Biblioteca de Prompts
Corrector de errores de Python
Recursos
- Overview
- Inicios rápidos
- Ficha técnica de Claude 3
- Tarjeta de sistema de Claude 3.7
- Estado del sistema
- Cursos de Anthropic
- Biblioteca de Prompts
- Biblioteca de Prompts
- Pulsaciones Cósmicas
- Clarividente corporativo
- Asistente de sitios web
- Experto en fórmulas de Excel
- Programador de scripts para Google Apps
- Corrector de errores de Python
- Consultor de viajes en el tiempo
- Compañero de narración
- Cita tus fuentes
- Hechicero SQL
- Intérprete de sueños
- Pun-dit
- Creador culinario
- Poeta de palabras combinadas
- Hal el ayudante humorístico
- Leyenda de LaTeX
- Colorizador de estados de ánimo
- Git gud
- Genio de los símiles
- Navegador de dilemas éticos
- Escriba de reuniones
- Iluminador de modismos
- Consultor de código
- Fabricante de funciones
- Creador de neologismos
- Conversor de CSV
- Codificador de emojis
- Pulidor de prosa
- Evaluador de perspectivas
- Generador de trivias
- Mentor de atención plena
- Simplificador de segundo grado
- Innovador de fitness en RV
- Purificador de PII
- Maestro de memorandos
- Entrenador de carrera profesional
- Gurú de calificación
- Trabalenguas
- Creador de preguntas para entrevistas
- Genio gramatical
- Adivina adivinanza
- Clarificador de código
- Antropólogo alienígena
- Organizador de datos
- Creador de marca
- Estimador de eficiencia
- Clasificador de reseñas
- Decodificador de instrucciones
- Musa motivacional
- Extractor de correos electrónicos
- Moderador experto
- Planificador de lecciones
- Sabio socrático
- Alquimista de aliteraciones
- Asesor de moda futurista
- Superpoderes políglotas
- Experto en nombres de productos
- Reflexiones filosóficas
- Hechicero de hojas de cálculo
- Simulador de escenarios de ciencia ficción
- Editor adaptativo
- Transmisiones de Babel
- Detector de tono de tweets
- Analista de códigos de aeropuerto
Biblioteca de Prompts
Corrector de errores de Python
Detecta y corrige errores en código Python.
Copia este prompt en nuestra Consola para desarrolladores para probarlo tú mismo.
Contenido | |
---|---|
System | Tu tarea es analizar el fragmento de código Python proporcionado, identificar cualquier error o fallo presente, y proporcionar una versión corregida del código que resuelva estos problemas. Explica los problemas que encontraste en el código original y cómo tus correcciones los solucionan. El código corregido debe ser funcional, eficiente y adherirse a las mejores prácticas en programación Python. |
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) |
Ejemplo de salida
Código Python corregido:
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)
Explicación:
- Cambié el nombre de la variable “sum” a “total” para evitar usar la función incorporada de Python “sum()”.
- Corregí el error tipográfico en la instrucción print, cambiando “results” a “result” para hacer referencia correctamente a la variable.
Solicitud de API
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);
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