Feature/c3s extract funs

[bzah]

Pull Request for the issue "C3S integration" (not logged in github)

• These changes were tested with real data and unit tests cover them as well.
• The relevant documentation has been added (or updated).
• A short description of the changes has been added to doc/source/references/release_notes.rst

Describe the changes you made

This PR covers multiple issues that c3s integration highlighted:

• Refactored ecad_functions (removed duplicated code, simplified function signatures...)
• Refactored IndexConfig to hide some technical knowledge which was leaked to other modules.
• Made a basic integration of clix-meta yaml to populate the generated docstring for c3s.
  This makes pyyaml an required dependency of icclim.
• Fixed an issue with aliasing of "icclim" module and "icclim" package
• Added some metadata to qualify the cead_indices and recognize the arguments necessary to compute them.

Example of generated code with index TG (click me!)

def tg(
    in_files: typing.Union[str, typing.List[str], xarray.Dataset],
    var_name: typing.Union[str, typing.List[str], None] = None,
    slice_mode: typing.Union[typing.Any, str, typing.List[typing.Union[str, typing.Tuple, int]]] = Frequency.YEAR,
    time_range: typing.List[datetime.datetime] = None,
    out_file: str = "icclim_out.nc",
    transfer_limit_Mbytes: float = None,
    ignore_Feb29th: bool = False,
    netcdf_version: typing.Union[str, icclim.models.netcdf_version.NetcdfVersion] = NetcdfVersion.NETCDF4,
    logs_verbosity: typing.Union[icclim.icclim_logger.Verbosity, str] = Verbosity.LOW) -> xarray.Dataset:
    """
    Mean of daily mean temperature
    Source: Source: ECA&D, Algorithm Theoretical Basis Document (ATBD) v11

    Parameters
    ----------
    in_files : Union[str, List[str], Dataset]
        Absolute path(s) to NetCDF dataset(s) (including OPeNDAP URLs),
        or xarray.Dataset.
    var_name : str
        ``optional`` Target variable name to process corresponding to ``in_files``.
        If None (default) on ECA&D index, the variable is guessed based on the climate
        index wanted.
        Mandatory for a user index.
    slice_mode : str
        Type of temporal aggregation:
        {"year", "month", "DJF", "MAM", "JJA", "SON", "ONDJFM" or "AMJJAS"}.
        Default is "year".
        See :ref:`slice_mode` for details.
    time_range : List[datetime.datetime]
        ``optional`` Temporal range: upper and lower bounds for temporal subsetting.
        If ``None``, whole period of input files will be processed.
        Default is ``None``.
    out_file : str
        Output NetCDF file name (default: "icclim_out.nc" in the current directory).
        Default is "icclim_out.nc".
        If the input ``in_files`` is a ``Dataset``, ``out_file`` field is ignored.
        Use the function returned value instead to retrieve the computed value.
        If ``out_file`` already exists, icclim will overwrite it!
    transfer_limit_Mbytes : float
        ``optional`` Maximum Dask chunk size in memory.
        The value should be around 200 MB.
        If empty, no chunking is performed, the whole dataset will be in memory and the
        performance might be poor.
    ignore_Feb29th : bool
        ``optional`` Ignoring or not February 29th (default: False).
    netcdf_version : icclim.models.netcdf_version.NetcdfVersion
        ``optional`` NetCDF version to create (default: "NETCDF3_CLASSIC").
    logs_verbosity : Union[str, Verbosity]
        ``optional`` Configure how verbose icclim is.
        Possible values: ``{"LOW", "HIGH", "SILENT"}`` (default: "LOW")

    Notes:
    ------
    This function has been auto-generated.
    """
    return icclim.index(
        index_name="TG",
        in_files=in_files,
        var_name=var_name,
        slice_mode=slice_mode,
        time_range=time_range,
        out_file=out_file,
        transfer_limit_Mbytes=transfer_limit_Mbytes,
        ignore_Feb29th=ignore_Feb29th,
        netcdf_version=netcdf_version,
        logs_verbosity=logs_verbosity)

Work in progress:

• unit tests for clix-meta module
• in extractor, replace the concatenation with a template (jinja or equivalent)
• we must consider integrating the generated code directly in icclim, it can certainly be useful to some users.
  Also, for user who would try icclim first in c3s toolbox, it would exposes a similar API to them.
• We should consider extracting user_index as well
• Add documentation links for clix-meta module
• Add tutorial to extract icclim functions

[pagecp]

Very impressive changes!

• We should consider extracting user_index as well: this will be very useful and will simplify the code structure to be even more understandable and modular I guess.