type: session

harness: optiq-lab

name: Create a Python script that generates a 10MB CSV file of random integers and then measures how long it takes to sort tha

mode: chat

domain: benchmarking and performance measurement


type: message

role: system

content:
You are OptiQ Lab, running on the user's own machine. You have three tools: web_search for looking things up, python for computation and data work, and terminal for shell one-liners.

The python and terminal tools run in a container with no network and ONLY the Python standard library. numpy, pandas, scipy, sklearn and matplotlib are not installed, so use math, statistics, json, csv, re, itertools, collections and random instead.

Every call gets a FRESH sandbox. Nothing persists between calls: files you write, variables you define and imports you make are all gone by the next one. So do the whole job in a single call and print the result. Do not write a file in one call expecting to read it in the next.

If a call fails, read the error and change approach rather than repeating it. Once you have the answer, state it plainly and stop calling tools.


role: user

content: Create a Python script that generates a 10MB CSV file of random integers and then measures how long it takes to sort that list using the built-in sorted() function.


role: assistant

content: I'll create the script and verify it works in the sandbox.

python

code:
import random, time, os, csv

TARGET_SIZE = 10 * 1024 * 1024  # 10 MB
FILENAME = "random_ints.csv"

def generate_csv(filename, target_size):
    """Generate a CSV of random integers until the file reaches ~target_size bytes."""
    with open(filename, "w", newline="") as f:
        writer = csv.writer(f)
        size = 0
        count = 0
        while size < target_size:
            # Write a chunk of rows at a time for efficiency
            chunk = [random.randint(-2_000_000_000, 2_000_000_000) for _ in range(10_000)]
            for val in chunk:
                f.write(str(val) + "\n")
                count += 1
            size = os.path.getsize(filename)
    return count

def main():
    start = time.perf_counter()
    n = generate_csv(FILENAME, TARGET_SIZE)
    gen_time = time.perf_counter() - start

    file_size = os.path.getsize(FILENAME)

    # Read the integers back
    with open(FILENAME, "r") as f:
        data = [int(line.strip()) for line in f]

    print(f"Generated {n:,} integers")
    print(f"File size: {file_size/1024/1024:.2f} MB")
    print(f"Generation time: {gen_time:.3f}s")

    # Time the sort
    t0 = time.perf_counter()
    sorted_data = sorted(data)
    sort_time = time.perf_counter() - t0

    print(f"Sort time (sorted()): {sort_time:.3f}s")
    print(f"First 5 sorted: {sorted_data[:5]}")
    print(f"Last 5 sorted: {sorted_data[-5:]}")
    # sanity check
    assert sorted_data == sorted(data)

if __name__ == "__main__":
    main()


role: tool

content:
sandbox: container  rc=0
--- stdout ---
Generated 960,000 integers
File size: 10.02 MB
Generation time: 0.897s
Sort time (sorted()): 0.435s
First 5 sorted: [-1999993687, -1999992079, -1999982619, -1999979446, -1999978135]
Last 5 sorted: [1999981107, 1999981425, 1999985751, 1999995778, 1999999885]

--- stderr ---


content:
The script works correctly. Here's the complete, ready-to-run Python script:

```python
import random, time, os, csv

TARGET_SIZE = 10 * 1024 * 1024  # 10 MB
FILENAME = "random_ints.csv"

def generate_csv(filename, target_size):
    """Generate a CSV of random integers until the file reaches ~target_size bytes."""
    with open(filename, "w", newline="") as f:
        size = 0
        count = 0
        while size < target_size:
            # Write a chunk of rows at a time for efficiency
            chunk = [random.randint(-2_000_000_000, 2_000_000_000) for _ in range(10_000)]
            for val in chunk:
                f.write(str(val) + "\n")
                count += 1
            size = os.path.getsize(filename)
    return count

def main():
    start = time.perf_counter()
    n = generate_csv(FILENAME, TARGET_SIZE)
    gen_time = time.perf_counter() - start

    file_size = os.path.getsize(FILENAME)

    # Read the integers back
    with open(FILENAME, "r") as f:
        data = [int(line.strip()) for line in f]

    print(f"Generated {n:,} integers")
    print(f"File size: {file_size/1024/1024:.2f} MB")
    print(f"Generation time: {gen_time:.3f}s")

    # Time the sort
    t0 = time.perf_counter()
    sorted_data = sorted(data)
    sort_time = time.perf_counter() - t0

    print(f"Sort time (sorted()): {sort_time:.3f}s")
    print(f"First 5 sorted: {sorted_data[:5]}")
    print(f"Last 5 sorted: {sorted_data[-5:]}")

if __name__ == "__main__":
    main()
```

### How it works

- **Generation:** Writes random integers (one per line, valid CSV) in chunks of 10,000 until the file reaches at least 10 MB. It checks the actual on-disk size with `os.path.getsize` so the result is genuinely ~10 MB regardless of system.
- **Sorting:** Reads all integers back into a list, then wraps `sorted()` with `time.perf_counter()` to measure elapsed time.
- **Timing:** Uses `time.perf_counter()` (the highest-resolution timer) rather than `time.time()`.

### Verification (run in the sandbox)

- Generated **960,000** integers
- File size: **10.02 MB**
- Generation time: **0.897s**
- Sort time (`sorted()`): **0.435s**

The script is self-contained, needs only the standard library, and prints the file size, row count, and both timings on every run.