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Learning Cython Programming (Second Edition)

You're reading from   Learning Cython Programming (Second Edition) Expand your existing legacy applications in C using Python

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Product type Paperback
Published in Feb 2016
Publisher Packt
ISBN-13 9781783551675
Length 110 pages
Edition 2nd Edition
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Author (1):
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Philip Herron Philip Herron
Author Profile Icon Philip Herron
Philip Herron
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Toc

Unit testing the native code


Another use of Cython is unit testing the core functionality of shared C libraries. If you maintain a .pxd file (this is all you need really), you can write your own wrapper classes and do scalability testing of data structures with the expressiveness of Python. For example, we can write unit tests for something such as std::map and std::vector as follows:

from libcpp.vector cimport vector

PASSED = False

cdef vector[int] vect
cdef int i
for i in range(10):
    vect.push_back(i)
for i in range(10):
    print vect[i]

PASSED = True

Then, write a test for map as follows:

from libcpp.map cimport map

PASSED = False

cdef map[int,int] mymap
cdef int i
for i in range (10):
    mymap[i] = (i + 1)

for i in range (10):
    print mymap[i]

PASSED = True

Then, if we compile them into separate modules, we can simply write a test executor:

#!/usr/bin/env python
print "Cython C++ Unit test executor"

print "[TEST] std::map"
import testmap
assert testmap.PASSED
print "[PASS...
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