1. Welcome
  2. Content
  3. 1. Introduction to Rust for Data Engineering
    1. 1.1. Introduction to Rust
    2. 1.2. History of Rust
    3. 1.3. Features of Rust
    4. 1.4. Advantages of Rust for Data Engineering
    5. 1.5. How does Rust compare to Python? (and other programming languages)
    6. 1.6. Conclusion
  4. 2. Getting started with Rust, developer environment setup and basics
    1. 2.1. Setting up a Rust developer environment
    2. 2.2. Configuring an IDE
    3. 2.3. Creating your first programs (rustc)
    4. 2.4. Working with Cargo
    5. 2.5. Basic syntax
    6. 2.6. Data types
    7. 2.7. Functions, modules & error handling
    8. 2.8. Rust specific features
    9. 2.9. Crates & dependencies
    10. 2.10. Rust for data in 15 minutes
  5. 3. Working with Data in Rust, data modelling, working with CSV, JSON, serialising and data structures
  6. 4. Testing and debugging with Rust
  7. 5. Parallel and concurrent programming in Rust
  8. 6. Your first data pipelines with Rust: Extract data with API requests, scraping, parquet, avro, databases & SQLite
  9. 7. Your first data pipelines with Rust: Transform data with pola.rs and Arrow DataFusion
  10. 8. 👩‍🏫 Your first data pipelines with Rust: Bringing it all together
  11. 9. 👩‍🏫 Simple data products with Rust: CLI job, create an API, process realtime data
  12. 10. 👩‍🏫 Advanced data products: benchmarking code, profiling and call Rust from Python with PyO3
  13. 11. Rust for the future
  14. Changelog
  15. Feedback
  16. Author
  17. Copyright
  18. Legal Notice
  19. Privacy Policy

Data With Rust

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