Code Generation

# **Code Generation**

Situation 1: Generate a Python function that takes a list of dictionaries and filters them based on a specified key-value condition, with error handling.  
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Prompt 1: You are an expert software engineer specializing in Python function creation.

Generate a Python function that takes a list of dictionaries and filters them based on a specified key-value condition.

The function should accept three parameters:  
\- data (list of dicts): the list to filter  
\- key (str): the dictionary key to filter on    
\- value: the value to match against

The function should return a filtered list of dictionaries.

Example usage:  
data \= \[{"name": "Alice", "role": "admin"}, {"name": "Bob", "role": "user"}\]  
filter\_dicts(data, "role", "admin")  
\# Returns: \[{"name": "Alice", "role": "admin"}\]

Make sure to include error handling for this function, including but not limited to these cases below:  
\- data is not a list  
\- items inside the list are not dictionaries  
\- key does not exist in a dictionary

Include type hints on all parameters and the return value. Include a docstring that describes what the function does, its parameters, and return value.  
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Situation 2: Generate a FastAPI endpoint that accepts a POST request with a JSON body, validates the required fields, and returns a structured response.  
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Prompt 2: You are an expert software engineer specializing in FastAPI development.

Generate a FastAPI POST endpoint for creating a contact record with   
the following requirements:

Endpoint: POST /contacts  
Required fields: name (str), email (str)  
Optional fields: phone (str), company (str), tags (list of str)

The endpoint should:  
\- Validate that all required fields are present  
\- Store the contact in an in-memory dictionary with an auto-incremented integer ID  
\- Return the created contact with its assigned ID and HTTP status 201  
\- Return a 422 error with a descriptive message if required fields are missing

Use Pydantic BaseModel for request validation.  
Include type hints and a docstring on the endpoint function.

Example success response:  
{"id": 1, "name": "Alice", "email": "alice@example.com", "phone": null,   
 "company": null, "tags": \[\]}  
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Situation 3: Generate a Python function that calls an external REST API with retry logic and exponential backoff on 429 and 500 errors.  
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Prompt 3: You are an expert software engineer specializing in Python and REST API implementation.

Generate a Python function that calls an external REST API with retry logic and exponential backoff on 429 and 500 errors.

The function should take in the following parameters:  
\- url (str): the endpoint to call  
\- method (str): GET, POST, etc.  
\- payload (dict): request body for POST calls  
\- max\_retries (int): amount of times to retry before giving up

The try/except format should be used for 429 and 500 errors. Specifically:  
\- On 429: wait 2^attempt before trying  
\- On 500: same backoff  
\- After max\_retries exhausted: raise an exception with a descriptive message

Example usage: result \= call\_api\_with\_retry(url="https://api.example.com/data", method="GET", max\_retries=3)

Parse and return the JSON response using .json(). The return type should be dict | list to reflect that API responses may be either.

Include type hints on all parameters and the return value. Include a docstring that describes what the function does, its parameters, and return value.