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Hey - first of all, looks great and I'll definitely look into it. Good job! Question - do you have any comparisons on the size of the resulting distributed exe
by gota 5y ago
Hey - first of all, looks great and I'll definitely look into it. Good job!
Question - do you have any comparisons on the size of the resulting distributed executable compared to Nuitka, pyinstaller?
This is the issue I've faced. Nontrivial programs (that, say, import pandas, numpy, selenium) are huge, implying a ~250MB+ download for the user - and then maybe up to 1GB in disk when its all unpacked.
- gota 5y agoBTW the error tracking described in the Manual sounds great. Are you affiliated to Sentry in any way?
- mherrmann 5y agoNo affiliation whatsoever. If you want to use Sentry for almost free, you can use my (old) scripts for deploying it to a $5 / month VPS: https://github.com/mherrmann/sentry-self-hosted https://github.com/mherrmann/sentry-self-hosted
- mherrmann 5y agoThanks! Regarding your question: fbs uses PyInstaller under the hood, so the binaries should be pretty similar in size.
- nyanpasu64 5y agoThe OpenBLAS version of NumPy (from pip rather than conda), plus PyQt5, can fit in around 100 megabytes uncompressed on disk for a Win64 binary. However I no longer recommend writing number crunching apps in Python, since you don't have thread-based parallelism due to the GIL, and have to awkwardly shuffle data across processes. (Last time I tried multiprocessing, some data can only be sent to workers on Linux using fork-based worker spawning, and not on Windows which lacks fork and requires pickling.)
- doubleunplussed 5y agoIf the number crunching is numpy-heavy, multiple threads absolutely can use real thread-based parallelism. C extensions like numpy release the GIL and so can run in parallel.
- deleted 5y ago[deleted]