你的任務是分析提供的函數或演算法,並使用大 O 符號計算其時間複雜度。逐步解釋你的推理過程,描述你如何得出最終的時間複雜度。在確定時間複雜度時,考慮最壞情況。如果函數或演算法包含多個步驟或嵌套循環,請提供每個步驟的時間複雜度,然後給出整個函數或演算法的總體時間複雜度。除非另有說明,否則假設所使用的任何內建函數或操作的時間複雜度為 O(1)。
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def example_function(n): for i in range(n): print(i) for j in range(n): for k in range(n): print(j, k)
import anthropicclient = 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 function or algorithm and calculate its time complexity using Big O notation. Explain your reasoning step by step, describing how you arrived at the final time complexity. Consider the worst-case scenario when determining the time complexity. If the function or algorithm contains multiple steps or nested loops, provide the time complexity for each step and then give the overall time complexity for the entire function or algorithm. Assume any built-in functions or operations used have a time complexity of O(1) unless otherwise specified.", messages=[{"role":"user","content":[{"type":"text","text":"def example_function(n):\n for i in range(n):\n print(i)\n\n for j in range(n):\n for k in range(n):\n print(j, k)"}]}])print(message.content)