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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
""":py:class:`Expr` — the logical expression type used to build DataFusion queries.
An :py:class:`Expr` represents a computation over columns or literals: a
column reference (``col("a")``), a literal (``lit(5)``), an operator
combination (``col("a") + lit(1)``), or the output of a function from
:py:mod:`datafusion.functions`. Expressions are passed to
:py:class:`~datafusion.dataframe.DataFrame` methods such as
:py:meth:`~datafusion.dataframe.DataFrame.select`,
:py:meth:`~datafusion.dataframe.DataFrame.filter`,
:py:meth:`~datafusion.dataframe.DataFrame.aggregate`, and
:py:meth:`~datafusion.dataframe.DataFrame.sort`.
Convenience constructors are re-exported at the package level:
:py:func:`datafusion.col` / :py:func:`datafusion.column` for column references
and :py:func:`datafusion.lit` / :py:func:`datafusion.literal` for scalar
literals.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, 3]})
>>> df.select((col("a") * lit(10)).alias("ten_a")).to_pydict()
{'ten_a': [10, 20, 30]}
See :ref:`expressions` in the online documentation for details on available
operators and helpers.
"""
# ruff: noqa: PLC0415
from __future__ import annotations
from collections.abc import Callable, Iterable, Sequence
from typing import TYPE_CHECKING, Any, ClassVar
try:
from warnings import deprecated # Python 3.13+
except ImportError:
from typing_extensions import deprecated # Python 3.12
import pyarrow as pa
from ._internal import expr as expr_internal
from ._internal import functions as functions_internal
from .ipc import get_sender_ctx
if TYPE_CHECKING:
from collections.abc import Sequence
from datafusion.common import ( # type: ignore[import]
DataTypeMap,
NullTreatment,
RexType,
)
from datafusion.context import SessionContext
from datafusion.plan import LogicalPlan
# Standard error message for invalid expression types
# Mention both alias forms of column and literal helpers
EXPR_TYPE_ERROR = "Use col()/column() or lit()/literal() to construct expressions"
# The following are imported from the internal representation. We may choose to
# give these all proper wrappers, or to simply leave as is. These were added
# in order to support passing the `test_imports` unit test.
# Tim Saucer note: It is not clear to me what the use case is for exposing
# these definitions to the end user.
Alias = expr_internal.Alias
Analyze = expr_internal.Analyze
Aggregate = expr_internal.Aggregate
AggregateFunction = expr_internal.AggregateFunction
Between = expr_internal.Between
BinaryExpr = expr_internal.BinaryExpr
Case = expr_internal.Case
Cast = expr_internal.Cast
Column = expr_internal.Column
CopyTo = expr_internal.CopyTo
CreateCatalog = expr_internal.CreateCatalog
CreateCatalogSchema = expr_internal.CreateCatalogSchema
CreateExternalTable = expr_internal.CreateExternalTable
@deprecated("CreateExternalTable.location() is deprecated; use locations() instead.")
def _create_external_table_location(self: Any) -> str:
"""Return the first external table location.
Use :meth:`CreateExternalTable.locations` instead.
Examples:
>>> class Command:
... def locations(self) -> list[str]:
... return ["data.csv"]
>>> Command().locations()
['data.csv']
"""
locations = self.locations()
return locations[0] if locations else ""
CreateExternalTable.location = _create_external_table_location
CreateFunction = expr_internal.CreateFunction
CreateFunctionBody = expr_internal.CreateFunctionBody
CreateIndex = expr_internal.CreateIndex
CreateMemoryTable = expr_internal.CreateMemoryTable
CreateView = expr_internal.CreateView
Deallocate = expr_internal.Deallocate
DescribeTable = expr_internal.DescribeTable
Distinct = expr_internal.Distinct
DmlStatement = expr_internal.DmlStatement
DropCatalogSchema = expr_internal.DropCatalogSchema
DropFunction = expr_internal.DropFunction
DropTable = expr_internal.DropTable
DropView = expr_internal.DropView
EmptyRelation = expr_internal.EmptyRelation
Execute = expr_internal.Execute
Exists = expr_internal.Exists
Explain = expr_internal.Explain
Extension = expr_internal.Extension
FileType = expr_internal.FileType
Filter = expr_internal.Filter
Join = expr_internal.Join
ILike = expr_internal.ILike
InList = expr_internal.InList
InSubquery = expr_internal.InSubquery
IsFalse = expr_internal.IsFalse
IsNotTrue = expr_internal.IsNotTrue
IsNull = expr_internal.IsNull
IsTrue = expr_internal.IsTrue
IsUnknown = expr_internal.IsUnknown
IsNotFalse = expr_internal.IsNotFalse
IsNotNull = expr_internal.IsNotNull
IsNotUnknown = expr_internal.IsNotUnknown
JoinConstraint = expr_internal.JoinConstraint
JoinType = expr_internal.JoinType
Like = expr_internal.Like
Limit = expr_internal.Limit
Literal = expr_internal.Literal
Negative = expr_internal.Negative
Not = expr_internal.Not
OperateFunctionArg = expr_internal.OperateFunctionArg
Partitioning = expr_internal.Partitioning
Placeholder = expr_internal.Placeholder
Prepare = expr_internal.Prepare
Projection = expr_internal.Projection
RecursiveQuery = expr_internal.RecursiveQuery
Repartition = expr_internal.Repartition
ScalarSubquery = expr_internal.ScalarSubquery
ScalarVariable = expr_internal.ScalarVariable
SetVariable = expr_internal.SetVariable
SimilarTo = expr_internal.SimilarTo
Sort = expr_internal.Sort
Subquery = expr_internal.Subquery
SubqueryAlias = expr_internal.SubqueryAlias
TableScan = expr_internal.TableScan
TransactionAccessMode = expr_internal.TransactionAccessMode
TransactionConclusion = expr_internal.TransactionConclusion
TransactionEnd = expr_internal.TransactionEnd
TransactionIsolationLevel = expr_internal.TransactionIsolationLevel
TransactionStart = expr_internal.TransactionStart
TryCast = expr_internal.TryCast
Union = expr_internal.Union
HigherOrderFunction = expr_internal.HigherOrderFunction
Lambda = expr_internal.Lambda
LambdaVariable = expr_internal.LambdaVariable
Unnest = expr_internal.Unnest
UnnestExpr = expr_internal.UnnestExpr
Values = expr_internal.Values
WindowExpr = expr_internal.WindowExpr
__all__ = [
"EXPR_TYPE_ERROR",
"Aggregate",
"AggregateFunction",
"Alias",
"Analyze",
"Between",
"BinaryExpr",
"Case",
"CaseBuilder",
"Cast",
"Column",
"CopyTo",
"CreateCatalog",
"CreateCatalogSchema",
"CreateExternalTable",
"CreateFunction",
"CreateFunctionBody",
"CreateIndex",
"CreateMemoryTable",
"CreateView",
"Deallocate",
"DescribeTable",
"Distinct",
"DmlStatement",
"DropCatalogSchema",
"DropFunction",
"DropTable",
"DropView",
"EmptyRelation",
"Execute",
"Exists",
"Explain",
"Expr",
"Extension",
"FileType",
"Filter",
"GroupingSet",
"HigherOrderFunction",
"ILike",
"InList",
"InSubquery",
"IsFalse",
"IsNotFalse",
"IsNotNull",
"IsNotTrue",
"IsNotUnknown",
"IsNull",
"IsTrue",
"IsUnknown",
"Join",
"JoinConstraint",
"JoinType",
"Lambda",
"LambdaVariable",
"Like",
"Limit",
"Literal",
"Literal",
"Negative",
"Not",
"OperateFunctionArg",
"Partitioning",
"Placeholder",
"Prepare",
"Projection",
"RecursiveQuery",
"Repartition",
"ScalarSubquery",
"ScalarVariable",
"SetVariable",
"SimilarTo",
"Sort",
"SortExpr",
"SortKey",
"Subquery",
"SubqueryAlias",
"TableScan",
"TransactionAccessMode",
"TransactionConclusion",
"TransactionEnd",
"TransactionIsolationLevel",
"TransactionStart",
"TryCast",
"Union",
"Unnest",
"UnnestExpr",
"Values",
"Window",
"WindowExpr",
"WindowFrame",
"WindowFrameBound",
"coerce_to_expr",
"coerce_to_expr_list",
"coerce_to_expr_or_none",
"ensure_expr",
"ensure_expr_list",
]
def ensure_expr(value: Expr | Any) -> expr_internal.Expr:
"""Return the internal expression from ``Expr`` or raise ``TypeError``.
This helper rejects plain strings and other non-:class:`Expr` values so
higher level APIs consistently require explicit :func:`~datafusion.col` or
:func:`~datafusion.lit` expressions.
See Also:
:func:`coerce_to_expr` — the opposite behavior: *wraps* non-``Expr``
values as literals instead of rejecting them.
Args:
value: Candidate expression or other object.
Returns:
The internal expression representation.
Raises:
TypeError: If ``value`` is not an instance of :class:`Expr`.
"""
if not isinstance(value, Expr):
raise TypeError(EXPR_TYPE_ERROR)
return value.expr
def ensure_expr_list(
exprs: Iterable[Expr | Iterable[Expr]],
) -> list[expr_internal.Expr]:
"""Flatten an iterable of expressions, validating each via ``ensure_expr``.
Args:
exprs: Possibly nested iterable containing expressions.
Returns:
A flat list of raw expressions.
Raises:
TypeError: If any item is not an instance of :class:`Expr`.
"""
def _iter(
items: Iterable[Expr | Iterable[Expr]],
) -> Iterable[expr_internal.Expr]:
for expr in items:
if isinstance(expr, Iterable) and not isinstance(
expr, Expr | str | bytes | bytearray
):
# Treat string-like objects as atomic to surface standard errors
yield from _iter(expr)
else:
yield ensure_expr(expr)
return list(_iter(exprs))
def coerce_to_expr(value: Any) -> Expr:
"""Coerce a native Python value to an ``Expr`` literal, passing ``Expr`` through.
This is the complement of :func:`ensure_expr`: where ``ensure_expr``
*rejects* non-``Expr`` values, ``coerce_to_expr`` *wraps* them via
:meth:`Expr.literal` so that functions can accept native Python types
(``int``, ``float``, ``str``, ``bool``, etc.) alongside ``Expr``.
Args:
value: An ``Expr`` instance (returned as-is) or a Python literal to wrap.
Returns:
An ``Expr`` representing the value.
"""
if isinstance(value, Expr):
return value
return Expr.literal(value)
def coerce_to_expr_or_none(value: Any | None) -> Expr | None:
"""Coerce a value to ``Expr`` or pass ``None`` through unchanged.
Same as :func:`coerce_to_expr` but accepts ``None`` for optional parameters.
Args:
value: An ``Expr`` instance, a Python literal to wrap, or ``None``.
Returns:
An ``Expr`` representing the value, or ``None``.
"""
if value is None:
return None
return coerce_to_expr(value)
def coerce_to_expr_list(values: Iterable[Any]) -> list[Expr]:
"""Coerce each item in an iterable to ``Expr`` via :func:`coerce_to_expr`.
Args:
values: Iterable of ``Expr`` instances or Python literals to wrap.
Returns:
A list of ``Expr`` instances.
"""
return [coerce_to_expr(value) for value in values]
def _to_raw_expr(value: Expr | str) -> expr_internal.Expr:
"""Convert a Python expression or column name to its raw variant.
Args:
value: Candidate expression or column name.
Returns:
The internal :class:`~datafusion._internal.expr.Expr` representation.
Raises:
TypeError: If ``value`` is neither an :class:`Expr` nor ``str``.
"""
if isinstance(value, str):
return Expr.column(value).expr
if isinstance(value, Expr):
return value.expr
error = (
"Expected Expr or column name, found:"
f" {type(value).__name__}. {EXPR_TYPE_ERROR}."
)
raise TypeError(error)
def expr_list_to_raw_expr_list(
expr_list: list[Expr] | Expr | None,
) -> list[expr_internal.Expr] | None:
"""Convert a sequence of expressions or column names to raw expressions."""
if isinstance(expr_list, Expr | str):
expr_list = [expr_list]
if expr_list is None:
return None
return [_to_raw_expr(e) for e in expr_list]
def sort_or_default(e: Expr | SortExpr) -> expr_internal.SortExpr:
"""Helper function to return a default Sort if an Expr is provided."""
if isinstance(e, SortExpr):
return e.raw_sort
return SortExpr(e, ascending=True, nulls_first=True).raw_sort
def sort_list_to_raw_sort_list(
sort_list: Sequence[SortKey] | SortKey | None,
) -> list[expr_internal.SortExpr] | None:
"""Helper function to return an optional sort list to raw variant."""
if isinstance(sort_list, Expr | SortExpr | str):
sort_list = [sort_list]
if sort_list is None:
return None
raw_sort_list = []
for item in sort_list:
if isinstance(item, SortExpr):
raw_sort_list.append(sort_or_default(item))
else:
raw_expr = _to_raw_expr(item) # may raise ``TypeError``
raw_sort_list.append(sort_or_default(Expr(raw_expr)))
return raw_sort_list
class Expr: # noqa: PLW1641
"""Expression object.
Expressions are one of the core concepts in DataFusion. See
:ref:`Expressions` in the online documentation for more information.
"""
def __init__(self, expr: expr_internal.RawExpr) -> None:
"""This constructor should not be called by the end user."""
self.expr = expr
def to_variant(self) -> Any:
"""Convert this expression into a python object if possible."""
return self.expr.to_variant()
def schema_name(self) -> str:
"""Returns the name of this expression as it should appear in a schema.
This name will not include any CAST expressions.
"""
return self.expr.schema_name()
def canonical_name(self) -> str:
"""Returns a complete string representation of this expression."""
return self.expr.canonical_name()
def variant_name(self) -> str:
"""Returns the name of the Expr variant.
Ex: ``IsNotNull``, ``Literal``, ``BinaryExpr``, etc
"""
return self.expr.variant_name()
def to_bytes(self, ctx: SessionContext | None = None) -> bytes:
"""Serialize this expression to bytes for shipping to another process.
Use this — or :func:`pickle.dumps` — to send an expression to a
worker process for distributed evaluation.
When ``ctx`` is supplied, encoding routes through that session's
installed :class:`LogicalExtensionCodec` (so settings like
:meth:`SessionContext.with_python_udf_inlining` take effect).
When ``ctx`` is ``None``, the default codec is used (Python UDF
inlining on, no user-installed extension codec).
Built-in functions travel inside the returned bytes. Python UDFs
(scalar, aggregate, window) also inline by default, so the worker
does not need to pre-register them; when the encoding session has
:meth:`SessionContext.with_python_udf_inlining` set to ``False``,
Python UDFs travel by name only and must be registered on the
worker. UDFs imported via the FFI capsule protocol always travel
by name only and must be registered on the worker.
.. warning:: Security
Bytes returned here may embed a cloudpickled Python
callable (when the expression carries a Python UDF).
Reconstructing them via :meth:`from_bytes` or
:func:`pickle.loads` executes arbitrary Python on the
receiver. Only accept payloads from trusted sources.
.. warning:: Portability
cloudpickle serializes Python bytecode, which is **not
stable across Python minor versions**. A payload produced
on Python 3.11 will fail to load on Python 3.12. The
wire format stamps the sender's ``(major, minor)``;
:meth:`from_bytes` raises a :class:`ValueError` naming
both versions on mismatch.
cloudpickle captures the UDF callable **by value** —
bytecode and closure cells inlined — but names the
callable resolves via ``import`` are captured **by
reference** (module path only) and must be importable on
the receiver.
**Self-contained — works anywhere:**
.. code-block:: python
# Lambda: bytecode captured inline
udf(lambda x: x * 2, [pa.int64()], pa.int64(),
volatility="immutable")
# Locally-defined function: bytecode captured inline
def double(x):
return x * 2
udf(double, [pa.int64()], pa.int64(), volatility="immutable")
# Closure over a local variable: value captured inline
factor = 3
udf(lambda x: x * factor, [pa.int64()], pa.int64(),
volatility="immutable")
**Requires matching environment on receiver:**
.. code-block:: python
# Top-level import: `foo` must be installed on receiver
from foo import double
udf(double, [pa.int64()], pa.int64(), volatility="immutable")
# Bound method of an imported class: same caveat
from mylib import Transformer
t = Transformer()
udf(t.transform, [pa.int64()], pa.int64(),
volatility="immutable")
Examples:
>>> from datafusion import col, lit
>>> blob = (col("a") + lit(1)).to_bytes()
>>> isinstance(blob, bytes)
True
"""
ctx_arg = ctx.ctx if ctx is not None else None
return self.expr.to_bytes(ctx_arg)
@classmethod
def from_bytes(cls, buf: bytes, ctx: SessionContext | None = None) -> Expr:
"""Reconstruct an expression from serialized bytes.
Accepts output of :meth:`to_bytes` or :func:`pickle.dumps`.
``ctx`` is the :class:`SessionContext` used to resolve any
function references that travel by name (e.g. FFI UDFs, or
Python UDFs sent with inlining disabled via
:meth:`SessionContext.with_python_udf_inlining`). When
``ctx`` is ``None`` the worker context installed via
:func:`datafusion.ipc.set_worker_ctx` is consulted; if no worker
context is installed, the global :class:`SessionContext` is used
(sufficient for built-ins and Python UDFs, plus any UDFs
registered on the global context).
Note that the global context carries no extension codecs, so
falling back to it cannot decode a payload written by one. A
worker that must decode extension-codec payloads has to install a
context carrying those codecs — see
:func:`datafusion.ipc.set_worker_ctx` and
:meth:`SessionContext.with_extensions`.
.. warning:: Security
Decoding may invoke ``cloudpickle.loads`` on bytes embedded
in the payload, which executes arbitrary Python code. Treat
``buf`` as code, not data — only decode bytes you produced
yourself or received from a trusted sender.
.. warning:: Portability
cloudpickle payloads are **not portable across Python
minor versions**. The wire format stamps the sender's
``(major, minor)``; if it does not match the current
interpreter, this method raises :class:`ValueError`
naming both versions. Modules the UDF imports must also
be importable on the receiver — see :meth:`to_bytes` for
by-value vs. by-reference details.
Examples:
>>> from datafusion import Expr, col, lit
>>> blob = (col("a") + lit(1)).to_bytes()
>>> Expr.from_bytes(blob).canonical_name()
'a + Int64(1)'
"""
from datafusion.ipc import _resolve_ctx
resolved = _resolve_ctx(ctx)
return cls(expr_internal.RawExpr.from_bytes(resolved.ctx, buf))
def __reduce__(self) -> tuple[Callable[[bytes], Expr], tuple[bytes]]:
"""Pickle protocol hook.
Lets expressions be shipped to worker processes via
:func:`pickle.dumps` / :func:`pickle.loads`. Built-in functions
and Python UDFs (scalar, aggregate, window) travel inside the
pickle bytes; only FFI-capsule UDFs require pre-registration on
the worker. The worker's :class:`SessionContext` for resolving
those references is looked up via
:func:`datafusion.ipc.set_worker_ctx`, falling back to the
global :class:`SessionContext` if none has been installed on
the worker.
.. warning:: Security
:func:`pickle.loads` on the returned tuple executes
arbitrary Python on the receiver, including any
cloudpickled UDF callable embedded in the payload. Only
unpickle expressions from trusted sources.
.. warning:: Portability
Sender and receiver must run the same Python
``(major, minor)`` version; cloudpickle bytecode is not
portable across minor versions. See :meth:`to_bytes` for
details on what travels by value vs. by reference.
The encoding side honors a driver-side sender context installed
via :func:`datafusion.ipc.set_sender_ctx` — that is how
:meth:`SessionContext.with_python_udf_inlining` propagates
through ``pickle.dumps``. The sender context is read by
``__reduce__``, so :func:`copy.copy` and :func:`copy.deepcopy`
— which also go through ``__reduce__`` — pick it up too.
Examples:
>>> import pickle
>>> from datafusion import col, lit
>>> e = col("a") * lit(2)
>>> pickle.loads(pickle.dumps(e)).canonical_name()
'a * Int64(2)'
"""
return (Expr._reconstruct, (self.to_bytes(get_sender_ctx()),))
@classmethod
def _reconstruct(cls, proto_bytes: bytes) -> Expr:
"""Internal entry point used by :meth:`__reduce__` on unpickle.
Examples:
>>> from datafusion import Expr, col, lit
>>> blob = (col("a") + lit(1)).to_bytes()
>>> Expr._reconstruct(blob).canonical_name()
'a + Int64(1)'
"""
return cls.from_bytes(proto_bytes)
def __richcmp__(self, other: Expr, op: int) -> Expr:
"""Comparison operator."""
return Expr(self.expr.__richcmp__(other.expr, op))
def __repr__(self) -> str:
"""Generate a string representation of this expression."""
return self.expr.__repr__()
def __add__(self, rhs: Any) -> Expr:
"""Addition operator.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__add__(rhs.expr))
def __sub__(self, rhs: Any) -> Expr:
"""Subtraction operator.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__sub__(rhs.expr))
def __truediv__(self, rhs: Any) -> Expr:
"""Division operator.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__truediv__(rhs.expr))
def __mul__(self, rhs: Any) -> Expr:
"""Multiplication operator.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__mul__(rhs.expr))
def __mod__(self, rhs: Any) -> Expr:
"""Modulo operator (%).
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__mod__(rhs.expr))
def __and__(self, rhs: Expr) -> Expr:
"""Logical AND."""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__and__(rhs.expr))
def __or__(self, rhs: Expr) -> Expr:
"""Logical OR."""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__or__(rhs.expr))
def __invert__(self) -> Expr:
"""Binary not (~)."""
return Expr(self.expr.__invert__())
def __getitem__(self, key: str | int) -> Expr:
"""Retrieve sub-object.
If ``key`` is a string, returns the subfield of the struct.
If ``key`` is an integer, retrieves the element in the array. Note that the
element index begins at ``0``, unlike
:py:func:`~datafusion.functions.array_element` which begins at ``1``.
If ``key`` is a slice, returns an array that contains a slice of the
original array. Similar to integer indexing, this follows Python convention
where the index begins at ``0`` unlike
:py:func:`~datafusion.functions.array_slice` which begins at ``1``.
"""
if isinstance(key, int):
return Expr(
functions_internal.array_element(self.expr, Expr.literal(key + 1).expr)
)
if isinstance(key, slice):
if isinstance(key.start, int):
start = Expr.literal(key.start + 1).expr
elif isinstance(key.start, Expr):
start = (key.start + Expr.literal(1)).expr
else:
# Default start at the first element, index 1
start = Expr.literal(1).expr
if isinstance(key.stop, int):
stop = Expr.literal(key.stop).expr
else:
stop = key.stop.expr
if isinstance(key.step, int):
step = Expr.literal(key.step).expr
elif isinstance(key.step, Expr):
step = key.step.expr
else:
step = key.step
return Expr(functions_internal.array_slice(self.expr, start, stop, step))
return Expr(self.expr.__getitem__(key))
def __eq__(self, rhs: object) -> Expr:
"""Equal to.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if rhs is None:
return self.is_null()
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__eq__(rhs.expr))
def __ne__(self, rhs: object) -> Expr:
"""Not equal to.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if rhs is None:
return self.is_not_null()
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__ne__(rhs.expr))
def __ge__(self, rhs: Any) -> Expr:
"""Greater than or equal to.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__ge__(rhs.expr))
def __gt__(self, rhs: Any) -> Expr:
"""Greater than.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__gt__(rhs.expr))
def __le__(self, rhs: Any) -> Expr:
"""Less than or equal to.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__le__(rhs.expr))
def __lt__(self, rhs: Any) -> Expr:
"""Less than.
Accepts either an expression or any valid PyArrow scalar literal value.
"""
if not isinstance(rhs, Expr):
rhs = Expr.literal(rhs)
return Expr(self.expr.__lt__(rhs.expr))
__radd__ = __add__
__rand__ = __and__
__rmod__ = __mod__
__rmul__ = __mul__
__ror__ = __or__
__rsub__ = __sub__
__rtruediv__ = __truediv__
@staticmethod
def literal(value: Any) -> Expr:
"""Creates a new expression representing a scalar value.
``value`` must be a valid PyArrow scalar value or easily castable to one.
"""
if isinstance(value, str):
value = pa.scalar(value, type=pa.string_view())
return Expr(expr_internal.RawExpr.literal(value))
@staticmethod
def literal_with_metadata(value: Any, metadata: dict[str, str]) -> Expr:
"""Creates a new expression representing a scalar value with metadata.
Args:
value: A valid PyArrow scalar value or easily castable to one.
metadata: Metadata to attach to the expression.
"""
if isinstance(value, str):
value = pa.scalar(value, type=pa.string_view())
return Expr(expr_internal.RawExpr.literal_with_metadata(value, metadata))
@staticmethod
def string_literal(value: str) -> Expr:
"""Creates a new expression representing a UTF8 literal value.
It is different from `literal` because it is pa.string() instead of
pa.string_view()
This is needed for cases where DataFusion is expecting a UTF8 instead of
UTF8View literal, like in:
https://github.com/apache/datafusion/blob/86740bfd3d9831d6b7c1d0e1bf4a21d91598a0ac/datafusion/functions/src/core/arrow_cast.rs#L179
"""
if isinstance(value, str):
value = pa.scalar(value, type=pa.string())
return Expr(expr_internal.RawExpr.literal(value))
return Expr.literal(value)
@staticmethod
def column(value: str) -> Expr:
"""Creates a new expression representing a column."""
return Expr(expr_internal.RawExpr.column(value))
def alias(self, name: str, metadata: dict[str, str] | None = None) -> Expr:
"""Assign a name to the expression.
Args:
name: The name to assign to the expression.
metadata: Optional metadata to attach to the expression.
Returns:
A new expression with the assigned name.
"""
return Expr(self.expr.alias(name, metadata))
def sort(self, ascending: bool = True, nulls_first: bool = True) -> SortExpr:
"""Creates a sort :py:class:`Expr` from an existing :py:class:`Expr`.
Args:
ascending: If true, sort in ascending order.
nulls_first: Return null values first.
"""
return SortExpr(self, ascending=ascending, nulls_first=nulls_first)
def is_null(self) -> Expr:
"""Returns ``True`` if this expression is null."""
return Expr(self.expr.is_null())
def is_not_null(self) -> Expr:
"""Returns ``True`` if this expression is not null."""
return Expr(self.expr.is_not_null())
def fill_nan(self, value: Any | Expr | None = None) -> Expr:
"""Fill NaN values with a provided value."""
if not isinstance(value, Expr):
value = Expr.literal(value)
return Expr(functions_internal.nanvl(self.expr, value.expr))
def fill_null(self, value: Any | Expr | None = None) -> Expr:
"""Fill NULL values with a provided value."""
if not isinstance(value, Expr):
value = Expr.literal(value)
return Expr(functions_internal.nvl(self.expr, value.expr))
_to_pyarrow_types: ClassVar[dict[type, pa.DataType]] = {
float: pa.float64(),
int: pa.int64(),
str: pa.string(),
bool: pa.bool_(),
}
def cast(self, to: pa.DataType[Any] | type) -> Expr:
"""Cast to a new data type."""
if not isinstance(to, pa.DataType):
try:
to = self._to_pyarrow_types[to]
except KeyError as err:
error_msg = "Expected instance of pyarrow.DataType or builtins.type"
raise TypeError(error_msg) from err
return Expr(self.expr.cast(to))
def try_cast(self, to: pa.DataType[Any] | type) -> Expr:
"""Cast to a new data type, returning NULL on failure.
Like :py:meth:`cast` but produces NULL instead of erroring when the
cast cannot be performed for a given row.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["oops"]})
>>> result = df.select(col("a").try_cast(pa.float64()).alias("c"))
>>> result.collect_column("c")[0].as_py() is None
True
"""
if not isinstance(to, pa.DataType):
try:
to = self._to_pyarrow_types[to]
except KeyError as err:
error_msg = "Expected instance of pyarrow.DataType or builtins.type"
raise TypeError(error_msg) from err
return Expr(self.expr.try_cast(to))
def between(self, low: Any, high: Any, negated: bool = False) -> Expr:
"""Returns ``True`` if this expression is between a given range.
Args:
low: lower bound of the range (inclusive).
high: higher bound of the range (inclusive).
negated: negates whether the expression is between a given range
"""
if not isinstance(low, Expr):
low = Expr.literal(low)
if not isinstance(high, Expr):
high = Expr.literal(high)
return Expr(self.expr.between(low.expr, high.expr, negated=negated))
def rex_type(self) -> RexType:
"""Return the Rex Type of this expression.
A Rex (Row Expression) specifies a single row of data.That specification
could include user defined functions or types. RexType identifies the
row as one of the possible valid ``RexType``.
"""
return self.expr.rex_type()
def types(self) -> DataTypeMap:
"""Return the ``DataTypeMap``.
Returns:
DataTypeMap which represents the PythonType, Arrow DataType, and
SqlType Enum which this expression represents.
"""
return self.expr.types()
def python_value(self) -> Any:
"""Extracts the Expr value into `Any`.