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meta_process.py
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meta_process.py
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#!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright 2019 Silvio Peroni <[email protected]>
# Copyright 2019-2020 Fabio Mariani <[email protected]>
# Copyright 2021 Simone Persiani <[email protected]>
# Copyright 2021-2022 Arcangelo Massari <[email protected]>
#
# Permission to use, copy, modify, and/or distribute this software for any purpose
# with or without fee is hereby granted, provided that the above copyright notice
# and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED 'AS IS' AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
# REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
# FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT,
# OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE,
# DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
# ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS
# SOFTWARE.
from __future__ import annotations
import csv
import os
import traceback
from argparse import ArgumentParser
from concurrent.futures import as_completed
from datetime import datetime
from itertools import cycle
from sys import executable, platform
from typing import List, Tuple
import redis
import yaml
from oc_meta.core.creator import Creator
from oc_meta.core.curator import Curator
from oc_meta.lib.file_manager import (get_csv_data, init_cache, normalize_path,
pathoo, sort_files, zipit)
from oc_meta.plugins.multiprocess.resp_agents_creator import RespAgentsCreator
from oc_meta.plugins.multiprocess.resp_agents_curator import RespAgentsCurator
from oc_meta.run.upload.on_triplestore import *
from pebble import ProcessPool
from time_agnostic_library.support import generate_config_file
from tqdm import tqdm
from oc_ocdm import Storer
from oc_ocdm.counter_handler.redis_counter_handler import RedisCounterHandler
from oc_ocdm.prov import ProvSet
from oc_ocdm.support.reporter import Reporter
class MetaProcess:
def __init__(self, settings:dict, meta_config_path: str):
# Mandatory settings
self.triplestore_url = settings['triplestore_url']
self.input_csv_dir = normalize_path(settings['input_csv_dir'])
self.base_output_dir = normalize_path(settings['base_output_dir'])
self.resp_agent = settings['resp_agent']
self.info_dir = os.path.join(self.base_output_dir, 'info_dir')
self.output_csv_dir = os.path.join(self.base_output_dir, 'csv')
self.distinct_output_dirs = True if settings['base_output_dir'] != settings['output_rdf_dir'] else False
self.output_rdf_dir = normalize_path(settings['output_rdf_dir']) + os.sep + 'rdf' + os.sep
self.indexes_dir = os.path.join(self.base_output_dir, 'indexes')
self.cache_path = os.path.join(self.base_output_dir, 'cache.txt')
self.errors_path = os.path.join(self.base_output_dir, 'errors.txt')
# Optional settings
self.base_iri = settings['base_iri']
self.normalize_titles = settings.get('normalize_titles', True)
self.context_path = settings['context_path']
self.dir_split_number = settings['dir_split_number']
self.items_per_file = settings['items_per_file']
self.default_dir = settings['default_dir']
self.rdf_output_in_chunks = settings['rdf_output_in_chunks']
self.zip_output_rdf = settings['zip_output_rdf']
self.source = settings['source']
self.valid_dois_cache = dict() if bool(settings['use_doi_api_service']) == True else None
self.workers_number = int(settings['workers_number'])
supplier_prefix:str = settings['supplier_prefix']
self.supplier_prefix = supplier_prefix[:-1] if supplier_prefix.endswith('0') else supplier_prefix
self.silencer = settings['silencer']
# Time-Agnostic_library integration
self.time_agnostic_library_config = os.path.join(os.path.dirname(meta_config_path), 'time_agnostic_library_config.json')
if not os.path.exists(self.time_agnostic_library_config):
generate_config_file(config_path=self.time_agnostic_library_config, dataset_urls=[self.triplestore_url], dataset_dirs=list(),
provenance_urls=settings['provenance_endpoints'], provenance_dirs=list(),
blazegraph_full_text_search=settings['blazegraph_full_text_search'], fuseki_full_text_search=settings['fuseki_full_text_search'],
virtuoso_full_text_search=settings['virtuoso_full_text_search'], graphdb_connector_name=settings['graphdb_connector_name'],
cache_endpoint=settings['cache_endpoint'], cache_update_endpoint=settings['cache_update_endpoint'])
# Redis settings
self.redis_host = settings.get('redis_host', 'localhost')
self.redis_port = settings.get('redis_port', 6379)
self.redis_db = settings.get('redis_db', 5)
self.redis_client = redis.Redis(host=self.redis_host, port=self.redis_port, db=self.redis_db)
self.counter_handler = RedisCounterHandler(host=self.redis_host, port=self.redis_port, db=self.redis_db)
def prepare_folders(self) -> List[str]:
completed = init_cache(self.cache_path)
files_in_input_csv_dir = {filename for filename in os.listdir(self.input_csv_dir) if filename.endswith('.csv')}
files_to_be_processed = sort_files(list(files_in_input_csv_dir.difference(completed)))
for dir in [self.output_csv_dir, self.indexes_dir, self.output_rdf_dir]:
pathoo(dir)
if self.rdf_output_in_chunks:
data_dir = os.path.join(self.output_rdf_dir, 'data' + os.sep)
prov_dir = os.path.join(self.output_rdf_dir, 'prov' + os.sep)
for dir in [prov_dir, data_dir]:
pathoo(dir)
csv.field_size_limit(128)
return files_to_be_processed
def curate_and_create(self, filename:str, cache_path:str, errors_path:str, worker_number:int=None, resp_agents_only:bool=False, settings:str|None=None, meta_config_path: str = None) -> Tuple[dict, str, str, str]:
if os.path.exists(os.path.join(self.base_output_dir, '.stop')):
return {'message': 'skip'}, cache_path, errors_path, filename
try:
filepath = os.path.join(self.input_csv_dir, filename)
print(filepath)
data = get_csv_data(filepath)
supplier_prefix = f'{self.supplier_prefix}0' if worker_number is None else f'{self.supplier_prefix}{str(worker_number)}0'
# Curator
self.info_dir = os.path.join(self.info_dir, supplier_prefix)
curator_info_dir = os.path.join(self.info_dir, 'curator' + os.sep)
if resp_agents_only:
curator_obj = RespAgentsCurator(
data=data,
ts=self.triplestore_url,
prov_config=self.time_agnostic_library_config,
counter_handler=self.counter_handler,
base_iri=self.base_iri,
prefix=supplier_prefix,
settings=settings,
meta_config_path=meta_config_path)
else:
curator_obj = Curator(
data=data,
ts=self.triplestore_url,
prov_config=self.time_agnostic_library_config,
counter_handler=self.counter_handler,
base_iri=self.base_iri,
prefix=supplier_prefix,
valid_dois_cache=self.valid_dois_cache,
settings=settings,
silencer=self.silencer,
meta_config_path=meta_config_path
)
name = f"{filename.replace('.csv', '')}_{datetime.now().strftime('%Y-%m-%dT%H-%M-%S')}"
curator_obj.curator(filename=name, path_csv=self.output_csv_dir, path_index=self.indexes_dir)
# Creator
if resp_agents_only:
creator_obj = RespAgentsCreator(
data=curator_obj.data,
endpoint=self.triplestore_url,
base_iri=self.base_iri,
counter_handler=self.counter_handler,
supplier_prefix=supplier_prefix,
resp_agent=self.resp_agent,
ra_index=curator_obj.index_id_ra,
preexisting_entities=curator_obj.preexisting_entities,
everything_everywhere_allatonce=curator_obj.everything_everywhere_allatonce,
settings=settings,
meta_config_path=meta_config_path)
else:
creator_obj = Creator(
data=curator_obj.data,
endpoint=self.triplestore_url,
base_iri=self.base_iri,
counter_handler=self.counter_handler,
supplier_prefix=supplier_prefix,
resp_agent=self.resp_agent,
ra_index=curator_obj.index_id_ra,
br_index=curator_obj.index_id_br,
re_index_csv=curator_obj.re_index,
ar_index_csv=curator_obj.ar_index,
vi_index=curator_obj.VolIss,
preexisting_entities=curator_obj.preexisting_entities,
everything_everywhere_allatonce=curator_obj.everything_everywhere_allatonce,
settings=settings,
meta_config_path=meta_config_path
)
creator = creator_obj.creator(source=self.source)
# Provenance
prov = ProvSet(creator, self.base_iri, wanted_label=False, supplier_prefix=supplier_prefix, custom_counter_handler=self.counter_handler)
modified_entities = prov.generate_provenance()
# Storer
repok = Reporter(print_sentences = False)
reperr = Reporter(print_sentences = True, prefix='[Storer: ERROR] ')
res_storer = Storer(abstract_set=creator, repok=repok, reperr=reperr, context_map={}, dir_split=self.dir_split_number, n_file_item=self.items_per_file, default_dir=self.default_dir, output_format='json-ld', zip_output=self.zip_output_rdf, modified_entities=modified_entities)
prov_storer = Storer(abstract_set=prov, repok=repok, reperr=reperr, context_map={}, dir_split=self.dir_split_number, n_file_item=self.items_per_file, output_format='json-ld', zip_output=self.zip_output_rdf, modified_entities=modified_entities)
# with suppress_stdout():
self.store_data_and_prov(res_storer, prov_storer, filename)
return {'message': 'success'}, cache_path, errors_path, filename
except Exception as e:
tb = traceback.format_exc()
template = "An exception of type {0} occurred. Arguments:\n{1!r}\nTraceback:\n{2}"
message = template.format(type(e).__name__, e.args, tb)
return {'message': message}, cache_path, errors_path, filename
def store_data_and_prov(self, res_storer:Storer, prov_storer:Storer, filename:str) -> None:
if self.rdf_output_in_chunks:
filename_without_csv = filename[:-4]
f = os.path.join(self.output_rdf_dir, 'data', filename_without_csv + '.json')
res_storer.store_graphs_in_file(f, self.context_path)
res_storer.upload_all(self.triplestore_url, self.output_rdf_dir, batch_size=10)
f_prov = os.path.join(self.output_rdf_dir, 'prov', filename_without_csv + '.json')
prov_storer.store_graphs_in_file(f_prov, self.context_path)
else:
res_storer.store_all(base_dir=self.output_rdf_dir, base_iri=self.base_iri, context_path=self.context_path, process_id=None)
prov_storer.store_all(self.output_rdf_dir, self.base_iri, self.context_path, process_id=None)
res_storer.upload_all(triplestore_url=self.triplestore_url, base_dir=self.output_rdf_dir, batch_size=10, save_queries=True)
def save_data(self):
output_dirname = f"meta_output_{datetime.now().strftime('%Y-%m-%dT%H_%M_%S_%f')}.zip"
dirs_to_zip = [self.base_output_dir, self.output_rdf_dir] if self.distinct_output_dirs else [self.base_output_dir]
zipit(dirs_to_zip, output_dirname)
def run_sparql_updates(self, endpoint: str, folder: str, batch_size: int = 10):
upload_sparql_updates(endpoint, folder, batch_size)
def run_meta_process(settings: dict, meta_config_path: str, resp_agents_only: bool=False) -> None:
meta_process = MetaProcess(settings=settings, meta_config_path=meta_config_path)
is_unix = platform in {'linux', 'linux2', 'darwin'}
# delete_lock_files(base_dir=meta_process.base_output_dir)
files_to_be_processed = meta_process.prepare_folders()
max_workers = meta_process.workers_number
if max_workers == 0:
workers = list(range(1, os.cpu_count()))
elif max_workers == 1:
workers = [None]
else:
tens = int(str(max_workers)[:-1]) if max_workers >= 10 else 0
multiples_of_ten = {i for i in range(1, max_workers + tens + 1) if int(i) % 10 == 0}
workers = [i for i in range(1, max_workers+len(multiples_of_ten)+1) if i not in multiples_of_ten]
generate_gentle_buttons(meta_process.base_output_dir, meta_config_path, is_unix)
with ProcessPool(max_workers=max_workers, max_tasks=1) as executor, tqdm(total=len(files_to_be_processed), desc="Processing files") as progress_bar:
futures = [executor.schedule(curate_and_create_wrapper, args=(file, worker, resp_agents_only, settings, meta_config_path))
for file, worker in zip(files_to_be_processed, cycle(workers))]
for future in as_completed(futures):
try:
result = future.result()
task_done(result) # Gestisci il risultato del task
except Exception as e:
# Gestisci l'eccezione per il task che ha sollevato un'errore
traceback_str = traceback.format_exc()
print(f"Errore durante l'elaborazione: {e}\nTraceback:\n{traceback_str}")
finally:
progress_bar.update(1)
if not os.path.exists(os.path.join(meta_process.base_output_dir, '.stop')):
if os.path.exists(meta_process.cache_path):
os.rename(meta_process.cache_path, meta_process.cache_path.replace('.txt', f'_{datetime.now().strftime("%Y-%m-%dT%H_%M_%S_%f")}.txt'))
if is_unix:
delete_lock_files(base_dir=meta_process.base_output_dir)
meta_process.run_sparql_updates(endpoint=settings['triplestore_url'], folder=os.path.join(meta_process.output_rdf_dir, 'to_be_uploaded'))
def curate_and_create_wrapper(file_to_be_processed, worker_number, resp_agents_only, settings, meta_config_path):
meta_process = MetaProcess(settings=settings, meta_config_path=meta_config_path)
return meta_process.curate_and_create(file_to_be_processed, meta_process.cache_path, meta_process.errors_path, worker_number, resp_agents_only, settings, meta_config_path)
def task_done(task_output: tuple) -> None:
message, cache_path, errors_path, filename = task_output
if message['message'] == 'skip':
pass
elif message['message'] == 'success':
if not os.path.exists(cache_path):
with open(cache_path, 'w', encoding='utf-8') as aux_file:
aux_file.write(filename + '\n')
else:
with open(cache_path, 'r', encoding='utf-8') as aux_file:
cache_data = aux_file.read().splitlines()
cache_data.append(filename)
try:
data_sorted = sorted(cache_data, key=lambda filename: int(filename.replace('.csv', '')), reverse=False)
except ValueError:
data_sorted = cache_data
with open(cache_path, 'w', encoding='utf-8') as aux_file:
aux_file.write('\n'.join(data_sorted))
else:
with open(errors_path, 'a', encoding='utf-8') as aux_file:
aux_file.write(f'{filename}: {message["message"]}' + '\n')
def chunks(lst:list, n:int) -> List[list]:
'''Yield successive n-sized chunks from lst.'''
for i in range(0, len(lst), n):
yield lst[i:i + n]
def delete_lock_files(base_dir:list) -> None:
for dirpath, _, filenames in os.walk(base_dir):
for filename in filenames:
if filename.endswith('.lock'):
os.remove(os.path.join(dirpath, filename))
def generate_gentle_buttons(dir:str, config:str, is_unix:bool):
if os.path.exists(os.path.join(dir, '.stop')):
os.remove(os.path.join(dir, '.stop'))
ext = 'sh' if is_unix else 'bat'
with open (f'gently_run.{ext}', 'w') as rsh:
rsh.write(f'{executable} -m oc_meta.lib.stopper -t "{dir}" --remove\n{executable} -m oc_meta.run.meta_process -c {config}')
with open (f'gently_stop.{ext}', 'w') as rsh:
rsh.write(f'{executable} -m oc_meta.lib.stopper -t "{dir}" --add')
if __name__ == '__main__': # pragma: no cover
arg_parser = ArgumentParser('meta_process.py', description='This script runs the OCMeta data processing workflow')
arg_parser.add_argument('-c', '--config', dest='config', required=True, help='Configuration file directory')
args = arg_parser.parse_args()
with open(args.config, encoding='utf-8') as file:
settings = yaml.full_load(file)
run_meta_process(settings=settings, meta_config_path=args.config, resp_agents_only=False)