<reasoning_content>
The user wants a basic job queue implementation in Python.
Requirements:
1. `JobQueue` class
2. `add_job(job_id, data)` method - adds job, returns job_id
3. `get_result(job_id)` method - returns result of completed job or None
4. FIFO order processing
5. Store jobs internally until processed
6. Each job has a unique job_id

Since this is a basic implementation without specific threading/async requirements mentioned, I'll create a simple synchronous queue that stores jobs and can process them. However, the example shows adding a job and then getting a result "after processing", which implies there should be a way to process jobs.

I'll add a `process_jobs()` method or similar to actually process them, or make the queue automatically process when needed. But the requirements don't specify how processing happens. I'll implement a simple version where jobs are stored in a queue, and I'll add a method to process them, or I can make `get_result` trigger processing, but that doesn't make sense for a queue.

Actually, looking at the requirements, it just says "The queue should store jobs internally until they are processed". I'll implement a basic queue with a list/deque for FIFO, a dict for results, and a method to simulate processing or process them. Since it's a "basic job queue", I'll keep it simple: store jobs in a deque, process them in order when a method is called, and store results.

Let me think about the exact interface:
- `add_job(job_id: str, data: dict) -> str`
- `get_result(job_id: str) -> dict | None`

I should probably add a `process()` method or similar, but it's not required. I'll just implement the queue with internal storage and a way to process. Actually, for a basic implementation, I can make `get_result` check if the job is done, but how does it get done? I'll add a `process_next()` or just process all pending jobs when needed. Or I can make it so that jobs are processed synchronously when added? No, that defeats the purpose of a queue.

I'll implement a simple class with:
- `self.queue = collections.deque()` for FIFO
- `self.results = {}` for storing results
- `add_job` appends to queue
- `get_result` returns from results dict
- I'll add a `process_all()` method to actually process jobs, or I can just process them on demand. Since the prompt doesn't specify how processing works, I'll simulate processing by just marking jobs as completed and storing a result.

Actually, a more standard approach for a basic job queue in Python would be to use `queue.Queue` from the standard library, but the requirements ask for a custom class with specific methods.

Let me implement it with a list/deque and a results dict. I'll add a simple process method that takes a function or just simulates processing. But to keep it simple and match the requirements exactly, I'll just store jobs and provide a way to process them. I'll make `get_result` return None if not completed, and add a `process_jobs()` method.

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 there's a separate processing step. I'll add a `process()` method that processes all queued jobs. For simplicity, I'll assume each job's result is just `{"status": "completed", "data": job_data}` or something similar. Or I can make it configurable, but that's overcomplicating.

Let's stick to the simplest valid implementation:
- Store jobs in a deque
- Store results in a dict
- `add_job` appends to deque, returns job_id
- `get_result` returns result or None
- Add `process_all()` method to process jobs in FIFO order

Actually, I can make `get_result` trigger processing if needed, but that's not standard. I'll just implement a clean version with a `process()` method.

Wait, the requirements say "Write only the Python code, no explanations." So I'll just provide the class implementation.

Let me draft it:

```python
import collections

class JobQueue:
    def __init__(self):
        self._queue = collections.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_all(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            # Simulate processing
            self._results[job_id] = {"status": "completed", "data": data}
```

But the requirements don't mention `process_all`. Maybe I should make it so that jobs are processed automatically when added? No, that's not a queue. Maybe the user expects a thread-safe queue with workers? The prompt says "basic job queue", so synchronous is fine.

Actually, I can make `get_result` return None if not processed, and add a comment or just leave it. But to be safe, I'll add a `process()` method. Or I can make the queue process jobs lazily? No.

Let me re-read: "The queue should store jobs internally until they are processed". This implies processing happens separately.

I'll stick with the deque approach and add a `process()` method. I'll also make sure type hints match the requirements.

Actually, I can implement it without external imports by using a list as a queue (pop(0) is O(n) but fine for basic), or just use `collections.deque`.

Let's refine:

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

class JobQueue:
    def __init__(self):
        self._queue: deque = 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 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()
            self._results[job_id] = {"status": "completed", "data": data}
```

Wait, `dict | None` syntax requires Python 3.10+. The prompt uses it, so it's fine. I'll keep it.

Actually, I can make it even simpler. The prompt doesn't require `process_jobs`, but it's needed to actually process. I'll include it. Alternatively, I can make `get_result` return None if not done, and the user is expected to call a process method. That's fine.

Let me check if there's a more standard way. Sometimes "basic job queue" just means a class that wraps a queue. I'll provide exactly what's asked plus a process method.

Actually, I can make the queue process jobs synchronously when `get_result` is called if they haven't been processed yet? No, that's weird.

I'll stick with `process_jobs()`.

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 the user will call something to process between add and get. I'll add a `process()` method.

Let's write it out cleanly.

```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))
        return job_id

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

    def process_all(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = {"status": "completed", "data": data}
```

Actually, I should use `dict | None` as specified. I'll keep it.

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

I'll make sure it's complete and matches requirements exactly. I'll also add type hints properly.

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

class JobQueue:
    def __init__(self):
        self._queue: deque = 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 get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id)

    def process_all(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = {"status": "completed", "data": data}
```

Wait, `dict | None` might cause a syntax error in older Python versions, but the prompt uses it, so I'll assume Python 3.10+. To be safe, I can use `Optional[dict]` but the prompt explicitly uses `dict | None`. I'll stick with `dict | None`.

Actually, I can just use `dict | None` as requested.

Let me reconsider the processing part. The prompt doesn't specify how jobs are processed. In many basic implementations, you might just store them and provide a method to run them. I'll keep `process_all`.

Alternatively, I could make `get_result` automatically process pending jobs if the job_id is in the queue? No, that breaks FIFO if multiple jobs are added.

I think `process_all` is fine.

One more thing: the prompt says "Each job has a unique job_id that is returned when added". My implementation does that.

I'll output just the code as requested.

Final check of the code:
- Class `JobQueue`
- `add_job` appends to deque, returns job_id
- `get_result` returns from results dict or None
- FIFO order via deque
- Stores jobs internally
- Unique job_id returned

Looks good. I'll write it out.
I'll remove the type hints that might cause issues or keep them simple. I'll use `dict | None` as in the prompt.

Actually, I'll make it self-contained without imports if possible, but `collections.deque` is standard. I'll keep it.

One minor adjustment: I'll make `process_all` just a simple method. The prompt doesn't require it, but it's necessary for the queue to work. I'll include it.

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_all(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = {"status": "completed", "data": data}
```

This matches all requirements. I'll output it.
Wait, should I make `get_result` return `None` if not found, or raise an error? The requirement says `-> dict | None`, so returning `None` is correct.

All good. Output matches.✅
I'll produce the final answer. 
One thing: the prompt says "Write only the Python code, no explanations." So I'll strictly follow that.
I'll make sure the code is complete and ready to run.
Done. 
Output matches the refined code. 
Proceeds. 
(Self-Correction/Refinement during thought)
Actually, I should consider if the user expects a thread-safe queue or async. The prompt says "basic job queue", so synchronous is fine. 
The `dict | None` syntax is Python 3.10+. I'll keep it as requested.
I'll output exactly the code block.
Done. 
Output generation. 
```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_all(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = {"status": "completed", "data": data}
```
Actually, I'll remove the `from typing import Optional` since it's unused. I'll keep `dict | None` as in the prompt.
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_all(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = {"status": "completed", "data": data}
```
This is clean and meets all requirements. Output matches. 
Proceeds. 
[Output Generation] -> *outputs the code*
(Note: I'll make sure formatting is exact)
All good. 
Done. 
[Final Check]
- `JobQueue` class: yes
- `add_job` returns job_id: yes
- `get_result` returns dict or None: yes
- FIFO: yes (deque)
- Stores internally: yes
- Unique job_id: yes (passed in, returned)
- Example usage works: yes
- Only Python code: yes
Ready. 
Output matches response. 
[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_all(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = {"status": "completed", "data": data}
```
</content>