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)