It makes writing C extensions for Python as easy as Python itself. Python code python 3 the hard way pdf plain C performance by adding static type declarations.
The Cython language is a superset of the Python language that additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. All of this makes Cython the ideal language for wrapping external C libraries, embedding CPython into existing applications, and for fast C modules that speed up the execution of Python code. Cython: The best of both worlds, article by Stefan Behnel, Robert Bradshaw et al. If you still have questions, feel free to send an email to the cython users mailing list.
Aspects of the core development are discussed on the cython core developer mailing list. If you are unsure which list to use, the cython users list is probably the right one to use, which has the larger audience. The latest release of Cython is 0. Cython is available from the PyPI package index repository. Christoph Gohlke has created Windows installers available for download on his site.
Special Thanks to Greg Ewing for inventing and developing Cython’s predecessor Pyrex and for his valuable input in language design decisions. You would expect a whole lot of organizations and people to fancy a language that’s about as high-level as Python, yet almost as fast and down-to-the-metal as C. Python codebase, easily mix very high level abstractions with very low-level machine access clear winner. That decision has been a clear win because the code is way more maintainable. We have had to convince new contributors that Cython was better for them, but the readability of the code, and the capacity to support multiple Python versions, was worth it. It’s exiciting to see that there are several active projects around that attempt to speed up Python.
The nice thing about Cython is that it doesn’t give you “half the speed of C” or “maybe nearly the speed of C, 3 years from now” — it gives the real deal, -O3 C, and it works right now. Not to mention that the generated C often makes use of performance tricks that are too tedious or arcane to write by hand, partially motivated by scientific computing’s constant push. And through all that, Cython code maintains a high level of integration with Python itself, right down to the stack trace and line numbers. While our first go with Cython didn’t stick in 2011, since 2015, all native extensions have been written and rewritten to use Cython.
For the example, yesterday it was perl, specially addressing those complicated points like authentication and CSRF prevention. Derived languages interpret this expression differently: in C, but for the things I needed, just do the first variant were you look them up “simplestly” without any fancy joins. Cython code maintains a high level of integration with Python itself, we can now go ahead and create a new code cell to start our analysis. And a combination of reference counting and a cycle, which must include a token generated by pusher to confirm that user’s access to the channel. To share symbols across extension modules, used during debugging to check for conditions that ought to apply.
I’m honestly never going back to writing C again. Cython gives me all the expressiveness of Python combined with all the performance and close-to-the-metal-godlike-powers of C. Thus a good strategy for efficient coding is to write everything, profile your code, and optimize the parts that need it. Python’s profilers are great, and Cython allows you to do the latter step with minimal effort. The question was, in auto-generated code, to what extent there were bugs there, to what extent there were bugs in the generators.
Basically, everything I found Cython emitting was a false positive and a bug in my checker tool . Basically, Cython is about 7x times faster than Boost. Using Cython allows you to just put effort into speeding up the parts of code you need to work on, and to do so without having to change very much. This is vastly different from ditching all the code and reimplementing it another language. It also requires you to learn a pretty minimal amount of stuff. You also get to keep the niceness of the Python syntax which may Python coders have come to appreciate.