Rust is emerging as a frontrunner for ensuring memory safety without sacrificing performance. Its growing popularity isn\u2019t solely based on the \u201cfearless concurrency\u201d mantra but also on its expanding ecosystem that fosters integration with various technologies. A domain Rust proves to be formidable is database interaction, and a pivotal player in this realm is the Diesel ORM. Diesel is an ORM and query builder designed with the philosophy of type safety and a simple API that primes application performance.<\/p>\n\n\n\n
In this article, I will demonstrate how to get up and running with Rust, connecting to SQL databases using the Diesel ORM<\/a>.<\/p>\n\n\n\n You\u2019ll need to download and install Rust<\/a> and your preferred SQL database management system to interact with SQL databases through Rust. Diesel. In this tutorial, we will use SQLite as the DBMS, but you can use your preferred relational database<\/p>\n\n\n\n After you\u2019ve installed Rust and a preferred SQL DBMS that Diesel supports, The Next, you\u2019ll add Diesel as a dependency and install the You need these tools to set up and use an SQL database with Diesel.<\/p>\n\n\n\n Setting up a database and connecting to a database with Diesel is a straightforward process.<\/p>\n\n\n\n First, create an environment variables .env file in the root directory of your project and add your database connection string with the KEY DATABASE_URL.<\/p>\n\n\n\n Then, run the On running the command, Diesel creates a Here\u2019s how you can setup migrations with the The command will generate two SQL files in the You can write the SQL for your database table definitions in the Here\u2019s an example of content for the Then your After writing the SQL files, you can run the You can use the Diesel generates a The output of the command should match the contents of your You can connect to your SQLite database with Diesel\u2019s The CRUD (Create, Read, Update, Delete) operations form the basis for most database operations, so you\u2019ll need to understand how to perform those operations to grasp the fundamentals of working with Diesel.<\/p>\n\n\n\n Here\u2019s the list of imports and statements you\u2019ll need throughout the CRUD operations.<\/p>\n\n\n\n The Diesel provides an Here\u2019s a struct that matches the data you\u2019d want to insert. Notice the macro definitions for the operation You\u2019ll initialize the The Here\u2019s the result of the insert operation:<\/p>\n\n\n\n <\/p>\n\n\n\n The struct for query operations will differ from the struct for insert operations, especially the Derive macro.<\/p>\n\n\n\n Here\u2019s the struct for an insert operation into the Human table:<\/p>\n\n\n\n You can use the Here, the <\/p>\n\n\n\n You\u2019ll need to implement the The You\u2019ll use the The You can use the The Diesel supports more operations than just CRUD operations. You can also work with multiple tables and perform more complex operations like storing a list of entries in the database:<\/p>\n\n\n\n One of the ways you can store a list of entries in the database is using a vector of structs that you\u2019ll iterate over and insert the values.<\/p>\n\n\n\n Here\u2019s how you can insert a vector of three structs (three entries) into the database:<\/p>\n\n\n\n After declaring three struct instances in the <\/p>\n\n\n\n Working with multiple tables is similar to working with single tables, except you\u2019ll have to set up migrations for the tables individually.<\/p>\n\n\n\n Here\u2019s how you can generate migrations for two tables named Now you can fill each table’s up.sql and down.sql files as usual to create and then drop the structures.<\/p>\n\n\n\n Now run the Now that you\u2019ve set up your database migrations, you can proceed to other operations, like inserting data into the tables.<\/p>\n\n\n\n Here\u2019s the list of imports you\u2019ll need for the insert operation.<\/p>\n\n\n\n Additionally, here are the structs you need for the insert operation:<\/p>\n\n\n\n Notice that the structs implement You can use Diesel\u2019s The Here\u2019s the result of the insert operation on the <\/p>\n\n\n\n Also, here\u2019s the result of the insert operation on the <\/p>\n\n\n\n You can query the database for the data from the Diesel provides robust support for writing raw SQL in its Here are the imports you need for the query operation, including Diesel\u2019s You can declare a struct that matches your schema to query the database with a struct as thus:<\/p>\n\n\n\n The structs implement Here\u2019s how you can query the tables with the item The The Here\u2019s the result of the operation:<\/p>\n\n\n\n <\/p>\n\n\n\n Diesel also provides functionality for code-first relationships on the Relations page that you can check out.<\/p>\n\n\n\n Note: building SQL to execute can lead to errors. Another name for this is dynamic SQL, which can sometimes allow someone to form a string that can cause harm to your database.<\/p>\n\n\n\n You\u2019ve deeply explored how to use Diesel to interact with SQL databases in your Rust apps. You learned how to set up your database, connect to databases, perform CRUD operations, and work with multiple tables, amongst other operations.<\/p>\n\n\n\n You can do so much with Diesel, including building REST APIs. You can use tools like Actix<\/a> and Rocket<\/a> to build APIs with Diesel. Since Diesel provides an interface for writing RAW SQL and has excellent community support,<\/p>\n\n\n\n Diesel is a compile-time safe ORM for Rust supporting PostgreSQL, MySQL, and SQLite. It generates type-safe SQL queries using Rust’s type system – column type mismatches or missing tables produce compile errors rather than runtime panics. Main alternatives: sqlx (async-first, raw SQL queries with compile-time checking, broader database support), Rusqlite (SQLite-specific, lower-level), and sea-orm (async ORM inspired by ActiveRecord). Diesel is a good choice when you prefer a traditional ORM model with struct-based mapping; sqlx is better when you want to write raw SQL and still catch errors at compile time.<\/p>\n <\/div>\n Add diesel = { version = “2.0”, features = [“postgres”] } and dotenvy to your Cargo.toml. Create a .env file with DATABASE_URL=postgres:\/\/user:password@localhost\/dbname. In code: use diesel::prelude::*; use dotenvy::dotenv; let database_url = std::env::var(“DATABASE_URL”).expect(“DATABASE_URL must be set”); let connection = PgConnection::establish(&database_url)?; Run diesel setup and diesel migration run to create and apply migrations. Define your table schema in schema.rs using Diesel’s table! macro.<\/p>\n <\/div>\n Define a struct with the Queryable derive macro, matching the column types in your table. Use Diesel’s query DSL: let results = users.filter(age.gt(18)).limit(10).load::<User>(&mut conn)?; The filter, order, limit, and select methods build a type-safe query – Diesel validates column names and types at compile time against the schema.rs definitions. For raw SQL when you need query features Diesel’s DSL doesn’t support, use diesel::sql_query(“SELECT * FROM users WHERE …”).load::<User>(&mut conn)?<\/p>\n <\/div>\n Diesel’s core API is synchronous. For async Rust applications (Tokio, async-std), use diesel-async, a separate crate that provides async versions of Diesel’s connection and query methods. Alternatively, sqlx is built async-first and may be a better fit for async-heavy applications. If using Diesel in an async context without diesel-async, run blocking Diesel calls in a Tokio spawn_blocking task to avoid blocking the async runtime thread.<\/p>\n <\/div>\n <\/section>\n","protected":false},"excerpt":{"rendered":" Connect Rust applications to SQL databases using the Diesel ORM. Covers database setup with .env configuration, basic CRUD operations (insert, query, update, delete), batch inserts, and Diesel’s derive macros for struct-to-table mapping.…<\/p>\n","protected":false},"author":340771,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":true,"footnotes":""},"categories":[53,147005],"tags":[159071],"coauthors":[147592],"class_list":["post-101867","post","type-post","status-publish","format-standard","hentry","category-featured","category-web","tag-rust"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/posts\/101867","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/users\/340771"}],"replies":[{"embeddable":true,"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/comments?post=101867"}],"version-history":[{"count":6,"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/posts\/101867\/revisions"}],"predecessor-version":[{"id":109776,"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/posts\/101867\/revisions\/109776"}],"wp:attachment":[{"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/media?parent=101867"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/categories?post=101867"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/tags?post=101867"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.red-gate.com\/simple-talk\/wp-json\/wp\/v2\/coauthors?post=101867"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}<\/a>Getting Started Using SQL Databases With Rust<\/h2>\n\n\n\n
you<\/code> can proceed to create a new Rust project with Cargo\u2019s init command<\/a>:<\/p>\n\n\n\ncargo init<\/pre>\n\n\n\n
cargo<\/code> init command initializes the new project and adds a cargo.toml<\/code> file in the root directory for dependency management.<\/p>\n\n\n\ndiesel_cli<\/code> tool to start working with databases.<\/p>\n\n\n\n# add diesel to dependencies with sqlite feature\ncargo add diesel --features \"sqlite\"\n\n# install diesel_cli \ncargo install diesel_cli\nchange to: cargo install diesel_cli --no-default-features --features sqlite\n\n#note: may get errors about \u201cnote: LINK : fatal error LNK1181: cannot open input file 'sqlite3.lib'\u201d if so, go to: https:\/\/github.com\/diesel-rs\/diesel\/issues\/487\n\n# add dotenv to dependencies\ncargo add dotenv<\/pre>\n\n\n\n
<\/a>Database Setup With Diesel<\/h2>\n\n\n\n
#database connection string example\nDATABASE_URL=sqlite:\/\/\/database.sqlite<\/pre>\n\n\n\n
diesel setup<\/code> command to set up the database for your project.<\/p>\n\n\n\ndiesel setup<\/pre>\n\n\n\n
migrations<\/code> directory, validates the connection to the database, and runs existing migrations.<\/p>\n\n\n\ndiesel migrations generate<\/code> command:<\/p>\n\n\n\ndiesel migration generate create_human<\/pre>\n\n\n\n
migrations<\/code> directory: up.sql<\/code> and down.sql<\/code>.<\/p>\n\n\n\nup.sql<\/code> file and the SQL query to drop the tables in the down.sql<\/code> file.<\/p>\n\n\n\nup.sql<\/code> file:<\/p>\n\n\n\n-- Your SQL goes here\nCREATE TABLE \"human\"\n(\n \"id\" INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,\n \"first_name\" TEXT NOT NULL,\n \"last_name\" TEXT NOT NULL,\n \"age\" INTEGER NOT NULL,\n \"username\" TEXT,\n \"email\" TEXT,\n \"location\" TEXT\n);<\/pre>\n\n\n\n
down.sql<\/code> file should look like this:<\/p>\n\n\n\nDROP TABLE \"human\"<\/pre>\n\n\n\n
migration run<\/code> command to run migrations.<\/p>\n\n\n\ndiesel migration run<\/pre>\n\n\n\n
migration redo<\/code> command to revert previous migrations:<\/p>\n\n\n\ndiesel migration redo<\/pre>\n\n\n\n
schema.rs<\/code> file in your src<\/code> folder, and you can print the contents of the file with the diesel print-schema<\/code> command:<\/p>\n\n\n\ndiesel print-schema<\/pre>\n\n\n\n
src\/schema.rs<\/code> file as thus:<\/p>\n\n\n\nSqliteConnection::establish<\/code> function that takes in the database URL and connects to the database:<\/p>\n\n\n\n\/\/src\/model.rs\n\nuse std::env;\nuse diesel::prelude::*;\nuse dotenv::dotenv;\n\npub fn establish_connection() -> SqliteConnection {\n dotenv().ok();\n let database_url = env::var(\"DATABASE_URL\").expect(\n \"DATABASE_URL must be set\");\n SqliteConnection::establish(&database_url)\n .unwrap_or_else(|_| panic!(\n \"Error connecting to the database: {}\", database_url))\n}<\/pre>\n\n\n\nestablish_connection()<\/code> function connects to the database and returns an SQLite connection instance that you can use for operations on the database.<\/p>\n\n\n\n<\/a>Basic CRUD Operations<\/h2>\n\n\n\n
#![feature(proc_macro_hygiene, decl_macro)]\nextern crate diesel;\nmod schema;\nmod database;\nuse crate::database::establish_connection;\nuse diesel::prelude::*;<\/pre>\n\n\n\n
diesel::prelude::*<\/code> statement imports most of Diesel\u2019s functionalities.<\/p>\n\n\n\n<\/a>Creating (Inserting) Records into a Database<\/h3>\n\n\n\n
insert_into<\/code> function that you can use to insert data into your database.<\/p>\n\n\n\nInsertable<\/code> and table_name = schema::human<\/code>.<\/p>\n\n\n\n\/\/ Specify the fully-qualified path for the table_name attribute#[derive(Insertable)]\n#[diesel(table_name = schema::human)]\npub struct NewHuman {\n pub first_name: String,\n pub last_name: String,\n pub age: i32,\n pub username: String,\n pub email: String,\n pub location: String,\n}<\/pre>\n\n\n\nNewHuman<\/code> struct and use the instance to insert data into the database as thus:<\/p>\n\n\n\nfn main() {\n let mut connection = establish_connection();\n let new_human = NewHuman {\n first_name: String::from(\"John\"),\n last_name: String::from(\"Doe\"),\n age: 30,\n username: String::from(\"johndoe\"),\n email: String::from(\"john.doe@example.com\"),\n location: String::from(\"New York\"),\n };\n diesel::insert_into(schema::human::table).values(&new_human).execute(&mut connection).expect(\"Error saving new human\");\n}<\/pre>\n\n\n\nmain<\/code> function establishes a connection to the database with the establish_connection<\/code> function and inserts the new_human<\/code> struct instance into the database with the insert_into<\/code> function\u2019s values<\/code> function.<\/p>\n\n\n\n![\"\"](\"https:\/\/www.red-gate.com\/simple-talk\/wp-content\/uploads\/2024\/03\/word-image-101867-1-2.png\")
<\/figure>\n\n\n\n<\/a>Querying (Reading) Data From the Database<\/h3>\n\n\n\n
#[derive(Debug, Queryable)]\npub struct Human {\n pub id: i32,\n pub first_name: String,\n pub last_name: String,\n pub age: i32,\n pub username: Option<String>, \n \/\/ Use Option for nullable columns\n pub email: Option<String>, \n \/\/ Use Option for nullable columns\n pub location: Option<String>, \n \/\/ Use Option for nullable columns\n}<\/pre>\n\n\n\nload<\/code> method on the table to load all the entries in the human<\/code> table:<\/p>\n\n\n\nfn main() {\n let mut connection = establish_connection();\n let humans = human::table\n .load::<Human>(&mut connection)\n .expect(\"Error loading humans\");\n println!(\"{:?}\", humans);\n}<\/pre>\n\n\n\nmain<\/code> function loads all the entries in the database with the load<\/code> method after establishing a connection to the database. The main<\/code> function prints the entries to the console.<\/p>\n\n\n\n![\"\"](\"https:\/\/www.red-gate.com\/simple-talk\/wp-content\/uploads\/2024\/03\/word-image-101867-2-2.png\")
<\/figure>\n\n\n\n<\/a>Updating Database Entries<\/h3>\n\n\n\n
AsChangeset<\/code> derive macro for your update struct to update entries in the database.<\/p>\n\n\n\n#[derive(Queryable, AsChangeset, Identifiable)]\n#[diesel(table_name = schema::human)]\nstruct UpdateHuman {\n pub id: i32,\n pub first_name: String,\n pub last_name: String,\n pub age: i32,\n pub username: Option<String>,\n pub email: Option<String>,\n pub location: Option<String>,\n}<\/pre>\n\n\n\nUpdateHuman<\/code> struct is the struct for update operations on the human<\/code> table.<\/p>\n\n\n\nupdate<\/code> function to update entries in your database tables:<\/p>\n\n\n\nfn main() {\n use crate::schema::human::dsl::*;\n let mut connection = establish_connection();\n let id_to_update = 1; \n \/\/ Replace with the ID of the human you want to update\n let human_update = UpdateHuman {\n id: 2,\n first_name: \"Janeen\".to_string(),\n last_name: \"Elixir\".to_string(),\n age: 30,\n username: Some(\"elixir\".to_string()),\n email: Some(\"jelixir@example.com\".to_string()),\n location: Some(\"Pars\".to_string()),\n };\n let updated_rows = diesel::update(human.find(id_to_update))\n .set(&human_update)\n .execute(&mut connection)\n .expect(\"Failed to update student\");\n println!(\"{:?}\", updated_rows);\n}<\/pre>\n\n\n\nmain<\/code> function uses an id<\/code> to search the database with the find<\/code> function on the table instance before proceeding with the update operation if the entry exists. The diesel::update<\/code> function updates the table with the new entry with the set function.<\/p>\n\n\n\n<\/a>Deleting Entries From the Database<\/h3>\n\n\n\n
delete<\/code> function to delete database entries based on an ID.<\/p>\n\n\n\nfn main() {\n let id_to_delete = 1;\n let mut connection = establish_connection();\n let deleted_rows = diesel::delete(human.find(id_to_delete)).execute(&mut connection)?;\n println!(\"Deleted {} rows.\", deleted_rows);\n}<\/pre>\n\n\n\nmain<\/code> function searches for the entry with the id through the find function that the delete<\/code> function takes in and executes the delete operation through the established connection.<\/p>\n\n\n\n<\/a>Popular Database Operations With Diesel<\/h2>\n\n\n\n
<\/a>Storing a List of Entries into the Database<\/h3>\n\n\n\n
fn main() {\n let mut connection = establish_connection();\n let new_humans = vec![\n NewHuman {\n first_name: String::from(\"John\"),\n last_name: String::from(\"Doe\"),\n age: 30,\n username: String::from(\"johndoe\"),\n email: String::from(\"john.doe@example.com\"),\n location: String::from(\"New York\"),\n },\n NewHuman {\n first_name: String::from(\"Alice\"),\n last_name: String::from(\"Smith\"),\n age: 28,\n username: String::from(\"alicesmith\"),\n email: String::from(\"alice.smith@example.com\"),\n location: String::from(\"Los Angeles\"),\n },\n NewHuman {\n first_name: String::from(\"David\"),\n last_name: String::from(\"Johnson\"),\n age: 35,\n username: String::from(\"davidjohnson\"),\n email: String::from(\"david.johnson@example.com\"),\n location: String::from(\"Chicago\"),\n },\n ];\n \/\/ Insert the new_humans vector into the database\n for new_human in new_humans {\n diesel::insert_into(schema::human::table)\n .values(&new_human)\n .execute(&mut connection)\n .expect(\"Error inserting human\");\n }\n}<\/pre>\n\n\n\nnew_humans<\/code> vector, the main<\/code> function uses a for-range loop to loop through the structs and insert the values into the database with the insert_into<\/code> function.<\/p>\n\n\n\n![\"\"](\"https:\/\/www.red-gate.com\/simple-talk\/wp-content\/uploads\/2024\/03\/word-image-101867-3-2.png\")
<\/figure>\n\n\n\nitem<\/code> and item_type<\/code>, respectively.<\/p>\n\n\n\ndiesel migration generate item\n\ndiesel migration generate item_type<\/pre>\n\n\n\n
-- migrations\/2023-09-23-145306_item\n-- Your SQL goes here\n-- Table definition for items\nCREATE TABLE IF NOT EXISTS items\n(\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n item_name TEXT NOT NULL,\n item_type_id INTEGER NOT NULL,\n acquired_time DATETIME NOT NULL,\n FOREIGN KEY (item_type_id) REFERENCES item_types (id)\n);\n\n-- code to drop items\nDROP TABLE items\n\n-- migrations\/2023-09-23-145316_item_type\n-- Your SQL goes here\nCREATE TABLE IF NOT EXISTS item_types\n(\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n name TEXT NOT NULL\n);\n\n-- code to drop item_types\nDROP TABLE item_types<\/pre>\n\n\n\n
diesel migration run<\/code> command to complete the setup process. Your schema.rs<\/code> file should look like this:<\/p>\n\n\n\ndiesel::table! {\n items (id) {\n id -> Integer,\n item_name -> Text,\n item_type_id -> Integer,\n acquired_time -> Timestamp,\n }\n}\ndiesel::table! {\n item_types (id) {\n id -> Integer,\n name -> Text,\n }\n}\ndiesel::joinable!(items -> item_types (item_type_id));\ndiesel::allow_tables_to_appear_in_same_query!(\n item_types,\n items,\n);<\/pre>\n\n\n\nextern crate diesel;\n\nuse chrono::prelude::*;\nuse diesel::prelude::*;\nuse diesel::dsl::now;\nuse diesel::sql_types::Timestamp;\nuse crate::database::establish_connection;\n\n\/\/ Import the table and schema macros.\nuse crate::schema::{item_types, items};\n\n<\/pre>\n\n\n\n#[derive(Insertable)]\n#[table_name = \"item_types\"]\nstruct NewItemType<'a> {\n name: &'a str,\n}\n#[derive(Insertable)]\n#[table_name = \"items\"]\nstruct NewItem<'a> {\n item_name: &'a str,\n item_type_id: i32,\n acquired_time: NaiveDateTime,\n}<\/pre>\n\n\n\nInsertable<\/code> for Diesel to be able to insert their instances into the database.<\/p>\n\n\n\ninsert_into<\/code> function to insert entries in the tables on instantiation as usual:<\/p>\n\n\n\nfn main() {\n let mut connection = establish_connection();\n let new_item = NewItem {\n item_name: \"Book\",\n item_type_id: 1,\n acquired_time: Utc::now().naive_utc(),\n };\n diesel::insert_into(items::table)\n .values(&new_item)\n .execute(&mut connection)\n .expect(\"Error saving new item\");\n let new_item_type = NewItemType { name: \"Education\" };\n diesel::insert_into(item_types::table)\n .values(&new_item_type)\n .execute(&mut connection)\n .expect(\"Error saving new item type\");\n}<\/pre>\n\n\n\nmain<\/code> function inserts data into the item<\/code> and item_type<\/code> tables with the insert_into<\/code> function that takes in the table declarations from the schema.rs<\/code> file.<\/p>\n\n\n\nitem<\/code> table:<\/p>\n\n\n\n![\"\"](\"https:\/\/www.red-gate.com\/simple-talk\/wp-content\/uploads\/2024\/03\/word-image-101867-4-2.png\")
<\/figure>\n\n\n\nitem_type<\/code> table:<\/p>\n\n\n\n![\"\"](\"https:\/\/www.red-gate.com\/simple-talk\/wp-content\/uploads\/2024\/03\/word-image-101867-5-2.png\")
<\/figure>\n\n\n\nitem<\/code> and item_type<\/code> tables.<\/p>\n\n\n\nsql_query<\/code> function that you can use for functionalities Diesel doesn’t support.<\/p>\n\n\n\nsql_query<\/code> function import:<\/p>\n\n\n\nextern crate diesel;\nmod schema;\nmod database;\nuse crate::database::establish_connection;\nuse diesel::prelude::*;\nuse diesel::sql_query;<\/pre>\n\n\n\n
#[derive(Debug, QueryableByName)]\n#[diesel(table_name = schema::item_types)]\nstruct ItemType {\n id: i32,\n name: String,\n}\n#[derive(Debug, QueryableByName)]\n#[diesel(table_name = schema::items)]\nstruct Item {\n id: i32,\n item_name: String,\n acquired_time: chrono::NaiveDateTime,\n \/\/ Assuming you use chrono for datetime fields\n item_type_id: i32,\n}<\/pre>\n\n\n\nDebug<\/code> and QueryableByName<\/code> for the query operation using raw SQL.<\/p>\n\n\n\nID<\/code> using raw SQL:<\/p>\n\n\n\nfn main() {\n let mut connection = establish_connection();\n let item_type_id_to_retrieve = 1;\n \/\/ Using raw SQL to retrieve the ItemType\n let item_type: ItemType = \n sql_query(\"SELECT * FROM item_types WHERE id = $1\")\n .bind::<diesel::sql_types::Integer, _>(item_type_id_to_retrieve)\n .get_result(&mut connection)\n .expect(\"Failed to find item type by ID\");\n \/\/ Using raw SQL to retrieve items of \n \/\/the specified item type\n let items_of_type: Vec<Item> \n = sql_query(\n \"SELECT * FROM items WHERE item_type_id = $1\")\n .bind::<diesel::sql_types::Integer, _>(item_type.id)\n .load(&mut connection)\n .expect(\"Failed to load items of item type\");\n println!(\"Items of type '{}':\", item_type.name);\n for item in items_of_type {\n println!(\n \"Item ID: {}, Name: {}, Acquired Time: {:?}\",\n item.id, item.item_name, item.acquired_time\n );\n }\n}<\/pre>\n\n\n\nmain<\/code> function connects to the database with the establish_connection<\/code> function before the item_type_id_to_retrieve<\/code> declaration. The string in the sql_query<\/code> function is the SQL statement for the operation, and you can bind the result to structs with the bind<\/code> function.<\/p>\n\n\n\nmain<\/code> function uses a for-range loop to print the fields of the struct instance.<\/p>\n\n\n\n![\"\"](\"https:\/\/www.red-gate.com\/simple-talk\/wp-content\/uploads\/2024\/03\/word-image-101867-6-2.png\")
<\/figure>\n\n\n\n<\/a>Conclusion<\/h2>\n\n\n\n
FAQs: How to Use Any SQL Database With Rust<\/h2>\n\n
1. What is Diesel and how does it compare to other Rust database libraries?<\/h3>\n
2. How do I connect Rust to a PostgreSQL database with Diesel?<\/h3>\n
3. How do I perform a SELECT query with Diesel in Rust?<\/h3>\n
4. Does Diesel support async Rust database access?<\/h3>\n