simpleeval (Simple Eval)
========================

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A 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 trying to stay simple to use and not have millions of features,
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 easy to add
whatever extra specific functionality you need (your own functions,
variable/name lookup, etc).

Basic Usage
-----------

To get very simple evaluating:

.. code-block:: python

    from simpleeval import simple_eval

    simple_eval("21 + 21")

returns ``42``.

Expressions can be as complex and convoluted as you want:

.. code-block:: python

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

returns ``535.714285714``.

You can add your own functions in as well.

.. code-block:: python

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

returns ``121``.

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

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

.. _Operators:

Operators
---------
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``            |
+--------+------------------------------------+
| ``>>`` | "Right shift" the number.          |
|        | ``100 >> 2`` -> ``25``             |
+--------+------------------------------------+
| ``<<`` | "Left shift" the number.           |
|        | ``100 << 2`` -> ``400``            |
+--------+------------------------------------+
| ``in`` | is something contained within      |
|        | something else.                    |
|        | ``"spam" in "my breakfast"``       |
|        | -> ``False``                       |
+--------+------------------------------------+
| ``^``  | "bitwise exclusive OR" (xor)       |
|        | ``62 ^ 20`` -> ``42``              |
+--------+------------------------------------+
| ``|``  | "bitwise OR"                       |
|        | ``8 | 34`` -> ``42``               |
+--------+------------------------------------+
| ``&``  | "bitwise AND"                      |
|        | ``100 & 63`` -> ``36``             |
+--------+------------------------------------+
| ``~``  | "bitwise invert"                   |
|        | ``~ -43`` -> ``42``                |
+--------+------------------------------------+


The ``^`` operator is often mistaken for a exponent operator, not the bitwise 
operation that it is in python, so if you want ``3 ^ 2`` to equal ``9``, you can
replace the operator like this:

.. code-block:: pycon

    >>> import ast
    >>> from simpleeval import safe_power

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

    >>> s.eval("3 ^ 2")
    9

for example.

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.MAX_POWER`` 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 ``MAX_POWER``
limit, it throws a ``NumberTooHigh`` exception for you. (Otherwise it would go
on for hours, or until the computer runs out of memory)

Strings (and other Iterables) Safety
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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.

If Expressions
--------------

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

.. code-block:: pycon

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

which, of course, can be nested:

.. code-block:: pycon

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


Functions
---------

You can define functions which you'd like the expressions to have access to:

.. code-block:: pycon

    >>> 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

.. code-block:: pycon

    >>> 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``                       |
+----------------+--------------------------------------------------+

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``:

.. code-block:: pycon

    >>> 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)

Names
-----

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

.. code-block:: pycon

    >>> 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:


.. code-block:: pycon

    >>> 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, looking up spreadsheet cells, say, or doing some kind of caching system.

In general, when it attempts to find a variable by name, if it cannot find one,
then it will look in the ``functions`` for a function of that name.  If you want your name handler
function to return an "I can't find that name!", then it should raise a ``simpleeval.NameNotDefined`` 
exception. Eg:

.. code-block:: pycon

   >>> def name_handler(node):
   ...     if node.id[0] == 'a':
   ...         return 21
   ...     raise NameNotDefined(node.id[0], "Not found")
   ...
   ... simple_eval('a + a', names=name_handler, functions={"b": 100})

   42

   >>> simple_eval('a + b', names=name_handler, functions={'b': 100})
   121

(Note: in that example, putting a number directly into the ``functions`` dict was done just to
show the fall-back to functions.  Normally only put actual callables in there.)


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).

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):

.. code-block:: pycon

    >>> s = SimpleEval()

    >>> s.eval("1 + 1")
    2

    >>> s.eval('100 * 10')
    1000

    # and so on...

One useful feature of using the ``SimpleEval`` object is that you can parse an expression
once, and then evaluate it multiple times using different ``names``:

.. code-block:: python

    # Set up & Cache the parse tree:
    expression = "foo + bar"
    parsed = s.parse(expression)

    # evaluate the expression multiple times:
    for names in [{"foo": 1, "bar": 10}, {"foo": 100, "bar": 42}]:
        s.names = names
        print(s.eval(expression, previously_parsed=parsed))

for instance.  This may help with performance.

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)

.. code-block:: python

    def boo():
        return 'Boo!'

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

or edit them after creation:

.. code-block:: python

    s.names['fortytwo'] = 42

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

.. code-block:: python

    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
--------------

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:

.. code-block:: pycon

    >>>  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``.

Extending
---------

The ``SimpleEval`` class is pretty easy to extend.  For instance, to create a
version that disallows method invocation on objects:

.. code-block:: python

    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.

Limiting Attribute Access
-------------------------

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.

Accessing modules as attributes is disallowed too.

Allowlist recommendation
------------------------

There is an additional layer of protection you can add in by passing in ``allowed_attrs``, which
makes all attribute access based opt-in rather than opt-out - which is a lot safer design:

.. code-block:: pycon

    >>> simpleeval("' hello   '.strip()", allowed_attrs={})

will throw FeatureNotAvailable - as we've now disabled all attribute access.  You can enable some
reasonably sensible defaults with BASIC_ALLOWED_ATTRS:

.. code-block:: pycon

    >>> from simpleeval import simpleeval, BASIC_ALLOWED_ATTRS
    >>> simpleeval("'  hello   '.strip()", allowed_attrs=BASIC_ALLOWED_ATTRS)

is fine - ``strip()`` should be safe on strings.

It is strongly recommended to add ``allowed_attrs=BASIC_ALLOWED_ATTRS``  whenever possible,
and it will be the default for 2.x.

You can add your own classes & limit access to attrs:

.. code-block:: pycon

    >>> from simpleeval import simpleeval, BASIC_ALLOWED_ATTRS
    >>> class Foo:
    >>>     bar = 42
    >>>     hidden = "secret"
    >>>
    >>> our_attributes = BASIC_ALLOWED_ATTRS.copy()
    >>> our_attributes[Foo] = {'bar'}
    >>> simpleeval("foo.bar", names={"foo": Foo()}, allowed_attrs=our_attributes)
    42

    >>> simpleeval("foo.hidden", names={"foo": Foo()}, allowed_attrs=our_attributes)
    simpleeval.FeatureNotAvailable: Sorry, 'hidden' access not allowed on 'Foo'

will now allow access to `foo.bar` but not allow anything else.

Module Access
-------------

By default, module access is not allowed in simpleeval to prevent accidental or
malicious access to dangerous functions. However, if you need to expose modules,
(eg. `numpy` or similar) you can use ``ModuleWrapper`` to do so safely.

``ModuleWrapper`` allows explicit opt-in to module access while still enforcing
restrictions on dangerous methods and private attributes:

.. code-block:: pycon

    >>> from simpleeval import SimpleEval, ModuleWrapper
    >>> import os.path
    >>> s = SimpleEval(names={'path': ModuleWrapper(os.path)})
    >>> s.eval("path.exists('/etc/passwd')")
    True

You can also restrict which attributes are accessible by passing an
``allowed_attrs`` set:

.. code-block:: pycon

    >>> s = SimpleEval(names={
    ...     'path': ModuleWrapper(os.path, allowed_attrs={'exists', 'join'})
    ... })
    >>> s.eval("path.exists('/etc/passwd')")
    True
    >>> s.eval("path.dirname('/etc/passwd')")  # Not in allowed_attrs
    simpleeval.FeatureNotAvailable: Access to 'dirname' is not allowed...

Private attributes (starting with ``_``) and methods in ``DISALLOW_METHODS``
are always blocked, even if not using an allowlist:

.. code-block:: pycon

    >>> s = SimpleEval(names={'path': ModuleWrapper(os.path)})
    >>> s.eval("path.__file__")
    simpleeval.FeatureNotAvailable: Access to private attribute '__file__'...

If you really really need that - you can make your own wrappers and overrides.
But I advise against it.

Other...
--------

The library supports Python 3.9 and higher.

The initial idea came from J.F. Sebastian on Stack Overflow
( http://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!

Developing
----------

Run tests::

    $ make test

Or to set the tests running on every file change:

    $ make autotest

(requires ``entr``) 

I'm trying to keep the codebase relatively clean with Black, isort, pylint & mypy.
See::

    $ make format

and::

    $ make lint

BEWARE
------

I've done the best I can with this library - but there's no warranty, no guarantee, 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.

The sandboxing / safety features of simpleeval *only apply to the expression* that is passed in to
be evaluated, and rely on the python interpreter working as normal.  If you have monkey-patched
the interpreter, or pass in objects/classes/functions with unsafe code in them, simpleeval cannot
protect you.
