API reference

Functions

`start(builtins=False, profile_threads=True, profile_greenlets=True)`

Starts profiling all threads in the current interpreter instance. This function can be called from any thread at any time.

Resumes profiling if stop() is called previously.

builtins enables profiling of builtin functions.

profile_threads enables profiling of all threads. If this flag is true, all current threads and the ones that are generated in the future will be profiled.

profile_greenlets enables profiling of multiple greenlets. This argument is only respected when context backend is 'greenlet' and ignored otherwise.

`stop()`

Stop the profiler.

Same profiling session might be resumed later by calling start().

`clear_stats()`

Clears the profiler results.

All results stay in memory unless application (all threads including the main thread) exits or clear_stats() is explicitly called.

`get_func_stats(tag=None, ctx_id=None, filter_callback=None)`

Returns the function stats as a list of YFuncStat object. As Yappi is a C extension, it catches the profile data in C API. Thus, the profile data collected is buffered until clear_stats is called. get_func_stats function enumerates the underlying buffered data and aggregates the information there. The functions that contain same index id will be aggregated in a single YFuncStat object. So, if you want to select a specific tag or ctx_id, you need to select by providing them as arguments to get_func_stats. Otherwise, data with different tag/ctx_id will be combined into one YFuncStat object. If you really would like to enumerate buffered stats in raw, you can use an undocumented function: _yappi.enum_func_stats(enum_callback, filter_dict). You can see the usage in get_func_stats function.

Note:

Filtering tag and ctx_id are very fast compared to using filter_callback since the filtering is completely done on the C extension with an internal hash table.

tag retrieves the YFuncStat objects having the same tag as specified.

ctx_id retrieves the YFuncStat objects having the same ctx_id as specified.

filter_callback is a callback which takes a YFuncStat object as an argument and returns a boolean value to indicate to include or exclude it. As the object is directly passed to the filter_callback you can easily filter on any attribute that YFuncStat has.

Note:

The filter dict is deprecated. Please do not use it anymore. We still support that for backward compatability but it is not recommended anymore.

An example demonstrating how filter_callback can be used to filter on a function name having foo:

stats = yappi.get_func_stats(
    filter_callback=lambda x: x.name == 'foo'
).print_all()

There are handy functions that can be used with filter_callback to match multiple functions or modules easily. See func_matches and module_matches.

`get_thread_stats()`

Returns the thread stats as a YThreadStat object.

`get_greenlet_stats()`

Returns the greenlet stats as a YGreenletStats object.

`is_running()`

Returns a boolean indicating whether profiler is running or not.

`get_clock_type()`

Returns information about the underlying clock type Yappi should use to measure timing.

Read Clock Types for more information.

`set_clock_type(type)`

Sets the underlying clock type. type must be one of "wall" or "cpu".

Read Clock Types for more information.

`func_matches(stat, funcs)`

This function returns True if the stat(YStat) object is in a given list of funcs(callable) list. An example usage is when filtering stats based on actual function objects:

def a():
    pass

def b():
    pass

...
stats = yappi.get_func_stats(
    filter_callback=lambda x: yappi.func_matches(x, [a, b])
)

Note:

Once a profile session is saved or loaded from a file, you cannot use func_matches on the items as the mapping between the stats and the functions are not serialized.

`module_matches(stat, modules)`

This function returns True if the stat(YStat) object is in a given list of modules(ModuleType) list. An example usage is when filtering stats based on actual module objects:

import collections
...
stats = yappi.get_func_stats(
    filter_callback=lambda x: yappi.module_matches(x, [collections])
)

Note:

Once a profile session is saved or loaded from a file, you cannot use func_matches on the items as the mapping between the stats and the functions are not serialized.

`set_context_backend(type='native_thread')`

Sets the internal context backend used to track execution context. Type must be one of 'greenlet' or 'native_thread'. Default is native_thread and there is no need to call this function for initialization.

Setting the context backend will reset any callbacks configured via:

- `set_context_id_callback`
- `set_context_name_callback`

`set_ctx_id_callback(callback)`

callback is a simple callable with no arguments that returns an integer. callback is called for every profile event to get the current context id of a running context.

In Yappi terminology a context means a construct that has its own callstack. It defaults to uniquely identifying a threading.Thread object, but there might be some advanced cases for this one, like a different threading library is used.

This is an internally used function, so please do not play with unless you have a good reason.

Note:

The context id callback can be called from the threading.Thread initialization code and thus can hold some related locks in threading library(e.x: _active_limbo_lock). So, it is not safe to use threading APIs like threading.current_thread() which can also use these locks and lead to deadlocks. However, it is safe to use threading.local() or global variables using your own locks.

`set_tag_callback(callback)` New in v1.2

callback is a simple callable with no arguments that returns an integer. callback is called for every profile event to get the current tag id of a running function.

In Yappi, every profiled function is associated with a tag. By default, this tag is same for all stats collected. You can change this behavior and aggregate different function stat data in different tags. This will give additional name-spacing on what kind of data to collect.

A recent use case for this functionality is aggregating of single request/response cycle in an ASGI application via contextvar module. See here for details. It can also be used for profiling multithreaded WSGI applications, too.

A simple example demonstrating on how it can be used to profile request/response cycles in a multithreaded WSGI application where every request/response is handled by a different thread. See here for more details.

_req_counter = 0
tlocal = threading.local()

def _worker_tag_cbk():
    global _req_counter

    if not hasattr(tlocal, '_request_id'):
        _req_counter += 1 # protect this with mutex
        tlocal._request_id = _req_counter
    
    return tlocal._request_id


yappi.set_tag_callback(_worker_tag_cbk)
yappi.start()
...
# code that starts a server serving request with different threads
...
yappi.stop()

# get per-request/response cycle profiling info
for i in range(_req_counter):
    req_stats = yappi.get_func_stats(filter={'tag': i})
    req_stats.print_all()

Note:

Relevant request id is held in a thread local storage and we simply increment the counter when we encounter a new thread. Above code will aggregate all stats into a single tag for every function called from the same thread.

`yappi.get_mem_usage()`

Returns the internal memory usage of the profiler itself.

`convert2pstats(stats)`

Converts the internal stat type of Yappi (as returned by YFuncStat.get()) to a pstats object.

Classes

`YFuncStat`

This holds the stat items as a list of YFuncStat objects.

Attribute	Description
name	name of the executed function
module	module name of the executed function
lineno	line number of the executed function
ncall	number of times the executed function is called.
nactualcall	number of times the executed function is called, excluding the recursive calls.
builtin	bool, indicating whether the executed function is a builtin
ttot	total time spent in the executed function
tsub	total time spent in the executed function, excluding subcalls
tavg	per-call average total time spent in the executed function.
index	unique id for the YFuncStat object
children	list of YChildFuncStat objects
ctx_id	id of the underlying context(thread)
ctx_name	name of the underlying context(thread)
full_name	unique full name of the executed function
tag	tag of the executed function. (set via `set_tag_callback` )

`get()`

This method retrieves the current profiling stats.

yappi.get_func_stats() is actually just a wrapper for this function.

`add(path, type="ystat")`

This method loads the saved profile stats stored in file at path.

type indicates the type of the saved profile stats.

Currently, only loading from "ystat" format is possible. "ystat" is the current Yappi internal format.`

`save(path, type="ystat")`

This method saves the current profile stats to file at path.

type indicates the target type that the profile stats will be saved in.

Can be either "pstat" or "callgrind".

`print_all(out=sys.stdout)`

This method prints the current profile stats to out.

`sort(sort_type, sort_order="desc")`

This method sorts the current profile stats.

The sort_type must be one of the following:

ncall
ttot
tsub
tavg

sort_order must be either "desc" or "asc"

`clear()`

Clears the stats.

Note:

This method only clears the current object. You need to explicitly call yappi.clear_stats() to clear the current profile session stats.

`empty()`

Returns a boolean indicating whether we have any stats available or not.

`strip_dirs()`

Strip the directory information from the results. Affects the child function stats too.

`debug_print()`

This method debug prints the current profile stats to stdout.

Debug print prints out callee functions and more detailed info than the print_all() function call.

`YThreadStat`

YThreadStat object has following attributes:

Attribute	Description
name	class name of the current thread object which is derived from the `threading.Thread` class
id	a unique id given by Yappi (ctx_id)
tid	the real OS thread id
ttot	total time spent in the thread
sched_count	number of times this thread is scheduled.

`YGreenletStats`

YGreenletStats object has following attributes:

Attribute	Description
name	class name of the current greenlet
id	a unique id given by Yappi (ctx_id)
ttot	total time spent in the thread
sched_count	number of times this thread is scheduled.

`get()`

This method retrieves the current thread stats.

yappi.get_thread_stats() is actually just a wrapper for this function.

`print_all(out=sys.stdout)`

This method prints the current profile stats to the file out.

`sort(sort_type, sort_order="desc")`

This method sorts the current profile stats.

sort_type must be either "ttot" or "scnt"

sort_order must be either "desc" or "asc"

`clear()`

Clears the retrieved stats.

Note:

This method only clears the current object. You need to explicitly call yappi.clear_stats() to clear the current profile session stats.

`empty()`

Returns a bool indicating whether we have any stats available or not.

`YChildFuncStat`

This holds a list of child functions called from the main executed function as a YChildFuncStat object.

This class holds a list of YChildFuncStat objects.

For example, if a calls b, then a.children will hold b as a YChildFuncStat object.

YChildFuncStat object has following attributes:

Attribute	Description
name	name of the executed function
module	module name of the executed function
lineno	line number of the executed function
ncall	number of times the executed function is called.
nactualcall	number of times the executed function is called, excluding the recursive calls.
builtin	bool, indicating whether the executed function is a builtin
ttot	total time spent in the executed function
tsub	total time spent in the executed function, excluding subcalls
tavg	per-call average total time spent in the executed function.
index	unique id for the YFuncStat object
full_name	unique full name of the executed function

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