SnakeViz VS gprof2dot

From the same guy, use snakeviz to diagnose code. Video: [9:57] https://www.youtube.com/watch?v=m_a0fN48Alw

Python profiling is enabled primarily through cprofile, and can be visualized with help of tools like snakeviz (output flame graph can look like this). There are also memory profilers like memray which does in-depth traces, or sampling profilers like py-spy.

I'm looking for a Rust equivalent Python's cProfile https://docs.python.org/3/library/profile.html if possible with visualizations like in SnakeViz https://jiffyclub.github.io/snakeviz/

If you want stats for only your list of functions, you can do that with pstats, or you could use some third-party tool like https://jiffyclub.github.io/snakeviz/ or myriad other options.

I would make a list of tuples where each tuple is (2,0),(-2,0),(0,2),etc... and put those in a list. Then you can use random.choice to pick a random one out of the list. How often are you going to be doing this next to the edge of the grid? If its not that much then I would just try to have it re-draw a new random choice from the list in those cases. This isn't an elegant solution, since it could take an unknown amount of time to draw something valid, but it might be fast enough in practice. Then if that ends up causing issues on the edge cases you could have some logic to select a list to draw from that only contains the valid choices. Also remember, don't assume that some part of your code is the slow part. Always profile it to get some actual information on how long each section is taking so you can optimize the parts of the code that actually need it. I use snakeviz for profiling python code.

Official site: http://jiffyclub.github.io/snakeviz/

I've always used snakeviz with the stdlib profiler https://jiffyclub.github.io/snakeviz/

In prod, the pyinstrument profiler has worked well for me https://pyinstrument.readthedocs.io/en/latest/guide.html#pro...

its going to be very hard to give advice on this without seeing the code. could you share the relevant code? if you're not sure what the slow part is, i recommend https://jiffyclub.github.io/snakeviz/ it should allow you to see what function is taking long

It also lets you run tools like https://github.com/jrfonseca/gprof2dot on the profiling results to generate comprehensive flowcharts (call graph) for your program.

The closes thing I can think of is gprof2dot. It's used for visual representations after profiling code: https://github.com/jrfonseca/gprof2dot

There are a few tools to visualise the profile dumps. Some of them providing a full GUI for navigatig within your profiling results ( RunSnakeRun), some of them represent the analysis result as a Graph (gprof2dot). I stopped on snakeviz, which is a browser based visualizer. It is easy installed using pip install snakeviz, and then simply run with snakeviz profile_dir. The result looks something like this, and you can dive in to each of the visual parts to see its more close detalization, which is in my opinion is super cool and handy.