Quiz: How to Use the Claude API in Python

Interactive Quiz ⋅ 9 QuestionsBy Joseph Peart Share In this quiz, you’ll test your knowledge of How to Use the Claude API in Python. By working through this quiz, you’ll revisit how to install the anthropic SDK, send prompts to Claude with client.messages.create(), shape responses with a system parameter, and return structured JSON output using a schema or Pydantic. The quiz contains 9 questions and there is no time limit. You’ll get 1 point for each correct answer. At the […]

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How to Use the Claude API in Python

The fastest way to use the Claude API in Python is to install anthropic, set your API key, and call client.messages.create(). You’ll have a working response in under a minute: Example of Using the Claude API in Python Claude is Anthropic’s large language model, accessible via a clean REST API with an official Python SDK. Unlike heavier AI frameworks that require you to wire up multiple components before    

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Quiz: Tapping Into the Zen of Python

Interactive Quiz ⋅ 8 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Tapping Into the Zen of Python. By working through this quiz, you’ll revisit the origins of the poem, the meaning of several aphorisms, and the inside jokes hidden throughout. The questions explore how the principles apply in practice and when it’s okay to bend the rules in the name of practicality. The quiz contains 8 questions and there is no time limit. You’ll get […]

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Quiz: Absolute vs Relative Imports in Python

Interactive Quiz ⋅ 7 QuestionsBy Joseph Peart Share In this quiz, you’ll test your understanding of Absolute vs Relative Imports in Python. By working through this quiz, you’ll revisit how Python’s import system resolves modules, the differences between absolute and relative imports, and the PEP 8 conventions for styling import statements. The quiz contains 7 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total […]

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Tapping Into the Zen of Python

The Zen of Python is a collection of 19 aphorisms that capture the guiding principles behind Python’s design. You can display them anytime by running import this in a Python REPL. Tim Peters wrote them in 1999 as a joke, but they became an iconic part of Python culture that was even formalized as PEP 20. By the end of this video course, you’ll understand: The Zen of Python is a humorous poem of 19 aphorisms describing Python’s design philosophy […]

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Python Built-in Functions: A Complete Guide

Python’s built-in functions are predefined functions you can use anywhere in your code without any imports. They handle common tasks across math, data type creation, iterable processing, and input and output. Knowing which ones to reach for makes your code shorter and more Pythonic. To get the most out of this tutorial, you’ll need to be familiar with Python programming, including topics like working with built-in data types, functions, classes, decorators, scopes, and the import system. Built-in Functions in Python […]

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Building Blocks for Foundation Model Training and Inference on AWS

For a long time, “scaling” in foundation models mostly meant one thing: spend more compute on pre-training and capabilities rise. That intuition was supported by empirical work such as Kaplan et al. (2020), which reported predictable power-law trends in loss as you scale model parameters, dataset size, and training compute. In practice, these trends justified sustained investment in large-scale accelerator capacity and the surrounding distributed infrastructure needed to keep it efficiently utilized. But the frontier has evolved—and scaling is no […]

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Unlocking asynchronicity in continuous batching

TL;DR: we explain how to separate CPU and GPU workloads to get a massive performance boost for inference. This is the second post in a series on efficient LLM inference. The first post covered continuous batching from first principles. It introduces some concepts we build upon: KV cache, FlashAttention, attention masks, etc. An H200 costs around $5 an hour on Inference Endpoints. That’s cheap for an hour, but use it for a day and you are already paying $120. If […]

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Granite Embedding Multilingual R2: Open Apache 2.0 Multilingual Embeddings with 32K Context — Best Sub-100M Retrieval Quality

TL;DR: Two new Apache 2.0 multilingual embedding models built on ModernBERT — a 97M-parameter compact model that beats every open sub-100M multilingual embedder on MTEB Multilingual Retrieval (60.3), and a 311M full-size model that scores 65.2 on MTEB Multilingual Retrieval (#2 among open models under 500M parameters) with Matryoshka support. Both cover 200+ languages, are tuned on 52 languages, handle 32K-token context (64x R1), and add code retrieval across 9 programming languages. In this post: Enterprise-Ready by Design · A […]

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Further Notes on Our Recent Research on AI Delegation and Long-Horizon Reliability

Our recent paper, “LLMs Corrupt Your Documents When You Delegate”, has generated discussion about the reliability of AI systems in delegated workflows. We appreciate the interest in this work and want to clarify several important points about what the paper does—and does not—claim. The research aims to develop robust evaluation methods for long-horizon delegated and collaborative tasks. More broadly, this work reflects an ongoing effort to better understand the gap between strong benchmark performance and certain real-world tasks. Using a […]

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