pandas-dev/pandas · error · SyntaxError

left hand side of an assignment must be a single resolvable

Error message

left hand side of an assignment must be a single resolvable name

What it means

After visiting the assignment target, expr.py:635 does self.assigner = getattr(assigner, 'name', assigner). If that resolves to None (the visited term has name=None, or the Name visit returned something without a usable name), the assignment LHS is not a resolvable identifier and pandas raises SyntaxError. This is a defensive guard for malformed-but-parsed LHS nodes.

Source

Thrown at pandas/core/computation/expr.py:637

        set the assigner at the top level, must be a Name node which
        might or might not exist in the resolvers

        """
        if len(node.targets) != 1:
            raise SyntaxError("can only assign a single expression")
        if not isinstance(node.targets[0], ast.Name):
            raise SyntaxError("left hand side of an assignment must be a single name")
        if self.env.target is None:
            raise ValueError("cannot assign without a target object")

        try:
            assigner = self.visit(node.targets[0], **kwargs)
        except UndefinedVariableError:
            assigner = node.targets[0].id

        self.assigner = getattr(assigner, "name", assigner)
        if self.assigner is None:
            raise SyntaxError(
                "left hand side of an assignment must be a single resolvable name"
            )

        return self.visit(node.value, **kwargs)

    def visit_Attribute(self, node, **kwargs):
        attr = node.attr
        value = node.value

        ctx = node.ctx
        if isinstance(ctx, ast.Load):
            # resolve the value
            visited_value = self.visit(value)
            if hasattr(visited_value, "value"):
                resolved = visited_value.value
            else:
                resolved = visited_value(self.env)
            try:

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Ensure the LHS is a plain, non-empty identifier string.
2. Validate the generated name is a str and not None before building the expression.
3. Avoid constructing expressions from untrusted/dynamic LHS tokens.

Example fix

// before
name = None
df.eval(f'{name} = a + b')
// after
name = 'c'
df.eval(f'{name} = a + b')

import ast
import keyword

def validate_lhs_resolvable(expr: str) -> None:
    for stmt in ast.parse(expr, mode='exec').body:
        if isinstance(stmt, ast.Assign):
            name = stmt.targets[0].id
            if not name or keyword.iskeyword(name):
                raise SyntaxError(f'LHS name {name!r} is not a valid resolvable identifier')

validate_lhs_resolvable(expr)

import ast, keyword

def lhs_is_valid_identifier(expr: str) -> bool:
    for s in ast.parse(expr, mode='exec').body:
        if isinstance(s, ast.Assign):
            n = s.targets[0].id
            if not n or keyword.iskeyword(n):
                return False
    return True

try:
    df.eval(expr)
except SyntaxError as e:
    if 'resolvable name' in str(e):
        # choose a concrete column name and rebuild
        df.eval('new_col = a + b')
    raise

When it happens

Trigger: Edge cases where a syntactically-valid LHS visits to a term whose .name attribute is None — e.g. a constant or a Term constructed without a name. Rare in normal use; usually surfaces from dynamically generated expression strings.

Common situations: Programmatically building LHS names from data that yields empty/None. Bugs in custom resolvers that return misshapen Term objects. Internal callers constructing AST by hand.

Related errors

• multi-line expressions are only valid in the context of data
• Multi-line expressions are only valid if all expressions con
• Cannot operate inplace if there is no assignment
• Cannot assign expression output to target
• can only assign a single expression

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/02c7712490254a56. Report an issue: GitHub.