home / skills / bobmatnyc / claude-mpm-skills / ecto-patterns
This skill helps you apply robust Ecto patterns in Phoenix/Elixir apps, ensuring safe schemas, migrations, queries, and multi-transaction workflows.
npx playbooks add skill bobmatnyc/claude-mpm-skills --skill ecto-patternsReview the files below or copy the command above to add this skill to your agents.
---
name: ecto-patterns
description: Ecto patterns for Phoenix/Elixir apps. Covers schemas, changesets, migrations, queries, Ecto.Multi, transactions, constraints, associations, pagination, tenant partitioning, performance, and testing.
version: 1.0.0
category: toolchain
author: Claude MPM Team
license: MIT
progressive_disclosure:
entry_point:
summary: "Ecto schemas/changesets, migrations, queries, transactions, constraints, pagination, tenancy, and performance for Phoenix apps."
when_to_use:
- "Designing schemas and changesets with validation/constraints"
- "Running migrations safely (DDL ordering, locks) and managing data migrations"
- "Executing transactional flows with Ecto.Multi"
- "Implementing pagination, preloading, and multi-tenant partitioning"
quick_start:
- "mix ecto.create && mix ecto.migrate"
- "Define schemas + changesets; enforce DB constraints (unique/foreign keys)"
- "Use Repo.transaction / Ecto.Multi for multi-step writes"
- "Preload associations; paginate with limit/offset or cursor libs (Scrivener/Flop)"
token_estimate:
entry: 170
full: 5400
---
# Ecto Patterns for Phoenix/Elixir
Ecto is the data layer for Phoenix applications: schemas, changesets, queries, migrations, and transactions. Good Ecto practice keeps domain logic in contexts, enforces constraints in the database, and uses transactions for multi-step workflows.
## Schemas and Changesets
```elixir
defmodule MyApp.Accounts.User do
use Ecto.Schema
import Ecto.Changeset
schema "users" do
field :email, :string
field :hashed_password, :string
field :confirmed_at, :naive_datetime
has_many :memberships, MyApp.Orgs.Membership
timestamps()
end
def registration_changeset(user, attrs) do
user
|> cast(attrs, [:email, :password])
|> validate_required([:email, :password])
|> validate_format(:email, ~r/@/)
|> validate_length(:password, min: 12)
|> unique_constraint(:email)
|> hash_password()
end
defp hash_password(%{valid?: true} = cs),
do: put_change(cs, :hashed_password, Argon2.hash_pwd_salt(get_change(cs, :password)))
defp hash_password(cs), do: cs
end
```
**Guidelines**
- Keep casting/validation in changesets; keep business logic in contexts.
- Always pair validation with DB constraints (`unique_constraint`, `foreign_key_constraint`).
- Use `changeset/2` for updates; avoid mass assigning without casting.
## Migrations
```elixir
def change do
create table(:users) do
add :email, :citext, null: false
add :hashed_password, :string, null: false
add :confirmed_at, :naive_datetime
timestamps()
end
create unique_index(:users, [:email])
end
```
**Safe migration tips**
- Prefer additive changes: add columns nullable, backfill, then enforce null: false.
- For large tables: use `concurrently: true` for indexes; disable in `change` and wrap in `up/down` for Postgres.
- Data migrations belong in separate modules called from `mix ecto.migrate` via `execute/1` or in distinct scripts; ensure idempotence.
- Coordinate locks: avoid long transactions; break migrations into small steps.
## Queries and Preloads
```elixir
import Ecto.Query
def list_users(opts \\ %{}) do
base =
from u in MyApp.Accounts.User,
preload: [:memberships],
order_by: [desc: u.inserted_at]
Repo.all(apply_pagination(base, opts))
end
defp apply_pagination(query, %{limit: limit, offset: offset}),
do: query |> limit(^limit) |> offset(^offset)
defp apply_pagination(query, _), do: query
```
**Patterns**
- Use `preload` rather than calling Repo in loops; prefer `Repo.preload/2` after fetching.
- Use `select` to avoid loading large blobs.
- For concurrency, use `Repo.transaction` with `lock: "FOR UPDATE"` in queries that need row-level locks.
## Transactions and Ecto.Multi
```elixir
alias Ecto.Multi
def onboard_user(attrs) do
Multi.new()
|> Multi.insert(:user, User.registration_changeset(%User{}, attrs))
|> Multi.insert(:org, fn %{user: user} ->
Org.changeset(%Org{}, %{owner_id: user.id, name: attrs["org_name"]})
end)
|> Multi.run(:welcome, fn _repo, %{user: user} ->
MyApp.Mailer.deliver_welcome(user)
{:ok, :sent}
end)
|> Repo.transaction()
end
```
**Guidelines**
- Prefer `Multi.run/3` for side effects that can fail; return `{:ok, value}` or `{:error, reason}`.
- Use `Multi.update_all` for batch updates; include `where` guards to prevent unbounded writes.
- Propagate errors upward; translate them in controllers/LiveViews.
## Associations and Constraints
- Use `on_replace: :delete`/`:nilify` to control nested changes.
- Define `foreign_key_constraint/3` and `unique_constraint/3` in changesets to surface DB errors cleanly.
- For many-to-many, prefer join schema (`has_many :memberships`) instead of automatic `many_to_many` when you need metadata.
## Pagination and Filtering
- Offset/limit for small datasets; cursor-based for large lists (`Scrivener`, `Flop`, `Paginator`).
- Normalize filters in contexts; avoid letting controllers build queries directly.
- Add composite indexes to match filter columns; verify with `EXPLAIN ANALYZE`.
## Multi-Tenancy Patterns
- **Prefix-based**: Postgres schemas per tenant (`put_source/2` with `prefix:`) — good isolation, needs per-tenant migrations.
- **Row-based**: `tenant_id` column + row filters — simpler migrations; add partial indexes per tenant when large.
- Always scope queries by tenant in contexts; consider using policies/guards to enforce.
## Performance and Ops
- Use `Repo.stream` for large exports; wrap in `Repo.transaction`.
- Cache hot reads with ETS/Cachex; invalidate on writes.
- Watch query counts in LiveView/Channels; preload before rendering to avoid N+1.
- Telemetry: `OpentelemetryEcto` exports query timings; add DB connection pool metrics.
## Testing
```elixir
use MyApp.DataCase, async: true
test "registration changeset validates email" do
changeset = User.registration_changeset(%User{}, %{email: "bad", password: "secretsecret"})
refute changeset.valid?
assert %{email: ["has invalid format"]} = errors_on(changeset)
end
```
- `DataCase` sets up sandboxed DB; keep tests async unless transactions conflict.
- Use factories/fixtures in `test/support` to build valid structs quickly.
- For migrations, add regression tests for constraints (unique/index-backed constraints).
## Common Pitfalls
- Running risky DDL in a single migration step (avoid locks; break apart).
- Skipping DB constraints and relying only on changesets.
- Querying associations in loops instead of preloading.
- Missing transactions for multi-step writes (partial state on failure).
- Forgetting tenant scoping on read/write in multi-tenant setups.
This skill provides a curated set of Ecto patterns for Phoenix/Elixir apps covering schemas, changesets, migrations, queries, transactions, associations, pagination, multi-tenancy, performance, and testing. It distills practical guidelines and idiomatic examples to help teams build resilient data layers. Use it to standardize data access, enforce constraints, and design safe migrations and workflows.
The skill inspects common Ecto workflows and recommends patterns: where to place validation, how to pair changesets with database constraints, and when to use Ecto.Multi or Repo.transaction for multi-step operations. It highlights migration best practices, query/preload strategies, tenant partitioning options, performance tactics (streaming, caching, telemetry), and testing approaches to keep DB work safe and observable. Examples demonstrate minimal, production-ready snippets you can adopt directly.
When should I prefer row-based vs prefix-based multi-tenancy?
Row-based tenancy is simpler for deployments and migrations; prefix/schema-based gives stronger isolation but requires per-tenant migration management. Choose based on isolation needs and operational complexity.
How do I avoid long-running locks during migrations on large tables?
Make additive changes, perform backfills off-line or in small batches, create indexes concurrently, and split risky DDL into multiple up/down steps to minimize lock durations.