Optimize fetch_all_users

The optimization replaces sequential async execution with concurrent execution using `asyncio.gather()`. 

**Key Change:**
- **Original**: Fetches users one-by-one in a loop with `await fetch_user(user_id)`, blocking until each completes
- **Optimized**: Uses `asyncio.gather(*(fetch_user(user_id) for user_id in user_ids))` to launch all fetch operations concurrently

**Why This Creates a Speedup:**
The original code suffers from "false serialization" - it waits for each 0.0001-second database call to complete before starting the next one. With N users, total time is roughly N × 0.0001 seconds. The optimized version launches all fetch operations simultaneously, so total time becomes approximately max(fetch_times) ≈ 0.0001 seconds regardless of list size.

**Performance Impact:**
- **Runtime improvement**: 785% speedup (302ms → 34.1ms)
- **Throughput improvement**: 558% increase (1,862 → 12,250 operations/second)

The line profiler shows the optimization eliminates the expensive sequential loop overhead - the original `fetch_all_users` spent 96.3% of time waiting on individual fetch calls, while the optimized version completes in a single concurrent operation.

**Test Case Performance:**
The optimization excels with larger datasets - test cases with 100-500 users show the most dramatic improvements since they maximize the concurrency benefit. Small lists (1-10 users) still benefit but see smaller gains due to the fixed asyncio.sleep overhead.

This pattern is particularly valuable for I/O-bound operations like database queries, API calls, or file operations where the underlying operations can run independently.

Author: codeflash-ai-dev[bot]

src/asynchrony/various.py

@@ -23,8 +23,4 @@ async def fetch_user(user_id: int) -> dict:
 
 
 async def fetch_all_users(user_ids: list[int]) -> list[dict]:
-    users = []
-    for user_id in user_ids:
-        user = await fetch_user(user_id)
-        users.append(user)
-    return users
+    return await asyncio.gather(*(fetch_user(user_id) for user_id in user_ids))