` argument has no effect but we keep it here for
+        # backwards compatibility because in `narwhals.stable.v1`
+        # function `.from_native()` will return a DataFrame for DuckDB.
+
+        if backend is not None:  # pragma: no cover
+            msg = "`backend` argument is not supported for DuckDB"
+            raise ValueError(msg)
         return self
 
     def with_columns(
diff --git a/narwhals/_pandas_like/dataframe.py b/narwhals/_pandas_like/dataframe.py
index f0724737..8972deb7 100644
--- a/narwhals/_pandas_like/dataframe.py
+++ b/narwhals/_pandas_like/dataframe.py
@@ -709,8 +709,44 @@ class PandasLikeDataFrame(CompliantDataFrame, CompliantLazyFrame):
         )
 
     # --- lazy-only ---
-    def lazy(self: Self) -> Self:
-        return self
+    def lazy(self: Self, *, backend: Implementation | None = None) -> CompliantLazyFrame:
+        from narwhals.utils import parse_version
+
+        if backend is None:
+            return self
+        elif backend is Implementation.DUCKDB:
+            import duckdb  # ignore-banned-import
+
+            from narwhals._duckdb.dataframe import DuckDBLazyFrame
+
+            df = self._native_frame  # noqa: F841
+            return DuckDBLazyFrame(
+                df=duckdb.table("df"),
+                backend_version=parse_version(duckdb.__version__),
+                version=self._version,
+            )
+        elif backend is Implementation.POLARS:
+            import polars as pl  # ignore-banned-import
+
+            from narwhals._polars.dataframe import PolarsLazyFrame
+
+            return PolarsLazyFrame(
+                df=pl.from_pandas(self._native_frame).lazy(),
+                backend_version=parse_version(pl.__version__),
+                version=self._version,
+            )
+        elif backend is Implementation.DASK:
+            import dask  # ignore-banned-import
+            import dask.dataframe as dd  # ignore-banned-import
+
+            from narwhals._dask.dataframe import DaskLazyFrame
+
+            return DaskLazyFrame(
+                native_dataframe=dd.from_pandas(self._native_frame),
+                backend_version=parse_version(dask.__version__),
+                version=self._version,
+            )
+        raise AssertionError  # pragma: no cover
 
     @property
     def shape(self: Self) -> tuple[int, int]:
diff --git a/narwhals/_polars/dataframe.py b/narwhals/_polars/dataframe.py
index 727912f1..b01894b3 100644
--- a/narwhals/_polars/dataframe.py
+++ b/narwhals/_polars/dataframe.py
@@ -29,6 +29,7 @@ if TYPE_CHECKING:
     from narwhals._polars.group_by import PolarsLazyGroupBy
     from narwhals._polars.series import PolarsSeries
     from narwhals.dtypes import DType
+    from narwhals.typing import CompliantLazyFrame
     from narwhals.utils import Version
 
     T = TypeVar("T")
@@ -231,12 +232,40 @@ class PolarsDataFrame:
             for name, dtype in schema.items()
         }
 
-    def lazy(self: Self) -> PolarsLazyFrame:
-        return PolarsLazyFrame(
-            self._native_frame.lazy(),
-            backend_version=self._backend_version,
-            version=self._version,
-        )
+    def lazy(self: Self, *, backend: Implementation | None = None) -> CompliantLazyFrame:
+        from narwhals.utils import parse_version
+
+        if backend is None or backend is Implementation.POLARS:
+            from narwhals._polars.dataframe import PolarsLazyFrame
+
+            return PolarsLazyFrame(
+                self._native_frame.lazy(),
+                backend_version=self._backend_version,
+                version=self._version,
+            )
+        elif backend is Implementation.DUCKDB:
+            import duckdb  # ignore-banned-import
+
+            from narwhals._duckdb.dataframe import DuckDBLazyFrame
+
+            df = self._native_frame  # noqa: F841
+            return DuckDBLazyFrame(
+                df=duckdb.table("df"),
+                backend_version=parse_version(duckdb.__version__),
+                version=self._version,
+            )
+        elif backend is Implementation.DASK:
+            import dask  # ignore-banned-import
+            import dask.dataframe as dd  # ignore-banned-import
+
+            from narwhals._dask.dataframe import DaskLazyFrame
+
+            return DaskLazyFrame(
+                native_dataframe=dd.from_pandas(self._native_frame.to_pandas()),
+                backend_version=parse_version(dask.__version__),
+                version=self._version,
+            )
+        raise AssertionError  # pragma: no cover
 
     @overload
     def to_dict(self: Self, *, as_series: Literal[True]) -> dict[str, PolarsSeries]: ...
diff --git a/narwhals/dataframe.py b/narwhals/dataframe.py
index d02d589c..805c8cd6 100644
--- a/narwhals/dataframe.py
+++ b/narwhals/dataframe.py
@@ -23,6 +23,7 @@ from narwhals.exceptions import OrderDependentExprError
 from narwhals.exceptions import ShapeError
 from narwhals.schema import Schema
 from narwhals.translate import to_native
+from narwhals.utils import Implementation
 from narwhals.utils import find_stacklevel
 from narwhals.utils import flatten
 from narwhals.utils import generate_repr
@@ -50,7 +51,6 @@ if TYPE_CHECKING:
     from narwhals.typing import IntoExpr
     from narwhals.typing import IntoFrame
     from narwhals.typing import SizeUnit
-    from narwhals.utils import Implementation
 
     PS = ParamSpec("PS")
 
@@ -498,54 +498,72 @@ class DataFrame(BaseFrame[DataFrameT]):
         pa_table = self.to_arrow()
         return pa_table.__arrow_c_stream__(requested_schema=requested_schema)
 
-    def lazy(self: Self) -> LazyFrame[Any]:
-        """Lazify the DataFrame (if possible).
+    def lazy(self: Self, *, backend: Implementation | None = None) -> LazyFrame[Any]:
+        """Restrict available API methods to lazy-only ones.
 
-        If a library does not support lazy execution, then this is a no-op.
+        If `backend` is specified, then a conversion between different backends
+        might be triggered.
+        If a library does not support lazy execution and `backend` is not specified,
+        then this is will only restrict the API to lazy-only operations. This is useful
+        if you want to ensure that you write dataframe-agnostic code which all has
+        the possibility of running entirely lazily.
+
+        Arguments:
+            backend: The (lazy) implementation to convert to. If not specified, and the
+                given library does not support lazy execution, then this will restrict
+                the API to lazy-only operations.
 
         Returns:
             A new LazyFrame.
 
         Examples:
-            Construct pandas, Polars and PyArrow DataFrames:
-
-            >>> import pandas as pd
             >>> import polars as pl
             >>> import pyarrow as pa
             >>> import narwhals as nw
-            >>> from narwhals.typing import IntoFrame
-            >>> data = {"foo": [1, 2, 3], "bar": [6.0, 7.0, 8.0], "ham": ["a", "b", "c"]}
-            >>> df_pd = pd.DataFrame(data)
-            >>> df_pl = pl.DataFrame(data)
-            >>> df_pa = pa.table(data)
-
-            We define a library agnostic function:
+            >>> df_native = pl.DataFrame({"a": [1, 2], "b": [4, 6]})
+            >>> df = nw.from_native(df_native)
 
-            >>> def agnostic_lazy(df_native: IntoFrame) -> IntoFrame:
-            ...     df = nw.from_native(df_native)
-            ...     return df.lazy().to_native()
+            If we call `df.lazy`, we get a `narwhals.LazyFrame` backed by a Polars
+            LazyFrame.
 
-            Note that then, pandas and pyarrow dataframe stay eager, but Polars DataFrame
-            becomes a Polars LazyFrame:
+            >>> df.lazy()  # doctest: +SKIP
+            ┌─────────────────────────────┐
+            |     Narwhals LazyFrame      |
+            |-----------------------------|
+            |<LazyFrame at 0x7F52B9937230>|
+            └─────────────────────────────┘
 
-            >>> agnostic_lazy(df_pd)
-               foo  bar ham
-            0    1  6.0   a
-            1    2  7.0   b
-            2    3  8.0   c
-            >>> agnostic_lazy(df_pl)
-            <LazyFrame ...>
-            >>> agnostic_lazy(df_pa)
-            pyarrow.Table
-            foo: int64
-            bar: double
-            ham: string
-            ----
-            foo: [[1,2,3]]
-            bar: [[6,7,8]]
-            ham: [["a","b","c"]]
+            We can also pass DuckDB as the backend, and then we'll get a
+            `narwhals.LazyFrame` backed by a `duckdb.DuckDBPyRelation`.
+
+            >>> df.lazy(backend=nw.Implementation.DUCKDB)
+            ┌──────────────────┐
+            |Narwhals LazyFrame|
+            |------------------|
+            |┌───────┬───────┐ |
+            |│   a   │   b   │ |
+            |│ int64 │ int64 │ |
+            |├───────┼───────┤ |
+            |│     1 │     4 │ |
+            |│     2 │     6 │ |
+            |└───────┴───────┘ |
+            └──────────────────┘
         """
-        return self._lazyframe(self._compliant_frame.lazy(), level="lazy")
+        supported_lazy_backends = (
+            Implementation.DASK,
+            Implementation.DUCKDB,
+            Implementation.POLARS,
+        )
+        if backend is not None and backend not in supported_lazy_backends:
+            msg = (
+                "Not-supported backend."
+                f"\n\nExpected one of {supported_lazy_backends} or `None`, got {backend}"
+            )
+            raise ValueError(msg)
+        return self._lazyframe(
+            self._compliant_frame.lazy(backend=backend),
+            level="lazy",
+        )
 
     def to_native(self: Self) -> DataFrameT:
         """Convert Narwhals DataFrame to native one.
diff --git a/narwhals/stable/v1/__init__.py b/narwhals/stable/v1/__init__.py
index ffd6fc43..cba00013 100644
--- a/narwhals/stable/v1/__init__.py
+++ b/narwhals/stable/v1/__init__.py
@@ -167,15 +167,25 @@ class DataFrame(NwDataFrame[IntoDataFrameT]):
     def __getitem__(self: Self, item: Any) -> Any:
         return super().__getitem__(item)
 
-    def lazy(self: Self) -> LazyFrame[Any]:
-        """Lazify the DataFrame (if possible).
+    def lazy(self: Self, *, backend: Implementation | None = None) -> LazyFrame[Any]:
+        """Restrict available API methods to lazy-only ones.
 
-        If a library does not support lazy execution, then this is a no-op.
+        If `backend` is specified, then a conversion between different backends
+        might be triggered.
+        If a library does not support lazy execution and `backend` is not specified,
+        then this is will only restrict the API to lazy-only operations. This is useful
+        if you want to ensure that you write dataframe-agnostic code which all has
+        the possibility of running entirely lazily.
+
+        Arguments:
+            backend: The (lazy) implementation to convert to. If not specified, and the
+                given library does not support lazy execution, then this will restrict
+                the API to lazy-only operations.
 
         Returns:
             A new LazyFrame.
         """
-        return super().lazy()  # type: ignore[return-value]
+        return super().lazy(backend=backend)  # type: ignore[return-value]
 
     # Not sure what mypy is complaining about, probably some fancy
     # thing that I need to understand category theory for


Test patch:
diff --git a/tests/frame/lazy_test.py b/tests/frame/lazy_test.py
index df27a4cc..fa9d871d 100644
--- a/tests/frame/lazy_test.py
+++ b/tests/frame/lazy_test.py
@@ -2,17 +2,49 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING
 
+import pytest
+
 import narwhals as nw
 import narwhals.stable.v1 as nw_v1
+from narwhals.utils import Implementation
 
 if TYPE_CHECKING:
     from tests.utils import ConstructorEager
 
 
+data = {"a": [1, 2, 3]}
+
+
 def test_lazy(constructor_eager: ConstructorEager) -> None:
-    df = nw.from_native(constructor_eager({"a": [1, 2, 3]}), eager_only=True)
+    df = nw.from_native(constructor_eager(data), eager_only=True)
     result = df.lazy()
     assert isinstance(result, nw.LazyFrame)
-    df = nw_v1.from_native(constructor_eager({"a": [1, 2, 3]}), eager_only=True)
+    df = nw_v1.from_native(constructor_eager(data), eager_only=True)
     result = df.lazy()
     assert isinstance(result, nw_v1.LazyFrame)
+
+
+@pytest.mark.parametrize(
+    "backend", [Implementation.POLARS, Implementation.DUCKDB, Implementation.DASK]
+)
+def test_lazy_backend(
+    request: pytest.FixtureRequest,
+    constructor_eager: ConstructorEager,
+    backend: Implementation,
+) -> None:
+    if "modin" in str(constructor_eager):
+        request.applymarker(pytest.mark.xfail)
+    if backend is Implementation.DASK:
+        pytest.importorskip("dask")
+    if backend is Implementation.DUCKDB:
+        pytest.importorskip("duckdb")
+    df = nw.from_native(constructor_eager(data), eager_only=True)
+    result = df.lazy(backend=backend)
+    assert isinstance(result, nw.LazyFrame)
+    assert result.implementation == backend
+
+
+def test_lazy_backend_invalid(constructor_eager: ConstructorEager) -> None:
+    df = nw.from_native(constructor_eager(data), eager_only=True)
+    with pytest.raises(ValueError, match="Not-supported backend"):
+        df.lazy(backend=Implementation.PANDAS)