continue
rshares = vote["rshares"]
if rshares < 50000000:
continue
rshares = rshares * upvote_multiplier * upvote_multiplier_adjusted
member_data[
vote["voter"]]["earned_rshares"] += rshares
member_data[
vote["voter"]]["curation_rshares"] += rshares
member_data[
vote["voter"]]["balance_rshares"] += rshares
comment_rshares += rshares
accounts_data[
account["name"]]["last_paid_comment"] = last_paid_comment
accounts_data[
account["name"]]["last_paid_post"] = last_paid_post
print("%d new curation rshares for posts" % post_rshares)
print("%d new curation rshares for comments" % comment_rshares)
print("write member database")
memberStorage.db = dataset.connect(databaseConnector2)
member_data_list = []
for m in member_data:
member_data_list.append(member_data[m])
memberStorage.add_batch(member_data_list)
member_data_list = []
for acc in accounts_data:
accountStorage.update(accounts_data[acc])
print("update curation rshares script run %.2f s" %
(time.time() - start_prep_time))
print("\n---------------------\n")
percentage_done = (block_num - start_block) / (end_block - start_block) * 100
print("Block %d -- Datetime %s -- %.2f %% finished" % (block_num, op["timestamp"], percentage_done))
running_hours = (end_block - block_num) * time_for_blocks / block_diff_for_db_storage / 60 / 60
print("Duration for %d blocks: %.2f s (%.3f s per block) -- %.2f hours to go" % (block_diff_for_db_storage, time_for_blocks, time_for_blocks / block_diff_for_db_storage, running_hours))
print("%d new comments, %d new votes" % (comment_cnt, vote_cnt))
start_time = time.time()
comment_cnt = 0
vote_cnt = 0
last_block_num = block_num
db = dataset.connect(databaseConnector)
db2 = dataset.connect(databaseConnector2)
accountTrx.db = db
curationOptimTrx.db = db
memberStorage.db = db2
accountTrx.add_batch(db_data)
db_data = []
if len(updated_member_data) > 0:
memberStorage.add_batch(updated_member_data)
updated_member_data = []
if len(curation_vote_list) > 0:
curationOptimTrx.add_batch(curation_vote_list)
curation_vote_list = []
cnt += 1
if len(db_data) > 0:
print(op["timestamp"])
db = dataset.connect(databaseConnector)
