Cython Magic Functions Extension¶
Loading the extension¶
IPtyhon has a cythonmagic extension that contains a number of magic functions for working with Cython code. This extension can be loaded using the %load_ext magic as follows:
%load_ext cythonmagic
The %cython_inline magic¶
The %%cython_inline magic uses Cython.inline to compile a Cython expression. This allows you to enter and run a function body with Cython code. Use a bare return statement to return values.
a = 10
b = 20
%%cython_inline
return a+b
The %cython_pyximport magic¶
The %%cython_pyximport magic allows you to enter arbitrary Cython code into a cell. That Cython code is written as a .pyx file in the current working directory and then imported using pyximport. You have the specify the name of the module that the Code will appear in. All symbols from the module are imported automatically by the magic function.
%%cython_pyximport foo
def f(x):
return 4.0*x
f(10)
The %cython magic¶
Probably the most important magic is the %cython magic. This is similar to the %%cython_pyximport magic, but doesn't require you to specify a module name. Instead, the %%cython magic uses manages everything using temporary files in the ~/.cython/magic directory. All of the symbols in the Cython module are imported automatically by the magic.
Here is a simple example of a Black-Scholes options pricing algorithm written in Cython:
%%cython
cimport cython
from libc.math cimport exp, sqrt, pow, log, erf
@cython.cdivision(True)
cdef double std_norm_cdf(double x) nogil:
return 0.5*(1+erf(x/sqrt(2.0)))
@cython.cdivision(True)
def black_scholes(double s, double k, double t, double v,
double rf, double div, double cp):
"""Price an option using the Black-Scholes model.
s : initial stock price
k : strike price
t : expiration time
v : volatility
rf : risk-free rate
div : dividend
cp : +1/-1 for call/put
"""
cdef double d1, d2, optprice
with nogil:
d1 = (log(s/k)+(rf-div+0.5*pow(v,2))*t)/(v*sqrt(t))
d2 = d1 - v*sqrt(t)
optprice = cp*s*exp(-div*t)*std_norm_cdf(cp*d1) - \
cp*k*exp(-rf*t)*std_norm_cdf(cp*d2)
return optprice
black_scholes(100.0, 100.0, 1.0, 0.3, 0.03, 0.0, -1)
%timeit black_scholes(100.0, 100.0, 1.0, 0.3, 0.03, 0.0, -1)