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How to display request headers with command line curl
Command line curl can display response header by using -D option, but I want to see what request header it is sending. How can I do that?
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When to use Cast() and Oftype() in Linq
... two methods of casting types to IEnumerable from an Arraylist in Linq and wondering in which cases to use them?
7 Answ...
What is __init__.py for?
... documentation.
Python defines two types of packages, regular packages and namespace packages. Regular packages are traditional packages as they existed in Python 3.2 and earlier. A regular package is typically implemented as a directory containing an __init__.py file. When a regular package is ...
How to print a list of symbols exported from a dynamic library
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man 1 nm is self-contained and will continue working when command line changes :p
– MK.
Oct 16 '15 at 12:33
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Why does the order of the loops affect performance when iterating over a 2D array?
... are two programs that are almost identical except that I switched the i and j variables around. They both run in different amounts of time. Could someone explain why this happens?
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ImportError: No module named PIL
I use this command in the shell to install PIL:
22 Answers
22
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HashMap and int as key
I am trying to build a HashMap which will have integer as keys and objects as values.
11 Answers
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Difference between static and shared libraries?
What is the difference between static and shared libraries?
8 Answers
8
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What is a “static” function in C?
...minology never uses the word "method"; that's Java terminology -- in C++ standard documents it is always called "member function" (see this answer or this glossary of C++ vs Java terms (e.g. C++ uses "data member" and Java uses "field", etc)).
– ShreevatsaR
Jan...
Generate random numbers with a given (numerical) distribution
... You can then use the rvs() method of the distribution object to generate random numbers.
As pointed out by Eugene Pakhomov in the comments, you can also pass a p keyword parameter to numpy.random.choice(), e.g.
numpy.random.choice(numpy.arange(1, 7), p=[0.1, 0.05, 0.05, 0.2, 0.4, 0.2])
If you a...