import typing as t import pymongo import pymongo.collection import contextlib import bson import logging import random from .config import MONGO_HOST, MONGO_PORT, WORKING_SET_SIZE, DATA_SET_SIZE log = logging.getLogger(__name__) class Review(t.TypedDict): _id: bson.ObjectId reviewerID: str asin: str reviewerName: str helpful: tuple[int, int] reviewText: str overall: float summary: str unixReviewTime: int reviewTime: str @contextlib.contextmanager def mongo_client_from_config() -> t.ContextManager[pymongo.MongoClient]: """ Create a new MongoDB client and yield it. """ log.debug("Opening connection to MongoDB...") client = pymongo.MongoClient( host=MONGO_HOST.__wrapped__, port=MONGO_PORT.__wrapped__, ) log.info("Opened connection to MongoDB: %s", client) yield client log.info("Closing connection to MongoDB: %s", client) client.close() log.debug("Closed connection to MongoDB!") @contextlib.contextmanager def mongo_reviews_collection_from_config() -> pymongo.collection.Collection[Review]: """ Create a new MongoDB client, access the ``reviews`` collection in the ``reviews`` database, and yield it. """ with mongo_client_from_config() as db: log.debug("Accessing the reviews collection...") collection = db.reviews.reviews log.debug("Collection accessed successfully: %s", collection) yield collection def sample_reviews(reviews: pymongo.collection.Collection, amount: int) -> t.Iterable[Review]: """ Get ``amount`` random reviews from the ``reviews`` collection. """ log.debug("Getting a sample of %d reviews...", amount) return reviews.aggregate([ {"$limit": WORKING_SET_SIZE.__wrapped__}, {"$sample": {"size": amount}}, ]) def sample_reviews_by_rating(reviews: pymongo.collection.Collection, rating: float, amount: int) -> t.Iterable[Review]: """ Get ``amount`` random reviews with ``rating`` stars from the ``reviews`` collection. """ log.debug("Getting a sample of %d reviews with %d stars...", amount, rating) return reviews.aggregate([ {"$limit": WORKING_SET_SIZE.__wrapped__}, {"$match": {"overall": rating}}, {"$sample": {"size": amount}}, ]) def get_reviews_dataset_polar(collection: pymongo.collection.Collection, amount: int) -> list[Review]: """ Get a list of shuffled 1-star and 5-star reviews. """ log.info("Building dataset with %d polar reviews...", amount * 2) # Sample the required reviews positive = sample_reviews_by_rating(collection, rating=5.0, amount=amount) negative = sample_reviews_by_rating(collection, rating=1.0, amount=amount) # Randomness here does not matter, so just merge the lists both = [*positive, *negative] # Shuffle the dataset, just in case it affects the performance # TODO: does it actually? random.shuffle(both) return both def get_reviews_dataset_uniform(collection: pymongo.collection.Collection, amount: int) -> list[Review]: """ Get a list of shuffled reviews of any rating. """ log.info("Building dataset with %d uniform reviews...", amount * 5) # Sample the required reviews terrible = sample_reviews_by_rating(collection, rating=1.0, amount=amount) negative = sample_reviews_by_rating(collection, rating=2.0, amount=amount) mixed = sample_reviews_by_rating(collection, rating=3.0, amount=amount) positive = sample_reviews_by_rating(collection, rating=4.0, amount=amount) great = sample_reviews_by_rating(collection, rating=5.0, amount=amount) # Randomness here does not matter, so just merge the lists full = [*terrible, *negative, *mixed, *positive, *great] # Shuffle the dataset, just in case it affects the performance # TODO: does it actually? random.shuffle(full) return full __all__ = ( "Review", "mongo_client_from_config", "mongo_reviews_collection_from_config", "sample_reviews", "sample_reviews_by_rating", "get_reviews_dataset_polar", )