<reasoning_content>
The user wants a basic job queue implementation in Python.
Requirements:
1. `JobQueue` class
2. `add_job(job_id: str, data: dict) -> str` method
3. `get_result(job_id: str) -> dict | None` method
4. FIFO order processing
5. Store jobs internally until processed
6. Return job_id when added

Wait, the example shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
But it doesn't specify how jobs are processed. The prompt says "The queue should store jobs internally until they are processed". It doesn't explicitly ask for a `process_jobs()` method, but typically a job queue needs a way to process them, or maybe it just stores them and the user expects a simple implementation where `get_result` returns the data if processed, or maybe it just stores the data and returns it? Wait, the prompt says "Each job has a unique job_id that is returned when added". And `get_result` returns `dict | None`.

Let's think about what "processed" means here. Maybe the queue just stores jobs, and `get_result` returns the data if it's been "processed"? Or maybe it's just a simple queue where `add_job` puts it in a queue, and there's a `process` method that moves it to results? The prompt doesn't specify a `process` method, but says "Jobs should be processed in FIFO order". I should probably add a `process_next()` or `process_all()` method, or maybe the `JobQueue` automatically processes? Or maybe it's just a simple queue and the example comment "# After processing..." implies the user will call some method, or maybe `get_result` just returns the data if it's done.

Actually, many simple job queue implementations in coding tests just have:
- A queue (deque) for pending jobs
- A dict for completed results
- A `process_job()` or similar method to move from queue to results, or maybe it's synchronous? But it says "queue", so likely asynchronous or manual processing.

Wait, the prompt says: "The queue should store jobs internally until they are processed". It doesn't explicitly ask for a processing method, but to fulfill "Jobs should be processed in FIFO order", I should probably implement a `process_jobs()` or `process_next()` method. Or maybe `add_job` just adds to a queue, and `get_result` checks if it's processed. I'll add a `process_next()` method to move a job from the queue to results, simulating processing. Or maybe the job processing is just a placeholder that returns the data? The prompt says `data: dict`, and `get_result` returns `dict | None`. I'll assume processing just stores the data as the result, or maybe applies some dummy processing. To keep it simple, I'll just move the job data to a results dict when processed.

Let's re-read carefully: "Implement a basic job queue in Python."
Requirements:
1. `add_job(job_id: str, data: dict) -> str`
2. `get_result(job_id: str) -> dict | None`
3. FIFO order
4. Store internally until processed
5. Unique job_id returned

I will implement:
- `__init__`: initializes a `deque` for pending jobs, and a `dict` for results.
- `add_job`: appends to deque, returns job_id.
- `process_next()` or `process_jobs()`: pops from deque, stores in results dict. Maybe I'll add a `process_all()` method. Or maybe the prompt expects `process_job()` to be called. I'll add `process_next()` that processes one job in FIFO order.
- `get_result`: returns result from dict if exists, else None.

Wait, maybe the prompt implies that `get_result` should block or just return None if not processed? It says `dict | None`.
I'll stick to a simple synchronous simulation:
```python
from collections import deque
from typing import 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))
        return job_id

    def process_next(self) -> bool:
        if not self._queue:
            return False
        job_id, data = self._queue.popleft()
        # Simulate processing: just store data as result
        self._results[job_id] = data
        return True

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

But the prompt doesn't explicitly ask for `process_next`. It just says "Jobs should be processed in FIFO order". Maybe I should name it `process_jobs()` or just assume the user will call a method. I'll add `process_jobs()` that processes all pending jobs, or `process_next()`. I'll stick with `process_next()` or `process()`. Actually, many simple implementations just have a `process()` method. I'll add `process_jobs()` to process all, or just `process_next()`. To be safe, I'll add `process_next()` and maybe `process_all()`. Or I can just implement `process_job()` that takes a job_id? No, FIFO implies automatic ordering.

Wait, maybe the prompt expects `add_job` to just queue it, and `get_result` to return it if processed. I'll provide a `process_next()` method. It's standard.

Let's reconsider: maybe the job processing is synchronous in `add_job`? No, it's a queue.
I'll implement `process_jobs()` that processes all queued jobs in FIFO order. Or maybe just `process_next()`. I'll go with `process_next()`.

Actually, the prompt says "The queue should store jobs internally until they are processed". It doesn't specify how they get processed. I'll add a `process_next()` method. To be thorough, I'll also add a `process_all()` method, but it's not strictly required. I'll just stick to the required methods and add a `process_next()` for completeness.

Wait, maybe the prompt expects a thread-based queue? "basic job queue" usually implies simple in-memory. I'll keep it simple.

Let's look at the exact wording:
"Implement a basic job queue in Python.
Requirements:
1. Create a `JobQueue` class with the following methods:
   - `add_job(job_id: str, data: dict) -> str`: Add a job to the queue, return job_id
   - `get_result(job_id: str) -> dict | None`: Get the result of a completed job
2. Jobs should be processed in FIFO (First-In-First-Out) order
3. The queue should store jobs internally until they are processed
4. Each job has a unique job_id that is returned when added"

It doesn't ask for a process method explicitly, but to fulfill requirement 2, I need a way to process them. I'll add a `process_jobs()` method that processes all pending jobs in FIFO order. Or maybe `process_next()`. I'll add `process_next()` as it's more standard for queues. Actually, I'll just add `process_jobs()` that processes all, or maybe the user expects `process()` to be called. I'll stick with `process_next()`.

Wait, maybe the processing is just moving from queue to results. I'll implement it simply.

Another interpretation: maybe `add_job` just adds to a list, and `get_result` returns the data if it's been "processed" by some external mechanism, but since it's a basic implementation, I'll include a `process_next()` method.

Let's write it out carefully.

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

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

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

    def process_next(self) -> bool:
        if not self._pending:
            return False
        job_id, data = self._pending.popleft()
        # Simulate processing: store data as result
        self._results[job_id] = data
        return True

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

But the prompt says "Write only the Python code, no explanations."
I should make sure it matches the type hints exactly. `dict | None` is valid in Python 3.10+. I'll use `Optional[dict]` or `dict | None`. The prompt uses `dict | None`, so I'll stick to that or import `Optional`. I'll just use `dict | None` as in the prompt.

Wait, maybe the prompt expects `process_jobs()` to be called automatically? No.
I'll add a `process_jobs()` method that processes all pending jobs, as it's common in basic implementations. Or I'll just leave `process_next()`. Actually, many coding platforms expect a `process()` method. I'll add `process_jobs()` that processes all in FIFO order.

Let's reconsider requirement 2: "Jobs should be processed in FIFO (First-In-First-Out) order". This implies that when processing happens, it respects FIFO. `deque.popleft()` does exactly that.

I'll implement it with `process_jobs()` to process all, or just `process_next()`. I'll stick to `process_next()` as it's more explicit about FIFO one-by-one. Actually, I'll just add `process_jobs()` that processes all pending jobs. It doesn't matter much.

To be safe, I'll provide exactly what's asked, plus a `process_jobs()` method for completeness.

Wait, maybe the prompt implies that `get_result` should block? No, it returns `dict | None`.
I'll keep it simple.

One thing: the prompt says "Each job has a unique job_id that is returned when added". That's just `return job_id`.

I'll write the code now.

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

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

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

    def process_jobs(self) -> None:
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = data

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

Actually, `process_jobs` might not be needed if the user just wants the structure. But requirement 2 says "Jobs should be processed in FIFO order", so I must provide a way to process them. I'll add `process_next()` or `process_jobs()`. I'll go with `process_jobs()` as it's cleaner for batch, or `process_next()` for one. I'll stick with `process_jobs()`.

Wait, maybe the prompt expects `process_job()`? I'll just add `process_next()` to be explicit about FIFO. Actually, I'll just add `process_jobs()` that processes all. It's fine.

Let's check type hints: `dict | None` is Python 3.10+. I'll use it as requested.
I'll make sure the code is self-contained.

One minor point: maybe the processing should simulate some work? The prompt doesn't specify, so storing the data as result is fine.

I'll output exactly the code.
To be extremely precise, I'll use `typing.Optional` for compatibility, but the prompt uses `dict | None`, so I'll keep that.

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))
        return job_id

    def process_next(self) -> bool:
        if not self._queue:
            return False
        job_id, data = self._queue.popleft()
        self._results[job_id] = data
        return True

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

Actually, I'll add `process_jobs()` instead of `process_next()` to process all at once, which is common. Or I'll just leave `process_next()`. It doesn't matter much. I'll stick with `process_jobs()` that processes all pending jobs in FIFO order.

Wait, the prompt says "Jobs should be processed in FIFO order". This is naturally handled by `deque.popleft()`.

I'll write it out.
One thing: `dict | None` syntax requires Python 3.10+. I'll assume it's fine.
I'll output only the code.
Done. 
Let's double check the prompt: "Write only the Python code, no explanations."
I will provide exactly that.
I'll make sure the class name and method signatures match exactly.
`add_job(job_id: str, data: dict) -> str`
`get_result(job_id: str) -> dict | None`
All good.
I'll add a `process_jobs()` method to fulfill the processing requirement.
Actually, maybe the prompt expects `process()` or similar. I'll just add `process_jobs()`.
Ready. 
Output matches response. 
Proceeds. 
(Self-Correction/Refinement during thought)
Wait, maybe the prompt implies that `get_result` should return the data if it's in the queue? No, "completed job".
I'll stick with the implementation.
One detail: `dict | None` is fine.
I'll produce the code now. 
All requirements met.
Code:
```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 process_jobs(self) -> None:
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = data

    def get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id)
```
This is clean and meets all requirements. I'll output it. 
Wait, should I include `process_next` or `process_jobs`? The prompt doesn't specify a method name for processing. I'll include `process_jobs()` as it's standard. Alternatively, I could just not include a processing method and assume the user knows, but requirement 2 says "Jobs should be processed in FIFO order", so I must provide a way. I'll stick with `process_jobs()`.
Actually, to be safer, I'll name it `process_next()` so it explicitly shows FIFO one by one, or just `process_jobs()`. It doesn't matter. I'll go with `process_jobs()`.
Done. 
Output matches. 
Proceeds. 
[Final Check]
- `JobQueue` class: yes
- `add_job(job_id: str, data: dict) -> str`: yes
- `get_result(job_id: str) -> dict | None`: yes
- FIFO: yes, using `deque` and `popleft`
- Store internally until processed: yes, `_queue` holds them, `_results` holds completed
- Unique job_id returned: yes
- Only Python code: yes
All good. 
Output generation. 
(Note: I'll use `dict | None` as requested, which is valid in Py3.10+. If compatibility is a concern, `Optional[dict]` is safer, but I'll stick to the prompt's syntax.)
I'll output exactly the code block. 
Done. 
[Output Generation] -> *Proceeds*

</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:
        self._queue.append((job_id, data))
        return job_id

    def process_jobs(self) -> None:
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = data

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