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Note however that if your distribution ships a version of Cython which is too old you can still use the instructions below to update Cython.
Unlike most Python software, Cython requires a C compiler to be present on the system. The details of getting a C compiler varies according to the system used:. On Ubuntu or Debian, for instance, the command sudo apt-get install build-essential will fetch everything you need.
Windows The CPython project recommends building extension modules including Cython modules with the same compiler that Python was built with.
But to someone who doesn't already drip CPython C modules, Cython is a godsend. It's very easy to learn for anyone familiar with both C and Python.
This shows that we can use the normal Python containers to manage objects. This is extremely convenient. Clearly, if you are building code from scratch and need speed, Cython is an excellent option. For this I really must congratulate the Cython and Pyrex developers. It took me 10 minutes to figure it out how Cython works and I gained a speed up of times!!! Successful in the sense that it was much faster than all code written by my predecessors mainly because the speed scales almost linearly with the number of cores.
Also, the code is shorter and much easier to read and maintain. As a Perl lover, this was impressive. We still get all the benefits of Python such as rapid development and clean object-oriented design patterns but with the speed of C. By simply replacing the class that contained the differential equation with a Cython version the calculation time dropped by a factor 5.
Not bad for half a Sunday afternoons work. I did not have to mess with make files or configure the compiles. Cython integrated well with NumPy and SciPy. This expands the programming tasks you can do with Python substantially. Their user base has tons of legacy code or external libraries that they need to interface, and most of the reason Python has had such a great adoption curve in that space is because Numpy has made the data portion of that interface easy.
Cython makes the code portion quite painless, as well. Just doing that, with no Cython specific code reduced the time of processing 10K records from 2. Not bad for that little work.
This way on machines that do not have a compiler users can still use fastavro. The end result is a package that reads Avro faster than Java and supports both Python 2 and Python 3. Using Cython and a little bit of work th[is] was achieved without too much effort. Zaytsev and Abigail Morrison. Both the Cython version and the C version are about 70x faster than the pure Python version, which uses Numpy arrays.
Fantastic way to write Python bindings for native libs or speed up computationally intensive code without having to write C yourself.
It's been a huge boon.
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