<reasoning_content>
The user wants a basic job queue implementation in Python.
Requirements:
1. `JobQueue` class with `add_job` and `get_result` methods.
2. FIFO order processing.
3. Internal storage of jobs until processed.
4. Unique job_id returned.

I need to implement:
- A queue data structure to store jobs in order.
- A way to store results.
- A mechanism to process jobs (though the prompt doesn't specify *how* they are processed, just that they should be processed in FIFO order and results retrievable. Usually, this implies a worker or a process method, but the example just shows adding and getting result. I'll add a `process_all` method or similar to simulate processing, or assume the user will call a method to process. Wait, the prompt says "Jobs should be processed in FIFO order" and "The queue should store jobs internally until they are processed". It doesn't explicitly ask for a processing method, but without one, the queue is just a data structure. However, looking at the example: `queue.add_job(...)` then `queue.get_result(...)`. This implies the job might be processed somewhere else, or I need to provide a way to process it. Given the simplicity, I'll implement a `process_job` method or `process_all` to simulate the processing logic, or just store the job and let the user know it needs processing. Actually, a common pattern in these simple implementations is to have a method that processes the next job. Let's add a `process_next()` method or `process_all()` to make it functional. Or, perhaps the prompt implies a background thread? "Basic job queue" usually implies a class that manages the queue. I will add a `process` method that takes a function or just simulates a result for the sake of the example working.
Wait, the example doesn't show calling a process method. It just adds and gets result. This suggests the processing might happen asynchronously or the user is expected to implement the processing logic. However, to make the code complete and runnable as per the example, I should probably include a way to mark a job as processed. Let's add a `process_job(job_id)` method that simulates processing and stores the result. Or better, a `process_all()` that processes all pending jobs.
Actually, looking at the requirements again: "Jobs should be processed in FIFO order". This is a behavior requirement. I'll implement a `process_next()` method that pops a job, simulates processing (e.g., returns a result dict), and stores it. I'll also add a `process_all()` for convenience.
To keep it simple and focused on the queue mechanics, I'll use `collections.deque` for the queue and a dict for results.
I'll add a `process_job` method that takes a processing function? No, that's overcomplicating. I'll just simulate processing by setting a result like `{"status": "completed", "data": job_data}`.
Wait, the prompt says "Write only the Python code". I should provide a complete class. I'll include a `process_all` method to demonstrate FIFO processing, or just leave it as a storage queue and add a comment? No, "Jobs should be processed" implies the class should handle processing or provide the mechanism. I'll add a `process_next` method.
Actually, many simple job queue implementations just store jobs and have a `get_next_job` method. But the requirement says "get_result", implying jobs are completed. I'll implement a simple synchronous processor for demonstration.
Let's stick to the minimal requirements: class, add_job, get_result. I'll add a `process_job` method to make it functional. I'll simulate processing by just marking it done.
To be safe, I'll implement a `process_all` method that processes all queued jobs in FIFO order and stores results. This satisfies "processed in FIFO order".
I'll use `uuid` or just use the provided `job_id`. The requirement says "Each job has a unique job_id that is returned when added". The example shows passing `job_id` as the first argument to `add_job`. So `job_id` is provided by the user. I'll store it as is.
Structure:
```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}
```
Wait, the requirement says "Jobs should be processed in FIFO order". It doesn't explicitly ask for a processing method, but without one, the queue does nothing. I'll include `process_all` or `process_next`. I'll stick with `process_all` for simplicity. Alternatively, I could use a threading approach, but that's overkill. I'll keep it synchronous.
Actually, the prompt might just want the storage part, and assume processing happens externally. But "Jobs should be processed" is a requirement for the class behavior. I'll add a `process_job` method that can be called, or just `process_all`. I'll add `process_all` to satisfy the requirement clearly.
Let's refine: The example shows `add_job` then `get_result`. It doesn't show processing. This implies the processing might be implicit or the user is expected to call a method. I'll add `process_next()` and `process_all()`. I'll just implement `process_all` for the example to work if they call it. Or maybe the queue is meant to be used with a worker thread? "Basic job queue" usually means a data structure. I'll provide the class with storage and a `process_all` method. I'll also make sure type hints are correct.
Wait, `dict | None` is Python 3.10+ syntax. I'll use `typing.Optional[dict]` or just stick to `dict | None` as requested. The prompt uses `dict | None`, so I'll use that.
I'll write the code concisely.

One thing: `add_job` returns `job_id`. The example passes `"job1"` as the first argument. So `job_id` is an input parameter.
I'll implement it exactly as requested.

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

Is there any need for thread safety? "Basic job queue" usually doesn't require it unless specified. I'll skip threading to keep it simple.
The prompt says "Write only the Python code, no explanations."
I'll output just the code.
I should check if `collections` needs to be imported. Yes.
I'll use `from collections import deque` for cleaner code.
Also, I'll add a `process_next` method just in case, but `process_all` is fine.
Actually, the requirement "Jobs should be processed in FIFO order" might just describe the queue's nature. I'll stick with `process_all`.
Wait, maybe the user expects the queue to process jobs automatically? Without a thread, that's impossible in a blocking way. I'll assume synchronous processing is fine.
I'll provide the class with `add_job`, `get_result`, and `process_all`.
Let's verify the example usage:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
If they don't call `process_all`, `result` will be `None`. That's fine. I'll add a comment or just leave it. The prompt says "After processing...", implying they will process it.
I'll add `process_all` method.
Code looks solid.
One minor thing: `dict | None` is valid in Python 3.10+. I'll keep it as is.
I'll write the complete code.
No extra text.
Done. 
Let's generate. 
Self-Correction/Refinement during thought: 
Should I make `process_all` part of the class? Yes. 
Should I handle duplicate job_ids? The requirement doesn't specify, but typically a job queue might allow duplicates or raise an error. I'll just append as is, or check if exists. I'll keep it simple: just append. 
The prompt says "Each job has a unique job_id that is returned when added". This implies the caller ensures uniqueness. 
I'll stick to the simple implementation. 
Final code:
```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()
            self._results[job_id] = {"status": "completed", "data": data}
```
This meets all requirements. I'll output it. 
Wait, should I include type hints for methods? Yes. 
The prompt uses `dict | None`, so I'll use that. 
All good. 
Output matches response. 
Proceeds. 
[Output Generation] -> *Self-Correction/Verification during generation prep*: 
The prompt says "Write only the Python code, no explanations." 
I will output exactly the code block. 
One thing: `collections` import is needed. 
I'll put it at the top. 
Done. 
Output matches the refined code. 
Proceeds. 
[Final Check]
- `JobQueue` class? Yes.
- `add_job(job_id, data) -> str`? Yes.
- `get_result(job_id) -> dict | None`? Yes.
- FIFO order? `deque` with `popleft` ensures FIFO.
- Stores internally? Yes, `_queue` and `_results`.
- Unique job_id returned? Yes.
- Example usage compatible? Yes.
- Only Python code? Yes.
All constraints satisfied. 
Output generation. 
```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()
            self._results[job_id] = {"status": "completed", "data": data}
```
Looks good. I will output this. 
Note: I'll make sure indentation is correct. 
Ready. 
[Output] -> *Proceeds*

</reasoning_content>

<content>
```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()
            self._results[job_id] = {"status": "completed", "data": data}
```
</content>