Method get_validator

plotly/validator_cache.py:17–66

(parent_path, prop_name)

    @staticmethod
    def get_validator(parent_path, prop_name):
        if ValidatorCache._json_cache is None:
            # Load the JSON validator params from the file
            validator_json_path = opath.join(
                opath.dirname(__file__), "validators", "_validators.json"
            )
            if not opath.exists(validator_json_path):
                raise FileNotFoundError(
                    f"Validator JSON file not found: {validator_json_path}"
                )
            with open(validator_json_path, "r") as f:
                ValidatorCache._json_cache = json.load(f)

        key = (parent_path, prop_name)
        if key not in ValidatorCache._cache:
            if "." not in parent_path and prop_name == "type":
                # Special case for .type property of traces
                validator = LiteralValidator("type", parent_path, parent_path)
            else:
                lookup_name = None
                if parent_path == "layout":
                    from .graph_objects import Layout

                    match = Layout._subplotid_prop_re.match(prop_name)
                    if match:
                        lookup_name = match.group(1)

                lookup_name = lookup_name or prop_name
                lookup = f"{parent_path}.{lookup_name}" if parent_path else lookup_name

                validator_item = ValidatorCache._json_cache.get(lookup)
                validator_classname = validator_item["superclass"]
                if validator_classname in DERIVED_CLASSES:
                    # If the superclass is a derived class, we need to get the base class
                    # and pass the derived class name as a parameter
                    base_item = ValidatorCache._json_cache.get(
                        DERIVED_CLASSES[validator_classname]
                    )
                    validator_params = base_item["params"]
                    validator_params.update(validator_item["params"])
                    validator_classname = base_item["superclass"]
                else:
                    validator_params = validator_item["params"]
                validator_params["plotly_name"] = prop_name
                validator_class = getattr(basevalidators, validator_classname)

                validator = validator_class(**validator_params)
            ValidatorCache._cache[key] = validator

        return ValidatorCache._cache[key]