Python bug buster - Anthropic

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	Content
System	Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.
User	def calculate_average(nums): sum = 0 for num in nums: sum += num average = sum / len(nums) return average numbers = [10, 20, 30, 40, 50] result = calculate_average(numbers) print(“The average is:”, results)

Example Output

Corrected Python code:

Python
def calculate_average(nums):
    total = 0
    for num in nums:
        total += num
    average = total / len(nums)
    return average

numbers = [10, 20, 30, 40, 50]
result = calculate_average(numbers)
print("The average is:", result)

Explanation:

Changed the variable name “sum” to “total” to avoid using the built-in Python function “sum()”.
Fixed the typo in the print statement, changing “results” to “result” to correctly reference the variable.

API Request

import anthropic

client = anthropic.Anthropic(
  # defaults to os.environ.get("ANTHROPIC_API_KEY")
  api_key="my_api_key",
)
message = client.messages.create(
  model="claude-opus-4-20250514",
  max_tokens=1000,
  temperature=0,
  system="Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.",
  messages=[
    {
    "role": "user",
    "content": [
        {
          "type": "text",
          "text": "def calculate_average(nums):\n sum = 0\n for num in nums:\n sum += num\n average = sum / len(nums)\n return average\n\nnumbers = [10, 20, 30, 40, 50]\nresult = calculate_average(numbers)\nprint(\"The average is:\", results)"
        }
      ]
    }
  ]
)
print(message.content)

import anthropic

client = anthropic.Anthropic(
  # defaults to os.environ.get("ANTHROPIC_API_KEY")
  api_key="my_api_key",
)
message = client.messages.create(
  model="claude-opus-4-20250514",
  max_tokens=1000,
  temperature=0,
  system="Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.",
  messages=[
    {
    "role": "user",
    "content": [
        {
          "type": "text",
          "text": "def calculate_average(nums):\n sum = 0\n for num in nums:\n sum += num\n average = sum / len(nums)\n return average\n\nnumbers = [10, 20, 30, 40, 50]\nresult = calculate_average(numbers)\nprint(\"The average is:\", results)"
        }
      ]
    }
  ]
)
print(message.content)

import Anthropic from "@anthropic-ai/sdk";

const anthropic = new Anthropic({
  apiKey: "my_api_key", // defaults to process.env["ANTHROPIC_API_KEY"]
});

const msg = await anthropic.messages.create({
  model: "claude-opus-4-20250514",
  max_tokens: 1000,
  temperature: 0,
  system: "Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.",
  messages: [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "def calculate_average(nums):\n   sum = 0\n   for num in nums:\n      sum += num\n   average = sum / len(nums)\n   return average\n\nnumbers = [10, 20, 30, 40, 50]\nresult = calculate_average(numbers)\nprint(\"The average is:\", results)"
        }
      ]
    }
  ]
});
console.log(msg);

from anthropic import AnthropicBedrock

# See https://docs.anthropic.com/claude/reference/claude-on-amazon-bedrock

# for authentication options

client = AnthropicBedrock()

message = client.messages.create(
model="anthropic.claude-opus-4-20250514-v1:0",
max_tokens=1000,
temperature=0,
system="Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "def calculate_average(nums):\n sum = 0\n for num in nums:\n sum += num\n average = sum / len(nums)\n return average\n\nnumbers = [10, 20, 30, 40, 50]\nresult = calculate_average(numbers)\nprint(\"The average is:\", results)"
}
]
}
]
)
print(message.content)

import AnthropicBedrock from "@anthropic-ai/bedrock-sdk";

// See https://docs.anthropic.com/claude/reference/claude-on-amazon-bedrock
// for authentication options
const client = new AnthropicBedrock();

const msg = await client.messages.create({
  model: "anthropic.claude-opus-4-20250514-v1:0",
  max_tokens: 1000,
  temperature: 0,
  system: "Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.",
  messages: [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "def calculate_average(nums):\n   sum = 0\n   for num in nums:\n      sum += num\n   average = sum / len(nums)\n   return average\n\nnumbers = [10, 20, 30, 40, 50]\nresult = calculate_average(numbers)\nprint(\"The average is:\", results)"
        }
      ]
    }
  ]
});
console.log(msg);

from anthropic import AnthropicVertex

client = AnthropicVertex()

message = client.messages.create(
model="claude-3-7-sonnet-v1@20250219",
max_tokens=1000,
temperature=0,
system="Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "def calculate_average(nums):\n sum = 0\n for num in nums:\n sum += num\n average = sum / len(nums)\n return average\n\nnumbers = [10, 20, 30, 40, 50]\nresult = calculate_average(numbers)\nprint(\"The average is:\", results)"
}
]
}
]
)
print(message.content)

import { AnthropicVertex } from '@anthropic-ai/vertex-sdk';

// Reads from the `CLOUD_ML_REGION` & `ANTHROPIC_VERTEX_PROJECT_ID` environment variables.
// Additionally goes through the standard `google-auth-library` flow.
const client = new AnthropicVertex();

const msg = await client.messages.create({
  model: "claude-3-7-sonnet-v1@20250219",
  max_tokens: 1000,
  temperature: 0,
  system: "Your task is to analyze the provided Python code snippet, identify any bugs or errors present, and provide a corrected version of the code that resolves these issues. Explain the problems you found in the original code and how your fixes address them. The corrected code should be functional, efficient, and adhere to best practices in Python programming.",
  messages: [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "def calculate_average(nums):\n   sum = 0\n   for num in nums:\n      sum += num\n   average = sum / len(nums)\n   return average\n\nnumbers = [10, 20, 30, 40, 50]\nresult = calculate_average(numbers)\nprint(\"The average is:\", results)"
        }
      ]
    }
  ]
});
console.log(msg);

Resources

​Example Output

​API Request

Example Output

API Request