# Source code for sympy.core.sympify

```
"""sympify -- convert objects SymPy internal format"""
from __future__ import print_function, division
from inspect import getmro
from .core import all_classes as sympy_classes
from .compatibility import iterable, string_types, range
from .evaluate import global_evaluate
class SympifyError(ValueError):
def __init__(self, expr, base_exc=None):
self.expr = expr
self.base_exc = base_exc
def __str__(self):
if self.base_exc is None:
return "SympifyError: %r" % (self.expr,)
return ("Sympify of expression '%s' failed, because of exception being "
"raised:\n%s: %s" % (self.expr, self.base_exc.__class__.__name__,
str(self.base_exc)))
converter = {} # See sympify docstring.
class CantSympify(object):
"""
Mix in this trait to a class to disallow sympification of its instances.
Examples
========
>>> from sympy.core.sympify import sympify, CantSympify
>>> class Something(dict):
... pass
...
>>> sympify(Something())
{}
>>> class Something(dict, CantSympify):
... pass
...
>>> sympify(Something())
Traceback (most recent call last):
...
SympifyError: SympifyError: {}
"""
pass
def _convert_numpy_types(a, **sympify_args):
"""
Converts a numpy datatype input to an appropriate sympy type.
"""
import numpy as np
if not isinstance(a, np.floating):
if np.iscomplex(a):
return converter[complex](np.asscalar(a))
else:
return sympify(np.asscalar(a), **sympify_args)
else:
try:
from sympy.core.numbers import Float
prec = np.finfo(a).nmant + 1
# E.g. double precision means prec=53 but nmant=52
# Leading bit of mantissa is always 1, so is not stored
a = str(list(np.reshape(np.asarray(a),
(1, np.size(a)))[0]))[1:-1]
return Float(a, precision=prec)
except NotImplementedError:
raise SympifyError('Translation for numpy float : %s '
'is not implemented' % a)
[docs]def sympify(a, locals=None, convert_xor=True, strict=False, rational=False,
evaluate=None):
"""Converts an arbitrary expression to a type that can be used inside SymPy.
For example, it will convert Python ints into instances of sympy.Integer,
floats into instances of sympy.Float, etc. It is also able to coerce symbolic
expressions which inherit from Basic. This can be useful in cooperation
with SAGE.
It currently accepts as arguments:
- any object defined in sympy
- standard numeric python types: int, long, float, Decimal
- strings (like "0.09" or "2e-19")
- booleans, including ``None`` (will leave ``None`` unchanged)
- lists, sets or tuples containing any of the above
.. warning::
Note that this function uses ``eval``, and thus shouldn't be used on
unsanitized input.
If the argument is already a type that SymPy understands, it will do
nothing but return that value. This can be used at the beginning of a
function to ensure you are working with the correct type.
>>> from sympy import sympify
>>> sympify(2).is_integer
True
>>> sympify(2).is_real
True
>>> sympify(2.0).is_real
True
>>> sympify("2.0").is_real
True
>>> sympify("2e-45").is_real
True
If the expression could not be converted, a SympifyError is raised.
>>> sympify("x***2")
Traceback (most recent call last):
...
SympifyError: SympifyError: "could not parse u'x***2'"
Locals
------
The sympification happens with access to everything that is loaded
by ``from sympy import *``; anything used in a string that is not
defined by that import will be converted to a symbol. In the following,
the ``bitcount`` function is treated as a symbol and the ``O`` is
interpreted as the Order object (used with series) and it raises
an error when used improperly:
>>> s = 'bitcount(42)'
>>> sympify(s)
bitcount(42)
>>> sympify("O(x)")
O(x)
>>> sympify("O + 1")
Traceback (most recent call last):
...
TypeError: unbound method...
In order to have ``bitcount`` be recognized it can be imported into a
namespace dictionary and passed as locals:
>>> from sympy.core.compatibility import exec_
>>> ns = {}
>>> exec_('from sympy.core.evalf import bitcount', ns)
>>> sympify(s, locals=ns)
6
In order to have the ``O`` interpreted as a Symbol, identify it as such
in the namespace dictionary. This can be done in a variety of ways; all
three of the following are possibilities:
>>> from sympy import Symbol
>>> ns["O"] = Symbol("O") # method 1
>>> exec_('from sympy.abc import O', ns) # method 2
>>> ns.update(dict(O=Symbol("O"))) # method 3
>>> sympify("O + 1", locals=ns)
O + 1
If you want *all* single-letter and Greek-letter variables to be symbols
then you can use the clashing-symbols dictionaries that have been defined
there as private variables: _clash1 (single-letter variables), _clash2
(the multi-letter Greek names) or _clash (both single and multi-letter
names that are defined in abc).
>>> from sympy.abc import _clash1
>>> _clash1
{'C': C, 'E': E, 'I': I, 'N': N, 'O': O, 'Q': Q, 'S': S}
>>> sympify('I & Q', _clash1)
I & Q
Strict
------
If the option ``strict`` is set to ``True``, only the types for which an
explicit conversion has been defined are converted. In the other
cases, a SympifyError is raised.
>>> print(sympify(None))
None
>>> sympify(None, strict=True)
Traceback (most recent call last):
...
SympifyError: SympifyError: None
Evaluation
----------
If the option ``evaluate`` is set to ``False``, then arithmetic and
operators will be converted into their SymPy equivalents and the
``evaluate=False`` option will be added. Nested ``Add`` or ``Mul`` will
be denested first. This is done via an AST transformation that replaces
operators with their SymPy equivalents, so if an operand redefines any
of those operations, the redefined operators will not be used.
>>> sympify('2**2 / 3 + 5')
19/3
>>> sympify('2**2 / 3 + 5', evaluate=False)
2**2/3 + 5
Extending
---------
To extend ``sympify`` to convert custom objects (not derived from ``Basic``),
just define a ``_sympy_`` method to your class. You can do that even to
classes that you do not own by subclassing or adding the method at runtime.
>>> from sympy import Matrix
>>> class MyList1(object):
... def __iter__(self):
... yield 1
... yield 2
... return
... def __getitem__(self, i): return list(self)[i]
... def _sympy_(self): return Matrix(self)
>>> sympify(MyList1())
Matrix([
[1],
[2]])
If you do not have control over the class definition you could also use the
``converter`` global dictionary. The key is the class and the value is a
function that takes a single argument and returns the desired SymPy
object, e.g. ``converter[MyList] = lambda x: Matrix(x)``.
>>> class MyList2(object): # XXX Do not do this if you control the class!
... def __iter__(self): # Use _sympy_!
... yield 1
... yield 2
... return
... def __getitem__(self, i): return list(self)[i]
>>> from sympy.core.sympify import converter
>>> converter[MyList2] = lambda x: Matrix(x)
>>> sympify(MyList2())
Matrix([
[1],
[2]])
Notes
=====
Sometimes autosimplification during sympification results in expressions
that are very different in structure than what was entered. Until such
autosimplification is no longer done, the ``kernS`` function might be of
some use. In the example below you can see how an expression reduces to
-1 by autosimplification, but does not do so when ``kernS`` is used.
>>> from sympy.core.sympify import kernS
>>> from sympy.abc import x
>>> -2*(-(-x + 1/x)/(x*(x - 1/x)**2) - 1/(x*(x - 1/x))) - 1
-1
>>> s = '-2*(-(-x + 1/x)/(x*(x - 1/x)**2) - 1/(x*(x - 1/x))) - 1'
>>> sympify(s)
-1
>>> kernS(s)
-2*(-(-x + 1/x)/(x*(x - 1/x)**2) - 1/(x*(x - 1/x))) - 1
"""
if evaluate is None:
if global_evaluate[0] is False:
evaluate = global_evaluate[0]
else:
evaluate = True
try:
if a in sympy_classes:
return a
except TypeError: # Type of a is unhashable
pass
try:
cls = a.__class__
except AttributeError: # a is probably an old-style class object
cls = type(a)
if cls in sympy_classes:
return a
if cls is type(None):
if strict:
raise SympifyError(a)
else:
return a
# Support for basic numpy datatypes
# Note that this check exists to avoid importing NumPy when not necessary
if type(a).__module__ == 'numpy':
import numpy as np
if np.isscalar(a):
return _convert_numpy_types(a, locals=locals,
convert_xor=convert_xor, strict=strict, rational=rational,
evaluate=evaluate)
try:
return converter[cls](a)
except KeyError:
for superclass in getmro(cls):
try:
return converter[superclass](a)
except KeyError:
continue
if isinstance(a, CantSympify):
raise SympifyError(a)
try:
return a._sympy_()
except AttributeError:
pass
if not strict:
# Put numpy array conversion _before_ float/int, see
# <https://github.com/sympy/sympy/issues/13924>.
try:
from ..tensor.array import Array
return Array(a.flat, a.shape) # works with e.g. NumPy arrays
except AttributeError:
pass
if not isinstance(a, string_types):
for coerce in (float, int):
try:
return sympify(coerce(a))
except (TypeError, ValueError, AttributeError, SympifyError):
continue
if strict:
raise SympifyError(a)
if iterable(a):
try:
return type(a)([sympify(x, locals=locals, convert_xor=convert_xor,
rational=rational) for x in a])
except TypeError:
# Not all iterables are rebuildable with their type.
pass
if isinstance(a, dict):
try:
return type(a)([sympify(x, locals=locals, convert_xor=convert_xor,
rational=rational) for x in a.items()])
except TypeError:
# Not all iterables are rebuildable with their type.
pass
# At this point we were given an arbitrary expression
# which does not inherit from Basic and doesn't implement
# _sympy_ (which is a canonical and robust way to convert
# anything to SymPy expression).
#
# As a last chance, we try to take "a"'s normal form via unicode()
# and try to parse it. If it fails, then we have no luck and
# return an exception
try:
from .compatibility import unicode
a = unicode(a)
except Exception as exc:
raise SympifyError(a, exc)
from sympy.parsing.sympy_parser import (parse_expr, TokenError,
standard_transformations)
from sympy.parsing.sympy_parser import convert_xor as t_convert_xor
from sympy.parsing.sympy_parser import rationalize as t_rationalize
transformations = standard_transformations
if rational:
transformations += (t_rationalize,)
if convert_xor:
transformations += (t_convert_xor,)
try:
a = a.replace('\n', '')
expr = parse_expr(a, local_dict=locals, transformations=transformations, evaluate=evaluate)
except (TokenError, SyntaxError) as exc:
raise SympifyError('could not parse %r' % a, exc)
return expr
def _sympify(a):
"""
Short version of sympify for internal usage for __add__ and __eq__ methods
where it is ok to allow some things (like Python integers and floats) in
the expression. This excludes things (like strings) that are unwise to
allow into such an expression.
>>> from sympy import Integer
>>> Integer(1) == 1
True
>>> Integer(1) == '1'
False
>>> from sympy.abc import x
>>> x + 1
x + 1
>>> x + '1'
Traceback (most recent call last):
...
TypeError: unsupported operand type(s) for +: 'Symbol' and 'str'
see: sympify
"""
return sympify(a, strict=True)
def kernS(s):
"""Use a hack to try keep autosimplification from distributing a
a number into an Add; this modification doesn't
prevent the 2-arg Mul from becoming an Add, however.
Examples
========
>>> from sympy.core.sympify import kernS
>>> from sympy.abc import x, y, z
The 2-arg Mul distributes a number (or minus sign) across the terms
of an expression, but kernS will prevent that:
>>> 2*(x + y), -(x + 1)
(2*x + 2*y, -x - 1)
>>> kernS('2*(x + y)')
2*(x + y)
>>> kernS('-(x + 1)')
-(x + 1)
If use of the hack fails, the un-hacked string will be passed to sympify...
and you get what you get.
XXX This hack should not be necessary once issue 4596 has been resolved.
"""
import string
from random import choice
from sympy.core.symbol import Symbol
hit = False
quoted = '"' in s or "'" in s
if '(' in s and not quoted:
if s.count('(') != s.count(")"):
raise SympifyError('unmatched left parenthesis')
# strip all space from s
s = ''.join(s.split())
olds = s
# now use space to represent a symbol that
# will
# step 1. turn potential 2-arg Muls into 3-arg versions
# 1a. *( -> * *(
s = s.replace('*(', '* *(')
# 1b. close up exponentials
s = s.replace('** *', '**')
# 2. handle the implied multiplication of a negated
# parenthesized expression in two steps
# 2a: -(...) --> -( *(...)
target = '-( *('
s = s.replace('-(', target)
# 2b: double the matching closing parenthesis
# -( *(...) --> -( *(...))
i = nest = 0
assert target.endswith('(') # assumption below
while True:
j = s.find(target, i)
if j == -1:
break
j += len(target) - 1
for j in range(j, len(s)):
if s[j] == "(":
nest += 1
elif s[j] == ")":
nest -= 1
if nest == 0:
break
s = s[:j] + ")" + s[j:]
i = j + 2 # the first char after 2nd )
if ' ' in s:
# get a unique kern
kern = '_'
while kern in s:
kern += choice(string.ascii_letters + string.digits)
s = s.replace(' ', kern)
hit = kern in s
for i in range(2):
try:
expr = sympify(s)
break
except: # the kern might cause unknown errors, so use bare except
if hit:
s = olds # maybe it didn't like the kern; use un-kerned s
hit = False
continue
expr = sympify(s) # let original error raise
if not hit:
return expr
rep = {Symbol(kern): 1}
def _clear(expr):
if isinstance(expr, (list, tuple, set)):
return type(expr)([_clear(e) for e in expr])
if hasattr(expr, 'subs'):
return expr.subs(rep, hack2=True)
return expr
expr = _clear(expr)
# hope that kern is not there anymore
return expr
```