style: format code in docstrings

ibis/backends/base/df/timecontext.py

@@ -183,9 +183,7 @@ def construct_time_context_aware_series(
     1    2.2
     2    3.3
     Name: value, dtype: float64
-    >>> construct_time_context_aware_series(
-    ...     series, df
-    ... )  # quartodoc: +SKIP # doctest: +SKIP
+    >>> construct_time_context_aware_series(series, df)  # quartodoc: +SKIP # doctest: +SKIP
        time
     0  2017-01-02    1.1
     1  2017-01-03    2.2

ibis/backends/base/sql/__init__.py

@@ -177,7 +177,6 @@ def raw_sql(self, query: str):
         >>> con = ibis.connect("duckdb://")
         >>> with con.raw_sql("SELECT 1") as cursor:
         ...     result = cursor.fetchall()
-        ...
         >>> result
         [(1,)]
         >>> cursor.closed

ibis/backends/base/sql/alchemy/__init__.py

@@ -636,7 +636,6 @@ def raw_sql(self, query: str | sa.sql.ClauseElement):
         >>> con = ibis.connect("duckdb://")
         >>> with con.raw_sql("SELECT 1") as cursor:
         ...     result = cursor.fetchall()
-        ...
         >>> result
         [(1,)]
         >>> cursor.closed

ibis/backends/bigquery/udf/__init__.py

@@ -73,7 +73,6 @@ def python(
         >>> @udf.python(input_type=[dt.double], output_type=dt.double)
         ... def add_one(x):
         ...     return x + 1
-        ...
         >>> print(add_one.sql)
         CREATE TEMPORARY FUNCTION add_one_0(x FLOAT64)
         RETURNS FLOAT64
@@ -84,9 +83,7 @@ def python(
         }
         return add_one(x);
         """;
-        >>> @udf.python(
-        ...     input_type=[dt.double, dt.double], output_type=dt.Array(dt.double)
-        ... )
+        >>> @udf.python(input_type=[dt.double, dt.double], output_type=dt.Array(dt.double))
         ... def my_range(start, stop):
         ...     def gen(start, stop):
         ...         curr = start
@@ -121,9 +118,7 @@ def python(
         """;
         >>> @udf.python(
         ...     input_type=[dt.double, dt.double],
-        ...     output_type=dt.Struct.from_tuples(
-        ...         [("width", "double"), ("height", "double")]
-        ...     ),
+        ...     output_type=dt.Struct.from_tuples([("width", "double"), ("height", "double")]),
         ... )
         ... def my_rectangle(width, height):
         ...     class Rectangle:

ibis/backends/duckdb/__init__.py

@@ -725,10 +725,7 @@ def list_tables(
         >>> con.list_tables(schema="my_schema")
         []
         >>> with con.begin() as c:
-        ...     c.exec_driver_sql(
-        ...         "CREATE TABLE my_schema.baz (a INTEGER)"
-        ...     )  # doctest: +ELLIPSIS
-        ...
+        ...     c.exec_driver_sql("CREATE TABLE my_schema.baz (a INTEGER)")  # doctest: +ELLIPSIS
         <...>
         >>> con.list_tables(schema="my_schema")
         ['baz']
@@ -815,7 +812,6 @@ def read_sqlite(self, path: str | Path, table_name: str | None = None) -> ir.Tab
         ...     con.execute(
         ...         "INSERT INTO t VALUES (1, 'a'), (2, 'b'), (3, 'c')"
         ...     )  # doctest: +ELLIPSIS
-        ...
         <...>
         >>> con = ibis.connect("duckdb://")
         >>> t = con.read_sqlite("/tmp/sqlite.db", table_name="t")
@@ -907,7 +903,6 @@ def attach_sqlite(
         ...     con.execute(
         ...         "INSERT INTO t VALUES (1, 'a'), (2, 'b'), (3, 'c')"
         ...     )  # doctest: +ELLIPSIS
-        ...
         <...>
         >>> con = ibis.connect("duckdb://")
         >>> con.list_tables()
@@ -1126,9 +1121,7 @@ def to_parquet(
 
         Partition on multiple columns.
 
-        >>> con.to_parquet(
-        ...     penguins, tempfile.mkdtemp(), partition_by=("year", "island")
-        ... )
+        >>> con.to_parquet(penguins, tempfile.mkdtemp(), partition_by=("year", "island"))
         """
         self._run_pre_execute_hooks(expr)
         query = self._to_sql(expr, params=params)

ibis/backends/impala/__init__.py

@@ -933,9 +933,7 @@ def insert(
         >>> con.insert(table, table_expr)  # quartodoc: +SKIP # doctest: +SKIP
 
         Completely overwrite contents
-        >>> con.insert(
-        ...     table, table_expr, overwrite=True
-        ... )  # quartodoc: +SKIP # doctest: +SKIP
+        >>> con.insert(table, table_expr, overwrite=True)  # quartodoc: +SKIP # doctest: +SKIP
         """
         table = self.table(table_name, database=database)
         return table.insert(
@@ -964,9 +962,7 @@ def drop_table(
         --------
         >>> table = "my_table"
         >>> db = "operations"
-        >>> con.drop_table(
-        ...     table, database=db, force=True
-        ... )  # quartodoc: +SKIP # doctest: +SKIP
+        >>> con.drop_table(table, database=db, force=True)  # quartodoc: +SKIP # doctest: +SKIP
         """
         statement = DropTable(name, database=database, must_exist=not force)
         self._safe_exec_sql(statement)
@@ -1024,9 +1020,7 @@ def cache_table(self, table_name, *, database=None, pool="default"):
         >>> table = "my_table"
         >>> db = "operations"
         >>> pool = "op_4GB_pool"
-        >>> con.cache_table(
-        ...     "my_table", database=db, pool=pool
-        ... )  # quartodoc: +SKIP # doctest: +SKIP
+        >>> con.cache_table("my_table", database=db, pool=pool)  # quartodoc: +SKIP # doctest: +SKIP
         """
         statement = ddl.CacheTable(table_name, database=database, pool=pool)
         self._safe_exec_sql(statement)

ibis/backends/pyspark/__init__.py

@@ -381,9 +381,7 @@ def create_table(
 
         Examples
         --------
-        >>> con.create_table(
-        ...     "new_table_name", table_expr
-        ... )  # quartodoc: +SKIP # doctest: +SKIP
+        >>> con.create_table("new_table_name", table_expr)  # quartodoc: +SKIP # doctest: +SKIP
         """
         import pandas as pd
         import pyarrow as pa
@@ -507,9 +505,7 @@ def drop_table_or_view(
         --------
         >>> table = "my_table"
         >>> db = "operations"
-        >>> con.drop_table_or_view(
-        ...     table, db, force=True
-        ... )  # quartodoc: +SKIP # doctest: +SKIP
+        >>> con.drop_table_or_view(table, db, force=True)  # quartodoc: +SKIP # doctest: +SKIP
         """
         statement = DropTable(name, database=database, must_exist=not force)
         self.raw_sql(statement.compile())
@@ -557,9 +553,7 @@ def insert(
         >>> con.insert(table, table_expr)  # quartodoc: +SKIP # doctest: +SKIP
 
         # Completely overwrite contents
-        >>> con.insert(
-        ...     table, table_expr, overwrite=True
-        ... )  # quartodoc: +SKIP # doctest: +SKIP
+        >>> con.insert(table, table_expr, overwrite=True)  # quartodoc: +SKIP # doctest: +SKIP
         """
         table = self.table(table_name, database=database)
         return table.insert(

ibis/common/annotations.py

@@ -569,7 +569,6 @@ def annotated(_1=None, _2=None, _3=None, **kwargs):
     >>> @annotated(x=instance_of(int), y=instance_of(str))
     ... def foo(x, y):
     ...     return float(x) + float(y)
-    ...
 
     3. With mixing type annotations and patterns where the latter takes precedence
 
@@ -582,7 +581,6 @@ def annotated(_1=None, _2=None, _3=None, **kwargs):
     >>> @annotated([instance_of(int), instance_of(str)], instance_of(float))
     ... def foo(x, y):
     ...     return float(x) + float(y)
-    ...
 
     Parameters
     ----------

ibis/common/collections.py

@@ -190,7 +190,6 @@ class MapSet(Mapping[K, V]):
     ...
     ...     def __repr__(self):
     ...         return f"MyMap({repr(self._data)})"
-    ...
     >>> m = MyMap(a=1, b=2)
     >>> n = dict(a=1, b=2, c=3)
     >>> m <= n

ibis/common/graph.py

@@ -49,7 +49,6 @@ def _flatten_collections(node: Any) -> Iterator[N]:
     ...     number: int
     ...     string: str
     ...     children: tuple[Node, ...]
-    ...
     >>> a = MyNode(4, "a", ())
     >>>
     >>> b = MyNode(3, "b", ())
@@ -96,7 +95,6 @@ def _recursive_lookup(obj: Any, dct: dict) -> Any:
     ...     number: int
     ...     string: str
     ...     children: tuple[Node, ...]
-    ...
     >>> a = MyNode(4, "a", ())
     >>>
     >>> b = MyNode(3, "b", ())

ibis/common/patterns.py

@@ -658,7 +658,6 @@ class GenericInstanceOf(Slotted, Pattern):
     ...
     ...     def __eq__(self, other):
     ...         return type(self) is type(other) and self.value == other.value
-    ...
     >>> p = GenericInstanceOf(MyNumber[int])
     >>> assert p.match(MyNumber(1), {}) == MyNumber(1)
     >>> assert p.match(MyNumber(1.0), {}) is NoMatch
@@ -802,7 +801,6 @@ class GenericCoercedTo(Slotted, Pattern):
     ...             return cls(float(value))
     ...         else:
     ...             raise CoercionError(f"Cannot coerce to {T}")
-    ...
     >>> p = GenericCoercedTo(MyNumber[int])
     >>> assert p.match(3.14, {}) == MyNumber(3)
     >>> assert p.match("15", {}) == MyNumber(15)
@@ -1571,7 +1569,6 @@ def pattern(obj: AnyType) -> Pattern:
     >>> @pattern
     ... def as_int(x, context):
     ...     return int(x)
-    ...
     >>>
     >>> assert as_int.match(1, {}) == 1
 

ibis/common/typing.py

@@ -102,14 +102,12 @@ def get_type_params(obj: Any) -> dict[str, type]:
     >>>
     >>> class MyList(List[T]):
     ...     ...
-    ...
     >>>
     >>> get_type_params(MyList[int])
     {'T': <class 'int'>}
     >>>
     >>> class MyDict(Dict[T, U]):
     ...     ...
-    ...
     >>>
     >>> get_type_params(MyDict[int, str])
     {'T': <class 'int'>, 'U': <class 'str'>}
@@ -147,7 +145,6 @@ def get_bound_typevars(obj: Any) -> dict[TypeVar, tuple[str, type]]:
     >>> class MyStruct(Generic[T, U]):
     ...     a: T
     ...     b: U
-    ...
     >>> get_bound_typevars(MyStruct[int, str])
     {~T: ('a', <class 'int'>), ~U: ('b', <class 'str'>)}
     >>>
@@ -157,7 +154,6 @@ def get_bound_typevars(obj: Any) -> dict[TypeVar, tuple[str, type]]:
     ...     @property
     ...     def myprop(self) -> U:
     ...         ...
-    ...
     >>> get_bound_typevars(MyStruct[float, bytes])
     {~T: ('a', <class 'float'>), ~U: ('myprop', <class 'bytes'>)}
     """

ibis/expr/api.py

@@ -1278,7 +1278,6 @@ def read_csv(
     ... '''
     >>> with open("/tmp/lines.csv", mode="w") as f:
     ...     nbytes = f.write(lines)  # nbytes is unused
-    ...
     >>> t = ibis.read_csv("/tmp/lines.csv")
     >>> t
     ┏━━━━━━━┳━━━━━━━━┓
@@ -1334,7 +1333,6 @@ def read_json(
     ... '''
     >>> with open("/tmp/lines.json", mode="w") as f:
     ...     nbytes = f.write(lines)  # nbytes is unused
-    ...
     >>> t = ibis.read_json("/tmp/lines.json")
     >>> t
     ┏━━━━━━━┳━━━━━━━━┓

ibis/legacy/udf/vectorized.py

@@ -134,16 +134,12 @@ def _coerce_to_dataframe(
     Examples
     --------
     >>> import pandas as pd
-    >>> _coerce_to_dataframe(
-    ...     pd.DataFrame({"a": [1, 2, 3]}), dt.Struct(dict(b="int32"))
-    ... )  # noqa: E501
+    >>> _coerce_to_dataframe(pd.DataFrame({"a": [1, 2, 3]}), dt.Struct(dict(b="int32")))  # noqa: E501
        b
     0  1
     1  2
     2  3
-    >>> _coerce_to_dataframe(
-    ...     pd.Series([[1, 2, 3]]), dt.Struct(dict.fromkeys("abc", "int32"))
-    ... )  # noqa: E501
+    >>> _coerce_to_dataframe(pd.Series([[1, 2, 3]]), dt.Struct(dict.fromkeys("abc", "int32")))  # noqa: E501
        a  b  c
     0  1  2  3
     >>> _coerce_to_dataframe(
@@ -157,9 +153,7 @@ def _coerce_to_dataframe(
     ... )  # noqa: E501
        a  b  c
     0  1  2  3
-    >>> _coerce_to_dataframe(
-    ...     [1, 2, 3], dt.Struct(dict.fromkeys("abc", "int32"))
-    ... )  # noqa: E501
+    >>> _coerce_to_dataframe([1, 2, 3], dt.Struct(dict.fromkeys("abc", "int32")))  # noqa: E501
        a  b  c
     0  1  2  3
     """
@@ -287,7 +281,6 @@ def analytic(input_type, output_type):
     >>> @analytic(input_type=[dt.double], output_type=dt.double)
     ... def zscore(series):  # note the use of aggregate functions
     ...     return (series - series.mean()) / series.std()
-    ...
 
     Define and use an UDF with multiple return columns:
 
@@ -329,14 +322,12 @@ def elementwise(input_type, output_type):
     >>> @elementwise(input_type=[dt.string], output_type=dt.int64)
     ... def my_string_length(series):
     ...     return series.str.len() * 2
-    ...
 
     Define an UDF with non-column parameters:
 
     >>> @elementwise(input_type=[dt.string], output_type=dt.int64)
     ... def my_string_length(series, *, times):
     ...     return series.str.len() * times
-    ...
 
     Define and use an UDF with multiple return columns:
 
@@ -375,7 +366,6 @@ def reduction(input_type, output_type):
     >>> @reduction(input_type=[dt.string], output_type=dt.int64)
     ... def my_string_length_agg(series, **kwargs):
     ...     return (series.str.len() * 2).sum()
-    ...
 
     Define and use an UDF with multiple return columns:
 

ibis/selectors.py

@@ -212,9 +212,7 @@ def of_type(dtype: dt.DataType | str | type[dt.DataType]) -> Predicate:
     >>> import ibis
     >>> import ibis.expr.datatypes as dt
     >>> import ibis.selectors as s
-    >>> t = ibis.table(
-    ...     dict(name="string", siblings="array<string>", parents="array<int64>")
-    ... )
+    >>> t = ibis.table(dict(name="string", siblings="array<string>", parents="array<int64>"))
     >>> expr = t.select(s.of_type(dt.Array(dt.string)))
     >>> expr.columns
     ['siblings']
@@ -329,9 +327,7 @@ def contains(
     >>> import ibis
     >>> import ibis.selectors as s
     >>> t = ibis.table(
-    ...     dict(
-    ...         a="int64", b="string", c="float", d="array<int16>", ab="struct<x: int>"
-    ...     )
+    ...     dict(a="int64", b="string", c="float", d="array<int16>", ab="struct<x: int>")
     ... )
     >>> expr = t.select(s.contains(("a", "b")))
     >>> expr.columns

pyproject.toml

@@ -500,6 +500,7 @@ required-imports = ["from __future__ import annotations"]
 [tool.ruff.format]
 exclude = [".direnv", "result-*", "_py310.py", "decompiled.py"]
 docstring-code-format = true
+docstring-code-line-length = 88
 
 [tool.conda-lock]
 channels = ["conda-forge"]