pythonx/c_src/pythonx/pythonx.cpp at main · filmor/pythonx · GitHub

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#include <cstddef>

#include <erl_nif.h>

#include <fine.hpp>

#include <iostream>

#include <map>

#include <mutex>

#include <optional>

#include <stdexcept>

#include <string>

#include <thread>

#include <tuple>

#include "python.hpp"

extern "C" void pythonx_handle_io_write(const char *message,

const char *eval_info_bytes, bool type);

namespace pythonx {

using namespace python;

// State

std::mutex init_mutex;

bool is_initialized = false;

std::wstring python_home_path_w;

std::wstring python_executable_path_w;

std::map<std::string, std::tuple<PyObjectPtr, PyObjectPtr>> compilation_cache;

std::mutex compilation_cache_mutex;

PyInterpreterStatePtr interpreter_state;

std::map<std::thread::id, PyThreadStatePtr> thread_states;

std::mutex thread_states_mutex;

// Wrapper around the Python Global Interpreter Lock (GIL).

// To acquire the GIL, the caller simply needs to initialize a new

// guard object. Once the guard object's lifetime ends, the GIL is

// automatically released. This is the use of RAII [1] pattern,

// similarly to `std::lock_guard`.

// [1]: https://en.wikipedia.org/wiki/Resource_acquisition_is_initialization

class PyGILGuard {

// The simplest way to implement this guard is to use `PyGILState_Ensure`

// and `PyGILState_Release`, however this can lead to segfaults when

// using libraries depending on pybind11.

// pybind11 is a popular library for writing C extensions in Python

// packages. It provides convenient C++ API on top of the Python C

// API. In particular, it provides conveniences for dealing with

// GIL, one of them being `gil_scoped_acquire`. The implementation

// has a bug that results in a dangling pointer being used. This

// bug only appears when the code runs in a non-main thread that

// manages the `gil_scoped_acquire` checks if the calling thread

// already holds GIL with `PyGILState_Ensure` and `PyGILState_Release`.

// Specifically, the GIL, in which case it stores the pointer to

// the corresponding `PyThreadState`. After `PyGILState_Release`,

// the thread state is freed, but subsequent usage of `gil_scoped_acquire`

// still re-uses the pointer. This issues has been reported in [1].

// In our case, we evaluate Python code dirty scheduler threads.

// This means that the threads are reused and we acquire the GIL

// every time. In order to avoid the pybind11 bug, we want to avoid

// using `PyGILState_Release`, and instead have a permanent `PyThreadState`

// for each of the dirty scheduler threads. We do this by creating

// new state when the given scheduler thread obtains the GIL for

// the first time. Then, we use `PyEval_RestoreThread` and `PyEval_SaveThread`

// to acquire and release the GIL respectively.

// NOTE: the dirty scheduler thread pool is fixed, so the map does

// not grow beyond that. If we ever need to acquire the GIL from

// other threads, we should extend this implementation to either

// allow removing the state on destruction, or have a variant with

// `PyGILState_Ensure` and `PyGILState_Release`, as long as it does

// not fall into the bug described above.

// [1]: https://github.com/pybind/pybind11/issues/2888

public:

PyGILGuard() {

auto thread_id = std::this_thread::get_id();

PyThreadStatePtr state;

{

auto guard = std::lock_guard<std::mutex>(thread_states_mutex);

if (thread_states.find(thread_id) == thread_states.end()) {

// Note that PyThreadState_New does not require GIL to be held.

state = PyThreadState_New(interpreter_state);

thread_states[thread_id] = state;

} else {

state = thread_states[thread_id];

}

PyEval_RestoreThread(state);

}

~PyGILGuard() { PyEval_SaveThread(); }

};

// Ensures the given object refcount is decremented when the guard

// goes out of scope.

class PyDecRefGuard {

PyObjectPtr py_object;

public:

PyDecRefGuard() : py_object(nullptr) {}

PyDecRefGuard(PyObjectPtr py_object) : py_object(py_object) {}

~PyDecRefGuard() {

if (this->py_object != nullptr) {

Py_DecRef(this->py_object);

}

PyDecRefGuard &operator=(PyObjectPtr py_object) {

this->py_object = py_object;

return *this;

}

};

void ensure_initialized() {

auto init_guard = std::lock_guard<std::mutex>(init_mutex);

if (!is_initialized) {

throw std::runtime_error("Python interpreter has not been initialized");

}

namespace atoms {

auto ElixirPythonxError = fine::Atom("Elixir.Pythonx.Error");

auto ElixirPythonxJanitor = fine::Atom("Elixir.Pythonx.Janitor");

auto ElixirPythonxObject = fine::Atom("Elixir.Pythonx.Object");

auto decref = fine::Atom("decref");

auto integer = fine::Atom("integer");

auto list = fine::Atom("list");

auto map = fine::Atom("map");

auto map_set = fine::Atom("map_set");

auto output = fine::Atom("output");

auto ref = fine::Atom("ref");

auto traceback = fine::Atom("traceback");

auto tuple = fine::Atom("tuple");

auto type = fine::Atom("type");

auto value = fine::Atom("value");

} // namespace atoms

struct ExObjectResource {

PyObjectPtr py_object;

ExObjectResource(PyObjectPtr py_object) : py_object(py_object) {}

void destructor(ErlNifEnv *env) {

// Decrementing refcount requires GIL and we should not block in

// the destructor, so we send a message to a known process and let

// it decrement the refcount for us. Also see [1].

// [1]:https://erlangforums.com/t/how-to-deal-with-destructors-that-can-take-a-while-to-run-and-possibly-block-the-scheduler/4290

if (!is_initialized) {

// If we allow multiple initializations, we need to add a counter

// and check that py_object comes from the current initialization

return;

}

auto ptr = reinterpret_cast<uint64_t>(this->py_object);

auto janitor_name = fine::encode(env, atoms::ElixirPythonxJanitor);

ErlNifPid janitor_pid;

if (enif_whereis_pid(env, janitor_name, &janitor_pid)) {

auto msg_env = enif_alloc_env();

auto msg = fine::encode(msg_env, std::make_tuple(atoms::decref, ptr));

enif_send(env, &janitor_pid, msg_env, msg);

enif_free_env(msg_env);

} else {

std::cerr << "[pythonx] whereis(Pythonx.Janitor) failed. This is "

"unexpected and a Python object will not be deallocated"

<< std::endl;

}

};

FINE_RESOURCE(ExObjectResource);

struct ExObject {

fine::ResourcePtr<ExObjectResource> resource;

ExObject() {}

ExObject(fine::ResourcePtr<ExObjectResource> resource) : resource(resource) {}

static constexpr auto module = &atoms::ElixirPythonxObject;

static constexpr auto fields() {

return std::make_tuple(std::make_tuple(&ExObject::resource, &atoms::ref));

}

};

struct ExError {

ExObject type;

ExObject value;

ExObject traceback;

ExError() {}

ExError(ExObject type, ExObject value, ExObject traceback)

: type(type), value(value), traceback(traceback) {}

static constexpr auto module = &atoms::ElixirPythonxError;

static constexpr auto fields() {

return std::make_tuple(

std::make_tuple(&ExError::type, &atoms::type),

std::make_tuple(&ExError::value, &atoms::value),

std::make_tuple(&ExError::traceback, &atoms::traceback));

}

static constexpr auto is_exception = true;

};

struct EvalInfo {

ErlNifPid stdout_device;

ErlNifPid stderr_device;

ErlNifEnv *env;

std::thread::id thread_id;

};

void raise_py_error(ErlNifEnv *env) {

PyObjectPtr py_type, py_value, py_traceback;

PyErr_Fetch(&py_type, &py_value, &py_traceback);

// If the error indicator was set, type should not be NULL, but value

// and traceback might

if (py_type == NULL) {

throw std::runtime_error(

"raise_py_error should only be called when the error indicator is set");

}

auto type = ExObject(fine::make_resource<ExObjectResource>(py_type));

// Default value and traceback to None object

auto value = fine::make_resource<ExObjectResource>(

py_value == NULL ? Py_BuildValue("") : py_value);

auto traceback = fine::make_resource<ExObjectResource>(

py_traceback == NULL ? Py_BuildValue("") : py_traceback);

auto error = ExError(type, value, traceback);

fine::raise(env, error);

}

void raise_if_failed(ErlNifEnv *env, PyObjectPtr py_object) {

if (py_object == NULL) {

raise_py_error(env);

}

void raise_if_failed(ErlNifEnv *env, const char *buffer) {

if (buffer == NULL) {

raise_py_error(env);

}

void raise_if_failed(ErlNifEnv *env, Py_ssize_t size) {

if (size == -1) {

raise_py_error(env);

}

ERL_NIF_TERM py_object_to_binary_term(ErlNifEnv *env, PyObjectPtr py_object) {

Py_ssize_t size;

auto buffer = PyUnicode_AsUTF8AndSize(py_object, &size);

raise_if_failed(env, buffer);

ERL_NIF_TERM binary_term;

auto data = enif_make_new_binary(env, size, &binary_term);

memcpy(data, buffer, size);

return binary_term;

}

fine::Ok<> init(ErlNifEnv *env, std::string python_dl_path,

ErlNifBinary python_home_path,

ErlNifBinary python_executable_path,

std::vector<ErlNifBinary> sys_paths) {

auto init_guard = std::lock_guard<std::mutex>(init_mutex);

if (is_initialized) {

throw std::runtime_error("Python interpreter has already been initialized");

}

// Raises runtime error on failure, which is propagated automatically

load_python_library(python_dl_path);

// The path needs to be available for the whole interpreter lifetime,

// so we store it in a global variable.

python_home_path_w = std::wstring(

python_home_path.data, python_home_path.data + python_home_path.size);

python_executable_path_w =

std::wstring(python_executable_path.data,

python_executable_path.data + python_executable_path.size);

// As part of the initialization, sys.path gets set. It is important

// that it gets set correctly, so that the built-in modules can be

// found, otherwise the initialization fails. This logic is internal

// to Python, but we can configure base paths used to infer sys.path.

// The Limited API exposes Py_SetPythonHome and Py_SetProgramName and

// it appears that setting either of them alone should be sufficient.

// Py_SetProgramName has the advantage that, when set to the executable

// inside venv, it results in the packages directory being added to

// sys.path automatically, however, when tested, this did not work

// as expected in Python 3.10 on Windows. For this reason we prefer

// to use Py_SetPythonHome and add other paths to sys.path manually.

// Even then, we still want to set Py_SetProgramName to a Python

// executable, otherwise `sys.executable` is going to point to the

// BEAM executable (`argv[0]`), which can be problematic.

// In the end, the most reliable combination seems to be to set both,

// and also add the extra sys.path manually.

// Note that Python home is the directory with lib/ child directory

// containing the built-in Python modules [1].

// [1]: https://docs.python.org/3/using/cmdline.html#envvar-PYTHONHOME

Py_SetPythonHome(python_home_path_w.c_str());

Py_SetProgramName(python_executable_path_w.c_str());

Py_InitializeEx(0);

interpreter_state = PyInterpreterState_Get();

// In order to use any of the Python C API functions, the calling

// thread must hold the GIL. Since every NIF call may run on a

// different dirty scheduler thread, we need to acquire the GIL at

// the beginning of each NIF and release it afterwards.

// After initializing the Python interpreter above, the current

// thread automatically holds the GIL, so we explicitly release it.

// See pyo3 [1] for an extra reference.

// [1]: https://github.com/PyO3/pyo3/blob/v0.23.3/src/gil.rs#L63-L74

thread_states[std::this_thread::get_id()] = PyEval_SaveThread();

is_initialized = true;

// We still hold the init_mutex, so we can obtain the GIL guard

// before any other concurrent NIF. At this point we marked the

// interpreter as initialized and now we continue with further

// preparation using Python APIs. If any exception is subsequently

// raised, it will propagate as expected, and since the interpreter

// is initialized, the exception formatting will also work.

auto gil_guard = PyGILGuard();

// Add extra paths to sys.path

auto py_sys = PyImport_AddModule("sys");

raise_if_failed(env, py_sys);

auto py_sys_path = PyObject_GetAttrString(py_sys, "path");

raise_if_failed(env, py_sys_path);

auto py_sys_path_guard = PyDecRefGuard(py_sys_path);

for (const auto &path : sys_paths) {

auto py_path = PyUnicode_FromStringAndSize(

reinterpret_cast<const char *>(path.data), path.size);

raise_if_failed(env, py_path);

auto py_path_guard = PyDecRefGuard(py_path);

raise_if_failed(env, PyList_Append(py_sys_path, py_path));

}

// Define global stdout and stdin overrides

auto py_builtins = PyEval_GetBuiltins();

raise_if_failed(env, py_builtins);

auto py_exec = PyDict_GetItemString(py_builtins, "exec");

raise_if_failed(env, py_exec);

const char code[] = R"(

import ctypes

import io

import sys

import inspect

pythonx_handle_io_write = ctypes.CFUNCTYPE(

None, ctypes.c_char_p, ctypes.c_char_p, ctypes.c_bool

)(pythonx_handle_io_write_ptr)

class Stdout(io.TextIOBase):

def __init__(self, type):

self.type = type

def write(self, string):

# The evaluation caller has __pythonx_eval_info_bytes__ set in

# their globals. It is not available in globals() here, because

# the globals dict in function definitions is fixed at definition

# time. To find the current evaluation globals, we look at the

# call stack using the inspect module and find the caller with

# __pythonx_eval_info_bytes__ in globals. We look specifically

# for the outermost caller, because intermediate functions could

# be defined by previous evaluations, in which case they would

# have __pythonx_eval_info_bytes__ in their globals, corresponding

# to that previous evaluation. When called within a thread, the

# evaluation caller is not in the stack, so __pythonx_eval_info_bytes__

# will be found in the thread entrypoint function globals.

call_stack = inspect.stack()

eval_info_bytes = next(

frame_info.frame.f_globals["__pythonx_eval_info_bytes__"]

for frame_info in reversed(call_stack)

if "__pythonx_eval_info_bytes__" in frame_info.frame.f_globals

)

pythonx_handle_io_write(string.encode("utf-8"), eval_info_bytes, self.type)

return len(string)

class Stdin(io.IOBase):

def read(self, size=None):

raise RuntimeError("stdin not supported")

sys.stdout = Stdout(0)

sys.stderr = Stdout(1)

sys.stdin = Stdin()

)";

auto py_code = PyUnicode_FromStringAndSize(code, sizeof(code) - 1);

raise_if_failed(env, py_code);

auto py_code_guard = PyDecRefGuard(py_code);

auto py_globals = PyDict_New();

raise_if_failed(env, py_globals);

auto py_globals_guard = PyDecRefGuard(py_globals);

raise_if_failed(

env, PyDict_SetItemString(py_globals, "__builtins__", py_builtins));

auto py_pythonx_handle_io_write_ptr = PyLong_FromUnsignedLongLong(

reinterpret_cast<uintptr_t>(pythonx_handle_io_write));

raise_if_failed(env, py_pythonx_handle_io_write_ptr);

auto py_pythonx_handle_io_write_ptr_guard =

PyDecRefGuard(py_pythonx_handle_io_write_ptr);

raise_if_failed(env, PyDict_SetItemString(py_globals,

"pythonx_handle_io_write_ptr",

py_pythonx_handle_io_write_ptr));

auto py_exec_args = PyTuple_Pack(2, py_code, py_globals);

raise_if_failed(env, py_exec_args);

auto py_exec_args_guard = PyDecRefGuard(py_exec_args);

auto py_result = PyObject_Call(py_exec, py_exec_args, NULL);

raise_if_failed(env, py_result);

Py_DecRef(py_result);

return fine::Ok<>();

}

FINE_NIF(init, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Ok<> janitor_decref(ErlNifEnv *env, uint64_t ptr) {

auto init_guard = std::lock_guard<std::mutex>(init_mutex);

// If the interpreter is no longer initialized, ignore the call

if (is_initialized) {

auto gil_guard = PyGILGuard();

auto object = reinterpret_cast<PyObjectPtr>(ptr);

Py_DecRef(object);

}

return fine::Ok<>();

}

FINE_NIF(janitor_decref, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject none_new(ErlNifEnv *env) {

ensure_initialized();

auto gil_guard = PyGILGuard();

// Note that Limited API has Py_GetConstant, but only since v3.13

auto py_none = Py_BuildValue("");

raise_if_failed(env, py_none);

return ExObject(fine::make_resource<ExObjectResource>(py_none));

}

FINE_NIF(none_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject false_new(ErlNifEnv *env) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_bool = PyBool_FromLong(0);

raise_if_failed(env, py_bool);

return ExObject(fine::make_resource<ExObjectResource>(py_bool));

}

FINE_NIF(false_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject true_new(ErlNifEnv *env) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_bool = PyBool_FromLong(1);

raise_if_failed(env, py_bool);

return ExObject(fine::make_resource<ExObjectResource>(py_bool));

}

FINE_NIF(true_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject long_from_int64(ErlNifEnv *env, int64_t number) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_long = PyLong_FromLongLong(number);

raise_if_failed(env, py_long);

return ExObject(fine::make_resource<ExObjectResource>(py_long));

}

FINE_NIF(long_from_int64, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject long_from_string(ErlNifEnv *env, std::string string, int64_t base) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_long =

PyLong_FromString(string.c_str(), NULL, static_cast<int>(base));

raise_if_failed(env, py_long);

return ExObject(fine::make_resource<ExObjectResource>(py_long));

}

FINE_NIF(long_from_string, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject float_new(ErlNifEnv *env, double number) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_float = PyFloat_FromDouble(number);

raise_if_failed(env, py_float);

return ExObject(fine::make_resource<ExObjectResource>(py_float));

}

FINE_NIF(float_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject bytes_from_binary(ErlNifEnv *env, ErlNifBinary binary) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_object = PyBytes_FromStringAndSize(

reinterpret_cast<const char *>(binary.data), binary.size);

raise_if_failed(env, py_object);

return ExObject(fine::make_resource<ExObjectResource>(py_object));

}

FINE_NIF(bytes_from_binary, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject unicode_from_string(ErlNifEnv *env, ErlNifBinary binary) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_object = PyUnicode_FromStringAndSize(

reinterpret_cast<const char *>(binary.data), binary.size);

raise_if_failed(env, py_object);

return ExObject(fine::make_resource<ExObjectResource>(py_object));

}

FINE_NIF(unicode_from_string, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Term unicode_to_string(ErlNifEnv *env, ExObject ex_object) {

ensure_initialized();

auto gil_guard = PyGILGuard();

return py_object_to_binary_term(env, ex_object.resource->py_object);

}

FINE_NIF(unicode_to_string, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject dict_new(ErlNifEnv *env) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_dict = PyDict_New();

raise_if_failed(env, py_dict);

return ExObject(fine::make_resource<ExObjectResource>(py_dict));

}

FINE_NIF(dict_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Ok<> dict_set_item(ErlNifEnv *env, ExObject ex_object, ExObject ex_key,

ExObject ex_value) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto result =

PyDict_SetItem(ex_object.resource->py_object, ex_key.resource->py_object,

ex_value.resource->py_object);

raise_if_failed(env, result);

return fine::Ok<>();

}

FINE_NIF(dict_set_item, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject tuple_new(ErlNifEnv *env, uint64_t size) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_tuple = PyTuple_New(size);

raise_if_failed(env, py_tuple);

return ExObject(fine::make_resource<ExObjectResource>(py_tuple));

}

FINE_NIF(tuple_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Ok<> tuple_set_item(ErlNifEnv *env, ExObject ex_object, uint64_t index,

ExObject ex_value) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto result = PyTuple_SetItem(ex_object.resource->py_object, index,

ex_value.resource->py_object);

raise_if_failed(env, result);

// PyTuple_SetItem steals a reference, so we add one back

Py_IncRef(ex_value.resource->py_object);

return fine::Ok<>();

}

FINE_NIF(tuple_set_item, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject list_new(ErlNifEnv *env, uint64_t size) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_tuple = PyList_New(size);

raise_if_failed(env, py_tuple);

return ExObject(fine::make_resource<ExObjectResource>(py_tuple));

}

FINE_NIF(list_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Ok<> list_set_item(ErlNifEnv *env, ExObject ex_object, uint64_t index,

ExObject ex_value) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto result = PyList_SetItem(ex_object.resource->py_object, index,

ex_value.resource->py_object);

raise_if_failed(env, result);

// PyList_SetItem steals a reference, so we add one back

Py_IncRef(ex_value.resource->py_object);

return fine::Ok<>();

}

FINE_NIF(list_set_item, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject set_new(ErlNifEnv *env) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_set = PySet_New(NULL);

raise_if_failed(env, py_set);

return ExObject(fine::make_resource<ExObjectResource>(py_set));

}

FINE_NIF(set_new, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Ok<> set_add(ErlNifEnv *env, ExObject ex_object, ExObject ex_key) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto result =

PySet_Add(ex_object.resource->py_object, ex_key.resource->py_object);

raise_if_failed(env, result);

return fine::Ok<>();

}

FINE_NIF(set_add, ERL_NIF_DIRTY_JOB_CPU_BOUND);

ExObject object_repr(ErlNifEnv *env, ExObject ex_object) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_repr = PyObject_Repr(ex_object.resource->py_object);

raise_if_failed(env, py_repr);

return ExObject(fine::make_resource<ExObjectResource>(py_repr));

}

FINE_NIF(object_repr, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Term format_exception(ErlNifEnv *env, ExError error) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_traceback_module = PyImport_ImportModule("traceback");

raise_if_failed(env, py_traceback_module);

auto py_traceback_module_guard = PyDecRefGuard(py_traceback_module);

auto format_exception =

PyObject_GetAttrString(py_traceback_module, "format_exception");

raise_if_failed(env, format_exception);

auto format_exception_guard = PyDecRefGuard(format_exception);

auto py_type = error.type.resource->py_object;

auto py_value = error.value.resource->py_object;

auto py_traceback = error.traceback.resource->py_object;

auto format_exception_args = PyTuple_Pack(3, py_type, py_value, py_traceback);

raise_if_failed(env, format_exception_args);

auto format_exception_args_guard = PyDecRefGuard(format_exception_args);

auto py_lines = PyObject_Call(format_exception, format_exception_args, NULL);

raise_if_failed(env, py_lines);

auto py_lines_guard = PyDecRefGuard(py_lines);

auto size = PyList_Size(py_lines);

raise_if_failed(env, size);

auto terms = std::vector<ERL_NIF_TERM>();

terms.reserve(size);

for (Py_ssize_t i = 0; i < size; i++) {

auto py_line = PyList_GetItem(py_lines, i);

raise_if_failed(env, py_line);

terms.push_back(py_object_to_binary_term(env, py_line));

}

return enif_make_list_from_array(env, terms.data(),

static_cast<unsigned int>(size));

}

FINE_NIF(format_exception, ERL_NIF_DIRTY_JOB_CPU_BOUND);

fine::Term decode_once(ErlNifEnv *env, ExObject ex_object) {

ensure_initialized();

auto gil_guard = PyGILGuard();

auto py_object = ex_object.resource->py_object;

auto is_none = Py_IsNone(py_object);

raise_if_failed(env, is_none);

if (is_none) {

return fine::encode(env, std::nullopt);

}

auto is_true = Py_IsTrue(py_object);

raise_if_failed(env, is_true);

if (is_true) {

return fine::encode(env, true);

}

auto is_false = Py_IsFalse(py_object);

raise_if_failed(env, is_false);

if (is_false) {

return fine::encode(env, false);

}

auto py_builtins = PyEval_GetBuiltins();

raise_if_failed(env, py_builtins);

auto py_int_type = PyDict_GetItemString(py_builtins, "int");

raise_if_failed(env, py_int_type);

auto is_long = PyObject_IsInstance(py_object, py_int_type);

raise_if_failed(env, is_long);

if (is_long) {

int overflow;

auto integer = PyLong_AsLongLongAndOverflow(py_object, &overflow);

if (PyErr_Occurred() != NULL) {

raise_py_error(env);

}

if (overflow == 0) {

return enif_make_int64(env, integer);

}

// Integer over 64 bits

auto py_str = PyObject_Str(py_object);

raise_if_failed(env, py_str);

auto py_str_guard = PyDecRefGuard(py_str);

auto binary_term = py_object_to_binary_term(env, py_str);

return fine::encode(

env, std::make_tuple(atoms::integer, fine::Term(binary_term)));

}

auto py_float_type = PyDict_GetItemString(py_builtins, "float");

raise_if_failed(env, py_float_type);

auto is_float = PyObject_IsInstance(py_object, py_float_type);

raise_if_failed(env, is_float);

if (is_float) {

double number = PyFloat_AsDouble(py_object);

if (PyErr_Occurred() != NULL) {

raise_py_error(env);

}

return enif_make_double(env, number);

}

auto py_tuple_type = PyDict_GetItemString(py_builtins, "tuple");

raise_if_failed(env, py_tuple_type);

auto is_tuple = PyObject_IsInstance(py_object, py_tuple_type);

raise_if_failed(env, is_tuple);

if (is_tuple) {

auto size = PyTuple_Size(py_object);

raise_if_failed(env, size);

auto terms = std::vector<ERL_NIF_TERM>();

terms.reserve(size);

for (Py_ssize_t i = 0; i < size; i++) {

auto py_item = PyTuple_GetItem(py_object, i);

raise_if_failed(env, py_item);

Py_IncRef(py_item);

auto ex_item = ExObject(fine::make_resource<ExObjectResource>(py_item));

terms.push_back(fine::encode(env, ex_item));

}

auto items = enif_make_list_from_array(env, terms.data(),

static_cast<unsigned int>(size));

return fine::encode(env, std::make_tuple(atoms::tuple, fine::Term(items)));

}

auto py_list_type = PyDict_GetItemString(py_builtins, "list");

raise_if_failed(env, py_list_type);

auto is_list = PyObject_IsInstance(py_object, py_list_type);

raise_if_failed(env, is_list);

if (is_list) {

auto size = PyList_Size(py_object);

raise_if_failed(env, size);

auto terms = std::vector<ERL_NIF_TERM>();

terms.reserve(size);

for (Py_ssize_t i = 0; i < size; i++) {

auto py_item = PyList_GetItem(py_object, i);

raise_if_failed(env, py_item);

Py_IncRef(py_item);

auto ex_item = ExObject(fine::make_resource<ExObjectResource>(py_item));

terms.push_back(fine::encode(env, ex_item));

}

auto items = enif_make_list_from_array(env, terms.data(),

static_cast<unsigned int>(size));

return fine::encode(env, std::make_tuple(atoms::list, fine::Term(items)));

}

auto py_dict_type = PyDict_GetItemString(py_builtins, "dict");

raise_if_failed(env, py_dict_type);

auto is_dict = PyObject_IsInstance(py_object, py_dict_type);

raise_if_failed(env, is_dict);

if (is_dict) {

auto size = PyDict_Size(py_object);

raise_if_failed(env, size);

auto terms = std::vector<ERL_NIF_TERM>();

terms.reserve(size);

PyObjectPtr py_key, py_value;

Py_ssize_t pos = 0;

while (PyDict_Next(py_object, &pos, &py_key, &py_value)) {

Py_IncRef(py_key);

auto ex_key = ExObject(fine::make_resource<ExObjectResource>(py_key));

Py_IncRef(py_value);

auto ex_value = ExObject(fine::make_resource<ExObjectResource>(py_value));

terms.push_back(fine::encode(env, std::make_tuple(ex_key, ex_value)));

}

auto items = enif_make_list_from_array(env, terms.data(),

static_cast<unsigned int>(size));

return fine::encode(env, std::make_tuple(atoms::map, fine::Term(items)));

}

auto py_str_type = PyDict_GetItemString(py_builtins, "str");

raise_if_failed(env, py_str_type);

auto is_unicode = PyObject_IsInstance(py_object, py_str_type);

raise_if_failed(env, is_unicode);

if (is_unicode) {

return py_object_to_binary_term(env, py_object);

}

auto py_bytes_type = PyDict_GetItemString(py_builtins, "bytes");

raise_if_failed(env, py_bytes_type);

auto is_bytes = PyObject_IsInstance(py_object, py_bytes_type);

raise_if_failed(env, is_bytes);

if (is_bytes) {

Py_ssize_t size;

char *buffer;

auto result = PyBytes_AsStringAndSize(py_object, &buffer, &size);

raise_if_failed(env, result);

ERL_NIF_TERM binary_term;

auto data = enif_make_new_binary(env, size, &binary_term);

memcpy(data, buffer, size);

return binary_term;

}

auto py_set_type = PyDict_GetItemString(py_builtins, "set");

raise_if_failed(env, py_set_type);

auto is_set = PyObject_IsInstance(py_object, py_set_type);

raise_if_failed(env, is_set);

auto py_frozenset_type = PyDict_GetItemString(py_builtins, "frozenset");

raise_if_failed(env, py_frozenset_type);

auto is_frozenset = PyObject_IsInstance(py_object, py_frozenset_type);

raise_if_failed(env, is_frozenset);

if (is_set || is_frozenset) {

auto size = PySet_Size(py_object);

raise_if_failed(env, size);

auto terms = std::vector<ERL_NIF_TERM>();

terms.reserve(size);

auto py_iter = PyObject_GetIter(py_object);

raise_if_failed(env, py_iter);

auto py_iter_guard = PyDecRefGuard(py_iter);

PyObjectPtr py_item = NULL;

while ((py_item = PyIter_Next(py_iter)) != NULL) {

// Note that PyIter_Next already returns a new reference

auto ex_item = ExObject(fine::make_resource<ExObjectResource>(py_item));

terms.push_back(fine::encode(env, ex_item));

}

if (PyErr_Occurred() != NULL) {

raise_py_error(env);

}

auto items = enif_make_list_from_array(env, terms.data(),

static_cast<unsigned int>(size));

return fine::encode(env,

std::make_tuple(atoms::map_set, fine::Term(items)));

}

// None of the built-ins, return %Pythonx.Object{} as is

return fine::encode(env, ex_object);

}

FINE_NIF(decode_once, ERL_NIF_DIRTY_JOB_CPU_BOUND);

std::tuple<PyObjectPtr, PyObjectPtr> compile(ErlNifEnv *env,

ErlNifBinary code) {

// Python code can be compiled in either "exec" mode (multiple

// statements with no result value) or "eval" mode (single expression

// with a result value). We want our eval API to accept arbitrary

// Python code with multiple statements, while also returning the

// final result. To achieve this we parse the code using Python

// standard library and check if the last statement is an expression.

// If that is the case, we split the code, "exec" the statements

// and "eval" the final expression separately.

// For the reference, below is a Python code corresponding to the

// described logic. Technically we could "exec" that Python code,

// but in order to avoid extra overhead we call the Python functions

// directly via the C API.

// import ast

// module = ast.parse(code, "<string>", mode="exec")

// body_code = None

// last_expr_code = None

// if module.body:

// last_statement = module.body[-1]

// if isinstance(last_statement, ast.Expr):

// expr = ast.Expression(module.body.pop().value)

// # Copy positional information to the expression root node

// expr.lineno = last_statement.lineno

// expr.col_offset = last_statement.col_offset

View remainder of file in raw view

pythonx/c_src/pythonx/pythonx.cpp at main · filmor/pythonx · GitHub

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