<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 processing order
5. Internal storage until processed
6. Unique job_id returned
7. Example usage provided
8. Write only Python code, no explanations.

I need to implement the `JobQueue` class. Since it's a basic queue, I can use `collections.deque` for FIFO ordering.
I also need a way to store results. A dictionary mapping job_id to result would work.
The processing part isn't explicitly detailed, but typically a job queue implies some background worker or a method to process jobs. However, the requirements just say "The queue should store jobs internally until they are processed" and provide `add_job` and `get_result`. I'll implement a simple synchronous processing method or assume the user will handle processing, but to make it functional as a "queue", I should probably include a way to process jobs or at least structure it so results can be stored. Actually, the prompt says "Implement a basic job queue", and gives `add_job` and `get_result`. I'll add a `process_job(job_id)` method or just keep it simple. Wait, the requirements only list `add_job` and `get_result`. I'll stick to those, but I might need a way to simulate processing or just store pending jobs. To be safe, I'll add a `process_next()` method or just let the user handle it, but the prompt says "Jobs should be processed in FIFO order". I'll implement a simple synchronous processor or just structure the data. Actually, a common pattern is to have a `process()` method that runs the next job. But the prompt doesn't ask for it. I'll just implement the storage and FIFO structure, and maybe a `process()` method that takes the first job, computes a dummy result (or just marks it complete), or I can just store jobs and results separately.

Let's think about what "processed" means in this context. Usually, it means a worker thread/process executes the job. Since this is a basic implementation request, I'll implement a simple in-memory queue with a `process()` method that simulates execution, or I'll just store jobs and let the user process them. Actually, I'll add a `process_job(job_id)` method that retrieves the job, simulates processing, stores the result, and removes it from the queue. Or better, I'll just implement the queue structure as requested and include a simple `process_next()` method to fulfill "processed in FIFO order".

Wait, the requirements are:
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

I'll use `collections.deque` for the queue and a `dict` for results and pending jobs.
To satisfy "processed", I'll add a `process()` method that takes the first job, computes a result (e.g., `{"status": "completed", "data": job_data}`), stores it, and removes it from the queue. Or I can just leave processing abstract, but it's better to make it functional.

Actually, a simpler approach: just store pending jobs in a deque, and results in a dict. The `get_result` returns from the dict. I'll add a `process()` method that runs the next job. But the prompt doesn't ask for `process()`. I'll just implement the class with the two methods, and maybe a `process()` method for completeness, or I'll just assume the user will call a processing function. I'll stick strictly to the requirements but make it work.

Let's implement:
```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, None)
        
    def process_next(self) -> bool:
        if not self.queue:
            return False
        job_id, data = self.queue.popleft()
        # Simulate processing
        self.results[job_id] = {"status": "completed", "data": data}
        return True
```

Wait, the prompt says "Write only the Python code, no explanations." and gives example usage:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
This implies `get_result` should work after processing. I'll include a `process()` method that processes all pending jobs or just one. To keep it simple and match typical queue implementations, I'll add a `process()` method that runs the next job, or maybe `process_all()`. Actually, I'll just implement `process()` that takes the first job.

But maybe the prompt expects a thread-safe queue or just a simple structure. I'll stick to a simple structure. I'll also add type hints as requested.

Let's refine:
```python
import collections
from typing import Dict, Optional

class JobQueue:
    def __init__(self):
        self._queue: collections.deque = collections.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) -> Optional[dict]:
        return self._results.get(job_id)

    def process_next(self) -> bool:
        if not self._queue:
            return False
        job_id, data = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": data}
        return True
```

Wait, the requirement says "Jobs should be processed in FIFO (First-In-First-Out) order". The `process_next` method does that. I'll also add a `process_all()` method for convenience, or just leave it. The prompt doesn't strictly require `process_next`, but it's needed to actually process jobs. I'll include it.

Actually, I can make it even simpler. The prompt might just want the storage and retrieval. I'll stick to the two required methods and add a `process()` method to fulfill the processing requirement. Or I can just implement a `run()` method that processes jobs. I think it's fine.

Let's check the exact wording: "Implement a basic job queue in Python." "Requirements: 1. Create a JobQueue class with the following methods: add_job, get_result. 2. Jobs should be processed in FIFO order. 3. The queue should store jobs internally until they are processed. 4. Each job has a unique job_id that is returned when added."

I'll implement exactly that. I'll use `collections.deque` for FIFO. I'll store pending jobs as `(job_id, data)` tuples. I'll store results in a dict. I'll add a `process()` method that processes the next job in FIFO order.

One thing: `get_result` should return `dict | None`. In Python 3.10+, `dict | None` is valid. I'll use `Optional[dict]` for broader compatibility, or just `dict | None` as requested. I'll stick to `dict | None` if Python 3.10+ is assumed, but `Optional[dict]` is safer. I'll use `dict | None` as in the prompt.

Let's write it out carefully.

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

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

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

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

    def process_next(self) -> bool:
        if not self._pending:
            return False
        job_id, data = self._pending.popleft()
        self._results[job_id] = {"status": "completed", "data": data}
        return True

    def process_all(self) -> int:
        count = 0
        while self.process_next():
            count += 1
        return count
```

Wait, the prompt says "Write only the Python code, no explanations." I will output just the code. I'll remove `process_all` if not needed, but it's fine. I'll keep it simple. Actually, I'll just implement the required methods and a `process()` method that processes one job. The prompt doesn't ask for `process_next`, but it's necessary to demonstrate FIFO processing. I'll include it.

Alternatively, maybe the queue is supposed to be processed externally, and the class just manages storage. But "Jobs should be processed in FIFO order" implies the class handles it or the structure enforces it. Using `deque` enforces FIFO order for retrieval.

I'll stick to the implementation above. It's clean and meets all requirements.

One minor thing: `dict | None` syntax requires Python 3.10+. I'll use `Optional[dict]` from typing to be safe, or just keep `dict | None` as requested. The prompt uses `dict | None`, so I'll use that.

Final code:
```python
import collections
from typing import Dict

class JobQueue:
    def __init__(self):
        self._queue: collections.deque = collections.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, None)

    def process_next(self) -> bool:
        if not self._queue:
            return False
        job_id, data = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": data}
        return True
```

Wait, should I include `process_all`? Not strictly required. I'll leave it out to keep it minimal. The prompt says "Write only the Python code". I'll output exactly that.

Let's double check requirements:
1. `add_job(job_id: str, data: dict) -> str` -> implemented
2. `get_result(job_id: str) -> dict | None` -> implemented
3. FIFO -> `deque` ensures this
4. Store internally until processed -> `_queue` stores until `process_next` is called
5. Unique job_id returned -> returns `job_id`
Example usage matches.

I'll add type hints properly. `dict | None` is fine. I'll use `from typing import Optional` just in case, but the prompt uses `dict | None`. I'll stick to `dict | None`.

One thing: `collections` is a module, I can just use `list` with `pop(0)` but `deque` is better for FIFO. I'll import `deque` from `collections`.

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

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, None)

    def process_next(self) -> bool:
        if not self._queue:
            return False
        job_id, data = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": data}
        return True
```

This looks solid. I'll output exactly this. No extra text.
Wait, should I make `process_next` part of the required interface? The prompt only lists `add_job` and `get_result`. I'll keep `process_next` as it's necessary to actually process jobs, but I could also just document it or leave it. It's fine.

I will output the code block only.
One minor adjustment: I'll use `typing.Optional` for broader compatibility, but the prompt explicitly uses `dict | None`. I'll stick to `dict | None`.
I'll also add a simple `process_all` method just in case, but it's optional. I'll skip it to be concise.

Final check of the prompt: "Write only the Python code, no explanations."
I will provide exactly the class implementation.
Ready.✅
Output matches response. 
Proceeds. 
Self-Correction/Refinement during thought: 
Should I include a worker thread? The prompt says "basic job queue", so synchronous is fine. 
The example shows `# After processing...` which implies external processing or a method call. I'll keep `process_next` as it's standard. 
All good. 
Output generation. 
```python
from collections import deque
from typing import Dict

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, None)

    def process_next(self) -> bool:
        if not self._queue:
            return False
        job_id, data = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": data}
        return True
```
This satisfies all constraints. I'll output it. 
Note: `dict | None` requires Python 3.10+. If the environment is older, it might error. I'll change to `Optional[dict]` to be safe, or keep `dict | None` as requested. I'll stick to `dict | None` as it's in the prompt. Actually, I'll use `typing.Optional` to be strictly compatible, but the prompt uses `dict | None`. I'll just use `dict | None` as written. It's fine.
Done. 
Output matches. 
Proceeds. 
[Output Generation] -> *Proceeds*

</reasoning_content>

<content>
```python
from collections import deque
from typing import Dict

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, None)

    def process_next(self) -> bool:
        if not self._queue:
            return False
        job_id, data = self._queue.popleft()
        self._results[job_id] = {"status": "completed", "data": data}
        return True
```
</content>