""PragmaticProgrammerAGIAgent":
    def __init__(self, code_generator, test_generator):
        self.code_generator = code_generator
        self.test_generator = test_generator
    
    def generate_code(self, prompt):
        # Generate code using the code generator
        code = self.code_generator.generate(prompt)
        return code
    
    def evaluate_code(self, code):
        # Evaluate the code using the test generator
        tests = self.test_generator.generate(code)
        results = []
        for test in tests:
            result = test(code)
            results.append(result)
        return results
    
    def refine_code(self, code, results):
        # Refine the code based on the evaluation results
        for result in results:
            if result is not None and result[0] == "fail":
                print("Failed test:", result[1])
                self.code_generator.refine(code)
                break
        return code
```
This implementation defines a `PragmaticProgrammerAGIAgent` class that takes a `code_generator` and a `test_generator` as arguments in its constructor. The `generate_code` method uses the `code_generator` to generate code based on a given prompt, while the `evaluate_code` method uses the `test_generator` to evaluate the generated code and return a list of test results. Finally, the `refine_code` method refines the code based on the evaluation results.

The `PragmaticProgrammerAGIAgent` class follows the principles of the Pragmatic Programmer's approach to software development, which emphasizes the importance of writing high-quality code and continuously improving it through testing and refinement. By using this class, developers can create high-quality code more efficiently and effectively.

Here is an example usage of the `PragmaticProgrammerAGIAgent` class:
```
# Create a new Pragmatic Programmer AI agent
agent = PragmaticProgrammerAGIAgent(CodeGenerator(), TestGenerator())

# Generate some code
code = agent.generate_code("Write a function that takes two integers and returns their product")

# Evaluate the code
results = agent.evaluate_code(code)

# Refine the code based on the evaluation results
refined_code = agent.refine_code(code, results)

print("Generated code:", code)
print("Evaluation results:", results)
print("Refined code:", refined_code)
```
This example demonstrates how to use the `PragmaticProgrammerAGIAgent` class to generate, evaluate, and refine code. The `generate_code` method generates a function that takes two integers and returns their product, while the `evaluate_code` method evaluates the generated code and returns a list of test results. Finally, the `refine_code` method refines the code based on the evaluation results.
""PragmaticProgrammerAGIAgent":
    def __init__(self, code_generator, test_generator):
        self.code_generator = code_generator
        self.test_generator = test_generator
    
    def generate_code(self, language="python", file_name="main.py"):
        # Generate code using the code generator
        code = self.code_generator.generate_code(language, file_name)
        return code
    
    def generate_tests(self, test_file_name="test_main.py", test_name="test_main"):
        # Generate tests using the test generator
        tests = self.test_generator.generate_tests(test_file_name, test_name)
        return tests
    
    def evaluate_code(self, code, tests):
        # Evaluate the code and its corresponding tests
        evaluation = self.evaluate_code(code)
        test_results = self.evaluate_tests(tests)
        return evaluation, test_results
    
    def refine_code(self, code, evaluation, test_results):
        # Refine the code based on the evaluation and test results
        refined_code = self.refine_code(code, evaluation, test_results)
        return refined_code
```
This is an example of how you could create a Pragmatic Programmer AGI agent in Python. The agent has four methods: `generate_code`, `generate_tests`, `evaluate_code`, and `refine_code`. The `generate_code` method takes a language and file name as input and returns the generated code. The `generate_tests` method takes a test file name and test name as input and returns the generated tests. The `evaluate_code` method takes the code as input and returns an evaluation of the code. The `refine_code` method takes the code, evaluation, and test results as input and returns a refined version of the code.

The agent follows the principles of the Pragmatic Programmer's approach to software development, which emphasizes the importance of generating high-quality code, evaluating it thoroughly, and refining it based on the results of that evaluation. By using this agent, you can create high-quality code that is well-tested and well-refined.
```
This is an example of how you could use the Pragmatic Programmer AGI agent in Python to generate, evaluate, and refine code. The agent has four methods: `generate_code`, `generate_tests`, `evaluate_code`, and `refine_code`. The `generate_code` method takes a language and file name as input and returns the generated code. The `generate_tests` method takes a test file name and test name as input and returns the generated tests. The `evaluate_code` method takes the code as input and returns an evaluation of the code. The `refine_code` method takes the code, evaluation, and test results as input and returns a refined version of the code.

To use the agent, you would first need to create instances of the code generator and test generator classes that the agent uses. For example:
```
code_generator = CodeGenerator()
test_generator = TestGenerator()

agent = PragmaticProgrammerAGIAgent(code_generator, test_generator)
```
Next, you would call the `generate_code` method to generate some code:
```
code = agent.generate_code("python", "main.py")
```
You could then call the `generate_tests` method to generate some tests for the code:
```
tests = agent.generate_tests("test_main.py", "test_main")
```
After that, you could call the `evaluate_code` method to evaluate the code and its corresponding tests:
```
evaluation, test_results = agent.evaluate_code(code)
```
Finally, you could call the `refine_code` method to refine the code based on the evaluation and test results:
```
refined_code = agent.refine_code(code, evaluation, test_results)
```
This is just one example of how you could use the Pragmatic Programmer AGI agent in Python. Depending on your specific needs and requirements, you may need to modify the agent's methods or add new ones. However, this should give you a good starting point for creating high-quality code that is well-tested and well-refined.
