def delete_dispatcher(args=sys.argv[1:]): """Parses command line and calls the different processing functions """ command = command_handling(args, COMMAND_LOG) # Parses command line arguments. command_args = a.parse_and_check(command) if command_args.resume: command_args, session_file, _ = get_stored_command( args, command_args.debug, command_log=COMMAND_LOG, dirs_log=DIRS_LOG, sessions_log=SESSIONS_LOG) else: if command_args.output_dir is None: command_args.output_dir = a.NOW directory = u.check_dir(os.path.join(command_args.output_dir, "tmp")) session_file = os.path.join(directory, SESSIONS_LOG) u.log_message(command.command + "\n", log_file=session_file) try: shutil.copy(DEFAULTS_FILE, os.path.join(directory, DEFAULTS_FILE)) except IOError: pass u.sys_log_message(u"%s\n" % os.path.abspath(directory), log_file=DIRS_LOG) # If --clear-logs the log files are cleared if "--clear-logs" in args: clear_log_files(LOG_FILES) # Creates the corresponding api instance api = a.get_api_instance(command_args, u.check_dir(session_file)) delete_resources(command_args, api) u.log_message("_" * 80 + "\n", log_file=session_file)
def report_dispatcher(args=sys.argv[1:]): """Parses command line and calls the different report functions """ command = command_handling(args, COMMAND_LOG) # Parses command line arguments. command_args = a.parse_and_check(command) port = DEFAULT_PORT if not command_args.port else command_args.port report_url = get_report_url(command_args) if not command_args.no_server: absolute_report_url = "http://%s:%s/%s" % (DEFAULT_HOST, port, report_url) current_directory = os.getcwd() os.chdir(os.path.join(HOME, SERVER_DIRECTORY)) httpd = None try: httpd = StoppableHTTPServer(\ (DEFAULT_HOST, port), SimpleHTTPServer.SimpleHTTPRequestHandler) thread.start_new_thread(httpd.serve, ()) except socket.error, exc: print exc # Open URL in new browser window webbrowser.open_new(absolute_report_url) # opens in default browser if httpd: raw_input("*********************************\n" "Press <RETURN> to stop the server\n" "*********************************\n") os.chdir(current_directory) if httpd: httpd.stop()
def analyze_dispatcher(args=sys.argv[1:]): """Main processing of the parsed options for BigMLer analyze """ # If --clear-logs the log files are cleared if "--clear-logs" in args: clear_log_files(LOG_FILES) command = command_handling(args, COMMAND_LOG) # Parses command line arguments. command_args = command.parser.parse_args(command.args) resume = command_args.resume if resume: command_args, session_file, _ = get_stored_command( args, command_args.debug, command_log=COMMAND_LOG, dirs_log=DIRS_LOG, sessions_log=SESSIONS_LOG) else: if command_args.output_dir is None: command_args.output_dir = a.NOW session_file = os.path.join(command_args.output_dir, SESSIONS_LOG) # If logging is required, open the file for logging log = None if command_args.log_file: u.check_dir(command_args.log_file) log = command_args.log_file # If --clear_logs the log files are cleared if command_args.clear_logs: clear_log_files([log]) if command_args.model_fields: model_fields = command_args.model_fields.split(',') command_args.model_fields_ = [ model_field.strip() for model_field in model_fields ] else: command_args.model_fields_ = {} u.sys_log_message(u"%s\n" % os.path.abspath(command_args.output_dir), log_file=DIRS_LOG) session_file = os.path.join(command_args.output_dir, SESSIONS_LOG) # create api instance form args api = a.get_api_instance(command_args, u.check_dir(session_file)) # Creates the corresponding api instance api = a.get_api_instance(command_args, u.check_dir(session_file)) a.transform_dataset_options(command_args, api) # --maximize flag will be deprecated. Use --optimize flag. if command_args.maximize is not None and command_args.optimize is None: command_args.optimize = command_args.maximize incompatible_flags = [ command_args.cv, command_args.features, command_args.nodes, command_args.random_fields ] if sum([int(bool(flag)) for flag in incompatible_flags]) > 1: sys.exit("The following flags cannot be used together:\n --features" "\n --cross-validation\n --nodes\n --random-fields") if (command_args.dataset is None and command_args.datasets is None and command_args.dataset_file is None): sys.exit("The analyze command needs an existing dataset ID. Please, " "use the --dataset flag.") if not any(incompatible_flags): sys.exit("You need to specify the type of analysis: features, node " "threshold, cross validation or random fields.") # k-fold cross-validation if command_args.cv and command_args.dataset is not None: create_kfold_cv(command_args, api, command.common_options, resume=resume) # features analysis elif command_args.features: create_features_analysis(command_args, api, command.common_options, resume=resume) # node threshold analysis elif command_args.nodes: create_nodes_analysis(command_args, api, command.common_options, resume=resume) # random fields analysis elif command_args.random_fields: create_candidates_analysis(command_args, api, command.common_options, resume=resume) else: sys.exit("You must choose one of the available analysis: --features," " --nodes, --random-fields or --cross-validation. Add" " your prefered option to" " the command line or type\n bigmler analyze --help\n" " to see all the available options.")
def analyze_dispatcher(args=sys.argv[1:]): """Main processing of the parsed options for BigMLer analyze """ # If --clear-logs the log files are cleared if "--clear-logs" in args: clear_log_files(LOG_FILES) command = command_handling(args, COMMAND_LOG) # Parses command line arguments. command_args = command.parser.parse_args(command.args) resume = command_args.resume if resume: command_args, session_file, _ = get_stored_command( args, command_args.debug, command_log=COMMAND_LOG, dirs_log=DIRS_LOG, sessions_log=SESSIONS_LOG) else: if command_args.output_dir is None: command_args.output_dir = a.NOW session_file = os.path.join(command_args.output_dir, SESSIONS_LOG) # If logging is required, open the file for logging log = None if command_args.log_file: u.check_dir(command_args.log_file) log = command_args.log_file # If --clear_logs the log files are cleared if command_args.clear_logs: clear_log_files([log]) if command_args.model_fields: model_fields = command_args.model_fields.split(',') command_args.model_fields_ = [model_field.strip() for model_field in model_fields] else: command_args.model_fields_ = {} u.sys_log_message(u"%s\n" % os.path.abspath(command_args.output_dir), log_file=DIRS_LOG) session_file = os.path.join(command_args.output_dir, SESSIONS_LOG) # create api instance form args api = a.get_api_instance(command_args, u.check_dir(session_file)) # Creates the corresponding api instance api = a.get_api_instance(command_args, u.check_dir(session_file)) a.transform_dataset_options(command_args, api) # --maximize flag will be deprecated. Use --optimize flag. if command_args.maximize is not None and command_args.optimize is None: command_args.optimize = command_args.maximize incompatible_flags = [command_args.cv, command_args.features, command_args.nodes, command_args.random_fields] if sum([int(bool(flag)) for flag in incompatible_flags]) > 1: sys.exit("The following flags cannot be used together:\n --features" "\n --cross-validation\n --nodes\n --random-fields") if (command_args.dataset is None and command_args.datasets is None and command_args.dataset_file is None): sys.exit("The analyze command needs an existing dataset ID. Please, " "use the --dataset flag.") if not any(incompatible_flags): sys.exit("You need to specify the type of analysis: features, node " "threshold, cross validation or random fields.") # k-fold cross-validation if command_args.cv and command_args.dataset is not None: create_kfold_cv(command_args, api, command, resume=resume) # features analysis elif command_args.features: create_features_analysis(command_args, api, command, resume=resume) # node threshold analysis elif command_args.nodes: create_nodes_analysis(command_args, api, command, resume=resume) # random fields analysis elif command_args.random_fields: create_candidates_analysis(command_args, api, command, resume=resume) else: sys.exit("You must choose one of the available analysis: --features," " --nodes, --random-fields or --cross-validation. Add" " your prefered option to" " the command line or type\n bigmler analyze --help\n" " to see all the available options.")