<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`: Add job, return job_id
3. `get_result(job_id: str) -> dict | None`: Get result of completed job
4. FIFO order processing
5. Store jobs internally until processed
6. Unique job_id returned when added

Wait, the example shows `add_job("job1", {"task": "process_data"})` but the signature says `add_job(job_id: str, data: dict) -> str`. The example passes "job1" as job_id, but typically job IDs are generated internally. However, the signature explicitly takes `job_id` as a parameter. I'll follow the signature. Actually, looking at the example: `job_id = queue.add_job("job1", {"task": "process_data"})`, it seems the user wants to pass the job_id or maybe generate it. The signature says `job_id: str`, so I'll accept it. But to ensure uniqueness, maybe I should generate it if not provided, or just use what's provided. I'll stick to the signature.

Wait, the requirement says "Each job has a unique job_id that is returned when added". This could mean the method generates it, or the caller provides it. I'll generate it internally to be safe, or just use the provided one. Let's re-read: "add_job(job_id: str, data: dict) -> str: Add a job to the queue, return job_id". I'll just use the provided job_id.

For processing: The requirement says "Jobs should be processed in FIFO order" and "The queue should store jobs internally until they are processed". It doesn't specify how processing happens. I'll add a `process_next()` method or assume the user will call a processing method, or maybe I should include a simple synchronous processor for demonstration? The prompt says "Implement a basic job queue", and the example just adds and gets result. I'll add a `process()` method that simulates processing, or maybe the user expects the queue to just hold jobs and results. I'll add a `process()` method that takes the next job and sets a result, or maybe just store jobs and provide a way to mark them as done. Actually, a simpler approach: I'll implement a `process()` method that simulates processing by just returning a result dict, or I'll leave processing abstract but provide a `run()` method. Wait, the prompt says "Each job has a unique job_id that is returned when added". I'll just store jobs in a list/queue and a dict for results.

Let's think about standard implementations. Usually, a job queue has an internal queue (collections.deque) and a results dict.
I'll add a `process()` method that pops a job, simulates processing, and stores the result. Or maybe the user just wants the data structure. I'll keep it simple: store jobs in a deque, store results in a dict. I'll add a `process_next()` method that takes `data`, computes a dummy result, and stores it. Or maybe I'll just store the job and let the user process it, but the requirement says "until they are processed", implying the queue handles processing or there's a way to process.

Actually, I can just implement a `run()` method that processes all jobs, or `process()` that processes one. I'll stick to a simple synchronous simulation: `process(job_data: dict) -> dict` that returns a result, and `process_next()` that processes the next job in FIFO order.

Wait, the example doesn't show processing. It just shows `add_job` and `get_result`. I'll assume the user will call a `process()` method or I'll provide one. I'll add a `process(job_data: dict) -> dict` method that simulates processing, and maybe `process_next()` to process from the queue.

Actually, a simpler interpretation: The queue just stores jobs. Processing is external, but the queue manages order. I'll implement `add_job`, `get_result`, and maybe `process()` that takes data and returns a result, storing it. Or I'll just store jobs and results, and add a `run()` method that processes them.

Let's re-read carefully: "Jobs should be processed in FIFO (First-In-First-Out) order". This implies the queue itself handles processing or at least the order of processing. I'll implement a `process()` method that takes the next job from the queue and simulates processing, storing the result. Or I'll just make a `execute()` method.

Actually, I'll keep it minimal. I'll use `collections.deque` for the queue. I'll store jobs as `(job_id, data)`. I'll have a `results` dict. I'll add a `process()` method that pops a job, computes a dummy result (e.g., `{"status": "completed", "data": job_data}`), and stores it. If the queue is empty, it returns None or raises an error.

Wait, the prompt says "Implement a basic job queue in Python." It's a coding exercise. I'll provide a clean implementation.

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

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

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

But the requirement says `add_job(job_id: str, data: dict) -> str`. It passes `job_id` as an argument. I'll stick to that.
Maybe I should generate the job_id if not provided? The signature says `job_id: str`, so it's required. I'll just use it.

Wait, "Each job has a unique job_id that is returned when added". This might mean the method should generate it. I'll change the signature slightly to `def add_job(self, data: dict, job_id: str = None) -> str:` but the prompt explicitly says `add_job(job_id: str, data: dict) -> str`. I'll follow the prompt exactly.

Actually, to be safe, I'll just follow the exact signature. I'll generate a UUID if needed, but the prompt says `job_id: str` is passed. I'll just use it.

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

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

    def process(self, job_data: dict) -> dict:
        # Simulate processing logic
        return {"status": "completed", "data": job_data}

    def run_next(self) -> Optional[dict]:
        if not self._queue:
            return None
        job_id, data = self._queue.popleft()
        result = self.process(data)
        self._results[job_id] = result
        return result
```

But the prompt doesn't ask for `process` or `run_next`. It just says "Jobs should be processed in FIFO order". Maybe I should just store jobs and provide a way to process them, or maybe the queue is meant to be used with a worker. I'll add a `process_next()` method as it's standard. Alternatively, I could make the queue process automatically, but that requires threading. I'll stick to synchronous.

Actually, a simpler approach that matches typical coding interview questions: just store jobs in a list/deque, and provide a `process()` method that takes a job and returns a result, or just store the job and mark it as done. But the prompt says "The queue should store jobs internally until they are processed". This implies the queue holds them until processed.

I'll implement it with a `process()` method that simulates processing, and `process_next()` to dequeue and process. Or maybe just `process(data)` is enough. I'll keep it simple.

Wait, maybe the user expects the queue to have a `run()` method that processes all, or maybe just `add_job` and `get_result` are enough, and processing is external. I'll add a `process()` method that takes `data` and returns a result, and `process_next()` that processes from the queue.

Actually, I'll just implement exactly what's asked, plus a simple `process()` method to fulfill "processed in FIFO order". I'll make `process_next()` the main processing method.

Let's reconsider the exact wording: "Jobs should be processed in FIFO (First-In-First-Out) order". This is a property of the queue. I'll just use `collections.deque` which naturally supports FIFO.

I'll write the code concisely.

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

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

    def process_next(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
```

This covers all requirements. It uses FIFO (deque), stores jobs internally, has unique job_id, returns it, and allows getting results. Processing is simulated in `process_next()`.

One thing: the example shows `add_job("job1", {"task": "process_data"})`. My signature matches.
I'll add type hints as requested. `dict | None` is Python 3.10+ syntax. I'll use `Optional[dict]` for compatibility, or stick to `dict | None` if assuming modern Python. The prompt uses `dict | None`, so I'll use that.

Let's adjust type hints to match prompt:
```python
import collections
from typing import Dict

class JobQueue:
    def __init__(self):
        self._queue = 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) -> 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
```

Wait, should I generate the job_id instead of taking it? The prompt says `add_job(job_id: str, data: dict) -> str`. It explicitly takes job_id. I'll keep it.

Is there any chance the prompt wants the queue to process automatically? "The queue should store jobs internally until they are processed" suggests external processing or a method to trigger it. I'll stick with `process_next()`.

Actually, to be safe, I'll make `process()` a method that takes `data` and returns a result, and `process_next()` uses it. Or I'll just keep it simple.

I think this is sufficient. I'll output only the Python code as requested.
One minor thing: `dict | None` requires Python 3.10+. I'll use `Optional[dict]` or just keep `dict | None` as in the prompt. The prompt uses `dict | None`, so I'll keep it.

Final check of the prompt: "Write only the Python code, no explanations."
I'll provide exactly that.

Code:
```python
import collections
from typing import Dict

class JobQueue:
    def __init__(self):
        self._queue = 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) -> 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
```

Wait, should `process_next` be part of the required methods? The prompt only lists `add_job` and `get_result`. It says "Jobs should be processed in FIFO order". It doesn't explicitly require a `process_next` method, but it's necessary to fulfill the processing requirement. I'll include it. Alternatively, I could make the queue process automatically when `get_result` is called? No, that's weird. I'll stick with `process_next`.

Actually, maybe the user expects a synchronous queue where you just add and it processes? No, "store jobs internally until they are processed" implies asynchronous or manual processing.

I'll keep `process_next`. It's standard.

One more thing: the prompt says `add_job(job_id: str, data: dict) -> str`. I'll follow it exactly.
I'll output the code now.
All good.
I will make sure type hints match the prompt's style.
Done. 
Let's produce the response. 
Self-Correction/Refinement during thought: 
Maybe I should generate the job_id if not provided, but the signature is fixed. I'll stick to it.
The prompt says "Each job has a unique job_id that is returned when added". This could just mean the method returns the job_id.
I'll keep it simple.
Code matches requirements.
Output matches request.
Proceed. 
```python
import collections
from typing import Dict

class JobQueue:
    def __init__(self):
        self._queue = 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) -> 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 looks solid. I'll output it. 
Wait, should I use `typing.Optional` instead of `dict | None` for broader compatibility? The prompt uses `dict | None`, so I'll keep it. Python 3.10+ is standard now.
All set. 
Output matches exactly.✅
Proceeds. 
[Output Generation] -> *Proceeds*
*(Self-Correction/Verification during generation prep)*
I notice the prompt says `add_job(job_id: str, data: dict) -> str`. But typically job IDs are generated. I'll stick to the prompt's signature.
The example shows `job_id = queue.add_job("job1", {"task": "process_data"})`. This matches.
I'll output the code. 
One minor point: `dict | None` is valid in Python 3.10+. I'll assume modern Python. If needed, I can use `Optional[dict]`, but the prompt explicitly uses `dict | None`. I'll keep it.
All good. 
Output matches request. 
Done. 
[Output] -> *Code Block*
```python
import collections
from typing import Dict

class JobQueue:
    def __init__(self):
        self._queue = 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) -> 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
```
Matches all constraints. Ready. 
(Self-Correction/Note during thought)
Actually, to be strictly compliant with "Write only the Python code, no explanations.", I will output just the code block.
I'll make sure indentation and syntax are correct.
Done. 
Proceeds. 
[Output Generation] (matches the refined code)
```python
import collections
from typing import Dict

class JobQueue:
    def __init__(self):
        self._queue = 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) -> 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
```
All good.✅
Output matches. 
[Final Check]
- `JobQueue` class: yes
- `add_job(job_id: str, data: dict) -> str`: yes
- `get_result(job_id: str) -> dict | None`: yes
- FIFO: `collections.deque` with `popleft`
- Stores internally: `_queue` and `_results`
- Unique job_id returned: yes
- Example usage compatible: yes
- Only Python code: yes
Ready. 
Output matches response. 
Proceeds. 
[Output Generation] (Proceeds)
*(Done)*

</reasoning_content>

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

class JobQueue:
    def __init__(self):
        self._queue = 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) -> dict | None:
        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
```
</content>