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TypeScript library that provides a simplified interface for interacting with Amazon DynamoDB, using the AWS SDK v3.","maintainers":[{"name":"feliperohdee","email":"feliperohdee@gmail.com"}],"readme":"# Use DynamoDB\n\nA TypeScript library that provides a simplified interface for interacting with Amazon DynamoDB, using the AWS SDK v3.\n\n[![TypeScript](https://img.shields.io/badge/-TypeScript-3178C6?style=flat-square&logo=typescript&logoColor=white)](https://www.typescriptlang.org/)\n[![Vitest](https://img.shields.io/badge/-Vitest-729B1B?style=flat-square&logo=vitest&logoColor=white)](https://vitest.dev/)\n[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)\n\n## 🚀 Features\n\n- ✅ Type-safe CRUD operations (Create, Read, Update, Delete)\n- 🔍 Flexible secondary index configuration:\n  - Automatic LSI/GSI determination based on partition key\n  - Optional forcing of GSI with forceGlobal flag\n  - Customizable attribute projections\n  - Support for both string and number key types\n- 📦 Batch operations with automatic chunking\n- 🔎 Query and Scan operations with filtering\n- 🔄 Optimistic locking with versioning\n- 📄 Automatic pagination\n- 🕒 Built-in timestamp management (**createdAt, **updatedAt, \\_\\_ts)\n- 🔒 Conditional updates and transactions\n- 🎯 Change tracking with callbacks\n- 🔄 Configurable retry strategy\n\n## 📦 Installation\n\n```bash\nyarn add use-dynamodb\n```\n\n## 🛠️ Usage\n\n### Initialization\n\nThe library supports several configuration options for customizing its behavior:\n\n#### Basic Configuration\n\n- `accessKeyId` and `secretAccessKey`: Your AWS credentials\n- `region`: AWS region for DynamoDB\n- `table`: Name of your DynamoDB table\n- `schema`: Defines the table's partition and sort keys\n- `indexes`: Array of GSI (Global Secondary Indexes) and LSI (Local Secondary Indexes) configurations\n\nExample with both formats:\n\n```typescript\nimport Dynamodb from 'use-dynamodb';\n\ntype Item = {\n\tpk: string;\n\tsk: string;\n\ttitle: string;\n\tcategory: string;\n\ttags: string[];\n};\n\nconst db = new Dynamodb<Item>({\n\taccessKeyId: 'YOUR_ACCESS_KEY',\n\tsecretAccessKey: 'YOUR_SECRET_KEY',\n\tregion: 'us-east-1',\n\ttable: 'YOUR_TABLE_NAME',\n\tschema: {\n\t\tpartition: 'pk',\n\t\tsort: 'sk',\n\t\tsortType: 'S' // Optional, defaults to 'S'\n\t},\n\tindexes: [\n\t\t{\n\t\t\tname: 'status-index',\n\t\t\tpartition: 'status',\n\t\t\tpartitionType: 'S',\n\t\t\tsort: 'createdAt',\n\t\t\tsortType: 'S',\n\t\t\tforceGlobal: true, // Forces the index to be GSI even if it shares partition key\n\t\t\tprojection: {\n\t\t\t\ttype: 'INCLUDE',\n\t\t\t\tnonKeyAttributes: ['title', 'description']\n\t\t\t}\n\t\t}\n\t]\n});\n```\n\n### Index Projections\n\nThe library supports configuring projections for both Global Secondary Indexes (GSI) and Local Secondary Indexes (LSI). You can specify which attributes should be projected into the index using the `projection` property:\n\n```typescript\nconst db = new Dynamodb<Item>({\n\t// ... other config\n\tindexes: [\n\t\t{\n\t\t\tname: 'status-index',\n\t\t\tpartition: 'status',\n\t\t\tpartitionType: 'S',\n\t\t\tsort: 'createdAt',\n\t\t\tsortType: 'S',\n\t\t\tprojection: {\n\t\t\t\ttype: 'INCLUDE', // Can be 'ALL', 'KEYS_ONLY', or 'INCLUDE'\n\t\t\t\tnonKeyAttributes: ['title', 'description'] // Required when type is 'INCLUDE'\n\t\t\t}\n\t\t},\n\t\t{\n\t\t\tname: 'category-index',\n\t\t\tpartition: 'category',\n\t\t\tpartitionType: 'S',\n\t\t\tprojection: {\n\t\t\t\ttype: 'ALL' // Project all attributes\n\t\t\t}\n\t\t},\n\t\t{\n\t\t\tname: 'date-index',\n\t\t\tpartition: 'date',\n\t\t\tpartitionType: 'S',\n\t\t\tprojection: {\n\t\t\t\ttype: 'KEYS_ONLY' // Only project key attributes\n\t\t\t}\n\t\t}\n\t]\n});\n```\n\nThe `projection` configuration supports three types:\n\n- `ALL` - Projects all attributes from the base table\n- `KEYS_ONLY` - Projects only the index and primary keys\n- `INCLUDE` - Projects only the specified attributes via `nonKeyAttributes`\n\nUsing projections effectively can help optimize storage costs and improve query performance by limiting the attributes stored in secondary indexes.\n\nThe transform function allows you to:\n\n- Modify values before they're combined\n- Filter out values by returning undefined\n- Apply custom formatting or normalization\n- Handle different data types appropriately\n\n### Table Operations\n\n#### Create Table\n\n```typescript\nawait db.createTable();\n```\n\n### Basic Operations\n\n#### Put Item\n\n```typescript\n// Simple put with automatic condition to prevent overwrites\nconst item = await db.put({\n\tpk: 'user#123',\n\tsk: 'profile',\n\tfoo: 'bar'\n});\n\n// Put with overwrite allowed\nconst overwrittenItem = await db.put(\n\t{\n\t\tpk: 'user#123',\n\t\tsk: 'profile',\n\t\tfoo: 'baz'\n\t},\n\t{\n\t\toverwrite: true\n\t}\n);\n\n// Put with conditions\nconst conditionalItem = await db.put(\n\t{\n\t\tpk: 'user#123',\n\t\tsk: 'profile',\n\t\tfoo: 'bar'\n\t},\n\t{\n\t\tattributeNames: { '#foo': 'foo' },\n\t\tattributeValues: { ':foo': 'bar' },\n\t\tconditionExpression: '#foo <> :foo'\n\t}\n);\n```\n\n#### Get Item\n\n```typescript\n// Get by partition and sort key\nconst item = await db.get({\n\titem: { pk: 'user#123', sk: 'profile' }\n});\n\n// Get with specific attributes\nconst partialItem = await db.get({\n\titem: { pk: 'user#123', sk: 'profile' },\n\tselect: ['foo']\n});\n\n// Get using query expression\nconst queriedItem = await db.get({\n\tattributeNames: { '#pk': 'pk' },\n\tattributeValues: { ':pk': 'user#123' },\n\tqueryExpression: '#pk = :pk'\n});\n\n// Get last by partition and sort key\nconst item = await db.getLast({\n\titem: { pk: 'user#123', sk: 'profile' }\n});\n```\n\n**Note:** `select` always includes the key attributes in the projection: the table's partition and sort keys, plus the index's partition and sort keys when the call uses an index. They come back in the returned items, so `lastEvaluatedKey` pagination and `batchGet` with `returnNullIfNotFound` keep working with any `select` (`get`, `query`, `scan`, `batchGet`).\n\n#### Update Item\n\n```typescript\n// Update using function\nconst updatedItem = await db.update({\n\tfilter: {\n\t\titem: { pk: 'user#123', sk: 'profile' }\n\t},\n\tupdateFunction: item => ({\n\t\t...item,\n\t\tfoo: 'updated'\n\t})\n});\n\n// Update using expression\nconst expressionUpdatedItem = await db.update({\n\tfilter: {\n\t\titem: { pk: 'user#123', sk: 'profile' }\n\t},\n\tattributeNames: { '#foo': 'foo' },\n\tattributeValues: { ':foo': 'updated' },\n\tupdateExpression: 'SET #foo = :foo'\n});\n\n// Upsert\nconst upsertedItem = await db.update({\n\tfilter: {\n\t\titem: { pk: 'user#123', sk: 'profile' }\n\t},\n\tupdateFunction: item => ({\n\t\t...item,\n\t\tfoo: 'new'\n\t}),\n\tupsert: true\n});\n\n// Update with partition/sort key change\nconst movedItem = await db.update({\n\tallowUpdatePartitionAndSort: true,\n\tfilter: {\n\t\titem: { pk: 'user#123', sk: 'profile' }\n\t},\n\tupdateFunction: item => ({\n\t\t...item,\n\t\tpk: 'user#124'\n\t})\n});\n```\n\n#### Delete Item\n\n```typescript\n// Delete by key\nconst deletedItem = await db.delete({\n\tfilter: {\n\t\titem: { pk: 'user#123', sk: 'profile' }\n\t}\n});\n\n// Delete with condition\nconst conditionalDelete = await db.delete({\n\tattributeNames: { '#foo': 'foo' },\n\tattributeValues: { ':foo': 'bar' },\n\tconditionExpression: '#foo = :foo',\n\tfilter: {\n\t\titem: { pk: 'user#123', sk: 'profile' }\n\t}\n});\n```\n\n### Query Operations\n\n```typescript\n// Query by partition key\nconst { items, count, lastEvaluatedKey } = await db.query({\n\titem: { pk: 'user#123' }\n});\n\n// Query with prefix matching\nconst prefixResults = await db.query({\n\titem: { pk: 'user#123', sk: 'profile#' },\n\tprefix: true\n});\n\n// Query with filter\nconst filteredResults = await db.query({\n\tattributeNames: { '#foo': 'foo' },\n\tattributeValues: { ':foo': 'bar' },\n\tfilterExpression: '#foo = :foo',\n\titem: { pk: 'user#123' }\n});\n\n// Query with pagination\nconst paginatedResults = await db.query({\n\titem: { pk: 'user#123' },\n\tlimit: 10,\n\tstartKey: lastEvaluatedKey\n});\n\n// Query using index\nconst indexResults = await db.query({\n\titem: { gsiPk: 'status#active' },\n\tindex: 'gs-index'\n});\n\n// Query with chunks processing\nconst chunkedResults = await db.query({\n\titem: { pk: 'user#123' },\n\tchunkLimit: 10,\n\tonChunk: async ({ items, count }) => {\n\t\t// Process items in chunks\n\t\tconsole.log(`Processing ${count} items`);\n\t}\n});\n```\n\n### Scan Operations\n\n```typescript\n// Basic scan\nconst { items, count, lastEvaluatedKey } = await db.scan();\n\n// Filtered scan\nconst filteredScan = await db.scan({\n\tattributeNames: { '#foo': 'foo' },\n\tattributeValues: { ':foo': 'bar' },\n\tfilterExpression: '#foo = :foo'\n});\n\n// Scan with selection\nconst partialScan = await db.scan({\n\tselect: ['foo', 'bar']\n});\n\n// Paginated scan\nconst paginatedScan = await db.scan({\n\tlimit: 10,\n\tstartKey: lastEvaluatedKey\n});\n```\n\n#### `scanAllPartition`\n\nEfficiently scans all items within a single partition by dividing the data into segments and querying them in parallel. This is particularly useful for processing large partitions that might otherwise exceed query limits or timeouts. This method requires the table to have a sort key.\n\n**Note:** When using `segmentsSize`, the method first performs a query to retrieve all sort keys for the partition to calculate the segments. This initial query can be costly for extremely large partitions. For better performance in such cases, consider providing pre-calculated `segments`.\n\n```typescript\n// Scan an entire partition in parallel, with 20 items per segment\nconst { items, count } = await db.scanAllPartition({\n\tpartitionKey: 'product-category#electronics',\n\tsegmentsSize: 20,\n\tmaxConcurrency: 10 // Optional: number of parallel queries, defaults to 10\n});\n\n// Scan using manually defined segments\nconst { items: manualSegmentItems } = await db.scanAllPartition({\n\tpartitionKey: 'product-category#electronics',\n\tsegments: [\n\t\t[null, 'item-100'], // from beginning to item-100\n\t\t['item-101', 'item-200'], // from item-101 to item-200\n\t\t['item-201', null] // from item-201 to the end\n\t]\n});\n```\n\n### Batch Operations\n\n```typescript\n// Batch write\nconst items = await db.batchWrite([\n\t{ pk: 'user#1', sk: 'profile', foo: 'bar' },\n\t{ pk: 'user#2', sk: 'profile', foo: 'baz' }\n]);\n\n// Batch get (rows come back in the order of the keys)\nconst retrievedItems = await db.batchGet([\n\t{ pk: 'user#1', sk: 'profile' },\n\t{ pk: 'user#2', sk: 'profile' }\n]);\n\n// Batch delete\nconst deletedItems = await db.batchDelete([\n\t{ pk: 'user#1', sk: 'profile' },\n\t{ pk: 'user#2', sk: 'profile' }\n]);\n\n// Clear table\nawait db.clear(); // Clear entire table\nawait db.clear('user#123'); // Clear by partition key\n```\n\n### Filter Operations\n\n```typescript\n// Filter is a higher-level abstraction that combines query and scan\nconst results = await db.filter({\n\titem: { pk: 'user#123' }, // Uses query\n\t// OR\n\tqueryExpression: '#pk = :pk', // Uses query\n\t// OR\n\tfilterExpression: '#status = :status' // Uses scan\n});\n```\n\n## Types\n\n### Key Types\n\n```typescript\ntype TableSchema = {\n\tpartition: string;\n\tsort?: string;\n\tsortType?: 'S' | 'N';\n};\n\ntype TableIndex = {\n\tforceGlobal?: boolean;\n\tname: string;\n\tpartition: string;\n\tpartitionType: 'S' | 'N';\n\tprojection?: IndexProjection;\n\tsort?: string;\n\tsortType?: 'S' | 'N';\n};\n\ntype IndexProjection = {\n\ttype: 'ALL' | 'KEYS_ONLY' | 'INCLUDE';\n\tnonKeyAttributes?: string[]; // Required when type is 'INCLUDE'\n};\n```\n\n### Item Types\n\n```typescript\ntype Dict = Record<string, any>;\n\ntype PersistedItem<T extends Dict = Dict> = T & {\n\t__createdAt: string;\n\t__ts: number;\n\t__updatedAt: string;\n};\n```\n\n### Change Tracking\n\n```typescript\ntype ChangeType = 'PUT' | 'UPDATE' | 'DELETE';\n\ntype ChangeEvent<T extends Dict = Dict> = {\n\titem: PersistedItem<T>;\n\tpartition: string;\n\tsort?: string | null;\n\ttable: string;\n\ttype: ChangeType;\n};\n\ntype OnChange<T extends Dict = Dict> = (events: ChangeEvent<T>[]) => Promise<void>;\n```\n\n## 🧪 Testing\n\n```bash\n# Set environment variables\nexport AWS_ACCESS_KEY='YOUR_ACCESS_KEY'\nexport AWS_SECRET_KEY='YOUR_SECRET_KEY'\n\n# Run tests\nyarn test\n```\n\n## 📝 Notes\n\n- The library automatically handles optimistic locking using the `__ts` attribute\n- All write operations (put, update, delete) trigger change events if an onChange handler is provided\n- Batch operations automatically handle chunking according to DynamoDB limits, and resend unprocessed keys/items with exponential backoff (up to 8 attempts, then they throw)\n- All timestamps are managed automatically (**createdAt, **updatedAt, \\_\\_ts)\n- Queries automatically handle pagination for large result sets\n- Indexes are automatically determined as LSI or GSI based on their partition key, with ability to force GSI using forceGlobal flag\n\n## 📝 License\n\nMIT © [Felipe Rohde](mailto:feliperohdee@gmail.com)\n\n## ⭐ Show your support\n\nGive a ⭐️ if this project helped you!\n\n## 👨‍💻 Author\n\n**Felipe Rohde**\n\n- Twitter: [@felipe_rohde](https://twitter.com/felipe_rohde)\n- Github: [@feliperohdee](https://github.com/feliperohdee)\n- Email: feliperohdee@gmail.com\n\n## 🙏 Acknowledgements\n\n- [AWS SDK for JavaScript v3](https://github.com/aws/aws-sdk-js-v3)\n- [Amazon DynamoDB](https://aws.amazon.com/dynamodb/)\n","readmeFilename":"README.md"}