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An unfaithful port of Linq to Sql to Typescript

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# Tinqer

A type-safe query builder for TypeScript. Queries are expressed as inline arrow functions, parsed into an expression tree, and compiled into SQL for PostgreSQL or SQLite. The API is similar to DotNet's LINQ-based frameworks.

## Installation

Install the core library and adapter for your database:

```bash
# Core library
npm install @tinqerjs/tinqer

# PostgreSQL adapter (pg-promise)
npm install @tinqerjs/pg-promise-adapter

# SQLite adapter (better-sqlite3)
npm install @tinqerjs/better-sqlite3-adapter
```

## Quick Start

### PostgreSQL Example

```typescript
import { createSchema } from "@tinqerjs/tinqer";
import { executeSelect } from "@tinqerjs/pg-promise-adapter";
import pgPromise from "pg-promise";

interface Schema {
  users: {
    id: number;
    name: string;
    email: string;
    age: number;
  };
}

const pgp = pgPromise();
const db = pgp("postgresql://user:pass@localhost:5432/mydb");
const schema = createSchema<Schema>();

const results = await executeSelect(
  db,
  schema,
  (q, params: { minAge: number }) =>
    q
      .from("users")
      .where((u) => u.age >= params.minAge)
      .orderBy((u) => u.name)
      .select((u) => ({ id: u.id, name: u.name })),
  { minAge: 18 },
);
// results: [{ id: 1, name: "Alice" }, { id: 2, name: "Bob" }]
```

**The same query works with SQLite** - just change the adapter and database connection:

```typescript
import Database from "better-sqlite3";
import { createSchema } from "@tinqerjs/tinqer";
import { executeSelect } from "@tinqerjs/better-sqlite3-adapter";

// Same schema definition
interface Schema {
  users: {
    id: number;
    name: string;
    email: string;
    age: number;
  };
}

const db = new Database("./data.db");
const schema = createSchema<Schema>();

// Identical query logic
const results = executeSelect(
  db,
  schema,
  (q, params: { minAge: number }) =>
    q
      .from("users")
      .where((u) => u.age >= params.minAge)
      .orderBy((u) => u.name)
      .select((u) => ({ id: u.id, name: u.name })),
  { minAge: 18 },
);
// results: [{ id: 1, name: "Alice" }, { id: 2, name: "Bob" }]
```

### SQL Generation Without Execution

**`execute*` functions** execute queries and return results. **`toSql` function** generates SQL and parameters without executing - useful for debugging, logging, or custom execution:

```typescript
import {
  createSchema,
  defineSelect,
  defineInsert,
  defineUpdate,
  defineDelete,
} from "@tinqerjs/tinqer";
import { toSql } from "@tinqerjs/pg-promise-adapter";

interface Schema {
  users: { id: number; name: string; age: number };
}

const schema = createSchema<Schema>();

// SELECT - returns { sql, params }
const select = toSql(
  defineSelect(schema, (q, params: { minAge: number }) =>
    q.from("users").where((u) => u.age >= params.minAge),
  ),
  { minAge: 18 },
);
// select.sql: SELECT * FROM "users" WHERE "age" >= $(minAge)
// select.params: { minAge: 18 }

// INSERT
const insert = toSql(
  defineInsert(schema, (q, params: { name: string; age: number }) =>
    q.insertInto("users").values({ name: params.name, age: params.age }),
  ),
  { name: "Alice", age: 30 },
);
// insert.sql: INSERT INTO "users" ("name", "age") VALUES ($(name), $(age))

// UPSERT (PostgreSQL + SQLite)
const upsert = toSql(
  defineInsert(schema, (q, params: { id: number; name: string; age: number }) =>
    q
      .insertInto("users")
      .values({ id: params.id, name: params.name, age: params.age })
      .onConflict((u) => u.id)
      .doUpdateSet((_existing, excluded) => ({ name: excluded.name, age: excluded.age })),
  ),
  { id: 1, name: "Alice", age: 30 },
);
// upsert.sql: INSERT INTO "users" (...) VALUES (...) ON CONFLICT ("id") DO UPDATE SET ...

// UPDATE
const update = toSql(
  defineUpdate(schema, (q, params: { newAge: number; userId: number }) =>
    q
      .update("users")
      .set({ age: params.newAge })
      .where((u) => u.id === params.userId),
  ),
  { newAge: 31, userId: 1 },
);
// update.sql: UPDATE "users" SET "age" = $(newAge) WHERE "id" = $(userId)

// DELETE
const del = toSql(
  defineDelete(schema, (q, params: { minAge: number }) =>
    q.deleteFrom("users").where((u) => u.age < params.minAge),
  ),
  { minAge: 18 },
);
// del.sql: DELETE FROM "users" WHERE "age" < $(minAge)
```

## Core Features

### Type-Safe Query Building

```typescript
const schema = createSchema<Schema>();

// Full TypeScript type inference
const query = (q) =>
  q
    .from("users")
    .where((u) => u.age >= 18 && u.email.includes("@company.com"))
    .orderBy((u) => u.name)
    .select((u) => ({ id: u.id, name: u.name, email: u.email }));

// The query builder returns a Queryable whose result type is inferred as
// { id: number; name: string; email: string }
```

### Query Composition

Query plans are **immutable and composable** - you can chain operations onto plan handles to create reusable base queries and branch into specialized variations.

#### Chaining Operations on Plans

```typescript
import { defineSelect } from "@tinqerjs/tinqer";
import { toSql } from "@tinqerjs/pg-promise-adapter";

const schema = createSchema<Schema>();

// Start with base query
const plan = defineSelect(schema, (q) => q.from("users"))
  .where((u) => u.age > 18)
  .where((u) => u.isActive)
  .orderBy((u) => u.name)
  .select((u) => ({ id: u.id, name: u.name }));

const { sql, params } = toSql(plan, {});
```

#### Reusable Base Queries

Plans are immutable - each operation returns a new plan without modifying the original. This enables creating base queries and branching:

```typescript
type DeptParams = { dept: number };

// Reusable base query
const usersInDept = defineSelect(schema, (q, p: DeptParams) =>
  q.from("users").where((u) => u.departmentId === p.dept),
);

// Branch 1: Active users only
const activeUsers = usersInDept
  .where((u) => u.isActive === true)
  .where<{ minAge: number }>((u, p) => u.age >= p.minAge);

// Branch 2: Inactive users only
const inactiveUsers = usersInDept
  .where((u) => u.isActive === false)
  .where<{ maxAge: number }>((u, p) => u.age <= p.maxAge);

// Execute branches with different parameters
toSql(activeUsers, { dept: 1, minAge: 25 });
toSql(inactiveUsers, { dept: 1, maxAge: 65 });
```

#### Parameter Accumulation

Parameters from the builder function and chained operations are merged:

```typescript
type BuilderParams = { baseAge: number };
type ChainParams = { maxAge: number };

const plan = defineSelect(schema, (q, p: BuilderParams) =>
  q.from("users").where((u) => u.age > p.baseAge),
).where<ChainParams>((u, p) => u.age < p.maxAge);

// Must provide both parameter types
toSql(plan, { baseAge: 18, maxAge: 65 });
```

Composition works with all operations: `defineSelect`, `defineInsert`, `defineUpdate`, `defineDelete`.

### Row Filters

Row filters let you attach row-level predicates to a schema so that **SELECT/UPDATE/DELETE** automatically include them (useful for authorization scoping). This is enforced at plan finalization time and **fails closed** if you forget to bind context.

```typescript
import { createSchema } from "@tinqerjs/tinqer";
import { executeSelect } from "@tinqerjs/pg-promise-adapter";

interface Schema {
  users: { id: number; orgId: number; email: string };
  posts: { id: number; orgId: number; title: string };
}

type ScopeContext = { orgId: number };

const dangerousUnrestrictedSchema = createSchema<Schema>();

const rowFilteredSchema = dangerousUnrestrictedSchema.withRowFilters<ScopeContext>({
  users: (u, ctx) => u.orgId === ctx.orgId,
  posts: (p, ctx) => p.orgId === ctx.orgId,
});

const schema = rowFilteredSchema.withContext({ orgId: 7 });

// Any SELECT/UPDATE/DELETE using `schema` includes the row filter automatically.
await executeSelect(db, schema, (q) => q.from("posts"), {});
```

Notes:

- Filters must be provided for every table (set a table’s filter to `null` to opt out).
- Row filters are not automatically applied to INSERT statements.
- Unrestricted access is done by using the base schema (`dangerousUnrestrictedSchema`) directly.

### Joins

Tinqer mirrors LINQ semantics. Inner joins have a dedicated operator; left outer and cross joins follow the familiar `groupJoin`/`selectMany` patterns from C#.

#### Inner Join

```typescript
interface Schema {
  users: { id: number; name: string; deptId: number };
  departments: { id: number; name: string };
}

const schema = createSchema<Schema>();

const query = (q) =>
  q
    .from("users")
    .join(
      q.from("departments"),
      (user) => user.deptId,
      (department) => department.id,
      (user, department) => ({
        userName: user.name,
        departmentName: department.name,
      }),
    )
    .orderBy((row) => row.userName);
```

#### Left Outer Join

```typescript
const query = (q) =>
  q
    .from("users")
    .groupJoin(
      q.from("departments"),
      (user) => user.deptId,
      (department) => department.id,
      (user, deptGroup) => ({ user, deptGroup }),
    )
    .selectMany(
      (group) => group.deptGroup.defaultIfEmpty(),
      (group, department) => ({
        user: group.user,
        department,
      }),
    )
    .select((row) => ({
      userId: row.user.id,
      departmentName: row.department ? row.department.name : null,
    }));
```

#### Cross Join

```typescript
const query = (q) =>
  q
    .from("departments")
    .selectMany(
      () => q.from("users"),
      (department, user) => ({ department, user }),
    )
    .select((row) => ({
      departmentId: row.department.id,
      userId: row.user.id,
    }));
```

Right and full outer joins still require manual SQL, just as in LINQ-to-Objects.

### Grouping and Aggregation

```typescript
const query = (q) =>
  q
    .from("orders")
    .groupBy((o) => o.product_id)
    .select((g) => ({
      productId: g.key,
      totalQuantity: g.sum((o) => o.quantity),
      avgPrice: g.avg((o) => o.price),
      orderCount: g.count(),
    }))
    .orderByDescending((row) => row.totalQuantity);
```

### Window Functions

Window functions enable calculations across rows related to the current row. Tinqer supports `ROW_NUMBER()`, `RANK()`, and `DENSE_RANK()` with optional partitioning and ordering.

```typescript
// Get top earner per department (automatically wrapped in subquery)
const topEarners = await executeSelect(
  db,
  schema,
  (q, params, h) =>
    q
      .from("employees")
      .select((e) => ({
        ...e,
        rank: h
          .window(e)
          .partitionBy((r) => r.department)
          .orderByDescending((r) => r.salary)
          .rowNumber(),
      }))
      .where((e) => e.rank === 1), // Filtering on window function result
  {},
);

// Generated SQL (automatically wrapped):
// SELECT * FROM (
//   SELECT *, ROW_NUMBER() OVER (PARTITION BY "department" ORDER BY "salary" DESC) AS "rank"
//   FROM "employees"
// ) AS "employees"
// WHERE "rank" = 1
```

**Automatic Subquery Wrapping**: Tinqer automatically detects when `where()` clauses reference window function columns and wraps the query in a subquery, since SQL doesn't allow filtering on window functions at the same level where they're defined.

See the [Window Functions Guide](docs/guide.md#8-window-functions) for detailed examples of `RANK()`, `DENSE_RANK()`, complex ordering, and [filtering on window results](docs/guide.md#85-filtering-on-window-function-results).

### Full-Text Search

Opt into full-text search per table with `withFts`, then use the `helpers.fts.match` (a boolean predicate) and `helpers.fts.rank` (a relevance score, higher = more relevant) helpers. Tinqer only **emits** the query — you are responsible for the underlying FTS objects (a PostgreSQL `tsvector`/GIN index or an SQLite FTS5 virtual table). Plain `LIKE`/`icontains` stays available; FTS is purely additive.

```typescript
import { createSchema } from "@tinqerjs/tinqer";

interface Schema {
  articles: { id: number; title: string; content: string };
}

const schema = createSchema<Schema>().withFts({
  // PostgreSQL: inline to_tsvector over these columns (or set pg.vector to a stored tsvector column).
  // SQLite: matching/ranking happens through the FTS5 virtual table.
  articles: {
    columns: ["title", "content"],
    pg: { config: "english" },
    sqlite: { table: "articles_fts" },
  },
});

const results = await executeSelect(
  db,
  schema,
  (q, p, h) =>
    q
      .from("articles")
      .where((a) => h.fts.match(a, p.term))
      .orderByDescending((a) => h.fts.rank(a, p.term)),
  { term: "graph databases" },
);

// PostgreSQL:
//   WHERE to_tsvector('english', coalesce("title", '') || ' ' || coalesce("content", ''))
//         @@ websearch_to_tsquery('english', $(term))
//   ORDER BY ts_rank(...) DESC
// SQLite:
//   WHERE "articles"."rowid" IN (SELECT "rowid" FROM "articles_fts" WHERE "articles_fts" MATCH @term)
//   ORDER BY (SELECT -bm25("articles_fts") FROM "articles_fts" WHERE ... ) DESC
```

The first argument scopes the match: the row (`a`) covers the table's whole index, a column (`a.title`) or array (`[a.title, a.content]`) restricts it. Options interpret the query string on PostgreSQL — `{ mode: "websearch" | "plain" | "phrase" | "raw" }` (default `websearch`) and `{ config: "english" }` (per-call regconfig override). SQLite uses the FTS5 query string as-is.

See the [Full-Text Search Guide](docs/guide.md#17-full-text-search) for the full mapping, dialect differences, and how to create the backing index/table.

### CRUD Operations

```typescript
import { createSchema } from "@tinqerjs/tinqer";
import { executeInsert, executeUpdate, executeDelete } from "@tinqerjs/pg-promise-adapter";

const schema = createSchema<Schema>();

// INSERT
const insertedRows = await executeInsert(
  db,
  schema,
  (q) =>
    q.insertInto("users").values({
      name: "Alice",
      email: "alice@example.com",
    }),
  {},
);

// UPDATE with RETURNING
const inactiveUsers = await executeUpdate(
  db,
  schema,
  (q, params: { cutoffDate: Date }) =>
    q
      .update("users")
      .set({ status: "inactive" })
      .where((u) => u.lastLogin < params.cutoffDate)
      .returning((u) => u.id),
  { cutoffDate: new Date("2023-01-01") },
);

// UPDATE with column self-reference (increment counters, etc.)
await executeUpdate(
  db,
  schema,
  (q, params: { userId: number }) =>
    q
      .update("users")
      .set((u) => ({ view_count: u.view_count + 1 }))
      .where((u) => u.id === params.userId),
  { userId: 1 },
);

// Tip: undefined values in .set() or .values() are ignored; explicit null sets NULL.

// DELETE
const deletedCount = await executeDelete(
  db,
  schema,
  (q) => q.deleteFrom("users").where((u) => u.status === "deleted"),
  {},
);

// SQLite note: executeInsert/executeUpdate ignore RETURNING clauses at runtime; run a follow-up SELECT if you need the affected rows.
```

### Parameters and Auto-Parameterisation

All literal values are automatically parameterized to prevent SQL injection:

```typescript
// External parameters via params object
const schema = createSchema<Schema>();

const sample = toSql(
  defineSelect(schema, (q, params: { minAge: number }) =>
    q.from("users").where((u) => u.age >= params.minAge),
  ),
  { minAge: 18 },
);
// SQL (PostgreSQL): SELECT * FROM "users" WHERE "age" >= $(minAge)
// params: { minAge: 18 }

// Literals auto-parameterized automatically
const literals = toSql(
  defineSelect(schema, (q) => q.from("users").where((u) => u.age >= 18)),
  {},
);
// params: { __p1: 18 }
```

### Case-Insensitive String Operations

```typescript
import { createSchema } from "@tinqerjs/tinqer";

const schema = createSchema<Schema>();

const query = (q, params, helpers) =>
  q.from("users").where((u) => helpers.functions.icontains(u.name, params.searchTerm)); // Case-insensitive substring match

// PostgreSQL: WHERE LOWER("name") LIKE '%' || LOWER($(searchTerm)) || '%'
// SQLite: WHERE LOWER("name") LIKE '%' || LOWER(@searchTerm) || '%'
```

## Key Concepts

### Query Lifecycle

1. **Build Query** - Construct fluent chain using `Queryable` API
2. **Parse Lambda** - Lambda expressions are parsed into expression tree (never executed)
3. **Auto-Parameterize** - Literal values extracted as parameters
4. **Generate SQL** - Adapter converts expression tree to database-specific SQL

### Expression Support

Tinqer supports a focused set of JavaScript/TypeScript expressions:

- **Comparison**: `===`, `!==`, `>`, `>=`, `<`, `<=`
- **Logical**: `&&`, `||`, `!`
- **Arithmetic**: `+`, `-`, `*`, `/`, `%`
- **String**: `.includes()`, `.startsWith()`, `.endsWith()`, `.toLowerCase()`, `.toUpperCase()`
- **Null handling**: `??` (null coalescing), `?.` (optional chaining)
- **Arrays**: `.includes()` for IN queries
- **Helper functions**: `helpers.functions.iequals()`, `helpers.functions.istartsWith()`, `helpers.functions.iendsWith()`, `helpers.functions.icontains()` (portable case-insensitive)
- **Window functions**: `helpers.window(row).partitionBy(...).orderBy(...).rowNumber()`, `helpers.window(row).rank()`, `helpers.window(row).denseRank()` with `orderByDescending()`, `thenBy()`, `thenByDescending()`
- **Full-text search** (opt-in via `withFts`): `helpers.fts.match(target, query, options?)` (boolean), `helpers.fts.rank(target, query, options?)` (relevance score)

## Database Support

### PostgreSQL

- Native boolean type (`true`/`false`)
- Case-insensitive helpers use `LOWER()` comparisons for portable SQL
- Full JSONB support
- Window functions: `ROW_NUMBER()`, `RANK()`, `DENSE_RANK()`
- Full-text search: `tsvector @@ tsquery` matching (inline `to_tsvector` or a stored GIN-indexed column) and `ts_rank` scoring
- Parameter placeholders: `$(name)` / `$(__p1)` (pg-promise format)

### SQLite

- Boolean values use INTEGER (0/1)
- Case-insensitive via `LOWER()` function
- JSON functions support
- Window functions: `ROW_NUMBER()`, `RANK()`, `DENSE_RANK()` (requires SQLite 3.25+)
- Full-text search: FTS5 virtual-table `MATCH` and `bm25()` scoring (negated so higher = more relevant)
- Parameter placeholders: `@name` / `@__p1`

See [Database Adapters](docs/adapters.md) for detailed comparison.

## Differences from .NET LINQ to SQL

- Lambdas cannot capture external variables; use params object
- Join operations (`join`, `groupJoin`, `selectMany`) must be composed inside the defineSelect builder; they cannot be chained on plan handles
- Left outer joins and cross joins supported via LINQ patterns (right/full joins still require manual SQL)
- No deferred execution; SQL generated on demand
- Grouping supports `count`, `sum`, `avg`, `min`, `max`

## Documentation

- **[Query Operations Guide](docs/guide.md)** - Complete reference for all query operations, parameters, and CRUD
- **[API Reference](docs/api-reference.md)** - Execution functions, type utilities, and helper APIs
- **[Database Adapters](docs/adapters.md)** - PostgreSQL and SQLite specifics, differences, limitations
- **[Development Guide](docs/development.md)** - Contributing, testing, troubleshooting

## Packages

| Package                            | Purpose                                                  |
| ---------------------------------- | -------------------------------------------------------- |
| `@tinqerjs/tinqer`                 | Core expression tree and types (re-exported by adapters) |
| `@tinqerjs/pg-promise-adapter`     | PostgreSQL adapter with pg-promise                       |
| `@tinqerjs/better-sqlite3-adapter` | SQLite adapter with better-sqlite3                       |

## Credits

Tinqer uses [OXC](https://oxc.rs/) - a fast JavaScript/TypeScript parser written in Rust - to parse lambda expressions at runtime. OXC's speed and reliability make Tinqer's runtime lambda parsing practical and performant.

## For AI/LLMs

A consolidated documentation file for AI assistants is available at [`llms.txt`](llms.txt). This file includes all documentation in a single text format optimized for Large Language Model consumption.

## License

MIT

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