aux4/db-sqlite

SQLite database tools for the aux4 CLI.

The aux4/db-sqlite package provides seamless integration with SQLite databases directly from your command line. You can execute SQL queries, perform batch inserts, stream results for large datasets, manage transactions, and handle errors gracefully. Ideal for quick prototypes, ETL pipelines, automation scripts, and interactive database tasks without writing custom scripts.

Installation

aux4 aux4 pkger install aux4/db-sqlite

Quick Start

Create a database, define a table, insert a record, and query data:

# Create a new database and users table
aux4 db sqlite execute \
  --database my.db \
  --query "CREATE TABLE IF NOT EXISTS users (id INTEGER PRIMARY KEY, name TEXT, age INTEGER, email TEXT)"

# Insert a user and return the inserted row as JSON
aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES ('Alice', 30, 'alice@example.com') returning *"

Usage

Main Commands

• aux4 db sqlite execute - Execute SQL statements on a SQLite database and return all results as a JSON array.
• aux4 db sqlite stream - Execute SQL statements and stream each row as a newline-delimited JSON object.
• aux4 db sqlite describe - Describe the columns of a table as a canonical JSON array (see Schema Introspection).
• aux4 db sqlite list tables - List the tables in the database.

Command Reference

aux4 db sqlite execute

Run one or more SQL statements on a SQLite database and collect all results in memory.

Usage:

aux4 db sqlite execute \
  [--database <path>] \
  [--query "<SQL>"] \
  [--file <script.sql>] \
  [--inputStream] \
  [--tx] \
  [--ignore]

Options:

• --database <path> Path to the SQLite file (default: :memory:)
• --query "<SQL>" SQL statement to execute (positional if arg: true)
• --file <sql_file.sql> Execute SQL from a file
• --inputStream Read a JSON array from stdin as input parameters
• --tx Wrap all operations in a single transaction
• --ignore Ignore errors and continue processing, reporting failures

Examples:

# Named-parameter insert
aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
  --name Bob --age 25 --email bob@example.com

# Batch insert from JSON via stdin
echo '[{"name":"Carol","age":22,"email":"carol@example.com"}]' | \
  aux4 db sqlite execute --database my.db \
    --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
    --inputStream

# Transactional insert (rollback on error)
echo '[{"name":"Tx1","age":40,"email":"tx1@example.com"},{"name":""}]' | \
  aux4 db sqlite execute --database my.db \
    --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
    --inputStream --tx

aux4 db sqlite stream

Stream query results row-by-row for large datasets or piping into other commands.

Usage:

aux4 db sqlite stream \
  [--database <path>] \
  [--query "<SQL>"] \
  [--file <script.sql>] \
  [--inputStream] \
  [--tx] \
  [--ignore]

Options are the same as execute, but results are emitted as newline-delimited JSON objects.

Examples:

# Stream all users
aux4 db sqlite stream --database my.db --query "SELECT * FROM users ORDER BY id"

# Stream with a filter parameter
aux4 db sqlite stream \
  --database my.db \
  --query "SELECT name, email FROM users WHERE age >= :minAge ORDER BY name" \
  --minAge 30

# ETL pipeline: stream and immediately insert into audit table
aux4 db sqlite stream --database my.db --query "SELECT id, name FROM users" | \
  aux4 db sqlite stream \
    --database my.db \
    --query "INSERT INTO user_audit (user_id, audit_name) VALUES (:id, :name) returning audit_id" \
    --inputStream

Output Formats

Execute Command Output

The execute command returns results as JSON arrays:

Success:

[
  {"id": 1, "name": "Alice", "age": 30, "email": "alice@example.com"},
  {"id": 2, "name": "Bob", "age": 25, "email": "bob@example.com"}
]

Errors (to stderr):

[{"item": {"name": "Bad Data"}, "query": "INSERT INTO users...", "error": "NOT NULL constraint failed: users.age"}]

Stream Command Output

The stream command returns newline-delimited JSON objects (NDJSON):

{"id": 1, "name": "Alice", "age": 30, "email": "alice@example.com"}
{"id": 2, "name": "Bob", "age": 25, "email": "bob@example.com"}

Errors (to stderr):

{"item": {}, "query": "SELECT invalid_column FROM users", "error": "no such column: invalid_column"}

Advanced Features

Batch Processing with inputStream

Process multiple records from JSON input:

# Create JSON file with batch data
cat > users.json << EOF
[
  {"name": "User1", "age": 25, "email": "user1@example.com"},
  {"name": "User2", "age": 30, "email": "user2@example.com"}
]
EOF

# Execute batch insert
cat users.json | aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
  --inputStream

Parameter Override

CLI parameters override JSON input parameters:

# Override email for all records in the batch
cat users.json | aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
  --email "override@example.com" \
  --inputStream

Transaction Management

With transactions (--tx):

• All operations execute within a single transaction
• On error, all changes are rolled back
• Ensures data consistency for batch operations

# Transactional batch - all or nothing
cat batch.json | aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
  --inputStream --tx

Without transactions:

• Each operation commits individually
• Successful operations persist even if later ones fail
• Faster for large batches but less consistent

Error Handling

Default behavior (--ignore not set):

• Stop on first error
• Exit with non-zero code
• Error details sent to stderr

With --ignore flag:

• Continue processing remaining records
• Output successful results to stdout
• Send errors to stderr but exit with zero code

# Process all records, ignoring failures
cat mixed_data.json | aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
  --inputStream --ignore

Examples

Basic Query

aux4 db sqlite execute --database my.db --query "SELECT * FROM users"

Insert with Named Parameters

aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
  --name "Dave" --age 45 --email dave@example.com

Query with Parameters

aux4 db sqlite execute \
  --database my.db \
  --query "SELECT * FROM users WHERE age >= :minAge AND email LIKE :domain" \
  --minAge 25 --domain "%@example.com"

Transaction Rollback Demonstration

# Good and bad records in a single batch; --tx rolls back all if any fail
echo '[{"name":"Good","age":20,"email":"good@example.com"},{"name":"Bad"}]' | \
  aux4 db sqlite execute --database my.db \
    --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
    --inputStream --tx

Stream Processing Pipeline

# Create audit table
aux4 db sqlite execute --database my.db \
  --query "CREATE TABLE user_audit (audit_id INTEGER PRIMARY KEY, user_id INTEGER, user_name TEXT, audit_timestamp TEXT DEFAULT CURRENT_TIMESTAMP)"

# Stream users and insert audit records
aux4 db sqlite stream --database my.db --query "SELECT id, name FROM users WHERE age >= 25" | \
  aux4 db sqlite stream --database my.db \
    --query "INSERT INTO user_audit (user_id, user_name) VALUES (:id, :name) returning audit_id" \
    --inputStream

Error Recovery with --ignore

# Process mixed data, continuing despite errors
cat > mixed_data.json << EOF
[
  {"name": "Valid User", "age": 30, "email": "valid@example.com"},
  {"invalid_field": "bad data"},
  {"name": "Another Valid User", "age": 25, "email": "another@example.com"}
]
EOF

cat mixed_data.json | aux4 db sqlite execute \
  --database my.db \
  --query "INSERT INTO users (name, age, email) VALUES (:name, :age, :email) returning *" \
  --inputStream --ignore

Real-World Scenario

Automate an audit pipeline that copies user changes into an audit table:

# Ensure audit table exists
aux4 db sqlite execute --database my.db --query "CREATE TABLE IF NOT EXISTS user_audit (audit_id INTEGER PRIMARY KEY, user_id INTEGER, audit_name TEXT, timestamp TEXT DEFAULT CURRENT_TIMESTAMP)"

# Stream users and insert audit entries
aux4 db sqlite stream --database my.db --query "SELECT id, name FROM users WHERE age >= 18" | \
  aux4 db sqlite stream --database my.db --query "INSERT INTO user_audit (user_id, audit_name) VALUES (:id, :name) returning audit_id" --inputStream

Schema Introspection

The introspection commands let you explore a database's structure — ideal for AI agents and scripts that need to discover tables and columns before querying. They reuse the same connection flag as execute: --database, the path to the SQLite file.

SQLite is a single-file engine. There is no server, no separate schema, and no cross-database namespace — a database is a file. So --database (the file path) is the only scope, and there is deliberately no --schema flag, no list databases, and no list schemas. SQLite also has no column or table comments and no MySQL-style extra metadata, so describe never emits comment or extra keys.

aux4 db sqlite describe

Return the columns of a table as a canonical JSON array, one object per column, in definition order.

Usage:

aux4 db sqlite describe \
  [--database <path>] \
  --table <table_name>

Options:

• --database <path> Path to the SQLite file (default: :memory:)
• --table <table_name> Name of the table to describe (bound safely as a named parameter via pragma_table_info(:table))

Example:

aux4 db sqlite describe --database my.db --table product

[
  {"name":"id","type":"INTEGER","nullable":true,"key":"PRI"},
  {"name":"name","type":"TEXT","nullable":false},
  {"name":"price","type":"NUMERIC","nullable":true,"default":"0"},
  {"name":"sku","type":"TEXT","nullable":true}
]

Only keys that carry a value are returned — null and empty ("") fields are omitted, so a plain column is just {"name", "type", "nullable"}. nullable is always present as a real JSON boolean.

SQLite quirk: a column declared INTEGER PRIMARY KEY is an alias for the internal rowid, and pragma_table_info reports its notnull flag as 0 — so describe faithfully reports it as nullable: true (as shown for id above) even though it can never actually hold NULL. A regular NOT NULL column reports nullable: false.

aux4 db sqlite list tables

List the tables in the database. Each row carries only the table name — SQLite has no meaningful namespace (database/schema) to qualify a table with, so name is the only key. Internal sqlite_* tables are excluded.

Usage:

aux4 db sqlite list tables \
  [--database <path>]

Example:

aux4 db sqlite list tables --database my.db

[
  {"name":"product"},
  {"name":"tag"}
]

Canonical Output Schema

Introspection output uses a fixed, dialect-independent set of keys so that tooling works identically across every aux4/db-* adapter. A key is present only when it carries a value — null and empty ("") fields are omitted rather than emitted, keeping the output compact.

describe — one object per column. When present, keys appear in this order:

| Key | Type | Presence | |-----|------|----------| | name | string | always | | type | string | always | | nullable | boolean | always — true if the column accepts NULL, else false | | default | string | only when the column has a default | | key | string | only when set — PRI for a primary-key column |

SQLite has no column comments and no extra metadata, so comment and extra (present on some other adapters such as MySQL) are never emitted here.

list tables — one object per table:

| Key | Type | Presence | |-----|------|----------| | name | string | always |

Unlike server-based engines, SQLite tables are not qualified by a database or schema namespace, so no such key is emitted.

License

This package does not specify a license in its manifest. Please refer to the repository or the aux4 hub listing for licensing details.