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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_common_cbc_transforms(requested_params, variable_args, valid_params=None):
 """Determines if any additional parameters from the InferenceFile are needed to get derived parameters that user has asked for. First it will try to add any base parameters that are required to calculate the derived parameters. Then it will add any sampling parameters that are required to calculate the base parameters needed. Parameters requested_params : list List of parameters that user wants. variable_args : list List of parameters that InferenceFile has. valid_params : list List of parameters that can be accepted. Returns ------- requested_params : list Updated list of parameters that user wants. all_c : list List of BaseTransforms to apply. """

    variable_args = set(variable_args) if not isinstance(variable_args, set) \
                                    else variable_args

    # try to parse any equations by putting all strings together
    # this will get some garbage but ensures all alphanumeric/underscored
    # parameter names are added
    new_params = []
    for opt in requested_params:
        s = ""
        for ch in opt:
            s += ch if ch.isalnum() or ch == "_" else " "
        new_params += s.split(" ")
    requested_params = set(list(requested_params) + list(new_params))

    # can pass a list of valid parameters to remove garbage from parsing above
    if valid_params:
        valid_params = set(valid_params)
        requested_params = requested_params.intersection(valid_params)

    # find all the transforms for the requested derived parameters
    # calculated from base parameters
    from_base_c = []
    for converter in common_cbc_inverse_transforms:
        if (converter.outputs.issubset(variable_args) or
                converter.outputs.isdisjoint(requested_params)):
            continue
        intersect = converter.outputs.intersection(requested_params)
        if (not intersect or intersect.issubset(converter.inputs) or
                intersect.issubset(variable_args)):
            continue
        requested_params.update(converter.inputs)
        from_base_c.append(converter)

    # find all the tranforms for the required base parameters
    # calculated from sampling parameters
    to_base_c = []
    for converter in common_cbc_forward_transforms:
        if (converter.inputs.issubset(variable_args) and
                len(converter.outputs.intersection(requested_params)) > 0):
            requested_params.update(converter.inputs)
            to_base_c.append(converter)
            variable_args.update(converter.outputs)

    # get list of transforms that converts sampling parameters to the base
    # parameters and then converts base parameters to the derived parameters
    all_c = to_base_c + from_base_c

    return list(requested_params), all_c