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type-safe query builder for TaylorDB","maintainers":[{"name":"adilovcode","email":"adilovcode@gmail.com"},{"name":"thetaung","email":"thetaung.dev@gmail.com"},{"name":"mythli","email":"npm@mythli.net"}],"readme":"# @taylordb/query-builder\n\n<img src=\"../../docs/media/logo.png\" width=\"200\" />\n\nThis package contains the official TypeScript query builder for TaylorDB. It provides a type-safe and intuitive API for building and executing queries against your TaylorDB database.\n\n## Features\n\n- **Type-Safe Queries**: Leverage your database schema to get full type safety and autocompletion for your queries.\n- **Runtime Schema Metadata**: Generated schemas are real JavaScript objects, so applications can inspect field types, required flags, select options, and link targets at runtime.\n- **Fluent API**: Chain methods together to build complex queries with ease.\n- **CRUD Operations**: Full support for `select`, `insert`, `update`, and `delete` operations.\n- **Advanced Filtering**: Filter your data with a rich set of operators and logical conjunctions.\n- **Pagination and Sorting**: Easily paginate and sort your query results.\n- **Batch Queries**: Execute multiple queries in a single request for improved performance.\n- **Aggregation Queries**: Perform powerful aggregation queries with grouping and aggregate functions.\n- **Transaction Support**: Execute multiple operations in a single atomic transaction.\n- **Attachment Uploads**: Upload files and link them to your records.\n\n## Getting Started\n\nFirst, you'll need to generate a `taylorclient.types.ts` file from your TaylorDB schema. You can do this using the TaylorDB CLI:\n\n```bash\nnpx @taylordb/cli generate-schema\n```\n\nThe generated file exports both a runtime schema object and the inferred `TaylorDatabase` type:\n\n```typescript\nimport { createQueryBuilder } from '@taylordb/query-builder';\nimport { TaylorDatabase, taylorSchema } from './taylorclient.types';\n\nconst qb = createQueryBuilder<TaylorDatabase>({\n  baseUrl: 'YOUR_TAYLORDB_BASE_URL',\n  apiKey: 'YOUR_TAYLORDB_API_KEY',\n  baseId: 'YOUR_TAYLORDB_BASE_ID',\n});\n\n// Runtime metadata is available to your app for validation/UI.\nconst statusOptions = taylorSchema.backlog.status.options;\n```\n\n`TaylorDatabase` is inferred from `typeof taylorSchema`, so query-builder type safety and runtime validation metadata stay in sync.\n\n### Runtime Schema Helpers\n\nThe CLI emits `taylorSchema` using helpers exported from `@taylordb/query-builder`:\n\n```typescript\nimport {\n  defineTaylorSchema,\n  singleLineTextField,\n  selectField,\n  linkField,\n} from '@taylordb/query-builder';\nimport type { InferTaylorDatabase } from '@taylordb/query-builder';\n\nexport const taylorSchema = defineTaylorSchema({\n  backlog: {\n    title: singleLineTextField({ required: false }),\n    status: selectField({\n      required: false,\n      mode: 'single',\n      options: ['Todo', 'Done'] as const,\n    }),\n    sprint: linkField({ required: false, linkedTo: 'sprints' }),\n  },\n});\n\nexport type TaylorDatabase = InferTaylorDatabase<typeof taylorSchema>;\n```\n\nAvailable field helpers include the generic helpers (`textField`, `numberField`, `checkboxField`, `dateField`, `searchField`, `linkField`, `attachmentField`, `selectField`, `autoNumberField`, `autoDateField`) plus field-specific Bamboo helpers such as `singleLineTextField`, `longTextField`, `jsonField`, `urlField`, `emailField`, `phoneNumberField`, `currencyField`, `percentField`, `countField`, `positionField`, `ratingField`, `durationField`, `createdAtField`, `updatedAtField`, `modifiedAtField`, `collaboratorsField`, `modifiedByField`, `createdByField`, `formulaField`, `lookupField`, `rollupField`, and `buttonField`.\n\n### Reusable Exported Types\n\n`@taylordb/query-builder` exports the same TypeScript helper types used by the builders, so application code can type values that pass through functions, forms, API handlers, or reusable components before calling the fluent API.\n\n```typescript\nimport type {\n  ColumnNames,\n  FieldWithDirection,\n  Filters,\n  FiltersSet,\n  InferActionInput,\n  InferActionResult,\n  Insertable,\n  LimitOffset,\n  Updatable,\n} from '@taylordb/query-builder';\nimport type { TaylorDatabase } from './taylorclient.types';\n\ntype CustomerCreate = Insertable<TaylorDatabase['customers']>;\ntype CustomerUpdate = Updatable<TaylorDatabase['customers']>;\ntype CustomerField = ColumnNames<TaylorDatabase['customers']> & string;\n\nconst newCustomer: CustomerCreate = {\n  firstName: 'Jane',\n  lastName: 'Doe',\n};\n\nconst customerPatch: CustomerUpdate = {\n  lastName: 'Smith',\n};\n\nconst activeCustomerFilter: Filters<CustomerField> = {\n  field: 'status',\n  operator: '=',\n  value: 'Active',\n};\n\nconst customerFilters: FiltersSet<CustomerField> = {\n  conjunction: 'and',\n  filtersSet: [\n    activeCustomerFilter,\n    { field: 'lastName', operator: 'isNotEmpty' },\n  ],\n};\n\nconst sort: FieldWithDirection<CustomerField> = {\n  field: 'lastName',\n  direction: 'asc',\n};\n\nconst pagination: LimitOffset = {\n  limit: 25,\n  offset: 0,\n};\n\ntype SendEmailInput = InferActionInput<TaylorDatabase, 'email', 'send'>;\ntype SendEmailResult = InferActionResult<TaylorDatabase, 'email', 'send'>;\n```\n\nRelated exported types include `TableNames`, `NonLinkColumnNames`, `LinkColumnNames`, `AggregateRecord`, `Aggregates`, `MetricsRecord`, `PaginationRequest`, `GroupingConfiguration`, `InsertNode`, `UpdateNode`, and `DeleteNode`.\n\n## Usage\n\n### Selecting Data\n\nYou can select data from a table using the `selectFrom` method. You can specify which fields to return, and you can filter, sort, and paginate the results.\n\n```typescript\nconst customers = await qb\n  .selectFrom('customers')\n  .select(['firstName', 'lastName'])\n  .where('firstName', '=', 'John')\n  .orderBy('lastName', 'asc')\n  .paginate(1, 10)\n  .execute();\n```\n\n#### Counting Records\n\nUse the `count()` method to get the total number of records that match your query. This is useful for pagination, statistics, or checking if records exist.\n\n```typescript\n// Count all users\nconst totalUsers = await qb\n  .selectFrom('users')\n  .count();\n\nconsole.log(`Total users: ${totalUsers}`);\n\n// Count with filters\nconst activeUsers = await qb\n  .selectFrom('users')\n  .where('status', '=', 'active')\n  .where('age', '>', 18)\n  .count();\n\nconsole.log(`Active adult users: ${activeUsers}`);\n\n// Count with relations filter\nconst usersWithPosts = await qb\n  .selectFrom('users')\n  .where('posts', 'isNotEmpty')\n  .count();\n\nconsole.log(`Users with posts: ${usersWithPosts}`);\n```\n\n**Note**: The `count()` method returns a `Promise<number>` directly (not an array), and it respects all filters, pagination, and sorting you've applied to the query.\n\n### Inserting Data\n\nYou can insert data into a table using the `insertInto` method.\n\n```typescript\nconst newCustomer = await qb\n  .insertInto('customers')\n  .values({\n    firstName: 'Jane',\n    lastName: 'Doe',\n  })\n  .execute();\n```\n\n### Updating Data\n\nYou can update data in a table using the `update` method.\n\n```typescript\nconst updatedCustomer = await qb\n  .update('customers')\n  .set({ lastName: 'Smith' })\n  .where('id', '=', 1)\n  .execute();\n```\n\n### Deleting Data\n\nYou can delete data from a table using the `deleteFrom` method.\n\n```typescript\nconst result = await qb.deleteFrom('customers').where('id', '=', 1).execute();\n```\n\n### Transactions\n\nYou can execute a series of operations within a single atomic transaction. If any operation within the transaction fails, all previous operations will be rolled back.\n\n```typescript\nconst newCustomer = await qb.transaction(async tx => {\n  const customer = await tx\n    .insertInto('customers')\n    .values({\n      firstName: 'John',\n      lastName: 'Doe',\n    })\n    .executeTakeFirst();\n\n  if (!customer) {\n    throw new Error('Customer creation failed.');\n  }\n\n  await tx\n    .insertInto('orders')\n    .values({\n      customerId: customer.id,\n      orderDate: new Date().toISOString(),\n      total: 100,\n    })\n    .execute();\n\n  return customer;\n});\n```\n\n### Handling Attachments\n\nYou can upload files and associate them with your records using the `uploadAttachments` method. This is useful for handling things like user avatars, product images, or any other file-based data.\n\nFirst, upload the file(s) to get `Attachment` instances:\n\n```typescript\nconst filesToUpload = [\n  { file: new Blob(['file content']), name: 'avatar.png' },\n];\nconst attachments = await qb.uploadAttachments(filesToUpload);\n```\n\nThen, you can use the returned `Attachment` instances when creating or updating records. The query builder will automatically convert them into the correct format.\n\n```typescript\n// Create a new customer with an avatar\nconst newCustomer = await qb\n  .insertInto('customers')\n  .values({\n    firstName: 'Jane',\n    lastName: 'Doe',\n    avatar: attachments[0], // Use the Attachment instance\n  })\n  .executeTakeFirst();\n\n// Update an existing customer's avatar\nconst { affectedRecords } = await qb\n  .update('customers')\n  .set({\n    avatar: attachments[0], // Use the Attachment instance\n  })\n  .where('id', '=', 1)\n  .execute();\n```\n\n### Batch Queries\n\nYou can execute multiple queries in a single batch request for improved performance. The result will be a tuple that corresponds to the results of each query in the batch.\n\n```typescript\nconst [customers, newCustomer] = await qb\n  .batch([\n    qb.selectFrom('customers').select(['firstName', 'lastName']),\n    qb.insertInto('customers').values({ firstName: 'John', lastName: 'Doe' }),\n  ])\n  .execute();\n```\n\n### Aggregation Queries\n\nYou can perform powerful aggregation queries using the `aggregateFrom` method. You can group by one or more fields and specify aggregate functions to apply.\n\n```typescript\nimport { count, sum } from '@taylordb/query-builder';\n\nconst aggregates = await qb\n  .aggregateFrom('customers')\n  .groupBy('firstName', 'asc')\n  .groupBy('lastName', 'desc')\n  .metrics({\n    idCount: count('id'),\n    idSum: sum('id'),\n  })\n  .execute();\n```\n\n## Recipes\n\n### Select with Relations\n\nYou can use the `with` method to fetch related records from a linked table.\n\n```typescript\n// Assuming 'customers' has a link field 'orders' to the 'orders' table\nconst customersWithOrders = await qb\n  .selectFrom('customers')\n  .select(['firstName', 'lastName'])\n  .with({\n    orders: qb => qb.select(['orderDate', 'total']),\n  })\n  .execute();\n```\n\n### Cross-Filters\n\nYou can filter records in one table based on the values in a linked table.\n\n```typescript\n// Get all customers who have placed an order with a total greater than 100\nconst highValueCustomers = await qb\n  .selectFrom('customers')\n  .where('orders', 'hasAnyOf', qb => qb.where('total', '>', 100))\n  .execute();\n```\n\n### Conditional Updates\n\nYou can use `where` clauses to update only the records that match a specific condition.\n\n```typescript\n// Update the status of all orders placed before a certain date\nconst { affectedRecords } = await qb\n  .update('orders')\n  .set({ status: 'archived' })\n  .where('orderDate', '<', '2023-01-01')\n  .execute();\n```\n","readmeFilename":"README.md"}