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Determining 32 vs 64 bit in C++
...vironment or not and use that to set my variables.
// Check windows
#if _WIN32 || _WIN64
#if _WIN64
#define ENVIRONMENT64
#else
#define ENVIRONMENT32
#endif
#endif
// Check GCC
#if __GNUC__
#if __x86_64__ || __ppc64__
#define ENVIRONMENT64
#else
#define ENVIRONMENT32
#endif
#endif
Another easi...
How to parse/read a YAML file into a Python object? [duplicate]
...e looks like this:
import yaml
with open('tree.yaml') as f:
# use safe_load instead load
dataMap = yaml.safe_load(f)
The variable dataMap now contains a dictionary with the tree data. If you print dataMap using PrettyPrint, you will get something like:
{'treeroot': {'branch1': {'branch1-...
Redirect stdout to a file in Python?
...
@mgold or you can use sys.stdout = sys.__stdout__ to get it back.
– clemtoy
Jul 9 '15 at 12:52
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show 9 ...
Where in a virtualenv does the custom code go?
...our packages right inside:
/foobar
/bin
{activate, activate.py, easy_install, python}
/include
{python2.6/...}
/lib
{python2.6/...}
/mypackage1
__init__.py
/mypackage2
__init__.py
The advantage of this approach is that you can always be sure to find find the activate...
How can I get dictionary key as variable directly in Python (not by searching from value)?
...f you want to print key and value, use the following:
for key, value in my_dict.iteritems():
print key, value
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...
Python Sets vs Lists
... as lists, except for their immutability.
Iterating
>>> def iter_test(iterable):
... for i in iterable:
... pass
...
>>> from timeit import timeit
>>> timeit(
... "iter_test(iterable)",
... setup="from __main__ import iter_test; iterable = set(range(1...
Why aren't superclass __init__ methods automatically invoked?
Why did the Python designers decide that subclasses' __init__() methods don't automatically call the __init__() methods of their superclasses, as in some other languages? Is the Pythonic and recommended idiom really like the following?
...
Elegant ways to support equivalence (“equality”) in Python classes
... and != operators. In Python, this is made possible by implementing the __eq__ and __ne__ special methods, respectively. The easiest way I've found to do this is the following method:
...
Share Large, Read-Only Numpy Array Between Multiprocessing Processes
...n
from multiprocessing import Process
import sharedmem
import numpy
def do_work(data, start):
data[start] = 0;
def split_work(num):
n = 20
width = n/num
shared = sharedmem.empty(n)
shared[:] = numpy.random.rand(1, n)[0]
print "values are %s" % shared
processes = [Proc...
Getting list of parameter names inside python function [duplicate]
....
>>> func = lambda x, y: (x, y)
>>>
>>> func.__code__.co_argcount
2
>>> func.__code__.co_varnames
('x', 'y')
>>>
>>> def func2(x,y=3):
... print(func2.__code__.co_varnames)
... pass # Other things
...
>>> func2(3,3)
('x', 'y')
>...