问题是,现在我必须使用Posix C getline
函数从文件中获取行,然后使用PyUnicode_DecodeUTF8
将其转换为Python Unicode对象,并使用我的caching policy算法对其进行缓存。与Python内置的for line in file
C实现相比,这个过程的性能要好得多。
如果我从代码中删除了PyUnicode_DecodeUTF8
调用,那么我使用Posix getline
的实现就会变得比使用Python内置的for line in file
C实现更快。因此,如果我可以让Python直接给我一个Python Unicode字符串对象,而不是必须首先调用Posix C getline
函数(然后才将其结果转换为Python Unicode对象),我的代码性能将几乎提高20%
(从最大的23%
),也就是说,它不会成为100%
等同于for line in file
的性能,因为我通过缓存东西做了一些工作,但是这个开销是最小的。
例如,我想在我的代码中使用_textiowrapper_readline()函数,如下所示:
#include <Python.h>
#include <textio.c.h> // C Python file defininig:
// _textiowrapper_readline(),
// CHECK_ATTACHED(),
// PyUnicode_READY(), etc
typedef struct
{
PyObject_HEAD
}
PyMymoduleExtendingPython;
static PyObject*
PyMymoduleExtendingPython_iternext(PyMymoduleExtendingPython* self, PyObject* args)
{
PyObject *line;
CHECK_ATTACHED(self);
line = _textiowrapper_readline(self, -1); // <- function from `textio.c`
if (line == NULL || PyUnicode_READY(line) == -1)
return NULL;
if (PyUnicode_GET_LENGTH(line) == 0) {
/* Reached EOF or would have blocked */
Py_DECREF(line);
Py_CLEAR(self->snapshot);
self->telling = self->seekable;
return NULL;
}
return line;
}
// create my module
PyMODINIT_FUNC PyInit_mymodule_extending_python_api(void)
{
PyObject* mymodule;
PyMymoduleExtendingPython.tp_iternext =
(iternextfunc) PyMymoduleExtendingPython_iternext;
Py_INCREF( &PyMymoduleExtendingPython );
PyModule_AddObject( mymodule, "FastFile", (PyObject*) &PyMymoduleExtendingPython );
return mymodule;
}
我如何包含来自C Python的textio实现,并在我自己的Python C扩展/API上重用它的代码?
正如我在上一个问题How to improve Python C Extensions file line reading?中所提到的,用来读取行的Python内置方法比我自己用C或C++标准方法从文件中获取行要快得多。
在this answer上,有人建议我通过读取8KB的数据块来重新实现Python算法,然后调用PyUnicode_DecodeUTF8
来解码它们,而不是在我读取的每一行都调用PyUnicode_DecodeUTF8
。
但是,我不需要重写所有已经编写/完成/准备读取行的C Python代码,我只需调用它的"getline“函数_textiowrapper_readline()
直接将行作为Python Unicode对象获取,然后缓存/使用,就像我已经对从Posix C getline
函数获得的行所做的那样(并传递给PyUnicode_DecodeUTF8()
将它们解码为Python Unicode对象)。
发布于 2019-05-27 05:26:30
我没有设法直接导入C API (扩展)函数,但我使用Python导入了io
模块,该模块具有作为io.open()
的全局内置函数open
的链接/引用。
bool hasfinished;
const char* filepath;
long long int linecount;
std::deque<PyObject*> linecache;
PyObject* iomodule;
PyObject* openfile;
PyObject* fileiterator;
FastFile(const char* filepath) : hasfinished(false), filepath(filepath), linecount(0) {
iomodule = PyImport_ImportModule( "io" );
if( iomodule == NULL ) {
std::cerr << "ERROR: FastFile failed to import the io module '"
<< filepath << "')!" << std::endl;
PyErr_Print();
return;
}
PyObject* openfunction = PyObject_GetAttrString( iomodule, "open" );
if( openfunction == NULL ) {
std::cerr << "ERROR: FastFile failed get the io module open function '"
<< filepath << "')!" << std::endl;
PyErr_Print();
return;
}
openfile = PyObject_CallFunction( openfunction, "s", filepath,
"s", "r", "i", -1, "s", "UTF8", "s", "replace" );
PyObject* iterfunction = PyObject_GetAttrString( openfile, "__iter__" );
Py_DECREF( openfunction );
if( iterfunction == NULL ) {
std::cerr << "ERROR: FastFile failed get the io module iterator function '"
<< filepath << "')!" << std::endl;
PyErr_Print();
return;
}
PyObject* openfileresult = PyObject_CallObject( iterfunction, NULL );
Py_DECREF( iterfunction );
if( openfileresult == NULL ) {
std::cerr << "ERROR: FastFile failed get the io module iterator object '"
<< filepath << "')!" << std::endl;
PyErr_Print();
return;
}
fileiterator = PyObject_GetAttrString( openfile, "__next__" );
Py_DECREF( openfileresult );
if( fileiterator == NULL ) {
std::cerr << "ERROR: FastFile failed get the io module iterator object '"
<< filepath << "')!" << std::endl;
PyErr_Print();
return;
}
}
~FastFile() {
this->close();
Py_XDECREF( iomodule );
Py_XDECREF( openfile );
Py_XDECREF( fileiterator );
for( PyObject* pyobject : linecache ) {
Py_DECREF( pyobject );
}
}
void close() {
PyObject* closefunction = PyObject_GetAttrString( openfile, "close" );
if( closefunction == NULL ) {
std::cerr << "ERROR: FastFile failed get the close file function for '"
<< filepath << "')!" << std::endl;
PyErr_Print();
return;
}
PyObject* closefileresult = PyObject_CallObject( closefunction, NULL );
Py_DECREF( closefunction );
if( closefileresult == NULL ) {
std::cerr << "ERROR: FastFile failed close open file '"
<< filepath << "')!" << std::endl;
PyErr_Print();
return;
}
Py_DECREF( closefileresult );
}
bool _getline() {
// Fix StopIteration being raised multiple times because
// _getlines is called multiple times
if( hasfinished ) { return false; }
PyObject* readline = PyObject_CallObject( fileiterator, NULL );
if( readline != NULL ) {
linecount += 1;
linecache.push_back( readline );
return true;
}
// PyErr_Print();
PyErr_Clear();
hasfinished = true;
return false;
}
在使用Visual Studio Compiler
进行编译时,使用this code时,它具有以下性能
print( 'fastfile_time %.2f%%, python_time %.2f%%' % (
fastfile_time/python_time, python_time/fastfile_time ), flush=True )
$ python3 fastfileperformance.py
Python timedifference 0:00:00.985254
FastFile timedifference 0:00:01.084283
fastfile_time 1.10%, python_time 0.91% = 0.09%
$ python3 fastfileperformance.py
Python timedifference 0:00:00.979861
FastFile timedifference 0:00:01.073879
fastfile_time 1.10%, python_time 0.91% = 0.09%
$ python3 fastfileperformance.py
Python timedifference 0:00:00.990369
FastFile timedifference 0:00:01.086416
fastfile_time 1.10%, python_time 0.91% = 0.09%
$ python3 fastfileperformance.py
Python timedifference 0:00:00.975223
FastFile timedifference 0:00:01.077857
fastfile_time 1.11%, python_time 0.90% = 0.10%
$ python3 fastfileperformance.py
Python timedifference 0:00:00.988327
FastFile timedifference 0:00:01.085866
fastfile_time 1.10%, python_time 0.91% = 0.09%
$ python3 fastfileperformance.py
Python timedifference 0:00:00.971848
FastFile timedifference 0:00:01.087894
fastfile_time 1.12%, python_time 0.89% = 0.11%
$ python3 fastfileperformance.py
Python timedifference 0:00:00.968116
FastFile timedifference 0:00:01.079976
fastfile_time 1.12%, python_time 0.90% = 0.10%
$ python3 fastfileperformance.py
Python timedifference 0:00:00.980856
FastFile timedifference 0:00:01.068325
fastfile_time 1.09%, python_time 0.92% = 0.08%
但是当用g++
编译它时,它的性能是这样的:
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.703964
FastFile timedifference 0:00:00.813478
fastfile_time 1.16%, python_time 0.87% = 0.13%
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.703432
FastFile timedifference 0:00:00.809531
fastfile_time 1.15%, python_time 0.87% = 0.13%
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.705319
FastFile timedifference 0:00:00.814130
fastfile_time 1.15%, python_time 0.87% = 0.13%
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.711852
FastFile timedifference 0:00:00.837132
fastfile_time 1.18%, python_time 0.85% = 0.15%
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.695033
FastFile timedifference 0:00:00.800901
fastfile_time 1.15%, python_time 0.87% = 0.13%
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.694661
FastFile timedifference 0:00:00.796754
fastfile_time 1.15%, python_time 0.87% = 0.13%
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.699377
FastFile timedifference 0:00:00.816715
fastfile_time 1.17%, python_time 0.86% = 0.14%
$ /bin/python3.6 fastfileperformance.py
Python timedifference 0:00:00.699229
FastFile timedifference 0:00:00.818774
fastfile_time 1.17%, python_time 0.85% = 0.15%
https://stackoverflow.com/questions/56286313
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