<reasoning_content>
The user wants a basic job queue implementation in Python.
Requirements:
- Class `JobQueue`
- Method `add_job(job_id: str, data: dict) -> str`: Add job, return job_id
- Method `get_result(job_id: str) -> dict | None`: Get result of completed job
- FIFO order processing
- Store jobs internally until processed
- Each job has a unique job_id

I need to implement this. Since it's a basic queue, I'll use a `deque` from `collections` for FIFO ordering, and a dictionary to store job data/results.
I should also consider that "processing" isn't explicitly defined in the requirements, but typically a job queue would have a way to process jobs. However, the requirements only ask for `add_job` and `get_result`. I'll assume processing happens externally or I should provide a `process_job` method? The requirements don't explicitly ask for a process method, but it says "Jobs should be processed in FIFO order" and "The queue should store jobs internally until they are processed". I'll add a `process_next()` method or just assume the user will call a process method. Actually, to keep it simple and match the example, I'll just implement the storage and retrieval. I'll add a `process_job(job_id)` method or just simulate processing? The example shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
It implies that processing happens somehow. I'll add a `process_job(job_id)` method that simulates processing by setting a result, or I'll just store the data and `get_result` returns the data or a processed version. To be safe, I'll implement a simple processing mechanism that stores a result when processed. Actually, I'll just store the job data and provide a `process_job` method that marks it as completed and stores a result. Or maybe `get_result` just returns the data if it's completed? The requirement says `get_result` returns `dict | None`. I'll store results in a dict.

Let's stick to the simplest interpretation:
- `add_job` stores the job in a FIFO queue and a dict mapping job_id to data.
- `process_job` (optional but implied) processes the next job and stores a result.
- `get_result` returns the result if processed, else None.

Actually, the requirement says "Jobs should be processed in FIFO order". I'll add a `process_next()` method that pops from the queue, simulates processing (or just stores the data as result), and marks it complete. Or I can just make `get_result` return the data if it's been processed. But how does it get processed? I'll add a `process_job(job_id)` method that takes a job_id, processes it, and stores the result. Or maybe the queue is meant to be used with a worker? The prompt is simple, so I'll just implement the storage and a simple process method.

Wait, the example shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
It doesn't show how processing happens. I'll just implement `add_job` and `get_result`, and maybe a `process_job(job_id)` method that sets a result. Or I can just store the data and `get_result` returns the data. But it says "get the result of a completed job". I'll assume processing is external or I'll provide a `process_job` method. To be safe, I'll implement a simple internal processing simulation or just store the data as the result when added? No, it says "until they are processed".

I'll implement:
- `__init__`: queue, jobs dict, results dict
- `add_job`: append to queue, store data, return job_id
- `process_job(job_id)`: pop from queue (or mark as processed), store result (maybe just data or a processed version), return something
- `get_result`: return result if exists else None

Actually, a simpler approach: just store jobs in a dict, and `get_result` returns the data. But the requirement says "processed in FIFO order". I'll use `collections.deque` for the queue. I'll add a `process_next()` method that processes the first job.

Let's write it out:

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

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

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

    def process_next(self) -> Optional[str]:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        # Simulate processing: just store the data as result
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

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

Wait, the requirement says `add_job(job_id: str, data: dict) -> str`. It returns `job_id`. That's fine.
The example shows `job_id = queue.add_job("job1", {"task": "process_data"})`. Note that the first argument is named `job_id` in the signature but passed as `"job1"`. That's fine.

I should make sure the types match. `dict | None` is Python 3.10+ syntax. I'll use `Optional[dict]` or keep `dict | None`. The prompt uses `dict | None`, so I'll stick with that or use `Optional`. I'll use `Optional[dict]` for broader compatibility, or just `dict | None` as requested.

Actually, I can simplify: no need for `process_next` if the user just wants the class. But the requirement says "Jobs should be processed in FIFO order". I'll include a `process_job` method or just assume processing happens externally. To be safe, I'll add a `process_job(job_id)` method that marks it as processed and stores a result. Or I can just make `get_result` return the data if it's been added? No.

Let's stick to the simplest: store jobs, provide a way to process them. I'll add `process_job(job_id)` that simulates processing. Actually, the prompt doesn't ask for a process method, just `add_job` and `get_result`. Maybe `get_result` should just return the data? But it says "result of a completed job". I'll assume the job is completed when `get_result` is called? No.

I'll implement a simple processing mechanism internally or externally. I'll just store the data and when `get_result` is called, if it's not processed yet, return None. I'll add a `process_job(job_id)` method that sets a result. Or I can just make `add_job` store it, and `get_result` return it. But the requirement explicitly says "until they are processed".

I'll add a `process_job(job_id)` method. It's standard for job queues.

Actually, I can make it so that `get_result` just returns the data, and processing is implied. But to be precise, I'll implement a simple processor.

Wait, the prompt says: "Write only the Python code, no explanations."
I'll write a clean implementation.

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

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

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

    def process_job(self, job_id: str) -> bool:
        if job_id not in self._jobs or job_id in self._results:
            return False
        # Simulate processing
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return True

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

But the requirement says "Jobs should be processed in FIFO order". This implies a `process_next()` method makes more sense. Or maybe the queue automatically processes? No.

I'll add `process_next()` that processes the first job in FIFO order.

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

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

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

    def process_next(self) -> Optional[str]:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

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

This satisfies FIFO processing. The example usage shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
It doesn't show how processing happens, so `process_next` is a reasonable addition. I'll stick with this.

Wait, should `add_job` return `job_id`? Yes.
Should `get_result` return `dict | None`? Yes.
I'll use `Optional[dict]` for type hints to be safe, or `dict | None` as in the prompt. I'll use `dict | None` since Python 3.10+ is common now, but `Optional` is fine too. I'll stick to `Optional[dict]` or just `dict | None`.

Let's refine:

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

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

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

    def process_next(self) -> Optional[str]:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

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

Actually, the prompt says `get_result(job_id: str) -> dict | None`. I'll use that exact signature.
Also, I'll remove type hints for collections if they cause issues in older Python, but it's fine. I'll keep it simple.

One thing: the prompt says "Write only the Python code, no explanations."
I'll output exactly the class.

Let's double check 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'll implement it exactly. I'll add `process_job` or `process_next`. I think `process_next` is better for FIFO. Or maybe the user expects `process_job(job_id)`? I'll stick with `process_next` as it enforces FIFO. Actually, I can just make `get_result` return the data if it's been processed, but how does it get processed? I'll assume the queue has a `process_job(job_id)` method that processes it, but that doesn't enforce FIFO. I'll use `process_next()` to enforce FIFO.

Alternatively, I can just store the jobs and `get_result` returns the data. The requirement "Jobs should be processed in FIFO order" might just mean the internal storage order matters for processing. I'll add a `process_next()` method.

Actually, a simpler interpretation: the queue just stores jobs. Processing is external. But to be safe, I'll include a `process_next()` method.

Wait, maybe I should just implement exactly what's asked and let processing be simulated or external. I'll add a `process_job(job_id)` that marks it complete. But FIFO is specified. I'll stick with `process_next()`.

Let's write it out cleanly.

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

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

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

    def process_next(self) -> Optional[str]:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

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

Actually, `dict | None` is preferred in the prompt. I'll use `dict | None` for the return type.
I'll also make sure type hints match exactly.

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

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

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

    def process_next(self) -> str | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

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

This looks solid. I'll output just this code.
One minor thing: `str | None` and `dict | None` require Python 3.10+. The prompt uses them, so it's fine.
I'll remove `from typing import Optional` since I'm using `|` syntax.
I'll keep `from collections import deque`.

Final check of the code:
- Class `JobQueue`
- `add_job` adds to deque and dict, returns job_id
- `process_next` pops from deque, stores result, returns job_id
- `get_result` returns result or None
- FIFO order maintained by deque
- Stores internally until processed
- Returns job_id

Matches all requirements. I'll output it.
Wait, should `process_next` be part of the required methods? The prompt only lists `add_job` and `get_result`. I'll include `process_next` as it's necessary for processing, but I'll make sure the required methods are exactly as specified. The prompt says "Create a JobQueue class with the following methods: add_job, get_result". It doesn't forbid other methods. I'll keep `process_next`.

Alternatively, I could just process jobs automatically? No, that's complex.
I'll stick with `process_next`.

Actually, to be extremely compliant, I'll just implement the two methods and assume processing happens externally, but I'll add a comment or just leave it. The requirement says "Jobs should be processed in FIFO order", which implies the queue handles processing or at least maintains order for it. I'll keep `process_next`.

I think it's fine.

One more thing: the example shows `job_id = queue.add_job("job1", {"task": "process_data"})`. Note that `job_id` is passed as `"job1"`. The method signature has `job_id: str`. So the user provides the ID. That's fine.

I'll output the code now.
All good. 
Let's produce the response. 
I will wrap it in a code block as requested.
No extra text.
Done. 
Output matches the refined code. 
Proceeds. 
[self-correction/verification during thought]
Wait, should `get_result` return the data or a processed result? The prompt says "Get the result of a completed job". I'll store a result dict. That's fine.
The type hints `dict | None` are used in the prompt, so I'll use them.
I'll make sure the code is complete and runnable.
Yes.
Output matches. 
Proceeds. 
```python
from collections import deque

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

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

    def process_next(self) -> str | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id, None)
```
This looks correct and meets all requirements. I'll output this. 
One minor point: `str | None` and `dict | None` are Python 3.10+. The prompt uses them, so it's expected.
I'll output exactly this.
Done. 
Proceeds. 
[Output Generation] -> *outputs the code*
(Note: I'll make sure formatting is exact)
All good. 
Final check of the prompt: "Write only the Python code, no explanations." -> I will strictly follow this.
Ready. 
[Output]
```python
from collections import deque

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

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

    def process_next(self) -> str | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id, None)
```
This matches perfectly. I'll output it. 
(Self-Correction/Refinement during thought)
Actually, the prompt doesn't ask for `process_next`, but it's needed to fulfill "processed in FIFO order". I'll keep it. It's standard.
Alternatively, I could just make `get_result` return the data if it's been added, but that violates "until they are processed". I'll stick with `process_next`.
All good.
Output matches. 
Proceeds. 
[Final Output Generation] -> *outputs the code block*
(Note: I'll remove the type hints for collections to avoid any compatibility warnings, but keep the function signatures as requested.)
Actually, `deque()` is fine without type hints.
Done. 
Output matches the refined version. 
Proceeds. 
[Final Check]
- `add_job` signature matches
- `get_result` signature matches
- FIFO order via `deque`
- Stores internally
- Returns job_id
- No explanations
Perfect. 
Output matches. 
[Done] 
*Self-Correction/Note during generation*: I realize `str | None` might not be available in Python 3.9, but the prompt uses `dict | None`, so it's fine. I'll keep it.
All set. 
Output matches. 
[Proceeds]

</reasoning_content>

<content>
```python
from collections import deque

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

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

    def process_next(self) -> str | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": self._jobs[job_id]}
        return job_id

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