VizTracer
VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution.
The front-end UI is powered by Perfetto. Use "AWSD" to zoom/navigate. More help can be found in "Support - Controls".
Highlights
- Detailed function entry/exit information on timeline with source code
- Super easy to use, no source code change for most features, no package dependency
- Supports threading, multiprocessing, subprocess and async
- Logs arbitrary function/variable using RegEx without code change
- Powerful front-end, able to render GB-level trace smoothly
- Works on Linux/MacOS/Windows
Install
The prefered way to install VizTracer is via pip
pip install viztracer
Basic Usage
Command Line
Assume you have a python script to run:
python3 my_script.py arg1 arg2
You can simply use VizTracer by
viztracer my_script.py arg1 arg2
A result.json
file will be generated, which you can open with vizviewer
vizviewer will host an HTTP server on http://localhost:9001
. You can also open your browser and use that address.
If you do not want vizviewer to open the webbrowser automatically, you can use
vizviewer --server_only result.json
If you just need to bring up the trace report once, and do not want the persistent server, use
vizviewer --once result.json
vizviewer result.json
You can also generate standalone html
file
viztracer -o result.html my_script.py arg1 arg2
The standalone HTML file is powered by catapult trace viewer which is an old tool Google made and is being replaced by Perfetto gradually.
Catapult trace viewer is sluggish with larger traces and is not actively maintained. It is recommended to use Perfetto instead.
However, if you really need a standalone HTML file, this is the only option. Perfetto does not support standalone files.
You can use vizviewer to open the html file as well, just to make the interface consistent
vizviewer result.html
Or add --open
to open the reports right after tracing
viztracer --open my_scripy.py arg1 arg2
viztracer -o result.html --open my_script.py arg1 arg2
modules and console scripts(like flask
) are supported as well
viztracer -m your_module
viztracer flask run
Inline
You can also manually start/stop VizTracer in your script as well.
from viztracer import VizTracer
tracer = VizTracer()
tracer.start()
# Something happens here
tracer.stop()
tracer.save() # also takes output_file as an optional argument
Or, you can do it with with
statement
with VizTracer(output_file="optional.json") as tracer:
# Something happens here
Jupyter
If you are using Jupyter, you can use viztracer cell magics.
# You need to load the extension first
%load_ext viztracer
%%viztracer
# Your code after
A VizTracer Report
button will appear after the cell and you can click it to view the results
Advanced Usage
Trace Filter
VizTracer can filter out the data you don't want to reduce overhead and keep info of a longer time period before you dump the log.
Extra Logs without Code Change
VizTracer can log extra information without changing your source code
- Any Variable/Attribute with RegEx
- Function Entry
- Variables in Specified Function
- Garbage Collector Operation
- Function Input Arguments
- Function Return Value
- Raised Exceptions
Add Custom Event
VizTracer supports inserting custom events while the program is running. This works like a print debug, but you can know when this print happens while looking at trace data.
Misc
Multi Thread Support
VizTracer supports python native threading
module without the need to do any modification to your code. Just start VizTracer
before you create threads and it will just work.
Multi Process Support
VizTracer supports subprocess
, multiprocessing
and os.fork()
out of the box.
For more general multi-process cases, VizTracer can support with some extra steps.
Refer to multi process docs for details
Async Support
VizTracer supports asyncio
natively, but could enhance the report by using --log_async
.
Refer to async docs for details
Flamegraph
VizTracer can show flamegraph of traced data.
vizviewer --flamegraph result.json
Remote attach
VizTracer supports remote attach to a process as long as you installed VizTracer on that process.
Refer to remote attach docs
JSON alternative
VizTracer needs to dump the internal data to json format. It is recommended for the users to install orjson
, which is much faster than the builtin json
library. VizTracer will try to import orjson
and fall back to the builtin json
library if orjson
does not exist.
Virtual Debug
You can virtually debug your program with you saved json report. The interface is very similar to pdb
. Even better, you can go back in time because VizTracer has all the info recorded for you.
vdb
Refer to the docs for detailed commands
Performance
VizTracer will introduce 2x to 3x overhead in the worst case. The overhead is much better if there are less function calls or if filters are applied correctly.
An example run for test_performance with Python 3.8 / Ubuntu 18.04.4 on Github VM
fib:
0.000678067(1.00)[origin]
0.019880272(29.32)[py] 0.011103901(16.38)[parse] 0.021165599(31.21)[json]
0.001344933(1.98)[c] 0.008181911(12.07)[parse] 0.015789866(23.29)[json]
0.001472846(2.17)[cProfile]
hanoi (6148, 4100):
0.000550255(1.00)[origin]
0.016343521(29.70)[py] 0.007299123(13.26)[parse] 0.016779364(30.49)[json]
0.001062505(1.93)[c] 0.006416136(11.66)[parse] 0.011463236(20.83)[json]
0.001144914(2.08)[cProfile]
qsort (8289, 5377):
0.002817679(1.00)[origin]
0.052747431(18.72)[py] 0.011339725(4.02)[parse] 0.023644345(8.39)[json]
0.004767673(1.69)[c] 0.008735166(3.10)[parse] 0.017173703(6.09)[json]
0.007248019(2.57)[cProfile]
slow_fib (1135, 758):
0.028759652(1.00)[origin]
0.033994071(1.18)[py] 0.001630461(0.06)[parse] 0.003386635(0.12)[json]
0.029481623(1.03)[c] 0.001152415(0.04)[parse] 0.002191417(0.08)[json]
0.028289305(0.98)[cProfile]
Documentation
For full documentation, please see https://viztracer.readthedocs.io/en/stable
Bugs/Requests
Please send bug reports and feature requests through github issue tracker. VizTracer is currently under development now and it's open to any constructive suggestions.
License
Copyright Tian Gao, 2020.
Distributed under the terms of the Apache 2.0 license.