This is a fork of the simpleeval library and fixes a compatibility issue with setuptools (for versions >= 58). This library is used by reportbro-lib (see ReportBro).
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, pull it in from PyPI (pip or easy_install), or even just a single file you can dump into a project.
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).
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 |
in |
is something contained within
something else.
"spam" in "my breakfast"
-> 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")
8
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)
There are also limits on string length (100000 characters,
MAX_STRING_LENGTH
). This can be changed if you wish.
Related to this, if you try to create a silly long string/bytes/list, by doing
'i want to break free'.split() * 9999999999
for instance, it will block you.
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'")
'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})
42
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})
202
If you don't provide your own functions
dict, then the the following defaults
are provided in the DEFAULT_FUNCTIONS
dict:
randint(x) |
Return a random int below x |
rand() |
Return a random float between 0 and 1 |
int(x) |
Convert x to an int . |
float(x) |
Convert x to a float . |
str(x) |
Convert x to a str (unicode in py2) |
If you want to provide a list of functions, but want to keep these as well,
then you can do a normal python .copy()
& .update
:
>>> my_functions = simpleeval.DEFAULT_FUNCTIONS.copy()
>>> my_functions.update(
square=(lambda x:x*x),
double=(lambda x:x+x),
)
>>> simple_eval('square(randint(100))', functions=my_functions)
Sometimes it's useful to have variables available, which in python terminology are called 'names'.
>>> simple_eval("a + b", names={"a": 11, "b": 100})
111
You can also hand the handling of names over to a function, if you prefer:
>>> def name_handler(node):
return ord(node.id[0].lower(a))-96
>>> simple_eval('a + b', names=name_handler)
3
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.
The two default names that are provided are True
and False
. So if you want to provide your own names, but want True
and False
to keep working, either provide them yourself, or .copy()
and .update
the DEFAULT_NAMES
. (See functions example above).
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")
2
>>> s.eval('100 * 10')
1000
# 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)
def boo():
return 'Boo!'
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.
Compound types (dict
, tuple
, list
, set
) in general just work if
you pass them in as named objects. If you want to allow creation of these, the
EvalWithCompoundTypes
class works. Just replace any use of SimpleEval
with
that.
The EvalWithCompoundTypes
class also contains support for simple comprehensions.
eg: [x + 1 for x in [1,2,3]]
. There's a safety MAX_COMPREHENSION_LENGTH to control
how many items it'll allow before bailing too. This also takes into account nested
comprehensions.
Since the primary intention of this library is short expressions - an extra 'sweetener' is enabled by default. You can access a dict (or similar's) keys using the .attr syntax:
>>> simple_eval("foo.bar", names={"foo": {"bar": 42}})
42
for instance. You can turn this off either by setting the module global ATTR_INDEX_FALLBACK
to False, or on the SimpleEval
instance itself. e.g. evaller.ATTR_INDEX_FALLBACK=False
.
The SimpleEval
class is pretty easy to extend. For instance, to create a
version that disallows method invocation on objects:
import ast
import simpleeval
class EvalNoMethods(simpleeval.SimpleEval):
def _eval_call(self, node):
if isinstance(node.func, ast.Attribute):
raise simpleeval.FeatureNotAvailable("No methods please, we're British")
return super(EvalNoMethods, self)._eval_call(node)
and then use EvalNoMethods
instead of the SimpleEval
class.
The library supports both python 2 and 3.
Object attributes that start with _
or func_
are disallowed by default.
If you really need that (BE CAREFUL!), then modify the module global
simpleeval.DISALLOW_PREFIXES
.
A few builtin functions are listed in simpleeval.DISALLOW_FUNCTIONS
. type
, open
, etc.
If you need to give access to this kind of functionality to your expressions, then be very
careful. You'd be better wrapping the functions in your own safe wrappers.
The initial idea came from J.F. Sebastian on Stack Overflow ( https://stackoverflow.com/a/9558001/1973500 ) with modifications and many improvements, see the head of the main file for contributors list.
Please read the test_simpleeval.py
file for other potential gotchas or
details. I'm very happy to accept pull requests, suggestions, or other issues.
Enjoy!
Run tests:
$ make test
Or to set the tests running on every file change:
$ make autotest
(requires entr
)
I've done the best I can with this library - but there's no warrenty, no guarentee, nada. A lot of very clever people think the whole idea of trying to sandbox CPython is impossible. Read the code yourself, and use it at your own risk.