Reputation: 26346
My website runs this Python script that would be way more optimized if Cython is used. Recently I needed to add Sympy with Lambdify, and this is not going well with Cython.
So I stripped the problem to a minimum working example. In the code, I have a dictionary with string keys with values that are lists. I would like to use these keys as variables. In the following simplified example, there's only 1 variable, but generally I need more. Please check the following example:
import numpy as np
from sympy.parsing.sympy_parser import parse_expr
from sympy.utilities.lambdify import lambdify, implemented_function
from sympy import S, Symbol
from sympy.utilities.autowrap import ufuncify
def CreateMagneticFieldsList(dataToSave,equationString,DSList):
expression = S(equationString)
numOfElements = len(dataToSave["MagneticFields"])
#initialize the magnetic field output array
magFieldsArray = np.empty(numOfElements)
magFieldsArray[:] = np.NaN
lam_f = lambdify(tuple(DSList),expression,modules='numpy')
try:
# pass
for i in range(numOfElements):
replacementList = np.zeros(len(DSList))
for j in range(len(DSList)):
replacementList[j] = dataToSave[DSList[j]][i]
try:
val = np.double(lam_f(*replacementList))
except:
val = np.nan
magFieldsArray[i] = val
except:
print("Error while evaluating the magnetic field expression")
return magFieldsArray
list={"MagneticFields":[1,2,3,4,5]}
out=CreateMagneticFieldsList(list,"MagneticFields*5.1",["MagneticFields"])
print(out)
Let's call this test.py
. This works very well. Now I would like to cythonize this, so I use the following script:
#!/bin/bash
cython --embed -o test.c test.py
gcc -pthread -fPIC -fwrapv -Ofast -Wall -L/lib/x86_64-linux-gnu/ -lpython3.4m -I/usr/include/python3.4 -o test.exe test.c
Now if I execute ./test.exe
, it throws an exception! Here's the exception:
Traceback (most recent call last):
File "test.py", line 42, in init test (test.c:1811)
out=CreateMagneticFieldsList(list,"MagneticFields*5.1",["MagneticFields"])
File "test.py", line 19, in test.CreateMagneticFieldsList (test.c:1036)
lam_f = lambdify(tuple(DSList),expression,modules='numpy')
File "/usr/local/lib/python3.4/dist-packages/sympy/utilities/lambdify.py", line 363, in lambdify
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
AttributeError: 'NoneType' object has no attribute 'f_locals'
So the question is: How can I get lambdify to work with Cython?
Notes: I would like to point out that I have Debian Jessie, and that's why I'm using Python 3.4. Also I would like to point out that I don't have any problem with Cython when not using lambdify
. Also I would like to point out that Cython is updated to the last version with pip3 install cython --upgrade
.
Upvotes: 3
Views: 476
Reputation: 30917
This is a something of a workround to the real problem (identified in the comments and @jjhakala's answer) that Cython doesn't generate full tracebacks/introspection information for compiled functions. I gather from your comments that you'd like to keep most of your program compiled with Cython for speed reasons.
The "solution" is to use the Python interpreter for only the individual function that needs to call lambdify
and leave the rest in Cython. You can do this using exec
.
A very simple example of the idea is
exec("""
def f(func_to_call):
return func_to_call()""")
# a Cython compiled version
def f2(func_to_call):
return func_to_call())
This can be compiled as a Cython module and imported, and upon being imported the Python interpreter runs the code in the string, and correctly adds f
to the module globals. If we create a pure Python function
def g():
return inspect.currentframe().f_back.f_locals
calling cython_module.f(g)
gives me a dictionary with key func_to_call
(as expected) while cython_module.f2(g)
gives me the __main__
module globals (but this is because I'm running from an interpreter rather than using --embed
).
Edit: Full example, based on your code
from sympy import S, lambdify # I'm assuming "S" comes from sympy
import numpy as np
CreateMagneticFieldsList = None # stops a compile error about CreateMagneticFieldsList being undefined
exec("""def CreateMagneticFieldsList(dataToSave,equationString,DSList):
expression = S(equationString)
numOfElements = len(dataToSave["MagneticFields"])
#initialize the magnetic field output array
magFieldsArray = np.empty(numOfElements)
magFieldsArray[:] = np.NaN
lam_f = lambdify(tuple(DSList),expression,modules='numpy')
try:
# pass
for i in range(numOfElements):
replacementList = np.zeros(len(DSList))
for j in range(len(DSList)):
replacementList[j] = dataToSave[DSList[j]][i]
try:
val = np.double(lam_f(*replacementList))
except:
val = np.nan
magFieldsArray[i] = val
except:
print("Error while evaluating the magnetic field expression")
return magFieldsArray""")
list={"MagneticFields":[1,2,3,4,5]}
out=CreateMagneticFieldsList(list,"MagneticFields*5.1",["MagneticFields"])
print(out)
When compiled with your script this prints
[ 5.1 10.2 15.3 20.4 25.5 ]
Substantially all I've done is wrapped your function in an exec
statement, so it's executed by the Python interpreter. This part won't see any benefit from Cython, however the rest of your program still will. If you want to maximise the amount compiled with Cython you could divide it up into multiple functions so that only the small part containing lambdify
is in the exec
.
Upvotes: 4
Reputation: 6214
It is stated in cython docs - limitations that
Stack frames
Currently we generate fake tracebacks as part of exception propagation, but don’t fill in locals and can’t fill in co_code. To be fully compatible, we would have to generate these stack frame objects at function call time (with a potential performance penalty). We may have an option to enable this for debugging.
f_locals
in
AttributeError: 'NoneType' object has no attribute 'f_locals'
seems to point towards this incompability issue.
Upvotes: 2