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All in all: there is no general answer for your question. If you have Python code that is performance-critical, try to use as much builtin functionality as possible (or ask a "How do I make my Python code faster" question). If that doesn't help, try to identify the code and port it to C (or Cython) and use the extension.

Try ShedSkin Python-to-C++ compiler, but it is far from perfect. Also there is Psyco - Python JIT if only speedup is needed. But IMHO this is not worth the effort. For speed-critical parts of code best solution would be to write them as C/C++ extensions.

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PyPy is a project to reimplement Python in Python, using compilation to native code as one of the implementation strategies (others being a VM with JIT, using JVM, etc.). Their compiled C versions run slower than CPython on average but much faster for some programs.

Jython has a compiler targeting JVM bytecode. The bytecode is fully dynamic, just like the Python language itself! Very cool. (Yes, as Greg Hewgill's answer alludes, the bytecode does use the Jython runtime, and so the Jython jar file must be distributed with your app.)

The answer is "Yes, it is possible". You could take Python code and attempt to compile it into the equivalent C code using the CPython API. In fact, there used to be a Python2C project that did just that, but I haven't heard about it in many years (back in the Python 1.5 days is when I last saw it.)

You could attempt to translate the Python code into native C as much as possible, and fall back to the CPython API when you need actual Python features. I've been toying with that idea myself the last month or two. It is, however, an awful lot of work, and an enormous amount of Python features are very hard to translate into C: nested functions, generators, anything but simple classes with simple methods, anything involving modifying module globals from outside the module, etc, etc.

If what you are looking for is an easy way to run Python code from C without relying on execp stuff. You could generate a shared library from python code wrapped with a few calls to Python embedding API. Well the application is a shared library, an .so that you can use in many other libraries/applications.

Also there is numba but they both don't aim to do what you want exactly. Generating a C header from Python code is possible, but only if you specify the how to convert the Python types to C types or can infer that information. See python astroid for a Python ast analyzer.

It does correctly call the function and it gets to the ret instruction. But when it tries to execute the ret instruction, it has a SIGBUS error. Is it because I'm executing code on a page that is not cleared for execution or something like that?

The second problem might be that the code you are invoking is invalid in some way. There's a certain procedure to calling a method in C, called the calling convention (you might be using the "cdecl" one, for example). It might not be enough for the called function to just "ret". It might also need to do some stack cleanup etc. otherwise the program will behave unexpectedly. This might prove an issue once you get past the first problem.

As everyone already said, you must ensure prog[] is executable, however the proper way to do it, unless you're writing a JIT compiler, is to put the symbol in an executable area, either by using a linker script or by specifying the section in the C code if the compiler allows , e.g.:

Virtually all C compilers will let you do this by embedding regular assembly language in your code. Of course it's a non-standard extension to C, but compiler writers recognise that it's often necessary. As a non-standard extension, you'll have to read your compiler manual and check how to do it, but the GCC "asm" extension is a fairly standard approach.

If you're writing the assembler code yourself, there is no good reason to set up that assembler as an array of bytes. It's not just a code smell - I'd say it is a genuine error which could only happen by being unaware of the "asm" extension which is the right way to embed assembler in your C.

Essentially this has been clamped down on because it was an open invitation to virus writers. But you can allocate and buffer and set it up with native machinecode in straight C - that's no problem. The issue is calling it. Whilst you can try setting up a function pointer with the address of the buffer and calling it, that's highly unlikely to work, and highly likely to break on the next version of the compiler if somehow you do manage to coax it into doing what you want. So the best bet is to simply resort to a bit of inline assembly, to set up the return and jump to the automatically generated code. But if the system protects against this, you'll have to find methods of circumventing the protection, as Rudi described in his answer (but very specific to one particular system).

In computer programming, machine code is computer code consisting of machine language instructions, which are used to control a computer's central processing unit (CPU). Although decimal computers were once common, the contemporary marketplace is dominated by binary computers; for those computers, machine code is "the binary representation of a computer program which is actually read and interpreted by the computer. A program in machine code consists of a sequence of machine instructions (possibly interspersed with data)."[1]

Early CPUs had specific machine code that might break backward compatibility with each new CPU released. The notion of an instruction set architecture (ISA) defines and specifies the behavior and encoding in memory of the instruction set of the system, without specifying its exact implementation. This acts as an abstraction layer, enabling compatibility within the same family of CPUs, so that machine code written or generated according to the ISA for the family will run on all CPUs in the family, including future CPUs.

In general, each architecture family (e.g. x86, ARM) has its own ISA, and hence its own specific machine code language. There are exceptions, such as the VAX architecture, which included optional support of the PDP-11 instruction set and IA-64, which included optional support of the IA-32 instruction set. Another example is the PowerPC 615, a processor designed to natively process both PowerPC and x86 instructions.

Machine code is a strictly numerical language, and is the lowest-level interface to the CPU intended for a programmer. Assembly language provides a direct mapping between the numerical machine code and a human-readable version where numerical opcodes and operands are replaced by readable strings (e.g. 0x90 is the NOP instruction on x86). While it is possible to write programs directly in machine code, managing individual bits and calculating numerical addresses and constants manually is tedious and error-prone. For this reason, programs are very rarely written directly in machine code in modern contexts, but may be done for low-level debugging, program patching (especially when assembler source is not available) and assembly language disassembly.

The majority of practical programs today are written in higher-level languages. Those programs are either translated into machine code by a compiler, or are interpreted by an interpreter, usually after being translated into an intermediate code, such as a bytecode, that is then interpreted.[nb 1]

Machine code is by definition the lowest level of programming detail visible to the programmer, but internally many processors use microcode or optimize and transform machine code instructions into sequences of micro-ops. Microcode and micro-ops are not generally considered to be machine code; except on some machines, the user cannot write microcode or micro-ops, and the operation of microcode and the transformation of machine-code instructions into micro-ops happens transparently to the programmer except for performance related side effects.

Every processor or processor family has its own instruction set. Instructions are patterns of bits, digits, or characters that correspond to machine commands. Thus, the instruction set is specific to a class of processors using (mostly) the same architecture. Successor or derivative processor designs often include instructions of a predecessor and may add new additional instructions. Occasionally, a successor design will discontinue or alter the meaning of some instruction code (typically because it is needed for new purposes), affecting code compatibility to some extent; even compatible processors may show slightly different behavior for some instructions, but this is rarely a problem. Systems may also differ in other details, such as memory arrangement, operating systems, or peripheral devices. Because a program normally relies on such factors, different systems will typically not run the same machine code, even when the same type of processor is used.

A processor's instruction set may have fixed-length or variable-length instructions. How the patterns are organized varies with the particular architecture and type of instruction. Most instructions have one or more opcode fields that specify the basic instruction type (such as arithmetic, logical, jump, etc.), the operation (such as add or compare), and other fields that may give the type of the operand(s), the addressing mode(s), the addressing offset(s) or index, or the operand value itself (such constant operands contained in an instruction are called immediate).[2]

Not all machines or individual instructions have explicit operands. On a machine with a single accumulator, the accumulator is implicitly both the left operand and result of most arithmetic instructions. Some other architectures, such as the x86 architecture, have accumulator versions of common instructions, with the accumulator regarded as one of the general registers by longer instructions. A stack machine has most or all of its operands on an implicit stack. Special purpose instructions also often lack explicit operands; for example, CPUID in the x86 architecture writes values into four implicit destination registers. This distinction between explicit and implicit operands is important in code generators, especially in the register allocation and live range tracking parts. A good code optimizer can track implicit as well as explicit operands which may allow more frequent constant propagation, constant folding of registers (a register assigned the result of a constant expression freed up by replacing it by that constant) and other code enhancements. e24fc04721