使用 DTrace 和 SystemTap 检测CPython¶
- 作者
David Malcolm
- 作者
Łukasz Langa
DTrace和SystemTap是监视工具,每个工具都提供了一种检查计算机系统上的进程正在执行的操作的方法。 它们都使用特定于域的语言,允许用户编写以下脚本:
进程监视的过滤器
从感兴趣的进程中收集数据
生成有关数据的报告
从Python 3.6开始,CPython可以使用嵌入式“标记”构建,也称为“探测器”,可以通过DTrace或SystemTap脚本观察,从而更容易监视系统上的CPython进程正在做什么。
CPython implementation detail: DTrace标记是CPython解释器的实现细节。 不保证CPython版本之间的探针兼容性。 更改CPython版本时,DTrace脚本可能会停止工作或无法正常工作而不会发出警告。
启用静态标记¶
macOS内置了对DTrace的支持。 在Linux上,为了使用SystemTap的嵌入式标记构建CPython,必须安装SystemTap开发工具。
在Linux机器上,这可以通过:
$ yum install systemtap-sdt-devel
或者:
$ sudo apt-get install systemtap-sdt-dev
然后必须将CPython配置为``--with-dtrace``:
checking for --with-dtrace... yes
在macOS上,您可以通过在后台运行Python进程列出可用的DTrace探测器,并列出Python程序提供的所有探测器:
$ python3.6 -q &
$ sudo dtrace -l -P python$! # or: dtrace -l -m python3.6
ID PROVIDER MODULE FUNCTION NAME
29564 python18035 python3.6 _PyEval_EvalFrameDefault function-entry
29565 python18035 python3.6 dtrace_function_entry function-entry
29566 python18035 python3.6 _PyEval_EvalFrameDefault function-return
29567 python18035 python3.6 dtrace_function_return function-return
29568 python18035 python3.6 collect gc-done
29569 python18035 python3.6 collect gc-start
29570 python18035 python3.6 _PyEval_EvalFrameDefault line
29571 python18035 python3.6 maybe_dtrace_line line
在Linux上,您可以通过查看是否包含“.note.stapsdt”部分来验证构建的二进制文件中是否存在SystemTap静态标记。
$ readelf -S ./python | grep .note.stapsdt
[30] .note.stapsdt NOTE 0000000000000000 00308d78
如果您已将Python构建为共享库(使用--enable-shared),则需要在共享库中查找。 例如:
$ readelf -S libpython3.3dm.so.1.0 | grep .note.stapsdt
[29] .note.stapsdt NOTE 0000000000000000 00365b68
足够现代的readelf命令可以打印元数据:
$ readelf -n ./python
Displaying notes found at file offset 0x00000254 with length 0x00000020:
Owner Data size Description
GNU 0x00000010 NT_GNU_ABI_TAG (ABI version tag)
OS: Linux, ABI: 2.6.32
Displaying notes found at file offset 0x00000274 with length 0x00000024:
Owner Data size Description
GNU 0x00000014 NT_GNU_BUILD_ID (unique build ID bitstring)
Build ID: df924a2b08a7e89f6e11251d4602022977af2670
Displaying notes found at file offset 0x002d6c30 with length 0x00000144:
Owner Data size Description
stapsdt 0x00000031 NT_STAPSDT (SystemTap probe descriptors)
Provider: python
Name: gc__start
Location: 0x00000000004371c3, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6bf6
Arguments: -4@%ebx
stapsdt 0x00000030 NT_STAPSDT (SystemTap probe descriptors)
Provider: python
Name: gc__done
Location: 0x00000000004374e1, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6bf8
Arguments: -8@%rax
stapsdt 0x00000045 NT_STAPSDT (SystemTap probe descriptors)
Provider: python
Name: function__entry
Location: 0x000000000053db6c, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6be8
Arguments: 8@%rbp 8@%r12 -4@%eax
stapsdt 0x00000046 NT_STAPSDT (SystemTap probe descriptors)
Provider: python
Name: function__return
Location: 0x000000000053dba8, Base: 0x0000000000630ce2, Semaphore: 0x00000000008d6bea
Arguments: 8@%rbp 8@%r12 -4@%eax
上述元数据包含SystemTap的信息,描述如何修补策略性放置的机器代码指令以启用SystemTap脚本使用的跟踪钩子。
静态DTrace探针¶
The following example DTrace script can be used to show the call/return hierarchy of a Python script, only tracing within the invocation of a function called "start". In other words, import-time function invocations are not going to be listed:
self int indent;
python$target:::function-entry
/copyinstr(arg1) == "start"/
{
self->trace = 1;
}
python$target:::function-entry
/self->trace/
{
printf("%d\t%*s:", timestamp, 15, probename);
printf("%*s", self->indent, "");
printf("%s:%s:%d\n", basename(copyinstr(arg0)), copyinstr(arg1), arg2);
self->indent++;
}
python$target:::function-return
/self->trace/
{
self->indent--;
printf("%d\t%*s:", timestamp, 15, probename);
printf("%*s", self->indent, "");
printf("%s:%s:%d\n", basename(copyinstr(arg0)), copyinstr(arg1), arg2);
}
python$target:::function-return
/copyinstr(arg1) == "start"/
{
self->trace = 0;
}
It can be invoked like this:
$ sudo dtrace -q -s call_stack.d -c "python3.6 script.py"
输出结果会像这样:
156641360502280 function-entry:call_stack.py:start:23
156641360518804 function-entry: call_stack.py:function_1:1
156641360532797 function-entry: call_stack.py:function_3:9
156641360546807 function-return: call_stack.py:function_3:10
156641360563367 function-return: call_stack.py:function_1:2
156641360578365 function-entry: call_stack.py:function_2:5
156641360591757 function-entry: call_stack.py:function_1:1
156641360605556 function-entry: call_stack.py:function_3:9
156641360617482 function-return: call_stack.py:function_3:10
156641360629814 function-return: call_stack.py:function_1:2
156641360642285 function-return: call_stack.py:function_2:6
156641360656770 function-entry: call_stack.py:function_3:9
156641360669707 function-return: call_stack.py:function_3:10
156641360687853 function-entry: call_stack.py:function_4:13
156641360700719 function-return: call_stack.py:function_4:14
156641360719640 function-entry: call_stack.py:function_5:18
156641360732567 function-return: call_stack.py:function_5:21
156641360747370 function-return:call_stack.py:start:28
Static SystemTap markers¶
The low-level way to use the SystemTap integration is to use the static markers directly. This requires you to explicitly state the binary file containing them.
For example, this SystemTap script can be used to show the call/return hierarchy of a Python script:
probe process("python").mark("function__entry") {
filename = user_string($arg1);
funcname = user_string($arg2);
lineno = $arg3;
printf("%s => %s in %s:%d\\n",
thread_indent(1), funcname, filename, lineno);
}
probe process("python").mark("function__return") {
filename = user_string($arg1);
funcname = user_string($arg2);
lineno = $arg3;
printf("%s <= %s in %s:%d\\n",
thread_indent(-1), funcname, filename, lineno);
}
It can be invoked like this:
$ stap \
show-call-hierarchy.stp \
-c "./python test.py"
输出结果会像这样:
11408 python(8274): => __contains__ in Lib/_abcoll.py:362
11414 python(8274): => __getitem__ in Lib/os.py:425
11418 python(8274): => encode in Lib/os.py:490
11424 python(8274): <= encode in Lib/os.py:493
11428 python(8274): <= __getitem__ in Lib/os.py:426
11433 python(8274): <= __contains__ in Lib/_abcoll.py:366
where the columns are:
time in microseconds since start of script
name of executable
PID of process
and the remainder indicates the call/return hierarchy as the script executes.
For a --enable-shared build of CPython, the markers are contained within the libpython shared library, and the probe's dotted path needs to reflect this. For example, this line from the above example:
probe process("python").mark("function__entry") {
should instead read:
probe process("python").library("libpython3.6dm.so.1.0").mark("function__entry") {
(assuming a debug build of CPython 3.6)
Available static markers¶
-
function__entry
(str filename, str funcname, int lineno)¶ This marker indicates that execution of a Python function has begun. It is only triggered for pure-Python (bytecode) functions.
The filename, function name, and line number are provided back to the tracing script as positional arguments, which must be accessed using
$arg1
,$arg2
,$arg3
:$arg1
:(const char *)
filename, accessible usinguser_string($arg1)
$arg2
:(const char *)
function name, accessible usinguser_string($arg2)
$arg3
:int
line number
-
function__return
(str filename, str funcname, int lineno)¶ This marker is the converse of
function__entry()
, and indicates that execution of a Python function has ended (either viareturn
, or via an exception). It is only triggered for pure-Python (bytecode) functions.The arguments are the same as for
function__entry()
-
line
(str filename, str funcname, int lineno)¶ This marker indicates a Python line is about to be executed. It is the equivalent of line-by-line tracing with a Python profiler. It is not triggered within C functions.
The arguments are the same as for
function__entry()
.
-
gc__start
(int generation)¶ Fires when the Python interpreter starts a garbage collection cycle.
arg0
is the generation to scan, likegc.collect()
.
-
gc__done
(long collected)¶ Fires when the Python interpreter finishes a garbage collection cycle.
arg0
is the number of collected objects.
-
import__find__load__start
(str modulename)¶ Fires before
importlib
attempts to find and load the module.arg0
is the module name.3.7 新版功能.
-
import__find__load__done
(str modulename, int found)¶ Fires after
importlib
's find_and_load function is called.arg0
is the module name,arg1
indicates if module was successfully loaded.3.7 新版功能.
-
audit
(str event, void *tuple)¶ Fires when
sys.audit()
orPySys_Audit()
is called.arg0
is the event name as C string,arg1
is aPyObject
pointer to a tuple object.3.8 新版功能.
SystemTap Tapsets¶
The higher-level way to use the SystemTap integration is to use a "tapset": SystemTap's equivalent of a library, which hides some of the lower-level details of the static markers.
Here is a tapset file, based on a non-shared build of CPython:
/*
Provide a higher-level wrapping around the function__entry and
function__return markers:
\*/
probe python.function.entry = process("python").mark("function__entry")
{
filename = user_string($arg1);
funcname = user_string($arg2);
lineno = $arg3;
frameptr = $arg4
}
probe python.function.return = process("python").mark("function__return")
{
filename = user_string($arg1);
funcname = user_string($arg2);
lineno = $arg3;
frameptr = $arg4
}
If this file is installed in SystemTap's tapset directory (e.g.
/usr/share/systemtap/tapset
), then these additional probepoints become
available:
-
python.function.entry
(str filename, str funcname, int lineno, frameptr)¶ This probe point indicates that execution of a Python function has begun. It is only triggered for pure-Python (bytecode) functions.
-
python.function.return
(str filename, str funcname, int lineno, frameptr)¶ This probe point is the converse of
python.function.return()
, and indicates that execution of a Python function has ended (either viareturn
, or via an exception). It is only triggered for pure-Python (bytecode) functions.
示例¶
This SystemTap script uses the tapset above to more cleanly implement the example given above of tracing the Python function-call hierarchy, without needing to directly name the static markers:
probe python.function.entry
{
printf("%s => %s in %s:%d\n",
thread_indent(1), funcname, filename, lineno);
}
probe python.function.return
{
printf("%s <= %s in %s:%d\n",
thread_indent(-1), funcname, filename, lineno);
}
The following script uses the tapset above to provide a top-like view of all running CPython code, showing the top 20 most frequently-entered bytecode frames, each second, across the whole system:
global fn_calls;
probe python.function.entry
{
fn_calls[pid(), filename, funcname, lineno] += 1;
}
probe timer.ms(1000) {
printf("\033[2J\033[1;1H") /* clear screen \*/
printf("%6s %80s %6s %30s %6s\n",
"PID", "FILENAME", "LINE", "FUNCTION", "CALLS")
foreach ([pid, filename, funcname, lineno] in fn_calls- limit 20) {
printf("%6d %80s %6d %30s %6d\n",
pid, filename, lineno, funcname,
fn_calls[pid, filename, funcname, lineno]);
}
delete fn_calls;
}