Implementation:Eventual Inc Daft Daft Sql Expr

Knowledge Sources	Daft Daft Docs
Domains	Data_Engineering, SQL
Last Updated	2026-02-08 00:00 GMT

Overview

Concrete tool for parsing SQL expression strings into Daft Expression objects provided by the Daft library.

Description

The daft.sql_expr function parses a SQL string into a Daft Expression. It delegates to the Rust _sql_expr function for parsing and wraps the result in a Python Expression object. The resulting expression can be used in any DataFrame operation that accepts expressions, such as select, with_column, where, and agg. This function is also called automatically by some DataFrame methods (like where) when a string argument is provided.

Usage

Import via import daft and call daft.sql_expr("expression"). Use when you want to construct DataFrame expressions using SQL syntax.

Code Reference

Source Location

• Repository: Daft
• File: daft/sql/sql.py
• Lines: L19-73

Signature

def sql_expr(sql: str) -> Expression

Import

import daft

expr = daft.sql_expr("col1 + col2")

I/O Contract

Inputs

Name	Type	Required	Description
sql	str	Yes	A SQL expression string to parse into a Daft Expression.

Outputs

Name	Type	Description
return	Expression	A Daft Expression representing the parsed SQL, usable in any DataFrame operation.

Usage Examples

Basic Usage

import daft

# Create a simple expression
expr = daft.sql_expr("1 + 2")
print(expr)  # lit(1) + lit(2)

# Use in a DataFrame operation
df = daft.from_pydict({"a": [1, 2, 3], "b": [4, 5, 6]})
df = df.with_column("c", daft.sql_expr("a + b"))
df.show()

Filter with SQL Expression

import daft

df = daft.from_pydict({"x": [1, 2, 3], "y": [4, 5, 6]})

# Using sql_expr explicitly
result = df.where(daft.sql_expr("x < 3 AND y > 4"))

# Or using automatic string conversion in where()
result = df.where("x < 3 AND y > 4")

Related Pages

Implements Principle

• Principle:Eventual_Inc_Daft_SQL_Expression_Building

Requires Environment

• Environment:Eventual_Inc_Daft_Python_PyArrow_Core