A swift app, will convert its dynamic frameworks into binaries. And once something is a binary, then it's no longer Swift/Ruby/Python, etc. It's machine code.
Same thing happens for a Python binary. So why aren't the machine codes compatible with each other out of the box?
Is it just that a simple mapping is required to bridge one language to the other?
Like if I needed to use a binary created from the Swift language — into a Python based app, then do I need to expose the Swift Headers to Python for it to work? Or something else is required?
I assume you're talking about making calls in one language to a library compiled in a different language.
At the assembly language level, there are standards (ABI, for Application Binary Interface) that define how function parameters are passed in registers, how values are returned, the behavior of the stack, etc. ABIs are architecture and operating-system-dependent. Usually any function that is exported in a library will follow the ABI.
It is plain that ABIs basically expect a C language model for functions: a single return value, a well-defined data type for each function parameter as well as the return value, the possibility of using pointers, etc.
Problems start to arise once you move to a higher level language. C++ already introduces complications: whereas the name of a C function is the same in assembly (often a _ character is prepended), in C++ function names must encode data types due to the possibility of overloaded functions with the same name but different parameters. Thus, names must be mangled and demangled -- this is why a prototype for a C function must be declared as extern "C" in C++. Then there are issues of the classes (this pointer, vtables), namespaces and so on, which complicate matters further.
Then you have dynamically typed languages like Python. In truth, there is no such thing as dynamic typing at the assembly language levels: the instruction encodings in machine language (i.e. binary codes as they're read by the CPU when executed) implicitly determine whether you're using an integer or floating-point or SIMD instruction (and the width of operands), which also determines which of the different register banks are accessed. Although the language makes dynamic typing transparent to you, at the assembly code level, the interpreter/JIT/compiler must resolve them somehow, because ultimately the CPU must be told exactly what data type to operate on.
This is why you can't directly call a C function (or in general any library function) from Python -- unlike a pure Python function which can disregard the types of its parameters, library functions must know the exact types of each parameter and the return type. Thus, you must use something like ctypes for Python, explicitly specifying the types in question for each function that needs to be called -- in a way, this is similar to function prototypes usually found in C headers. It is possible to write functions in C that are directly callable from Python (and, in that case, essentially from Python alone), but you'll have to jump through a few hoops.
As for the particular language pairing you're interested in (Python/Swift), a cursory search came up with this thread in the Swift forums (this one, linked from there, may also be interesting. Reading the thread, there appears to be two feasible solutions at this time: first, use the #_cdecl attribute (which isn't officially supported) to make a C function, and then call it from Python using ctypes. But the second and apparently more promising one is to use the #objc attribute in Swift, and use PyObjC in Python. I assume this will allow using some of the higher-level features of Swift, at least those that intersect with what Objective-C offers.
The premise: I'm writing a plug-in DLL which conforms to an industry standard interface / function signature. This will be used in at least two different software packages used internally at my company, both of which have some example skeleton code or empty shells of this particular interface. One vendor authors their example in C/C++, the other in Fortran.
Ideally I'd like to just have to write and maintain this library code in one language and not duplicate it (especially as I'm only just now getting some comfort level in various flavors of C, but haven't touched Fortran).
I've emailed off to both our vendors to see if there's anything specific their solvers need when they import this DLL, but this has made me curious at a more fundamental level. If I compile a DLL with an exposed method void foo(int bar) in both C and Fortran... by the time it's down to x86 machine instructions - does it make any difference in how that method is called by program "X"? I've gathered so far that if I were to do C++ I'd need the extern "C" bit to avoid "mangling" - there anything else I should be aware of?
It matters. The exported function must use a specific calling convention, there are several incompatible ones in common use in 32-bit code. The calling convention dictates where the function arguments are stored, in what order they are passed and how they are removed again. As well as how the function return value is passed back.
And the name of the function matters, exported function names are often decorated with extra characters. Which is what extern "C" is all about, it suppresses the name mangling that a C++ compiler uses to prevent overloaded functions from having the same exported name. So the name is one that the linker for a C compiler can recognize.
The way a C compiler makes function calls is pretty much the standard if you interop with code written in other languages. Any modern Fortran compiler will support declarations to make them compatible with a C program. And surely this is something that's already used by whatever software vendor you are working with that provides an add-on that was written in Fortran. And the other way around, as long as you provide functions that can be used by a C compiler then the Fortran programmer has a good chance at being able to call it.
Yes it has been discussed here many many times. Study answers and questions in this tag https://stackoverflow.com/questions/tagged/fortran-iso-c-binding .
The equivalent of extern "C" in fortran is bind(C). The equivalency of the datatypes is done using the intrinsic module iso_c_binding.
Also be sure to use the same calling conventions. If you do not specify anything manually, the default is usually the same for both. On Linux this is non-issue.
extern "C" is used in C++ code. So if you DLL is written in C++, you mustn't pass any C++ objects (classes).
If you stick with C types, you need to make sure the function passes parameters in a single way e.g. use C's default of _cdecl. Not sure what Fortran uses.
I am writing a static library by C++, expecting it to be used by either Fortran or C. Since Fortran has all its index starting from 1, I have to do some index modification inside my library when called by Fortran. Because I am passing an array of indices to the library and it is important for further computation.
Of course an intuitive way to solve this problem is to set a argument at interface to let user tell me what language they are using, but I don't think it is a cool way to do this.
So I wonder if there is anyway to detect in my library if it is called by Fortran or C?
Thanks!
If you are just passing arrays and their lengths, there shouldn't be any issue. The problem is only if you pass an index, then you need to know what that index is relative to. (Which in Fortran could be any value, if the array is explicitly declared to start with an index other than one). If you have this case, my suggestion is to write glue routines for one of the languages that will convert the index values, then call the regular library routines. The problem with this solution is that it obligates the user of the "special" language to call the special glue routines; calling the regular routines is a mistake.
Applications and libraries in any language will be built to target the same ABI. The ABI defines calling conventions and other details that make it possible for two functions built by different compilers (possibly for different languages) to call each other. There shouldn't be anything obviously different in the calls because great effort has gone into avoiding those differences.
You could look for out-of-band information like symbols provided by the FORTRAN compiler (or pulled in from its utility libraries). You would declare some symbol with the weak attribute and if it became valid you would know that there was some FORTRAN somewhere in the current executable image. However, you could not know if it was calling you directly or simply due to some other library pulled in.
The right solution appears to be using explicit wrappers to call C from FORTRAN: Calling a FORTRAN subroutine from C
It would be better if you set a start index. Fortran arrays do not necessarily have to start at 1. They can start at any number. The array may have been declared as
float, dimension(-20:20):: neg
float, dimension(4:99) pos
So passing an index of 5 for neg would mean the 26th element and passing an index of 5 for pos would mean the 2nd element.
I have an R package which uses lots of Fortran subroutines for nested loops of recursive linear algebra computations (depending heavily on BLAS and LAPACK routines). As an interface to Fortran, I use .Fortran function. I just read Jonathan Callahan's blog post about using .Call instead of .C in case of subroutines written in C/C++, and it got me thinking that would it be better to use .Call interface also when using Fortran subroutines, by writing a simple wrapper in C which then calls the Fortran subroutines?
As said, my Fortran codes are quite simple in a sense that I just play with multidimensional arrays of type double or integer. But I have learned that I must write quite a lot of checks in R side to ensure that everything doesn't crash because of I accidentally forgot to change the storage mode of some matrix to integer or the dimensions of some matrix were changed etc.
Subroutines are written as F90/95.
There might be an advantage if you are working with a large dataset. .Call can be much faster because you are not copying the data each time you call the function. For the case described in this question, there will be no such advantage, because the R 2.15.1 release notes state
.C() and .Fortran() do less copying: arguments which are raw, logical, integer, real or complex vectors and are unnamed are not copied before the call, and (named or not) are not copied after the call. Lists are no longer copied (they are supposed to be used read-only in the C code).
Switching to .Call means you give up the convenience of the .Fortran interface. You'd pass SEXPs into the C code, do any checks/manipulation of the data using the (scary and not well-documented) R API, and then call a Fortran function from C. Anyone else working with your code will have to understand the R API and C/Fortran interop.
The R package dotCall64 could be an interesting alternative. It provides .C64() which is an enhanced version of the Foreign Function Interface, i.e., .C() and .Fortran().
The interface .C64() can be used to interface both Fortran and C/C++ code. It
has a similar usage as .C() and .Fortran()
provides a mechanism to avoid unnecessary copies of read-only and write-only arguments
supports long vectors (vectors with more then 2^31-1 elements)
supports 64-bit integer type arguments
Hence, one can avoid unnecessary copies of read-only arguments while avoiding the .Call() interface in combination with a C wrapper function.
Some links:
The R package dotCall64: https://CRAN.R-project.org/package=dotCall64
Description of dotCall64 with examples: https://doi.org/10.1016/j.softx.2018.06.002
An illustration where dotCall64 is used to make the sparse matrix algebra R package spam compatible with huge sparse matrices (more than 2^31-1 non-zero elements): https://doi.org/10.1016/j.cageo.2016.11.015
I am one of the authors of dotCall64 and spam.
I know it is not supported, but I am wondering if there are any tricks around it. Any tips?
Reflection in general is a means for a program to analyze the structure of some code.
This analysis is used to change the effective behavior of the code.
Reflection as analysis is generally very weak; usually it can only provide access to function and field names. This weakness comes from the language implementers essentially not wanting to make the full source code available at runtime, along with the appropriate analysis routines to extract what one wants from the source code.
Another approach is tackle program analysis head on, by using a strong program analysis tool, e.g., one that can parse the source text exactly the way the compiler does it.
(Often people propose to abuse the compiler itself to do this, but that usually doesn't work; the compiler machinery wants to be a compiler and it is darn hard to bend it to other purposes).
What is needed is a tool that:
Parses language source text
Builds abstract syntax trees representing every detail of the program.
(It is helpful if the ASTs retain comments and other details of the source
code layout such as column numbers, literal radix values, etc.)
Builds symbol tables showing the scope and meaning of every identifier
Can extract control flows from functions
Can extact data flow from the code
Can construct a call graph for the system
Can determine what each pointer points-to
Enables the construction of custom analyzers using the above facts
Can transform the code according to such custom analyses
(usually by revising the ASTs that represent the parsed code)
Can regenerate source text (including layout and comments) from
the revised ASTs.
Using such machinery, one implements analysis at whatever level of detail is needed, and then transforms the code to achieve the effect that runtime reflection would accomplish.
There are several major benefits:
The detail level or amount of analysis is a matter of ambition (e.g., it isn't
limited by what runtime reflection can only do)
There isn't any runtime overhead to achieve the reflected change in behavior
The machinery involved can be general and applied across many languages, rather
than be limited to what a specific language implementation provides.
This is compatible with the C/C++ idea that you don't pay for what you don't use.
If you don't need reflection, you don't need this machinery. And your language
doesn't need to have the intellectual baggage of weak reflection built in.
See our DMS Software Reengineering Toolkit for a system that can do all of the above for C, Java, and COBOL, and most of it for C++.
[EDIT August 2017: Now handles C11 and C++2017]
Tips and tricks always exists. Take a look at Metaresc library https://github.com/alexanderchuranov/Metaresc
It provides interface for types declaration that will also generate meta-data for the type. Based on meta-data you can easily serialize/deserialize objects of any complexity. Out of the box you can serialize/deserialize XML, JSON, XDR, Lisp-like notation, C-init notation.
Here is a simple example:
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include "metaresc.h"
TYPEDEF_STRUCT (point_t,
double x,
double y
);
int main (int argc, char * argv[])
{
point_t point = {
.x = M_PI,
.y = M_E,
};
char * str = MR_SAVE_XML (point_t, &point);
if (str)
{
printf ("%s\n", str);
free (str);
}
return (EXIT_SUCCESS);
}
This program will output
$ ./point
<?xml version="1.0"?>
<point>
<x>3.1415926535897931</x>
<y>2.7182818284590451</y>
</point>
Library works fine for latest gcc and clang on Linux, MacOs, FreeBSD and Windows.
Custom macro language is one of the options. User could do declaration as usual and generate types descriptors from DWARF debug info. This moves complexity to the build process, but makes adoption much easier.
any tricks around it? Any tips?
The compiler will probably optionally generate 'debug symbol file', which a debugger can use to help debug the code. The linker may also generate a 'map file'.
A trick/tip might be to generate and then read these files.
Based on the responses to How can I add reflection to a C++ application? (Stack Overflow) and the fact that C++ is considered a "superset" of C, I would say you're out of luck.
There's also a nice long answer about why C++ doesn't have reflection (Stack Overflow).
I needed reflection in a bunch of structs in a C++ project.
I created a xml file with the description of all those structs - fortunately the fields types were primitive types.
I used a template (not C++ template) to auto generate a class for each struct along with setter/getter methods.
In each class I used a map to associate string names and class members (pointers to members).
I didn't regret using reflection because it opened new ways to design my core functionality that I couldn't even imagine without reflection.
(BTW, it was an external report generator for a program that uses a raw database)
So, I used code generation, function pointers and maps to simulate reflection.
I know of the following options, but all come at cost and a lot of limitations:
Use libdl (#include <dfcln.h>)
Call a tool like objdump or nm
Parse the object files yourself (using a corresponding library)
Involve a parser and generate the necessary information at compile time.
"Abuse" the linker to generate symbol arrays.
I'll use a bit of unit test frameworks as examples further down, because automatic test discovery for unit test frameworks is a typical example where reflection comes in very handy, and it's something that most unit test frameworks for C fall short of.
Using libdl (#include <dfcln.h>) (POSIX)
If you're on a POSIX environment, a little bit of reflection can be done using libdl. Plugins are developed that way.
Use
#include <dfcln.h>
in your source code and link with -ldl.
Then you have access to functions dlopen(), dlerror(), dlsym() and dlclose() with which you could load and access / run shared objects at runtime. However, it does not give you easy access to the symbol table.
Another disadvantage of this approach is that you basically restrict reflection to objects loaded as dynamic library (shared object loaded at runtime via dlopen()).
Running nm or objdump
You could run nm or objdump to show the symbol table and parse the output.
For me, nm -P --defined-only -g xyz.o gives good results, and parsing the output is trivial.
You'd be interested in the first word of each line only, which is the symbol name, and maybe the second one, which is the section type.
If you do not know the object name in some static way, i.e. the object is actually a shared object, at least on Linux you then might want to skip symbol names starting with '_'.
objdump, nm or similar tools are also often available outside POSIX environments.
Parsing the object files yourself
You could parse the object files yourself. You probably don't want to implement that from scratch but use an existing library for that. This is how nm, objdump and even libdl are implemented. You could peek at the source code of nm, objdump and libdl and the libraries they use in order to find out how they do what they do.
Involving a Parser
You could write a parser and code generator which generates the necessary reflective information at compile time and stores it in the object file. Then you have a lot of freedom and could even implement primitive forms of annotations. That's what some unit test frameworks like AceUnit do.
I found that writing a parser which covers straight-forward C syntax is fairly trivial. Writing a parser which really understands C and could deal with all cases is NOT trivial.
So, this has limitations which depend on how exotic the C syntax is that you want to reflect upon.
"Abusing" the linker to generate symbol arrays
You could put references to symbols which you want to reflect upon in a special section and use a linker configuration to emit the section boundaries so you can access them in C.
I've described here N-Dependency injection in C - better way than linker-defined arrays? how this works.
But beware, this is depending on a lot of things and not very portable. I have only tried this with GCC/ld, and I know it doesn't work with all compilers / linkers. Also, it's almost guaranteed that dead code elimination will not detect how you call this stuff, so if you use dead code elimination, you will have to add all the reflected symbols as entry points.
Pitfalls
For some of the mechanisms, dead code elimination can be a problem, in particular when you "abuse" the linker to generate a symbol arrays. It can be worked around by telling the reflected symbols as entry points to the linker, and depending on the amount of symbols this might be neither nice nor convenient.
Conclusion
Combining nm and libdl can actually give quite good results. The combination can be almost as powerful as the level of Reflection used by JUnit 3.x in Java. The level of reflection given is sufficient to implement a JUnit 3.x-style unit test framework for C, including test-case discovery by naming convention.
Involving a parser is more work and limited to objects that you compile yourself, but gives you most power and freedom. The level of reflection given can be sufficient to implement a JUnit 4.x-style unit test framework for C, including test-case discovery by annotations. AceUnit is a unit test framework for C that does exactly this.
Combining parsing and the linker to generate symbol arrays can give very nice results - if your environment is so much under your control that you can ensure that working with the linker that way works for you.
And of course you can combine all approaches to stitch together the bits and pieces until they fit your needs.
You would need to implement it from yourself from the ground up. In straight C, there is no runtime information whatsoever kept on structure and composite types. Metadata simply does not exist in the standard.
Implementing reflection for C would be much simpler... because C is simple language.
There is some basic options for analazing program, like detect if function exists by calling dlopen/dlsym -- depends on your needs.
There are tools for creating code that can modify/extend itselfusing tcc.
You may use the above tool in order to create your own code analizers.
For similar reasons to the author of the question, I have been working on a C-type-reflection-API along with a C reflection graph database format and a clang plug-in that writes reflection metadata.
The intent is to use the C reflection API for writing serialization and deserialization routines, such as mappers for ASN.1, function argument printers, function proxies, fuzzers, etc. Clang and GCC both have plugin APIs that allow access to the AST but there currently is no standard graph format for C reflection metadata.
The proposed C reflection API is called Crefl:
https://github.com/michaeljclark/crefl
The Crefl API provides runtime access to reflection metadata for C structure declarations with support for arbitrarily nested combinations of: intrinsic, set, enum, struct, union, field (member), array, constant, variable.
The Crefl reflection graph database format for portable reflection metadata.
The Crefl clang plug-in outputs C reflection metadata used by the library.
The Crefl API provides task-oriented query access to C reflection metadata
A C reflection API provides access to runtime reflection metadata for C structure declarations with support for arbitrarily nested combinations of: intrinsic, set, enum, struct, union, field, array, constant, variable. The Crefl C reflection data model is essentially a transcription of the C data types in ISO/IEC 9899:9999.
C intrinsic data types.
integer types.
floating-point types.
complex number types.
boolean type.
nested struct, union, field, and bitfield
arrays and pointers
typedef type aliases
enum and enum constants
functions and function parameters
const, volatile and restrict qualifiers
GNU-C style attributes using (__attribute__).
The library is still a work in progress. The hope is to find others who are interested in reflection support in C.
Parsers and Debug Symbols are great ideas. However, the gotcha is that C does not really have arrays. Just pointers to stuff.
For example, there is no way by reading the source code to know whether a char * points to a character, a string, or a fixed array of bytes based on some "nearby" length field. This is a problem for human readers let alone any automated tool.
Why not use a modern language, like Java or .Net? Can be faster than C as well.