pyarrow.dataset.Expression#

class pyarrow.dataset.Expression#

Bases: _Weakrefable

A logical expression to be evaluated against some input.

To create an expression:

Use the factory function pyarrow.compute.scalar() to create a scalar (not necessary when combined, see example below).
Use the factory function pyarrow.compute.field() to reference a field (column in table).
Compare fields and scalars with <, <=, ==, >=, >.
Combine expressions using python operators & (logical and), | (logical or) and ~ (logical not). Note: python keywords and, or and not cannot be used to combine expressions.
Create expression predicates using Expression methods such as pyarrow.compute.Expression.isin().

Examples

>>> import pyarrow.compute as pc
>>> (pc.field("a") < pc.scalar(3)) | (pc.field("b") > 7)
<pyarrow.compute.Expression ((a < 3) or (b > 7))>
>>> pc.field('a') != 3
<pyarrow.compute.Expression (a != 3)>
>>> pc.field('a').isin([1, 2, 3])
<pyarrow.compute.Expression is_in(a, {value_set=int64:[
  1,
  2,
  3
], null_matching_behavior=MATCH})>

__init__(*args, **kwargs)#

Methods

`__init__`(args, *kwargs)
`cast`(self[, type, safe, options])	Explicitly set or change the expression's data type.
`equals`(self, Expression other)	Parameters:
`from_substrait`(message)	Deserialize an expression from Substrait
`is_nan`(self)	Check whether the expression is NaN.
`is_null`(self, bool nan_is_null=False)	Check whether the expression is null.
`is_valid`(self)	Check whether the expression is not-null (valid).
`isin`(self, values)	Check whether the expression is contained in values.
`to_substrait`(self, Schema schema, ...)	Serialize the expression using Substrait

cast(self, type=None, safe=None, options=None)#

Explicitly set or change the expression’s data type.

This creates a new expression equivalent to calling the cast compute function on this expression.

Parameters:

typeDataType, default None: Type to cast array to.
safebool, default True: Whether to check for conversion errors such as overflow.
optionsCastOptions, default None: Additional checks pass by CastOptions

Returns:

castExpression

equals(self, Expression other)#

Parameters:

otherpyarrow.dataset.Expression

Returns:

bool

static from_substrait(message)#

Deserialize an expression from Substrait

The serialized message must be an ExtendedExpression message that has only a single expression. The name of the expression and the schema the expression was bound to will be ignored. Use pyarrow.substrait.deserialize_expressions if this information is needed or if the message might contain multiple expressions.

Parameters:

messagebytes or Buffer or a protobuf Message: The Substrait message to deserialize

Returns:

Expression: The deserialized expression

is_nan(self)#

Check whether the expression is NaN.

This creates a new expression equivalent to calling the is_nan compute function on this expression.

Returns:

is_nanExpression

is_null(self, bool nan_is_null=False)#

Check whether the expression is null.

This creates a new expression equivalent to calling the is_null compute function on this expression.

Parameters:

nan_is_nullbool, default False: Whether floating-point NaNs are considered null.

Returns:

is_nullExpression

is_valid(self)#

Check whether the expression is not-null (valid).

This creates a new expression equivalent to calling the is_valid compute function on this expression.

Returns:

is_validExpression

isin(self, values)#

Check whether the expression is contained in values.

This creates a new expression equivalent to calling the is_in compute function on this expression.

Parameters:

valuesArray or iterable: The values to check for.

Returns:

isinExpression: A new expression that, when evaluated, checks whether this expression’s value is contained in values.

to_substrait(self, Schema schema, bool allow_arrow_extensions=False)#

Serialize the expression using Substrait

The expression will be serialized as an ExtendedExpression message that has a single expression named “expression”

Parameters:

schemaSchema: The input schema the expression will be bound to
allow_arrow_extensionsbool, default False: If False then only functions that are part of the core Substrait function definitions will be allowed. Set this to True to allow pyarrow-specific functions but the result may not be accepted by other compute libraries.

Returns:

Buffer: A buffer containing the serialized Protobuf plan.