experimental/cuda-ubi9/: pure-eval-0.2.2 metadata and description

Homepage Simple index

Safely evaluate AST nodes without side effects

author Alex Hall
author_email alex.mojaki@gmail.com
  • Intended Audience :: Developers
  • Programming Language :: Python :: 3.5
  • Programming Language :: Python :: 3.6
  • Programming Language :: Python :: 3.7
  • Programming Language :: Python :: 3.8
  • Programming Language :: Python :: 3.9
  • Programming Language :: Python :: 3.10
  • License :: OSI Approved :: MIT License
  • Operating System :: OS Independent
description_content_type text/markdown
license MIT
provides_extras tests
  • pytest ; extra == 'tests'
File Tox results History
11 KB
Python Wheel


Build Status Coverage Status Supports Python versions 3.5+

This is a Python package that lets you safely evaluate certain AST nodes without triggering arbitrary code that may have unwanted side effects.

It can be installed from PyPI:

pip install pure_eval

To demonstrate usage, suppose we have an object defined as follows:

class Rectangle:
    def __init__(self, width, height):
        self.width = width
        self.height = height

    def area(self):
        print("Calculating area...")
        return self.width * self.height

rect = Rectangle(3, 5)

Given the rect object, we want to evaluate whatever expressions we can in this source code:

source = "(rect.width, rect.height, rect.area)"

This library works with the AST, so let's parse the source code and peek inside:

import ast

tree = ast.parse(source)
the_tuple = tree.body[0].value
for node in the_tuple.elts:


Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load())
Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load())
Attribute(value=Name(id='rect', ctx=Load()), attr='area', ctx=Load())

Now to actually use the library. First construct an Evaluator:

from pure_eval import Evaluator

evaluator = Evaluator({"rect": rect})

The argument to Evaluator should be a mapping from variable names to their values. Or if you have access to the stack frame where rect is defined, you can instead use:

evaluator = Evaluator.from_frame(frame)

Now to evaluate some nodes, using evaluator[node]:

print("rect.width:", evaluator[the_tuple.elts[0]])
print("rect:", evaluator[the_tuple.elts[0].value])


rect.width: 3
rect: <__main__.Rectangle object at 0x105b0dd30>

OK, but you could have done the same thing with eval. The useful part is that it will refuse to evaluate the property rect.area because that would trigger unknown code. If we try, it'll raise a CannotEval exception.

from pure_eval import CannotEval

    print("rect.area:", evaluator[the_tuple.elts[2]])  # fails
except CannotEval as e:
    print(e)  # prints CannotEval

To find all the expressions that can be evaluated in a tree:

for node, value in evaluator.find_expressions(tree):
    print(ast.dump(node), value)


Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) 3
Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) 5
Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30>
Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30>
Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30>

Note that this includes rect three times, once for each appearance in the source code. Since all these nodes are equivalent, we can group them together:

from pure_eval import group_expressions

for nodes, values in group_expressions(evaluator.find_expressions(tree)):
    print(len(nodes), "nodes with value:", values)


1 nodes with value: 3
1 nodes with value: 5
3 nodes with value: <__main__.Rectangle object at 0x10d374d30>

If we want to list all the expressions in a tree, we may want to filter out certain expressions whose values are obvious. For example, suppose we have a function foo:

def foo():

If we refer to foo by its name as usual, then that's not interesting:

from pure_eval import is_expression_interesting

node = ast.parse('foo').body[0].value
print(is_expression_interesting(node, foo))


Name(id='foo', ctx=Load())

But if we refer to it by a different name, then it's interesting:

node = ast.parse('bar').body[0].value
print(is_expression_interesting(node, foo))


Name(id='bar', ctx=Load())

In general is_expression_interesting returns False for the following values:

To make things easier, you can combine finding expressions, grouping them, and filtering out the obvious ones with:


To get the source code of an AST node, I recommend asttokens.

Here's a complete example that brings it all together:

from asttokens import ASTTokens
from pure_eval import Evaluator

source = """
x = 1
d = {x: 2}
y = d[x]

names = {}
exec(source, names)
atok = ASTTokens(source, parse=True)
for nodes, value in Evaluator(names).interesting_expressions_grouped(atok.tree):
    print(atok.get_text(nodes[0]), "=", value)


x = 1
d = {1: 2}
y = 2
d[x] = 2