Topic

RustRover

2 posts about RustRover. Every summary links to the original.

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Posts

Jetbrains
RustRover vs VS Code + rust-analyzer: What Changes in Your Rust Workflow
This post compares RustRover and VS Code with the rust-analyzer extension for Rust development, detailing their architectural differences. VS Code, a general-purpose editor, relies on the rust-analyzer language server to provide completion, diagnostics, inlay hints, navigation, quick-fixes, and refactoring. RustRover is a dedicated professional IDE using JetBrains’ own analysis engine that builds a model of crates, dependencies, targets, and code structure from the Cargo workspace, with built-in debugging, testing, and version control. Key differences include RustRover’s integrated debugger versus VS Code’s need for an extension like CodeLLDB, and RustRover’s project-wide refactoring with affected-usage review. AI assistant capabilities also differ, with RustRover offering agent-driven tasks through Air and JetBrains AI while VS Code supports inline suggestions and agent providers like Copilot. The post offers a five-step migration guide for VS Code users and concludes the choice depends on whether one prefers a modular editor or an integrated IDE experience.

Jetbrains
100 Exercises to Learn Rust, Updated
The post announces a major update to the free JetBrains Academy course ‘100 Exercises to Learn Rust,’ which runs inside RustRover. The course teaches Rust through hands-on exercises building a ticket management system across eight chapters from ownership to futures, assuming fluency in another language. The update adds a rebuilt introduction, an FAQ, a final challenge turning the system into an async REST API by editing Cargo.toml and verifying with a requests.http file, visible test assertions, and a dev/release profile experiment. A ‘fast track’ lets experienced users skip to the final challenge to quickly see which areas need revisiting. The post advises using AI for explanations, not code generation, and turning off AI code completion during exercises to maximize learning from getting stuck and working out solutions.

The best engineering reads, once a week.

Topic

2 posts about RustRover. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

Jetbrains
RustRover vs VS Code + rust-analyzer: What Changes in Your Rust Workflow
This post compares RustRover and VS Code with the rust-analyzer extension for Rust development, detailing their architectural differences. VS Code, a general-purpose editor, relies on the rust-analyzer language server to provide completion, diagnostics, inlay hints, navigation, quick-fixes, and refactoring. RustRover is a dedicated professional IDE using JetBrains’ own analysis engine that builds a model of crates, dependencies, targets, and code structure from the Cargo workspace, with built-in debugging, testing, and version control. Key differences include RustRover’s integrated debugger versus VS Code’s need for an extension like CodeLLDB, and RustRover’s project-wide refactoring with affected-usage review. AI assistant capabilities also differ, with RustRover offering agent-driven tasks through Air and JetBrains AI while VS Code supports inline suggestions and agent providers like Copilot. The post offers a five-step migration guide for VS Code users and concludes the choice depends on whether one prefers a modular editor or an integrated IDE experience.

Jetbrains
100 Exercises to Learn Rust, Updated
The post announces a major update to the free JetBrains Academy course ‘100 Exercises to Learn Rust,’ which runs inside RustRover. The course teaches Rust through hands-on exercises building a ticket management system across eight chapters from ownership to futures, assuming fluency in another language. The update adds a rebuilt introduction, an FAQ, a final challenge turning the system into an async REST API by editing Cargo.toml and verifying with a requests.http file, visible test assertions, and a dev/release profile experiment. A ‘fast track’ lets experienced users skip to the final challenge to quickly see which areas need revisiting. The post advises using AI for explanations, not code generation, and turning off AI code completion during exercises to maximize learning from getting stuck and working out solutions.

The best engineering reads, once a week.