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Kirill Smelkov
cython
Commits
692abf58
Commit
692abf58
authored
Jun 17, 2018
by
scoder
Committed by
GitHub
Jun 17, 2018
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Merge pull request #2353 from gabrieldemarmiesse/test_memory_allocation_1
Added tests for "memory allocation" Part 1
parents
3464b14e
1b964d5e
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2 changed files
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31 additions
and
21 deletions
+31
-21
docs/examples/tutorial/memory_allocation/malloc.pyx
docs/examples/tutorial/memory_allocation/malloc.pyx
+19
-0
docs/src/tutorial/memory_allocation.rst
docs/src/tutorial/memory_allocation.rst
+12
-21
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docs/examples/tutorial/memory_allocation/malloc.pyx
0 → 100644
View file @
692abf58
import
random
from
libc.stdlib
cimport
malloc
,
free
def
random_noise
(
int
number
=
1
):
cdef
int
i
# allocate number * sizeof(double) bytes of memory
cdef
double
*
my_array
=
<
double
*>
malloc
(
number
*
sizeof
(
double
))
if
not
my_array
:
raise
MemoryError
()
try
:
ran
=
random
.
normalvariate
for
i
in
range
(
number
):
my_array
[
i
]
=
ran
(
0
,
1
)
return
[
x
for
x
in
my_array
[:
number
]]
finally
:
# return the previously allocated memory to the system
free
(
my_array
)
docs/src/tutorial/memory_allocation.rst
View file @
692abf58
...
...
@@ -32,27 +32,18 @@ in cython from ``clibc.stdlib``. Their signatures are:
void* realloc(void* ptr, size_t size)
void free(void* ptr)
A very simple example of malloc usage is the following::
import random
from libc.stdlib cimport malloc, free
def random_noise(int number=1):
cdef int i
# allocate number * sizeof(double) bytes of memory
cdef double *my_array = <double *>malloc(number * sizeof(double))
if not my_array:
raise MemoryError()
try:
ran = random.normalvariate
for i in range(number):
my_array[i] = ran(0,1)
return [ my_array[i] for i in range(number) ]
finally:
# return the previously allocated memory to the system
free(my_array)
A very simple example of malloc usage is the following:
.. literalinclude:: ../../examples/tutorial/memory_allocation/malloc.pyx
:linenos:
.. note::
Here we take Python doubles (with ``ran(0, 1)``) and convert
them to C doubles when putting them in ``my_array``. After that,
we put them back into a Python list at line 19. So those C doubles
are converted again into Python doubles. This is highly inefficient,
and only for demo purposes.
Note that the C-API functions for allocating memory on the Python heap
are generally preferred over the low-level C functions above as the
...
...
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