team-10/venv/Lib/site-packages/narwhals/_duckdb/dataframe.py
2025-08-02 02:00:33 +02:00

516 lines
19 KiB
Python

from __future__ import annotations
from functools import reduce
from operator import and_
from typing import TYPE_CHECKING, Any
import duckdb
from duckdb import StarExpression
from narwhals._duckdb.utils import (
DeferredTimeZone,
F,
catch_duckdb_exception,
col,
evaluate_exprs,
lit,
native_to_narwhals_dtype,
window_expression,
)
from narwhals._sql.dataframe import SQLLazyFrame
from narwhals._utils import (
Implementation,
ValidateBackendVersion,
Version,
generate_temporary_column_name,
not_implemented,
parse_columns_to_drop,
requires,
)
from narwhals.dependencies import get_duckdb
from narwhals.exceptions import InvalidOperationError
if TYPE_CHECKING:
from collections.abc import Iterator, Mapping, Sequence
from io import BytesIO
from pathlib import Path
from types import ModuleType
import pandas as pd
import pyarrow as pa
from duckdb import Expression
from duckdb.typing import DuckDBPyType
from typing_extensions import Self, TypeIs
from narwhals._compliant.typing import CompliantDataFrameAny
from narwhals._duckdb.expr import DuckDBExpr
from narwhals._duckdb.group_by import DuckDBGroupBy
from narwhals._duckdb.namespace import DuckDBNamespace
from narwhals._duckdb.series import DuckDBInterchangeSeries
from narwhals._utils import _LimitedContext
from narwhals.dataframe import LazyFrame
from narwhals.dtypes import DType
from narwhals.stable.v1 import DataFrame as DataFrameV1
from narwhals.typing import AsofJoinStrategy, JoinStrategy, LazyUniqueKeepStrategy
class DuckDBLazyFrame(
SQLLazyFrame[
"DuckDBExpr",
"duckdb.DuckDBPyRelation",
"LazyFrame[duckdb.DuckDBPyRelation] | DataFrameV1[duckdb.DuckDBPyRelation]",
],
ValidateBackendVersion,
):
_implementation = Implementation.DUCKDB
def __init__(
self,
df: duckdb.DuckDBPyRelation,
*,
version: Version,
validate_backend_version: bool = False,
) -> None:
self._native_frame: duckdb.DuckDBPyRelation = df
self._version = version
self._cached_native_schema: dict[str, DuckDBPyType] | None = None
self._cached_columns: list[str] | None = None
if validate_backend_version:
self._validate_backend_version()
@property
def _backend_version(self) -> tuple[int, ...]:
return self._implementation._backend_version()
@staticmethod
def _is_native(obj: duckdb.DuckDBPyRelation | Any) -> TypeIs[duckdb.DuckDBPyRelation]:
return isinstance(obj, duckdb.DuckDBPyRelation)
@classmethod
def from_native(
cls, data: duckdb.DuckDBPyRelation, /, *, context: _LimitedContext
) -> Self:
return cls(data, version=context._version)
def to_narwhals(
self, *args: Any, **kwds: Any
) -> LazyFrame[duckdb.DuckDBPyRelation] | DataFrameV1[duckdb.DuckDBPyRelation]:
if self._version is Version.V1:
from narwhals.stable.v1 import DataFrame as DataFrameV1
return DataFrameV1(self, level="interchange") # type: ignore[no-any-return]
return self._version.lazyframe(self, level="lazy")
def __narwhals_dataframe__(self) -> Self: # pragma: no cover
# Keep around for backcompat.
if self._version is not Version.V1:
msg = "__narwhals_dataframe__ is not implemented for DuckDBLazyFrame"
raise AttributeError(msg)
return self
def __narwhals_lazyframe__(self) -> Self:
return self
def __native_namespace__(self) -> ModuleType:
return get_duckdb() # type: ignore[no-any-return]
def __narwhals_namespace__(self) -> DuckDBNamespace:
from narwhals._duckdb.namespace import DuckDBNamespace
return DuckDBNamespace(version=self._version)
def get_column(self, name: str) -> DuckDBInterchangeSeries:
from narwhals._duckdb.series import DuckDBInterchangeSeries
return DuckDBInterchangeSeries(self.native.select(name), version=self._version)
def _iter_columns(self) -> Iterator[Expression]:
for name in self.columns:
yield col(name)
def collect(
self, backend: ModuleType | Implementation | str | None, **kwargs: Any
) -> CompliantDataFrameAny:
if backend is None or backend is Implementation.PYARROW:
from narwhals._arrow.dataframe import ArrowDataFrame
return ArrowDataFrame(
self.native.arrow(),
validate_backend_version=True,
version=self._version,
validate_column_names=True,
)
if backend is Implementation.PANDAS:
from narwhals._pandas_like.dataframe import PandasLikeDataFrame
return PandasLikeDataFrame(
self.native.df(),
implementation=Implementation.PANDAS,
validate_backend_version=True,
version=self._version,
validate_column_names=True,
)
if backend is Implementation.POLARS:
from narwhals._polars.dataframe import PolarsDataFrame
return PolarsDataFrame(
self.native.pl(), validate_backend_version=True, version=self._version
)
msg = f"Unsupported `backend` value: {backend}" # pragma: no cover
raise ValueError(msg) # pragma: no cover
def head(self, n: int) -> Self:
return self._with_native(self.native.limit(n))
def simple_select(self, *column_names: str) -> Self:
return self._with_native(self.native.select(*column_names))
def aggregate(self, *exprs: DuckDBExpr) -> Self:
selection = [val.alias(name) for name, val in evaluate_exprs(self, *exprs)]
try:
return self._with_native(self.native.aggregate(selection)) # type: ignore[arg-type]
except Exception as e: # noqa: BLE001
raise catch_duckdb_exception(e, self) from None
def select(self, *exprs: DuckDBExpr) -> Self:
selection = (val.alias(name) for name, val in evaluate_exprs(self, *exprs))
try:
return self._with_native(self.native.select(*selection))
except Exception as e: # noqa: BLE001
raise catch_duckdb_exception(e, self) from None
def drop(self, columns: Sequence[str], *, strict: bool) -> Self:
columns_to_drop = parse_columns_to_drop(self, columns, strict=strict)
selection = (name for name in self.columns if name not in columns_to_drop)
return self._with_native(self.native.select(*selection))
def lazy(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(self, *exprs: DuckDBExpr) -> Self:
new_columns_map = dict(evaluate_exprs(self, *exprs))
result = [
new_columns_map.pop(name).alias(name)
if name in new_columns_map
else col(name)
for name in self.columns
]
result.extend(value.alias(name) for name, value in new_columns_map.items())
try:
return self._with_native(self.native.select(*result))
except Exception as e: # noqa: BLE001
raise catch_duckdb_exception(e, self) from None
def filter(self, predicate: DuckDBExpr) -> Self:
# `[0]` is safe as the predicate's expression only returns a single column
mask = predicate(self)[0]
try:
return self._with_native(self.native.filter(mask))
except Exception as e: # noqa: BLE001
raise catch_duckdb_exception(e, self) from None
@property
def schema(self) -> dict[str, DType]:
if self._cached_native_schema is None:
# Note: prefer `self._cached_native_schema` over `functools.cached_property`
# due to Python3.13 failures.
self._cached_native_schema = dict(zip(self.columns, self.native.types))
deferred_time_zone = DeferredTimeZone(self.native)
return {
column_name: native_to_narwhals_dtype(
duckdb_dtype, self._version, deferred_time_zone
)
for column_name, duckdb_dtype in zip(self.native.columns, self.native.types)
}
@property
def columns(self) -> list[str]:
if self._cached_columns is None:
self._cached_columns = (
list(self.schema)
if self._cached_native_schema is not None
else self.native.columns
)
return self._cached_columns
def to_pandas(self) -> pd.DataFrame:
# only if version is v1, keep around for backcompat
return self.native.df()
def to_arrow(self) -> pa.Table:
# only if version is v1, keep around for backcompat
return self.native.arrow()
def _with_version(self, version: Version) -> Self:
return self.__class__(self.native, version=version)
def _with_native(self, df: duckdb.DuckDBPyRelation) -> Self:
return self.__class__(df, version=self._version)
def group_by(
self, keys: Sequence[str] | Sequence[DuckDBExpr], *, drop_null_keys: bool
) -> DuckDBGroupBy:
from narwhals._duckdb.group_by import DuckDBGroupBy
return DuckDBGroupBy(self, keys, drop_null_keys=drop_null_keys)
def rename(self, mapping: Mapping[str, str]) -> Self:
df = self.native
selection = (
col(name).alias(mapping[name]) if name in mapping else col(name)
for name in df.columns
)
return self._with_native(self.native.select(*selection))
def join(
self,
other: Self,
*,
how: JoinStrategy,
left_on: Sequence[str] | None,
right_on: Sequence[str] | None,
suffix: str,
) -> Self:
native_how = "outer" if how == "full" else how
if native_how == "cross":
if self._backend_version < (1, 1, 4):
msg = f"'duckdb>=1.1.4' is required for cross-join, found version: {self._backend_version}"
raise NotImplementedError(msg)
rel = self.native.set_alias("lhs").cross(other.native.set_alias("rhs"))
else:
# help mypy
assert left_on is not None # noqa: S101
assert right_on is not None # noqa: S101
it = (
col(f'lhs."{left}"') == col(f'rhs."{right}"')
for left, right in zip(left_on, right_on)
)
condition: Expression = reduce(and_, it)
rel = self.native.set_alias("lhs").join(
other.native.set_alias("rhs"),
# NOTE: Fixed in `--pre` https://github.com/duckdb/duckdb/pull/16933
condition=condition, # type: ignore[arg-type, unused-ignore]
how=native_how,
)
if native_how in {"inner", "left", "cross", "outer"}:
select = [col(f'lhs."{x}"') for x in self.columns]
for name in other.columns:
col_in_lhs: bool = name in self.columns
if native_how == "outer" and not col_in_lhs:
select.append(col(f'rhs."{name}"'))
elif (native_how == "outer") or (
col_in_lhs and (right_on is None or name not in right_on)
):
select.append(col(f'rhs."{name}"').alias(f"{name}{suffix}"))
elif right_on is None or name not in right_on:
select.append(col(name))
res = rel.select(*select).set_alias(self.native.alias)
else: # semi, anti
res = rel.select("lhs.*").set_alias(self.native.alias)
return self._with_native(res)
def join_asof(
self,
other: Self,
*,
left_on: str,
right_on: str,
by_left: Sequence[str] | None,
by_right: Sequence[str] | None,
strategy: AsofJoinStrategy,
suffix: str,
) -> Self:
lhs = self.native
rhs = other.native
conditions: list[Expression] = []
if by_left is not None and by_right is not None:
conditions.extend(
col(f'lhs."{left}"') == col(f'rhs."{right}"')
for left, right in zip(by_left, by_right)
)
else:
by_left = by_right = []
if strategy == "backward":
conditions.append(col(f'lhs."{left_on}"') >= col(f'rhs."{right_on}"'))
elif strategy == "forward":
conditions.append(col(f'lhs."{left_on}"') <= col(f'rhs."{right_on}"'))
else:
msg = "Only 'backward' and 'forward' strategies are currently supported for DuckDB"
raise NotImplementedError(msg)
condition: Expression = reduce(and_, conditions)
select = ["lhs.*"]
for name in rhs.columns:
if name in lhs.columns and (
right_on is None or name not in {right_on, *by_right}
):
select.append(f'rhs."{name}" as "{name}{suffix}"')
elif right_on is None or name not in {right_on, *by_right}:
select.append(str(col(name)))
# Replace with Python API call once
# https://github.com/duckdb/duckdb/discussions/16947 is addressed.
query = f"""
SELECT {",".join(select)}
FROM lhs
ASOF LEFT JOIN rhs
ON {condition}
""" # noqa: S608
return self._with_native(duckdb.sql(query))
def collect_schema(self) -> dict[str, DType]:
return self.schema
def unique(
self, subset: Sequence[str] | None, *, keep: LazyUniqueKeepStrategy
) -> Self:
if subset_ := subset if keep == "any" else (subset or self.columns):
# Sanitise input
if error := self._check_columns_exist(subset_):
raise error
idx_name = generate_temporary_column_name(8, self.columns)
count_name = generate_temporary_column_name(8, [*self.columns, idx_name])
name = count_name if keep == "none" else idx_name
idx_expr = window_expression(F("row_number"), subset_).alias(idx_name)
count_expr = window_expression(
F("count", StarExpression()), subset_, ()
).alias(count_name)
return self._with_native(
self.native.select(StarExpression(), idx_expr, count_expr)
.filter(col(name) == lit(1))
.select(StarExpression(exclude=[count_name, idx_name]))
)
return self._with_native(self.native.unique(", ".join(self.columns)))
def sort(self, *by: str, descending: bool | Sequence[bool], nulls_last: bool) -> Self:
if isinstance(descending, bool):
descending = [descending] * len(by)
if nulls_last:
it = (
col(name).nulls_last() if not desc else col(name).desc().nulls_last()
for name, desc in zip(by, descending)
)
else:
it = (
col(name).nulls_first() if not desc else col(name).desc().nulls_first()
for name, desc in zip(by, descending)
)
return self._with_native(self.native.sort(*it))
def drop_nulls(self, subset: Sequence[str] | None) -> Self:
subset_ = subset if subset is not None else self.columns
keep_condition = reduce(and_, (col(name).isnotnull() for name in subset_))
return self._with_native(self.native.filter(keep_condition))
def explode(self, columns: Sequence[str]) -> Self:
dtypes = self._version.dtypes
schema = self.collect_schema()
for name in columns:
dtype = schema[name]
if dtype != dtypes.List:
msg = (
f"`explode` operation not supported for dtype `{dtype}`, "
"expected List type"
)
raise InvalidOperationError(msg)
if len(columns) != 1:
msg = (
"Exploding on multiple columns is not supported with DuckDB backend since "
"we cannot guarantee that the exploded columns have matching element counts."
)
raise NotImplementedError(msg)
col_to_explode = col(columns[0])
rel = self.native
original_columns = self.columns
not_null_condition = col_to_explode.isnotnull() & F("len", col_to_explode) > lit(
0
)
non_null_rel = rel.filter(not_null_condition).select(
*(
F("unnest", col_to_explode).alias(name) if name in columns else name
for name in original_columns
)
)
null_rel = rel.filter(~not_null_condition).select(
*(
lit(None).alias(name) if name in columns else name
for name in original_columns
)
)
return self._with_native(non_null_rel.union(null_rel))
def unpivot(
self,
on: Sequence[str] | None,
index: Sequence[str] | None,
variable_name: str,
value_name: str,
) -> Self:
index_ = [] if index is None else index
on_ = [c for c in self.columns if c not in index_] if on is None else on
if variable_name == "":
msg = "`variable_name` cannot be empty string for duckdb backend."
raise NotImplementedError(msg)
if value_name == "":
msg = "`value_name` cannot be empty string for duckdb backend."
raise NotImplementedError(msg)
unpivot_on = ", ".join(str(col(name)) for name in on_)
rel = self.native # noqa: F841
# Replace with Python API once
# https://github.com/duckdb/duckdb/discussions/16980 is addressed.
query = f"""
unpivot rel
on {unpivot_on}
into
name "{variable_name}"
value "{value_name}"
"""
return self._with_native(
duckdb.sql(query).select(*[*index_, variable_name, value_name])
)
@requires.backend_version((1, 3))
def with_row_index(self, name: str, order_by: Sequence[str]) -> Self:
if order_by is None:
msg = "Cannot pass `order_by` to `with_row_index` for DuckDB"
raise TypeError(msg)
expr = (window_expression(F("row_number"), order_by=order_by) - lit(1)).alias(
name
)
return self._with_native(self.native.select(expr, StarExpression()))
def sink_parquet(self, file: str | Path | BytesIO) -> None:
df = self.native # noqa: F841
query = f"""
COPY (SELECT * FROM df)
TO '{file}'
(FORMAT parquet)
""" # noqa: S608
duckdb.sql(query)
gather_every = not_implemented.deprecated(
"`LazyFrame.gather_every` is deprecated and will be removed in a future version."
)
tail = not_implemented.deprecated(
"`LazyFrame.tail` is deprecated and will be removed in a future version."
)