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 these all together and splits the content into 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. To do this, sort files by size (largest first) and add files in order always to the smallest one. "/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 these all together and splits the content into 16 files called /tmp/merged_%d for i in 0..15 where each is approximately the same size. To do this, sort files by size (largest first) and add files in order always to the smallest one. "/tmp/files" is a list of file paths, one per line.

Output

Here’s a Python script that accomplishes your task: 

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import os

def main():
    # Read the list of file paths
    with open('/tmp/files', 'r') as f:
        file_paths = [line.strip() for line in f.readlines()]

    # Get the size of each file and sort by size (largest first)
    file_sizes = [(path, os.path.getsize(path)) for path in file_paths]
    file_sizes.sort(key=lambda x: x[1], reverse=True)

    # Initialize 16 output files with their current sizes
    output_files = [f'/tmp/merged_{i}' for i in range(16)]
    output_sizes = [0] * 16

    # Open all output files for writing
    with open(output_files[0], 'w') as f0, \
         open(output_files[1], 'w') as f1, \
         open(output_files[2], 'w') as f2, \
         open(output_files[3], 'w') as f3, \
         open(output_files[4], 'w') as f4, \
         open(output_files[5], 'w') as f5, \
         open(output_files[6], 'w') as f6, \
         open(output_files[7], 'w') as f7, \
         open(output_files[8], 'w') as f8, \
         open(output_files[9], 'w') as f9, \
         open(output_files[10], 'w') as f10, \
         open(output_files[11], 'w') as f11, \
         open(output_files[12], 'w') as f12, \
         open(output_files[13], 'w') as f13, \
         open(output_files[14], 'w') as f14, \
         open(output_files[15], 'w') as f15:
        file_handles = [f0, f1, f2, f3, f4, f5, f6, f7, f8, f9, f10, f11, f12, f13, f14, f15]

        # Process each file
        for path, size in file_sizes:
            # Find the output file with the smallest size
            min_index = output_sizes.index(min(output_sizes))

            # Read the content of the input file
            with open(path, 'r') as input_file:
                content = input_file.read()

            # Write the content to the selected output file
            file_handles[min_index].write(content)

            # Update the size of the selected output file
            output_sizes[min_index] += size

if __name__ == '__main__':
    main()
### Explanation: 1. **Read the file paths**: The script reads the list of file paths from `/tmp/files`. 2. **Sort files by size**: It calculates the size of each file and sorts them in descending order. 3. **Initialize output files**: It creates 16 output files (`/tmp/merged_0` to `/tmp/merged_15`) and keeps track of their sizes. 4. **Distribute files**: For each file, it finds the output file with the smallest current size, appends the file's content to it, and updates the size of that output file. 5. **Write content**: The content of each file is read and written to the appropriate output file. ### Notes: - The script assumes that all files are text files and can be read and written as such. - If the files are binary, you should open them in binary mode (`'rb'` and `'wb'`). - The script ensures that the output files are approximately the same size by always adding content to the smallest one. Run this script in your Python environment to merge and split the files as described.

Extract Code

I extracted the following code from that output: 

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import os

def main():
    # Read the list of file paths
    with open('/tmp/files', 'r') as f:
        file_paths = [line.strip() for line in f.readlines()]

    # Get the size of each file and sort by size (largest first)
    file_sizes = [(path, os.path.getsize(path)) for path in file_paths]
    file_sizes.sort(key=lambda x: x[1], reverse=True)

    # Initialize 16 output files with their current sizes
    output_files = [f'/tmp/merged_{i}' for i in range(16)]
    output_sizes = [0] * 16

    # Open all output files for writing
    with open(output_files[0], 'w') as f0, \
         open(output_files[1], 'w') as f1, \
         open(output_files[2], 'w') as f2, \
         open(output_files[3], 'w') as f3, \
         open(output_files[4], 'w') as f4, \
         open(output_files[5], 'w') as f5, \
         open(output_files[6], 'w') as f6, \
         open(output_files[7], 'w') as f7, \
         open(output_files[8], 'w') as f8, \
         open(output_files[9], 'w') as f9, \
         open(output_files[10], 'w') as f10, \
         open(output_files[11], 'w') as f11, \
         open(output_files[12], 'w') as f12, \
         open(output_files[13], 'w') as f13, \
         open(output_files[14], 'w') as f14, \
         open(output_files[15], 'w') as f15:
        file_handles = [f0, f1, f2, f3, f4, f5, f6, f7, f8, f9, f10, f11, f12, f13, f14, f15]

        # Process each file
        for path, size in file_sizes:
            # Find the output file with the smallest size
            min_index = output_sizes.index(min(output_sizes))

            # Read the content of the input file
            with open(path, 'r') as input_file:
                content = input_file.read()

            # Write the content to the selected output file
            file_handles[min_index].write(content)

            # Update the size of the selected output file
            output_sizes[min_index] += size

if __name__ == '__main__':
    main()

Run Code Interpreter

Running the following program: 

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import os

def main():
    # Read the list of file paths
    with open('/tmp/files', 'r') as f:
        file_paths = [line.strip() for line in f.readlines()]

    # Get the size of each file and sort by size (largest first)
    file_sizes = [(path, os.path.getsize(path)) for path in file_paths]
    file_sizes.sort(key=lambda x: x[1], reverse=True)

    # Initialize 16 output files with their current sizes
    output_files = [f'/tmp/merged_{i}' for i in range(16)]
    output_sizes = [0] * 16

    # Open all output files for writing
    with open(output_files[0], 'w') as f0, \
         open(output_files[1], 'w') as f1, \
         open(output_files[2], 'w') as f2, \
         open(output_files[3], 'w') as f3, \
         open(output_files[4], 'w') as f4, \
         open(output_files[5], 'w') as f5, \
         open(output_files[6], 'w') as f6, \
         open(output_files[7], 'w') as f7, \
         open(output_files[8], 'w') as f8, \
         open(output_files[9], 'w') as f9, \
         open(output_files[10], 'w') as f10, \
         open(output_files[11], 'w') as f11, \
         open(output_files[12], 'w') as f12, \
         open(output_files[13], 'w') as f13, \
         open(output_files[14], 'w') as f14, \
         open(output_files[15], 'w') as f15:
        file_handles = [f0, f1, f2, f3, f4, f5, f6, f7, f8, f9, f10, f11, f12, f13, f14, f15]

        # Process each file
        for path, size in file_sizes:
            # Find the output file with the smallest size
            min_index = output_sizes.index(min(output_sizes))

            # Read the content of the input file
            with open(path, 'r') as input_file:
                content = input_file.read()

            # Write the content to the selected output file
            file_handles[min_index].write(content)

            # Update the size of the selected output file
            output_sizes[min_index] += size

if __name__ == '__main__':
    main()
And got the output:

PyFunc

final: True Resulting in output: True