gprof2dot VS tuna

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.

Every minor detail matters and adds to the total import time as part of the cold start. We need to optimize our code and imports. If you use Python, you can analyze your code with a tool like Tuna and optimize your libraries (perhaps replace slower ones) and your imports.

I started to examine the output of python -X importtime -m gefyra 2> import.log just to check the imports. There is an awesome tool to analyze the Python imports: tuna (see: https://github.com/nschloe/tuna). tuna allows analyzing the import times from the log. Run it like so tuna import.log. It opens a browser window and visualizes the import times. With that I was able to manually move all imports to the functions in which they are needed (and bring in some other optimizations). This greatly violates PEP 8 (https://peps.python.org/pep-0008/#imports) but leads to very fast startup times.