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bda-6-steffo/unimore_bda_6/database/queries.py

135 lines
4.2 KiB
Python

import logging
import pymongo
import typing as t
from ..config import WORKING_SET_SIZE
from .datatypes import TextReview
log = logging.getLogger(__name__)
SampleFunc = t.Callable[[pymongo.collection.Collection, int], t.Iterator[TextReview]]
def sample_reviews(collection: pymongo.collection.Collection, amount: int) -> t.Iterator[TextReview]:
"""
Get ``amount`` random reviews from the ``reviews`` collection.
"""
log.debug("Getting a sample of %d reviews...", amount)
cursor = collection.aggregate([
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$sample": {"size": amount}},
])
cursor = map(TextReview.from_mongoreview, cursor)
return cursor
def sample_reviews_by_rating(collection: pymongo.collection.Collection, rating: float, amount: int) -> t.Iterator[TextReview]:
"""
Get ``amount`` random reviews with ``rating`` stars from the ``reviews`` collection.
"""
log.debug("Getting a sample of %d reviews with %d stars...", amount, rating)
cursor = collection.aggregate([
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": rating}},
{"$sample": {"size": amount}},
])
return cursor
def sample_reviews_polar(collection: pymongo.collection.Collection, amount: int) -> t.Iterator[TextReview]:
category_amount = amount // 2
log.debug("Getting a sample of %d polar reviews...", category_amount * 2)
cursor = collection.aggregate([
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": 1.0}},
{"$sample": {"size": category_amount}},
{"$unionWith": {
"coll": collection.name,
"pipeline": [
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": 5.0}},
{"$sample": {"size": category_amount}},
],
}},
{"$addFields": {
"sortKey": {"$rand": {}},
}},
{"$sort": {
"sortKey": 1,
}}
])
cursor = map(TextReview.from_mongoreview, cursor)
return cursor
def sample_reviews_varied(collection: pymongo.collection.Collection, amount: int) -> t.Iterator[TextReview]:
category_amount = amount // 5
log.debug("Getting a sample of %d varied reviews...", category_amount * 5)
cursor = collection.aggregate([
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": 1.0}},
{"$sample": {"size": category_amount}},
{"$unionWith": {
"coll": collection.name,
"pipeline": [
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": 2.0}},
{"$sample": {"size": category_amount}},
{"$unionWith": {
"coll": collection.name,
"pipeline": [
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": 3.0}},
{"$sample": {"size": category_amount}},
{"$unionWith": {
"coll": collection.name,
"pipeline": [
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": 4.0}},
{"$sample": {"size": category_amount}},
{"$unionWith": {
"coll": collection.name,
"pipeline": [
{"$limit": WORKING_SET_SIZE.__wrapped__},
{"$match": {"overall": 5.0}},
{"$sample": {"size": category_amount}},
],
}}
],
}}
],
}}
],
}},
{"$addFields": {
"sortKey": {"$rand": {}},
}},
{"$sort": {
"sortKey": 1,
}}
])
cursor = map(TextReview.from_mongoreview, cursor)
return cursor
__all__ = (
"SampleFunc",
"sample_reviews",
"sample_reviews_by_rating",
"sample_reviews_polar",
"sample_reviews_varied",
)