[ENH] Improve Global Config Architecture

[SimonBlanke]

The config module uses extensive globals and I agree with this comment: https://github.com/openml/openml-python/blob/main/openml/config.py#L395

This is problematic for the following reasons:

• Any code can modify openml.config.apikey = "x". So bad or no encapsulation
• Global state persists between tests, causing flaky tests
• openml.config.apikey = 123 silently accepts wrong type. So no validation

And I am sure there are more reasons.

I think it was done to have this kind of API instead of function-call-like syntax:

openml.config.apikey = "my-key"
openml.config.server = "https://test.openml.org/api/v1/xml"

We can preserve this API and still get rid of most of these globals()/global, by defining a module level __getattr__ and __setattr__ and use a dataclass for the data encapsulation and validation:

  from dataclasses import dataclass, replace

  @dataclass
  class OpenMLConfig:
      apikey: str = ""
      server: str = "https://www.openml.org/api/v1/xml"
      # ... 

  _config = OpenMLConfig()

  def __getattr__(name: str):
      if hasattr(_config, name):
          return getattr(_config, name)
      raise AttributeError(f"module 'openml.config' has no attribute '{name}'")

  def __setattr__(name: str, value):
      global _config
      if hasattr(_config, name):
          _config = replace(_config, **{name: value})
      else:
          raise AttributeError(f"module 'openml.config' has no attribute '{name}'")

This is still not a solution I am completely content with, but it is an improvement and not too difficult to implement.

[satvshr]

Picking this one up. Given I also wanted to look more into architecture design, I will try to figure out a better approach too given you aren't happy with the fix you suggested either!