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

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