Tech Events & Workshops
Discover and join virtual tech events, workshops, and meetups from the Ubuntu community worldwide. Connect with developers, engineers, and tech enthusiasts.
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Rust Data Pipelines: From Files to Clean Databases and Web Dashboards
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.
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Rust Data Pipelines: From Files to Clean Databases and Web Dashboards
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.
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Rust Data Processing with Polars: CSV, Parquet, Joins, and Lazy Queries
A practical two-hour session on Rust Data Processing with Polars, focused on CSV, Parquet, Joins, and Lazy Queries. Rust is used as the implementation context while the core lesson stays on software engineering fundamentals, reliability, testing, and operational clarity. Audience: entry-level and intermediate developers who want a practical engineering session, not a language tour. Outcomes: - Explain the practical boundaries of Rust Data Processing with Polars - Apply CSV in a small working example - Apply Parquet in a small working example - Apply Joins in a small working example Format: two hours with a short framing walkthrough, a concrete example, discussion of tradeoffs, and a closing checklist for practice.
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