Python's power comes from the packages that come with it. You can use Python to interface external libraries but you can use it to inspect Python itself. Much of what you find on this page
The nargin, nargout emulation
The inspect module allows to look at the context in which a function is executed.
An example is implemented in 'test_nargin.py'.
Anonymous functions '@' and lambda
Python 'lambda' has a very similar functionality to MALTAB's '@' symbol. There are however subtle differences in treatment of local variables variables. Python uses references
Python and numpy (no OMPC)
| MATLAB | >>> a = zeros([1,5]);
>>> b = lambda x: a+x;
>>> b(2)
array([[ 2., 2., 2., 2., 2.]])
>>> a[:] = ones([1,5]);
>>> a
array([[ 1., 1., 1., 1., 1.]])
>>> b(2)
array([[ 3., 3., 3., 3., 3.]]) | >> a = zeros(1,5);
>> b = @(x) a+x;
>> b(2)
ans =
2 2 2 2 2
>> a(:) = ones(1,5);
>> a
a =
1 1 1 1 1
>> b(2)
ans =
2 2 2 2 2
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The possible solution is to implement 'anonymous' function that takes MATLAB's '@' and returns a regular python function with local variables that are copies of the parameter values.
Strings
All strings have to compiled using the raw operator
'\1' ---> r'\1'
espacially in the case above, common in regular expressions, Python interprets '\1' as '\x01'.
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