def fill_self_cites_tables(rank_method_code, config):
"""
This will fill the self-cites tables with data
The purpose of this function is to fill these tables on a website that
never ran the self-cites daemon
This is an optimization when running on empty tables, and we hope the
result is the same as the compute_and_store_self_citations.
"""
begin_date = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
algorithm = config['algorithm']
tags = get_authors_tags()
selfcites_dic = {}
all_ids = intbitset(run_sql('SELECT id FROM bibrec ORDER BY id'))
citations_fun = get_citations_fun(algorithm)
write_message('using %s' % citations_fun.__name__)
if algorithm == 'friends':
# We only needs this table for the friends algorithm or assimilated
# Fill intermediary tables
for index, recid in enumerate(all_ids):
if index % 1000 == 0:
msg = 'intermediate %d/%d' % (index, len(all_ids))
task_update_progress(msg)
write_message(msg)
task_sleep_now_if_required()
update_self_cites_tables(recid, config, tags)
# Fill self-cites table
for index, recid in enumerate(all_ids):
if index % 1000 == 0:
msg = 'final %d/%d' % (index, len(all_ids))
task_update_progress(msg)
write_message(msg)
task_sleep_now_if_required()
compute_and_store_self_citations(recid,
tags,
citations_fun,
selfcites_dic)
intoDB(selfcites_dic, begin_date, rank_method_code)
store_weights_cache(selfcites_dic)
def fill_self_cites_tables(rank_method_code, config):
"""
This will fill the self-cites tables with data
The purpose of this function is to fill these tables on a website that
never ran the self-cites daemon
This is an optimization when running on empty tables, and we hope the
result is the same as the compute_and_store_self_citations.
"""
begin_date = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
algorithm = config['algorithm']
tags = get_authors_tags()
selfcites_dic = {}
all_ids = intbitset(run_sql('SELECT id FROM bibrec ORDER BY id'))
citations_fun = get_citations_fun(algorithm)
write_message('using %s' % citations_fun.__name__)
if algorithm == 'friends':
# We only needs this table for the friends algorithm or assimilated
# Fill intermediary tables
for index, recid in enumerate(all_ids):
if index % 1000 == 0:
msg = 'intermediate %d/%d' % (index, len(all_ids))
task_update_progress(msg)
write_message(msg)
task_sleep_now_if_required()
update_self_cites_tables(recid, config, tags)
# Fill self-cites table
for index, recid in enumerate(all_ids):
if index % 1000 == 0:
msg = 'final %d/%d' % (index, len(all_ids))
task_update_progress(msg)
write_message(msg)
task_sleep_now_if_required()
compute_and_store_self_citations(recid,
tags,
citations_fun,
selfcites_dic)
intoDB(selfcites_dic, begin_date, rank_method_code)
store_weights_cache(selfcites_dic)
def process_updates(rank_method_code):
"""
This is what gets executed first when the task is started.
It handles the --rebuild option. If that option is not specified
we fall back to the process_one()
"""
write_message("Running rank method: %s" % rank_method_code, verbose=0)
selfcites_config = read_configuration(rank_method_code)
config = {
'algorithm': selfcites_config.get(rank_method_code, "algorithm"),
'friends_threshold': selfcites_config.get(rank_method_code, "friends_threshold")
}
quick = task_get_option("quick") != "no"
if not quick:
return rebuild_tables(rank_method_code, config)
tags = get_authors_tags()
recids, end_date = fetch_concerned_records(rank_method_code,
task_get_option("id"))
citations_fun = get_citations_fun(config['algorithm'])
weights = fromDB(rank_method_code)
write_message("recids %s" % str(recids))
total = len(recids)
for count, recid in enumerate(recids):
task_sleep_now_if_required(can_stop_too=True)
msg = "Extracting for %s (%d/%d)" % (recid, count + 1, total)
task_update_progress(msg)
write_message(msg)
process_one(recid, tags, citations_fun, weights)
intoDB(weights, end_date, rank_method_code)
store_weights_cache(weights)
write_message("Complete")
return True
def process_updates(rank_method_code):
"""
This is what gets executed first when the task is started.
It handles the --rebuild option. If that option is not specified
we fall back to the process_one()
"""
write_message("Running rank method: %s" % rank_method_code, verbose=0)
selfcites_config = read_configuration(rank_method_code)
config = {
'algorithm': selfcites_config.get(rank_method_code, "algorithm"),
'friends_threshold': selfcites_config.get(rank_method_code, "friends_threshold")
}
quick = task_get_option("quick") != "no"
if not quick:
return rebuild_tables(rank_method_code, config)
tags = get_authors_tags()
recids, end_date = fetch_concerned_records(rank_method_code,
task_get_option("id"))
citations_fun = get_citations_fun(config['algorithm'])
weights = fromDB(rank_method_code)
write_message("recids %s" % str(recids))
total = len(recids)
for count, recid in enumerate(recids):
task_sleep_now_if_required(can_stop_too=True)
msg = "Extracting for %s (%d/%d)" % (recid, count + 1, total)
task_update_progress(msg)
write_message(msg)
process_one(recid, tags, citations_fun, weights)
intoDB(weights, end_date, rank_method_code)
store_weights_cache(weights)
write_message("Complete")
return True
