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

To achieve this, you can write a Python script that reads the list of file paths from `/tmp/files`, calculates the total size of all files, and then distributes the files into 16 output files (`/tmp/merged_0` to `/tmp/merged_15`) such that each output file has approximately the same total size. Here’s a Python script that does this: 

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import os

def get_file_size(file_path):
    """Returns the size of the file in bytes."""
    return os.path.getsize(file_path)

def distribute_files(file_paths, num_output_files):
    """Distributes files into output files such that each output file has approximately the same total size."""
    # Calculate the total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Calculate the target size for each output file
    target_size = total_size / num_output_files
    
    # Initialize variables
    output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(num_output_files)]
    current_sizes = [0] * num_output_files
    current_file_index = 0
    
    # Distribute files
    for file_path in file_paths:
        file_size = get_file_size(file_path)
        
        # Find the output file with the smallest current size
        current_file_index = current_sizes.index(min(current_sizes))
        
        # Write the file content to the selected output file
        with open(file_path, 'rb') as input_file:
            output_files[current_file_index].write(input_file.read())
        
        # Update the current size of the selected output file
        current_sizes[current_file_index] += file_size
    
    # Close all output files
    for output_file in output_files:
        output_file.close()

def main():
    # Read the list of file paths from /tmp/files
    with open('/tmp/files', 'r') as file_list:
        file_paths = [line.strip() for line in file_list if line.strip()]
    
    # Distribute the files into 16 output files
    distribute_files(file_paths, 16)

if __name__ == "__main__":
    main()
### Explanation: 1. **get_file_size(file_path)**: This function returns the size of a file in bytes. 2. **distribute_files(file_paths, num_output_files)**: This function distributes the files into the output files. It calculates the total size of all files and then distributes them such that each output file has approximately the same total size. 3. **main()**: This function reads the list of file paths from `/tmp/files` and calls `distribute_files` to distribute the files into 16 output files. ### How it works: - The script first calculates the total size of all files. - It then calculates the target size for each output file by dividing the total size by the number of output files (16 in this case). - The script iterates over the list of file paths and writes each file to the output file with the smallest current size, ensuring that the output files are balanced in terms of total size. ### Usage: 1. Save the script to a file, e.g., `merge_files.py`. 2. Run the script using Python: 
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   python3 merge_files.py
3. The script will create 16 files (`/tmp/merged_0` to `/tmp/merged_15`) with the merged content, each approximately the same size. ### Notes: - The script assumes that the file paths in `/tmp/files` are absolute or relative to the script's working directory. - The script uses binary mode (`'wb'`) to write the output files, ensuring that the content is copied exactly as is.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(file_path):
    """Returns the size of the file in bytes."""
    return os.path.getsize(file_path)

def distribute_files(file_paths, num_output_files):
    """Distributes files into output files such that each output file has approximately the same total size."""
    # Calculate the total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Calculate the target size for each output file
    target_size = total_size / num_output_files
    
    # Initialize variables
    output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(num_output_files)]
    current_sizes = [0] * num_output_files
    current_file_index = 0
    
    # Distribute files
    for file_path in file_paths:
        file_size = get_file_size(file_path)
        
        # Find the output file with the smallest current size
        current_file_index = current_sizes.index(min(current_sizes))
        
        # Write the file content to the selected output file
        with open(file_path, 'rb') as input_file:
            output_files[current_file_index].write(input_file.read())
        
        # Update the current size of the selected output file
        current_sizes[current_file_index] += file_size
    
    # Close all output files
    for output_file in output_files:
        output_file.close()

def main():
    # Read the list of file paths from /tmp/files
    with open('/tmp/files', 'r') as file_list:
        file_paths = [line.strip() for line in file_list if line.strip()]
    
    # Distribute the files into 16 output files
    distribute_files(file_paths, 16)

if __name__ == "__main__":
    main()

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(file_path):
    """Returns the size of the file in bytes."""
    return os.path.getsize(file_path)

def distribute_files(file_paths, num_output_files):
    """Distributes files into output files such that each output file has approximately the same total size."""
    # Calculate the total size of all files
    total_size = sum(get_file_size(path) for path in file_paths)
    
    # Calculate the target size for each output file
    target_size = total_size / num_output_files
    
    # Initialize variables
    output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(num_output_files)]
    current_sizes = [0] * num_output_files
    current_file_index = 0
    
    # Distribute files
    for file_path in file_paths:
        file_size = get_file_size(file_path)
        
        # Find the output file with the smallest current size
        current_file_index = current_sizes.index(min(current_sizes))
        
        # Write the file content to the selected output file
        with open(file_path, 'rb') as input_file:
            output_files[current_file_index].write(input_file.read())
        
        # Update the current size of the selected output file
        current_sizes[current_file_index] += file_size
    
    # Close all output files
    for output_file in output_files:
        output_file.close()

def main():
    # Read the list of file paths from /tmp/files
    with open('/tmp/files', 'r') as file_list:
        file_paths = [line.strip() for line in file_list if line.strip()]
    
    # Distribute the files into 16 output files
    distribute_files(file_paths, 16)

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

PyFunc

final: False Resulting in output: False