I built upon a few posts here to make an evaluator class. Also used
eval example which I basically rewrote into a class object.
import sys
import ast
import operator as op
import abc
import math
class IEvaluator:
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def eval_expr(cls, expr, subs): # @NoSelf
'''IMPORTANT: this is class method, overload it with @classmethod!
Evaluate an expression given in the expr string.
:param expr: str. String expression.
:param subs: dict. Dictionary with values to substitute.
:returns: Evaluated expression result.
'''
class Evaluator(IEvaluator):
'''Generic evaluator for a string expression. Uses ast and operator
modules. The expr string is parsed with ast resulting in a node tree.
Then the node tree is recursively traversed and evaluated with operations
from the operator module.
:implements: IEvaluator
'''
@classmethod
def _get_op(cls, node):
'''Get the operator corresponding to the node.
:param node: Operator node type with node.op property.
'''
# supported operators
operators = {
ast.Add: op.add,
ast.Sub: op.sub,
ast.Mult: op.mul,
ast.Div: op.truediv,
ast.Pow: op.pow,
ast.BitXor: op.xor,
ast.USub: op.neg
}
return operators[type(node.op)]
@classmethod
def _get_op_fun(cls, node):
# fun_call = {'sin': math.sin, 'cos': math.cos}[node.func.id]
fun_call = getattr(math, node.func.id)
return fun_call
@classmethod
def _num_op(cls, node, subs):
'''Return the value of the node.
:param node: Value node type with node.n property.
'''
return node.n
@classmethod
def _bin_op(cls, node, subs):
'''Eval the left and right nodes, and call the binary operator.
:param node: Binary operator with node.op, node.left, and node.right
properties.
'''
op = cls._get_op(node)
left_node = cls.eval(node.left, subs)
right_node = cls.eval(node.right, subs)
return op(left_node, right_node)
@classmethod
def _unary_op(cls, node, subs):
'''Eval the node operand and call the unary operator.
:param node: Unary operator with node.op and node.operand properties.
'''
op = cls._get_op(node)
return op(cls.eval(node.operand, subs))
@classmethod
def _subs_op(cls, node, subs):
'''Return the value of the variable represented by the node.
:param node: Name node with node.id property to identify the variable.
'''
try:
return subs[node.id]
except KeyError:
raise TypeError(node)
@classmethod
def _call_op(cls, node, subs):
arg_list = []
for node_arg in node.args:
arg_list.append(cls.eval(node_arg, subs))
fun_call = cls._get_op_fun(node)
return fun_call(*arg_list)
@classmethod
def eval(cls, node, subs):
'''The node is actually a tree. The node type i.e. type(node) is:
ast.Num, ast.BinOp, ast.UnaryOp or ast.Name.
Depending on the node type the node will have the following properties:
node.n - Nodes value.
node.id - Node id corresponding to a key in the subs dictionary.
node.op - operation node. Type of node.op identifies the operation.
type(node.op) is one of ast.Add, ast.Sub, ast.Mult, ast.Div,
ast.Pow, ast.BitXor, or ast.USub.
node.left or node.right - Binary operation node needs to have links
to left and right nodes.
node.operand - Unary operation node needs to have an operand.
The binary and unary operations call eval recursively.
'''
# The functional logic is:
# if isinstance(node, ast.Num): # <number>
# return node.n
# elif isinstance(node, ast.BinOp): # <left> <operator> <right>
# return operators[type(node.op)](eval_(node.left, subs),
# eval_(node.right, subs))
# elif isinstance(node, ast.UnaryOp): # <operator> <operand> e.g., -1
# return operators[type(node.op)](eval_(node.operand, subs))
# else:
# try:
# return subs[node.id]
# except KeyError:
# raise TypeError(node)
node_type = type(node)
return {
# Value in the expression. Leaf.
ast.Num: cls._num_op, # <number>
# Bin operation with two operands.
ast.BinOp: cls._bin_op, # <left> <operator> <right>
# Unary operation such as neg.
ast.UnaryOp: cls._unary_op, # <operator> <operand> e.g., -1
# Sub the value for the variable. Leaf.
ast.Name: cls._subs_op, # <variable>
ast.Call: cls._call_op
}[node_type](node, subs)
@classmethod
def eval_expr(cls, expr, subs=None):
'''Evaluates a string expression. The expr string is parsed with ast
resulting in a node tree. Then the eval method is used to recursively
traverse and evaluate the nodes. Symbolic params are taken from subs.
:Example:
>>> eval_expr('2^6')
4
>>> eval_expr('2**6')
64
>>> eval_expr('1 + 2*3**(4^5) / (6 + -7)')
-5.0
>>> eval_expr('x + y', {'x': 1, 'y': 2})
3
:param expr: str. String expression.
:param subs: dict. (default: globals of current and calling stack.)
:returns: Result of running the evaluator.
:implements: IEvaluator.eval_expr
'''
# ref: https://mcmap.net/q/41518/-evaluating-a-mathematical-expression-in-a-string
if subs is None:
# Get the globals
frame = sys._getframe()
subs = {}
subs.update(frame.f_globals)
if frame.f_back:
subs.update(frame.f_back.f_globals)
expr_tree = ast.parse(expr, mode='eval').body
return cls.eval(expr_tree, subs)
Here are some examples:
import sympy
from eval_sympy import Evaluator
# test case...
x = sympy.Symbol('x')
y = sympy.Symbol('y')
expr = x * 2 - y ** 2
# z = expr.subs({x:1, y:2})
str_expr = str(expr)
print str_expr
x = 1
y = 2
out0 = Evaluator.eval_expr(str_expr)
print '(x, y): ({}, {})'.format(x, y)
print str_expr, ' = ', out0
subs1 = {'x': 1, 'y': 2}
out1 = Evaluator.eval_expr(str_expr, subs1)
print 'subs: ', subs1
print str_expr, ' = ', out1
sin_subs = {'x': 1, 'y': 2}
sin_out = Evaluator.eval_expr('sin(log10(x*y))', sin_subs)
print 'sin_subs: ', sin_subs
print 'sin(log10(x*y)) = ', sin_out
Results
2*x - y**2
(x, y): (1, 2)
2*x - y**2 = -2
subs: {'y': 2, 'x': 1}
2*x - y**2 = -2
sin_subs: {'y': 2, 'x': 1}
sin(log10(x*y)) = 0.296504042171
eval. I am rather hoping for a math expression parser library. I updated the question to reflect that, thanks. – Ellieellingerfunctionandcodetypes is(lambda:0).__class__and(lambda:0).func_code.__class__resp. – Frierson