chore: fix remaining signatures

ibis/backends/__init__.py

@@ -388,7 +388,6 @@ def read_csv(
         -------
         ir.Table
             The just-registered table
-
         """
         raise NotImplementedError(
             f"{self.name} does not support direct registration of CSV data."
@@ -559,6 +558,7 @@ def to_csv(
     def to_delta(
         self,
         expr: ir.Table,
+        /,
         path: str | Path,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,

ibis/backends/athena/__init__.py

@@ -530,6 +530,7 @@ def list_tables(
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,
@@ -556,6 +557,7 @@ def to_pyarrow_batches(
     def to_pyarrow(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/bigquery/__init__.py

@@ -766,6 +766,7 @@ def _to_query(
     def to_pyarrow(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,
@@ -786,6 +787,7 @@ def to_pyarrow(
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/databricks/__init__.py

@@ -513,6 +513,7 @@ def list_tables(
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,
@@ -554,6 +555,7 @@ def batch_producer(con, sql):
     def to_pyarrow(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/flink/__init__.py

@@ -953,6 +953,7 @@ def insert(
     def to_pyarrow(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,
@@ -978,6 +979,7 @@ def to_pyarrow(
     def to_pyarrow_batches(
         self,
         expr: ir.Table,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         chunk_size: int | None = None,

ibis/backends/impala/__init__.py

@@ -1333,6 +1333,8 @@ def _table_command(self, cmd, name, database=None):
     def to_pyarrow(
         self,
         expr: ir.Expr,
+        /,
+        *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,
         **kwargs: Any,
@@ -1355,6 +1357,7 @@ def to_pyarrow(
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/mysql/__init__.py

@@ -501,6 +501,7 @@ def _register_in_memory_table(self, op: ops.InMemoryTable) -> None:
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/polars/__init__.py

@@ -124,7 +124,7 @@ def sql(
 
     def read_csv(
         self,
-        paths: str | Path | list[str | Path] | tuple[str | Path],
+        path: str | Path | list[str | Path] | tuple[str | Path],
         /,
         *,
         table_name: str | None = None,
@@ -134,7 +134,7 @@ def read_csv(
 
         Parameters
         ----------
-        paths
+        path
             The data source. A string or Path to the CSV file.
         table_name
             An optional name to use for the created table. This defaults to
@@ -149,7 +149,7 @@ def read_csv(
         ir.Table
             The just-registered table
         """
-        source_list = normalize_filenames(paths)
+        source_list = normalize_filenames(path)
         # Flatten the list if there's only one element because Polars
         # can't handle glob strings, or compressed CSVs in a single-element list
         if len(source_list) == 1:
@@ -262,7 +262,7 @@ def read_pandas(
 
     def read_parquet(
         self,
-        paths: str | Path | Iterable[str | Path],
+        path: str | Path | Iterable[str | Path],
         /,
         *,
         table_name: str | None = None,
@@ -272,7 +272,7 @@ def read_parquet(
 
         Parameters
         ----------
-        paths
+        path
             The data source(s). May be a path to a file, an iterable of files,
             or directory of parquet files.
         table_name
@@ -290,22 +290,22 @@ def read_parquet(
             The just-registered table
         """
         table_name = table_name or gen_name("read_parquet")
-        if not isinstance(paths, (str, Path)) and len(paths) == 1:
-            paths = paths[0]
+        if not isinstance(path, (str, Path)) and len(path) == 1:
+            path = path[0]
 
-        if not isinstance(paths, (str, Path)) and len(paths) > 1:
+        if not isinstance(path, (str, Path)) and len(path) > 1:
             self._import_pyarrow()
             import pyarrow.dataset as ds
 
-            paths = [normalize_filename(p) for p in paths]
+            path = [normalize_filename(p) for p in path]
             obj = pl.scan_pyarrow_dataset(
-                source=ds.dataset(paths, format="parquet"),
+                source=ds.dataset(path, format="parquet"),
                 **kwargs,
             )
             self._add_table(table_name, obj)
         else:
-            paths = normalize_filename(paths)
-            self._add_table(table_name, pl.scan_parquet(paths, **kwargs))
+            path = normalize_filename(path)
+            self._add_table(table_name, pl.scan_parquet(path, **kwargs))
 
         return self.table(table_name)
 
@@ -480,6 +480,8 @@ def execute(
     def to_polars(
         self,
         expr: ir.Expr,
+        /,
+        *,
         params: Mapping[ir.Expr, object] | None = None,
         limit: int | None = None,
         streaming: bool = False,
@@ -520,6 +522,8 @@ def _to_pyarrow_table(
     def to_pyarrow(
         self,
         expr: ir.Expr,
+        /,
+        *,
         params: Mapping[ir.Expr, object] | None = None,
         limit: int | None = None,
         **kwargs: Any,
@@ -530,6 +534,7 @@ def to_pyarrow(
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/snowflake/__init__.py

@@ -454,6 +454,7 @@ def reconnect(self) -> None:
     def to_pyarrow(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,
@@ -483,6 +484,7 @@ def _fetch_from_cursor(self, cursor, schema: sch.Schema) -> pd.DataFrame:
     def to_pandas_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,
@@ -503,6 +505,7 @@ def to_pandas_batches(
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/sqlite/__init__.py

@@ -320,6 +320,7 @@ def _fetch_from_cursor(
     def to_pyarrow_batches(
         self,
         expr: ir.Expr,
+        /,
         *,
         params: Mapping[ir.Scalar, Any] | None = None,
         limit: int | str | None = None,

ibis/backends/tests/test_signatures.py

@@ -103,34 +103,22 @@ def _scrape_methods(modules, params):
         ),
     ),
     "list_tables": pytest.param(
-        BaseBackend,
-        "list_tables",
-        marks=pytest.mark.notyet(["flink"]),
+        BaseBackend, "list_tables", marks=pytest.mark.notyet(["flink"])
     ),
     "read_csv": pytest.param(
         BaseBackend,
         "read_csv",
-        marks=pytest.mark.notyet(["duckdb", "flink", "pyspark", "datafusion"]),
-    ),
-    "read_delta": pytest.param(
-        BaseBackend,
-        "read_delta",
-        marks=pytest.mark.notyet(["polars", "pyspark"]),
+        marks=pytest.mark.notyet(["duckdb", "pyspark", "datafusion"]),
     ),
+    "read_delta": pytest.param(BaseBackend, "read_delta"),
     "read_json": pytest.param(
-        BaseBackend,
-        "read_json",
-        marks=pytest.mark.notyet(["duckdb", "flink", "pyspark"]),
+        BaseBackend, "read_json", marks=pytest.mark.notyet(["duckdb", "pyspark"])
     ),
     "read_parquet": pytest.param(
-        BaseBackend,
-        "read_parquet",
-        marks=pytest.mark.notyet(["duckdb", "flink"]),
+        BaseBackend, "read_parquet", marks=pytest.mark.notyet(["duckdb"])
     ),
     "to_parquet_dir": pytest.param(
-        BaseBackend,
-        "to_parquet_dir",
-        marks=pytest.mark.notyet(["pyspark"]),
+        BaseBackend, "to_parquet_dir", marks=pytest.mark.notyet(["pyspark"])
     ),
 }