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

Certainly! Below is a Python script that achieves the described functionality. This script reads the list of file paths from `/tmp/files`, sorts them by size in descending order, and then merges their contents into 16 approximately equally sized files. 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_path):
    with open(file_path, 'r') as f:
        return [line.strip() for line in f]

def distribute_files(file_paths):
    # Get sizes and sort files by size in descending order
    file_sizes = [(fp, get_file_size(fp)) for fp in file_paths]
    file_sizes.sort(key=lambda x: x[1], reverse=True)
    
    # Initialize the target files and their sizes
    merged_files = [f"/tmp/merged_{i}" for i in range(16)]
    merged_sizes = [0] * 16
    
    # Distribute files to the target files based on current sizes
    for fp, size in file_sizes:
        # Find the smallest target file
        smallest_index = merged_sizes.index(min(merged_sizes))
        # Append file content to the smallest target file
        with open(merged_files[smallest_index], 'ab') as mf:
            with open(fp, 'rb') as f:
                mf.write(f.read())
        # Update the size of the target file
        merged_sizes[smallest_index] += size

if __name__ == "__main__":
    file_list_path = "/tmp/files"
    file_paths = read_file_paths(file_list_path)
    distribute_files(file_paths)
    print("Files have been successfully merged and distributed.")
### Explanation: 1. **Helper Functions**: - `get_file_size(file_path)`: Returns the size of the file. - `read_file_paths(file_path)`: Reads the file paths from the given file and returns them as a list. 2. **Main Function (`distribute_files`)**: - **Sorting**: It sorts the file paths by their sizes in descending order. - **Initialization**: Initializes the target merged files (`/tmp/merged_0` to `/tmp/merged_15`) and their sizes. - **Distribution**: It iterates over the sorted files, finding the smallest merged file (by size) and appending the content of the current file to it. It then updates the size of the merged file. 3. **Script Execution**: - The script reads the list of file paths from `/tmp/files`. - It then calls `distribute_files` to sort and distribute the content of these files into the 16 target files. ### Note: - The script opens the files in binary mode (`'rb'` for reading and `'ab'` for appending) to handle any type of file content. - Ensure the `/tmp/files` contains the correct list of file paths and that the script has the necessary permissions to read the input files and write to the output files in `/tmp`. This script assumes that the list of file paths is correctly formatted and accessible. Adjustments may be needed based on the specific environment and requirements.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_path):
    with open(file_path, 'r') as f:
        return [line.strip() for line in f]

def distribute_files(file_paths):
    # Get sizes and sort files by size in descending order
    file_sizes = [(fp, get_file_size(fp)) for fp in file_paths]
    file_sizes.sort(key=lambda x: x[1], reverse=True)
    
    # Initialize the target files and their sizes
    merged_files = [f"/tmp/merged_{i}" for i in range(16)]
    merged_sizes = [0] * 16
    
    # Distribute files to the target files based on current sizes
    for fp, size in file_sizes:
        # Find the smallest target file
        smallest_index = merged_sizes.index(min(merged_sizes))
        # Append file content to the smallest target file
        with open(merged_files[smallest_index], 'ab') as mf:
            with open(fp, 'rb') as f:
                mf.write(f.read())
        # Update the size of the target file
        merged_sizes[smallest_index] += size

if __name__ == "__main__":
    file_list_path = "/tmp/files"
    file_paths = read_file_paths(file_list_path)
    distribute_files(file_paths)
    print("Files have been successfully merged and distributed.")

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_path):
    with open(file_path, 'r') as f:
        return [line.strip() for line in f]

def distribute_files(file_paths):
    # Get sizes and sort files by size in descending order
    file_sizes = [(fp, get_file_size(fp)) for fp in file_paths]
    file_sizes.sort(key=lambda x: x[1], reverse=True)
    
    # Initialize the target files and their sizes
    merged_files = [f"/tmp/merged_{i}" for i in range(16)]
    merged_sizes = [0] * 16
    
    # Distribute files to the target files based on current sizes
    for fp, size in file_sizes:
        # Find the smallest target file
        smallest_index = merged_sizes.index(min(merged_sizes))
        # Append file content to the smallest target file
        with open(merged_files[smallest_index], 'ab') as mf:
            with open(fp, 'rb') as f:
                mf.write(f.read())
        # Update the size of the target file
        merged_sizes[smallest_index] += size

if __name__ == "__main__":
    file_list_path = "/tmp/files"
    file_paths = read_file_paths(file_list_path)
    distribute_files(file_paths)
    print("Files have been successfully merged and distributed.")
And got the output: Files have been successfully merged and distributed.

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 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

Certainly! Below is a Python script that accomplishes the task you described. This script reads the list of file paths from "/tmp/files", sorts them by size in descending order, and distributes the content into 16 approximately equal-sized files. 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_list_path):
    with open(file_list_path, 'r') as file:
        return [line.strip() for line in file]

def merge_and_split_files(file_paths, output_prefix, num_output_files):
    # Get sizes of all files
    file_sizes = [(file_path, get_file_size(file_path)) for file_path in file_paths]
    # Sort files by size in descending order
    file_sizes.sort(key=lambda x: x[1], reverse=True)
    
    # Initialize output files and their sizes
    output_files = [open(f"{output_prefix}_{i}", 'wb') for i in range(num_output_files)]
    output_sizes = [0] * num_output_files
    
    for file_path, size in file_sizes:
        # Find the output file with the smallest size
        min_index = output_sizes.index(min(output_sizes))
        with open(file_path, 'rb') as f:
            output_files[min_index].write(f.read())
        output_sizes[min_index] += size

    # Close all output files
    for file in output_files:
        file.close()

if __name__ == "__main__":
    file_list_path = "/tmp/files"
    output_prefix = "/tmp/merged"
    num_output_files = 16

    file_paths = read_file_paths(file_list_path)
    merge_and_split_files(file_paths, output_prefix, num_output_files)
### Explanation: 1. **get_file_size(file_path)**: This function returns the size of the file at the given path. 2. **read_file_paths(file_list_path)**: This function reads the list of file paths from the given file and returns a list of file paths. 3. **merge_and_split_files(file_paths, output_prefix, num_output_files)**: This function performs the merging and splitting of files: - It first calculates the size of each file and sorts them in descending order based on size. - It initializes 16 output files and keeps track of their sizes. - It iterates over the sorted list of file paths, always adding the current file to the output file with the smallest total size. - Finally, it closes all the output files. ### Usage: - Place the script in a Python file, for example, `merge_split_files.py`. - Ensure that the list of file paths is correctly placed in `/tmp/files`. - Run the script using a Python interpreter: `python merge_split_files.py`. This script ensures that the output files are approximately the same size by always adding the next largest file to the smallest output file, balancing the sizes as it proceeds.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_list_path):
    with open(file_list_path, 'r') as file:
        return [line.strip() for line in file]

def merge_and_split_files(file_paths, output_prefix, num_output_files):
    # Get sizes of all files
    file_sizes = [(file_path, get_file_size(file_path)) for file_path in file_paths]
    # Sort files by size in descending order
    file_sizes.sort(key=lambda x: x[1], reverse=True)
    
    # Initialize output files and their sizes
    output_files = [open(f"{output_prefix}_{i}", 'wb') for i in range(num_output_files)]
    output_sizes = [0] * num_output_files
    
    for file_path, size in file_sizes:
        # Find the output file with the smallest size
        min_index = output_sizes.index(min(output_sizes))
        with open(file_path, 'rb') as f:
            output_files[min_index].write(f.read())
        output_sizes[min_index] += size

    # Close all output files
    for file in output_files:
        file.close()

if __name__ == "__main__":
    file_list_path = "/tmp/files"
    output_prefix = "/tmp/merged"
    num_output_files = 16

    file_paths = read_file_paths(file_list_path)
    merge_and_split_files(file_paths, output_prefix, num_output_files)

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_list_path):
    with open(file_list_path, 'r') as file:
        return [line.strip() for line in file]

def merge_and_split_files(file_paths, output_prefix, num_output_files):
    # Get sizes of all files
    file_sizes = [(file_path, get_file_size(file_path)) for file_path in file_paths]
    # Sort files by size in descending order
    file_sizes.sort(key=lambda x: x[1], reverse=True)
    
    # Initialize output files and their sizes
    output_files = [open(f"{output_prefix}_{i}", 'wb') for i in range(num_output_files)]
    output_sizes = [0] * num_output_files
    
    for file_path, size in file_sizes:
        # Find the output file with the smallest size
        min_index = output_sizes.index(min(output_sizes))
        with open(file_path, 'rb') as f:
            output_files[min_index].write(f.read())
        output_sizes[min_index] += size

    # Close all output files
    for file in output_files:
        file.close()

if __name__ == "__main__":
    file_list_path = "/tmp/files"
    output_prefix = "/tmp/merged"
    num_output_files = 16

    file_paths = read_file_paths(file_list_path)
    merge_and_split_files(file_paths, output_prefix, num_output_files)
And got the output:

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 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

Certainly! Below is a Python script that performs the task you described. The script reads the list of file paths from `/tmp/files`, sorts them by size in descending order, and then distributes their content into 16 output files named `/tmp/merged_0` to `/tmp/merged_15` such that each output file is approximately the same size. Here's the complete script: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def distribute_files(file_paths, num_outputs):
    # Sort files by size in descending order
    sorted_files = sorted(file_paths, key=get_file_size, reverse=True)
    
    # Initialize the output files and their sizes
    output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(num_outputs)]
    output_sizes = [0] * num_outputs
    
    # Distribute files to the smallest output file
    for file_path in sorted_files:
        # Find the index of the smallest output file
        smallest_index = output_sizes.index(min(output_sizes))
        
        # Read the content of the current file
        with open(file_path, 'rb') as f:
            content = f.read()
        
        # Write the content to the chosen output file
        output_files[smallest_index].write(content)
        
        # Update the size of the chosen output file
        output_sizes[smallest_index] += get_file_size(file_path)
    
    # Close all the output files
    for f in output_files:
        f.close()

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

    # Number of output files
    num_outputs = 16
    
    # Distribute files into output files
    distribute_files(file_paths, num_outputs)

if __name__ == '__main__':
    main()
### Explanation: 1. **Function `get_file_size(file_path)`**: - This helper function returns the size of a file given its path. 2. **Function `distribute_files(file_paths, num_outputs)`**: - This function sorts the list of file paths by size in descending order. - It initializes 16 output files and their corresponding size counters. - For each file in the sorted list, it finds the output file with the smallest current size and appends the file's contents to it, updating the size counter accordingly. - Finally, it closes all the output files. 3. **Function `main()`**: - This function reads the list of file paths from the file `/tmp/files`. - It then calls `distribute_files` with the list of file paths and the number of output files (`16`). ### Usage: 1. Save the script to a file, for example, `merge_and_split.py`. 2. Ensure the list of file paths is correctly formatted in `/tmp/files`. 3. Run the script using Python: 
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This script will create 16 output files in `/tmp/` named `merged_0` to `merged_15`, each containing approximately equal amounts of data from the source files.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def distribute_files(file_paths, num_outputs):
    # Sort files by size in descending order
    sorted_files = sorted(file_paths, key=get_file_size, reverse=True)
    
    # Initialize the output files and their sizes
    output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(num_outputs)]
    output_sizes = [0] * num_outputs
    
    # Distribute files to the smallest output file
    for file_path in sorted_files:
        # Find the index of the smallest output file
        smallest_index = output_sizes.index(min(output_sizes))
        
        # Read the content of the current file
        with open(file_path, 'rb') as f:
            content = f.read()
        
        # Write the content to the chosen output file
        output_files[smallest_index].write(content)
        
        # Update the size of the chosen output file
        output_sizes[smallest_index] += get_file_size(file_path)
    
    # Close all the output files
    for f in output_files:
        f.close()

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

    # Number of output files
    num_outputs = 16
    
    # Distribute files into output files
    distribute_files(file_paths, num_outputs)

if __name__ == '__main__':
    main()

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def distribute_files(file_paths, num_outputs):
    # Sort files by size in descending order
    sorted_files = sorted(file_paths, key=get_file_size, reverse=True)
    
    # Initialize the output files and their sizes
    output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(num_outputs)]
    output_sizes = [0] * num_outputs
    
    # Distribute files to the smallest output file
    for file_path in sorted_files:
        # Find the index of the smallest output file
        smallest_index = output_sizes.index(min(output_sizes))
        
        # Read the content of the current file
        with open(file_path, 'rb') as f:
            content = f.read()
        
        # Write the content to the chosen output file
        output_files[smallest_index].write(content)
        
        # Update the size of the chosen output file
        output_sizes[smallest_index] += get_file_size(file_path)
    
    # Close all the output files
    for f in output_files:
        f.close()

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

    # Number of output files
    num_outputs = 16
    
    # Distribute files into output files
    distribute_files(file_paths, num_outputs)

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

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 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

Certainly! Below is a Python script that accomplishes the task described. This script reads the file paths from `/tmp/files`, sorts them by size in descending order, and distributes their contents into 16 files (`/tmp/merged_0` to `/tmp/merged_15`) such that each file is approximately the same size. 

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import os

def get_file_sizes(file_paths):
    file_sizes = []
    for file_path in file_paths:
        size = os.path.getsize(file_path)
        file_sizes.append((size, file_path))
    return file_sizes

def distribute_files(file_sizes, num_files):
    merged_files = [[] for _ in range(num_files)]
    merged_sizes = [0] * num_files
    
    for size, file_path in file_sizes:
        # Find the index of the smallest merged file
        min_index = merged_sizes.index(min(merged_sizes))
        # Add this file to the smallest merged file
        merged_files[min_index].append(file_path)
        merged_sizes[min_index] += size
    
    return merged_files

def main():
    input_file_path = "/tmp/files"
    output_dir = "/tmp"
    num_output_files = 16

    with open(input_file_path, 'r') as f:
        file_paths = [line.strip() for line in f if line.strip()]
    
    # Get file sizes and sort by size (largest first)
    file_sizes = get_file_sizes(file_paths)
    file_sizes.sort(reverse=True, key=lambda x: x[0])
    
    # Distribute files among the output files
    distributed_files = distribute_files(file_sizes, num_output_files)
    
    # Merge the files into the output files
    for i in range(num_output_files):
        output_file_path = os.path.join(output_dir, f"merged_{i}")
        with open(output_file_path, 'wb') as output_file:
            for file_path in distributed_files[i]:
                with open(file_path, 'rb') as input_file:
                    output_file.write(input_file.read())

if __name__ == "__main__":
    main()
### Explanation: 1. **Reading File Paths**: - The script reads the file paths from `/tmp/files` and stores them in a list, stripping any extra whitespace. 2. **Getting File Sizes**: - The `get_file_sizes` function takes a list of file paths and returns a list of tuples containing the file size and the file path. 3. **Sorting by Size**: - The script sorts the list of file sizes in descending order based on the size. 4. **Distributing Files**: - The `distribute_files` function distributes the files into 16 lists (one for each merged file). It always adds the next file to the currently smallest merged file to keep the sizes balanced. 5. **Merging Files**: - The script merges the content of the distributed files into the output files named `/tmp/merged_0` through `/tmp/merged_15`. ### Execution - Save the script to a file (e.g., `merge_files.py`) and execute it using Python: 
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Ensure that you have appropriate permissions to read the files in `/tmp/files` and write to `/tmp/merged_*`.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_sizes(file_paths):
    file_sizes = []
    for file_path in file_paths:
        size = os.path.getsize(file_path)
        file_sizes.append((size, file_path))
    return file_sizes

def distribute_files(file_sizes, num_files):
    merged_files = [[] for _ in range(num_files)]
    merged_sizes = [0] * num_files
    
    for size, file_path in file_sizes:
        # Find the index of the smallest merged file
        min_index = merged_sizes.index(min(merged_sizes))
        # Add this file to the smallest merged file
        merged_files[min_index].append(file_path)
        merged_sizes[min_index] += size
    
    return merged_files

def main():
    input_file_path = "/tmp/files"
    output_dir = "/tmp"
    num_output_files = 16

    with open(input_file_path, 'r') as f:
        file_paths = [line.strip() for line in f if line.strip()]
    
    # Get file sizes and sort by size (largest first)
    file_sizes = get_file_sizes(file_paths)
    file_sizes.sort(reverse=True, key=lambda x: x[0])
    
    # Distribute files among the output files
    distributed_files = distribute_files(file_sizes, num_output_files)
    
    # Merge the files into the output files
    for i in range(num_output_files):
        output_file_path = os.path.join(output_dir, f"merged_{i}")
        with open(output_file_path, 'wb') as output_file:
            for file_path in distributed_files[i]:
                with open(file_path, 'rb') as input_file:
                    output_file.write(input_file.read())

if __name__ == "__main__":
    main()

Run Code Interpreter

Running the following program: 

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import os

def get_file_sizes(file_paths):
    file_sizes = []
    for file_path in file_paths:
        size = os.path.getsize(file_path)
        file_sizes.append((size, file_path))
    return file_sizes

def distribute_files(file_sizes, num_files):
    merged_files = [[] for _ in range(num_files)]
    merged_sizes = [0] * num_files
    
    for size, file_path in file_sizes:
        # Find the index of the smallest merged file
        min_index = merged_sizes.index(min(merged_sizes))
        # Add this file to the smallest merged file
        merged_files[min_index].append(file_path)
        merged_sizes[min_index] += size
    
    return merged_files

def main():
    input_file_path = "/tmp/files"
    output_dir = "/tmp"
    num_output_files = 16

    with open(input_file_path, 'r') as f:
        file_paths = [line.strip() for line in f if line.strip()]
    
    # Get file sizes and sort by size (largest first)
    file_sizes = get_file_sizes(file_paths)
    file_sizes.sort(reverse=True, key=lambda x: x[0])
    
    # Distribute files among the output files
    distributed_files = distribute_files(file_sizes, num_output_files)
    
    # Merge the files into the output files
    for i in range(num_output_files):
        output_file_path = os.path.join(output_dir, f"merged_{i}")
        with open(output_file_path, 'wb') as output_file:
            for file_path in distributed_files[i]:
                with open(file_path, 'rb') as input_file:
                    output_file.write(input_file.read())

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

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 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

Sure, here's a Python script that reads the file paths from `/tmp/files`, sorts them by size, and then merges and splits the contents into 16 approximately equal-sized files. The script ensures that the distribution of file sizes is balanced by always adding the next largest file to the currently smallest output file. 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_path):
    with open(file_path, 'r') as f:
        return [line.strip() for line in f]

def main():
    input_list_file = '/tmp/files'
    output_files = [f'/tmp/merged_{i}' for i in range(16)]
    
    file_paths = read_file_paths(input_list_file)
    file_paths.sort(key=get_file_size, reverse=True)
    
    output_handlers = [open(file, 'wb') for file in output_files]
    output_sizes = [0] * 16
    
    for file_path in file_paths:
        smallest_index = output_sizes.index(min(output_sizes))
        with open(file_path, 'rb') as input_file:
            content = input_file.read()
            output_handlers[smallest_index].write(content)
            output_sizes[smallest_index] += len(content)
    
    for handler in output_handlers:
        handler.close()

if __name__ == '__main__':
    main()
### Explanation: 1. **`get_file_size(file_path)`**: - This function returns the size of the file at the given path. 2. **`read_file_paths(file_path)`**: - This function reads and returns a list of file paths from the given file, where each path is on a new line. 3. **`main()`**: - The script reads the list of file paths from `/tmp/files`. - It sorts the file paths by the size of each file in descending order. - It opens 16 output files for writing in binary mode (`wb`). - It iterates over each file path, reading its contents and writing it to the currently smallest output file (determined by the size of contents already written to it). - After processing all files, it closes all output file handlers. ### How to Run the Script: 1. Save the script to a file, e.g., `merge_files.py`. 2. Ensure the file `/tmp/files` exists and contains the list of file paths. 3. Run the script using Python: 
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   python merge_files.py
This script ensures that the contents are evenly distributed among the 16 output files by always adding the next largest input file to the currently smallest output file.

Extract Code

I extracted the following code from that output: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_path):
    with open(file_path, 'r') as f:
        return [line.strip() for line in f]

def main():
    input_list_file = '/tmp/files'
    output_files = [f'/tmp/merged_{i}' for i in range(16)]
    
    file_paths = read_file_paths(input_list_file)
    file_paths.sort(key=get_file_size, reverse=True)
    
    output_handlers = [open(file, 'wb') for file in output_files]
    output_sizes = [0] * 16
    
    for file_path in file_paths:
        smallest_index = output_sizes.index(min(output_sizes))
        with open(file_path, 'rb') as input_file:
            content = input_file.read()
            output_handlers[smallest_index].write(content)
            output_sizes[smallest_index] += len(content)
    
    for handler in output_handlers:
        handler.close()

if __name__ == '__main__':
    main()

Run Code Interpreter

Running the following program: 

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import os

def get_file_size(file_path):
    return os.path.getsize(file_path)

def read_file_paths(file_path):
    with open(file_path, 'r') as f:
        return [line.strip() for line in f]

def main():
    input_list_file = '/tmp/files'
    output_files = [f'/tmp/merged_{i}' for i in range(16)]
    
    file_paths = read_file_paths(input_list_file)
    file_paths.sort(key=get_file_size, reverse=True)
    
    output_handlers = [open(file, 'wb') for file in output_files]
    output_sizes = [0] * 16
    
    for file_path in file_paths:
        smallest_index = output_sizes.index(min(output_sizes))
        with open(file_path, 'rb') as input_file:
            content = input_file.read()
            output_handlers[smallest_index].write(content)
            output_sizes[smallest_index] += len(content)
    
    for handler in output_handlers:
        handler.close()

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

PyFunc

final: True Resulting in output: True