django-debug-toolbar VS SWIG

The reason behind this splitting is that we can safely use packages and related settings only where we need. For example, this starter kit has the package django-debug-toolbar. This is only intended for your development environment and not for your production. This can be very risky if used in production because if your Django project encounters errors, all the debug info will be shown to the user which is a severe security risk. Similarly, for tracking errors in production, we're using Sentry which is not needed in our local environment since we already have django-debug-toolbar. For keeping these settings file separate so that they don't conflict with each other, the settings file is split for serving different environments.

django-debug-toolbar: https://github.com/jazzband/django-debug-toolbar

https://github.com/jazzband/django-debug-toolbar/issues?q=is%3Aopen+is%3Aissue+label%3ABug

https://github.com/jazzband/django-debug-toolbar Allows you to check which sql queries are being run on your app. See if they are optimized first.

Perhaps try the django-debug-toolbar. It might be able to tell you what is causing the slow load time.

I would start with https://github.com/jazzband/django-debug-toolbar and figure out what causes the slowness.

-> The debugging above from django-debug-toolbar

Documentation, including installation and configuration instructions, is available at https://django-debug-toolbar.readthedocs.io/.

How is this any different than a mature tool such as SWIG (https://www.swig.org/)?

I've used SWIG extensively with Python to call C code and import C headers for testing/tooling purposes.

For pure C, CGO. For C++ they are likely creating shims with Swig: https://www.swig.org/

I mostly write in C and C++ so for language bindings I use Swig a lot. Say Im creating a machine learning library in C++, its very easy to create a Python API that can call the C++ classes and methods using Swig. iirc, I am using the same swig interface file to create bindings for Python, OCaml, R and even Fortran. Feel free to DM me if you got any more questions or anything!

Swig can make c++ types and functions available to python.

The likes of SWIG is often used to link C library-like code to 11-ish other widely used languages.

Maybe you could use swig to create a wrapper for Java.

But, you might find these links interesting: * https://github.com/swig/swig/issues/918 * https://github.com/kaby76/swigged.llvm