cluster.txes() is taking too long to execute

[0xrajath]

cluster.txes() is taking too long and memory is eventually running out in the AWS instance.
Is there a more optimized way to get all the transactions that a cluster is involved in?

Right now I'm doing the following:

import blocksci
import collections
import pandas as pd
import numpy as np
import blocksci.cluster_python

chain = blocksci.Blockchain("/home/ubuntu/bitcoin")
cm = blocksci.cluster_python.ClusterManager("/home/ubuntu/bitcoin/clusters", chain)
address = chain.address_from_string("1BTCDiceLs79syendE1DM1XCaHcKkzBNnP")
cluster = cm.cluster_with_address(address)
#The below line is taking too long to execute
cluster_txns_list = cluster.txes()

[hkalodner]

The cluster that your trying to list transactions from is a super cluster which contains over 200 millions addresses which is why you running into problems with this. You can get the number of addresses in a cluster by calling len(cluster) Improving the clustering module is on our todo list, but for now this remains a problem. At some point soon I’m planning on changing calls like cluster.txes() to return iterators rather than lists which will at least make it possible to iterate over large groupings like this.

[hkalodner]

This situation has been fairly resolved as of v0.5. cluster.txes() still has the same problem which has not been directly fixed. However cluster.outs() returns a OutputIterator which allows you to iterate over all the outputs linked to a cluster without allocating a list of all of them at once. Having cluster.txes() return an iterator rather than a list is infeasible.