Dynamo DB Provider

Fast Develop for DynamoDB with this type-safe & single-table awareness library!

Introduction

No matter if you are using v2 or v3, the DynamoDB SDK is not very friendly (or type safe). With interesting (to say the least) design choices, developing and handling easy operations onto it requires a lot of boiler plate (even more if you are not using the DocumentClient). From building string expressions and trying to avoid collisions and code repetition you are generally left with a lot of code that does little, its hard to maintain and is inevitable wrapped inside a custom abstraction that may fall short.

After trying different approaches and used DynamoDB for years with them, interchanging between some table-to-table and single-table designs, I decided to create an easy-to-inject + customize wrapper around the dynamoDB calls that can work well on each use-case I've seen over these years.

Nice: apart from the established uuid and ksuid libraries to generate IDs on the schema part, this library has zero dependencies!

Three part lib

With the different use cases DynamoDB has, it would not suffice to simply abstract and type the dynamoDB calls. That is, however, the first step to tame the beast. Because you can be in a table-to-table environment and/or single-table (yes, could be both!), what this provider offers had to be split to better accommodate each use case as much as possible.

As such, 3 different main concepts are exposed:

A DynamoDB client-like provider. This is where you'll find the abstraction to each method (get, update, transaction...). If you are not using single-table, you may only need this.
SingleTable instance, in which you can define your table config and easily execute all the methods (contained in the provider) without repeating yourself about keys/indexes etc that are always fixed
Schema capabilities inside your SingleTable instance, in which you can define partitions, entities and collections to properly define you DB data and execute actions on them with ease

This division is done with a bit of extensibility in mind. If you like the lib's abstraction, but pictured the schema part a bit differently (or even, the whole single-table aspect), you can use our abstractions to then customize the usages to your liking.

For the future there is a plan to fully expose the DynamoDB methods, params and responses through a raw section of our 1. Provider to facilitate this more and not lock you with our abstractions/responses while keeping the type-safe etc in check.

It's important to note that while it looks like an ORM while using 2 + 3, its still not quite there. This is by design, as each dynamodb single-table design has its own query/join conditions and choices. I do plan on creating more options on this matter, without being as opinionated as some might be.

Now lets dive on these 3 parts

1. DynamoDB Provider (client)

The DynamodbProvider substitutes you aws clients, but is created with them so you can customize it as needed to work properly. The provider accepts either v2 or v3 clients, but they must be the DocumentClient type. Yes, this lib only worries about the DocumentClient version, not the convoluted default version.

Using v2

import { DynamoDB } from 'aws-sdk';
import { DynamodbProvider } from 'dynamodb-provider'

const provider = new DynamodbProvider({
  dynamoDB: {
    target: 'v2',

    instance: new DynamoDB.DocumentClient({
      // any config you may need. region, credentials...
    }),
  },
});

Using v3

import { DynamoDBClient } from "@aws-sdk/client-dynamodb";
import {
  DynamoDBDocumentClient,
  BatchGetCommand,
  GetCommand,
  DeleteCommand,
  PutCommand,
  UpdateCommand,
  ScanCommand,
  QueryCommand,
  TransactWriteCommand,
 } from "@aws-sdk/lib-dynamodb";

import { DynamodbProvider } from 'dynamodb-provider'

const ddbClient = new DynamoDBClient({
  // any config you may need. region, credentials...
});

const documentClient = DynamoDBDocumentClient.from(ddbClient);

const provider = new DynamodbProvider({
  dynamoDB: {
    target: 'v3',

    instance: documentClient,

    commands: {
      BatchGetCommand,
      GetCommand,
      DeleteCommand,
      PutCommand,
      UpdateCommand,
      ScanCommand,
      QueryCommand,
      TransactWriteCommand,
    };
  },
});

As you have the choice, this lib does not come with any of the aws libraries and is up to you when implementing. We simply receive v3's commands if you choose to use it.

Configuration params

Apart from the dynamoDB version, the provider currently supports the following params:

interface DynamoDbProviderParams {
  dynamoDB: DynamoDBConfig;

  logCallParams?: boolean;
}

logCallParams

A bolean param that enables you to tap in on dynamoDB call params. That will log to the console the actual params produced by the lib and passed by the X dynamodb call

Usefull for debugging or tracking each action that actually reached your Dynamo.

On the future more tap-in params will be provided, both on instance creation and on specific methods.

Provider Methods

Here you'll find each method exposed on the provider.

Quick Access

get
create
delete
update
batchGet
list
listAll
query

get

The get method retrieves a single item from a DynamoDB table based on its primary key. This method allows you to specify whether to use strongly consistent reads, and it also provides the flexibility to retrieve only specific properties from the item.

Signature

interface Method {
  get<Entity = AnyObject, PKs extends StringKey<Entity> | unknown = unknown>(
    params: GetItemParams<Entity, PKs>,
  ): Promise<Entity | undefined>;
}

Parameters

Entity (Type Parameter):

The expected type of the entity being retrieved. This allows for strong typing of the return value based on the entity structure.

PKs (Type Parameter):

Specifies the primary key(s) to be used for the query. This is typically the partition key and optional sort key for composite keys. It can be inferred or passed explicitly.

This allows for narrow operations and is mostly used internally, but exposed if you want to do those kind of restrictions or building from the provider into a custom handler

GetItemParams<Entity, PKs>

table: string The name of the DynamoDB table from which to retrieve the item.
key: EntityPK<Entity, PKs>

The primary key of the item. This can include both partition key and sort key, depending on your table schema. The key structure will be inferred based on the entity type.

consistentRead: boolean (optional)

If set to true, the operation will use strongly consistent reads, ensuring the most up-to-date data is retrieved. Defaults to false, meaning the operation uses eventually consistent reads (faster but may return stale data).

propertiesToRetrieve: (keyof Entity)[] (optional)

An array of specific properties (attributes) to retrieve from the item. If not specified, all attributes of the item will be retrieved. Currently, this only supports root-level attributes (no nested fields).

Return Value

Promise<Entity | undefined>

The method returns a promise that resolves to the retrieved item (Entity) or undefined if the item does not exist.

Usage

interface User {
  userId: string;
  name: string;
  email: string;
  age: number;
}

const result = await db.get<User>({
  table: 'UsersTable',

  key: {
    userId: '12345',
  },

  consistentRead: true,  // Optional: Ensures strongly consistent reads

  propertiesToRetrieve: ['name', 'email'],  // Optional: Fetches only name and email
});

Error Handling

If the table name or key is invalid, an error will be thrown by DynamoDB. The method itself does not return any errors directly, but errors can occur due to invalid parameters or issues with the underlying DynamoDB service.

create

Create an item to your dynamodb table. Remember: dynamo's create (put) action can overwrite existing items. If that is an issue, usse the conditions property to ensure the creation only happens when it should.

Method Signature

type Method {
  create<Entity>(params: CreateItemParams<Entity>): Promise<Entity>;
}

Method Signature

Entity (Type Parameter): The type of the entity being created. This allows for strong typing and validation of the provided data based on the entity structure.

Parameters (Object):

An object containing the following properties:

table (string): The name of the DynamoDB table into which the item will be inserted.
item (Object):

The item to be created in the table. This object should include all necessary attributes, such as the partition key and (if applicable) the sort key, along with any other attributes defined by the entity.

conditions (Array<ItemExpression>): (optinal) An optional set of conditions that must be fulfilled before the item is created. This can be used to ensure that specific attributes or values meet criteria before inserting.

Example: Creating an user only if it does not exists

interface User {
  userId: string;
  name: string;
  email: string;
  age: number;
}

const createdUser = await provider.create({
  table: 'Users',

  item: {
    userId: '12345',
    name: 'John Doe',
    email: 'john@example.com',
    age: 30,
  },

  conditions: [
    {
      condition: 'not_exists',
      property: 'userId',
    },
  ],
});

Just remember that if your table has a partition key and a range key, you need to check for both:

{
  conditions: [
    {
      condition: 'not_exists',
      property: 'paritionKey',
    },
    {
      condition: 'not_exists',
      property: 'rangeKey',
    },
  ],
}

// this condition will check if the item being created does not previously exist on your table, failing if true

Valid Conditions

Heres a breakdown of all condition types

export type ExpressionOperation =
  | 'equal'
  | 'not_equal'
  | 'lower_than'
  | 'lower_or_equal_than'
  | 'bigger_than'
  | 'bigger_or_equal_than'
  | 'begins_with'
  | 'contains'
  | 'not_contains'
  | 'between'
  | 'in'
  | 'not_in'
  | 'exists'
  | 'not_exists';

interface BasalExpressionValues<Entity> {
  /**
   * The property to perform the expression on
   */
  property: StringKey<Entity>;

  /**
   * How should this expression be joined with other expressions?
   *
   * This does not take into account parenthesis
   */
  joinAs?: 'and' | 'or';
}

export interface BasicExpression<Entity> extends BasalExpressionValues<Entity> {
  value: string | number;

  operation: Extract<
    ExpressionOperation,
    | 'equal'
    | 'not_equal'
    | 'lower_than'
    | 'lower_or_equal_than'
    | 'bigger_than'
    | 'bigger_or_equal_than'
    | 'begins_with'
    | 'contains'
    | 'not_contains'
  >;
}

export interface BetweenExpression<Entity> extends BasalExpressionValues<Entity> {
  low: string | number;
  high: string | number;

  operation: Extract<ExpressionOperation, 'between'>;
}

export interface ListExpression<Entity> extends BasalExpressionValues<Entity> {
  values: (string | number)[];

  operation: Extract<ExpressionOperation, 'in' | 'not_in'>;
}

export interface AttributeExistenceExpression<Entity> extends BasalExpressionValues<Entity> {
  operation: Extract<ExpressionOperation, 'exists' | 'not_exists'>;
}

export type ItemExpression<Entity> =
  | BasicExpression<Entity>
  | BetweenExpression<Entity>
  | AttributeExistenceExpression<Entity>
  | ListExpression<Entity>;

The joinAs property ensures the expression you are building will be properly created. Inner expressions are not currently supported.

delete

The delete method removes an item from a DynamoDB table based on the provided primary key. You can also add conditions to control the deletion process, ensuring that certain conditions must be met before the item is deleted.

Method Signature

interface Method {
  delete<Entity extends Record<string, any>>(
    params: DeleteItemParams<Entity>,
  ): Promise<void> {
    await this.remover.delete(params);
  }
}

Parameters

Entity (Type Parameter): The type of the entity being deleted. This ensures the primary key type matches the expected structure.
params (Object): The object containing the following properties:
- table (string): The name of the DynamoDB table from which the item should be deleted.
- key (Object): The primary key of the item to delete.
- conditions (Array, Optional): An optional set of conditions that must be met before the deletion occurs. This can be used to ensure that the item matches certain criteria before being deleted. Same strucute as the create method

Return Value

No value is returned. If the operation fails (dynamoDB error), that is thrown

Example Usage

  interface User {
    id: string;
    name: string;
    email: string;
  }

  await dynamoDB.delete<User>({
    table: 'Users',

    key: {
      id: '12345',
    },

    conditions: [
      {
        condition: 'exists',
        property: 'id',
      },
    ]
  });

update

The update method modifies an item in a DynamoDB table based on the provided primary key. You can selectively update, remove, or apply atomic operations to the item. Additionally, you can add conditions to ensure specific criteria are met before updating the item.

Method Signature

interface Method {
  async update<Entity = AnyObject, PKs extends StringKey<Entity> | unknown = unknown>(
    params: UpdateParams<Entity, PKs>,
  ): Promise<Partial<Entity> | undefined>;
}

Parameters

Entity (Type Parameter): The type of the entity being updated. This ensures the primary key and update data match the expected structure.
params (Object): The object containing the following properties:
- table (string): The name of the DynamoDB table where the item should be updated.
- key (Object): The primary key of the item to update. It can include both the partition key and sort key, depending on the table's schema.
- remove (Array, Optional): A list of attributes to remove from the item. Note: Only root-level properties are supported for removal.
- values (Object, Optional): A partial object with the values to update. This allows you to update specific fields of the item.
- atomicOperations (Array, Optional): Defines atomic operations to be executed on the item. Supported operations include:
  - Math Operations: sum, subtract, add
  - Set Operations: add_to_set, remove_from_set
  - Conditional Operations: set_if_not_exists
- conditions (Array, Optional): An optional set of conditions that must be fulfilled before the update occurs. If any condition is not met, the update will fail.
- returnUpdatedProperties (boolean, Optional): If set to true, this will return the updated properties after the operation. This can be useful for tracking atomic operations such as counters.

Return Value

Returns a Promise that resolves to the updated entity (or a partial version of it) if returnUpdatedProperties is set to true, or undefined otherwise.

Example Usage

  interface User {
    userId: string;
    name: string;
    email: string;
    age: number;
  }

  const params = {
    table: 'Users',

    key: {
      userId: '12345',
    },

    values: {
      name: 'John Doe',
    },

    atomicOperations: [
      { operation: 'add', property: 'age', value: 1 },
    ],

    conditions: [
      {
        condition: 'exists',
        attribute: 'userId',
      },
    ],

    returnUpdatedProperties: true,
  };

  const updatedUser = await provider.update(params);

  // updatedUser will be { name, age }

One common use case of this operation is to control the number of items you have with another item. Say you want to control User with incremental ids:

// whenever creating an user

// operation 1

const { count } = await provider.update({
  table: 'CONTROL_TABLE',

  key: { pk: 'USER_COUNT', sk: 'USER_COUNT' },

  atomicOperations: [
    {
      operation: 'add',
      property: 'count',
      value: 1
    },
  ],

  returnUpdatedProperties: true
})

// operation 2

await provider.create({
  table: 'Users',

  item: {
    // ...user data
    id: count // unique counter, updated from op1
  }
})

batchGet

The batchGet method retrieves multiple items from a DynamoDB table in a single operation. You specify an array of primary keys and DynamoDB will return all matching items. This operation supports retries for unprocessed items and offers the ability to specify which properties should be retrieved.

Method Signature

  async batchGet<Entity = AnyObject, PKs extends StringKey<Entity> | unknown = unknown>(
    options: BatchListItemsArgs<Entity, PKs>,
  ): Promise<Entity[]>;

Parameters

Entity (Type Parameter): The type of the entities being retrieved. This ensures that the retrieved items match the expected structure.
Params (Object): The object containing the following properties:

table (string): The name of the DynamoDB table from which the items should be retrieved.

keys (Array): An array of primary keys for the items you want to retrieve. Each primary key should contain the partition key and, if applicable, the sort key. It handles more than 100 items for you! If you pass more than 100 keys (dynamoDB limit, it'll split the requests appropriately)

consistentRead (boolean, Optional): If set to true, the operation uses strongly consistent reads. Otherwise, eventually consistent reads are used. Default is false.

propertiesToRetrieve (Array, Optional): A list of root-level properties to retrieve from the items. Note: The return type is currently not affected by this field.

throwOnUnprocessed (boolean, Optional): By default, this method will try up to 8 times to resolve any UnprocessedItems returned from the batchGet call. If unprocessed items still exist after all retries, the method will return whatever items were processed successfully. Set this to true if you want the method to throw an error if any unprocessed items remain.

maxRetries (number, Optional): The maximum number of retry attempts for unprocessed items. Default is 8 retries, with exponential backoff.

Return Value

Returns a Promise that resolves to an array of the retrieved entities.

Example Usage

interface Product {
  productId: string;
  name: string;
  price: number;
}

const products = await dynamoDB.batchGet({
  table: 'Products',

  keys: [
    { productId: '123' },
    { productId: '456' },
  ],

  consistentRead: true,

  propertiesToRetrieve: ['name', 'price'],

  throwOnUnprocessed: true,

  maxRetries: 5,
});

`list`

The list method retrieves multiple items from a DynamoDB table based on the specified options. Its a wrapper on Scan. It supports filters, limits, pagination, and parallel scans. The method returns a list of items and an optional pagination token that can be used to continue the retrieval in subsequent calls if more items are available than the limit.

Method Signature

interface Method {
  async list<Entity = AnyObject>(
    table: string,
    options = {} as ListOptions<Entity>,
  ): Promise<ListTableResult<Entity>>;
}

Parameters

Entity (Type Parameter): The type of the entities being retrieved. This ensures that the retrieved items match the expected structure.
table (string): The name of the DynamoDB table from which the items should be listed.
options (ListOptions, Optional): An object containing the following properties for filtering and configuring the list operation:
- propertiesToGet (Array, Optional): A list of root-level properties to retrieve from each entity.
- filters (Object, Optional): Conditions that the entities must meet to be included in the result. You can use three different syntaxes for defining filters:
  1. key:value - Filters for equality (e.g., status: 'active').
  2. key:value[] - Filters for any of the provided values (e.g., status: ['active', 'inactive']).
  3. key:{<FilterConfig>} - More complex filters using a filter configuration.
- limit (number, Optional): Defines the maximum number of items to retrieve. Note: DynamoDB might return fewer items if the maximum allowed MB per request is reached. In such cases, a paginationToken will be returned for further retrieval.
- consistentRead (boolean, Optional): When set to true, the operation uses strongly consistent reads. Default is false.
- parallelRetrieval (Object, Optional): Allows parallel scans across different segments of the table. Use this to speed up scanning by dividing the workload across multiple workers. You can specify the following properties:
  - segment (number): The zero-based segment index to scan.
  - total (number): The total number of parallel scans to run.
- index (string, Optional): The Local or Global Secondary Index to be scanned.
- paginationToken (string, Optional): A token that allows you to continue the list operation from where a previous request left off. Note: This is an abstraction of DynamoDB's LastEvaluatedKey, which is returned as an object. The paginationToken simplifies this process by converting the object into a string.

Advanced Filter Options

As noted, you can simply match value(s) to the relevant properties. But if you need to perform complex operations (such as bigger_than), you need to provide a different structure:

export type BasicFilterConfig = Pick<BasicExpression<any>, 'operation' | 'value' | 'joinAs'>;

export type BetweenFilterConfig = Pick<
  BetweenExpression<any>,
  'operation' | 'high' | 'low' | 'joinAs'
>;

export type AttributeExistenceFilterConfig = Pick<
  AttributeExistenceExpression<any>,
  'operation' | 'joinAs'
>;

export type ListFilterConfig = Pick<ListExpression<any>, 'operation' | 'values' | 'joinAs'>;

export type FilterConfig =
  | BasicFilterConfig
  | BetweenFilterConfig
  | AttributeExistenceFilterConfig
  | ListFilterConfig;

This type is based on the Expression type used on conditions on operations such as update, create or delete.

Return Value

Returns a Promise that resolves to a ListTableResult object containing:

items (Array): The array of items retrieved from the table.
paginationToken (string, Optional): If there are more items to retrieve, a token is returned to continue the operation in the next call. Note: This is an abstraction of DynamoDB's LastEvaluatedKey, which is converted into a string for easier use.

Example Usage

Simple listing:

interface Product {
  productId: string;
  name: string;
  price: number;
  category: string;
}

const result = await dynamoDB.list<Product>('Products', {
  propertiesToGet: ['productId', 'name', 'price'],

  filters: {
    category: 'electronics',
  },

  limit: 100,

  consistentRead: true,
});

Listing with complex filtering:

interface Product {
  productId: string;
  name: string;
  price: number;
  category: string;
}

const result = await dynamoDB.list<Product>('Products', {
  filters: {
    price: {
      operation: 'bigger_than',
      value: 100,
    },

    name: {
      operation: 'begins_with',
      value: 'k'
    }
  },

  limit: 100,

  consistentRead: true,
});

`listAll`

The listAll method retrieves all items from a DynamoDB table, running sequential scan operations until there are no more items to retrieve. It removes the need to handle pagination manually, unlike the list method, which may return a paginationToken for further retrieval. This method is useful when you need to scan an entire table without worrying about setting pagination tokens or limits.

Method Signature

interface Method {
  async listAll<Entity = AnyObject>(
    table: string,
    options = {} as ListAllOptions<Entity>,
  ): Promise<Entity[]>;
}

Parameters

Entity (Type Parameter): The type of the entities being retrieved. This ensures that the retrieved items match the expected structure.
table (string): The name of the DynamoDB table from which the items should be retrieved.
options (ListAllOptions, Optional): An object containing the following properties for filtering and configuring the retrieval:
- propertiesToGet (Array, Optional): A list of root-level properties to retrieve from each entity.
- filters (Object, Optional): Conditions that the entities must meet to be included in the result. You can use three different syntaxes for defining filters:
  1. key:value- Filters for equality (e.g., status: 'active').
  2. key:value[]- Filters for any of the provided values (e.g., status: ['active', 'inactive']).
  3. key:{<FilterConfig>}- More complex filters using a filter configuration.
- consistentRead (boolean, Optional): When set to true, the operation uses strongly consistent reads. Default is false.
- parallelRetrieval (Object, Optional): Allows parallel scans across different segments of the table. Use this to speed up scanning by dividing the workload across multiple workers. You can specify the following properties:
  - segment (number): The zero-based segment index to scan.
  - total (number): The total number of parallel scans to run.
- index (string, Optional): The Local or Global Secondary Index to be scanned.

Return Value

Returns a Promise that resolves to an array of Entity[], containing all items retrieved from the table.

Key Differences from `list`

The listAll method differs from the list method in the following ways:

It automatically handles pagination by performing multiple scan operations until all items are retrieved.
The paginationToken and limit options are not available in listAll as it retrieves all items in one go.

Example Usage

interface Product {
  productId: string;
  name: string;
  price: number;
  category: string;
}

// all electronics products
const allProducts = await dynamoDB.listAll<Product>('Products', {
  propertiesToGet: ['productId', 'name', 'price'],

  filters: {
    category: 'electronics',
  },
});

query

The query method allows you to retrieve items from a DynamoDB table by querying using the partition key and (optionally) the range key. This method leverages DynamoDB's efficient querying abilities and supports further filtering and pagination. It allows both local and global index querying and supports ordering and filtering of results.

Method Signature

interface Method {
  query<Entity = AnyObject>(params: QueryParams<Entity>): Promise<QueryResult<Entity>>;
}

Parameters

Entity (Type Parameter): The type of the entities being retrieved. This ensures that the retrieved items match the expected structure.
params (Object): An object containing the following properties for querying the DynamoDB table:
- table (string): The name of the DynamoDB table to query.
- index (string, Optional): The name of the Local or Global Index to be queried.
- partitionKey (Object): The partition key condition for the query. Contains two properties:
  - name (string): The name of the partition key on your table.
  - value (string): The value of the partition key to query.
- rangeKey (Object, Optional): Further enhance the query with range key conditions. This supports operations as:
  - equal
  - lower_than
  - lower_or_equal_than
  - bigger_than
  - bigger_or_equal_than
  - begins_with
  - between
  RangeKey Configuration comes in two forms:
  - BasicRangeKeyConfig: For single condition operations (equal, lower_than, etc.).
  - BetweenRangeKeyConfig: For a between operation, providing both low and high values.
- retrieveOrder (string, Optional): Specifies the order of the results. By default, DynamoDB retrieves items in ASC order. You can set this to ASC or DESC.
- paginationToken (string, Optional): A token from a previous query result to continue retrieving items. Useful for paginated queries.
- limit (number, Optional): The maximum number of items to retrieve in this query operation. This has higher precedence than fullRetrieval Note: If set, fewer items might be retrieved due to DynamoDB's item size limitations.
- fullRetrieval (boolean, Optional): When set to true, the query will continue retrieving all items matching the partition key, even if multiple requests are needed. Default is true.
- filters (Object, Optional): Additional filtering conditions to apply on the items returned. You can use three different syntaxes for defining filters:
  1. key:value- Filters for equality (e.g., status: 'active').
  2. key:value[]- Filters for any of the provided values (e.g., status: ['active', 'inactive']).
  3. key:{<FilterConfig>}- More complex filters using a filter configuration.

Return Value

Returns a Promise that resolves to a QueryResult<Entity> object containing the following:

items (Array): An array of items matching the query.
paginationToken (string?): A token that can be used for paginated queries to continue retrieving items. This is an abstraction of DynamoDB's LastEvaluatedKey.

Example Usage

  interface Order {
    orderId: string;
    customerId: string;
    status: string;
    totalAmount: number;
  }

  const { items, paginationToken } = await provider.query<Order>({
    table: 'Orders',

    partitionKey: {
      name: 'customerId',
      value: '12345',
    },

    rangeKey: {
      name: 'orderId',
      operation: 'bigger_or_equal_than',
      value: 'A100',
    },

    retrieveOrder: 'DESC',

    limit: 10,

    filters: {
      status: 'shipped',
    },
  });

`executeTransaction` Method

Description

The executeTransaction method allows you to perform multiple DynamoDB operations (such as creating, updating, deleting, or conditionally validating items) as a single transaction. It ensures that all operations either succeed or fail as a group, maintaining DynamoDB's ACID (Atomicity, Consistency, Isolation, Durability) properties. Its a wrap under TransactWrite

Method Signature

interface Method {
  executeTransaction(configs: (TransactionConfig | null)[]): Promise<void>;
}

Parameters

configs (Array<TransactionConfig | null>): An array of configuration objects, where each object defines a transaction operation. You null to easily create inline conditions while generating the params

Important: The limit of valid configs inside a transaction is 100 (or 4MB total), as per dynamodb doc

Each item in the array can be one of the following transaction types:
- UpdateTransaction Represents an update operation. Fields:
  - update (UpdateParams): Parameters for the update operation.
- CreateTransaction Represents a create (put item) operation. Fields:
  - create (CreateItemParams): Parameters for the creation operation.
- DeleteTransaction Represents a delete operation. Fields:
  - erase (DeleteItemParams): Parameters for the deletion operation.
- ConditionCheckTransaction Represents a condition check operation. This operation validates certain conditions before allowing other transactions to proceed. Fields:
  - validate (ValidateTransactParams): Parameters for the condition check operation.

Example Usage

This example executes a fairly complex operation of updating an order to complete status, while deleting its related Card, creating a finilized ClientOrder while also validating that specific Client exists

The usage of this specific use case can be discussed, but it clearly represents the abilities of the method with ease.

await dynamoDB.executeTransaction([
  {
    update: {
      table: 'Orders',
      key: { orderId: 'A100' },
      values: { status: 'completed' },
      conditions: [
        {
          property: 'status'
          operation: 'equal',
          value: 'pending',
        }
      ],
    },
  },
  {
    erase: {
      table: 'Carts',
      key: { cardId: 'C100' },
    },
  },
  {
    create: {
      table: 'ClientOrders',
      item: {
        orderId: 'A100',
        customerId: '12345',
        status: 'completed',
        totalAmount: 100,
      },
    },
  },
  {
    validate: {
      table: 'Client',

      key: { id: '12345' },

      conditions: [
        {
          operation: 'exists',
          property: 'id'
        }
      ],
    },
  },
]);

Helper methods

Aside from the methods that execute an action on dynamoDB, the provider exposes 2 helper methods to interact with the actions

createSet
generateTransactionConfigList

create set

Depending on the sdk version, referencing a set to be created on DynamoDB is different. To get around this and ensure a normalized usage, you can use the createSet method:

await provider.create({
  table:  'table-name',

  item: {
    id: '111',
    // ...props
    someSetProp: provider.createSet([1, 2, 10, 40]),

    statuses: provider.createSet(['done', 'archived'])
  }
})

generate transaction config list

A type helper to generate transaction params referenced to an entity

interface Method {
  generateTransactionConfigList<Item>(
    items: Item[],
    generator: (item: Item) => (TransactionConfig | null)[],
  ): TransactionConfig[]
}

If you do not use Single Table, this is as far as you need to go to

Single table

If you are familiar with single table design, you know there's quite a bit of boiler plate setup to be done. If you are not organized with it, it can quickly become a hassle, compromising your code readability and increasing maintenance time.

To enforce a pattern, you can create a single table instance to configure your table and execute your actions on it. For each table you might have, you can create an instance.

The SingleTable instance requires a DynamoDbProvider to be created.

Parameters

`dynamodbProvider`

Type: IDynamodbProvider
Description: An instance of DynamodbProvider, configured with the appropriate settings and required to interact with DynamoDB.

`keySeparator`

Type: string
Default: #
Description: The logical separator used to join key paths. For example, if the item key is ['USER', id], the actual DynamoDB key becomes USER#id.

`table`

Type: string
Description: The name of the DynamoDB table.

`partitionKey`

Type: string
Description: The partition (hash) key column used in the single table.

`rangeKey`

Type: string
Description: The range (sort) key column used in the single table.

`typeIndex`

Type: object
Description: A global index that uniquely identifies each entity in the table. The methods listType and findType rely on this index to work. Future versions will hide these methods if typeIndex is not provided.
- partitionKey: The partition/hash column for this index.
- rangeKey: Defaults to the item's creation timestamp (ISO format new Date().toISOString()).
- name: The index name.
- rangeKeyGenerator(item, type): Generates a range key value for the type index. If you are not actually using the index, you can pass in () => undefined, which will not produce the sort property on the item.

Important: You do not need to actually have the index on the table to enforce the type prop on your items. Although recommended, as its the easiest to extract the "tables" inside, you can simply define a type property, and it would only produce it. Not having a type like property at all inside your single table entities is extremely not recommended

`expiresAt`

Type: string
Description: Specifies the TTL column name if Time to Live (TTL) is configured in the DynamoDB table.

`indexes`

Type: Record<string, { partitionKey: string; rangeKey: string; }>
Description: Configures additional indexes in the table. Use this to define local or global secondary indexes.
- key: Index name, as its named on dynamodb
- partitionKey: The partition/hash column for the index.
- rangeKey: The range/sort column for the index.

`autoRemoveTableProperties`

Type: boolean
Default: true
Description: Automatically removes internal properties from items before they are returned by the methods. Internal properties include partition keys, range keys, TTL attributes, and index keys. This ensures that items have all relevant properties independently, without relying on key extractions. Remember, its the best practice to not rely on these internal properties for your actual data. Even if your PK is USER#id, you should have a separate property "id" on the entity.

`keepTypeProperty`

Type: boolean
Default: false
Description: Keeps the typeIndex partition key from removal during item cleanup. Useful when the entity type is needed to distinguish between different query results or use-cases.

`propertyCleanup`

Type: (item: AnyObject) => AnyObject
Description: A function that processes and returns the item to be exposed by the methods. Overrides the automatic cleanup behavior set by autoRemoveTableProperties and keepTypeProperty. Useful for customizing how internal properties are removed from items.

`blockInternalPropUpdate`

Type: boolean
Default: true
Description: Enables a safety check on every update operation inside your single table to block (with a thrown error) any operation that tries to update an internal property of an item. This includes any key, index key, type key or TTL attribute. Useful to prevent indirect code to mess with the internal configuration of your items. You can set this to false and use the badUpdateValidation to further customize which property should be blocked

`badUpdateValidation`

Type: (propertiesInUpdate: Set<string>) => boolean | string
Description: Validates updates by inspecting all properties referenced in an update (in values, remove, or atomicOperations). The default validation ensures that the partition key is not modified, which is a DynamoDB rule. You can use this validation to block internal property updates or throw a custom error message. This has a niche use case and should not see much usage.

Single Table usage

import { SingleTable, DynamodbProvider } from 'dynamodb-provider'

const provider = new DynamodbProvider({
  // provider params
});


const table = new SingleTable({
  dynamodbProvider: provider,

  table: 'YOUR_TABLE_NAME',

  partitionKey: 'pk',
  rangeKey: 'sk',

  keySeparator: '#',

  typeIndex: {
    name: 'TypeIndexName',

    partitionKey: '_type',
    rangeKey: '_timestamp',
  },

  expiresAt: 'ttl',

  indexes: {
    SomeIndex: {
      partitionKey: 'gsipk1',
      rangeKey: 'gsisk1',
    }
  }
})

Single Table Methods

With your single table created, you can now use it to execute all the same actions from the provider, but fully aware of the table config.

Available Methods:

get
batchGet
create
delete
update
query
executeTransaction
listType
listAllFromType

single table get

Parameters:

partitionKey: The partition key of the item you want to retrieve.
rangeKey: The range key of the item you want to retrieve.
consistentRead (optional): If set to true, the operation uses strongly consistent reads; otherwise, it uses eventually consistent reads. Default is false.
propertiesToRetrieve (optional): Specifies which properties to retrieve from the item. This is helpful when you only need specific fields instead of the entire item.

Valid Keys

type Key = null | string | Array<string | number | null>;

Note: null is mainly useful if you want to block an index update to happen due to lack of params. We'll see an example later on.

Example

import { SingleTable } from 'dynamodb-provider'

const table = new SingleTable({
  // ...config
})

const user = await table.get({
  partitionKey: ['USER', id],

  rangeKey: '#DATA',

  consistentRead: true,
})

The call above correctly matches your table actual keys under the hood, joins any array key with the configured separator for you.

You can use these methods as they are, create your own entity x repository like extraction methods out of it or use our own entity abstraction to fully utilize the best out of the single table design.

single table batch get

Parameters:

keys: An array of objects, where each object contains:
- partitionKey: The partition key of the item.
- rangeKey: The range key
consistentRead (optional): If set to true, the operation uses strongly consistent reads; otherwise, it uses eventually consistent reads. Default is false.
propertiesToRetrieve (optional): Specifies which properties to retrieve for each item.
throwOnUnprocessed (optional): By default, this call will try up to 8 times to resolve any UnprocessedItems result from the batchGet call. If any items are still left unprocessed, the method will return them. If set to true, the method will throw an error if there are unprocessed items.

Example:

  const items = await singleTable.batchGet({
    keys: [
      { partitionKey: 'USER#123', rangeKey: 'INFO#456' },
      { partitionKey: 'USER#789', rangeKey: 'INFO#012' },
    ],

    propertiesToRetrieve: ['name', 'email'],

    throwOnUnprocessed: true,
  });

single table create

Parameters:

item: The object representing the item you want to create. The object should contain all the fields of the entity.
key: An object containing:
- partitionKey: The partition key for the new item.
- rangeKey: The range key (if applicable) for the new item.
indexes (optional): If applicable, provides the index key information for other indexes the item will be added to. Structure: Record<IndexName, { partitionKey, rangeKey }>
expiresAt (optional): A UNIX timestamp for setting a TTL on the item. Only acceptable if expiresAt is configured on table.
type (optional): Defines the entity type for a single table design setup. Only acceptable if typeIndex is configured on table.

Example:

const user = await singleTable.create({
  key: {
    partitionKey: 'USER#123',
    rangeKey: '#DATA',
  },

  item: {
    id: '123',
    name: 'John Doe',
    email: 'john.doe@example.com',
  },

  type: 'USER',

  expiresAt: Math.floor(Date.now() / 1000) + 60 * 60 * 24 * 30, // 30 days TTL
});

single table delete

Parameters:

partitionKey: The partition key of the item you want to delete.
rangeKey: The range key of your item.
conditions (optional): A set of conditions that must be met before the deletion is executed.

Example:

await singleTable.delete({
  partitionKey: 'USER#123',
  rangeKey: '#DATA',
});

single table update

We'll show just the params that differ from update

Parameters:

partitionKey: The primary partition key of the item to update.
rangeKey: The range key of the item to update
indexes (optional): Allows updating associated secondary indexes. You can specify which indexes to update by providing partial or full values for the index's partition and/or range keys.
expiresAt (optional): The UNIX timestamp defining when the item should expire (for tables configured with TTL).
values (optional): An object containing key-value pairs representing the properties to update. These values will be merged into the existing item.
remove (optional): An array of properties to be removed from the item.
atomicOperations (optional): A list of operations to perform on numeric or set properties. Supported operations:
- sum: Add a value to an existing numeric property.
- subtract: Subtract a value from an existing numeric property.
- add_to_set: Add values to a set property.
- remove_from_set: Remove values from a set property.
- set_if_not_exists: Set a property value only if it does not already exist.
conditions (optional): A set of conditions that must be satisfied for the update to succeed. The update will be aborted if the conditions are not met.
returnUpdatedProperties (optional): If true, the updated properties are returned. This is useful if you're performing atomic operations and want to retrieve the result.

Example:

const result = await singleTable.update({
  partitionKey: ['USER', 'some-id'],

  rangeKey: '#DATA',

  values: {
    email: 'newemail@example.com',
    status: 'active'
  },

  remove: ['someProperty'],

  atomicOperations: [{ operation: 'sum', prop: 'loginCount', value: 1 }],

  expiresAt: Math.floor(Date.now() / 1000) + 60 * 60 * 24 * 30, // Expires in 30 days

  indexes: {
    SomeIndex: { partitionKey: 'NEW_PARTITION' },
  },

  conditions: [{ key: 'status', value: 'pending', operation: 'equal' }],

  returnUpdatedProperties: true,
});

single table query

Most of the params are the same from the query method from provider

Different Parameters:

partition: Simply the Key, as we know the column name
range: Here you can build your key condition exactly as before, but also wi

Example:

Retrieving the last 10 user logs:

const results = await singleTable.query({
  partition: ['USER', 'your-id'],

  range: {
    value: 'LOG#',
    operation: 'begins_with',
  },

  retrieveOrder: 'DESC',

  limit: 10,
});

single table execute transaction

Works the logic same as executeTransaction from the provider, the params for the create/update/delete methods can be used here to build the transaction, as well as using validate calls to ensure the rules of your action are being respected

Parameters reminder:

configs: An array of transaction configurations. Each transaction can be one of the following:
- update: An update operation (see the update method for more details).
- create: A create operation (see the create method for more details).
- erase: A delete operation (see the delete method for more details).
- validate: A condition check (ensures certain conditions are met before applying other operations).

single table list all from type

Important: This method only works if you have a proper defined typeIndex that matches an existing index on the table.

This method retrieves all items of a specified type from the table. It is a wrapper around the query function that simplifies the retrieval of all items associated with a particular type.

Parameters:

type: string - The entity type to retrieve from the table, based on the typeIndex partition key.

Example Usage:

const items = await table.listAllFromType('USER');

single table list type

Important: This method only works if you have a proper defined typeIndex that matches an existing index on the table.

This method performs a paginated query to retrieve items of a specific type, supporting range key filtering, pagination, and other query parameters.

Parameters:

params: ListItemTypeParams - An object with the following properties:
- type: string - The entity type to retrieve from the table, based on the typeIndex partition key.
- range?: BasicRangeConfig | BetweenRangeConfig - Optional range key filter. This can either be a single comparison operation (e.g., greater than) or a between operation.
- limit?: number - Limits the number of items returned in a single call.
- paginationToken?: string - Token to continue retrieving paginated results.
- retrieveOrder?: 'ASC' | 'DESC' - The order in which items should be retrieved, either ascending (ASC) or descending (DESC).
- fullRetrieval?: boolean - If set to true, retrieves all items until no more pagination tokens are returned.
- filters?: FilterConfig - Additional filters to apply on the query.

Returns:

An object containing:

items: Entity[] - The list of items retrieved.
paginationToken?: string - If applicable, a token for retrieving the next set of paginated results.

Example Usage:

const result = await table.listType({
  type: 'USER',

  range: {
    operation: 'begins_with',
    value: 'john',
  },

  limit: 10,
});

Because type match is such a common use case, we also provide 2 helper methods for handling item lists:

interface TypeHelperMethods {
  findTableItem<Entity>(items: AnyObject[], type: string): Entity | undefined

  filterTableItens<Entity>(items: AnyObject[], type: string): Entity[]
}

Single Table Schema

Now that every direct single table method is covered, it time to talk about the last part of the library: schema abilities.

With your single table instance, you can define partitions, entities and even collections to be easily acted upon. Lets explore this with the most basic type of DB piece you may need: entity

Single Table Schema: Entity

Entities are the representation of a data type inside your table. There can be made a parallel between an SQL table and a single table entity

Creating entity syntax

type tUser = {
  id: string;
  name: string;
  createdAr: string;
  // ... more props
}

const User = table.schema.createEntity<User>().withParams({
  // create entity params
})

We have a double invocation here to properly forward the entities type in conjunction with the params inferred from the creation. This is done as you'll see the entity type is solely reliant on TS' types as of now, there's not in code schema definition atm.

Lets explore the params allowed:

Create entity params

getPartitionKey: A partition resolver for your entity
getRangeKey: A range resolver for your entity

Both key resolvers have the same key getter structure as before, but restricted to the actual entity properties:

type EntityKeyResolvers<Entity> = {
  getPartitionKey: (params: EntityParamsOnly<Entity>) => KeyValue;

  getRangeKey: (params: EntityParamsOnly<Entity>) => KeyValue;
};

This means you can't pass in a getter that uses params not found in its type:

type tUser = {
  id: string;
  name: string;
  createdAr: string;
  // ... more props
}

const BadUser = table.schema.createEntity<User>().withParams({
  // create entity params
  getPartitionKey: ({userId}: {userId: string}) => ['USER', userId] // TYPE ERROR!
})

const User = table.schema.createEntity<User>().withParams({
  // create entity params
  getPartitionKey: ({ id }: Pick<User, 'id'>) => ['USER', id] // ok!
})

As a reminder, the allowed values:

type KeyValue = null | string | Array<string | number | null>;

Just remember null is useful if you want to indicate that you generated a bad key that shouldn't be updated. That means its relevant on index key getters, but no actual partition/range context

type (string): An unique describer of an entity inside your single table. Think of it as the "table name". If you try to create 2 entities with the same type, an error is thrown.
autoGen (object, optional): Defined properties that should be auto generated onCreation or onUpdate:
```
type AutoGenFieldConfig<Entity> = {
  [Key in keyof Entity]?: AutoGenOption;
};

export type AutoGenParams<Entity> = {
  onCreate?: AutoGenFieldConfig<Entity>;

  onUpdate?: AutoGenFieldConfig<Entity>;
};
```
AutoGenOption are as follows:
- UUID: generates a v4 uuid
- KSUID: generates a K-Sortable Globally Unique IDs (KSUID)
- count: automatically assigns 0
- timestamp: generates the current timestamp with new Date().toISOString()
- () => any: Pass in a function if you need a custom auto-generation strategy
rangeQueries (object, optional): Configure possible queries to be easily referenced when using the entity. Here you can easily define query configuration to be used to retrieve the entity

Pass in an object in which:
- Key: query name
- Value: query config, which operation will be performed, and value getter
```
type tLogs = {
  type: string;
  timestamp: string;
  // ...props
}

const Logs = table.schema.createEntity<tLogs>().withParams({
  type: 'APP_LOGS',

  getPartitionKey: () => ['APP_LOG'],

  getRangeKey: ({ timestamp }: Pick<tLogs, 'timestamp'>) => timestamp,

  rangeQueries: {
    dateSlice: {
      operation: 'between',
      getValues: ({ start, end }: { start: string, end: string }) => ({
        low: start,
        high: end,
      })
    }
  }
})
```
When the time comes to use the entity, this will produce a dateSlice method, which will require start and end params to work (as our partition key does not require any addition params), properly typed. the method will build the underlying dynamodb query need to perform the retrieval. You can further configure the dateSlice methods with the query params we have.

index (object, optional): Only available if table configured with indexes. A record mapping of your entity indexes definition:

Format: Record<string, IndexConfig>

key: a custom index name to describe it
value: IndexConfig
- getPartitionKey - same logic as the root entity getPartitionKey
- getRangeKey - same logic as the root entity getRangeKey
- index - the actual table index name related, as is on the dynamodb table
- rangeQueries? - same logic as the root entity rangeQueries

Example:

type tLogs = {
  type: string;
  timestamp: string;
  // ...props
}

const table = new SingleTable({
  // ... other params

  indexes: {
    DynamoIndex1: {
      partitionKey: 'gsipk1',
      rangeKey: 'gsipsk1',
    },

    OtherTableIndex: {
      partitionKey: 'gsipk2',
      rangeKey: 'gsipsk2',
    },
  }
})

const Logs = table.schema.createEntity<tLogs>().withParams({
  type: 'APP_LOGS',

  getPartitionKey: () => ['APP_LOG'],

  getRangeKey: ({ timestamp }: Pick<tLogs, 'timestamp'>) => timestamp,

  indexes: {
    MY_CUSTOM_INDEX_NAME: {
      getPartitionKey: ({ type }: Pick<tLogs, 'type'>) => ['APP_LOG_BY_TYPE', type],

      getRangeKey: ({ timestamp }: Pick<tLogs, 'timestamp'>) => timestamp,

      index: 'DynamoIndex1' // could be DynamoIndex1 or OtherTableIndex as per config
    }
  }
})

extend: A function you can use to add/modify properties from the entity automatically upon retrieval on fromEntity calls

  type tUser = {
    id: string;
    name: string;
    dob: string;
    // ... more props
  }

  const User = table.schema.createEntity<User>().withParams({
    // ...other props

    extend: ({ dob }) => ({
      age: calculateAge(dob)
    })
  })

The example above represent a property addition, the user calculate age. It will be present automatically after every retrieval call from fromEntity. Its also applied to the fromCollection result.

Single table entity usage

The generated entity has properties that you can leverage to interact with the single table methods, such as:

Relevant entity properties

getKey - A complete key getter that accepts the exact params required in getPartitionKey and getRangeKey to generate the entity key reference { partitionKey: KevValue, rangeKey: KeyValue }
getCreationParams(item: Entity, { expiresAt?: number }?) - as the name implies, generates the single table create params. If expiresAt is defined in your table, a second optional param with allowed if that configuration
getUpdateParams(params: UpdateParams) - same logic as the getCreationParams, but produces the params for single table update instead. Here all the key params are required, plus the updates such as values, atomicOperations and etc
transact param builders - You can easily generate any of the create, update, erase and/or validate transact params with:
- transactCreateParams - results in { create: {...} }
- transactUpdateParams - results in { update: {...} }
- transactDeleteParams - results in { erase: {...} }
- transactValidateParams - results in { validate: {...} }

Using entity directly on schema

You can also leverage the schema.fromEntity method to create a "repository-like" instance to perform actions on your entity:

type tUser = {
  id: string;
  name: string;
  createdAr: string;
  // ... more props
}

const User = table.schema.createEntity<User>().withParams({
  type: 'USER',

  getPartitionKey: ({ id }: Pick<User, 'id'>) => ['USER', id],

  getRangeKey: () => ['#DATA'],
})

const userActions = table.schema.fromEntity(User)

This will expose all the methods we are used to, but fully specified to meet the user needs/type. For example:

const userActions = table.schema.fromEntity(User)

await userActions.create({
  // all user props that are required on the User type
})

await userActions.update({
  id: 'user-id', // because its a key param

  values: {
    status: 'new-status'
  }

  // other update specific params
})

Here's a list of all available methods:

get
batchGet
create
update
delete
listAll - only if typeIndex is present
list - only if typeIndex is present
query
queryIndex - only if entity has index defined

Out of these methods, query and queryIndex are in a different format. As you can execute custom queries and/or have pre-defined queries on rangeQueries:

query exposes a custom method to execute any query on the entity partition plus each range query defined
queryIndex while queryIndex exposes a similar structure as query, but for each individual index defined

Example:

type tLogs = {
  type: string;
  timestamp: string;
  // ...props
}

const Logs = table.schema.createEntity<tLogs>().withParams({
  type: 'APP_LOGS',

  getPartitionKey: () => ['APP_LOG'],

  getRangeKey: ({ timestamp }: Pick<tLogs, 'timestamp'>) => timestamp,

  indexes: {
    logsByType: {
      getPartitionKey: ({ type }: Pick<tLogs, 'type'>) => ['APP_LOG_BY_TYPE', type],

      getRangeKey: ({ timestamp }: Pick<tLogs, 'timestamp'>) => timestamp,

      index: 'DynamoIndex1',

      dateSlice: {
        operation: 'between',
        getValues: ({ start, end }: { start: string, end: string }) => ({
          low: start,
          high: end,
        })
      }
    }
  }
})

// all valid queries:

await table.fromEntity(Logs).query.custom() // valid call, as getPartitionKey does not have params, it will simply execute a query against its partition

await table.fromEntity(Logs).query.custom({
  limit: 10,
  retrieveOrder: 'DESC'
})

await table.fromEntity(Logs).queryIndex.logsByType.custom({
  type: 'LOG-TYPE-1', // required as logsByType getPartitionKey expects it
})

await table.fromEntity(Logs).queryIndex.logsByType.dateSlice({
  type: 'LOG-TYPE-2',
  start: 'some-ts',
  end: 'some-ts',
  limit: 20,
})

Note: Any retrieval method will apply the extend action if available

With the fromEntity you can strongly enforce the data access patterns you have within you table, simplifying the process of handling the underlying table properties that should be excluded from app logic.

Single Table Schema: Partition

As you might be familiar while using the single table design, it's all about partitions. If you are new to it, partitions are all the data under a certain partitionKey logic. It could have one type of entity or many.

Lets use the user example, in which the partitionKey is in the USER#userId format. Under it, we have entities for the main user data, permissions, login logs and purchase history. To closely keep that information together with the partition/range key, it is recommended to create a partition before its relative entities.

const userPartition = table.schema.createPartition({
  name: 'USER_PARTITION',

  getPartitionKey: ({ userId }: { userId: string }) => ['USER', userId],

  entries: {
    mainData: () => ['#DATA'],

    permissions: ({ permissionId }: { permissionId: string }) => ['PERMISSION', permissionId],

    loginAttempt: ({ timestamp }: { timestamp: string }) => ['LOGIN_ATTEMPT', timestamp],

    orders: ({ orderId }: { { orderId: string } }) => ['ORDER', orderId],
  },
})

Its recommended to give the partition params the most descriptive names possible, why we chose userId and not id

With your created partition, you can now use it to create its relative entities. If you need to adjust the key getter params, you can do it here too:

type tUser = {
  id: string;
  name: string;
  createdAt: string;
  email: string;
  updatedAt?: string;
}

type tUserLoginAttempt = {
  userId: string;
  timestamp: string;
  success: boolean;
  ip: string;
}

const User = userPartition.use('mainData').create<tUser>().entity({
  type: 'USER',

  // This is an optional param
  // it accepts as keys every param inside the partitionKey + the entry used (mainData here)
  // it will produce an entity that the key getters reference 'id' to work, instead of userId!
  paramMatch: {
    userId: 'id'
  },

  // every other create entity param...
})

const UserLoginAttempt = userPartition.use('loginAttempt').create<tUserLoginAttempt>().entity({
  type: 'USER_LOGIN_ATTEMPT',

  // since all key params from partition+loginAttempt are already present on tUserLoginAttempt,
  // we do not need to match params
})

Important You can only use each entry once.

Index Partition

Its also common to have partitions localized to certain table's index instead of the main pk+sk combo. You can create an index partition easily as well. So let's repeat the above example with an Index based logic:

type tUser = {
  id: string;
  name: string;
  createdAt: string;
  email: string;
  updatedAt?: string;
}

type tUserLoginAttempt = {
  userId: string;
  timestamp: string;
  success: boolean;
  ip: string;
}

const userIndexPartition = table.schema.createPartition({
  name: 'USER_PARTITION',

  index: 'YourIndexNameFromConfig',

  getPartitionKey: ({ userId }: { userId: string }) => ['USER', userId],

  entries: {
    mainData: () => ['#DATA'],

    permissions: ({ permissionId }: { permissionId: string }) => ['PERMISSION', permissionId],

    loginAttempt: ({ timestamp }: { timestamp: string }) => ['LOGIN_ATTEMPT', timestamp],

    // other entries...
  },
})

const User = table.schema.createEntity<tUser>().withParams({
  type: 'USER',

  getPartitionKey: () => ['APP_USERS'],

  getRangeKey: ({ id }: Pick<tUser, 'id'>) => ['USER', id],

  indexes: {
    userData: userIndexPartition.use('mainData').create<tUser>().index({
      paramMatch: {
        userId: 'id'
      },

      // rangeQueries? ... other index params
    }),
  }
})

const UserLoginAttempt = table.schema.createEntity<tUserLoginAttempt>().withParams({
  type: 'USER_LOGIN_ATTEMPT',

  getPartitionKey: () => ['APP_LOGINS'],

  getRangeKey: ({ id, timestamp }: Pick<tUserLoginAttempt, 'id' | 'timestamp'>) => ['USER_LOGIN', timestamp, id],

    indexes: {
      // no param to match or other index params? no need to provide params
      userData: userIndexPartition.use('loginAttempt').create<tUser>().index(),
    }
})

As you have noticed, the use('entry').create<EntryType>() call can either provide you with an entity OR an index, based on if your partition is default or index based.

Partition Creation Params

All params have been covered on the example above, but here's them aggregated:

name: An UNIQUE name to your partition
getPartitionKey: The partition getter
index?: The table index this partition might be from
entries: An object mapping a partition entity to its getRangeKey resolver

Single Table Schema: Collection

Now that we know how to create and use entities, be it solo or partition types, we need a way to define precisely which complex structures we can retrieve. In the user example above, we could want to retrieve the entire User type, including permissions, login attempts, etc. This is a common pattern on single table design, as ofter our data is spread across multiple entries on the table.

To help you define these complex structures that live inside your table, you can create a Collection.

Collection Parameters

ref: The root entity of the collection. It can be null if the base entry will be an empty object with the join keys.
type: Specifies the join type, either 'SINGLE' or 'MULTIPLE'.
getPartitionKey: Function or reference for retrieving the partition key for the collection. If this is provided, partition is not accepted
index?: Which table index this collection is relevant. Only acceptable if you provide getPartitionKey instead of a partition.
partition: An existing partition for your collection. It can be either entity or index partition. The collection will properly infer the index/non-index state to perform the query If this is provided, getPartitionKey and index are not accepted
narrowBy: Optional filter to narrow down the range key search for the collection, either by a range key prefix or a custom function. Accepted values:
- RANGE_KEY: will narrow the query starting with the getRangeKey of the ref entity. Only works if ref is an entity
- (params?: AnyObject) => RangeQueryConfig: A custom handler that returns the range query to be passed down to the collection query
join: Configuration for how entities should be joined together. Each key will represent an entity relationship in the collection. Structure: Record<string, JoinConfig>. Each key referenced here will be the resulting key on the extracted result

Each entry in the join object should follow the structure:
```
type JoinConfig = {
  entity: RefEntity;

  type: 'SINGLE' | 'MULTIPLE';

  extractor?: (item: AnyObject) => any;

  sorter?: Sorter;

  joinBy?: 'POSITION' | 'TYPE' | JoinResolver;

  join?: Record<string, JoinConfig>;
}
```
Lets explore each param:
- entity (Required): The reference to the entity you want to join with.
- type (Required): Specifies whether the join will result in a single reference ('SINGLE') or multiple references ('MULTIPLE').
- extractor (Optional): A function to extract and return specific data from the joined entity before adding it to the parent entity. Example: Extracting only a subset of the fields like permission from the UserPermission entity.
- sorter (Optional): A function to custom sort the list of entities when type is 'MULTIPLE'. This is ignored for 'SINGLE' joins. Example: Sorting the user login attempts by a timestamp or a custom logic
- joinBy (Optional): Defines how the join is performed. It defaults to 'POSITION' but supports the following options:
  - POSITION: Joins entities based on their sequential extraction from the query. Requires a typeIndex to exist in the table.
  - TYPE: Joins entities by their type. Required at least your entities to have the typeIndex.partitionKey defined. The index does not need to actually exist in the table
  - Custom Resolver: A function to define custom join logic, with the signature (parent, child) => boolean. It returns true if the entities should be joined.
- join (Optional): A nested configuration for joining other entities that are related to the current entity. You can create complex join chains by adding more entities within this property. The structure of each nested join follows the same format as the root-level join.

Returns

A Collection to be used both for type definition and table extraction.

Extracting Collection Type

A GetCollectionType is exposed for you to infer correctly its type using type YourType = GetCollectionType<typeof yourCollection>

Example Usage

const userPartition = table.schema.createPartition({
  name: 'USER_PARTITION',

  getPartitionKey: ({ userId }: { userId: string }) => ['USER', userId],

  entries: {
    mainData: () => ['#DATA'],

    permissions: ({ permissionId }: { permissionId: string }) => ['PERMISSION', permissionId],

    loginAttempt: ({ timestamp }: { timestamp: string }) => ['LOGIN_ATTEMPT', timestamp],

    orders: ({ orderId }: { { orderId: string } }) => ['ORDER', orderId],
  },
})

type tUser = {
  id: string;
  name: string;
  createdAt: string;
  email: string;
  updatedAt?: string;
}

type tUserLoginAttempt = {
  userId: string;
  timestamp: string;
  success: boolean;
  ip: string;
}

const User = userPartition.use('mainData').create<tUser>().entity({
  type: 'USER',

  paramMatch: {
    userId: 'id'
  },
})

const UserLoginAttempt = userPartition.use('loginAttempt').create<tUserLoginAttempt>().entity({
  type: 'USER_LOGIN_ATTEMPT',
})

const userWithLoginAttemptsCollection = createCollection({
  ref: User,

  join: {
    logins: {
      entity: UserLoginAttempt,

      type: 'MULTIPLE',

      joinBy: 'TYPE',
    },
  },

  type: 'SINGLE',

  partition: userPartition,
});

/*
  UserWithLoginAttempts = tUser & { logins: tUserLoginAttempt[] }
*/
type UserWithLoginAttempts = GetCollectionType<typeof userWithLoginAttemptsCollection>

Or, creating simply the user's attempts and permissions:

type tUserPermission = {
  permissionId: string;
  timestamp: string;
  addedBy: string;
}

const UserPermission = userPartition.use('permissions').create<tUserPermission>().entity({
  type: 'USER_PERMISSION',
})

const someCollection = createCollection({
  ref: null, // this!

  join: {
    logins: {
      entity: UserLoginAttempt,

      type: 'MULTIPLE',

      joinBy: 'TYPE',
    },

    permissions: {
      entity: UserPermission,

      type: 'MULTIPLE',

      joinBy: 'TYPE',

      extractor: ({ permissionId }: tUserPermission) => permissionId,
    }
  },

  type: 'SINGLE',

  partition: userPartition,
});

/*
  YourCollection = { logins: tUserLoginAttempt[], permissions: string[] }
*/
type YourCollection = GetCollectionType<typeof someCollection>

Using your collection

Same as with the entity, you can now leverage the schema to execute actions on your collection.

For now, only the get method is exposed:

const userWithAttempts = await table.schema.fromCollection(userWithLoginAttemptsCollection).get({
  // its the partition param passed to the collection!
  userId: 'user-id-12',
})

And thats it! The result will be of the expected type (or undefined if not found, since its a SINGLE collection)

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Dynamo DB Provider

Introduction

Three part lib

1. DynamoDB Provider (client)

Using v2

Using v3

Configuration params

logCallParams

Provider Methods

get

Signature

Parameters

GetItemParams<Entity, PKs>

Return Value

Usage

Error Handling

create

Method Signature

Method Signature

Valid Conditions

delete

Method Signature

Parameters

Return Value

Example Usage

update

Method Signature

Parameters

Return Value

Example Usage

batchGet

Method Signature

Parameters

Return Value

Example Usage

list

Method Signature

Parameters

Advanced Filter Options

Return Value

Example Usage

listAll

Method Signature

Parameters

Return Value

Key Differences from list

Example Usage

query

Method Signature

Parameters

Return Value

Example Usage

executeTransaction Method

Description

Method Signature

Parameters

Example Usage

Helper methods

create set

generate transaction config list

Single table

Parameters

dynamodbProvider

keySeparator

table

partitionKey

rangeKey

typeIndex

expiresAt

indexes

autoRemoveTableProperties

keepTypeProperty

propertyCleanup

blockInternalPropUpdate

`list`

`listAll`

Key Differences from `list`

`executeTransaction` Method

`dynamodbProvider`

`keySeparator`

`table`

`partitionKey`

`rangeKey`

`typeIndex`

`expiresAt`

`indexes`

`autoRemoveTableProperties`

`keepTypeProperty`

`propertyCleanup`

`blockInternalPropUpdate`

`badUpdateValidation`

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