feat(python): add to_init_repr methods to DataFrame and Series

py-polars/docs/source/reference/dataframe/export.rst

@@ -12,6 +12,7 @@ Export DataFrame data to other formats:
     DataFrame.to_arrow
     DataFrame.to_dict
     DataFrame.to_dicts
+    DataFrame.to_init_repr
     DataFrame.to_numpy
     DataFrame.to_pandas
     DataFrame.to_struct

py-polars/docs/source/reference/functions.rst

@@ -15,6 +15,7 @@ Conversion
     from_numpy
     from_pandas
     from_records
+    from_repr
 
 Eager/Lazy functions
 ~~~~~~~~~~~~~~~~~~~~

py-polars/docs/source/reference/series/export.rst

@@ -13,3 +13,4 @@ Export Series data to other formats:
    Series.to_list
    Series.to_numpy
    Series.to_pandas
+   Series.to_init_repr

py-polars/polars/convert.py

@@ -273,6 +273,11 @@ def from_repr(tbl: str) -> DataFrame:
     Currently compound types such as List and Struct are not supported,
     (and neither is Time) though support is planned.
 
+    See Also
+    --------
+    polars.DataFrame.to_init_repr
+    polars.Series.to_init_repr
+
     Examples
     --------
     >>> df = pl.from_repr(

py-polars/polars/dataframe/frame.py

@@ -2106,6 +2106,64 @@ def to_series(self, index: int = 0) -> Series:
             index = len(self.columns) + index
         return wrap_s(self._df.select_at_idx(index))
 
+    def to_init_repr(self, n: int = 1000) -> str:
+        """
+        Convert DataFrame to instantiatable string representation.
+
+        Parameters
+        ----------
+        n
+            Only use first n rows.
+
+        See Also
+        --------
+        polars.Series.to_init_repr
+        polars.from_repr
+
+        Examples
+        --------
+        >>> df = pl.DataFrame(
+        ...     [
+        ...         pl.Series("foo", [1, 2, 3], dtype=pl.UInt8),
+        ...         pl.Series("bar", [6.0, 7.0, 8.0], dtype=pl.Float32),
+        ...         pl.Series("ham", ["a", "b", "c"], dtype=pl.Categorical),
+        ...     ]
+        ... )
+        >>> print(df.to_init_repr())
+        pl.DataFrame(
+            [
+                pl.Series("foo", [1, 2, 3], dtype=pl.UInt8),
+                pl.Series("bar", [6.0, 7.0, 8.0], dtype=pl.Float32),
+                pl.Series("ham", ['a', 'b', 'c'], dtype=pl.Categorical),
+            ]
+        )
+
+        >>> df_from_str_repr = eval(df.to_init_repr())
+        >>> df_from_str_repr
+        shape: (3, 3)
+        ┌─────┬─────┬─────┐
+        │ foo ┆ bar ┆ ham │
+        │ --- ┆ --- ┆ --- │
+        │ u8  ┆ f32 ┆ cat │
+        ╞═════╪═════╪═════╡
+        │ 1   ┆ 6.0 ┆ a   │
+        │ 2   ┆ 7.0 ┆ b   │
+        │ 3   ┆ 8.0 ┆ c   │
+        └─────┴─────┴─────┘
+
+        """
+        output = StringIO()
+        output.write("pl.DataFrame(\n    [\n")
+
+        for i in range(self.width):
+            output.write("        ")
+            output.write(self.to_series(i).to_init_repr(n))
+            output.write(",\n")
+
+        output.write("    ]\n)\n")
+
+        return output.getvalue()
+
     @overload
     def write_json(
         self,

py-polars/polars/series/series.py

@@ -3257,6 +3257,41 @@ def to_pandas(  # noqa: D417
         pd_series.name = self.name
         return pd_series
 
+    def to_init_repr(self, n: int = 1000) -> str:
+        """
+        Convert Series to instantiatable string representation.
+
+        Parameters
+        ----------
+        n
+            Only use first n elements.
+
+        See Also
+        --------
+        polars.Series.to_init_repr
+        polars.from_repr
+
+        Examples
+        --------
+        >>> s = pl.Series("a", [1, 2, None, 4], dtype=pl.Int16)
+        >>> print(s.to_init_repr())
+        pl.Series("a", [1, 2, None, 4], dtype=pl.Int16)
+        >>> s_from_str_repr = eval(s.to_init_repr())
+        >>> s_from_str_repr
+        shape: (4,)
+        Series: 'a' [i16]
+        [
+            1
+            2
+            null
+            4
+        ]
+
+        """
+        return (
+            f'pl.Series("{self.name}", {self.head(n).to_list()}, dtype=pl.{self.dtype})'
+        )
+
     def set(self, filter: Series, value: int | float | str) -> Series:
         """
         Set masked values.

py-polars/tests/unit/test_interop.py

@@ -884,3 +884,33 @@ def test_from_repr() -> None:
         "ident": pl.Utf8,
         "timestamp": pl.Datetime("us", "Asia/Tokyo"),
     }
+
+
+def test_to_init_repr() -> None:
+    # round-trip various types
+    with pl.StringCache():
+        df = (
+            pl.LazyFrame(
+                {
+                    "a": [1, 2, None],
+                    "b": [4.5, 5.5, 6.5],
+                    "c": ["x", "y", "z"],
+                    "d": [True, False, True],
+                    "e": [None, "", None],
+                    "f": [date(2022, 7, 5), date(2023, 2, 5), date(2023, 8, 5)],
+                    "g": [time(0, 0, 0, 1), time(12, 30, 45), time(23, 59, 59, 999000)],
+                    "h": [
+                        datetime(2022, 7, 5, 10, 30, 45, 4560),
+                        datetime(2023, 10, 12, 20, 3, 8, 11),
+                        None,
+                    ],
+                },
+            )
+            .with_columns(
+                pl.col("c").cast(pl.Categorical),
+                pl.col("h").cast(pl.Datetime("ns")),
+            )
+            .collect()
+        )
+
+        assert_frame_equal(eval(df.to_init_repr().replace("datetime.", "")), df)