PyInstaller VS lisa

Not sure if fixed in this patch, but pyinstaller had an issue in 3.12.0 https://github.com/pyinstaller/pyinstaller/issues/7992

You are right. I think I've misremembered the module name - it was uwsgi, not uvicorn.

This is a github issue where I discussed my original issue with PyInstaller devs - the dev explained the situation very well: https://github.com/pyinstaller/pyinstaller/issues/6362

PyInstaller seemed like the most maintained and developed tool to freeze python script into an executable, so I went with it. As expected, the freezed interface with the model was gigabytes large, so I had to figure out how to squeeze this. Fortunately, Onnx worked wonders and packaged the model into an inference only state, so I could throw away the Pytorch and Torchtext dependencies when freezing with Pyinstaller.Now the size of the executable with the model was 43MB instead of 4GB.

You might want to see Pyinstaller and auto_py_to_exe if you want a GUI interface.

It uses the pyinstaller command behind and please read their docs if you want to know more details.

I also found another link on github that may have some solutions to try: https://github.com/pyinstaller/pyinstaller/issues/3600

I made a Django react app. Now I want to make it a desktop application so that the user does not have type python manage.py runserver and also activate the environment every time. I used pyinstaller. I did all the steps mentioned for django

First, instead of creating a VM for windows, you may need to use a software called Wine mentioned in the pyinstaller FAQs

You might be interested in that: https://github.com/ARM-software/lisa/blob/master/lisa/monad.py

This is to replace the current flow purely based on pandas dataframe and offline trace.dat parsing used in LISA: https://github.com/ARM-software/lisa (collecting a trace.dat is nice for debugging but limits to small durations, and pandas does not allow running computations in constant memory, which is an issue for very big traces)

The module added by this PR seems to be a pretty good fit: https://github.com/ARM-software/lisa/pull/1722

I made that thing taking some vague inspiration from SML module system: https://github.com/ARM-software/lisa/pull/1722/files

import builtins from operator import add import functools # These functions can be found at: # https://github.com/ARM-software/lisa/blob/master/lisa/utils.py#L147 # Note: my implementation of curry() seems to be broken wrt named parameters (or for parameters with defaults, haven't looked at the details) for some reason but for this example it does not matter from lisa.utils import compose, curry def even(x): return x % 2 == 0 # The builtin functions don't have a signature, which will upset curry() so we # redefine it here def map(f, iterable): return builtins.map(f, iterable) def filter(f, iterable): return builtins.filter(f, iterable) # Swapped init and iterable to be curry-friendly def reduce(f, init, iterable): return functools.reduce(f, iterable, init) def pipeline(*items): # Add a currying layer so that we spare the user the need to do it return compose(*(curry(f)(*args) for (f, *args) in items)) # x = filter(even, list) |> map(lambda x: x+1) |> reduce(+) f = pipeline( (filter, even), (map, lambda x: x+1), (reduce, add, 0), ) l = [1,2,3,4] x = f(l) print(x)