<reasoning_content>
The user wants a basic job queue implementation in Python.
Requirements:
1. `JobQueue` class with `add_job(job_id: str, data: dict) -> str` and `get_result(job_id: str) -> dict | None`
2. FIFO order processing
3. Store jobs internally until processed
4. Unique job_id returned when added (though the example shows passing the job_id in `add_job`, the requirement says "Each job has a unique job_id that is returned when added". I'll stick to the signature provided: `add_job(job_id: str, data: dict) -> str`. Wait, the example shows `queue.add_job("job1", {"task": "process_data"})` and assigns it to `job_id`. So the user provides the job_id, or maybe I should generate it? The signature says `job_id: str` as a parameter, so I'll use the provided one. Actually, the requirement says "Each job has a unique job_id that is returned when added". I'll just use the passed `job_id` or generate one if needed, but the signature is fixed. I'll stick to the signature.)

Wait, the requirement says:
`add_job(job_id: str, data: dict) -> str`: Add a queue, return job_id.
So the method takes `job_id` and returns it.

How are jobs processed? The prompt doesn't specify a `process()` or `run()` method, or a background thread. It just says "The queue should store jobs internally until they are processed". I should probably add a `process()` method or assume the user will call it. Or maybe I should simulate processing? The prompt says "After processing..." in the example. I'll add a `process()` method that simulates processing, or maybe just a simple synchronous processing method. Actually, the prompt says "Implement a basic job queue". I'll add a `process_all()` or `process()` method. Or maybe the queue itself doesn't process, but the user expects a way to process. I'll add a `process()` method that processes the next job and stores the result. Or maybe I should just make `get_result` wait? No, that's overcomplicating.

Let's stick to a simple synchronous queue. I'll add a `process()` method that takes a function or just simulates processing. Actually, the example just shows `add_job` and `get_result`. I'll assume processing happens elsewhere or I'll provide a `process()` method. To keep it simple, I'll implement a `process()` method that pops the next job, simulates some work (or just marks it as done), and stores the result. Or maybe the result is just the data? The requirement says `get_result(job_id: str) -> dict | None`. I'll store results in a dictionary.

Wait, the prompt says "Implement a basic job queue in Python." It doesn't specify how processing happens. I'll just add a `process()` method that processes the first job in the queue, or maybe `process_all()`. Actually, I can just make it so that `add_job` adds to a list, and `get_result` returns the result if processed. I'll add a `process()` method.

Let's think about typical implementations. Often, a job queue has a `submit` method and a `run` or `process` method. I'll add `process()` that processes the next job. To make it useful, I'll store jobs as objects or dicts with status.

Actually, the prompt might just want a simple FIFO queue with a dictionary for results. I'll implement:
- `__init__`: `self.queue = []`, `self.results = {}`
- `add_job`: append to queue, return job_id
- `get_result`: return from results
- `process`: pop from queue, simulate processing (or just mark as done), store result. Maybe the result is just `{"status": "completed", "data": data}`.

Wait, the example shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
It doesn't show how processing is triggered. I'll add a `process()` method. Or maybe I should just make `get_result` block? No.
I'll add a `process()` method that processes the next job. To keep it simple, I'll just mark jobs as completed and store a dummy result, or maybe the result is just the input data. Actually, it's better to allow a processing function, but the prompt doesn't ask for it. I'll just simulate processing by storing `{"status": "completed", "data": data}`.

Wait, maybe the prompt expects a background thread? "The queue should store jobs internally until they are processed". I'll stick to synchronous processing for simplicity, but add a `process()` method. Alternatively, I can make `get_result` just return the result if it exists.

Let's re-read carefully: "Implement a basic job queue in Python."
Requirements:
1. `add_job` and `get_result`
2. FIFO
3. Store internally
4. Unique job_id returned

I'll implement:
```python
from typing import Dict, List, Optional

class JobQueue:
    def __init__(self):
        self._queue: List[dict] = []
        self._results: Dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)

    def process(self) -> Optional[str]:
        if not self._queue:
            return None
        job = self._queue.pop(0)
        # Simulate processing
        result = {"status": "completed", "data": job["data"]}
        self._results[job["job_id"]] = result
        return job["job_id"]
```

But the prompt doesn't mention `process()`. Maybe it's implied that the queue processes jobs automatically? Or maybe I should just provide the class with the two methods, and assume processing is external? The prompt says "The queue should store jobs internally until they are processed". It doesn't specify the processing mechanism. I'll add a `process()` method for completeness, or maybe `process_all()`.

Actually, many simple queue implementations just have `put` and `get`. But here it's `add_job` and `get_result`. I'll stick to the two methods plus a `process()` method. Or maybe I should make it so that `get_result` doesn't need an explicit process step? No, that doesn't make sense.

Wait, maybe the user expects a class that simulates processing when `get_result` is called? Unlikely.
I'll just add `process()` and `process_all()` methods. Or maybe I'll just implement exactly what's asked, and add a `process()` method for completeness.

Let's think about standard coding interview questions. They often just want the class with `__init__`, `add_job`, `get_result`, and maybe `process`. I'll provide a clean implementation.

Actually, I can make `get_result` return `None` if not processed, as specified.
I'll add a `process()` method that processes the next job. To keep it simple, I'll just store the result as `{"status": "completed", "data": data}`.

Wait, the prompt says "Each job has a unique job_id that is returned when added". The signature is `add_job(job_id: str, data: dict) -> str`. So the caller provides the job_id, or maybe I should generate one if not provided? The type hint says `job_id: str`, so it's required. I'll just use it.

Let's write it out.

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

class JobQueue:
    def __init__(self):
        self._queue: List[dict] = []
        self._results: Dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)

    def process(self) -> Optional[str]:
        if not self._queue:
            return None
        job = self._queue.pop(0)
        # Simulate job processing
        result = {"status": "completed", "data": job["data"]}
        self._results[job["job_id"]] = result
        return job["job_id"]
```

Is there anything else? The prompt says "Write only the Python code, no explanations."
I'll remove comments to be safe, or keep them minimal.
I should also consider if `get_result` should return `None` or raise an error. It says `-> dict | None`, so `None` is fine.
I'll use `typing.Optional` or `dict | None` (Python 3.10+). I'll stick to `Optional[dict]` for broader compatibility, or just `dict | None` since the prompt uses it. I'll use `from typing import Optional, Dict, List`.

Wait, the prompt uses `dict | None` in the requirement. I'll use that.
I'll make sure the code matches exactly.

One thing: The example shows `queue.add_job("job1", {"task": "process_data"})`. The first argument is `"job1"`, which is the `job_id`. So the signature matches.

I'll add a `process()` method. It's standard.
Alternatively, maybe the queue should process automatically in a thread? The prompt says "basic job queue", so synchronous is fine.

I'll write the code now.
To be safe, I'll include `process()` and `process_all()` or just `process()`. I'll stick to `process()`.

Actually, maybe the user expects `get_result` to just work after `add_job`? No, that contradicts "until they are processed".
I'll provide the class with `add_job`, `get_result`, and `process`.

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

class JobQueue:
    def __init__(self):
        self._queue: List[dict] = []
        self._results: Dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)

    def process(self) -> Optional[str]:
        if not self._queue:
            return None
        job = self._queue.pop(0)
        self._results[job["job_id"]] = {"status": "completed", "data": job["data"]}
        return job["job_id"]
```

Wait, `Optional[dict]` is fine. I'll use `dict | None` to match the prompt.
I'll also add type hints properly.

One minor point: The prompt says `add_job(job_id: str, data: dict) -> str`. It returns `job_id`.
The prompt says `get_result(job_id: str) -> dict | None`.
I'll use `from typing import Optional` or just `dict | None`. I'll stick to `dict | None`.

Let's check if there's any ambiguity about "unique job_id that is returned when added". It might mean the method should generate one if not provided, but the signature has `job_id: str` as a parameter. I'll assume the caller passes it, or maybe I should generate it if `job_id` is not provided? But the signature says `job_id: str`, so it's required. I'll keep it as is.

Actually, to be robust, I could ignore the passed `job_id` and generate one, but that violates the signature. I'll just use the passed `job_id`.

I think this is sufficient.
I'll output only the code.
One thing: I'll make sure imports are included.
I'll write it cleanly.

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

class JobQueue:
    def __init__(self):
        self._queue: List[dict] = []
        self._results: Dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)

    def process(self) -> Optional[str]:
        if not self._queue:
            return None
        job = self._queue.pop(0)
        self._results[job["job_id"]] = {"status": "completed", "data": job["data"]}
        return job["job_id"]
```

Wait, `Optional[dict]` vs `dict | None`. I'll use `dict | None` to match the prompt exactly, though `Optional` is more compatible. I'll stick to `dict | None` as requested. Python 3.10+ supports it. I'll assume modern Python.

Actually, I'll just use `dict | None` in type hints.
I'll remove comments to keep it concise.
All good.
Output matches requirements.
Proceed. 
Let's double check the prompt: "Write only the Python code, no explanations."
I will output exactly the code.
One thing: `get_result` should return `dict | None`. I'll use `-> dict | None`.
I'll add `from typing import Dict, List` if needed, but `dict` and `list` are built-in. I'll just use standard typing.
Actually, `dict | None` is fine without imports in 3.10+. I'll just use it.
I'll write it out. 
Done. 
Self-Correction/Refinement during thought: 
Should `process` be part of the class? The prompt doesn't explicitly ask for it, but it's necessary to fulfill "until they are processed". I'll include it. If the user wants automatic processing, they didn't ask for threads. Synchronous `process()` is standard for "basic job queue".
I'll also add `process_all()` just in case, but `process()` is enough.
I'll stick to the code above.
Ready. 
Output matches. 
Proceeds. 
[Output Generation] -> *Proceeds*
```python
from typing import Dict, List, Optional

class JobQueue:
    def __init__(self):
        self._queue: List[dict] = []
        self._results: Dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)

    def process(self) -> Optional[str]:
        if not self._queue:
            return None
        job = self._queue.pop(0)
        self._results[job["job_id"]] = {"status": "completed", "data": job["data"]}
        return job["job_id"]
```
Wait, `Optional[dict]` vs `dict | None`. I'll change to `dict | None` to strictly match the prompt's type hint style.
Also, I'll remove `from typing import ...` if not strictly necessary, but it's good practice. I'll keep it.
Actually, `dict | None` is valid in Python 3.10+. I'll use it.
Final code:
```python
class JobQueue:
    def __init__(self):
        self._queue: list[dict] = []
        self._results: dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

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

    def process(self) -> str | None:
        if not self._queue:
            return None
        job = self._queue.pop(0)
        self._results[job["job_id"]] = {"status": "completed", "data": job["data"]}
        return job["job_id"]
```
This uses built-in generics for typing, which is Python 3.9+. Safe enough.
I'll output this. All requirements met. FIFO is handled by list pop(0). Stores internally. Returns job_id. Handles result retrieval.
Done. 
Output matches response. 
Proceeds. 
[Final Check]
- `JobQueue` class? Yes.
- `add_job(job_id: str, data: dict) -> str`? Yes.
- `get_result(job_id: str) -> dict | None`? Yes.
- FIFO? Yes, `pop(0)`.
- Stores internally? Yes, `_queue` and `_results`.
- Unique job_id returned? Yes.
- Only Python code? Yes.
All good. 
Output matches. 
*Self-Correction/Note during generation*: I should make sure `process` is clearly defined. The prompt doesn't specify it, but it's necessary. I'll include it. If the prompt implies automatic processing, it would say so. Basic queue usually needs a `process` or `run` method. I'll keep it.
One minor thing: `job_id` in `add_job` is passed by the caller, so uniqueness is caller's responsibility, or I could generate one. The prompt says "Each job has a unique job_id that is returned when added". This might mean I should generate it if not provided, but the signature has `job_id: str`. I'll assume the caller provides it, or I'll just use it as is. It's fine.
I'll output the code. 
Done. 
[Output Generation] -> *Proceeds*

</reasoning_content>

<content>
```python
class JobQueue:
    def __init__(self):
        self._queue: list[dict] = []
        self._results: dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

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

    def process(self) -> str | None:
        if not self._queue:
            return None
        job = self._queue.pop(0)
        self._results[job["job_id"]] = {"status": "completed", "data": job["data"]}
        return job["job_id"]
```
</content>