Claude API Python Tutorial

This guide covers using the Claude API in Python with both the native Anthropic SDK and the OpenAI-compatible client. All examples work with APIMaster.ai—swap in your own base URL and API key.

Installation

pip install anthropic          # Native Anthropic SDK
pip install openai             # OpenAI-compatible (optional)

Basic Setup

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_APIMASTER_KEY",
    base_url="https://apimaster.ai",  # No /v1 for Anthropic SDK
)

Or with OpenAI SDK (easier if you already use OpenAI):

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_APIMASTER_KEY",
    base_url="https://apimaster.ai/v1",
)

Your First Claude API Call

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_APIMASTER_KEY",
    base_url="https://apimaster.ai",
)

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain the difference between lists and tuples in Python."}
    ],
)

print(message.content[0].text)

System Prompts

response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=512,
    system="You are a senior Python engineer. Be concise and use code examples.",
    messages=[
        {"role": "user", "content": "What's the fastest way to flatten a nested list?"}
    ],
)
print(response.content[0].text)

Multi-Turn Conversation

conversation = []

def chat(user_message):
    conversation.append({"role": "user", "content": user_message})
    response = client.messages.create(
        model="claude-sonnet-4-6",
        max_tokens=1024,
        messages=conversation,
    )
    assistant_message = response.content[0].text
    conversation.append({"role": "assistant", "content": assistant_message})
    return assistant_message

print(chat("What is a decorator in Python?"))
print(chat("Can you show me a practical example?"))

Streaming Responses

Streaming returns tokens as they're generated—better UX for long outputs:

with client.messages.stream(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a Python web scraper using requests and BeautifulSoup."}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
print()  # newline at end

Vision: Analyzing Images

Claude Sonnet and Opus support image inputs (base64 or URL):

import base64

with open("chart.png", "rb") as f:
    image_data = base64.standard_b64encode(f.read()).decode("utf-8")

response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=512,
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image",
                    "source": {
                        "type": "base64",
                        "media_type": "image/png",
                        "data": image_data,
                    },
                },
                {"type": "text", "text": "Summarize what this chart shows."},
            ],
        }
    ],
)
print(response.content[0].text)

Tool Use (Function Calling)

tools = [
    {
        "name": "get_weather",
        "description": "Get current weather for a city",
        "input_schema": {
            "type": "object",
            "properties": {
                "city": {"type": "string", "description": "City name"},
            },
            "required": ["city"],
        },
    }
]

response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=256,
    tools=tools,
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
)

# Check if Claude wants to call a tool
if response.stop_reason == "tool_use":
    tool_call = next(b for b in response.content if b.type == "tool_use")
    print(f"Tool: {tool_call.name}, Input: {tool_call.input}")

Async Usage

import asyncio
import anthropic

async def main():
    client = anthropic.AsyncAnthropic(
        api_key="YOUR_APIMASTER_KEY",
        base_url="https://apimaster.ai",
    )
    response = await client.messages.create(
        model="claude-sonnet-4-6",
        max_tokens=256,
        messages=[{"role": "user", "content": "Hello!"}],
    )
    print(response.content[0].text)

asyncio.run(main())

Error Handling

import anthropic

try:
    response = client.messages.create(
        model="claude-sonnet-4-6",
        max_tokens=256,
        messages=[{"role": "user", "content": "Hello"}],
    )
except anthropic.AuthenticationError:
    print("Invalid API key")
except anthropic.RateLimitError:
    print("Rate limit—add retry logic")
except anthropic.APIStatusError as e:
    print(f"API error {e.status_code}: {e.message}")

Choosing the Right Claude Model for Python Projects

Task	Model	Reason
Chatbots, Q&A	claude-haiku-4-5	Fast + cheap
Code generation	claude-sonnet-4-6	Best balance
Complex reasoning	claude-opus-4-8	Highest accuracy
Document analysis	claude-sonnet-4-6	200K context

Get Claude API Access

Register at APIMaster.ai to get a Claude API key that works worldwide, with discounted pricing and fingerprint-verified authentic models.

See also: Claude API Pricing · How to Get a Claude API Key