Ejemplo n.º 1
0
def simulation_a1(n):
    init_tx = simulator.init()
    process(init_tx)

    create_tx = simulator.create((init_tx['transaction']['outputs'][0],), None, (str(n),))
    process(create_tx)

    outputs = create_tx['transaction']['outputs']
    transactions = [simulator.consume((output,)) for output in outputs]
    process_many(transactions)
Ejemplo n.º 2
0
def simulation_a3(n):
    init_tx = simulator.init()
    dump(init_tx)

    create_tx = simulator.create((init_tx['transaction']['outputs'][0],), None, (str(n),))
    dump(create_tx)

    outputs = create_tx['transaction']['outputs']
    transactions = [simulator.consume((output,)) for output in outputs]
    dump_many(transactions)
Ejemplo n.º 3
0
def simulation_batched(n,
                       inputs_per_tx,
                       batch_size=100,
                       batch_sleep=2,
                       nonce=True,
                       shards_per_tx=None,
                       num_shards=None,
                       co=False):
    init_tx = simulator.init()
    process(init_tx)

    parameters = [
        str(n * inputs_per_tx),
    ]
    if nonce:
        parameters.append(str(random.randint(1, 1000000)))
    create_tx = simulator.create((init_tx['transaction']['outputs'][0], ),
                                 None, parameters)
    process(create_tx)
    time.sleep(5)

    outputs = create_tx['transaction']['outputs']

    if shards_per_tx is not None:
        outputs_map = {}
        for shard in range(num_shards):
            outputs_map[shard] = []
        for output in outputs:
            outputs_map[map_object_id_to_shard(
                num_shards, output.object_id)].append(output)

    transactions = []
    try:
        for i in range(0, len(outputs), inputs_per_tx):
            if shards_per_tx is not None:
                rand = random.randint(0, num_shards - shards_per_tx)
            objects = []
            for j in range(inputs_per_tx):
                if shards_per_tx is None:
                    objects.append(outputs[i + j])
                else:
                    shard_id = j % shards_per_tx
                    shard_id = shard_id + rand
                    objects.append(outputs_map[shard_id].pop())
            if co:
                transactions.append(simulator.consume_co(objects))
            else:
                transactions.append(simulator.consume(objects))
    except IndexError:
        pass

    for i in range(0, len(transactions), batch_size):
        dump_many(transactions[i:i + batch_size])
        time.sleep(batch_sleep)
Ejemplo n.º 4
0
def simulation_b2(n, inputs_per_tx):
    init_tx = simulator.init()
    process(init_tx)

    create_tx = simulator.create((init_tx['transaction']['outputs'][0],), None, (str(n),))
    process(create_tx)

    outputs = create_tx['transaction']['outputs']

    transactions = []
    for i in range(0, len(outputs), inputs_per_tx):
        objects = []
        for j in range(inputs_per_tx):
            objects.append(outputs[i+j])
        transactions.append(simulator.consume(objects))

    dump_many(transactions)
Ejemplo n.º 5
0
def simulation_batched(n, inputs_per_tx, batch_size=100, batch_sleep=2, nonce=True):
    init_tx = simulator.init()
    process(init_tx)

    parameters = [str(n*inputs_per_tx),]
    if nonce:
        parameters.append(str(random.randint(1,1000000)))
    create_tx = simulator.create((init_tx['transaction']['outputs'][0],), None, parameters)
    process(create_tx)
    time.sleep(5)

    outputs = create_tx['transaction']['outputs']

    transactions = []
    for i in range(0, len(outputs), inputs_per_tx):
        objects = []
        for j in range(inputs_per_tx):
            objects.append(outputs[i+j])
        transactions.append(simulator.consume(objects))

    for i in range(0, len(transactions), batch_size):
        dump_many(transactions[i:i+batch_size])
        time.sleep(batch_sleep)