How to set up `timesteps_total` in the config in Python API? (RLlib)

Question

I just started playing with RLlib and I wanted to test offline DQN training on a CartPole. Thus, I generated the data as in the tutorial:

rllib train --run=PG --env=CartPole-v1 --config='{"output": "/tmp/cartpole-out", "output_max_file_size": 5000000}' --stop='{"timesteps_total": 100000}'

And then run offline the training via

rllib train --run=DQN --env=CartPole-v1 --config='{"input": "/tmp/cartpole-out","explore": false}' --stop='{"timesteps_total": 1000000}'

However, now I want to reproduce offline training using Python API and I get a little confused about timesteps_total. I have written the following code:

if __name__ == '__main__':
    config = (
        DQNConfig()
        .environment(env="CartPole-v1")
        .framework("torch")
        .offline_data(input_="/tmp/cartpole-out")
        .exploration(explore=False)
    )

    algo = config.build()
    for _ in tqdm(range(100)):
        algo.train()

but I am not sure how timesteps_total is related to the training loop with the above snippet. I looked inside AlgorithmConfig class, but I found that self.timesteps_per_iteration = DEPRECATED_VALUE. Thus, the question:

How to set up timesteps_total in the config in Python API?

Disclaimer: I asked ChatGPT about that, but it confidently gave me the wrong answer with a detailed explanation.