<reasoning_content>
*   Target: Implement a basic `JobQueue` class in Python.
    *   Required methods:
        *   `add_job(job_id: str, data: dict) -> str` (adds a job, returns ID).
        *   `get_result(job_id: str) -> dict | None` (retrieves result).
    *   Requirements:
        *   FIFO order.
        *   Internal storage until processed.
        *   Unique `job_id`.
    *   Constraint: Write *only* the Python code, no explanations.

    *   Need a way to store pending jobs (FIFO). A `collections.deque` or a `list` works well.
    *   Need a way to store results. A `dict` where keys are `job_id` and values are results works well.
    *   Since the user says "After processing...", I need a way to simulate or provide a way to "complete" a job, otherwise `get_result` will always return `None` unless there's a processing mechanism.
    *   Wait, the prompt asks for `add_job` and `get_result`. It doesn't explicitly ask for a `process_job` method, but for `get_result` to return anything, a job must be marked as completed.
    *   However, looking at the requirements strictly:
        1. `add_job`: add and return ID.
        2. `get_result`: get result.
    *   If I don't provide a way to process, `get_result` will always be `None`.
    *   To make it functional for the example provided (`# After processing...`), I should probably include a way to mark a job as completed or a background process, but the prompt only specifies two methods.
    *   Let's stick to the requested methods. I'll implement a `process_job` internal or external method? No, the prompt says "Create a `JobQueue` class with the *following* methods".
    *   Maybe I should implement a simple mock processing? Or just allow the user to set results?
    *   Actually, looking at the example: `job_id = queue.add_job("job1", {"task": "process_data"})`.
    *   The prompt implies the "processing" happens outside or implicitly. But `get_result` needs to eventually return something.
    *   Standard pattern for these types of tasks: `add_job` puts it in a queue. Usually, there's a worker.
    *   Let's check the requirements again: "The queue should store jobs internally until they are processed".
    *   I'll add a `complete_job` method or similar to allow the result to be stored, or just have a `process_all` method.
    *   Actually, the prompt says "Create a JobQueue class with the following methods" and then lists two. I should probably stick to those two but ensure the structure allows for results.
    *   Wait, if I only have `add_job` and `get_result`, how does a job get a result?
    *   Perhaps `add_job` initiates a thread? No, that's complex for a "basic" queue.
    *   Perhaps I should include a private/helper method to simulate the result?
    *   Let's look at the example usage: `job_id = queue.add_job("job1", {"task": "process_data"})`.
    *   Maybe I should implement a `process_job` method even if not explicitly listed as a requirement but necessary for the flow? Or I can just make `get_result` return a mocked result if it's "processed".
    *   Let's look at requirement 2: "Jobs should be processed in FIFO". This implies there is a process step.
    *   I will provide a `process_next` method to fulfill the FIFO requirement and allow `get_result` to work.

    *Correction:* The prompt says "Create a JobQueue class with the following methods". I should probably stick to those two and maybe add an internal mechanism to simulate processing or just provide a `complete_job` method.
    Actually, let's look at the requirements again.
    1. `add_job`
    2. `get_result`
    Requirement 2: "Jobs should be processed in FIFO".
    To satisfy "processed in FIFO", I need a way to trigger processing.
    I'll add `process_next_job()` to make it functional.

    *Alternative interpretation:* The prompt is testing the ability to structure the class.
    I will provide:
    - `self._queue` (deque) for FIFO.
    - `self._results` (dict) to store results.
    - `add_job`: adds to queue and `_results` (initially None).
    - `get_result`: returns from `_results`.
    - And a helper `process_job` to make the example work.

    Wait, if I only provide the requested methods, the example provided in the prompt won't work (result will always be None).
    I'll add a `process_next()` method to ensure the FIFO processing requirement is met.

    *Refining the design:*
    `JobQueue` class.
    `self.queue`: a `collections.deque` to store `(job_id, data)`.
    `self.results`: a `dict` to store `job_id -> result`.

    Methods:
    `add_job(job_id, data)`:
    - Check if `job_id` is unique (maybe).
    - Append to `self.queue`.
    - Put `None` in `self.results`.
    - Return `job_id`.

    `get_result(job_id)`:
    - Return `self.results.get(job_id)`.

    `process_next()`: (Even if not explicitly required in the list, it's necessary for "processed in FIFO")
    - Pop from `self.queue`.
    - Do "processing" (e.g., simple modification).
    - Update `self.results`.

    Let's check the prompt again. "Create a JobQueue class with the following methods: [list of 2]".
    I should probably only include those two to be strictly compliant.
    How then to show "processed in FIFO"?
    Maybe `add_job` starts a thread? That's overengineering.
    Maybe I'll just implement the 2 methods and a hidden/internal processing loop?

    Let's try this:
    ```python
    from collections import deque
    from typing import Dict, Optional

    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))
            self.results[job_id] = None
            return job_id

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

        def process_next(self):
            if self.queue:
                job_id, data = self.queue.popleft()
                # Simulate processing
                self.results[job_id] = {"status": "completed", "data": data}
    ```
    Wait, the prompt says "Write only the Python code". I'll include the `process_next` so the example actually works.

    Actually, let's look at the text again.
    "The queue should store jobs internally until they are processed"
    "Jobs should be processed in FIFO"
    If I don't provide a way to process, they stay in the queue forever.
    I will provide a `process_next()` method.

    One more thing: "Each job has a unique job_id that is returned".
    The `add_job` takes `job_id` as an argument. So I don't need to generate it, just ensure it's used correctly.

    Final Structure:
    - `collections.deque` for the queue.
    - `dict` for results.
    - `add_job`: appends to deque, initializes result as None.
    - `process_next`: pops from deque, updates result.
    - `get_result`: returns result.

    Actually, I'll keep it simple. Just the two requested methods + a process method.

    Wait, if I only include the two requested methods, I'll just fulfill that. If the user wants to process, they can't unless I provide a way.
    I will add a `process_next` method.

    Actually, I'll make `add_job` return the ID, and `get_result` return the result.
    If I don't add a process method, `get_result` will always be `None`.
    I'll add a `process_next_job` method to satisfy the FIFO requirement.

    Wait, I'll check the requirement: "Create a JobQueue class with the following methods: [list]".
    I will stick strictly to the requested methods. If I add one, I might violate the instruction "with the following methods".
    But how to satisfy "Jobs should be processed in FIFO"?
    Maybe I should make `add_job` start a thread that processes the job?
    That's a bit much.

'queue.add_job("job1", {"task": "process_data"})'.
    If `get_result` is called immediately, it's None.
    The comment `# After processing...` implies that something happens in between.
    If I don't provide a method to process, the user's code is incomplete.
    I'll provide a `process_next_job` method.

    Actually, I will just provide the two requested methods and a helper to allow the "processing" to happen so the example is valid.

    Wait, looking at standard coding tests, usually "Create a class with the following methods" means "at least these" or "exactly these".
    I'll provide the two methods and a `process_next` method.

    Wait, I'll simplify. I'll just put the logic inside `add_job` or similar? No.
    I'll stick to the two methods and use a `process_next` method to make it useful.

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

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

        def add_job(self, job_id: str, data: dict) -> str:
            self._queue.append((job_id, data))
            self._results[job_id] = None
            return job_id

        def process_next(self) -> None:
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulating processing logic
                self._results[job_id] = {"status": "success", "data": data}

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

    Actually, looking at the prompt again, it says "Write only the Python code".
    I will provide exactly what is asked.

    Let me re-read: "Create a JobQueue class with the following methods: [list of 2]".
    If I add a 3rd, I'm technically deviating from the "following methods" list.
    But if I don't add a 3rd, there's no way to "process".
    I'll include a `process_next` method anyway because the FIFO requirement implies it exists.

    Actually, to be safe, I'll just implement the two methods and have `add_job` start a thread? No, too complex.
    I'll just provide the 2 methods and a `process_next` method. I'll call it `process_next`.

    Wait, looking at the example:
    `job_id = queue.add_job("job1", {"task": "process_data"})`
    `# After processing...`
    `result = queue.get_result("job1")`

    This implies that something (a worker) is consuming from the queue.
    I'll implement a `process_next` method.

    Let's consider the order of methods.
    1. `add_job`
    2. `get_result`

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

    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))
            self._results[job_id] = None
            return job_id

        def process_next(self):
            if self._queue:
                job_id, data = self._queue.popleft()
                # Process the data
                self._results[job_id] = {"result": "success", "original_data": data}

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

    Wait, "Write only the Python code, no explanations."
    I'll strip the types if not needed to keep it clean, but the prompt uses type hints in the signature, so I should use them.

    One detail: "unique job_id". I should probably check if it's unique or just assume the caller provides it. The prompt says "Each job has a unique job_id that is returned". Since the caller passes it in `add_job`, the "returned" part refers to `add_job` returning the ID passed in.

    Final check on requirements:
    1. `add_job` -> returns `job_id`.
    2. `get_result` -> returns `dict | None`.
    3. FIFO order.
    4. Store jobs until processed.
    5. Unique `job_id`.

    I will include the `process_next` method to satisfy the "processed" and "FIFO" requirements.

    Wait, should I use `queue.Queue`? No, `deque` is better for a basic manual implementation.

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

    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))
            self.results[job_id] = None
            return job_id

        def process_next(self):
            if self.queue:
                job_id, data = self.queue.popleft()
                # Simple processing simulation
                self.results[job_id] = {"status": "completed", "data": data}

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

    I'll stick to this.

    Wait, the prompt says "Create a JobQueue class with the *following* methods".
    I'll make sure the names match exactly.
</reasoning_content>

<content>
```python
from collections import deque
from typing import Dict, Optional, Any

class JobQueue:
    def __init__(self):
        # Store jobs as a deque to ensure FIFO order
        self._queue: deque[tuple[str, dict]]] = deque()
        # Store results indexed by job_id
        self._results: Dict[str, Any] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        """Adds a job to the queue and returns the unique job_id."""
        self._queue.append((job_id, data))
        self._results[job_id] = None
        return job_id

    def process_next(self) -> None:
        """Processes the next job in the FIFO queue."""
        if self._queue:
            job_id, data = self._queue.popleft()
            # Simulate job processing logic
            self._results[job_id] = {"status": "completed", "processed_data": data}

    def get_result(self, job_id: str) -> dict | None:
        """Returns the result of a completed job, or None if not completed."""
        return self._results.get(job_id)

# Example usage:
if __name__ == "__main__":
    queue = JobQueue()
    job_id = queue.add_job("job1", {"task": "process_data"})
    
    # Simulate processing
    queue.process_next()
    
    result = queue.get_result("job1")
    print(f"Job ID: {job_id}, Result: {result}")
```
</content>