<reasoning_content>
*   Task: Implement a basic job queue in Python.
    *    Class name: `JobQueue`.
    *    Required methods:
        *   `add_job(job_id: str, data: dict) -> str`
        *   `get_result(job_id: str) -> dict | None`
    *    Requirements:
        *   FIFO (First-In-First-Out) order for processing.
        *   Store jobs internally until processed.
        *   Unique `job_id` (though the example shows the user providing the ID, the requirement says "Each job has a unique job_id that is returned when added", suggesting the user *might* provide it, or the system might generate it. Looking at the example: `queue.add_job("job1", ...)` implies the user provides it. Wait, the requirement says "Each job has a unique job_id that is returned when added". If the user provides it, it's already there. If I'm supposed to generate it, the signature changes. Let's look at the example again: `job_id = queue.add_job("job1", ...)` suggests the user provides the string, but the requirement "Each job has a unique job_id that is returned" usually implies generation. However, since the signature takes `job_id` as an input, I will treat it as input and ensure it's unique/stored).
    *    Actually, looking closely: `add_job(job_id: str, data: dict)`. If the user passes "job1", I return "job1".
    *    I need a way to "process" the jobs. Since the prompt asks for a "queue", but doesn't specify a background worker, I should probably have a mechanism to process them or at least a way to store results.
    *    The example shows `queue.get_result("job1")`. To make this work, there must be a mechanism to mark a job as finished. Since the prompt doesn't specify a `process()` method but says "Jobs should be processed in FIFO", I'll implement a simple processing logic or a way to simulate it.
    *    Wait, the requirements are minimal. If I just have `add_job` and `get_result`, how does a job get "processed"? Usually, a job queue has a worker. Since the prompt doesn't ask for a worker thread/process, I'll simulate the "processing" logic or provide a way to trigger it.
    *    Actually, let's look at the requirements again.
        1. `add_job`: Adds to queue.
        2. `get_result`: Gets result of completed job.
        3. FIFO order.
        4. Internal storage.
    *    To make `get_result` work, there must be a state where a job goes from "pending" to "completed".
    *    I'll use a `collections.deque` for the FIFO queue and a dictionary to store results.

    *   `self.queue`: a deque of `(job_id, data)`.
    *   `self.results`: a dict mapping `job_id` to result data.
    *   Since there's no `process()` method in the requirements, but it says "Jobs should be processed in FIFO", I'll provide a simple internal `_process_next_job()` or similar logic that is called whenever a job is added or results are checked? No, that's messy.
    *    Maybe I should add a `process_next()` method even if not explicitly requested to satisfy the "processed in FIFO" requirement? Or maybe the jobs are "processed" immediately upon adding if I simulate it?
    *    Let's look at the example: `queue.add_job(...)`, `queue.get_result(...)`.
    *    If I call `add_job`, it goes into the queue. If I want `get_result` to return something, someone has to process it.
    *    I'll implement an internal `_process_jobs()` method that processes all pending jobs in the queue. Or, I'll assume the prompt implies that the queue *manages* the processing.
    *    Revised plan:
        *   `add_job`: puts `(job_id, data)` into a deque.
        *   `get_result`: checks if `job_id` is in `results`. If not, it might try to process the next job in the queue until it finds the result or the queue is empty.
        *    Actually, a simpler interpretation: The `JobQueue` class has an internal worker or a `process` method. But the requirement only lists two methods.
        *    Let's try to make it so that `add_job` adds to a queue, and `get_result` triggers processing of the queue until the result for that ID is found.

    *    Wait, "Jobs should be processed in FIFO order". If I just process them on demand in `get_result`, that satisfies the requirement.

    *    Let's refine:
        *   `self._queue = deque()`
        *   `self._results = {}`
        *   `add_job(job_id, data)`: `self._queue.append((job_id, data)))`, return `job_id`.
        *   `get_result(job_id)`:
            While `self._queue` is not empty:
                Pop first item `(jid, data)`.
                "Process" it (e.g., `self._results[jid] = {"result": "success", "data": data}`)
            Check if `job_id` in `self._results`. Return it.

    *    Wait, if I process *everything* every time `get_result` is called, that's inefficient but technically correct for a "basic" implementation.

    *    Requirement 4: "Each job has a unique job_id that is returned when added". If the user provides `job1`, I should check if it's already there? The prompt doesn't specify error handling, so I'll assume unique IDs are provided by the caller or I handle them.

    *    Let's add a simple processing logic.

    *    `collections.deque` for FIFO.
    *    `dict` for results.

    *    Let's write the code.

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

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

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

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

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

Wait, the prompt says "Write only the Python code, no explanations."

One small detail: "Jobs should be processed in FIFO order". If `get_result` triggers processing of the whole queue every time, it is indeed FIFO.

Actually, another way to interpret "Jobs should be processed in FIFO" is that there's a background process. But I can't easily do threading/multiprocessing in a "basic" code block without extra imports/overhead. I will stick to the simplest functional implementation.

One more thing: "Each job has a unique job_id that is returned when added".
 If I check for uniqueness:
 `if job_id in self._results or any(jid for jid, _ in self._queue): raise ValueError`.
 But the prompt doesn't require error handling.

 Let's look at the example again.
 `job_id = queue.add_job("job1", {"task": "process_data"})`
 `result = queue.get_result("job1")`
 In this example, `get_result` is called immediately after `add_job`. If I process on demand, `get_result` will return the result.

 I'll refine the `_process_queue` slightly to ensure it only processes what is in the queue.

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

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

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

    def _process_next(self):
        if self._queue:
            job_id, data = self._queue.popleft()
            # Simulate work
            self._results[job_id] = {"result": "success", "input_data": data}

    def get_result(self, job_id: str) -> dict | None:
        # Process jobs until the queue is empty or we find the result
        # To maintain FIFO, we must process the queue in order.
        while self._queue:
            self._process_next()
            if job_id in self._results:
                break
        
        return self._results.get(job_id)
```
Wait, if I call `get_result` for "job2" but "job1" is still in the queue, I must process "job1" first to maintain FIFO. My `while` loop does exactly that.

Actually, the requirement says "Jobs should be processed in FIFO order". It doesn't say "process until you find this specific ID". But usually, a queue works that way.

Let's simplify. `get_result` should probably just trigger processing of the current head of the queue until the requested ID is reached or queue is empty.

Actually, I'll just process the whole queue whenever `get_result` is called for simplicity, as it still preserves FIFO order.

One final check: `dict | None` requires `from __future__ import annotations` or Python 3.10+. I'll just use `Optional[dict]` or standard `dict | None` if I assume modern Python. The prompt uses `dict | None`, so I will use that.

```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            jid, data = self._queue.popleft()
            # Simulate processing
            self._results[jid] = {"status": "completed", "data": data}
            if jid == job_id:
                break
        
        return self._results.get(job_id)
```
Wait, if `job_id` is "job2" and the queue is `["job1", "job2"]`, the loop pops `job1`, processes it, then pops `job2`, processes it, then `jid == job_id` matches, and returns `self._results["job2"]`. This is correct.

If `job_id` is "job3" (not in queue), it clears the whole queue and returns `None`. Correct.

One detail: "The queue should store jobs internally until they are processed". My code does this via `self._queue`.

Final check on signature:
`add_job(job_id: str, data: dict) -> str`
`get_result(job_id: str) -> dict | None`

One small thing: `dict | None` is Python 3.10 syntax.

```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            curr_id, curr_data = self._queue.popleft()
            # Simulated processing logic
            self._results[curr_id] = {"status": "completed", "data": curr_data}
            
            if curr_id == job_id:
                break
                
        return self._results.get(job_id)

```
Actually, I'll make the processing slightly more generic so it doesn't look like a stub.

```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            current_id, current_data = self._queue.popleft()
            # Perform processing logic here
            self._results[current_id] = {"result": "success", "input": current_data}
            
            if current_id == job_id:
                break
                
        return self._results.get(job_id)
```
Wait, if a user calls `get_result("job1")` then `get_result("job2")`, does "job2" get processed? 
If I use the `while` loop:
1. `get_result("job1")`: 
   - pops `job1`, processes it.
   - `current_id == "job1"` is true. Break.
   - returns result of `job1`.
2. `get_result("job2")`:
   - `self._queue` is empty.
   - returns `None` (because `job2` was never in the queue or processed).

Wait! If `job2` was in the queue behind `job1`, and the user asked for `job1` first, `job1` is processed. Then the user asks for `job2`. The queue is empty? No, the loop `while self._queue` would run. But in step 1, if the user asked for `job2` but `job1` was in front, `job2` would be processed *and* `job1` would be processed.

This means `get_result` for a later job forces the processing of all preceding jobs. This satisfies FIFO.

But what if `get_result("job1")` is called, then `get_result("job2")` is called? 
If `job2` was already processed during the call to `get_result("job1")`, it's already in `self._results`.
If it wasn't, it would be processed now.

Actually, there's a bug in my logic:
If `job1` and `job2` are in queue.
User calls `get_result("job2")`.
Loop:
- `curr_id` is `job1`. Processes `job1`.
- `curr_id == "job2"` is false.
- Loop continues.
- `curr_id` is `job2`. Processes `job2`.
- `curr_id == "job2"` is true. Break.
- Return result of `job2`.
This is correct.

User calls `get_result("job1")`.
- `curr_id` is `job1`. Processes `job1`.
- `curr_id == "job1"` is true. Break.
- Return result of `job1`.
Now `job2` is still in `self._queue`.

User calls `get_result("job2")`.
- `curr_id` is `job2`. Processes `job2`.
- `curr_id == "job2"` is true. Break.
- Return result of `job2`.

This works perfectly and satisfies all requirements.

Final check: "Each job has a unique job_id that is returned when added". 
The signature `add_job(job_id: str, data: dict) -> str` implies the user provides the ID. If I want to be safe, I could check if it's unique, but the prompt doesn't ask for it.

```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            current_id, current_data = self._queue.popleft()
            # Simulate processing logic
            self._results[current_id] = {"status": "completed", "data": current_data}
            
            if current_id == job_id:
                break
                
        return self._results.get(job_id)
```
One tiny detail: `dict | None` is available in 3.10+. I'll ensure the code is clean.

```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            current_id, current_data = self._queue.popleft()
            # Simulate the processing of the job
            self._results[current_id] = {"status": "completed", "data": current_data}
            
            if current_id == job_id:
                break
        
        return self._results.get(job_id)
```

Wait, one detail: "The queue should store jobs internally until they are processed".
My `self._queue` stores them until they are popped. Correct.

Final check on requirements:
1. `JobQueue` class with `add_job` and `get_result`. (Yes)
2. FIFO order. (Yes, via `deque.popleft()`)
3. Store jobs internally until processed. (Yes)
4. Unique `job_id` returned. (Yes)

One thought: Does the prompt imply I should generate the ID?
 "Each job has a unique job_id that is returned when added".
 If I generate it: `add_job(data: dict) -> str`.
 But the prompt signature is `add_job(job_id: str, data: dict) -> str`.
 Since the signature is provided, I must accept `job_id` as an argument. If I accept it, then the "unique" part is a constraint on the input or a requirement that I verify. I'll just assume the caller provides unique IDs as per the example `job_id = queue.add_job("job1", ...)` where "job1" is clearly chosen by the user.

```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            current_id, current_data = self._queue.popleft()
            # Simulate processing logic
            self._results[current_id] = {"status": "completed", "data": current_data}
            
            if current_id == job_id:
                break
        
        return self._results.get(job_id)
```
Wait, the return type `dict | None` is explicitly requested. I will use that.

Final check on "Write only the Python code, no explanations."

```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            current_id, current_data = self._queue.popleft()
            # Simulate job processing
            self._results[current_id] = {"status": "completed", "data": current_data}
            
            if current_id == job_id:
                break
                
        return self._results.get(job_id)
```
</reasoning_content>

<content>
```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = 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:
        while self._queue:
            current_id, current_data = self._queue.popleft()
            
            # Simulate the processing of the job
            self._results[current_id] = {
                "status": "completed",
                "input_data": current_data
            }
            
            # If we reached the requested job, stop processing the queue
            if current_id == job_id:
                break
                
        return self._results.get(job_id)
```
</content>