transpiler VS Dependency Injector

At the moment it can recognise the type of statements in the training data set [1] and transpile them to Python, Java or C++ using the mappings defined here [2].

This is very different from how Codex/Autopilot work as it is trained using an NLU framework [3] which is usually used for training chatbots.

[1]: https://github.com/Flex-lang/transpiler/tree/master/transpil...

[2]: https://github.com/Flex-lang/transpiler/tree/master/transpil...

[3]: https://github.com/RasaHQ/rasa

Nothing to do with the nature of the language, but with the nature of the program.

If you're writing a few line script, you don't need a DI container. Once your program gets large, it becomes extremely messy without one. It's no surprise projects like [1] exist.

[1] https://github.com/ets-labs/python-dependency-injector

Totally agree with this. And I’ve found this pattern pairs really well with https://python-dependency-injector.ets-labs.org/

dependency_injector: https://github.com/ets-labs/python-dependency-injector

As projects continue to grow, its recommended to utilise a dependency injection framework to “inject” these dependencies, such as Dependency Injector, to inject dependency arguments automatically ✨.

One approach is to pass this config as a variable to every class it is required, which I dont prefer. Another option is to annotate the config class as singleton and create the config object at every place where I need them. I also came across this library called Dependency_Injector. https://python-dependency-injector.ets-labs.org/ This seems a bit heavy weight for my use case though. I am looking forward to know how other solve this problem

Dependency Injector

dependency-injector (docs) is python library that provides a framework which enables you to implement DI and IoC in Python.