<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. Internal storage until processed
6. Unique job_id returned when added
7. Example usage provided (though it shows passing "job1" as job_id, the requirement says "Each job has a unique job_id that is returned when added", which implies the method might generate it or accept it. The example shows `queue.add_job("job1", ...)` returning a job_id, so I'll accept the job_id parameter as input, or generate one if not provided. The signature says `add_job(job_id: str, data: dict) -> str`, so it takes a job_id. I'll stick to the signature.)
8. "Jobs should be processed in FIFO order" - This implies there's a processing mechanism. Since it's a "basic job queue", I should probably include a simple processing method or thread/process that processes jobs. However, the requirements don't explicitly ask for a `process()` or `start()` method. They just say "Jobs should be processed in FIFO order" and "The queue should store jobs internally until they are processed". I'll add a simple `process()` method or use a background thread, but to keep it simple and synchronous as per typical coding challenge expectations, I'll add a `process_all()` or just simulate processing. Actually, the example shows `# After processing...`, implying processing happens externally or via a method. I'll add a `process()` method that processes the next job, or `process_all()`. Let's add a `process()` method that takes a worker function or just simulates a result. Wait, the requirement doesn't specify how jobs are processed. I'll make it so that `process()` simulates a result or allows registering a processor. To keep it self-contained and simple, I'll add a `process()` method that generates a dummy result, or I'll just store the jobs and let the user call a `process()` method. Actually, a common pattern is to have a `process()` method that processes the next job and stores the result. I'll implement a simple synchronous `process()` method that takes the job data, does something trivial (or just marks it as done), and stores the result. Alternatively, I can just store jobs and have a `process_all()` method. Let's stick to a simple `process()` method that processes the next job in queue. To make it useful, I'll add a `process()` method that simulates processing and returns the result, or just stores it. Actually, the requirement says `get_result(job_id: str) -> dict | None`, so results are stored. I'll add a `process()` method that processes the next job and stores the result. I'll make it simple: `process()` pops the next job, generates a result like `{"status": "completed", "data": job_data}`, and stores it. Or I can just leave processing abstract, but the requirement says "Jobs should be processed in FIFO order", so I should implement a processing mechanism. I'll add a `process()` method.

Let's refine:
```python
from collections import deque
import threading
import time
import uuid

class JobQueue:
    def __init__(self):
        self.queue = deque()
        self.results = {}
        self._lock = threading.Lock()
        self._processor_thread = None
        self._running = False

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

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

    def process(self):
        with self._lock:
            if not self.queue:
                return None
            job_id, data = self.queue.popleft()
        # Simulate processing
        time.sleep(0.1)
        result = {"status": "completed", "data": data}
        with self._lock:
            self.results[job_id] = result
        return result

    def process_all(self):
        while self.queue:
            self.process()
```

Wait, 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 calling `process()`. Maybe the queue is expected to be processed automatically or via a method. I'll add a `process()` method. The requirement doesn't specify method names for processing, just that it should be processed in FIFO order. I'll stick with `process()` or `process_all()`.

Actually, to be safe and minimal, I'll just implement the class with the required methods, and add a simple `process()` method. I'll also make sure type hints match Python 3.10+ syntax (`dict | None`), but I'll use `Optional[dict]` for broader compatibility if needed, or just stick to `dict | None` as requested.

Let's keep it simple. I'll implement a synchronous queue with a `process()` method. I won't overcomplicate with threads unless necessary. The prompt says "basic job queue".

I'll write:
```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 get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)

    def process(self) -> Optional[dict]:
        if not self._queue:
            return None
        job_id, data = self._queue.popleft()
        # Simulate job processing
        result = {"status": "completed", "data": data}
        self._results[job_id] = result
        return result

    def process_all(self):
        while self._queue:
            self.process()
```

Wait, the requirement says `get_result(job_id: str) -> dict | None`. I'll use that exact type hint.
Also, the example shows `job_id = queue.add_job("job1", {"task": "process_data"})`. It passes "job1" as job_id. The requirement says "Each job has a unique job_id that is returned when added". This could mean the method generates it, but the signature takes `job_id: str`. I'll keep it as is.

Let's adjust type hints to match exactly: `dict | None` is Python 3.10+. I'll use it.

One thing: "Jobs should be processed in FIFO order" - deque handles this.
"The queue should store jobs internally until they are processed" - handled.
"Each job has a unique job_id that is returned when added" - handled.

I'll make sure the code is clean and matches requirements.

Should I add a background processor? The prompt says "basic job queue", so synchronous processing is fine. I'll stick with `process()` and `process_all()`.

Let's verify the example usage:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
queue.process() # or queue.process_all()
result = queue.get_result("job1")
```
This works.

I'll write the complete class. I'll add `from typing import Optional` or just use `dict | None`. I'll use `dict | None` as requested.

One minor point: `add_job` returns `job_id`, but it's passed in. That's fine.
I'll implement it now.

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

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

    def process_all(self):
        while self._queue:
            self.process()
```

Wait, `dict | None` is valid in Python 3.10+. The prompt uses it, so I'll keep it. I'll remove `from typing import Optional` to avoid unused import, or keep it if I use it. I'll just use `dict | None`.

Is there any requirement for thread safety? Not explicitly. I'll keep it simple.

One thing: The prompt says "Each job has a unique job_id that is returned when added". This might imply that if no job_id is provided, it should generate one, but the signature explicitly takes `job_id: str`. I'll stick to the signature.

I think this satisfies all requirements. I'll output only the code.
Let's double check the prompt: "Write only the Python code, no explanations."
I will output just the class definition.

One minor adjustment: I'll make `get_result` return `dict | None` as specified.
I'll also add a simple `process()` method since processing mechanism is implied by "Jobs should be processed in FIFO order".

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

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

    def process_all(self):
        while self._queue:
            self.process()
```

This looks solid. It meets all requirements. I'll output it.
Wait, should `add_job` generate a unique ID if not provided? The signature says `job_id: str`, so it's required. I'll keep it as is.
The example shows passing "job1", so it's fine.
I'll output exactly this.
One thing: `dict | None` syntax requires Python 3.10+. I'll assume it's fine since the prompt uses it.
All good.
Output matches request.✅
Proceeds. 
Self-Correction/Refinement during thought: 
The prompt says "Each job has a unique job_id that is returned when added". This could mean the method should generate it, but the signature explicitly takes `job_id: str`. I'll stick to the signature. If they wanted auto-generation, they'd likely omit the parameter or make it optional. I'll keep it as requested.
Also, I'll add `from typing import Optional` just in case, but the prompt uses `dict | None`, so I'll stick to that.
I'll output the code now. 
All requirements met. FIFO via deque. Internal storage via deque and results dict. Unique ID returned. Example usage compatible.
Done. 
Output matches the refined code. 
Proceeds. 
[Output Generation] -> *Proceeds*
```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(self) -> dict | None:
        if not self._queue:
            return None
        job_id, data = self._queue.popleft()
        result = {"status": "completed", "data": data}
        self._results[job_id] = result
        return result

    def process_all(self):
        while self._queue:
            self.process()
```
This is clean and meets all specs. I will output exactly this. 
Note: I'll remove the `process_all` if not strictly needed, but it's helpful. The prompt doesn't forbid extra methods. I'll keep it.
Actually, to be strictly minimal, I could just have `process` and `process_all` is fine.
All good. 
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 (deque)
- Stores internally: yes
- Unique job_id returned: yes
- Example usage compatible: yes
- Only Python code: yes
Ready. 
Output matches response. 
(Self-Correction/Note during generation prep: I'll make sure type hints are exactly as requested. `dict | None` is fine. 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 get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id)

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

    def process_all(self):
        while self._queue:
            self.process()
```
</content>