Redowan Delowar

@rednafi.com

1767 Followers 570 Following

Roving amateur fumbling through software, systems, & sundry. Engineering @Doordash/Wolt Writing rednafi.com Currently in Berlin, Germany

A hand holds the front cover of the paperback book, The Rust Programming Language, 3rd Edition, against a textured off-white wall. Book Cover Details * Header: A dark red triangle in the top-right corner features the white text "3RD EDITION". * Title: The main title, "THE RUST PROGRAMMING LANGUAGE", is printed in large, bold, dark-brown capital letters on a cream-colored background. * Authors: A horizontal black banner below the title contains the text: "STEVE KLABNIK, CAROL NICHOLS, and CHRIS KRYCHO, with CONTRIBUTIONS from THE RUST COMMUNITY". * Illustration: The bottom half of the cover features a yellow, black, and white cartoon illustration of a marine scene. Ferris, the cute, wide-eyed Rust mascot crab, is sitting happily on a mound. The surrounding seabed includes simplified drawings of seaweed, smiling starfish, and small eels emerging from the sand. * Green Badge: A rounded green speech bubble near the top right of the illustration contains the white text "RUST 2024". * Publisher Logo: The circular black "no starch press" logo is located in the bottom-right corner. Framing and Composition A person with a medium-brown complexion holds the book by its left edge. The upper background is a textured, light-gray wall, while the bottom background shows a dark, reflective surface.
A good way to begin building readable APIs is to write pseudo-code and documentation before the implementation. Write pseudo- code that uses the API, think about the outcome for different inputs, and turn your insights from that exercise into documentation for the API. Only then, should you begin implementing it. This will give you a sense of how the API will be used. and let vou tweak and improve the experience before you put effort into the implementation. or get attached to a specific API or behavior. By making this a habit, you will built a better intuition for library design so that over time you need to do this less often.
both traces and metrics are an abstraction built on top of logs that pre-process and encode information along two orthogonal axes, one being request centric, the other being system centric
A code snippet in SQL syntax that defines a Cassandra table named `order_items`. The table has the following columns: - `customer_id` (UUID) - `order_id` (UUID) - `sku_id` (UUID) - `item_name` (text) - `quantity` (int) The `PRIMARY KEY` is a composite key with a **composite partition key** `((customer_id, order_id))` and a **clustering column** `sku_id`. The clustering order for `sku_id` is specified as descending using the `WITH CLUSTERING ORDER BY (sku_id DESC)` clause. The code is syntax-highlighted with keywords in purple and data types in muted colors.
Pydantic Logfire plan Free plan: $0, includes 10 million spans/metrics per month, free indefinitely, upgrade anytime. Pro plan: $2/million spans/metrics, includes 10 million spans/metrics per month, $2 per additional million, downgrade anytime, scale to zero.