dynamodb-toolbox-patterns
by giuseppe-trisciuoglio
Provides TypeScript patterns for DynamoDB-Toolbox v2 including schema/table/entity modeling, .build() command workflow, query/scan access patterns, batch and transaction operations, and single-table design with computed keys. Use when implementing type-safe DynamoDB access layers with DynamoDB-Toolbox v2 in TypeScript services or serverless applications.
安装
安装命令
git clone https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-typescript/skills/dynamodb-toolbox-patterns文档
DynamoDB-Toolbox v2 Patterns (TypeScript)
Overview
This skill provides practical TypeScript patterns for using DynamoDB-Toolbox v2 with AWS SDK v3 DocumentClient. It focuses on type-safe schema modeling, .build() command usage, and production-ready single-table design.
When to Use
- Defining DynamoDB tables and entities with strict TypeScript inference
- Modeling schemas with
item,string,number,list,set,map, andrecord - Implementing
GetItem,PutItem,UpdateItem,DeleteItemvia.build() - Building query and scan access paths with primary keys and GSIs
- Handling batch and transactional operations
- Designing single-table systems with computed keys and entity patterns
Instructions
- Start from access patterns: identify read/write queries first, then design keys.
- Create table + entity boundaries: one table, multiple entities if using single-table design.
- Define schemas with constraints: apply
.key(),.required(),.default(),.transform(),.link(). - Use
.build()commands everywhere: avoid ad-hoc command construction for consistency and type safety. - Add query/index coverage: validate GSI/LSI paths for each required access pattern.
- Use batch/transactions intentionally: batch for throughput, transactions for atomicity.
- Keep items evolvable: use optional fields, defaults, and derived attributes for schema evolution.
Examples
Install and Setup
npm install dynamodb-toolbox @aws-sdk/client-dynamodb @aws-sdk/lib-dynamodb
import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb';
import { Table } from 'dynamodb-toolbox/table';
import { Entity } from 'dynamodb-toolbox/entity';
import { item, string, number, list, map } from 'dynamodb-toolbox/schema';
const client = new DynamoDBClient({ region: process.env.AWS_REGION ?? 'eu-west-1' });
const documentClient = DynamoDBDocumentClient.from(client);
export const AppTable = new Table({
name: 'app-single-table',
partitionKey: { name: 'PK', type: 'string' },
sortKey: { name: 'SK', type: 'string' },
indexes: {
byType: { type: 'global', partitionKey: { name: 'GSI1PK', type: 'string' }, sortKey: { name: 'GSI1SK', type: 'string' } }
},
documentClient
});
Entity Schema with Modifiers and Complex Attributes
const now = () => new Date().toISOString();
export const UserEntity = new Entity({
name: 'User',
table: AppTable,
schema: item({
tenantId: string().required('always'),
userId: string().required('always'),
email: string().required('always').transform(input => input.toLowerCase()),
role: string().enum('admin', 'member').default('member'),
loginCount: number().default(0),
tags: list(string()).default([]),
profile: map({
displayName: string().optional(),
timezone: string().default('UTC')
}).default({ timezone: 'UTC' })
}),
computeKey: ({ tenantId, userId }) => ({
PK: `TENANT#${tenantId}`,
SK: `USER#${userId}`,
GSI1PK: `TENANT#${tenantId}#TYPE#USER`,
GSI1SK: `EMAIL#${userId}`
})
});
.build() CRUD Commands
import { PutItemCommand } from 'dynamodb-toolbox/entity/actions/put';
import { GetItemCommand } from 'dynamodb-toolbox/entity/actions/get';
import { UpdateItemCommand, $add } from 'dynamodb-toolbox/entity/actions/update';
import { DeleteItemCommand } from 'dynamodb-toolbox/entity/actions/delete';
await UserEntity.build(PutItemCommand)
.item({ tenantId: 't1', userId: 'u1', email: 'A@Example.com' })
.send();
const { Item } = await UserEntity.build(GetItemCommand)
.key({ tenantId: 't1', userId: 'u1' })
.send();
await UserEntity.build(UpdateItemCommand)
.item({ tenantId: 't1', userId: 'u1', loginCount: $add(1) })
.send();
await UserEntity.build(DeleteItemCommand)
.key({ tenantId: 't1', userId: 'u1' })
.send();
Query and Scan Patterns
import { QueryCommand } from 'dynamodb-toolbox/table/actions/query';
import { ScanCommand } from 'dynamodb-toolbox/table/actions/scan';
const byTenant = await AppTable.build(QueryCommand)
.query({
partition: `TENANT#t1`,
range: { beginsWith: 'USER#' }
})
.send();
const byTypeIndex = await AppTable.build(QueryCommand)
.query({
index: 'byType',
partition: 'TENANT#t1#TYPE#USER'
})
.options({ limit: 25 })
.send();
const scanned = await AppTable.build(ScanCommand)
.options({ limit: 100 })
.send();
Batch and Transaction Workflows
import { BatchWriteCommand } from 'dynamodb-toolbox/table/actions/batchWrite';
import { TransactWriteCommand } from 'dynamodb-toolbox/table/actions/transactWrite';
await AppTable.build(BatchWriteCommand)
.requests(
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u2', email: 'u2@example.com' }),
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u3', email: 'u3@example.com' })
)
.send();
await AppTable.build(TransactWriteCommand)
.requests(
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u4', email: 'u4@example.com' }),
UserEntity.build(UpdateItemCommand).item({ tenantId: 't1', userId: 'u1', loginCount: $add(1) })
)
.send();
Single-Table Design Guidance
- Model each business concept as an entity with strict schema.
- Keep PK/SK predictable and composable (
TENANT#,USER#,ORDER#). - Encode access paths into GSI keys, not in-memory filters.
- Prefer append-only timelines for audit/history data.
- Keep hot partitions under control with scoped partitions and sharding where needed.
Best Practices
- Design keys from access patterns first, then derive entity attributes.
- Keep one source of truth for key composition (
computeKey) to avoid drift. - Use
.options({ consistent: true })only where strict read-after-write is required. - Prefer targeted queries over scans for runtime request paths.
- Add conditional expressions for idempotency and optimistic concurrency control.
- Validate batch/transaction size limits before execution to avoid partial failures.
Constraints and Warnings
- DynamoDB-Toolbox v2 relies on AWS SDK v3 DocumentClient integration.
- Avoid table scans in request paths unless explicitly bounded.
- Use conditional writes for concurrency-sensitive updates.
- Transactions are limited and slower than single-item writes; use only for true atomic requirements.
- Validate key design against target throughput before implementation.
References
Primary references curated from Context7 are available in:
references/api-dynamodb-toolbox-v2.md
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