Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

LLM Generation

Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

Output

Below is one complete solution. This script reads the list of file paths from "/tmp/files", obtains the size of each file, and then uses a greedy “bin‐packing” approach to assign files to one of 16 output bins (i.e. merged files) so that their total sizes are as equal as possible. Finally, it goes through each bin and copies the file contents into the corresponding "/tmp/merged_i" file. Note that this solution assumes that the files can be read in binary mode (so it works for both text and binary files) and that the file sizes can be obtained via os.stat(). You may want to adjust error‐handling or the buffer size for performance on very large files. Here’s the complete script: ------------------------------------------------------------ #!/usr/bin/env python3 import os import sys import shutil NUM_MERGED_FILES = 16 FILE_LIST_PATH = "/tmp/files" # file containing the list of file paths, one per line. OUTPUT_BASENAME = "/tmp/merged_" # will be appended with the index 0..15 def get_file_size(path): try: return os.stat(path).st_size except OSError as e: sys.stderr.write(f"Warning: Could not stat {path}: {e}\n") return 0 def assign_files_to_bins(file_infos, num_bins): # bins will be a list of tuples (total_size, list_of_file_paths) bins = [(0, []) for _ in range(num_bins)] # Process files in descending order by size for a better greedy result: for size, path in sorted(file_infos, key=lambda x: x[0], reverse=True): # Find the bin with the least total size min_index = min(range(num_bins), key=lambda i: bins[i][0]) current_total, paths = bins[min_index] # Append this file to that bin bins[min_index] = (current_total + size, paths + [path]) return bins def merge_files(bin_files, output_filename): # Opens the output file and copies in each file assigned in the bin. with open(output_filename, "wb") as outfile: for in_path in bin_files: try: # Read and write in chunks. with open(in_path, "rb") as infile: shutil.copyfileobj(infile, outfile) except OSError as e: sys.stderr.write(f"Warning: Could not merge {in_path}: {e}\n") def main(): # Read the file list from /tmp/files. if not os.path.exists(FILE_LIST_PATH): sys.stderr.write(f"Error: File {FILE_LIST_PATH} does not exist.\n") sys.exit(1) with open(FILE_LIST_PATH, "r") as f: file_paths = [line.strip() for line in f if line.strip()] if not file_paths: sys.stderr.write("Error: No file paths found in the file list.\n") sys.exit(1) # Get file sizes and prepare list of tuples: (size, path) file_infos = [] for path in file_paths: size = get_file_size(path) file_infos.append((size, path)) # Assign the files to bins trying to equalize total size. bins = assign_files_to_bins(file_infos, NUM_MERGED_FILES) # For debugging or logging, you might want to print the total sizes for i, (total_size, paths) in enumerate(bins): print(f"Bin {i}: {len(paths)} files, total {total_size} bytes.") # Merge the files for each bin into one output file. for i, (total_size, paths) in enumerate(bins): output_file = OUTPUT_BASENAME + str(i) print(f"Writing {len(paths)} files to {output_file} (approx. {total_size} bytes)") merge_files(paths, output_file) if __name__ == "__main__": main() ------------------------------------------------------------ How It Works: 1. The script reads the file paths from "/tmp/files", stripping whitespace. 2. It gets the size of each file (using os.stat) and creates a list of tuples (size, path). 3. It sorts the list in descending order (largest first) and assigns each file to the bin with the smallest current total size. 4. It then writes the contents of all files assigned to each bin into one output file: "/tmp/merged_0", "/tmp/merged_1", …, "/tmp/merged_15". You can run this script directly using Python 3. Adjust logging or error‐handling as needed for your environment.

Extract Code

I extracted the following code from that output: 

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#!/usr/bin/env python3
import os
import sys
import shutil

NUM_MERGED_FILES = 16
FILE_LIST_PATH = "/tmp/files"  # file containing the list of file paths, one per line.
OUTPUT_BASENAME = "/tmp/merged_"  # will be appended with the index 0..15

def get_file_size(path):
    try:
        return os.stat(path).st_size
    except OSError as e:
        sys.stderr.write(f"Warning: Could not stat {path}: {e}\n")
        return 0

def assign_files_to_bins(file_infos, num_bins):
    # bins will be a list of tuples (total_size, list_of_file_paths)
    bins = [(0, []) for _ in range(num_bins)]
    # Process files in descending order by size for a better greedy result:
    for size, path in sorted(file_infos, key=lambda x: x[0], reverse=True):
        # Find the bin with the least total size
        min_index = min(range(num_bins), key=lambda i: bins[i][0])
        current_total, paths = bins[min_index]
        # Append this file to that bin
        bins[min_index] = (current_total + size, paths + [path])
    return bins

def merge_files(bin_files, output_filename):
    # Opens the output file and copies in each file assigned in the bin.
    with open(output_filename, "wb") as outfile:
        for in_path in bin_files:
            try:
                # Read and write in chunks.
                with open(in_path, "rb") as infile:
                    shutil.copyfileobj(infile, outfile)
            except OSError as e:
                sys.stderr.write(f"Warning: Could not merge {in_path}: {e}\n")

def main():
    # Read the file list from /tmp/files.
    if not os.path.exists(FILE_LIST_PATH):
        sys.stderr.write(f"Error: File {FILE_LIST_PATH} does not exist.\n")
        sys.exit(1)
    
    with open(FILE_LIST_PATH, "r") as f:
        file_paths = [line.strip() for line in f if line.strip()]

    if not file_paths:
        sys.stderr.write("Error: No file paths found in the file list.\n")
        sys.exit(1)

    # Get file sizes and prepare list of tuples: (size, path)
    file_infos = []
    for path in file_paths:
        size = get_file_size(path)
        file_infos.append((size, path))

    # Assign the files to bins trying to equalize total size.
    bins = assign_files_to_bins(file_infos, NUM_MERGED_FILES)

    # For debugging or logging, you might want to print the total sizes
    for i, (total_size, paths) in enumerate(bins):
        print(f"Bin {i}: {len(paths)} files, total {total_size} bytes.")

    # Merge the files for each bin into one output file.
    for i, (total_size, paths) in enumerate(bins):
        output_file = OUTPUT_BASENAME + str(i)
        print(f"Writing {len(paths)} files to {output_file} (approx. {total_size} bytes)")
        merge_files(paths, output_file)

if __name__ == "__main__":
    main()

Run Code Interpreter

Running the following program: 

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#!/usr/bin/env python3
import os
import sys
import shutil

NUM_MERGED_FILES = 16
FILE_LIST_PATH = "/tmp/files"  # file containing the list of file paths, one per line.
OUTPUT_BASENAME = "/tmp/merged_"  # will be appended with the index 0..15

def get_file_size(path):
    try:
        return os.stat(path).st_size
    except OSError as e:
        sys.stderr.write(f"Warning: Could not stat {path}: {e}\n")
        return 0

def assign_files_to_bins(file_infos, num_bins):
    # bins will be a list of tuples (total_size, list_of_file_paths)
    bins = [(0, []) for _ in range(num_bins)]
    # Process files in descending order by size for a better greedy result:
    for size, path in sorted(file_infos, key=lambda x: x[0], reverse=True):
        # Find the bin with the least total size
        min_index = min(range(num_bins), key=lambda i: bins[i][0])
        current_total, paths = bins[min_index]
        # Append this file to that bin
        bins[min_index] = (current_total + size, paths + [path])
    return bins

def merge_files(bin_files, output_filename):
    # Opens the output file and copies in each file assigned in the bin.
    with open(output_filename, "wb") as outfile:
        for in_path in bin_files:
            try:
                # Read and write in chunks.
                with open(in_path, "rb") as infile:
                    shutil.copyfileobj(infile, outfile)
            except OSError as e:
                sys.stderr.write(f"Warning: Could not merge {in_path}: {e}\n")

def main():
    # Read the file list from /tmp/files.
    if not os.path.exists(FILE_LIST_PATH):
        sys.stderr.write(f"Error: File {FILE_LIST_PATH} does not exist.\n")
        sys.exit(1)
    
    with open(FILE_LIST_PATH, "r") as f:
        file_paths = [line.strip() for line in f if line.strip()]

    if not file_paths:
        sys.stderr.write("Error: No file paths found in the file list.\n")
        sys.exit(1)

    # Get file sizes and prepare list of tuples: (size, path)
    file_infos = []
    for path in file_paths:
        size = get_file_size(path)
        file_infos.append((size, path))

    # Assign the files to bins trying to equalize total size.
    bins = assign_files_to_bins(file_infos, NUM_MERGED_FILES)

    # For debugging or logging, you might want to print the total sizes
    for i, (total_size, paths) in enumerate(bins):
        print(f"Bin {i}: {len(paths)} files, total {total_size} bytes.")

    # Merge the files for each bin into one output file.
    for i, (total_size, paths) in enumerate(bins):
        output_file = OUTPUT_BASENAME + str(i)
        print(f"Writing {len(paths)} files to {output_file} (approx. {total_size} bytes)")
        merge_files(paths, output_file)

if __name__ == "__main__":
    main()
And got the output: Bin 0: 34 files, total 38513 bytes. Bin 1: 37 files, total 38513 bytes. Bin 2: 46 files, total 38515 bytes. Bin 3: 53 files, total 38517 bytes. Bin 4: 55 files, total 38514 bytes. Bin 5: 71 files, total 38516 bytes. Bin 6: 71 files, total 38516 bytes. Bin 7: 71 files, total 38516 bytes. Bin 8: 70 files, total 38514 bytes. Bin 9: 70 files, total 38514 bytes. Bin 10: 70 files, total 38513 bytes. Bin 11: 70 files, total 38513 bytes. Bin 12: 70 files, total 38513 bytes. Bin 13: 71 files, total 38513 bytes. Bin 14: 70 files, total 38514 bytes. Bin 15: 71 files, total 38515 bytes. Writing 34 files to /tmp/merged_0 (approx. 38513 bytes) Writing 37 files to /tmp/merged_1 (approx. 38513 bytes) Writing 46 files to /tmp/merged_2 (approx. 38515 bytes) Writing 53 files to /tmp/merged_3 (approx. 38517 bytes) Writing 55 files to /tmp/merged_4 (approx. 38514 bytes) Writing 71 files to /tmp/merged_5 (approx. 38516 bytes) Writing 71 files to /tmp/merged_6 (approx. 38516 bytes) Writing 71 files to /tmp/merged_7 (approx. 38516 bytes) Writing 70 files to /tmp/merged_8 (approx. 38514 bytes) Writing 70 files to /tmp/merged_9 (approx. 38514 bytes) Writing 70 files to /tmp/merged_10 (approx. 38513 bytes) Writing 70 files to /tmp/merged_11 (approx. 38513 bytes) Writing 70 files to /tmp/merged_12 (approx. 38513 bytes) Writing 71 files to /tmp/merged_13 (approx. 38513 bytes) Writing 70 files to /tmp/merged_14 (approx. 38514 bytes) Writing 71 files to /tmp/merged_15 (approx. 38515 bytes)

PyFunc

final: True Resulting in output: True

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

LLM Generation

Query

I have a list of several thousand file paths in /tmp/files. Write a python script that merges the content int 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. "/tmp/files" is a list of file paths, one per line.

Output

Below is one way to do it. This script reads the list of file paths found in "/tmp/files" (one per line), gets the file size for each file, sorts them in descending order, and then uses a greedy algorithm to assign each file to one of 16 bins (i.e. merged files) so that the total amount of data per bin is roughly balanced. Finally, it opens each output file ("/tmp/merged_0" … "/tmp/merged_15") in binary write mode and writes the contents of the files assigned to that bin. (Adjust the script if your files are text only.) #!/usr/bin/env python3 import os NUM_MERGED = 16 FILE_LIST_PATH = "/tmp/files" def main(): # Step 1: Read file paths with open(FILE_LIST_PATH, 'r') as f_list: paths = [line.strip() for line in f_list if line.strip()] if not paths: print("No files found in", FILE_LIST_PATH) return # Step 2: Get (size, path) for each file. files = [] for path in paths: try: size = os.path.getsize(path) except OSError as e: print(f"Warning: Could not get size for {path}: {e}") size = 0 files.append((size, path)) # Sort files descending by file size (largest first) files.sort(key=lambda tup: tup[0], reverse=True) # Step 3: Greedy partitioning into NUM_MERGED bins. # bins is a list of tuples: (current_total_size, [list of file paths]) bins = [(0, []) for _ in range(NUM_MERGED)] for size, path in files: # choose the bin with currently the smallest total size min_index = min(range(NUM_MERGED), key=lambda i: bins[i][0]) total_size, file_list = bins[min_index] file_list.append(path) bins[min_index] = (total_size + size, file_list) # (Optional) print out the total bytes in each bin for debugging. for i, (total, file_list) in enumerate(bins): print(f"Bin {i}: {total} bytes from {len(file_list)} files.") # Step 4: Write out each merged file. for i, (total, file_list) in enumerate(bins): output_path = f"/tmp/merged_{i}" print(f"Writing {len(file_list)} files to {output_path} (≈{total} bytes)") with open(output_path, 'wb') as out_f: # For each file assigned to this bin for fpath in file_list: try: with open(fpath, 'rb') as in_f: # Copy in blocks to avoid loading whole files into memory. while True: chunk = in_f.read(4096) if not chunk: break out_f.write(chunk) except Exception as e: print(f"Error reading {fpath}: {e}") if __name__ == '__main__': main() ───────────────────────── Explanation: 1. The script reads the file paths from "/tmp/files". It ignores any blank lines. 2. Each file’s size is retrieved (errors are caught, and a size of 0 is used if the file is inaccessible). 3. Files are sorted by size (largest first) so that when using the greedy assignment (putting the next largest file into the smallest current bin) the bins’ total sizes end up being roughly balanced. 4. For each merged file output ("/tmp/merged_0" to "/tmp/merged_15"), the script writes the content of every file assigned to that bin. The files are read and written in binary mode in blocks (here, 4096 bytes) to avoid high memory usage. You can save the script to a file (for example, merge_files.py), make it executable (chmod +x merge_files.py), and then run it with Python 3.

Extract Code

I extracted the following code from that output: 

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#!/usr/bin/env python3
import os

NUM_MERGED = 16
FILE_LIST_PATH = "/tmp/files"

def main():
    # Step 1: Read file paths
    with open(FILE_LIST_PATH, 'r') as f_list:
        paths = [line.strip() for line in f_list if line.strip()]
    if not paths:
        print("No files found in", FILE_LIST_PATH)
        return

    # Step 2: Get (size, path) for each file.
    files = []
    for path in paths:
        try:
            size = os.path.getsize(path)
        except OSError as e:
            print(f"Warning: Could not get size for {path}: {e}")
            size = 0
        files.append((size, path))

    # Sort files descending by file size (largest first)
    files.sort(key=lambda tup: tup[0], reverse=True)

    # Step 3: Greedy partitioning into NUM_MERGED bins.
    # bins is a list of tuples: (current_total_size, [list of file paths])
    bins = [(0, []) for _ in range(NUM_MERGED)]
    for size, path in files:
        # choose the bin with currently the smallest total size
        min_index = min(range(NUM_MERGED), key=lambda i: bins[i][0])
        total_size, file_list = bins[min_index]
        file_list.append(path)
        bins[min_index] = (total_size + size, file_list)

    # (Optional) print out the total bytes in each bin for debugging.
    for i, (total, file_list) in enumerate(bins):
        print(f"Bin {i}: {total} bytes from {len(file_list)} files.")

    # Step 4: Write out each merged file.
    for i, (total, file_list) in enumerate(bins):
        output_path = f"/tmp/merged_{i}"
        print(f"Writing {len(file_list)} files to {output_path} (≈{total} bytes)")
        with open(output_path, 'wb') as out_f:
            # For each file assigned to this bin
            for fpath in file_list:
                try:
                    with open(fpath, 'rb') as in_f:
                        # Copy in blocks to avoid loading whole files into memory.
                        while True:
                            chunk = in_f.read(4096)
                            if not chunk:
                                break
                            out_f.write(chunk)
                except Exception as e:
                    print(f"Error reading {fpath}: {e}")

if __name__ == '__main__':
    main()

Run Code Interpreter

Running the following program: 

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#!/usr/bin/env python3
import os

NUM_MERGED = 16
FILE_LIST_PATH = "/tmp/files"

def main():
    # Step 1: Read file paths
    with open(FILE_LIST_PATH, 'r') as f_list:
        paths = [line.strip() for line in f_list if line.strip()]
    if not paths:
        print("No files found in", FILE_LIST_PATH)
        return

    # Step 2: Get (size, path) for each file.
    files = []
    for path in paths:
        try:
            size = os.path.getsize(path)
        except OSError as e:
            print(f"Warning: Could not get size for {path}: {e}")
            size = 0
        files.append((size, path))

    # Sort files descending by file size (largest first)
    files.sort(key=lambda tup: tup[0], reverse=True)

    # Step 3: Greedy partitioning into NUM_MERGED bins.
    # bins is a list of tuples: (current_total_size, [list of file paths])
    bins = [(0, []) for _ in range(NUM_MERGED)]
    for size, path in files:
        # choose the bin with currently the smallest total size
        min_index = min(range(NUM_MERGED), key=lambda i: bins[i][0])
        total_size, file_list = bins[min_index]
        file_list.append(path)
        bins[min_index] = (total_size + size, file_list)

    # (Optional) print out the total bytes in each bin for debugging.
    for i, (total, file_list) in enumerate(bins):
        print(f"Bin {i}: {total} bytes from {len(file_list)} files.")

    # Step 4: Write out each merged file.
    for i, (total, file_list) in enumerate(bins):
        output_path = f"/tmp/merged_{i}"
        print(f"Writing {len(file_list)} files to {output_path} (≈{total} bytes)")
        with open(output_path, 'wb') as out_f:
            # For each file assigned to this bin
            for fpath in file_list:
                try:
                    with open(fpath, 'rb') as in_f:
                        # Copy in blocks to avoid loading whole files into memory.
                        while True:
                            chunk = in_f.read(4096)
                            if not chunk:
                                break
                            out_f.write(chunk)
                except Exception as e:
                    print(f"Error reading {fpath}: {e}")

if __name__ == '__main__':
    main()
And got the output: Bin 0: 36146 bytes from 34 files. Bin 1: 36149 bytes from 40 files. Bin 2: 36147 bytes from 45 files. Bin 3: 36146 bytes from 57 files. Bin 4: 36145 bytes from 58 files. Bin 5: 36156 bytes from 70 files. Bin 6: 36153 bytes from 70 files. Bin 7: 36158 bytes from 70 files. Bin 8: 36152 bytes from 70 files. Bin 9: 36147 bytes from 69 files. Bin 10: 36145 bytes from 69 files. Bin 11: 36152 bytes from 70 files. Bin 12: 36148 bytes from 69 files. Bin 13: 36156 bytes from 70 files. Bin 14: 36149 bytes from 70 files. Bin 15: 36147 bytes from 69 files. Writing 34 files to /tmp/merged_0 (≈36146 bytes) Writing 40 files to /tmp/merged_1 (≈36149 bytes) Writing 45 files to /tmp/merged_2 (≈36147 bytes) Writing 57 files to /tmp/merged_3 (≈36146 bytes) Writing 58 files to /tmp/merged_4 (≈36145 bytes) Writing 70 files to /tmp/merged_5 (≈36156 bytes) Writing 70 files to /tmp/merged_6 (≈36153 bytes) Writing 70 files to /tmp/merged_7 (≈36158 bytes) Writing 70 files to /tmp/merged_8 (≈36152 bytes) Writing 69 files to /tmp/merged_9 (≈36147 bytes) Writing 69 files to /tmp/merged_10 (≈36145 bytes) Writing 70 files to /tmp/merged_11 (≈36152 bytes) Writing 69 files to /tmp/merged_12 (≈36148 bytes) Writing 70 files to /tmp/merged_13 (≈36156 bytes) Writing 70 files to /tmp/merged_14 (≈36149 bytes) Writing 69 files to /tmp/merged_15 (≈36147 bytes)

PyFunc

final: True Resulting in output: True