C track: compiling C programs.

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Cython is an optimising static compiler for both the Python programming language and the extended Cython programming language based on Pyrex. It makes writing C extensions for Python as easy as Python itself.

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.

We regularly run integration tests against all supported CPython versions and their latest in-development branches to make sure that the generated code stays widely compatible and well adapted to each version. PyPy support is work in progress on both sides and is considered mostly usable since Cython 0.

The latest Generating c source for a binary edition version is always recommended here. All of this makes Cython the ideal language for generating c source for a binary edition external C libraries, embedding CPython into existing applications, and for fast C modules that speed up the execution of Python code. Cython Documentation The Cython Wiki. Smith, O'Reilly Cython: The best of both worldsarticle 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 generating c source for a binary edition 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. Cython is freely available under the open source Apache License.

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. 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 generating c source for a binary edition 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. And through all that, Cython code maintains a high level of integration with Python itself, right down to the stack trace and line numbers.

PayPal has certainly benefitted from their efforts through high-performance Cython users like gevent, lxml, and NumPy. 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. Basically, everything I found Cython emitting was a false positive and a bug in my checker tool [CPyChecker]. Python, which astonished me. 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. 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 generating c source for a binary edition 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 Generating c source for a binary edition 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. Having used swig, hand writing wrappers, and pyrex before i can say i much prefer cython.

Thank you for the generating c source for a binary edition work. Using cython it went from running single calculation in hours to seconds, focking nice The worst you'll usually get is a lack of performance gain at which point cython -a is your friend.

Wringing out all the performance you can get can require a reasonable working knowledge of C -- but you don't have to know it that well to do pretty darn well. It's unfortunate that it's not as wide-spread and I think it's generating c source for a binary edition underappreciated what you can do in Cython. Essentially, it's a superset of the Python language, you can strictly type it and it will compile to C and you will have C speed.

You can easily achieve it, with a syntax more similar to Python. Definitely check out Cython. About Cython Cython is an optimising static compiler for both the Python programming language and the extended Cython programming language based on Pyrex. Cython Tutorial ; Fast Numerical Computations with Cython If you still have questions, feel free to send an email to the cython users mailing list.

Download Cython is freely available under the open source Apache License. What users have to say about Cython: The new implementation also generating c source for a binary edition the compile-time dependency on NumPy and provides numerous additional maintainability benefits by reducing complexity and increasing comprehensibility of the code.

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It is important to understand that while some computer languages e. Scheme or Basic are normally used with an interactive interpreter where you type in commands that are immediately executed , C doesn't work that way. C source code files are always compiled into binary code by a program called a "compiler" and then executed. This is actually a multi-step process which we describe in some detail here.

Regular source code files. These files contain function definitions, and have names which end in ". These files contain function declarations also known as function prototypes and various preprocessor statements see below. They are used to allow source code files to access externally-defined functions.

Header files end in ". These files are produced as the output of the compiler. They consist of function definitions in binary form, but they are not executable by themselves. Object files end in ". These are produced as the output of a program called a "linker". The linker links together a number of object files to produce a binary file which can be directly executed. Binary executables have no special suffix on Unix operating systems, although they generally end in ". There are other kinds of files as well, notably libraries ".

Before the C compiler starts compiling a source code file, the file is processed by a preprocessor. This is in reality a separate program normally called " cpp ", for "C preprocessor" , but it is invoked automatically by the compiler before compilation proper begins.

What the preprocessor does is convert the source code file you write into another source code file you can think of it as a "modified" or "expanded" source code file. That modified file may exist as a real file in the file system, or it may only be stored in memory for a short time before being sent to the compiler. Either way, you don't have to worry about it, but you do have to know what the preprocessor commands do. Preprocessor commands start with the pound sign " ".

There are several preprocessor commands; two of the most important are:. For instance, the statement:. This is important in case you need to change the constant value later on; it's much less bug-prone to change it once, in the define , than to have to change it in multiple places scattered all over the code. This is used to access function definitions defined outside of a source code file. In this case, we use include in order to be able to use functions such as printf and scanf , whose declarations are located in the file stdio.

C compilers do not allow you to use a function unless it has previously been declared or defined in that file; include statements are thus the way to re-use previously-written code in your C programs. There are a number of other preprocessor commands as well, but we will deal with them as we need them. After the C preprocessor has included all the header files and expanded out all the define and include statements as well as any other preprocessor commands that may be in the original file , the compiler can compile the program.

It does this by turning the C source code into an object code file, which is a file ending in ". Object code is not directly executable, though. In order to make an executable, you also have to add code for all of the library functions that were include d into the file this is not the same as including the declarations, which is what include does. This is the job of the linker see the next section. This tells the compiler to run the preprocessor on the file foo. The -c option means to compile the source code file into an object file but not to invoke the linker.

If your entire program is in one source code file, you can instead do this:. This tells the compiler to run the preprocessor on foo.

The -o option states that the next word on the line is the name of the binary executable file program. If you don't specify the -o , i.

Note also that the name of the compiler we are using is gcc , which stands for "GNU C compiler" or "GNU compiler collection" depending on who you listen to. Other C compilers exist; many of them have the name cc , for "C compiler". On Linux systems cc is an alias for gcc. The job of the linker is to link together a bunch of object files. This includes both the object files that the compiler created from your source code files as well as object files that have been pre-compiled for you and collected into library files.

These files have names which end in. Like the preprocessor, the linker is a separate program called ld. Also like the preprocessor, the linker is invoked automatically for you when you use the compiler. The normal way of using the linker is as follows:. This line tells the compiler to link together three object files foo.

This is all you need to know to begin compiling your own C programs. Generally, we also recommend that you use the -Wall command-line option:. The -Wall option causes the compiler to warn you about legal but dubious code constructs, and will help you catch a lot of bugs very early.

If you want to be even more anal and who doesn't? The -Wstrict-prototypes option means that the compiler will warn you if you haven't written correct prototypes for all your functions.

The -ansi and -pedantic options cause the compiler to warn about any non-portable construct e. The GNU Info documentation on gcc. This is far more information than most people could possibly absorb in the average millenium.