Skip to main content

Hasura-shape aggregations over Django querysets in Strawberry GraphQL — count, sum, avg, min, max, stddev, variance, array_agg + Odoo-grade group-by with timezone-correct date bucketing.

Project description

strawberry-django-aggregates

Hasura-shape aggregations over Django querysets in Strawberry GraphQL.

count · count_distinct · sum · avg · min · max · stddev · variance · bool_and · bool_or · array_agg · string_agg — composed with multi-level group_by, having filters, and ordering on aggregate aliases. Inspired by Hasura's <table>_aggregate, PostGraphile's pg-aggregates, and Odoo 18's _read_group. Built for strawberry-django over PostgreSQL and SQLite.

from decimal import Decimal
from datetime import datetime
from strawberry import auto
import strawberry, strawberry_django
from strawberry_django_aggregates import AggregateBuilder

from .models import Order

@strawberry_django.type(Order)
class OrderType:
    id: auto
    customer: "CustomerType"
    total: Decimal
    status: str
    created_at: datetime

# One call wires count/sum/avg/min/max + group_by + having into the schema:
order_aggs = AggregateBuilder(
    model=Order,
    aggregate_fields=["total"],
    group_by_fields=["customer", "status", "created_at"],
).build()

@strawberry.type
class Query:
    orders_aggregate = order_aggs.aggregate_field
    orders_group_by  = order_aggs.group_by_field

Generates a fully-typed GraphQL surface:

type Query {
  ordersAggregate(filter: OrderFilter): OrderAggregate!
  ordersGroupBy(
    filter:    OrderFilter
    groupBy:   [OrderGroupBySpec!]!
    having:    OrderHaving
    orderBy:   [OrderGroupOrder!]
    pagination: OffsetPagination
  ): OrderGroupedResult!
}

type OrderAggregate {
  count:           Int!
  countDistinct(field: OrderCountableField!): Int!
  sum:             OrderSumFields
  avg:             OrderAvgFields
  min:             OrderMinFields
  max:             OrderMaxFields
  stddev:          OrderStddevFields    # Postgres only
  variance:        OrderVarianceFields  # Postgres only
}

type OrderGrouped {
  key:   OrderGroupKey!   # composite — every requested groupBy field present
  count: Int!
  sum:   OrderSumFields
  # ... no recursive subgroups field — flat results
}

Features

  • Hasura-canonical schema shape. <Model>Aggregate { count, countDistinct, sum, avg, min, max, stddev, variance, boolAnd, boolOr, arrayAgg, stringAgg }.
  • Odoo-grade group-by. Multi-level via composite keys (flat result rows), dual date-granularity tracks (date_trunc returning DateTime AND date_part::int returning Int), timezone-correct bucketing.
  • HAVING with aggregate aliases. { countGt: 5, sumTotalGt: 1000 } — typed inputs generated per measure.
  • Ordering on aggregates. [{ field: "total:sum", direction: DESC }] — fail-loud on unknown terms (Odoo's pre-17 silent-drop bug avoided).
  • Standalone backend primitive. compute_aggregation(qs, group_by, aggregates, having, order_by, ...) is callable from any Python context — DRF view, Celery task, admin script, MCP tool — not just GraphQL resolvers.
  • Determinism. Type generation produces byte-identical SDL for the same inputs.
  • No magic. Every operator, every granularity, every type is whitelisted.

Non-goals

  • Cross-database aggregation. PostgreSQL + SQLite only. SQLite degrades gracefully on array_agg/string_agg/stddev/variance — those operators raise OperatorNotSupportedError at resolver entry.
  • Auto-traversal of one-to-many / many-to-many for measures. This is the silent row-multiplication footgun Odoo refuses to ship; we follow. array_agg is the explicit escape hatch.
  • Permission integration. The library expects a pre-scoped queryset — the caller has already applied accessible_by(user) or equivalent. This keeps the library compatible with django-guardian, django-rules, django-rebac (when shipped), or hand-rolled permission systems.

Status

Beta (v0.2.1). The schema shape, operator vocabulary, and compute_aggregation signature are stable for early adopters, but minor-level iteration is still expected before a 1.0 stability commitment — see docs/SPEC.md § 16. Runtime: Python 3.13, Django 6.0.

Documentation

  • Full contract: docs/SPEC.md — operator catalog, granularity tracks, HAVING semantics, ordering rules, timezone handling, and the Odoo-derived footgun audit.
  • Naming and wire vocabulary: docs/TERMINOLOGY.md
  • Contributor quality gate: CONTRIBUTING.md

License

BSD-3-Clause.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

strawberry_django_aggregates-0.2.1.tar.gz (124.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

strawberry_django_aggregates-0.2.1-py3-none-any.whl (88.1 kB view details)

Uploaded Python 3

File details

Details for the file strawberry_django_aggregates-0.2.1.tar.gz.

File metadata

File hashes

Hashes for strawberry_django_aggregates-0.2.1.tar.gz
Algorithm Hash digest
SHA256 dd33ca90c46cba62c70718fe168de35898249bba783a6a653130d74688ca8bb7
MD5 0b4fa01ad46a4d54050287a311de9f77
BLAKE2b-256 e63ba8785e03906940fdd9d5c9616d0fd85f50c6d32b0df324d2ace7f1e6dc14

See more details on using hashes here.

File details

Details for the file strawberry_django_aggregates-0.2.1-py3-none-any.whl.

File metadata

File hashes

Hashes for strawberry_django_aggregates-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 afd1d2478d50422a9fc34805ef3de38d3bb5bb49b541f162113278f4fcd77572
MD5 f5bf8d1784355fab0857b89924bb69f7
BLAKE2b-256 f510314379db0e554725cd067281baf50fc02d94ff83443776ceab97bc9148bd

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page