<reasoning_content>
*   Goal: Implement a basic job queue in Python.
    *   Class: `JobQueue`.
    *   Methods:
        *   `add_job(job_id: str, data: dict) -> str`
        *   `get_result(job_id: str) -> dict | None`
    *   Ordering: FIFO (First-In-First-Out).
    *   Internal Storage: Must store jobs until processed.
    *   Unique IDs: `job_id` is returned (the prompt implies inputting a `job_id` but also says "returned when added"). Re-reading: "Add a job to the queue, return job_id". If the user provides `job_id`, returning it is straightforward. If the user wants unique IDs automatically generated, that's different, but the signature says `add_job(job_id: str, ...)` implying the user provides it.
    *   Processing logic: The prompt says "Jobs should be processed in FIFO order" and "store jobs until they are processed". However, it doesn't specify a worker thread/loop, just the storage structure. Usually, a "queue" implies a processing mechanism, but the `get_result` suggests an asynchronous or background processing pattern. Since no worker logic is requested, I'll implement the data structure part.

    *   Wait, how does a job move from "added" to "completed" so `get_result` works?
    *   If I just have a queue, how is it "processed"?
    *   The prompt asks for a "basic job queue".
    *   Let's look at the example:
        `job_id = queue.add_job("job1", {"task": "process_data"})`
        `# After processing...`
        `result = queue.get_result("job1")`
    *   Since the prompt doesn't specify a worker thread, I should probably provide a way to "complete" or "process" a job, or simulate processing. But the prompt only specifies two methods: `add_job` and `get_result`.
    *   Actually, usually in these coding tasks, "JobQueue" implies a `process_next` or a background thread. But the requirements are very specific about the methods.
    *n   Let's assume a simplified model:
        1. `jobs_queue`: a deque for FIFO ordering.
        2. `results_storage`: a dictionary to store results.
    *   Wait, if `add_job` is called, it goes into a queue. How does it get processed?
    *   Maybe I should add a private/internal method or simulate processing to make the example work? No, the prompt says "Write only the Python code".
    *   Let's rethink. If I just have `add_job` and `get_result`, how does a job ever finish?
    *   Perhaps I should implement a `process_jobs` method or something similar? No, the requirements only list two methods.
    *   Maybe `add_job` should put it in a queue, and I need a way to transition it to "done".
    *   Let's look at Requirement 3: "The queue should store jobs internally until they are processed".
    *   Let's provide a way to mark a job as done or simulate the process.
    *   Actually, a common way to implement this in an interview context is a `process_next` method. Since it's not in the requirements, but the example shows a result being returned, I'll add a `complete_job` method or similar to allow the "processing" to happen, or I'll simulate it in `add_job` (not good for async), or I'll just implement the storage logic.

    *   Refined interpretation:
        `add_job` adds to a list/deque.
        `get_result` checks if it's finished.
        To make the example work, I need a way for a job to be "processed".
        I'll include a `process_next` or similar if allowed? No, stick to requirements.
        Maybe `add_job` simulates a delay? No, that blocks.
        Maybe the prompt implies that `add_job` starts a thread?

    *   Let's look at Requirement 2: "Jobs should be processed in FIFO order". This implies there's a processor.
    *   I will implement a `process_jobs` method or a simple `process` internal mechanism to satisfy the "processed" part.
    *   Wait, if I only provide the two methods, the user can't actually "process" it in the example unless I have a mechanism.
    *   Let's add a `complete_job` method just to make it functional, or simply allow `add_job` to be the entry point and assume some external actor processes it?
    *   Actually, a standard Job Queue pattern:
        `add_job` -> `queue.append()`
        `process_next()` -> `queue.popleft()` -> calculate result -> `results[id] = result`.
    *   Since `process_next` isn't requested, but "Jobs should be processed" is, I'll assume a worker is expected or I'll provide a simple `complete_job` to facilitate the "After processing..." comment.

    Actually, looking at the prompt again: "Write only the Python code".
    Maybe I should just implement the `add_job` and `get_result` and keep a dictionary for results and a deque for the order.

    Let's try to make it runnable by adding a small internal processing helper or a `process_jobs` method, but strictly adhering to the requested methods.

    Actually, the most logical way to satisfy "processed in FIFO order" and "store until processed" while only having `add_job` and `get_result` is to have a method that processes the queue. I'll include `process_jobs`.

    Wait, the requirements say: "Create a JobQueue class with the following methods: [list]". It doesn't say *only* those methods, but usually, that's the hint.

    If I only have those two:
    `add_job` puts it in a `collections.deque`.
    `get_result` looks it up in a `results` dict.
    How does it get into the `results` dict?
    I'll add a `process_jobs` method to satisfy Requirement 2.

    *Self-Correction:* The prompt is likely a simplified "design a data structure" task.
    1. `self.queue = deque()`
    2. `self.results = {}`
    3. `add_job(id, data)` -> `self.queue.append((id, data))`, `self.results[id] = None`
    4. `get_result(id)` -> `return self.results.get(id)`
    5. `process_jobs()` -> `while self.queue: id, data = self.queue.popleft(); self.results[id] = {"status": "done", "data": data}`

    This seems complete. I will include `process_jobs` so the example can actually reach a state where `get_result` returns something.

    Wait, looking at the prompt again: "Write only the Python code, no explanations."
    I'll provide the class with the two required methods, plus a `process_next` to handle the FIFO requirement.

    Actually, many people use `queue.Queue` which is thread-safe.
    But I'll use `collections.deque` and a `dict`.

    Let's refine the methods:
    `add_job`:
    ```python
    def add_job(self, job_id: str, data: dict) -> str:
        self.queue.append((job_id, data))
        self.results[job_id] = None
        return job_id
    ```

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

    To make it "processed", I'll add `process_next`.

    Actually, is there a way to do it without `process_next`?
    If the user calls `add_job`, and nothing else happens, `get_result` is always None.
    The prompt says "After processing...". This implies there's a step between adding and getting.

    One more thought: Maybe the user wants me to simulate the "processing" inside `add_job` using a thread? No, that's usually not what "basic job queue" means.

    I will implement `add_job`, `get_result`, and `process_next`.

    ```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) -> Optional[dict]:
            return self.results.get(job_id)

        def process_next(self) -> None:
            if self.queue:
                job_id, data = self.queue.popleft()
                # Simulate processing
                self.results[job_id] = {"status": "completed", "data": data}
    ```

    Wait, if I add `process_next`, it wasn't requested.
    If I don't add it, the code is technically correct according to the prompt's method list, but the "After processing" comment in the example would be impossible to achieve with just those two methods.
    However, I'll stick to the requested methods strictly but ensure the logic allows for results to be stored.
    Actually, I'll add a `process_jobs` method. It's safer to provide functionality that makes the example work.

    Wait, another way:
    The prompt says "Jobs should be processed in FIFO order".
    This implies a loop.
    I'll write the class with the two methods plus a `process_next` to make it usable.

    Actually, I'll check if there's any other way.
    Maybe `add_job` starts a thread that processes the job immediately?
    "Jobs should be processed in FIFO order".
    If I use a ThreadPoolExecutor or similar, it handles the queue.
    But the prompt asks for a `JobQueue` class, usually implying the queue logic itself.

    Let's stick to the simplest implementation:
    1. `deque` for the queue.
    2. `dict` for results.
    3. The two required methods.
    4. A `process_next` method (even if not explicitly requested, it's necessary for the "FIFO" and "processed" requirements).

    Revised plan: I'll strictly implement the two requested methods. To handle "processed", I'll include a `process_jobs` method as well, as it's the only way to fulfill Requirement 2 and 3.

    Actually, looking at similar prompts online, sometimes the "processing" is just a separate method the user is supposed to call.

    One detail: "The queue should store jobs internally until they are processed".
    This means `self.queue` should only shrink when `process_next` is called.

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

    class JobQueue:
        def __init__(self):
            self.queue = deque()
            self.results: Dict[str, Optional[dict]] = {}

        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) -> Optional[dict]:
            return self.results.get(job_id)

        def process_next(self) -> None:
            if self.queue:
                job_id, data = self.queue.popleft()
                # Simulate processing logic
                self.results[job_id] = {"status": "completed", "data": data}
    ```

    I'll remove the type hints for `Dict` and `Optional` if it makes it cleaner, but `dict | None` is Python 3.10+. I'll use that as requested in the prompt.

    Final check of requirements:
    1. `JobQueue` class with `add_job` and `get_result`. (Done)
    2. FIFO order. (Done via `deque.popleft`)
    3. Store jobs until processed. (Done)
    4. Unique job_id returned. (Done)

    Wait, "Each job has a unique job_id that is returned when added".
    If the user provides the `job_id` in the argument `add_job(job_id: str, ...)`, then returning it is easy. If the user *expects* the class to generate it, the signature would usually be `add_job(data: dict) -> str`. But the signature provided is `add_job(job_id: str, data: dict) -> str`. So the user provides the ID, and I return it.

    One edge case: What if the user provides a non-unique ID? The prompt doesn't ask me to handle collisions, so I won't overcomplicate.

    ```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))
            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) -> None:
            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".

    One last thought: Should I use `threading.Lock`? The prompt doesn't mention thread safety, and usually, "basic" implies no locking unless specified. I'll skip it to keep it simple.

    Final code structure:
    ```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))
            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_jobs(self):
            while self.queue:
                job_id, data = self.queue.popleft()
                # Simulate work
                self.results[job_id] = {"status": "completed", "data": data}
    ```
    Wait, `process_jobs` vs `process_next`? Requirement 2 says "Jobs should be processed in FIFO order". This is naturally handled by the queue. I'll include `process_next` as it's the standard way to handle a queue item by item.

    Wait, I'll just stick to the two methods requested. If the user wants to see results, they have to have a way to process. I'll include a `process_next` method anyway because without it, the provided example cannot be completed.

    Actually, looking at the signature again: `add_job(job_id: str, data: dict) -> str`.
    The prompt doesn't say `process_next` is required, but the requirement "Jobs should be processed..." implies a process method exists.

    Let's refine the result storage to be clear.

    ```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))
            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()
                self.results[job_id] = {"status": "completed", "data": data}
    ```

    Wait, I should check if `None` is acceptable for `get_result`. Yes, the signature says `dict | None`.

    Final check on "store jobs internally until they are processed".
    My code:
    `add_job` -> `queue.append` (stored)
    `process_next` -> `queue.popleft` (removed from queue, moved to results)
    This satisfies the requirement.

    Actually, I'll omit `process_next` to strictly follow the "Create a JobQueue class with the following methods" list, but then the example is technically unrunnable unless the user adds their own logic.
    However, the prompt asks to "Implement a basic job queue", which logically includes the processing part. I'll include a `process_next` method.

    Wait, one more look at the prompt.
    "Requirement 2: Jobs should be processed in FIFO order".
    If I don't provide a method to process, I'm not fulfilling the "processed" part of the requirement.

    I will provide `process_next`.
</reasoning_content>

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

class JobQueue:
    def __init__(self):
        # Internal storage for jobs waiting to be processed (FIFO)
        self.queue = deque()
        # Internal storage for results of completed jobs
        self.results: Dict[str, Optional[dict]] = {}

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

    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)

    def process_next(self) -> None:
        """
        Processes the next job in the queue (FIFO) and stores the result.
        This method facilitates the 'processed' state required by the prompt.
        """
        if self.queue:
            job_id, data = self.queue.popleft()
            # Simulate job processing logic
            self.results[job_id] = {
                "status": "completed",
                "data": data
            }
```
</content>