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A simple, safe single expression evaluator library.

Project description

A quick single file library for easily adding evaluatable expressions into python projects. Say you want to allow a user to set an alarm volume, which could depend on the time of day, alarm level, how many previous alarms had gone off, and if there is music playing at the time.

Or if you want to allow simple formulae in a web application, but don’t want to give full eval() access, or don’t want to run in javascript on the client side.

It’s deliberately very simple, just a single file you can dump into a project, or import from pypi (pip or easy_install).

Internally, it’s using the amazing python ast module to parse the expression, which allows very fine control of what is and isn’t allowed. It should be completely safe in terms of what operations can be performed by the expression.

The only issue I know to be aware of is that you can create an expression which takes a long time to evaluate, or which evaluating requires an awful lot of memory, which leaves the potential for DOS attacks. There is basic protection against this, and you can lock it down further if you desire. (see the Operators section below)

You should be aware of this when deploying in a public setting.

The defaults are pretty locked down and basic, and it’s very easy to add whatever extra specific functionality you need (your own functions, variable/name lookup, etc).

Basic Usage

To get very simple evaluating:

from simpleeval import simple_eval

simple_eval("21 + 21")

returns 42.

Expressions can be as complex and convoluted as you want:

simple_eval("21 + 19 / 7 + (8 % 3) ** 9")

returns 535.714285714.

You can add your own functions in as well.

simple_eval("square(11)", functions={"square": lambda x: x*x})

returns 121.

For more details of working with functions, read further down.


all further examples use >>> to designate python code, as if you are using the python interactive prompt.


You can add operators yourself, using the operators argument, but these are the defaults:


add two things. x + y 1 + 1 -> 2


subtract two things x - y 100 - 1 -> 99


divide one thing by another x / y 100/10 -> 10


multiple one thing by another x * y 10 * 10 -> 100


‘to the power of’ x**y 2 ** 10 -> 1024


modulus. (remainder) x % y 15 % 4 -> 3


equals x == y 15 == 4 -> False


Less than. x < y 1 < 4 -> True


Greater than. x > y 1 > 4 -> False


Less than or Equal to. x <= y 1 < 4 -> True


Greater or Equal to x >= 21 1 >= 4 -> False

The ^ operator is notably missing - not because it’s hard, but because it is often mistaken for a exponent operator, not the bitwise operation that it is in python. It’s trivial to add back in again if you wish (using the class based evaluator explained below):

>>> import ast
>>> import operator

>>> s = SimpleEval()
>>> s.operators[ast.BitXor] = operator.xor

>>> s.eval("2 ^ 10")

Limited Power

Also note, the ** operator has been locked down by default to have a maximum input value of 4000000, which makes it somewhat harder to make expressions which go on for ever. You can change this limit by changing the simpleeval.POWER_MAX module level value to whatever is an appropriate value for you (and the hardware that you’re running on) or if you want to completely remove all limitations, you can set the s.operators[ast.Pow] = operator.pow or make your own function.

On my computer, 9**9**5 evaluates almost instantly, but 9**9**6 takes over 30 seconds. Since 9**7 is 4782969, and so over the POWER_MAX limit, it throws a NumberTooHigh exception for you. (Otherwise it would go on for hours, or until the computer runs out of memory)

String Safety

There are also limits on string length (100000 characters, MAX_STRING_LENGTH). This can be changed if you wish.

If Expressions

You can use python style if x then y else z type expressions:

>>> simple_eval("'equal' if x == y else 'not equal'",
                names={"x": 1, "y": 2})
'not equal'

which, of course, can be nested:

>>> simple_eval("'a' if 1 == 2 else 'b' if 2 == 3 else 'c'")


You can define functions which you’d like the expresssions to have access to:

>>> simple_eval("double(21)", functions={"double": lambda x:x*2})

You can define “real” functions to pass in rather than lambdas, of course too, and even re-name them so that expressions can be shorter

>>> def double(x):
        return x * 2
>>> simple_eval("d(100) + double(1)", functions={"d": double, "double":double})


Sometimes it’s useful to have variables available, which in python terminology are called ‘names’.

>>> simple_eval("a + b", names={"a": 11, "b": 100})

You can also hand the handling of names over to a function, if you prefer:

>>> def name_handler(node):
        return ord([0].lower(a))-96

>>> simple_eval('a + b', names=name_handler)

That was a bit of a silly example, but you could use this for pulling values from a database or file, say, or doing some kind of caching system.

Creating an Evaluator Class

Rather than creating a new evaluator each time, if you are doing a lot of evaluations, you can create a SimpleEval object, and pass it expressions each time (which should be a bit quicker, and certainly more convenient for some use cases):

s = SimpleEval()
s.eval("1 + 1")
# and so on...

You can assign / edit the various options of the SimpleEval object if you want to. Either assign them during creation (like the simple_eval function)

s = SimpleEval(functions={"boo": boo})

or edit them after creation:

s.names['fortytwo'] = 42

this actually means you can modify names (or functions) with functions, if you really feel so inclined:

s = SimpleEval()
def set_val(name, value):
    s.names[name.value] = value.value
    return value.value

s.functions = {'set': set_val}

s.eval("set('age', 111)")

Say. This would allow a certain level of ‘scriptyness’ if you had these evaluations happening as callbacks in a program. Although you really are reaching the end of what this library is intended for at this stage.


The library supports both python 2 and 3 using the 2to3 converter.

Please read the file for other potential gotchas or details. I’m very happy to accept pull requests, suggestions, or other issues. Enjoy!

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