ModuleNotFoundError: No module named 'hook'

Olá! Mesmo seguinto a sugestão na aula de inserir import sys e sys.path.append("airflowalura") sigo tendo o seguinte erro:

(venv) user@user:~/Documentos/airflowalura$ python3 operators/twitter_operator.py
Traceback (most recent call last):
  File "/home/bruna/Documentos/airflowalura/operators/twitter_operator.py", line 4, in <module>
    from hook.twitter_hook import TwitterHook
ModuleNotFoundError: No module named 'hook'

Meu código para o twitter_operator.py:

import sys 
sys.path.append("airflowalura")
from airflow.models import BaseOperator, DAG, TaskInstance
from hook.twitter_hook import TwitterHook
import json
from datetime import datetime, timedelta

class TwitterOperator(BaseOperator):
    
    def __init__(self, end_time, start_time, query, **kwargs):
        self.end_time = end_time
        self.start_time = start_time
        super().__init__(**kwargs)

    def execute(self, context):
        end_time = self.end_time
        start_time = self.start_time
        query = self.query

        with open("extract_twitter.json", "w") as output_file:
            for pg in TwitterHook(end_time, start_time, query).run():
                json.dump(pg, output_file)
                output_file.write("\n")


if __name__ == "__main__":
    TIMESTAMP_FORMAT = "%Y-%m-%dT%H:%M:%S.00Z"

    end_time = datetime.now().strftime(TIMESTAMP_FORMAT)
    start_time = (datetime.now() + timedelta(-1)).date().strftime(TIMESTAMP_FORMAT)
    query = "data science"

    with DAG(dag_id = "TwitterTest", start_date = datetime.now()) as dag:
        to = TwitterOperator(query=query, start_time=start_time, end_time=end_time, task_id="test_run")
        ti = TaskInstance(task=to)
        to.execute(ti.task_id)
        

Meu código para o twitter_hook.py:

from airflow.providers.http.hooks.http import HttpHook
import requests
from datetime import datetime, timedelta
import json

class TwitterHook(HttpHook):

    def __init__(self, end_time, start_time, query, conn_id=None):
        self.end_time = end_time
        self.start_time = start_time
        self.query = query
        self.conn_id = conn_id or "twitter_default"
        super().__init__(http_conn_id=self.conn_id)

    def create_url(self):
    
        TIMESTAMP_FORMAT = "%Y-%m-%dT%H:%M:%S.00Z"

        end_time = self.end_time
        start_time = self.start_time
        query = "data science"

        tweet_fields = "tweet.fields=author_id,conversation_id,created_at,id,in_reply_to_user_id,public_metrics,lang,text"
        user_fields = "expansions=author_id&user.fields=id,name,username,created_at"

        url_raw = f"{self.base_url}/2/tweets/search/recent?query={query}&{tweet_fields}&{user_fields}&start_time={start_time}&end_time={end_time}"

        return url_raw
    
    def connect_to_endpoint(self, url, session):
        request = requests.Request("GET", url)
        prep = session.prepare_request(request)
        self.log.info(f"URL: {url}")
        return self.run_and_check(session, prep, {})
    
    def paginate(self, url_raw, session):
        lista_json_response = []
        #imprimir json
        response = self.connect_to_endpoint(url_raw, session)
        json_response = response.json()
        lista_json_response.append(json_response)
        contador = 1

        while "next_token" in json_response.get("meta",{}) and contador<100:
            next_token = json_response['meta']['next_token']
            url = f"{url_raw}&next_token={next_token}"
            response = self.connect_to_endpoint(url, session)
            json_response = response.json()
            lista_json_response.append(json_response)
            contador += 1

        return lista_json_response

    def run(self):
        session = self.get_conn()
        url_raw = self.create_url()

        return self.paginate(url_raw, session)
    
if __name__ == "__main__":
    TIMESTAMP_FORMAT = "%Y-%m-%dT%H:%M:%S.00Z"

    end_time = datetime.now().strftime(TIMESTAMP_FORMAT)
    start_time = (datetime.now() + timedelta(-1)).date().strftime(TIMESTAMP_FORMAT)
    query = "data science"

    for pg in TwitterHook(end_time, start_time, query).run():
        print(json.dumps(pg, indent=4, sort_keys=True))

E print da minha estrutura de pastas: