Basic Examples

This page shows basic examples of common aggregation patterns using Mongo Aggro.

Filtering and Sorting

Get Active Users Sorted by Date

from mongo_aggro import Pipeline, Match, Sort, Limit, DESCENDING

pipeline = Pipeline([
    Match(query={"status": "active"}),
    Sort(fields={"createdAt": DESCENDING}),
    Limit(count=100),
])

# Pass pipeline directly - no to_list() needed!
results = collection.aggregate(pipeline)

Filter with Multiple Conditions

from mongo_aggro import Pipeline, Match, Project

pipeline = Pipeline([
    Match(query={
        "status": "active",
        "age": {"$gte": 18, "$lte": 65},
        "country": {"$in": ["US", "UK", "CA"]},
    }),
    Project(fields={
        "_id": 0,
        "name": 1,
        "email": 1,
        "country": 1,
    }),
])

Grouping and Aggregation

Count by Category

from mongo_aggro import Pipeline, Group, Sort, DESCENDING

pipeline = Pipeline([
    Group(id="$category", accumulators={"count": {"$sum": 1}}),
    Sort(fields={"count": DESCENDING}),
])

Sales Summary by Product

from mongo_aggro import (
    Pipeline, Match, Group, Sort,
    Sum, Avg, merge_accumulators, DESCENDING
)

pipeline = Pipeline([
    Match(query={"status": "completed"}),
    Group(
        id="$productId",
        accumulators=merge_accumulators(
            Sum(name="totalSales", field="amount"),
            Sum(name="quantity", field="qty"),
            Avg(name="avgPrice", field="price"),
        )
    ),
    Sort(fields={"totalSales": DESCENDING}),
])

Group by Multiple Fields

from mongo_aggro import Pipeline, Group, Sort, Sum, DESCENDING

pipeline = Pipeline([
    Group(
        id={"year": "$year", "month": "$month"},
        accumulators={"total": {"$sum": "$amount"}}
    ),
    Sort(fields={"_id.year": DESCENDING, "_id.month": DESCENDING}),
])

Working with Arrays

Unwind and Count

from mongo_aggro import Pipeline, Unwind, Group, Sort, DESCENDING

pipeline = Pipeline([
    Unwind(path="tags"),
    Group(id="$tags", accumulators={"count": {"$sum": 1}}),
    Sort(fields={"count": DESCENDING}),
])

Flatten Nested Arrays

from mongo_aggro import Pipeline, Match, Unwind, Project

pipeline = Pipeline([
    Match(query={"status": "active"}),
    Unwind(path="items"),
    Project(fields={
        "orderId": "$_id",
        "itemName": "$items.name",
        "itemPrice": "$items.price",
    }),
])

Pagination

Basic Pagination

from mongo_aggro import Pipeline, Match, Sort, Skip, Limit, DESCENDING

page = 2
page_size = 20

pipeline = Pipeline([
    Match(query={"status": "active"}),
    Sort(fields={"createdAt": DESCENDING}),
    Skip(count=(page - 1) * page_size),
    Limit(count=page_size),
])

Pagination with Total Count

from mongo_aggro import (
    Pipeline, Match, Facet, Sort, Skip, Limit, Count, DESCENDING
)

page = 2
page_size = 20

pipeline = Pipeline([
    Match(query={"status": "active"}),
    Facet(pipelines={
        "data": Pipeline([
            Sort(fields={"createdAt": DESCENDING}),
            Skip(count=(page - 1) * page_size),
            Limit(count=page_size),
        ]),
        "total": Pipeline([
            Count(field="count"),
        ]),
    }),
])

Field Transformation

Rename Fields

from mongo_aggro import Pipeline, Project

pipeline = Pipeline([
    Project(fields={
        "_id": 0,
        "userId": "$_id",
        "fullName": "$name",
        "emailAddress": "$email",
    }),
])

Computed Fields

from mongo_aggro import Pipeline, AddFields, Project

pipeline = Pipeline([
    AddFields(fields={
        "totalPrice": {"$multiply": ["$price", "$quantity"]},
        "discountedPrice": {
            "$subtract": [
                {"$multiply": ["$price", "$quantity"]},
                "$discount"
            ]
        },
    }),
    Project(fields={
        "name": 1,
        "totalPrice": 1,
        "discountedPrice": 1,
    }),
])

Conditional Logic

Using $cond

from mongo_aggro import Pipeline, AddFields

pipeline = Pipeline([
    AddFields(fields={
        "status": {
            "$cond": {
                "if": {"$gte": ["$score", 70]},
                "then": "pass",
                "else": "fail"
            }
        }
    }),
])

Using $switch

from mongo_aggro import Pipeline, AddFields

pipeline = Pipeline([
    AddFields(fields={
        "grade": {
            "$switch": {
                "branches": [
                    {"case": {"$gte": ["$score", 90]}, "then": "A"},
                    {"case": {"$gte": ["$score", 80]}, "then": "B"},
                    {"case": {"$gte": ["$score", 70]}, "then": "C"},
                    {"case": {"$gte": ["$score", 60]}, "then": "D"},
                ],
                "default": "F"
            }
        }
    }),
])