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github crates.io docs.rs

An easy local data persistence layer, backed by SQLite.

  • Schema auto-defined by your Rust structs
  • Automatic schema migrations
  • Super-simple basic INSERT/SELECT/UPDATE/DELETE operations
  • Use complex SQL if that’s your jam
  • Validates all SQL (including user-supplied) at compile time


use turbosql::{Turbosql, select, execute};

#[derive(Turbosql, Default)]
struct Person {
    rowid: Option<i64>, // rowid member required & enforced at compile time
    name: Option<String>,
    age: Option<i64>,
    image_jpg: Option<Vec<u8>>

fn main() -> Result<(), Box<dyn std::error::Error>> {

    let name = "Joe";

    // INSERT a row
    let rowid = Person {
        name: Some(name.to_string()),
        age: Some(42),

    // SELECT all rows
    let people = select!(Vec<Person>)?;

    // SELECT multiple rows with a predicate
    let people = select!(Vec<Person> "WHERE age > " 21)?;

    // SELECT a single row with a predicate
    let mut person = select!(Person "WHERE name = " name)?;

    // UPDATE based on rowid, rewrites all fields in database row
    person.age = Some(43);

    // UPDATE with manual SQL
    execute!("UPDATE person SET age = " 44 " WHERE name = " name)?;

    // DELETE
    execute!("DELETE FROM person WHERE rowid = " 1)?;


See integration_test.rs or trevyn/turbo for more usage examples!

Under the Hood

Turbosql generates a SQLite schema and prepared queries for each struct:

use turbosql::Turbosql;

#[derive(Turbosql, Default)]
struct Person {
    rowid: Option<i64>, // rowid member required & enforced
    name: Option<String>,
    age: Option<i64>,
    image_jpg: Option<Vec<u8>>

        ↓      auto-generates and validates the schema

    name TEXT,
    age INTEGER,
    image_jpg BLOB,

INSERT INTO person (rowid, name, age, image_jpg) VALUES (?, ?, ?, ?)

SELECT rowid, name, age, image_jpg FROM person

Queries with SQL predicates are also assembled and validated at compile time. Note that SQL types vs Rust types for parameter bindings are not currently checked at compile time.

let people = select!(Vec<Person> "WHERE age > ?", 21);


SELECT rowid, name, age, image_jpg FROM person WHERE age > ?

Automatic Schema Migrations

At compile time, the #[derive(Turbosql)] macro runs and creates a migrations.toml file in your project root that describes the database schema.

Each time you change a struct declaration and the macro is re-run (e.g. by cargo or rust-analyzer), migration SQL statements are generated that update the database schema. These new statements are recorded in migrations.toml, and are automatically embedded in your binary.

#[derive(turbosql::Turbosql, Default)]
struct Person {
    rowid: Option<i64>,
    name: Option<String>

        ↓      auto-generates migrations.toml

migrations_append_only = [
output_generated_schema_for_your_information_do_not_edit = '''
  CREATE TABLE person (
    name TEXT

When your schema changes, any new version of your binary will automatically migrate any older database file to the current schema by applying the appropriate migrations in sequence.

This migration process is a one-way ratchet: Old versions of the binary run on a database file with a newer schema will detect a schema mismatch and will be blocked from operating on the futuristically-schema’d database file.

Unused or reverted migrations that are created during development can be manually removed from migrations.toml before being released, but any database files that have already applied these deleted migrations will error and must be rebuilt. Proceed with care. When in doubt, refrain from manually editing migrations.toml, and everything should work fine.

  • Just declare and freely append fields to your structs.
  • Check out the migrations.toml file that is generated in your project root to see what’s happening.
  • If you run into any weird compiler errors, try just re-compiling first; depending on the order the proc macros run, sometimes it just needs a little push to get in sync after a schema change.
  • Schema migrations are one-way, append-only. This is similar to the approach taken by leafac/sqlite-migration for the Node.js ecosystem; see that project for a discussion of the advantages!
  • On launch, versions of your binary built with a newer schema will automatically apply the appropriate migrations to an older database.
  • If you’re feeling adventurous, you can add your own schema migration entries to the bottom of the list. (For creating indexes, etc.)
  • You can hand-write complex migrations as well, see turbo/migrations.toml for some examples.
  • Please open a GitHub issue with any questions or suggestions!

Where’s my data?

The SQLite database file is created in the directory returned by directories_next::ProjectDirs::data_dir() + your executable’s filename stem, which resolves to something like:


$XDG_DATA_HOME/{exe_name} or $HOME/.local/share/{exe_name} /home/alice/.local/share/fooapp/fooapp.sqlite


$HOME/Library/Application Support/{exe_name} /Users/Alice/Library/Application Support/org.fooapp.fooapp/fooapp.sqlite


{FOLDERID_LocalAppData}\{exe_name}\data C:\Users\Alice\AppData\Local\fooapp\fooapp\data\fooapp.sqlite

Transactions and async

SQLite, and indeed many filesystems in general, only provide blocking (synchronous) APIs. The correct approach when using blocking APIs in a Rust async ecosystem is to use your executor’s facility for running a closure on a thread pool in which blocking is expected. For example:

#[derive(turbosql::Turbosql, Default)]
struct Person {
    rowid: Option<i64>,
    name: Option<String>

async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let person = tokio::task::spawn_blocking(|| {
        turbosql::select!(Option<Person> "WHERE name = ?", "Joe")

(Note that spawn_blocking returns a JoinHandle that must itself be unwrapped, hence the need for ?? near the end of these examples.)

Under the hood, Turbosql uses persistent thread_local database connections, so a continuous sequence of database calls from the same thread are guaranteed to use the same exclusive database connection. Thus, async transactions can be performed as such:

use turbosql::{Turbosql, select, execute};

#[derive(Turbosql, Default)]
struct Person {
    rowid: Option<i64>,
    age: Option<i64>

async fn main() -> Result<(), Box<dyn std::error::Error>> {
    tokio::task::spawn_blocking(|| -> Result<(), turbosql::Error> {
        Person { rowid: None, age: Some(21) }.insert()?;
        let p = select!(Person "WHERE rowid = ?", 1)?;
        // [ ...do any other blocking things... ]
            "UPDATE person SET age = ? WHERE rowid = ?",
            p.age.unwrap_or_default() + 1,

Turbosql sets a SQLite busy_timeout of 3 seconds, so any table lock contention is automatically re-tried up to that duration, after which the command that was unable to acquire a lock will return with an error.

For further discussion of Turbosql’s approach to async and transactions, see https://github.com/trevyn/turbosql/issues/4. Ideas for improvements to the ergonomics of the solution are very welcome.

-wal and -shm files

SQLite is an extremely reliable database engine, but it helps to understand how it interfaces with the filesystem. The main .sqlite file contains the bulk of the database. During database writes, SQLite also creates .sqlite-wal and .sqlite-shm files. If the host process is terminated without flushing writes, you may end up with these three files when you expected to have a single file. This is always fine; on next launch, SQLite knows how to resolve any interrupted writes and make sense of the world. However, if the -wal and/or -shm files are present, they must be considered essential to database integrity. Deleting them may result in a corrupted database. See https://sqlite.org/tempfiles.html.

Example Query Forms

Check integration_test.rs for more examples of what works and is tested in CI.

 Primitive type
let result = select!(String "SELECT name FROM person")?;

Returns one value cast to specified type, returns Error if no rows available.

let result = select!(String "name FROM person WHERE rowid = ?", rowid)?;

SELECT keyword is always optional when using select!; it’s added automatically as needed.
Parameter binding is straightforward.

let result = select!(Vec<String> "name FROM person")?;

Returns Vec containing another type. If no rows, returns empty Vec.

let result = select!(Option<String> "name FROM person")?;

Returns Ok(None) if no rows, Error(_) on error.

 Your struct
let result = select!(Person "WHERE name = ?", name)?;

Column list and table name are optional if type is a #[derive(Turbosql)] struct.

let result = select!(Vec<NameAndAdult> "name, age >= 18 AS adult FROM person")?;

You can use other struct types as well; column names must match the struct and you must specify the source table in the SQL.
Implement Default to avoid specifying unused column names.
(And, of course, you can put it all in a Vec or Option as well.)

let result = select!(Vec<Person>)?;

Sometimes everything is optional; this example will retrieve all Person rows.

“turbosql” or “Turbosql”?

Your choice, but you definitely do not want to capitalize any of the other letters in the name! ;)

License: MIT OR Apache-2.0 OR CC0-1.0 (public domain)


Executes a SQL statement. On success, returns the number of rows that were changed or inserted or deleted.

Executes a SQL SELECT statement with optionally automatic SELECT and FROM clauses.




#[derive(Turbosql)] generates impls for this trait.


Checkpoint the DB. If no other threads have open connections, this will clean up the -wal and -shm files as well.

Convenience function that returns the current time as milliseconds since UNIX epoch.

Set the local path and filename where Turbosql will store the underlying SQLite database.

Type Definitions

Wrapper for Vec<u8> that may one day impl Read, Write and Seek traits.

Derive Macros

Derive this on a struct to create a corresponding SQLite table and Turbosql trait methods.