8.Python3原始碼—Code物件與pyc檔案
8.1. Python程式的執行過程
Python直譯器在執行任何一個Python程式檔案時,首先進行的動作都是先對檔案中的Python原始碼進行編譯,編譯的主要結果是產生一組Python的byte code(位元組碼),然後將編譯的結果交給Python的虛擬機器(Virtual Machine),由虛擬機器按照順序一條一條地執行位元組碼,從而完成對Python程式的執行動作。
對於Python編譯器來說,PyCodeObject物件才是其真正的編譯結果,而pyc檔案只是這個物件在硬碟上的表現形式,它們實際上是Python對原始檔編譯的結果的兩種不同存在方式。
在程式執行期間,編譯結果存在於記憶體的PyCodeObject物件中;而Python結束執行後,編譯結果又被儲存到了pyc檔案中。當下一次執行相同的程式時,Python會根據pyc檔案中記錄的編譯結果直接建立記憶體中的PyCodeObject物件,而不用再次對原始檔進行編譯了。
對整體流程認識清晰後完全可以寫一個工具,將基於Python3.7生成的pyc檔案解析出來,pyc檔案的內容用json格式組織一下如下圖:
寫工具的目的只是為了更加理解整個流程。實際上使用Python的dis模組可以輸出更為詳細清晰的內容,如下圖:
8.2. PyCodeObject原始碼
// code.h
typedef struct {
PyObject_HEAD
int co_argcount;
int co_kwonlyargcount;
int co_nlocals;
int co_stacksize;
int co_flags;
int co_firstlineno;
PyObject *co_code;
PyObject *co_consts;
PyObject *co_names;
PyObject *co_varnames;
PyObject *co_freevars;
PyObject *co_cellvars;
Py_ssize_t *co_cell2arg;
PyObject *co_filename;
PyObject *co_name;
PyObject *co_lnotab;
void *co_zombieframe;
PyObject *co_weakreflist;
void *co_extra;
} PyCodeObject;
- Code Block:
Python編譯器在對Python原始碼進行編譯的時候,對於程式碼中的一個Code Block,會建立一個PyCodeObject物件與這段程式碼對應。當進入一個新的名字空間,或者說作用域時,就算是進入了一個新的Code Block了。比如下面的程式碼有三個code block:一個對應整個test.py檔案,一個對應class A,一個對應def Fun。
# test.py
class A:
pass
def Fun():
pass
a = A()
Fun()
- 名字空間:
名字空間是符號的上下文環境,符號的含義取決於名字空間。更具體地說,一個變數名對應的變數值是什麼,在Python中,這並不是確定的,而是需要通過名字空間來決定。一個Code Block,對應著一個名字空間,它會對應一個PyCodeObject物件。 - Python中的code物件:
在Python中,有與C語言下的PyCodeObject物件對應的物件——code物件,這個物件是對C語言下的PyCodeObject物件的一個簡單包裝,通過code物件,我們可以訪問PyCodeObject物件中的各個域。
8.3. 生成pyc檔案
# pyc_generator.py
import imp
import sys
def generate_pyc(name):
fp, pathname, description = imp.find_module(name)
try:
imp.load_module(name, fp, pathname, description)
finally:
if fp:
fp.close()
if __name__ == `__main__`:
generate_pyc(sys.argv[1])
命令列中輸入如下命令會生成pyc檔案:
>>> ./python3.7 pyc_generator.py test
8.3.1. 生成PyCodeObject物件和pyc檔案的C流程
從上面的pyc_generator檔案中的imp.load_module開始,函式呼叫順序如下:
// imp.py
load_module
=>load_source
// _bootstrap.py[1]
=>_load
=>_load_unlocked
// _bootstrap_external.py
=> exec_module
=> get_code
get_code方法中呼叫source_to_code方法生成PyCodeObject物件,呼叫_code_to_timestamp_pyc將PyCodeObject轉為二進位制資料,呼叫_cache_bytecode方法將二進位制資料寫入檔案。
值得注意的是真正的Python不會呼叫_bootstrap.py的_load方法(上面函式呼叫順序中的[1]),在Lib/importlib/__init__.py中:
# __init__.py
try:
import _frozen_importlib as _bootstrap
except ImportError:
from . import _bootstrap
_bootstrap._setup(sys, _imp)
else:
# do sth
try:
import _frozen_importlib_external as _bootstrap_external
except ImportError:
from . import _bootstrap_external
_bootstrap_external._setup(_bootstrap)
_bootstrap._bootstrap_external = _bootstrap_external
else:
# do sth
可以看到實際上呼叫的是_frozen_importlib中的_load方法,而不是_bootstrap中的_load方法,此lib的內容在Python/importlib.h中被定義:
不太明白為什麼要這麼處理,但是分析整體流程時將此處換成了_bootstrap,便於閱讀原始碼。
下面會詳細分析生成PyCodeObject物件,將PyCodeObject轉為二進位制資料和將二進位制資料寫入檔案的流程。
8.3.2. 生成PyCodeObject物件原始碼
// _bootstrap_external.py
source_to_code
// _bootstrap.py
=>_call_with_frames_removed
// bltinmodule.c
=> builtin_compile_impl
builtin_compile_impl的C原始碼如下:
// bltinmodule.c
static PyObject *
builtin_compile_impl(PyObject *module, PyObject *source, PyObject *filename, const char *mode, int flags, int dont_inherit, int optimize)
{
PyObject *source_copy;
const char *str;
int compile_mode = -1;
int is_ast;
PyCompilerFlags cf;
int start[] = {Py_file_input, Py_eval_input, Py_single_input};
PyObject *result;
cf.cf_flags = flags | PyCF_SOURCE_IS_UTF8;
if (flags &
~(PyCF_MASK | PyCF_MASK_OBSOLETE | PyCF_DONT_IMPLY_DEDENT | PyCF_ONLY_AST))
{
PyErr_SetString(PyExc_ValueError,
"compile(): unrecognised flags");
goto error;
}
/* XXX Warn if (supplied_flags & PyCF_MASK_OBSOLETE) != 0? */
if (optimize < -1 || optimize > 2) {
PyErr_SetString(PyExc_ValueError,
"compile(): invalid optimize value");
goto error;
}
if (!dont_inherit) {
PyEval_MergeCompilerFlags(&cf);
}
if (strcmp(mode, "exec") == 0)
compile_mode = 0;
else if (strcmp(mode, "eval") == 0)
compile_mode = 1;
else if (strcmp(mode, "single") == 0)
compile_mode = 2;
else {
PyErr_SetString(PyExc_ValueError,
"compile() mode must be `exec`, `eval` or `single`");
goto error;
}
is_ast = PyAST_Check(source);
if (is_ast == -1)
goto error;
if (is_ast) {
// do sth.
}
str = source_as_string(source, "compile", "string, bytes or AST", &cf, &source_copy);
if (str == NULL)
goto error;
result = Py_CompileStringObject(str, filename, start[compile_mode], &cf, optimize);
Py_XDECREF(source_copy);
goto finally;
error:
result = NULL;
finally:
Py_DECREF(filename);
return result;
}
其中:
- 呼叫source_as_string方法將上面的test.py原始碼載入進記憶體:
- 呼叫Py_CompileStringObject方法生成PyCodeObject物件:
// pythonrun.c
PyObject *
Py_CompileStringObject(const char *str, PyObject *filename, int start,
PyCompilerFlags *flags, int optimize)
{
PyCodeObject *co;
mod_ty mod;
PyArena *arena = PyArena_New();
if (arena == NULL)
return NULL;
mod = PyParser_ASTFromStringObject(str, filename, start, flags, arena);
if (mod == NULL) {
PyArena_Free(arena);
return NULL;
}
if (flags && (flags->cf_flags & PyCF_ONLY_AST)) {
PyObject *result = PyAST_mod2obj(mod);
PyArena_Free(arena);
return result;
}
co = PyAST_CompileObject(mod, filename, flags, optimize, arena);
PyArena_Free(arena);
return (PyObject *)co;
}
呼叫PyParser_ASTFromStringObject方法生成語法樹,呼叫PyAST_CompileObject方法生成PyCodeObject物件。此處不對語法解析和編譯做深入分析。
8.3.3. 將PyCodeObject物件轉為二進位制資料
_code_to_timestamp_pyc方法負責將PyCodeObject物件轉為二進位制資料,原始碼如下:
// _bootstrap_external.py
def _code_to_timestamp_pyc(code, mtime=0, source_size=0):
"Produce the data for a timestamp-based pyc."
data = bytearray(MAGIC_NUMBER)
data.extend(_w_long(0))
data.extend(_w_long(mtime))
data.extend(_w_long(source_size))
data.extend(marshal.dumps(code))
return data
可以看出一個pyc檔案包含幾部分內容:
- MAGIC_NUMBER:不同版本的Python實現都會定義不同的MAGIC_NUMBER,比如Python 3.7a0 3392,Python 3.6a0 3360,防止載入不相容的pyc檔案;
- 0:不清楚是用作什麼;
- mtime:py檔案建立或最近一次修改的時間資訊,如果修改時間沒有改變則不需要轉為二進位制儲存,即不需要修改pyc檔案;
- source_size:原始碼大小;
- marshal.dumps(code):PyCodeObject物件的二進位制流;
marshal.dumps呼叫marshal_dumps_impl方法:
// marshal.c
static PyObject *
marshal_dumps_impl(PyObject *module, PyObject *value, int version)
/*[clinic end generated code: output=9c200f98d7256cad input=a2139ea8608e9b27]*/
{
return PyMarshal_WriteObjectToString(value, version);
}
PyMarshal_WriteObjectToString原始碼為:
// marshal.c
PyObject *
PyMarshal_WriteObjectToString(PyObject *x, int version)
{
WFILE wf;
memset(&wf, 0, sizeof(wf));
wf.str = PyBytes_FromStringAndSize((char *)NULL, 50);
if (wf.str == NULL)
return NULL;
wf.ptr = wf.buf = PyBytes_AS_STRING((PyBytesObject *)wf.str);
wf.end = wf.ptr + PyBytes_Size(wf.str);
wf.error = WFERR_OK;
wf.version = version;
if (w_init_refs(&wf, version)) {
Py_DECREF(wf.str);
return NULL;
}
w_object(x, &wf);
w_clear_refs(&wf);
if (wf.str != NULL) {
char *base = PyBytes_AS_STRING((PyBytesObject *)wf.str);
if (wf.ptr - base > PY_SSIZE_T_MAX) {
Py_DECREF(wf.str);
PyErr_SetString(PyExc_OverflowError,
"too much marshal data for a bytes object");
return NULL;
}
if (_PyBytes_Resize(&wf.str, (Py_ssize_t)(wf.ptr - base)) < 0)
return NULL;
}
if (wf.error != WFERR_OK) {
Py_XDECREF(wf.str);
if (wf.error == WFERR_NOMEMORY)
PyErr_NoMemory();
else
PyErr_SetString(PyExc_ValueError,
(wf.error==WFERR_UNMARSHALLABLE)?"unmarshallable object"
:"object too deeply nested to marshal");
return NULL;
}
return wf.str;
此處最關鍵的方法為w_object,該方法會呼叫w_complex_object,真正將PyCodeObject物件轉為二進位制資料就在w_complex_object方法中:
// marshal.c
static void
w_complex_object(PyObject *v, char flag, WFILE *p)
{
// do sth.
else if (PyCode_Check(v)) {
PyCodeObject *co = (PyCodeObject *)v;
W_TYPE(TYPE_CODE, p);
w_long(co->co_argcount, p);
w_long(co->co_kwonlyargcount, p);
w_long(co->co_nlocals, p);
w_long(co->co_stacksize, p);
w_long(co->co_flags, p);
w_object(co->co_code, p);
w_object(co->co_consts, p);
w_object(co->co_names, p);
w_object(co->co_varnames, p);
w_object(co->co_freevars, p);
w_object(co->co_cellvars, p);
w_object(co->co_filename, p);
w_object(co->co_name, p);
w_long(co->co_firstlineno, p);
w_object(co->co_lnotab, p);
}
// do sth.
}
可以看出:
- PyCodeObject物件的型別是TYPE_CODE,8.2節中的test.py檔案會生成三個PyCodeObject物件,它們之間的關係為一個PyCodeObject物件巢狀兩個PyCodeObject物件;
- co_argcount、co_kwonlyargcount等欄位是通過呼叫w_long(呼叫w_byte方法寫入四個位元組),co_code、co_consts 等欄位是通過呼叫w_object(實際上是呼叫w_long、w_string等方法),最終轉為二進位制資料的。這些欄位的具體含義之後再進行深入分析;
- 需要注意的是有一個特殊的型別:TYPE_REF,可以通過該型別節約儲存空間。以co_filename為例,這個欄位的含義為py檔案的完整路徑,下面為test.py生成的pyc檔案中co_filename欄位的值:
// class A
"co_filename": {
"type": "unicode",
"size": 49,
"value": "/Users/l.wang/Documents/pythonindepth/bin/test.py"
}
// def Fun
"co_filename": {
"type": "ref",
"ref": 6
}
// test.py
"co_filename": {
"type": "ref",
"ref": 6
}
這是通過w_ref方法實現的,w_ref的原始碼如下。其中有一個hash表,該表的key為物件的地址,value為index,如果表中存在相同地址的物件,則寫入TYPE_REF型別和index,從而節省空間。
// marshal.c
static int
w_ref(PyObject *v, char *flag, WFILE *p)
{
_Py_hashtable_entry_t *entry;
int w;
if (p->version < 3 || p->hashtable == NULL) {
return 0; /* not writing object references */
}
/* if it has only one reference, it definitely isn`t shared */
if (Py_REFCNT(v) == 1) {
return 0;
}
entry = _Py_HASHTABLE_GET_ENTRY(p->hashtable, v);
if (entry != NULL) {
/* write the reference index to the stream */
_Py_HASHTABLE_ENTRY_READ_DATA(p->hashtable, entry, w);
/* we don`t store "long" indices in the dict */
assert(0 <= w && w <= 0x7fffffff);
w_byte(TYPE_REF, p);
w_long(w, p);
return 1;
} else {
size_t s = p->hashtable->entries;
/* we don`t support long indices */
if (s >= 0x7fffffff) {
PyErr_SetString(PyExc_ValueError, "too many objects");
goto err;
}
w = (int)s;
Py_INCREF(v);
if (_Py_HASHTABLE_SET(p->hashtable, v, w) < 0) {
Py_DECREF(v);
goto err;
}
*flag |= FLAG_REF;
return 0;
}
err:
p->error = WFERR_UNMARSHALLABLE;
return 1;
}
這個過程的逆序實現過程如下。如果flag不為0,則向list表中增加實際的值。如果型別為TYPE_REF,則根據讀取的index從list表中獲取真實的值。
static PyObject *
r_object(RFILE *p)
{
PyObject *v, *v2;
Py_ssize_t idx = 0;
long i, n;
int type, code = r_byte(p);
int flag, is_interned = 0;
PyObject *retval = NULL;
if (code == EOF) {
PyErr_SetString(PyExc_EOFError,
"EOF read where object expected");
return NULL;
}
p->depth++;
if (p->depth > MAX_MARSHAL_STACK_DEPTH) {
p->depth--;
PyErr_SetString(PyExc_ValueError, "recursion limit exceeded");
return NULL;
}
flag = code & FLAG_REF;
type = code & ~FLAG_REF;
#define R_REF(O) do{
if (flag)
O = r_ref(O, flag, p);
} while (0)
switch (type) {
// do sth.
case TYPE_REF:
n = r_long(p);
if (n < 0 || n >= PyList_GET_SIZE(p->refs)) {
if (n == -1 && PyErr_Occurred())
break;
PyErr_SetString(PyExc_ValueError, "bad marshal data (invalid reference)");
break;
}
v = PyList_GET_ITEM(p->refs, n);
if (v == Py_None) {
PyErr_SetString(PyExc_ValueError, "bad marshal data (invalid reference)");
break;
}
Py_INCREF(v);
retval = v;
break;
// do sth.
}
}
這裡存在一個問題,為什麼w_ref沒有像r_object中根據flag的值決定哪個欄位寫入hash表中,目前沒有想明白。
8.3.4. 將二進位制資料寫入檔案
_cache_bytecode方法負責將將二進位制資料寫入檔案,原始碼如下:
# _bootstrap_external.py
def _cache_bytecode(self, source_path, bytecode_path, data):
# Adapt between the two APIs
mode = _calc_mode(source_path)
return self.set_data(bytecode_path, data, _mode=mode)
set_data方法原始碼如下:
def set_data(self, path, data, *, _mode=0o666):
"""Write bytes data to a file."""
parent, filename = _path_split(path)
path_parts = []
# Figure out what directories are missing.
while parent and not _path_isdir(parent):
parent, part = _path_split(parent)
path_parts.append(part)
# Create needed directories.
for part in reversed(path_parts):
parent = _path_join(parent, part)
try:
_os.mkdir(parent)
except FileExistsError:
# Probably another Python process already created the dir.
continue
except OSError as exc:
# Could be a permission error, read-only filesystem: just forget
# about writing the data.
_bootstrap._verbose_message(`could not create {!r}: {!r}`,
parent, exc)
return
try:
_write_atomic(path, data, _mode)
_bootstrap._verbose_message(`created {!r}`, path)
except OSError as exc:
# Same as above: just don`t write the bytecode.
_bootstrap._verbose_message(`could not create {!r}: {!r}`, path,
exc)
寫入檔案的關鍵方法為_write_atomic,原始碼如下。該方法採用寫入臨時檔案,而後重新命名的方式,用於保證要麼有異常從而不會生成檔案,要麼無異常生成指定名稱的檔案。
def _write_atomic(path, data, mode=0o666):
"""Best-effort function to write data to a path atomically.
Be prepared to handle a FileExistsError if concurrent writing of the
temporary file is attempted."""
# id() is used to generate a pseudo-random filename.
path_tmp = `{}.{}`.format(path, id(path))
fd = _os.open(path_tmp,
_os.O_EXCL | _os.O_CREAT | _os.O_WRONLY, mode & 0o666)
try:
# We first write data to a temporary file, and then use os.replace() to
# perform an atomic rename.
with _io.FileIO(fd, `wb`) as file:
file.write(data)
_os.replace(path_tmp, path)
except OSError:
try:
_os.unlink(path_tmp)
except OSError:
pass
raise
8.4. 參考
- Python原始碼剖析
8.5. 附錄
分析清楚pyc檔案生成的流程後,就可以實現8.1節中提到的工具,工具原始碼如下:
# -*- coding:utf-8 -*-
import json
import datetime
import sys
FLAG_REF = ord(`x80`)
TYPE_CODE = ord(`c`)
TYPE_STRING = ord(`s`)
TYPE_SMALL_TUPLE = ord(`)`)
TYPE_INT = ord(`i`)
TYPE_SHORT_ASCII = ord(`z`)
TYPE_SHORT_ASCII_INTERNED = ord(`Z`)
TYPE_REF = ord(`r`)
TYPE_NONE = ord(`N`)
REFS_HASH = {}
def parse_code(fp):
code = int.from_bytes(fp.read(1), `little`)
code_type = code & ~FLAG_REF
code_flag = code & FLAG_REF
idx = len(REFS_HASH)
if code_flag:
REFS_HASH[idx] = None
code_dict = {}
if code_type == TYPE_CODE:
code_dict[`type`] = `code`
code_dict[`co_argcount`] = int.from_bytes(fp.read(4), `little`)
code_dict[`co_kwonlyargcount`] = int.from_bytes(fp.read(4), `little`)
code_dict[`co_nlocals`] = int.from_bytes(fp.read(4), `little`)
code_dict[`co_stacksize`] = int.from_bytes(fp.read(4), `little`)
code_dict[`co_flags`] = int.from_bytes(fp.read(4), `little`)
code_dict[`co_code`] = parse_code(fp)
code_dict[`co_consts`] = parse_code(fp)
code_dict[`co_names`] = parse_code(fp)
code_dict[`co_varnames`] = parse_code(fp)
code_dict[`co_freevars`] = parse_code(fp)
code_dict[`co_cellvars`] = parse_code(fp)
code_dict[`co_filename`] = parse_code(fp)
code_dict[`co_name`] = parse_code(fp)
code_dict[`co_firstlineno`] = int.from_bytes(fp.read(4), `little`)
code_dict[`co_lnotab`] = parse_code(fp)
elif code_type == TYPE_STRING:
code_dict[`type`] = `string`
length = int.from_bytes(fp.read(4), `little`)
code_dict[`length`] = length
# todo
value = fp.read(length)
code_dict[`value`] = str(value)
if code_flag:
REFS_HASH[idx] = code_dict[`value`]
elif code_type == TYPE_SMALL_TUPLE:
code_dict[`type`] = `tuple`
size = int.from_bytes(fp.read(1), `little`)
code_dict[`size`] = size
items = []
for _ in range(size):
items.append(parse_code(fp))
code_dict[`items`] = items
if code_flag:
REFS_HASH[idx] = code_dict[`items`]
elif code_type == TYPE_INT:
code_dict[`type`] = `long`
value = int.from_bytes(fp.read(4), `little`)
code_dict[`value`] = value
if code_flag:
REFS_HASH[idx] = code_dict[`value`]
elif code_type == TYPE_SHORT_ASCII:
code_dict[`type`] = `unicode`
size = int.from_bytes(fp.read(1), `little`)
code_dict[`size`] = size
code_dict[`value`] = fp.read(size).decode()
if code_flag:
REFS_HASH[idx] = code_dict[`value`]
elif code_type == TYPE_SHORT_ASCII_INTERNED:
code_dict[`type`] = `unicode`
size = int.from_bytes(fp.read(1), `little`)
code_dict[`size`] = size
code_dict[`value`] = fp.read(size).decode()
if code_flag:
REFS_HASH[idx] = code_dict[`value`]
elif code_type == TYPE_REF:
code_dict[`type`] = `ref`
code_dict[`ref`] = int.from_bytes(fp.read(4), `little`)
code_dict[`value`] = REFS_HASH[code_dict[`ref`]]
elif code_type == TYPE_NONE:
code_dict[`type`] = `none`
else:
print(code_type)
return code_dict
def parse_pyc(file_name):
pyc_dict = {}
with open(file_name, `rb`) as fp:
magic_number = int.from_bytes(fp.read(2), `little`)
if magic_number >= 3390 and magic_number <= 3392:
pyc_dict[`version`] = `Python 3.7`
else:
print(`only support Python 3.7`)
exit(0)
_ = fp.read(2)
_ = fp.read(4)
timestamp = int.from_bytes(fp.read(4), `little`)
pyc_dict[`modified`] = str(datetime.datetime.fromtimestamp(timestamp))
source_size = int.from_bytes(fp.read(4), `little`)
pyc_dict[`size`] = source_size
pyc_dict[`code`] = parse_code(fp)
return(pyc_dict)
if __name__ == `__main__`:
file_name = sys.argv[1]
print(json.dumps(parse_pyc(file_name), indent=2))
分析test.py後結果為:
實現了對TYPE_REF的處理,下面的value值並不在真實的二進位制中包含:
"co_filename": {
"type": "ref",
"ref": 6,
"value": "/Users/l.wang/Documents/pythonindepth/bin/test.py"
}
目前沒有對指令集做處理。
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