chore: Clean remove_prefix since python3.9 is now the minimum Python (#…

…19070)

py-polars/polars/convert/normalize.py

@@ -16,10 +16,6 @@
     from polars.schema import Schema
 
 
-def _remove_prefix(text: str, prefix: str) -> str:
-    return text.removeprefix(prefix)
-
-
 def _simple_json_normalize(
     data: dict[Any, Any] | Sequence[dict[Any, Any] | Any],
     separator: str,
@@ -206,7 +202,7 @@ def normalize_json(
                 new_key = f"{key_string}{separator}{key}"
 
                 if not key_string:
-                    new_key = _remove_prefix(new_key, separator)
+                    new_key = new_key.removeprefix(separator)
 
                 normalize_json(
                     data=value,

py-polars/polars/dataframe/frame.py

@@ -8506,9 +8506,7 @@ def unstack(
             n_cols = step
             n_rows = math.ceil(height / n_cols)
 
-        n_fill = n_cols * n_rows - height
-
-        if n_fill:
+        if n_fill := n_cols * n_rows - height:
             if not isinstance(fill_values, list):
                 fill_values = [fill_values for _ in range(df.width)]
 

py-polars/polars/io/csv/batched_reader.py

@@ -130,8 +130,7 @@ def next_batches(self, n: int) -> list[DataFrame] | None:
         -------
         list of DataFrames
         """
-        batches = self._reader.next_batches(n)
-        if batches is not None:
+        if (batches := self._reader.next_batches(n)) is not None:
             if self.new_columns:
                 return [
                     _update_columns(wrap_df(df), self.new_columns) for df in batches

py-polars/polars/io/delta.py

@@ -347,8 +347,7 @@ def _check_for_unsupported_types(dtypes: list[DataType]) -> None:
     # Note that this overlap check does NOT work correctly for Categorical, so
     # if Categorical is added back to unsupported_types a different check will
     # need to be used.
-    overlap = schema_dtypes & unsupported_types
 
-    if overlap:
+    if overlap := schema_dtypes & unsupported_types:
         msg = f"dataframe contains unsupported data types: {overlap!r}"
         raise TypeError(msg)

py-polars/polars/lazyframe/in_process.py

@@ -32,8 +32,7 @@ def fetch(self) -> DataFrame | None:
         If it is ready, a materialized DataFrame is returned.
         If it is not ready it will return `None`.
         """
-        out = self._inner.fetch()
-        if out is not None:
+        if (out := self._inner.fetch()) is not None:
             return wrap_df(out)
         else:
             return None

py-polars/polars/series/series.py

@@ -1225,7 +1225,7 @@ def __contains__(self, item: Any) -> bool:
             return self.has_nulls()
         return self.implode().list.contains(item).item()
 
-    def __iter__(self) -> Generator[Any, None, None]:
+    def __iter__(self) -> Generator[Any]:
         if self.dtype in (List, Array):
             # TODO: either make a change and return py-native list data here, or find
             #  a faster way to return nested/List series; sequential 'get_index' calls

py-polars/polars/series/utils.py

@@ -100,8 +100,7 @@ def call_expr(func: SeriesMethod) -> SeriesMethod:
     def wrapper(self: Any, *args: P.args, **kwargs: P.kwargs) -> Series:
         s = wrap_s(self._s)
         expr = F.col(s.name)
-        namespace = getattr(self, "_accessor", None)
-        if namespace is not None:
+        if (namespace := getattr(self, "_accessor", None)) is not None:
             expr = getattr(expr, namespace)
         f = getattr(expr, func.__name__)
         return s.to_frame().select_seq(f(*args, **kwargs)).to_series()