import yaml from flatten_dict import unflatten from server.default_config import get_default_config from server.common.config.dataset_config import DatasetConfig from server.common.config.server_config import ServerConfig from server.common.config.external_config import ExternalConfig from server.common.errors import ConfigurationError class AppConfig(object): """ AppConfig stores all the configuration for cellxgene. AppConfig contains one or more DatasetConfig(s) and one ServerConfig. The server_config contains attributes that refer to the server process as a whole. The dataset_config refers to attributes that are associated with the features and presentations of a dataset. AppConfig has methods to initialize, modify, and access the configuration. """ def __init__(self): # the default configuration (see default_config.py) # TODO @madison -- if we always read from the default config (hard coded path) can we set those values as # defaults within the config class? self.default_config = get_default_config() # the server configuration self.server_config = ServerConfig(self, self.default_config["server"]) # the dataset config self.dataset_config = DatasetConfig(None, self, self.default_config["dataset"]) # external config self.external_config = ExternalConfig(self, self.default_config["external"]) # Set to true when config_completed is called self.is_completed = False def get_dataset_config(self): return self.dataset_config def check_config(self): """Verify all the attributes in the config have been type checked""" if not self.is_completed: raise ConfigurationError("The configuration has not been completed") self.server_config.check_config() self.dataset_config.check_config() self.external_config.check_config() def update_server_config(self, **kw): self.server_config.update(**kw) self.is_complete = False def update_dataset_config(self, **kw): self.dataset_config.update(**kw) self.is_complete = False def update_single_config_from_path_and_value(self, path, value): """Update a single config parameter with the value. Path is a list of string, that gives a path to the config parameter to be updated. For example, path may be ["server","app","port"]. """ self.is_complete = False if not isinstance(path, list): raise ConfigurationError(f"path must be a list of strings, got '{str(path)}'") for part in path: if not isinstance(part, str): raise ConfigurationError(f"path must be a list of strings, got '{str(path)}'") if len(path) < 1 or path[0] not in ("server", "dataset"): raise ConfigurationError("path must start with 'server', or 'dataset'") if path[0] == "server": attr = "__".join(path[1:]) try: self.update_server_config(**{attr: value}) except ConfigurationError: raise ConfigurationError(f"unknown config parameter at path: '{str(path)}'") elif path[0] == "dataset": attr = "__".join(path[1:]) try: self.update_dataset_config(**{attr: value}) except ConfigurationError: raise ConfigurationError(f"unknown config parameter at path: '{str(path)}'") def update_from_config_file(self, config_file): try: with open(config_file) as yml_file: config = yaml.safe_load(yml_file) except yaml.YAMLError as e: raise ConfigurationError(f"The specified config file contained an error: {e}") except OSError as e: raise ConfigurationError(f"Issue retrieving the specified config file: {e}") if config.get("server"): self.server_config.update_from_config(config["server"], "server") if config.get("dataset"): self.dataset_config.update_from_config(config["dataset"], "dataset") if config.get("external"): self.external_config.update_from_config(config["external"], "external") self.is_complete = False def config_to_dict(self): """return the configuration as an unflattened dict""" server = self.server_config.create_mapping(self.server_config.default_config) dataset = self.dataset_config.create_mapping(self.dataset_config.default_config) external = self.external_config.create_mapping(self.external_config.default_config) config = dict(server={}, dataset={}) for attrname in server.keys(): config["server__" + attrname] = getattr(self.server_config, attrname) for attrname in dataset.keys(): config["dataset__" + attrname] = getattr(self.dataset_config, attrname) for attrname in external.keys(): config["external__" + attrname] = getattr(self.external_config, attrname) config = unflatten(config, splitter=lambda key: key.split("__")) return config def write_config(self, config_file): """output the config to a yaml file""" config = self.config_to_dict() yaml.dump(config, open(config_file, "w")) def changes_from_default(self): """Return all the attribute that are different from the default""" diff_server = self.server_config.changes_from_default() diff_dataset = self.dataset_config.changes_from_default() diff_external = self.external.changes_from_default() diff = dict(server=diff_server, dataset=diff_dataset, external=diff_external) return diff def complete_config(self, messagefn=None): """The configure options are checked, and any additional setup based on the config parameters is done""" if messagefn is None: def noop(message): pass messagefn = noop # TODO: to give better error messages we can add a mapping between where each config # attribute originated (e.g. command line argument or config file), then in the error # messages we can give correct context for attributes with bad value. context = dict(messagefn=messagefn) # complete config for external_config first, since this may update values in the other sections self.external_config.complete_config(context) self.server_config.complete_config(context) self.dataset_config.complete_config(context) self.is_completed = True self.check_config() def get_matrix_data_cache_manager(self): return self.server_config.matrix_data_cache_manager def get_title(self, data_adaptor): return ( self.server_config.single_dataset__title if self.server_config.single_dataset__title else data_adaptor.get_title() ) def get_about(self, data_adaptor): return ( self.server_config.single_dataset__about if self.server_config.single_dataset__about else data_adaptor.get_about() )