diff options
Diffstat (limited to 'resources/tools/presentation/input_data_parser.py')
| -rw-r--r-- | resources/tools/presentation/input_data_parser.py | 219 |
1 files changed, 179 insertions, 40 deletions
diff --git a/resources/tools/presentation/input_data_parser.py b/resources/tools/presentation/input_data_parser.py index d0f9eed9a4..9428b2cdc9 100644 --- a/resources/tools/presentation/input_data_parser.py +++ b/resources/tools/presentation/input_data_parser.py @@ -18,10 +18,11 @@ - provide access to the data. """ +import multiprocessing +import os import re import pandas as pd import logging -import xml.etree.ElementTree as ET from robot.api import ExecutionResult, ResultVisitor from robot import errors @@ -698,7 +699,7 @@ class InputData(object): self._cfg = spec # Data store: - self._input_data = None + self._input_data = pd.Series() @property def data(self): @@ -749,14 +750,16 @@ class InputData(object): return self.data[job][build]["tests"] @staticmethod - def _parse_tests(job, build): + def _parse_tests(job, build, log): """Process data from robot output.xml file and return JSON structured data. :param job: The name of job which build output data will be processed. :param build: The build which output data will be processed. + :param log: List of log messages. :type job: str :type build: dict + :type log: list of tuples (severity, msg) :returns: JSON data structure. :rtype: dict """ @@ -770,54 +773,129 @@ class InputData(object): try: result = ExecutionResult(data_file) except errors.DataError as err: - logging.error("Error occurred while parsing output.xml: {0}". - format(err)) + log.append(("ERROR", "Error occurred while parsing output.xml: " + "{0}".format(err))) return None checker = ExecutionChecker(metadata) result.visit(checker) return checker.data - def download_and_parse_data(self): + def _download_and_parse_build(self, pid, data_queue, job, build, repeat): + """Download and parse the input data file. + + :param pid: PID of the process executing this method. + :param data_queue: Shared memory between processes. Queue which keeps + the result data. This data is then read by the main process and used + in further processing. + :param job: Name of the Jenkins job which generated the processed input + file. + :param build: Information about the Jenkins build which generated the + processed input file. + :param repeat: Repeat the download specified number of times if not + successful. + :type pid: int + :type data_queue: multiprocessing.Manager().Queue() + :type job: str + :type build: dict + :type repeat: int + """ + + logs = list() + + logging.info(" Processing the job/build: {0}: {1}". + format(job, build["build"])) + + logs.append(("INFO", " Processing the job/build: {0}: {1}". + format(job, build["build"]))) + + state = "failed" + success = False + data = None + do_repeat = repeat + while do_repeat: + success = download_and_unzip_data_file(self._cfg, job, build, pid, + logs) + if success: + break + do_repeat -= 1 + if not success: + logs.append(("ERROR", "It is not possible to download the input " + "data file from the job '{job}', build " + "'{build}', or it is damaged. Skipped.". + format(job=job, build=build["build"]))) + if success: + logs.append(("INFO", " Processing data from the build '{0}' ...". + format(build["build"]))) + data = InputData._parse_tests(job, build, logs) + if data is None: + logs.append(("ERROR", "Input data file from the job '{job}', " + "build '{build}' is damaged. Skipped.". + format(job=job, build=build["build"]))) + else: + state = "processed" + + try: + remove(build["file-name"]) + except OSError as err: + logs.append(("ERROR", "Cannot remove the file '{0}': {1}". + format(build["file-name"], err))) + logs.append(("INFO", " Done.")) + + result = { + "data": data, + "state": state, + "job": job, + "build": build, + "logs": logs + } + data_queue.put(result) + + def download_and_parse_data(self, repeat=1): """Download the input data files, parse input data from input files and store in pandas' Series. + + :param repeat: Repeat the download specified number of times if not + successful. + :type repeat: int """ logging.info("Downloading and parsing input files ...") - job_data = dict() + work_queue = multiprocessing.JoinableQueue() + + manager = multiprocessing.Manager() + + data_queue = manager.Queue() + + cpus = multiprocessing.cpu_count() + workers = list() + for cpu in range(cpus): + worker = Worker(work_queue, + data_queue, + self._download_and_parse_build) + worker.daemon = True + worker.start() + workers.append(worker) + os.system("taskset -p -c {0} {1} > /dev/null 2>&1". + format(cpu, worker.pid)) + for job, builds in self._cfg.builds.items(): - logging.info(" Processing data from the job '{0}' ...". - format(job)) - builds_data = dict() for build in builds: - logging.info(" Processing the build '{0}'". - format(build["build"])) - self._cfg.set_input_state(job, build["build"], "failed") - if not download_and_unzip_data_file(self._cfg, job, build): - logging.error("It is not possible to download the input " - "data file from the job '{job}', build " - "'{build}', or it is damaged. Skipped.". - format(job=job, build=build["build"])) - continue + work_queue.put((job, build, repeat)) - logging.info(" Processing data from the build '{0}' ...". - format(build["build"])) - data = InputData._parse_tests(job, build) - if data is None: - logging.error("Input data file from the job '{job}', build " - "'{build}' is damaged. Skipped.". - format(job=job, build=build["build"])) - continue + work_queue.join() - self._cfg.set_input_state(job, build["build"], "processed") + logging.info("Done.") - try: - remove(build["file-name"]) - except OSError as err: - logging.error("Cannot remove the file '{0}': {1}". - format(build["file-name"], err)) + while not data_queue.empty(): + result = data_queue.get() + job = result["job"] + build_nr = result["build"]["build"] + + if result["data"]: + data = result["data"] build_data = pd.Series({ "metadata": pd.Series(data["metadata"].values(), index=data["metadata"].keys()), @@ -825,15 +903,35 @@ class InputData(object): index=data["suites"].keys()), "tests": pd.Series(data["tests"].values(), index=data["tests"].keys())}) - builds_data[str(build["build"])] = build_data - build["status"] = "processed" - logging.info(" Done.") - job_data[job] = pd.Series(builds_data.values(), - index=builds_data.keys()) - logging.info(" Done.") + if self._input_data.get(job, None) is None: + self._input_data[job] = pd.Series() + self._input_data[job][str(build_nr)] = build_data + + self._cfg.set_input_file_name(job, build_nr, + result["build"]["file-name"]) + + self._cfg.set_input_state(job, build_nr, result["state"]) + + for item in result["logs"]: + if item[0] == "INFO": + logging.info(item[1]) + elif item[0] == "ERROR": + logging.error(item[1]) + elif item[0] == "DEBUG": + logging.debug(item[1]) + elif item[0] == "CRITICAL": + logging.critical(item[1]) + elif item[0] == "WARNING": + logging.warning(item[1]) + + del data_queue + + # Terminate all workers + for worker in workers: + worker.terminate() + worker.join() - self._input_data = pd.Series(job_data.values(), index=job_data.keys()) logging.info("Done.") @staticmethod @@ -997,3 +1095,44 @@ class InputData(object): merged_data[ID] = item_data return merged_data + + +class Worker(multiprocessing.Process): + """Worker class used to download and process input files in separate + parallel processes. + """ + + def __init__(self, work_queue, data_queue, func): + """Initialization. + + :param work_queue: Queue with items to process. + :param data_queue: Shared memory between processes. Queue which keeps + the result data. This data is then read by the main process and used + in further processing. + :param func: Function which is executed by the worker. + :type work_queue: multiprocessing.JoinableQueue + :type data_queue: multiprocessing.Manager().Queue() + :type func: Callable object + """ + super(Worker, self).__init__() + self._work_queue = work_queue + self._data_queue = data_queue + self._func = func + + def run(self): + """Method representing the process's activity. + """ + + while True: + try: + self.process(self._work_queue.get()) + finally: + self._work_queue.task_done() + + def process(self, item_to_process): + """Method executed by the runner. + + :param item_to_process: Data to be processed by the function. + :type item_to_process: tuple + """ + self._func(self.pid, self._data_queue, *item_to_process) |