Tech Events & Workshops

A practical two-hour session investigating how SQLx can detect invalid SQL, incompatible parameters, missing columns, and incorrect Rust mappings during compilation rather than after deployment. The session follows a query through the boundary between Rust and the database: from the SQL text and bound parameters, through schema inspection and type analysis, to the Rust value returned to the application. We will deliberately break queries, change schemas, and introduce type mismatches to understand what SQLx can prove before runtime—and what it cannot. The emphasis is not on memorizing an API. It is on understanding the engineering model behind compile-time checked SQL, the role of migrations in preserving that model, and the practical consequences for local development, testing, continuous integration, and deployment. Audience: developers who want to understand how Rust can provide stronger guarantees around ordinary SQL without replacing SQL with an ORM or query language. Outcomes: * Trace how SQLx validates a query during compilation * Understand how database metadata informs Rust type checking * See compile-time failures caused by invalid queries and incompatible result types * Understand why the current schema matters during a build * Connect database migrations to query correctness * Distinguish checked macros from runtime query APIs * Evaluate when compile-time SQL checking improves a project and when it adds friction Format: two hours with a guided investigation, broken-query experiments, migration examples, discussion of operational tradeoffs, and a reusable checklist for database code.

A practical two-hour session on building reliable data pipelines in Rust, starting from messy input files and ending with clean data that can be stored, queried, and visualized in a web application. The session combines Rust, Polars, command-line data workflows, and SQLx to show how a developer can take CSV or Parquet files, validate and transform the data, handle errors clearly, persist clean records into a database, and prepare the results for charts, dashboards, or reporting screens. Rust is used as the implementation context, but the main lesson stays focused on software engineering fundamentals: data contracts, repeatable workflows, visible progress, reliable error handling, database migrations, compile-time query checks, and operational clarity. Audience: entry-level and intermediate developers who want a practical engineering session on turning raw files into clean, queryable, visualizable data. Outcomes: * Build a Rust command-line workflow that accepts input files and produces structured outputs * Clean and validate CSV or Parquet data before storing it * Use Polars for filtering, selecting, joining, grouping, and lazy execution * Store clean records in a database with SQLx * Use migrations and compile-time checks to make database access safer * Prepare stored data for visualization in a web application Format: two hours with a short framing walkthrough, a concrete end-to-end example, discussion of tradeoffs, and a closing checklist for practice.