Python Reference#
The entire LLDB API is available as Python functions through a script bridging interface. This means the LLDB APIâs can be used directly from python either interactively or to build python apps that provide debugger features.
Additionally, Python can be used as a programmatic interface within the lldb command interpreter (we refer to this for brevity as the embedded interpreter). Of course, in this context it has full access to the LLDB API - with some additional conveniences we will call out in the FAQ.
Documentation#
The LLDB API is contained in a python module named lldb. A useful resource when writing Python extensions is the lldb Python classes reference guide.
The documentation is also accessible in an interactive debugger session with the following command:
(lldb) script help(lldb)
Help on package lldb:
NAME
lldb - The lldb module contains the public APIs for Python binding.
FILE
/System/Library/PrivateFrameworks/LLDB.framework/Versions/A/Resources/Python/lldb/__init__.py
DESCRIPTION
...
You can also get help using a module class name. The full API that is exposed for that class will be displayed in a man page style window. Below we want to get help on the lldb.SBFrame class:
(lldb) script help(lldb.SBFrame)
Help on class SBFrame in module lldb:
class SBFrame(__builtin__.object)
| Represents one of the stack frames associated with a thread.
| SBThread contains SBFrame(s). For example (from test/lldbutil.py),
|
| def print_stacktrace(thread, string_buffer = False):
| '''Prints a simple stack trace of this thread.'''
|
...
Or you can get help using any python object, here we use the lldb.process object which is a global variable in the lldb module which represents the currently selected process:
(lldb) script help(lldb.process)
Help on SBProcess in module lldb object:
class SBProcess(__builtin__.object)
| Represents the process associated with the target program.
|
| SBProcess supports thread iteration. For example (from test/lldbutil.py),
|
| # ==================================================
| # Utility functions related to Threads and Processes
| # ==================================================
|
...
Embedded Python Interpreter#
The embedded python interpreter can be accessed in a variety of ways from within LLDB. The easiest way is to use the lldb command script with no arguments at the lldb command prompt:
(lldb) script
Python Interactive Interpreter. To exit, type 'quit()', 'exit()' or Ctrl-D.
>>> 2+3
5
>>> hex(12345)
'0x3039'
>>>
This drops you into the embedded python interpreter. When running under the script command, lldb sets some convenience variables that give you quick access to the currently selected entities that characterize the program and debugger state. In each case, if there is no currently selected entity of the appropriate type, the variableâs IsValid method will return false. These variables are:
Variable |
Type |
Equivalent |
Description |
|
Contains the debugger object whose |
||
|
Contains the currently selected target - for instance the one made with the
|
||
|
Contains the process of the currently selected target.
The |
||
|
Contains the currently selected thread.
The |
||
|
Contains the currently selected stack frame.
The |
While extremely convenient, these variables have a couple caveats that you should be aware of. First of all, they hold the values of the selected objects on entry to the embedded interpreter. They do not update as you use the LLDB APIâs to change, for example, the currently selected stack frame or thread.
Moreover, they are only defined and meaningful while in the interactive Python
interpreter. There is no guarantee on their value in any other situation, hence
you should not use them when defining Python formatters, breakpoint scripts and
commands (or any other Python extension point that LLDB provides). For the
latter youâll be passed an SBDebugger
, SBTarget
, SBProcess
, SBThread
or
SBFrame
instance and you can use the functions from the âEquivalentâ column
to navigate between them.
As a rationale for such behavior, consider that lldb can run in a multithreaded environment, and another thread might call the âscriptâ command, changing the value out from under you.
To get started with these objects and LLDB scripting, please note that almost all of the lldb Python objects are able to briefly describe themselves when you pass them to the Python print function:
(lldb) script
Python Interactive Interpreter. To exit, type 'quit()', 'exit()' or Ctrl-D.
>>> print lldb.debugger
Debugger (instance: "debugger_1", id: 1)
>>> print lldb.target
a.out
>>> print lldb.process
SBProcess: pid = 59289, state = stopped, threads = 1, executable = a.out
>>> print lldb.thread
SBThread: tid = 0x1f03
>>> print lldb.frame
frame #0: 0x0000000100000bb6 a.out main + 54 at main.c:16
Running a python script when a breakpoint gets hit#
One very powerful use of the lldb Python API is to have a python script run when a breakpoint gets hit. Adding python scripts to breakpoints provides a way to create complex breakpoint conditions and also allows for smart logging and data gathering.
When your process hits a breakpoint to which you have attached some python code, the code is executed as the body of a function which takes three arguments:
def breakpoint_function_wrapper(frame, bp_loc, internal_dict):
# Your code goes here
or:
def breakpoint_function_wrapper(frame, bp_loc, extra_args, internal_dict):
# Your code goes here
Argument |
Type |
Description |
|
The current stack frame where the breakpoint got hit.
The object will always be valid.
This |
|
|
The breakpoint location that just got hit. Breakpoints are represented by |
|
|
|
|
|
|
The python session dictionary as a standard python dictionary object. |
Optionally, a Python breakpoint command can return a value. Returning False tells LLDB that you do not want to stop at the breakpoint. Any other return value (including None or leaving out the return statement altogether) is akin to telling LLDB to actually stop at the breakpoint. This can be useful in situations where a breakpoint only needs to stop the process when certain conditions are met, and you do not want to inspect the program state manually at every stop and then continue.
An example will show how simple it is to write some python code and attach it to a breakpoint. The following example will allow you to track the order in which the functions in a given shared library are first executed during one run of your program. This is a simple method to gather an order file which can be used to optimize function placement within a binary for execution locality.
We do this by setting a regular expression breakpoint that will match every function in the shared library. The regular expression â.â will match any string that has at least one character in it, so we will use that. This will result in one lldb.SBBreakpoint object that contains an lldb.SBBreakpointLocation object for each function. As the breakpoint gets hit, we use a counter to track the order in which the function at this particular breakpoint location got hit. Since our code is passed the location that was hit, we can get the name of the function from the location, disable the location so we wonât count this function again; then log some info and continue the process.
Note we also have to initialize our counter, which we do with the simple one-line version of the script command.
Here is the code:
(lldb) breakpoint set --func-regex=. --shlib=libfoo.dylib
Breakpoint created: 1: regex = '.', module = libfoo.dylib, locations = 223
(lldb) script counter = 0
(lldb) breakpoint command add --script-type python 1
Enter your Python command(s). Type 'DONE' to end.
> # Increment our counter. Since we are in a function, this must be a global python variable
> global counter
> counter += 1
> # Get the name of the function
> name = frame.GetFunctionName()
> # Print the order and the function name
> print '[%i] %s' % (counter, name)
> # Disable the current breakpoint location so it doesn't get hit again
> bp_loc.SetEnabled(False)
> # No need to stop here
> return False
> DONE
The breakpoint command add command above attaches a python script to breakpoint 1. To remove the breakpoint command:
(lldb) breakpoint command delete 1
Using the python apiâs to create custom breakpoints#
Another use of the Python APIâs in lldb is to create a custom breakpoint resolver. This facility was added in r342259.
It allows you to provide the algorithm which will be used in the breakpointâs search of the space of the code in a given Target to determine where to set the breakpoint locations - the actual places where the breakpoint will trigger. To understand how this works you need to know a little about how lldb handles breakpoints.
In lldb, a breakpoint is composed of three parts: the Searcher, the Resolver, and the Stop Options. The Searcher and Resolver cooperate to determine how breakpoint locations are set and differ between each breakpoint type. Stop options determine what happens when a location triggers and includes the commands, conditions, ignore counts, etc. Stop options are common between all breakpoint types, so for our purposes only the Searcher and Resolver are relevant.
The Searcherâs job is to traverse in a structured way the code in the current target. It proceeds from the Target, to search all the Modules in the Target, in each Module it can recurse into the Compile Units in that module, and within each Compile Unit it can recurse over the Functions it contains.
The Searcher can be provided with a SearchFilter that it will use to restrict this search. For instance, if the SearchFilter specifies a list of Modules, the Searcher will not recurse into Modules that arenât on the list. When you pass the -s modulename flag to break set you are creating a Module-based search filter. When you pass -f filename.c to break set -n you are creating a file based search filter. If neither of these is specified, the breakpoint will have a no-op search filter, so all parts of the program are searched and all locations accepted.
The Resolver has two functions. The most important one is the callback it provides. This will get called at the appropriate time in the course of the search. The callback is where the job of adding locations to the breakpoint gets done.
The other function is specifying to the Searcher at what depth in the above described recursion it wants to be called. Setting a search depth also provides a stop for the recursion. For instance, if you request a Module depth search, then the callback will be called for each Module as it gets added to the Target, but the searcher will not recurse into the Compile Units in the module.
One other slight subtlety is that the depth at which you get called back is not necessarily the depth at which the SearchFilter is specified. For instance, if you are doing symbol searches, it is convenient to use the Module depth for the search, since symbols are stored in the module. But the SearchFilter might specify some subset of CompileUnits, so not all the symbols you might find in each module will pass the search. You donât need to handle this situation yourself, since SBBreakpoint::AddLocation will only add locations that pass the Search Filter. This API returns an SBError to inform you whether your location was added.
When the breakpoint is originally created, its Searcher will process all the currently loaded modules. The Searcher will also visit any new modules as they are added to the target. This happens, for instance, when a new shared library gets added to the target in the course of running, or on rerunning if any of the currently loaded modules have been changed. Note, in the latter case, all the locations set in the old module will get deleted and you will be asked to recreate them in the new version of the module when your callback gets called with that module. For this reason, you shouldnât try to manage the locations you add to the breakpoint yourself. Note that the Breakpoint takes care of deduplicating equal addresses in AddLocation, so you shouldnât need to worry about that anyway.
At present, when adding a scripted Breakpoint type, you can only provide a custom Resolver, not a custom SearchFilter.
The custom Resolver is provided as a Python class with the following methods:
Name |
Arguments |
Description |
|
|
This is the constructor for the new Resolver.
|
|
|
This is the Resolver callback.
The For instance, if you asked for a search depth of lldb.eSearchDepthCompUnit, then the
target, module and compile_unit fields of the sym_ctx will be filled. The callback should look just in the
context passed in |
|
|
Specify the depth at which you wish your callback to get called. The currently supported options are:
For instance, if you are looking
up symbols, which are stored at the Module level, you will want to get called back module by module.
So you would want to return |
|
|
This is an optional method. If provided, the returned string will be printed at the beginning of the description for this breakpoint. |
To define a new breakpoint command defined by this class from the lldb command line, use the command:
(lldb) breakpoint set -P MyModule.MyResolverClass
You can also populate the extra_args SBStructuredData with a dictionary of key/value pairs with:
(lldb) breakpoint set -P MyModule.MyResolverClass -k key_1 -v value_1 -k key_2 -v value_2
Although you canât write a scripted SearchFilter, both the command line and the SB APIâs for adding a scripted resolver allow you to specify a SearchFilter restricted to certain modules or certain compile units. When using the command line to create the resolver, you can specify a Module specific SearchFilter by passing the -s ModuleName option - which can be specified multiple times. You can also specify a SearchFilter restricted to certain compile units by passing in the -f CompUnitName option. This can also be specified more than once. And you can mix the two to specify âthis comp unit in this moduleâ. So, for instance,
(lldb) breakpoint set -P MyModule.MyResolverClass -s a.out
will use your resolver, but will only recurse into or accept new locations in the module a.out.
Another option for creating scripted breakpoints is to use the SBTarget.CreateBreakpointFromScript API. This one has the advantage that you can pass in an arbitrary SBStructuredData object, so you can create more complex parametrizations. SBStructuredData has a handy SetFromJSON method which you can use for this purpose. Your __init__ function gets passed this SBStructuredData object. This API also allows you to directly provide the list of Modules and the list of CompileUnits that will make up the SearchFilter. If you pass in empty lists, the breakpoint will use the default âsearch everywhere,accept everythingâ filter.
Using the python APIâ to create custom stepping logic#
A slightly esoteric use of the Python APIâs is to construct custom stepping types. LLDBâs stepping is driven by a stack of âthread plansâ and a fairly simple state machine that runs the plans. You can create a Python class that works as a thread plan, and responds to the requests the state machine makes to run its operations.
There is a longer discussion of scripted thread plans and the state machine, and several interesting examples of their use in:
https://github.com/llvm/llvm-project/blob/main/lldb/examples/python/scripted_step.py
And for a MUCH fuller discussion of the whole state machine, see:
https://github.com/llvm/llvm-project/blob/main/lldb/include/lldb/Target/ThreadPlan.h
If you are reading those comments it is useful to know that scripted thread plans are set to be âControllingPlansâ, and not âOkayToDiscardâ.
To implement a scripted step, you define a python class that has the following methods:
Name |
Arguments |
Description |
|
|
This is the underlying |
|
|
Return True if this stop is part of your thread plans logic, false otherwise. |
|
|
If your plan is no longer relevant (for instance, you were stepping in a particular stack frame, but some other operation pushed that frame off the stack) return True and your plan will get popped. |
|
|
Return |
|
|
If your plan wants to stop and return control to the user at this point, return True. If your plan is done at this point, call SetPlanComplete on your thread plan instance. Also, do any work you need here to set up the next stage of stepping. |
To use this class to implement a step, use the command:
(lldb) thread step-scripted -C MyModule.MyStepPlanClass
Or use the SBThread.StepUsingScriptedThreadPlan API. The SBThreadPlan passed into your __init__ function can also push several common plans (step in/out/over and run-to-address) in front of itself on the stack, which can be used to compose more complex stepping operations. When you use subsidiary plans your explains_stop and should_stop methods wonât get called until the subsidiary plan is done, or the process stops for an event the subsidiary plan doesnât explain. For instance, step over plans donât explain a breakpoint hit while performing the step-over.
Create a new lldb command using a Python function#
Python functions can be used to create new LLDB command interpreter commands, which will work like all the natively defined lldb commands. This provides a very flexible and easy way to extend LLDB to meet your debugging requirements.
To write a python function that implements a new LLDB command define the function to take five arguments as follows:
def command_function(debugger, command, exe_ctx, result, internal_dict):
# Your code goes here
The meaning of the arguments is given in the table below.
If you provide a Python docstring in your command function LLDB will use it when providing âlong helpâ for your command, as in:
def command_function(debugger, command, result, internal_dict):
"""This command takes a lot of options and does many fancy things"""
# Your code goes here
though providing help can also be done programmatically (see below).
Prior to lldb 3.5.2 (April 2015), LLDB Python command definitions didnât take the SBExecutionContext argument. So you may still see commands where the command definition is:
def command_function(debugger, command, result, internal_dict):
# Your code goes here
Using this form is strongly discouraged because it can only operate on the âcurrently selectedâ target, process, thread, frame. The command will behave as expected when run directly on the command line. But if the command is used in a stop-hook, breakpoint callback, etc. where the response to the callback determines whether we will select this or that particular process/frame/thread, the global âcurrently selectedâ entity is not necessarily the one the callback is meant to handle. In that case, this command definition form canât do the right thing.
Argument |
Type |
Description |
|
The current debugger object. |
|
|
|
A python string containing all arguments for your command. If you need to chop up the arguments
try using the |
|
An execution context object carrying around information on the inferior processâ context in which the command is expected to act Optional since lldb 3.5.2, unavailable before |
|
|
A return object which encapsulates success/failure information for the command and output text that needs to be printed as a result of the command. The plain Python âprintâ command also works but text wonât go in the result by default (it is useful as a temporary logging facility). |
|
|
|
The dictionary for the current embedded script session which contains all variables and functions. |
Since lldb 3.7, Python commands can also be implemented by means of a class which should implement the following interface:
class CommandObjectType:
def __init__(self, debugger, internal_dict):
this call should initialize the command with respect to the command interpreter for the passed-in debugger
def __call__(self, debugger, command, exe_ctx, result):
this is the actual bulk of the command, akin to Python command functions
def get_short_help(self):
this call should return the short help text for this command[1]
def get_long_help(self):
this call should return the long help text for this command[1]
def get_flags(self):
this will be called when the command is added to the command interpreter,
and should return a flag field made from or-ing together the appropriate
elements of the lldb.CommandFlags enum to specify the requirements of this command.
The CommandInterpreter will make sure all these requirements are met, and will
return the standard lldb error if they are not.[1]
def get_repeat_command(self, command):
The auto-repeat command is what will get executed when the user types just
a return at the next prompt after this command is run. Even if your command
was run because it was specified as a repeat command, that invocation will still
get asked for IT'S repeat command, so you can chain a series of repeats, for instance
to implement a pager.
The command argument is the command that is about to be executed.
If this call returns None, then the ordinary repeat mechanism will be used
If this call returns an empty string, then auto-repeat is disabled
If this call returns any other string, that will be the repeat command [1]
[1] This method is optional.
As a convenience, you can treat the result object as a Python file object, and say
print >>result, "my command does lots of cool stuff"
SBCommandReturnObject and SBStream both support this file-like behavior by providing write() and flush() calls at the Python layer.
The commands that are added using this class definition are what lldb calls ârawâ commands. The command interpreter doesnât attempt to parse the command, doesnât handle option values, neither generating help for them, or their completion. Raw commands are useful when the arguments passed to the command are unstructured, and having to protect them against lldb command parsing would be onerous. For instance, âexprâ is a raw command.
You can also add scripted commands that implement the âparsed commandâ, where the options and their types are specified, as well as the argument and argument types. These commands look and act like the majority of lldb commands, and you can also add custom completions for the options and/or the arguments if you have special needs.
The easiest way to do this is to derive your new command from the lldb.ParsedCommand class. That responds in the same way to the help & repeat command interfaces, and provides some convenience methods, and most importantly an LLDBOptionValueParser, accessed throught lldb.ParsedCommand.get_parser(). The parser is used to set your command definitions, and to retrieve option values in the __call__ method.
To set up the command definition, implement the ParsedCommand abstract method:
def setup_command_definition(self):
This is called when your command is added to lldb. In this method you add the options and their types, the option help strings, etc. to the command using the API:
def add_option(self, short_option, long_option, help, default,
dest = None, required=False, groups = None,
value_type=lldb.eArgTypeNone, completion_type=None,
enum_values=None):
"""
short_option: one character, must be unique, not required
long_option: no spaces, must be unique, required
help: a usage string for this option, will print in the command help
default: the initial value for this option (if it has a value)
dest: the name of the property that gives you access to the value for
this value. Defaults to the long option if not provided.
required: if true, this option must be provided or the command will error out
groups: Which "option groups" does this option belong to. This can either be
a simple list (e.g. [1, 3, 4, 5]) or you can specify ranges by sublists:
so [1, [3,5]] is the same as [1, 3, 4, 5].
value_type: one of the lldb.eArgType enum values. Some of the common arg
types also have default completers, which will be applied automatically.
completion_type: currently these are values form the lldb.CompletionType enum. If
you need custom completions, implement handle_option_argument_completion.
enum_values: An array of duples: ["element_name", "element_help"]. If provided,
only one of the enum elements is allowed. The value will be the
element_name for the chosen enum element as a string.
"""
Similarly, you can add argument types to the command:
def make_argument_element(self, arg_type, repeat = "optional", groups = None):
"""
arg_type: The argument type, one of the lldb.eArgType enum values.
repeat: Choose from the following options:
"plain" - one value
"optional" - zero or more values
"plus" - one or more values
groups: As with add_option.
"""
Then implement the body of the command by defining:
def __call__(self, debugger, args_array, exe_ctx, result):
"""This is the command callback. The option values are
provided by the 'dest' properties on the parser.
args_array: This is the list of arguments provided.
exe_ctx: Gives the SBExecutionContext on which the
command should operate.
result: Any results of the command should be
written into this SBCommandReturnObject.
"""
This differs from the ârawâ commandâs __call__ in that the arguments are already parsed into the args_array, and the option values are set in the parser, and can be accessed using their property name. The LLDBOptionValueParser class has a couple of other handy methods:
returns True if the option was specified on the command line.
def dest_for_option(self, long_option_name):
"""
This will return the value of the dest variable you defined for opt_name.
Mostly useful for handle_completion where you get passed the long option.
"""
lldb will handle completing your option names, and all your enum values automatically. If your option or argument types have associated built-in completers, then lldb will also handle that completion for you. But if you have a need for custom completions, either in your arguments or option values, you can handle completion by hand as well. To handle completion of option value arguments, your lldb.ParsedCommand subclass should implement:
def handle_option_argument_completion(self, long_option, cursor_pos):
"""
long_option: The long option name of the option whose value you are
asked to complete.
cursor_pos: The cursor position in the value for that option - which
you can get from the option parser.
"""
And to handle the completion of arguments:
def handle_argument_completion(self, args, arg_pos, cursor_pos):
"""
args: A list of the arguments to the command
arg_pos: An index into the args list of the argument with the cursor
cursor_pos: The cursor position in the arg specified by arg_pos
"""
When either of these APIâs is called, the command line will have been parsed up to the word containing the cursor, and any option values set in that part of the command string are available from the option value parser. Thatâs useful for instance if you have a âshared-library option that would constrain the completions for, say, a symbol name option or argument.
The return value specifies what the completion options are. You have four choices:
True
: the completion was handled with no completions.False
: the completion was not handled, forward it to the regular
completion machinery.
A dictionary with the key: âcompletionâ: there is one candidate,
whose value is the value of the âcompletionâ key. Optionally you can pass a âmodeâ key whose value is either âpartialâ or âcompleteâ. Return partial if the âcompletionâ string is a prefix for all the completed value.
For instance, if the string you are completing is âTestâ and the available completions are: âTest1â, âTest11â and âTest111â, you should return the dictionary:
return {"completion": "Test1", "mode" : "partial"}
and then lldb will add the â1â at the curson and advance it after the added string, waiting for more completions. But if âTest1â is the only completion, return:
{"completion": "Test1", "mode": "complete"}
and lldb will add â1 â at the cursor, indicating the command string is complete.
The default is âcompleteâ, you donât need to specify a âmodeâ in that case.
A dictionary with the key: âvaluesâ whose value is a list of candidate completion
strings. The command interpreter will present those strings as the available choices. You can optionally include a âdescriptionsâ key, whose value is a parallel array of description strings, and the completion will show the description next to each completion.
One other handy convenience when defining lldb command-line commands is the command âcommand script importâ which will import a module specified by file path, so you donât have to change your PYTHONPATH for temporary scripts. It also has another convenience that if your new script module has a function of the form:
where debugger and internal_dict are as above, that function will get run when
the module is loaded allowing you to add whatever commands you want into the
current debugger. Note that this function will only be run when using the LLDB
command command script import
, it will not get run if anyone imports your
module from another module.
The standard test for __main__
, like many python modules do, is useful for
creating scripts that can be run from the command line. However, for command
line scripts, the debugger instance must be created manually. Sample code would
look like:
if __name__ == '__main__':
# Initialize the debugger before making any API calls.
lldb.SBDebugger.Initialize()
# Create a new debugger instance in your module if your module
# can be run from the command line. When we run a script from
# the command line, we won't have any debugger object in
# lldb.debugger, so we can just create it if it will be needed
debugger = lldb.SBDebugger.Create()
# Next, do whatever work this module should do when run as a command.
# ...
# Finally, dispose of the debugger you just made.
lldb.SBDebugger.Destroy(debugger)
# Terminate the debug session
lldb.SBDebugger.Terminate()
Now we can create a module called ls.py in the file ~/ls.py that will implement a function that can be used by LLDBâs python command code:
#!/usr/bin/env python
import lldb
import commands
import optparse
import shlex
def ls(debugger, command, result, internal_dict):
print >>result, (commands.getoutput('/bin/ls %s' % command))
# And the initialization code to add your commands
def __lldb_init_module(debugger, internal_dict):
debugger.HandleCommand('command script add -f ls.ls ls')
print 'The "ls" python command has been installed and is ready for use.'
Now we can load the module into LLDB and use it
$ lldb
(lldb) command script import ~/ls.py
The "ls" python command has been installed and is ready for use.
(lldb) ls -l /tmp/
total 365848
-rw-r--r--@ 1 someuser wheel 6148 Jan 19 17:27 .DS_Store
-rw------- 1 someuser wheel 7331 Jan 19 15:37 crash.log
You can also make âcontainerâ commands to organize the commands you are adding to lldb. Most of the lldb built-in commands structure themselves this way, and using a tree structure has the benefit of leaving the one-word command space free for user aliases. It can also make it easier to find commands if you are adding more than a few of them. Hereâs a trivial example of adding two âutilityâ commands into a âmy-utilitiesâ container:
#!/usr/bin/env python
import lldb
def first_utility(debugger, command, result, internal_dict):
print("I am the first utility")
def second_utility(debugger, command, result, internal_dict):
print("I am the second utility")
# And the initialization code to add your commands
def __lldb_init_module(debugger, internal_dict):
debugger.HandleCommand('command container add -h "A container for my utilities" my-utilities')
debugger.HandleCommand('command script add -f my_utilities.first_utility -h "My first utility" my-utilities first')
debugger.HandleCommand('command script add -f my_utilities.second_utility -h "My second utility" my-utilities second')
print('The "my-utilities" python command has been installed and its subcommands are ready for use.')
Then your new commands are available under the my-utilities node:
(lldb) help my-utilities
A container for my utilities
Syntax: my-utilities
The following subcommands are supported:
first -- My first utility Expects 'raw' input (see 'help raw-input'.)
second -- My second utility Expects 'raw' input (see 'help raw-input'.)
For more help on any particular subcommand, type 'help <command> <subcommand>'.
(lldb) my-utilities first
I am the first utility
A more interesting template has been created in the source repository that can help you to create lldb command quickly:
https://github.com/llvm/llvm-project/blob/main/lldb/examples/python/cmdtemplate.py
A commonly required facility is being able to create a command that does some token substitution, and then runs a different debugger command (usually, it poâes the result of an expression evaluated on its argument). For instance, given the following program:
#import <Foundation/Foundation.h>
NSString*
ModifyString(NSString* src)
{
return [src stringByAppendingString:@"foobar"];
}
int main()
{
NSString* aString = @"Hello world";
NSString* anotherString = @"Let's be friends";
return 1;
}
you may want a pofoo X command, that equates po [ModifyString(X) capitalizedString]. The following debugger interaction shows how to achieve that goal:
(lldb) script
Python Interactive Interpreter. To exit, type 'quit()', 'exit()' or Ctrl-D.
>>> def pofoo_funct(debugger, command, result, internal_dict):
... cmd = "po [ModifyString(" + command + ") capitalizedString]"
... debugger.HandleCommand(cmd)
...
>>> ^D
(lldb) command script add pofoo -f pofoo_funct
(lldb) pofoo aString
$1 = 0x000000010010aa00 Hello Worldfoobar
(lldb) pofoo anotherString
$2 = 0x000000010010aba0 Let's Be Friendsfoobar
Using the lldb.py module in Python#
LLDB has all of its core code build into a shared library which gets used by
the lldb
command line application. On macOS this shared library is a
framework: LLDB.framework and on other unix variants the program is a shared
library: lldb.so. LLDB also provides an lldb.py module that contains the
bindings from LLDB into Python. To use the LLDB.framework to create your own
stand-alone python programs, you will need to tell python where to look in
order to find this module. This is done by setting the PYTHONPATH environment
variable, adding a path to the directory that contains the lldb.py python
module. The lldb driver program has an option to report the path to the lldb
module. You can use that to point to correct lldb.py:
For csh and tcsh:
% setenv PYTHONPATH `lldb -P`
For sh and bash:
$ export PYTHONPATH=`lldb -P`
Alternately, you can append the LLDB Python directory to the sys.path list directly in your Python code before importing the lldb module.
Now your python scripts are ready to import the lldb module. Below is a python script that will launch a program from the current working directory called âa.outâ, set a breakpoint at âmainâ, and then run and hit the breakpoint, and print the process, thread and frame objects if the process stopped:
#!/usr/bin/env python
import lldb
import os
def disassemble_instructions(insts):
for i in insts:
print i
# Set the path to the executable to debug
exe = "./a.out"
# Create a new debugger instance
debugger = lldb.SBDebugger.Create()
# When we step or continue, don't return from the function until the process
# stops. Otherwise we would have to handle the process events ourselves which, while doable is
#a little tricky. We do this by setting the async mode to false.
debugger.SetAsync (False)
# Create a target from a file and arch
print "Creating a target for '%s'" % exe
target = debugger.CreateTargetWithFileAndArch (exe, lldb.LLDB_ARCH_DEFAULT)
if target:
# If the target is valid set a breakpoint at main
main_bp = target.BreakpointCreateByName ("main", target.GetExecutable().GetFilename());
print main_bp
# Launch the process. Since we specified synchronous mode, we won't return
# from this function until we hit the breakpoint at main
process = target.LaunchSimple (None, None, os.getcwd())
# Make sure the launch went ok
if process:
# Print some simple process info
state = process.GetState ()
print process
if state == lldb.eStateStopped:
# Get the first thread
thread = process.GetThreadAtIndex (0)
if thread:
# Print some simple thread info
print thread
# Get the first frame
frame = thread.GetFrameAtIndex (0)
if frame:
# Print some simple frame info
print frame
function = frame.GetFunction()
# See if we have debug info (a function)
if function:
# We do have a function, print some info for the function
print function
# Now get all instructions for this function and print them
insts = function.GetInstructions(target)
disassemble_instructions (insts)
else:
# See if we have a symbol in the symbol table for where we stopped
symbol = frame.GetSymbol();
if symbol:
# We do have a symbol, print some info for the symbol
print symbol
Writing lldb frame recognizers in Python#
Frame recognizers allow for retrieving information about special frames based on ABI, arguments or other special properties of that frame, even without source code or debug info. Currently, one use case is to extract function arguments that would otherwise be inaccessible, or augment existing arguments.
Adding a custom frame recognizer is done by implementing a Python class and using the âframe recognizer addâ command. The Python class should have a âget_recognized_argumentsâ method and it will receive an argument of type lldb.SBFrame representing the current frame that we are trying to recognize. The method should return a (possibly empty) list of lldb.SBValue objects that represent the recognized arguments.
An example of a recognizer that retrieves the file descriptor values from libc functions âreadâ, âwriteâ and âcloseâ follows:
class LibcFdRecognizer(object):
def get_recognized_arguments(self, frame):
if frame.name in ["read", "write", "close"]:
fd = frame.EvaluateExpression("$arg1").unsigned
target = frame.thread.process.target
value = target.CreateValueFromExpression("fd", "(int)%d" % fd)
return [value]
return []
The file containing this implementation can be imported via command script import
and then we can register this recognizer with frame recognizer add
.
Itâs important to restrict the recognizer to the libc library (which is
libsystem_kernel.dylib on macOS) to avoid matching functions with the same name
in other modules:
(lldb) command script import .../fd_recognizer.py
(lldb) frame recognizer add -l fd_recognizer.LibcFdRecognizer -n read -s libsystem_kernel.dylib
When the program is stopped at the beginning of the âreadâ function in libc, we can view the recognizer arguments in âframe variableâ:
(lldb) b read
(lldb) r
Process 1234 stopped
* thread #1, queue = 'com.apple.main-thread', stop reason = breakpoint 1.3
frame #0: 0x00007fff06013ca0 libsystem_kernel.dylib`read
(lldb) frame variable
(int) fd = 3
Writing Target Stop-Hooks in Python#
Stop hooks fire whenever the process stops just before control is returned to the user. Stop hooks can either be a set of lldb command-line commands, or can be implemented by a suitably defined Python class. The Python based stop-hooks can also be passed as set of -key -value pairs when they are added, and those will get packaged up into a SBStructuredData Dictionary and passed to the constructor of the Python object managing the stop hook. This allows for parametrization of the stop hooks.
To add a Python-based stop hook, first define a class with the following methods:
Name |
Arguments |
Description |
|
|
This is the constructor for the new stop-hook.
|
|
|
This is the called when the target stops.
The return value is a âShould Stopâ vote from this thread. If the method returns either True or no return this thread votes to stop. If it returns False, then the thread votes to continue after all the stop-hooks are evaluated. Note, the âauto-continue flag to âtarget stop-hook addâ overrides a True return value from the method. |
To use this class in lldb, run the command:
(lldb) command script import MyModule.py
(lldb) target stop-hook add -P MyModule.MyStopHook -k first -v 1 -k second -v 2
where MyModule.py is the file containing the class definition MyStopHook.