The tuple should contain a:
- boolean for success or failure
- dictionary with the data to return to the algorithm

The format is:

"loop": {
    "input": {
        "type": "data_format_name"
    },
    "output": {
        "type": "data_format_name"
    }
}

The format is:

"loop": {
    "input": {
        "type": "data_format_name"
    },
    "output": {
        "type": "data_format_name"
    }
}

- loop is the validation algorithm
- loop_user is the algorithm communicating with the loop

This will call the validation method of the loop algorithm.

To distinguish from classic algorithms.

This an algorithm that must implement a validate method
that will do the analysis of the output and provide a
boolean feedback. It might also write additional information
on an output.

This is an additionnal communication channel needed for
the loop to inter-operate with the algorithm block.

This allows to have a different process method signature
for algorithm using a loop block and no need to modify
existing algorithms.

It contains custom exceptions used in the package.

Fix lazy loading of algorithm's runner

See merge request !25

Improve zero handling

See merge request !24

In this case, don't do the check as numpy.array will guess the
value as int64 whatever the original dtype might be. In this case
return 0 as the dtype requested.

Improve array creation

See merge request !23

If a proper dtype is given as argument, then use it to create
the array. This will ensure that the expected type is used
rather than guessed.

Implement warning if prepare is present with api_version 2 property for algorithm

See merge request !22