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

Wait, the requirements mention "After processing..." in the example, but there's no explicit method for processing jobs mentioned in the requirements. The requirements only specify `add_job` and `get_result`. I should probably include a method to process jobs, or assume the processing happens externally, but the queue should store jobs internally until processed. Actually, the requirement says "The queue should store jobs internally until they are processed". This implies there might be a processing mechanism, or perhaps I should add a `process_jobs()` method or similar. But the requirements only explicitly list `add_job` and `get_result`. I'll stick to what's explicitly requested, but I might need a way to simulate processing or just store the state. Actually, for a basic queue, I can just store jobs in a list and process them in order when needed, or just keep them as pending/completed.

Let's re-read carefully: "Jobs should be processed in FIFO (First-In-First-Out) order", "The queue should store jobs internally until they are processed". It doesn't specify how processing happens. I'll add a simple `process_next()` method or just assume the user will call something, but to keep it simple and match the example, I'll just store the jobs and maybe add a `process_jobs()` method, or I can just make `get_result` handle pending jobs? No, that's not right.

Actually, a simpler interpretation: The queue stores jobs. When `add_job` is called, it adds to a list. I'll add a `process_jobs()` method that processes them in FIFO order and stores results. Or maybe the processing is simulated. Since it's a "basic job queue", I'll implement a simple in-memory queue using `collections.deque` for FIFO, a dictionary for results, and a dictionary for pending jobs. I'll also add a `process()` method to actually process them, or just leave it as storing state.

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 happens. I'll implement a `process()` method that simulates processing (or just marks jobs as completed with a dummy result), or I can just store the jobs and let the user process them. But to satisfy "processed in FIFO order", I should probably process them in order when a method is called, or add a `process_jobs()` method.

Actually, I'll just implement the queue with a list/deque for pending jobs, a dict for results, and a `process()` method that processes all pending jobs in FIFO order and stores results with a simple transformation (e.g., `{"status": "completed", "data": job_data}`). Or I can just make `get_result` return the job data if not processed yet? No, requirement says "Get the result of a completed job".

Let's stick to the simplest valid implementation:
- Use `collections.deque` for FIFO queue
- Use `dict` for storing jobs and results
- `add_job` appends to deque, stores job data, returns ID
- `get_result` returns result if completed, else None
- I'll add a `process_jobs()` method that processes them in FIFO order and stores results. Or maybe the processing is external, but the queue should just manage state. Actually, I'll just implement a `process()` method that simulates processing, or I can just leave it without processing method if not required, but that contradicts "until they are processed". I'll add `process()` for completeness.

Wait, the prompt says "Write only the Python code, no explanations."
I'll implement it cleanly.

```python
import collections

class JobQueue:
    def __init__(self):
        self._queue = collections.deque()
        self._jobs = {}
        self._results = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append(job_id)
        self._jobs[job_id] = data
        return job_id

    def process_jobs(self):
        while self._queue:
            job_id = self._queue.popleft()
            data = self._jobs[job_id]
            # Simulate processing
            self._results[job_id] = {"status": "completed", "data": data}
            del self._jobs[job_id]

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

But the requirements don't ask for `process_jobs`. Maybe I should just process jobs on demand or assume external processing? The example comment says "# After processing...". I'll add a `process()` method to make it functional, or I can just process in `add_job`? No, FIFO order implies they wait.

Actually, a simpler approach: just store pending jobs in a list, and provide a `process()` method. Or maybe the user expects the queue to just store and retrieve, and processing is simulated externally. I'll stick with `process_jobs()` or `process()`.

Wait, maybe I should just implement exactly what's asked and add a simple `process()` method to demonstrate FIFO. Or I can make `get_result` trigger processing? No.

Let's re-read: "Jobs should be processed in FIFO (First-In-First-Out) order". This is a requirement for the queue's behavior. I'll add a `process()` method that processes all pending jobs in order.

Actually, I can just implement it without an explicit process method if I assume the user will call something, but it's better to include it. Or I can just process jobs when `get_result` is called? No.

I'll add `process_jobs()` method. But to be strictly compliant with "Write only the Python code", I'll provide the class with the required methods plus a necessary `process()` method to make it work as described.

Alternatively, maybe the queue is just a data structure that holds jobs, and processing is external. The requirement "Jobs should be processed in FIFO order" might just mean that when they are processed, they come out in FIFO order. I'll stick with `deque`.

Let's refine:
```python
import collections

class JobQueue:
    def __init__(self):
        self._pending = collections.deque()
        self._jobs = {}
        self._results = {}

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

    def process_jobs(self):
        while self._pending:
            job_id = self._pending.popleft()
            data = self._jobs.pop(job_id)
            self._results[job_id] = {"status": "completed", "data": data}

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

Wait, the type hint `dict | None` requires Python 3.10+. I'll use `Optional[dict]` or keep `dict | None` as requested. The prompt uses `dict | None`, so I'll keep it.

Actually, I can make it even simpler. The prompt says "Implement a basic job queue". I'll just provide the class.

One thing: `get_result` should return `dict | None`. I'll use `typing.Optional` or just `dict | None`. I'll stick to `dict | None` as in the prompt.

Let's consider if processing should be automatic or manual. I'll add a `process()` method. But maybe the prompt expects the queue to just store and retrieve, and processing is simulated by just marking as done? I'll add `process_jobs()` to be safe.

Actually, I can implement it so that `get_result` returns the job data if it's still pending? No, requirement says "completed job".

I'll just provide the class with `add_job`, `get_result`, and a `process()` method. To be concise:

```python
import collections
from typing import Optional

class JobQueue:
    def __init__(self):
        self._queue = collections.deque()
        self._jobs = {}
        self._results = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append(job_id)
        self._jobs[job_id] = data
        return job_id

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

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

Wait, `dict | None` is valid in Python 3.10+. I'll keep it as is.
The prompt says "Write only the Python code, no explanations."
I'll output exactly that.

One minor thing: `typing.Optional` is more compatible, but I'll stick to the prompt's type hint style. I'll just use `dict | None`.

Actually, I can make `process_jobs` named `process` for brevity. Or I can just process jobs on demand? No.

Let's think if there's a simpler way that matches typical coding interview expectations. Often, they just want the queue structure. I'll add `process()` method.

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 `process()` being called. Maybe the processing is simulated or external. I'll just implement `process_jobs()` and maybe call it in the example? No, I'll just provide the class. The user can call `process_jobs()` as needed.

Actually, I'll make `process_jobs()` a method. It's fine.

Let's ensure it meets all requirements:
1. `JobQueue` class with `add_job` and `get_result` - yes
2. FIFO order - `collections.deque` ensures this
3. Stores jobs internally until processed - yes, `_jobs` dict and `_queue` deque
4. Unique job_id returned - yes

I'll write it out cleanly.

One thing: `get_result` type hint in prompt is `dict | None`. I'll use that.
I'll avoid imports if possible, but `collections` is standard. I can just use a list for queue, but `deque` is better for FIFO. I'll stick with `collections.deque`.

Final code:
```python
import collections

class JobQueue:
    def __init__(self):
        self._pending = collections.deque()
        self._jobs = {}
        self._results = {}

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

    def process_jobs(self):
        while self._pending:
            job_id = self._pending.popleft()
            data = self._jobs.pop(job_id)
            self._results[job_id] = {"status": "completed", "data": data}

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

Wait, should `get_result` return `None` or raise an error if not completed? Prompt says `-> dict | None`, so returning `None` is fine.

Is there any ambiguity about "processed"? I'll assume `process_jobs` is sufficient. If the user expects automatic processing, they didn't specify. I'll keep it explicit.

Actually, I can make `process_jobs` optional or just name it `process`. I'll stick with `process_jobs`.

One more check: The prompt says "Write only the Python code, no explanations." I will output just the code block.

I'll make sure the type hints match exactly. `dict | None` is fine.

Code looks solid. I'll output it.
Wait, maybe I should use `typing.Optional[dict]` for broader compatibility, but the prompt uses `dict | None`, so I'll keep it.

I'll remove the `process_jobs` if it's not strictly required, but it's needed to satisfy "until they are processed". I'll keep it.

Actually, I can implement it so that `get_result` processes jobs if needed? No, that mixes concerns.

I'll just provide the class as is. It's clean and meets requirements.
One minor adjustment: I'll add `from typing import Optional` and use `Optional[dict]` to be safe, or just keep `dict | None`. I'll stick to `dict | None` as requested.

Final check of the prompt: "Implement a basic job queue in Python."
Requirements list methods. I'll include exactly those plus `process_jobs` to make it functional.

I think it's good.
Output matches request.
Proceed. 
I will wrap it in a code block as is standard, but the prompt says "Write only the Python code, no explanations." so I'll just output the raw code.
Actually, I'll output just the code block.
Done. 
Let's generate. 
Wait, should I include the example usage? The prompt shows it, but says "Write only the Python code". I'll just provide the class implementation. If they want the example, they already have it. I'll stick to the class.

One thing: `dict | None` might cause syntax error in Python < 3.10. I'll use `typing.Optional[dict]` to be safe, or just keep `dict | None` as it's modern. I'll keep `dict | None`.

All good.
Output matches. 
Proceeds. 
[Self-Correction/Refinement during thought]
Actually, to be strictly compliant with "Write only the Python code", I'll just output the class. I'll make sure imports are included.
I'll use `collections.deque` for FIFO.
The code:
```python
import collections

class JobQueue:
    def __init__(self):
        self._queue = collections.deque()
        self._jobs = {}
        self._results = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append(job_id)
        self._jobs[job_id] = data
        return job_id

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

    def get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id)
```
This looks correct and complete. I'll output it. 
One detail: `dict | None` is valid in 3.10+. I'll keep it. If needed, I can change to `typing.Optional[dict]`, but it's fine.
I'll output exactly this.✅
Done. 
Output matches response. 
Proceeds. 
[Final Check]
- Class `JobQueue`? Yes.
- `add_job(job_id: str, data: dict) -> str`? Yes.
- `get_result(job_id: str) -> dict | None`? Yes.
- FIFO? `deque` ensures it.
- Stores internally until processed? Yes, `_jobs` and `_queue` hold them.
- Unique job_id returned? Yes.
- Only Python code? Yes.
All requirements met.
Output matches. 
Proceeds. 
[Output Generation] -> *Self-Correction/Note during generation prep*: I should make sure the type hint matches exactly. I'll use `from typing import Optional` and `Optional[dict]` to avoid any version issues, but the prompt uses `dict | None`, so I'll stick to that. It's fine.
I'll output the code now. 
```python
import collections

class JobQueue:
    def __init__(self):
        self._pending = collections.deque()
        self._jobs = {}
        self._results = {}

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

    def process_jobs(self):
        while self._pending:
            job_id = self._pending.popleft()
            data = self._jobs.pop(job_id)
            self._results[job_id] = {"status": "completed", "data": data}

    def get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id)
```
Looks good. Output matches. 
Proceeds. 
[Final Output Generation] (matches the refined code)
Note: I'll remove the `process_jobs` method if it's not strictly requested, but it's necessary for the queue to actually process jobs. The prompt says "Jobs should be processed in FIFO order", implying a mechanism is needed. I'll keep it. If the user wanted it purely as a data structure, they wouldn't mention processing. It's fine.
I'll output exactly the code.
Done. 
[Output] -> *Proceeds*

</reasoning_content>

<content>
```python
import collections

class JobQueue:
    def __init__(self):
        self._pending = collections.deque()
        self._jobs = {}
        self._results = {}

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

    def process_jobs(self):
        while self._pending:
            job_id = self._pending.popleft()
            data = self._jobs.pop(job_id)
            self._results[job_id] = {"status": "completed", "data": data}

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