<jupyter_start><jupyter_text>Create 5000 messages on each queue<jupyter_code>for i in tqdm(range(0, 500)):
    sqs.send_message_batch(QueueUrl=queue_url, Entries=[
        {
            'Id': f'Regular{i}_{j}',
            'MessageBody': f'Hi regular queue {i}/{j}'
        } for j in range(0, 10)
    ])
# Send messages to the FIFO queue with random groups so we can have more than one in flight at a time
for i in tqdm(range(0, 500)):
    sqs.send_message_batch(QueueUrl=fifo_queue_url, Entries=[
        {
            'Id': f'Regular{i}_{j}',
            'MessageBody': f'Hi regular queue {i}/{j}',
            'MessageGroupId': random_id(),
            'MessageDeduplicationId': f'{i}_{j}'
        } for j in range(0, 10)
    ])<jupyter_output><empty_output><jupyter_text>Receive MessagesUse a visibility timeout to ensure messages are regarded as 'in-flight', triggering the threshold forinflight messages percent for the test project.<jupyter_code>sqs.receive_message(QueueUrl=queue_url, VisibilityTimeout=10)
message_ids_regular = []
sqs.receive_message(QueueUrl=queue_url, VisibilityTimeout=10)
for _ in tqdm(range(0, 1201)):
    msg_id = sqs.receive_message(QueueUrl=queue_url, VisibilityTimeout=1000)['Messages'][0]['MessageId']
    message_ids_regular.append(msg_id)
sqs.receive_message(QueueUrl=fifo_queue_url, VisibilityTimeout=10)
for _ in tqdm(range(0, 181)):
    resp = sqs.receive_message(QueueUrl=fifo_queue_url, VisibilityTimeout=1000)
    msg_id = resp['Messages'][0]['MessageId']
    message_ids_fifo.append(msg_id)<jupyter_output><empty_output><jupyter_text>Clean up queues<jupyter_code>for url in tqdm([queue_url, fifo_queue_url]):
    sqs.purge_queue(QueueUrl=url)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12223515715948778, 'fraction_numerical': 0.025029103608847497, 'mean_word_length': 4.886986301369863, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '505251', 'license': 'Apache-2.0', 'n_tokens_mistral': 630, 'n_tokens_neox': 591, 'n_words': 121, 'path': 'testing/trigger_sqs.ipynb', 'repo_name': 'asionek/slic-watch', 'size': '1718'}