Improve services parallelization

[guillaume-chevalier]

Improve services parallelization

What it is

This pull request allows:

• Doing pickling checks on the parallelized services for them to avoid deadlocking the multithreading queues by having picklables services.
• It also repairs several bugs that impacted the parallelism and sometimes causing deadlocks.
• Moving some modules around and removing some dependencies between modules.

How it works

Behavior unchanged except that some repositories now have a wrapper and that the context does not have a global lock anymore, which is good.

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Checklist before merging PR.

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•  If this is your first contribution to Neuraxle, please read the guide to contributing to the Neuraxle framework.
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• Argument's dimensions and types are specified for new steps (important), with examples in docstrings when needed.
• Class names and argument / API variables are very clear: there is no possible ambiguity. They also respect the existing code style (avoid duplicating words for the same concept) and are intuitive.
• Use typing like variable: Typing = ... as much as possible. Also use typing for function arguments and return values like def my_func(self, my_list: Dict[int, List[str]]) -> 'OrderedDict[int, str]':.
• Classes are documented: their behavior is explained beyond just the title of the class. You may even use the description written in your pull request above to fill some docstrings accurately.
• If a numpy array is used, it is important to remember that these arrays are a special type that must be documented accordingly, and that numpy array should not be abused. This is because Neuraxle is a library that is not only limited to transforming numpy arrays. To this effect, numpy steps should probably be located in the existing numpy python files as much as possible, and not be all over the place. The same applies to Pandas DataFrames.
• Code coverage is above 90% for the added code for the unit tests.
• The above description of the pull request in natural language was used to document the new code inside the code's docstrings so as to have complete documentation, with examples.
• Respect the Unit Testing status check
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• Code files that were edited were reformatted automatically using PyCharm's Ctrl+Alt+L shortcut. You may have reorganized imports as well.