anthropic-sdk-guide

Anthropic SDK Guide

Comprehensive reference for building with the Anthropic Python and TypeScript SDKs. Covers initialization, messages API, streaming, prompt caching, batches, and error handling.

When to Use

• User is setting up Anthropic SDK (Python or TypeScript)
• User is calling the Messages API or needs streaming responses
• User wants prompt caching, batch processing, or token counting
• User is debugging API errors or rate limits
• User asks about Claude model IDs or API configuration

Core Patterns

SDK Installation and Setup

# Python
pip install anthropic

# TypeScript
npm install @anthropic-ai/sdk

# Python - client initialization
import anthropic

client = anthropic.Anthropic()  # Uses ANTHROPIC_API_KEY env var
# Or explicit: anthropic.Anthropic(api_key="sk-ant-...")

// TypeScript - client initialization
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();  // Uses ANTHROPIC_API_KEY env var

Messages API - Basic Usage

# Python - simple message
message = client.messages.create(
    model="claude-sonnet-4-6-20250514",
    max_tokens=1024,
    system="You are a helpful coding assistant.",
    messages=[
        {"role": "user", "content": "Explain async/await in Python."}
    ]
)
print(message.content[0].text)

// TypeScript - simple message
const message = await client.messages.create({
  model: "claude-sonnet-4-6-20250514",
  max_tokens: 1024,
  system: "You are a helpful coding assistant.",
  messages: [
    { role: "user", content: "Explain async/await in Python." }
  ],
});
console.log(message.content[0].text);

Streaming Responses

# Python - streaming with context manager
with client.messages.stream(
    model="claude-sonnet-4-6-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a short story."}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

# Access final message after stream completes
final_message = stream.get_final_message()