<reasoning_content>
The user wants a basic job queue implementation in Python with specific 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 processing order
5. Internal storage until processed
6. Unique job_id returned when added

Since it's a "basic" job queue and the example shows adding a job and then getting a result "after processing", I need to simulate or actually process jobs. The requirements don't specify how jobs are processed, but typically a job queue would have a worker or a process method. However, the requirements only mention `add_job` and `get_result`. I should probably include a way to process jobs, maybe a `process_next()` or `run()` method, or process them automatically when added. But the example says "# After processing...", implying processing happens separately.

Let's re-read carefully: "Jobs should be processed in FIFO (First-In-First-Out) order", "The queue should store jobs internally until they are processed". This implies there should be a mechanism to process jobs. I'll add a `process_next()` method or similar, or maybe process them in a background thread, but the prompt says "basic job queue". I'll keep it simple: store jobs in a queue, provide a method to process them, and store results.

Actually, I can implement it with a `collections.deque` for the queue, a dict for pending jobs, and a dict for completed results. I'll add a `process()` method that processes the next job in FIFO order. Since no specific processing logic is given, I'll simulate processing by just storing the data as the result, or maybe add a placeholder processing step.

Wait, the prompt says "Write only the Python code, no explanations." I should just provide the class.

Let's design it:
```python
from collections import deque
import uuid
import time

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_next(self):
        if not self._queue:
            return None
        job_id, data = self._queue.popleft()
        # Simulate processing
        result = {"status": "completed", "data": data}
        self._results[job_id] = result
        return result
```

But the prompt doesn't explicitly ask for a `process_next` method. It just says "Jobs should be processed in FIFO order". Maybe I should process them automatically when added? Or maybe the queue is just meant to store them, and processing is external? The example shows `queue.add_job(...)` then `# After processing...` then `queue.get_result(...)`. This implies processing happens somewhere. I'll add a `process()` method that processes all pending jobs, or `process_next()`.

Actually, a common simple implementation would just have the queue store jobs, and maybe a `run()` or `process()` method. I'll stick with `process_next()` or just process them in a loop. To be safe, I'll implement a `process()` method that processes the next job, or I'll just make it so that `add_job` queues it, and there's a `process_all()` or similar.

Wait, the requirements are very specific:
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

It doesn't specify a process method, but says "Jobs should be processed in FIFO order". I'll add a `process_next()` method to fulfill the FIFO processing requirement. Or maybe I should just use a `queue.Queue` and a worker thread? That might be overkill.

Let's keep it simple and synchronous. I'll add a `process()` method that processes jobs in FIFO order. Actually, I can just process them when `get_result` is called if not processed yet? No, that violates FIFO.

I'll implement a simple synchronous queue with a `process_next()` method. Or maybe the prompt expects me to just implement the class with those two methods, and processing is implied to be handled elsewhere, but I need to ensure FIFO. I'll use `collections.deque` for FIFO storage.

Actually, many basic job queue implementations in interviews just want you to use a deque and a dict for results, with a method to process. I'll add `process_next()` and `process_all()` for completeness, but keep it minimal.

Wait, the prompt says "Write only the Python code, no explanations." I'll just provide the class.

Let's refine:
```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_next(self) -> dict | None:
        if not self._queue:
            return None
        job_id, data = self._queue.popleft()
        # Simulate job processing
        result = {"job_id": job_id, "status": "completed", "data": data}
        self._results[job_id] = result
        return result
```

But the prompt says "Jobs should be processed in FIFO (First-In-First-Out) order". This is inherently handled by `deque.popleft()`.

Is there any chance they want an async/threaded queue? "basic job queue" usually implies synchronous or simple threading. I'll stick to synchronous.

Actually, I can make it so that processing happens automatically in the background, but that's more complex. I'll keep it simple.

Wait, the example shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
This implies that processing might be triggered by some other means, or maybe `add_job` triggers it? If `add_job` triggers processing immediately, then FIFO is trivial but pointless. The comment "# After processing..." suggests processing happens separately.

I'll add a `process()` method that processes all pending jobs in FIFO order, or just `process_next()`. I think `process_next()` is fine.

Actually, to strictly match the requirements without adding extra methods not requested, maybe I should just implement the two methods and assume processing is external, but I need to show how FIFO is maintained. I'll store jobs in a deque. When a job is "processed" (maybe by an external worker calling a method, or I'll add a `run()` method), it moves to results.

I'll add a `process()` method that processes the next job. It's standard.

Let's reconsider: maybe they want a queue that automatically processes jobs when added? No, "store jobs internally until they are processed" implies they wait.

I'll implement it with a `process_next()` method. It's safe.

Actually, I can make it even simpler: just use `collections.deque` and a dict. I'll provide exactly what's asked.

```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_next(self) -> dict | None:
        if not self._queue:
            return None
        job_id, data = self._queue.popleft()
        # Process job (simulated)
        result = {"status": "completed", "data": data}
        self._results[job_id] = result
        return result
```

Wait, the type hint `dict | None` requires Python 3.10+. I'll use `Optional[dict]` or keep `dict | None` as requested. The prompt uses `dict | None`, so I'll stick with that.

One thing: the prompt says "Each job has a unique job_id that is returned when added". The `add_job` method takes `job_id` as parameter, so it's provided by the caller. That's fine.

I think this is sufficient. I'll output just the code.

Let's double check the requirements:
1. `JobQueue` class with `add_job` and `get_result`
2. FIFO order
3. Store internally until processed
4. Unique job_id returned

I'll add a `process()` method to actually process jobs, otherwise "processed" is never triggered. Or maybe I should process them in a background thread? The prompt says "basic job queue", so synchronous is fine. I'll stick with `process_next()` or `process_all()`. Actually, I'll just add a `process()` method that processes the next job.

Alternatively, I could make `add_job` schedule it, and provide a `run()` method. I'll keep it simple.

Actually, many simple job queue implementations just have a `process()` method that loops through the queue. I'll add `process_next()` as it's clear.

Wait, maybe the prompt expects the queue to automatically process jobs? "Jobs should be processed in FIFO order" might just mean the internal data structure maintains FIFO. I'll use `collections.deque` which guarantees FIFO.

I'll write the code now.
One minor thing: I'll use `typing.Optional` for compatibility, or just `dict | None` as in the prompt. I'll stick to `dict | None`.

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

This meets all requirements. I'll output it.
Wait, should I include `process_all()`? Not required. The prompt says "Write only the Python code, no explanations." I'll just output the class.

One thing: the prompt says "Each job has a unique job_id that is returned when added". The `add_job` signature already returns `job_id`. That's fine.

I think it's good.
I will output exactly the code.
Let's verify type hints: `dict | None` is valid in Python 3.10+. I'll keep it.
I'll add `from typing import Optional` just in case, but the prompt uses `dict | None`, so I'll stick to that.

Actually, to be safe and standard, I'll use `dict | None` as requested.

Code looks solid.
Output matches request.
Proceed. 
One minor adjustment: I'll make sure the class is complete and ready to use.
```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_next(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
```
This is fine. I'll output it. 
Wait, should I process jobs automatically in a separate thread? The prompt says "basic job queue", so synchronous is standard for such exercises unless specified otherwise. I'll stick with synchronous.
All good.
Output matches. 
Proceeding. 
(Self-Correction/Refinement during thought)
Actually, the prompt says "Jobs should be processed in FIFO order". It doesn't explicitly ask for a process method, but it's implied. I'll keep `process_next()`. Alternatively, I could just have the queue store jobs and assume an external worker calls a method. But providing `process_next()` makes it functional.
I'll output the code exactly.
Done. 
Output generation. 
```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_next(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
```
This matches all constraints. I'll provide it. 
Note: I'll remove the comments to keep it clean, as requested "Write only the Python code, no explanations."
Done. 
Output matches response. 
Proceeds. 
[Final Check]
- Class name: JobQueue ✓
- Methods: add_job, get_result ✓
- FIFO: deque ensures FIFO ✓
- Stores internally: _queue and _results ✓
- Returns job_id: yes ✓
- Type hints: match prompt ✓
- No explanations: yes ✓
All good. 
Output generation. 
```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_next(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
```
Looks ready.✅
I will output this exactly. 
One thing: `dict | None` syntax requires Python 3.10+. If they want broader compatibility, `Optional[dict]` is safer, but the prompt explicitly uses `dict | None`, so I'll keep it. 
Done. 
Output matches. 
[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_next(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
```
</content>