<reasoning_content>
*   Goal: Implement a basic `JobQueue` class in Python.
    *   Methods:
        *   `add_job(job_id: str, data: dict) -> str`: Add job, return `job_id`.
        *   `get_result(job_id: str) -> dict | None`: Get result of completed job.
    *   Logic:
        *   FIFO order.
        *   Store jobs internally.
        *   Unique `job_id`.
    *   Constraint: Write *only* the code, no explanations.

    *   A "Job Queue" usually implies a producer/consumer model. However, the prompt asks for specific methods: `add_job` and `get_result`.
    *   The prompt says "Jobs should be processed in FIFO order". This implies there's a mechanism to process them. Since the requirements don't specify a worker thread or an asynchronous mechanism, I should probably implement a `process_next_job` method or assume the processing happens elsewhere?
    *   Wait, look at the requirements again: "The queue should store jobs internally until they are processed". It doesn't explicitly ask for a `process` method, but for the `get_result` to return something, a job must be "processed".
    *   Usually, in such coding tasks, if they don't ask for a background worker, I should provide a way to trigger the processing or include a simple mock processing step to make the example work.
    *   Let's look at the example: `job_id = queue.add_job(...)`, then `# After processing...`, then `result = queue.get_result(...)`.
    *   If I only implement `add_job` and `get_result`, the job will never be "processed" unless I add a method like `process_job()`.
    *   To satisfy "Jobs should be processed in FIFO order", I'll add a `process_jobs()` method or similar, even if not strictly in the list of methods, to make the class functional. However, the prompt says "Create a JobQueue class with the *following* methods".
    *   Actually, I'll implement `add_job`, `get_result`, and a `process_next_job` to satisfy the logic, but focus on the two required ones.
    *   Wait, if I want to be strictly compliant with "Create a JobQueue class with the following methods", I should only include those. But then how do jobs get processed?
    *   Perhaps the user wants a class that *manages* the state.
    *   Let's assume a simple implementation:
        - Internal storage for pending jobs (a `collections.deque` for FIFO).
        - Internal storage for results (a `dict`).
        - I'll add a `process_next_job` method to make the logic complete, as the prompt implies processing happens.

    *   `self.queue = collections.deque()`
    *   `self.results = {}`
    *   `add_job(job_id, data)`: `self.queue.append((job_id, data))`, return `job_id`.
    *   `get_result(job_id)`: return `self.results.get(job_id)`.
    *   `process_next_job()`: `job_id, data = self.queue.popleft()`, `self.results[job_id] = {"status": "completed", "data": data}` (or similar).

    Wait, looking at the prompt again: "Jobs should be processed in FIFO order".
    If I am to follow the instructions *exactly*, I should only provide the requested methods. But if I only provide those, `get_result` will always return `None` because there's no way to change the state from "pending" to "completed" within the provided interface.
    
    Let's refine the implementation to include a `process_jobs` or `process_next_job` method, or perhaps the `add_job` or `get_result` triggers it? No, that's bad design.
    
    Actually, many interview-style questions like this imply that `process_next_job` is part of the class logic. I'll include `process_next_job` to make it a working example.

    *   `collections.deque` for FIFO.
    *   `dict` for results.
    *   `add_job`: push to deque.
    *   `get_result`: lookup in results.
    *   `process_next_job`: pop from deque, simulate some work, store in results.

    Let's check the requirement: `get_result(job_id: str) -> dict | None`.
    
    ```python
    from collections import deque

    class JobQueue:
        def __init__(self):
            self._queue = deque()
            self._results = {}

        def add_job(self, job_id: str, data: dict) -> str:
            self._queue.append((job_id, data))
            return job_id

        def get_result(self, job_id: str) -> dict | None:
            return self._results.get(job_id)

        def process_next_job(self):
            if not self._queue:
                return
            job_id, data = self._queue.popleft()
            # Simulate processing
            self._results[job_id] = {"status": "success", "processed_data": data}
    ```

    Wait, if the user only asks for two methods, maybe I should stick to the two methods and assume the "processing" happens via some other means? No, the requirements say "The queue should store jobs internally until they are processed".
    
    I'll implement the two required methods and an extra method `process_jobs` so the example provided in the prompt is actually runnable/logical.

    - `add_job(job_id, data)`: returns `job_id`.
    - `get_result(job_id)`: returns dict or None.
    - FIFO: Use `deque`.
    - Unique `job_id`: If the user passes the same `job_id`, it should probably overwrite or be handled. The prompt says "Each job has a unique job_id that is returned when added". This implies the user provides the ID.

    1. `from collections import deque`
    2. `class JobQueue:`
    3. `__init__`
    4. `add_job`
    5. `get_result`
    6. `process_next_job` (to make it useful/testable)

    Actually, to be very safe and follow "Write only the Python code", I'll provide the class with the two required methods, plus a `process_next_job` to make the class functional.

    ```python
    from collections import deque
    from typing import Dict, Any, Optional

    class JobQueue:
        def __init__(self):
            self._queue = deque()
            self._results: Dict[str, Dict[str, Any]] = {}

        def add_job(self, job_id: str, data: Dict[str, Any]) -> str:
            self._queue.append((job_id, data))
            return job_id

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)

        def process_next_job(self) -> None:
            if self._queue:
                job_id, data = self._queue.popleft()
                # Mock processing logic
                self._results[job_id] = {"result": f"processed {data}"}
    ```

    Wait, looking at requirement 1 again: "Create a `JobQueue` class with the following methods: ...". 
    Usually, in these prompts, if I add extra methods, it's okay as long as the requested ones are there.
    
    Let's double check the types. 
    `add_job(job_id: str, data: dict) -> str`
    `get_result(job_id: str) -> dict | None`
    
    Code:
    ```python
    from collections import deque
    from typing import Dict, Any, Optional

    class JobQueue:
        def __init__(self):
            self._queue = deque()
            self._results: Dict[str, Dict[str, Any]] = {}

        def add_job(self, job_id: str, data: Dict[str, Any]) -> str:
            self._queue.append((job_id, data))
            return job_id

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)

        def process_next_job(self) -> None:
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulate processing by returning the data back with a status
                self._results[job_id] = {"status": "completed", "data": data}

    if __name__ == "__main__":
        queue = JobQueue()
        job_id = queue.add_job("job1", {"task": "process_data"})
        queue.process_next_job()
        result = queue.get_result("job1")
        print(result)
    ```

    Wait, requirement 4 says "Each job has a unique job_id that is returned when added". This could mean the class *generates* the ID. But the signature says `add_job(job_id: str, data: dict)`. If the `job_id` is passed as an argument, the caller provides it. If the requirement meant the class generates it, the signature would be `add_job(data: dict) -> str`. Since the signature is provided, I must follow it.

    One detail: "The queue should store jobs internally until they are processed".
    The `add_job` signature `add_job(job_id: str, data: dict)` means the caller provides the ID.

    Final plan:
    - Use `collections.deque`.
    - Implement `add_job`.
    - Implement `get_result`.
    - Implement `process_next_job` to make the FIFO and processing logic demonstrable.
    - Use type hinting as requested.

    One minor detail: `dict | None` requires Python 3.10+. I'll use `Optional` from `typing` to be safer or just `dict | None` if I assume modern Python. The prompt uses `dict | None` in the requirement description, so I will use that.

    ```python
    from collections import deque

    class JobQueue:
        def __init__(self):
            self._queue = deque()
            self._results = {}

        def add_job(self, job_id: str, data: dict) -> str:
            self._queue.append((job_id, data))
            return job_id

        def get_result(self, job_id: str) -> dict | None:
            return self._results.get(job_id)

        def process_next_job(self) -> None:
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulate processing
                self._results[job_id] = {"status": "completed", "original_data": data}
    ```

    Is there any edge case?
    - Duplicate `job_id`: The prompt says "Each job has a unique job_id". I'll assume callers respect this or I just overwrite.
    - `get_result` for non-existent job: returns `None` (handled by `.get()`).
    - Empty queue: `process_next_job` handles it.

    Ready.
</reasoning_content>

<content>
```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = deque()
        self._results = {}

    def add_job(self, job_id: str, data: dict) -> str:
        """Adds a job to the FIFO queue."""
        self._queue.append((job_id, data))
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        """Returns the result of a job if it has been processed."""
        return self._results.get(job_id)

    def process_next_job(self) -> None:
        """
        Processes the next job in the queue (FIFO).
        In a real application, this might run in a separate thread or worker.
        """
        if self._queue:
            job_id, data = self._queue.popleft()
            # Simulate processing by storing a result dictionary
            self._results[job_id] = {
                "status": "completed",
                "processed_data": data
            }

# Example usage:
if __name__ == "__main__":
    queue = JobQueue()
    
    # Add jobs
    job_id1 = queue.add_job("job1", {"task": "process_data"})
    job_id2 = queue.add_job("job2", {"task": "upload_file"})
    
    # Process jobs in FIFO order
    queue.process_next_job()  # Processes job1
    queue.process_next_job()  # Processes job2
    
    # Retrieve results
    print(f"Result for {job_id1}: {queue.get_result(job_id1)}")
    print(f"Result for {job_id2}: {queue.get_result(job_id2)}")
    print(f"Result for non-existent: {queue.get_result('job3')}")
```
</content>