aswi2020sebela-gitlab/modules/crawler/Pipeline.py @ 587b1c57

from Utilities import FolderProcessor, ConfigureFunctions
from Utilities.Database import DatabaseLoader

import logging
from datetime import date


# Path to crawled data
CRAWLED_DATA_PATH = "CrawledData/"
# Path to processed data
PROCESSED_DATA_PATH = "ProcessedData/"
# Path to crawler logs
CRAWLER_LOGS_PATH = "CrawlerLogs/"
# Path to dataset crawler implementations
CRAWLER_LIB_PATH = "DatasetCrawler."
# Path to dataset processor implementations
PROCESSOR_LIB_PATH = "DatasetProcessing."


#logger
logging.basicConfig(filename=CRAWLER_LOGS_PATH + "CommonRecords/" + 'Applicationlog-' + date.today().strftime("%b-%Y") + '.log',
                    level=logging.INFO,
                    format='%(asctime)s %(message)s'
                    )


def check_last_update(config):
    """
    Loads integer from updated.txt in CrawlerLogs/"dataset_name"
    representing number of days from last update if number equals
    number in confing update period updates it and reset number of
    days to zero else increment the number

    Arguments:
        config loaded configuration file of dataset

    Returns:
       True if updating
       Else if incementing days from last update
    """
    dataset_name = config["dataset-name"]

    with open(CRAWLER_LOGS_PATH + dataset_name + "/" + "updated.txt", "r+") as file:
        last_update = file.read()
        last_update = int(last_update)
        file.seek(0)

        confing_update_period = int(config["update-period"])

        if config["update-period"] <= last_update:
            logging.info("Dataset " + dataset_name + " is being updated today")
            file.write("0")
            file.truncate()
            return True
        else:
            last_update_days = last_update + 1
            logging.info("Dataset " + dataset_name + " will be updated in " + str(confing_update_period - last_update_days) + "days")
            file.write(str(last_update_days))
            file.truncate()
            return False



def crawl_data(config):
    """
      Imports dataset crawler in DatasetCrawler/"dataset_name"Crawler.py
      runs crawler.

    Args:
        config: loaded configuration file of dataset
    """
    dataset_name = config["dataset-name"]

    crawl_func = __import__(CRAWLER_LIB_PATH + dataset_name + "Crawler", globals(), locals(), ['crawl']).crawl
    crawl_func(config)

    dataset_name += '/'


def process_data(dataset_name):
    """
    Goes trough every not processed file(not contained in CrawledData/"dataset_name"/ignore.txt)
    Imports dataset processor in DatasetProcessing/"dataset_name"Processor.py
    Runs processor on every file
    After successful processing updates ignore.txt

    Args:
        dataset_name: name of dataset that has existing configuration file
    """
    dataset_path = dataset_name + '/'

    process_file_func = __import__(PROCESSOR_LIB_PATH + dataset_name + "Processor", globals(), locals(),
                                   ['process_file']).process_file

    not_processed_files = FolderProcessor.list_of_all_files(CRAWLED_DATA_PATH + dataset_path)
    logging.info(dataset_name + " has downloaded " + str(len(not_processed_files)) + " new files")

    for not_processed_file in not_processed_files:
        process_file_func(CRAWLED_DATA_PATH + dataset_path + not_processed_file)
        FolderProcessor.update_ignore_set(CRAWLED_DATA_PATH + dataset_path, not_processed_file)

    logging.info(dataset_name + " has processed " + str(len(not_processed_files)) + " newly crawled files")


def validate_process_data(config):
    """
    Function goes through newly processed data and checks theirs status

    Args:
        config: loaded configuration file of dataset

    Returns:
        boolean variable TRUE/FALSE.
        Data processed correctly - TRUE
        Wrong format or NEW unknown devices - FALSE
    """
    processed_devices_set = FolderProcessor.get_devices_set(PROCESSED_DATA_PATH + config["dataset-name"] + '/')
    unknown_devices_set = FolderProcessor.get_unknown_devices_set(config, processed_devices_set)
    unknown_devices_size = len(unknown_devices_set)

    if unknown_devices_size != 0:
        logging.info("There is " + str(unknown_devices_size) + " unknown devices")
        logging.info("Adding devices to " + config["dataset-name"] + " config file")
        ConfigureFunctions.update_configuration(config["dataset-name"], unknown_devices_set)
        return False

    for device in config["devices"]:
        device = config["devices"][device]
        if device["x"] == "UNKNOWN!" or device["y"] == "UNKNOWN!":
            logging.info(config["dataset-name"] + " config file contains devices with UNKOWN! values please update them!!")
            return False

    return True


def load_data_to_database(config):
    """
    Goes trough every not loaded file(not contained in ProcessedData/ignore.txt)
    loads data appends coordination from configurations
    and exports it into the database
    After successful exporting updates ignore.txt

    Args:
        config: loaded configuration file of dataset
    """
    dataset_name = config["dataset-name"]
    dataset_path = dataset_name + '/'

    # get all unprocessed files from dataset
    not_loaded_files = FolderProcessor.list_of_all_files(PROCESSED_DATA_PATH + dataset_path)

    # load every file
    for not_loaded_file in not_loaded_files:
        # load processed data
        processed_data = DatabaseLoader.get_data_from_file(not_loaded_file, config)
        # load processed data to database
        DatabaseLoader.load_data_to_database(dataset_name, processed_data)
        FolderProcessor.update_ignore_set(PROCESSED_DATA_PATH + dataset_path, not_loaded_file)

    logging.info(dataset_name + " has loaded to databse " + str(len(not_loaded_files)) + " newly processed files.")


def run_full_pipeline(dataset_name):
    """
    Loads config file and starts full pipeline
    -crawl data
    -process data
    -load data to database

    Args:
        dataset_name: name of dataset that has existing configuration file
    """
    logging.info("Starting pipeline for dataset " + dataset_name)
    
    config = ConfigureFunctions.load_configuration(dataset_name)
    crawl_data(config)
    process_data(config["dataset-name"])

    validation_test = validate_process_data(config)

    if validation_test:
        load_data_to_database(config)



def run_full_pipeline_crone(dataset_name):
    """
    Loads config file and starts full pipeline
    -crawl data
    -process data
    -load data to database

    Args:
        dataset_name: name of dataset that has existing configuration file
    """
    logging.info("Starting pipeline for dataset " + dataset_name)

    config = ConfigureFunctions.load_configuration(dataset_name)
    update_test = check_last_update(config)
    if update_test:
        crawl_data(config)
        process_data(config["dataset-name"])

        validation_test = validate_process_data(config)

        if validation_test:
            load_data_to_database(config)