How do you use the OpenAI API for code generation, review, and debugging tasks?

from openai import OpenAI
client = OpenAI()

# 1. Code generation with constraints:
generated = client.responses.create(
    model="gpt-5.5",
    instructions="""You are a senior Python engineer. Always:
    - Add type hints
    - Write docstrings (Google style)
    - Include basic error handling
    - Add a usage example in if __name__ == "__main__"
    """,
    input="Write a function to parse a CSV file and return a list of dicts.",
    reasoning={"effort": "medium"},
)

# 2. Code review with structured output:
from pydantic import BaseModel
class Review(BaseModel):
    summary: str
    bugs: list[str]
    security_issues: list[str]
    performance_issues: list[str]
    suggested_improvements: list[str]
    severity: str  # "clean" | "low" | "medium" | "high" | "critical"

review = client.responses.create(
    model="gpt-5.5",
    input=f"Review this code:\n\n```python\n{code_to_review}\n```",
    text={"format": {"type": "json_schema",
                     "json_schema": {"name": "review", "schema": Review.model_json_schema(), "strict": True}}},
)
result = Review.model_validate_json(review.output_text)

# 3. Debugging:
debug_response = client.responses.create(
    model="gpt-5.5",
    input=f"""Debug this code. I get this error:\n\n{error_traceback}\n\nCode:\n{code}\n\nExplain the root cause and provide a fix.""",
    reasoning={"effort": "high"},
)

# 4. Unit test generation:
tests = client.responses.create(
    model="gpt-5.5",
    instructions="Generate comprehensive pytest tests. Include edge cases, error cases, and typical usage.",
    input=f"Generate tests for:\n\n{function_code}",
    tools=[{"type": "code_interpreter"}],  # run tests to verify they pass
)