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

To accomplish this task, we can follow these steps in a Python script: 1. **Read the list of file paths** from `/tmp/files`. 2. **Determine the size of each file** in the list and sort them by size in descending order. 3. **Merge and split the content** by allocating files to the 16 output files in a way that keeps the total size of each output file approximately the same. Here's how you could implement the script: 

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import os

# Step 1: Read the list of file paths
with open('/tmp/files', 'r') as file_list:
    file_paths = [line.strip() for line in file_list]

# Step 2: Determine the size of each file and sort them by size (largest first)
file_sizes = [(path, os.path.getsize(path)) for path in file_paths]
sorted_files_by_size = sorted(file_sizes, key=lambda x: x[1], reverse=True)

# Prepare data structures for managing the merged files.
output_files_info = [{'filename': f'/tmp/merged_{i}', 'size': 0, 'contents': []} for i in range(16)]

# Step 3: Merge and split the content
for file_path, size in sorted_files_by_size:
    # Find the output file with the smallest current total size.
    smallest_output_file = min(output_files_info, key=lambda x: x['size'])
    
    # Update the chosen output file's information.
    smallest_output_file['size'] += size
    smallest_output_file['contents'].append(file_path)

# Write the contents to the respective files.
for output_file in output_files_info:
    with open(output_file['filename'], 'wb') as merged_file:
        for content_path in output_file['contents']:
            with open(content_path, 'rb') as content_file:
                # Read and write the entire content to the merged file.
                merged_file.write(content_file.read())

print("Merging and splitting done.")
### Notes: - This script reads the list of file paths from `/tmp/files`, assumes one file path per line, and trims any whitespace. - It calculates the size of each file and sorts them in descending order by size. - The script then distributes these files across 16 output files, aiming to keep the total size of each approximately equal. It does this by always adding the next file to the currently smallest output file (in terms of total size). - Finally, it writes the contents of the chosen files into each of the 16 output files. The files are opened in binary mode (`'rb'` and `'wb'`) to ensure compatibility with all file types, including binary files. - Depending on the number of files and their sizes, this process may take some time, especially for large files or a large number of files. - This approach doesn't ensure the output files are exactly the same size but aims to approximate it based on the file sizes. The final sizes may vary depending on how the file sizes are distributed. Make sure you have the necessary permissions to read the files listed in `/tmp/files` and to write the output files to `/tmp/`.

Extract Code

I extracted the following code from that output: 

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import os

# Step 1: Read the list of file paths
with open('/tmp/files', 'r') as file_list:
    file_paths = [line.strip() for line in file_list]

# Step 2: Determine the size of each file and sort them by size (largest first)
file_sizes = [(path, os.path.getsize(path)) for path in file_paths]
sorted_files_by_size = sorted(file_sizes, key=lambda x: x[1], reverse=True)

# Prepare data structures for managing the merged files.
output_files_info = [{'filename': f'/tmp/merged_{i}', 'size': 0, 'contents': []} for i in range(16)]

# Step 3: Merge and split the content
for file_path, size in sorted_files_by_size:
    # Find the output file with the smallest current total size.
    smallest_output_file = min(output_files_info, key=lambda x: x['size'])
    
    # Update the chosen output file's information.
    smallest_output_file['size'] += size
    smallest_output_file['contents'].append(file_path)

# Write the contents to the respective files.
for output_file in output_files_info:
    with open(output_file['filename'], 'wb') as merged_file:
        for content_path in output_file['contents']:
            with open(content_path, 'rb') as content_file:
                # Read and write the entire content to the merged file.
                merged_file.write(content_file.read())

print("Merging and splitting done.")

Run Code Interpreter

Running the following program: 

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import os

# Step 1: Read the list of file paths
with open('/tmp/files', 'r') as file_list:
    file_paths = [line.strip() for line in file_list]

# Step 2: Determine the size of each file and sort them by size (largest first)
file_sizes = [(path, os.path.getsize(path)) for path in file_paths]
sorted_files_by_size = sorted(file_sizes, key=lambda x: x[1], reverse=True)

# Prepare data structures for managing the merged files.
output_files_info = [{'filename': f'/tmp/merged_{i}', 'size': 0, 'contents': []} for i in range(16)]

# Step 3: Merge and split the content
for file_path, size in sorted_files_by_size:
    # Find the output file with the smallest current total size.
    smallest_output_file = min(output_files_info, key=lambda x: x['size'])
    
    # Update the chosen output file's information.
    smallest_output_file['size'] += size
    smallest_output_file['contents'].append(file_path)

# Write the contents to the respective files.
for output_file in output_files_info:
    with open(output_file['filename'], 'wb') as merged_file:
        for content_path in output_file['contents']:
            with open(content_path, 'rb') as content_file:
                # Read and write the entire content to the merged file.
                merged_file.write(content_file.read())

print("Merging and splitting done.")
And got the output: Merging and splitting done.

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

The task you're asking for involves a few steps: reading the list of file paths, sorting these files by size, merging their content, and splitting the result into 16 approximately equally sized files. Below is a Python script that accomplishes this. This script assumes that the list of file paths in `/tmp/files` is accurate and that you have permission to read those files and write to the target directory. 

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import os

# Read the list of file paths
with open('/tmp/files', 'r') as file_list:
    files = file_list.read().splitlines()

# Sort files by size, largest first
files_sorted = sorted(files, key=lambda x: os.path.getsize(x), reverse=True)

# Read content of files and keep track of total size
file_contents = []
total_size = 0
for file_path in files_sorted:
    with open(file_path, 'r') as file:
        content = file.read()
        file_contents.append((file_path, content))
        total_size += len(content)

# Calculate target size for each of the 16 files
target_size = total_size // 16

# Prepare data for the merged files
merged_files = [[] for _ in range(16)]
merged_sizes = [0] * 16

# Distribute files always to the currently smallest merged file
for path, content in file_contents:
    smallest_idx = merged_sizes.index(min(merged_sizes))
    merged_files[smallest_idx].append(content)
    merged_sizes[smallest_idx] += len(content)

# Write the merged content into 16 files
for i, contents in enumerate(merged_files):
    with open(f'/tmp/merged_{i}', 'w') as merged_file:
        for content in contents:
            merged_file.write(content)

print("Merging and splitting complete.")
This script does not handle potential issues like: - Files that are too large to be read into memory all at once. - Binary files (it reads and writes as text). - Files that might not be readable due to permissions or other errors. - Ensuring the final split files are balanced as closely as possible (the script aims for approximate equality). For handling very large files or a massive number of files, consider adapting the script to work with streams or chunks of data instead of reading entire file contents into memory. Additionally, consider adding error handling to manage inaccessible files or directories gracefully.

Extract Code

I extracted the following code from that output: 

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import os

# Read the list of file paths
with open('/tmp/files', 'r') as file_list:
    files = file_list.read().splitlines()

# Sort files by size, largest first
files_sorted = sorted(files, key=lambda x: os.path.getsize(x), reverse=True)

# Read content of files and keep track of total size
file_contents = []
total_size = 0
for file_path in files_sorted:
    with open(file_path, 'r') as file:
        content = file.read()
        file_contents.append((file_path, content))
        total_size += len(content)

# Calculate target size for each of the 16 files
target_size = total_size // 16

# Prepare data for the merged files
merged_files = [[] for _ in range(16)]
merged_sizes = [0] * 16

# Distribute files always to the currently smallest merged file
for path, content in file_contents:
    smallest_idx = merged_sizes.index(min(merged_sizes))
    merged_files[smallest_idx].append(content)
    merged_sizes[smallest_idx] += len(content)

# Write the merged content into 16 files
for i, contents in enumerate(merged_files):
    with open(f'/tmp/merged_{i}', 'w') as merged_file:
        for content in contents:
            merged_file.write(content)

print("Merging and splitting complete.")

Run Code Interpreter

Running the following program: 

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import os

# Read the list of file paths
with open('/tmp/files', 'r') as file_list:
    files = file_list.read().splitlines()

# Sort files by size, largest first
files_sorted = sorted(files, key=lambda x: os.path.getsize(x), reverse=True)

# Read content of files and keep track of total size
file_contents = []
total_size = 0
for file_path in files_sorted:
    with open(file_path, 'r') as file:
        content = file.read()
        file_contents.append((file_path, content))
        total_size += len(content)

# Calculate target size for each of the 16 files
target_size = total_size // 16

# Prepare data for the merged files
merged_files = [[] for _ in range(16)]
merged_sizes = [0] * 16

# Distribute files always to the currently smallest merged file
for path, content in file_contents:
    smallest_idx = merged_sizes.index(min(merged_sizes))
    merged_files[smallest_idx].append(content)
    merged_sizes[smallest_idx] += len(content)

# Write the merged content into 16 files
for i, contents in enumerate(merged_files):
    with open(f'/tmp/merged_{i}', 'w') as merged_file:
        for content in contents:
            merged_file.write(content)

print("Merging and splitting complete.")
And got the output: Merging and splitting complete.

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

To achieve the task described, you can follow these steps in your Python script: 1. Read the list of file paths from `/tmp/files`. 2. Determine the size of each file and sort them by size in descending order. 3. Initialize 16 files for output and keep track of their sizes. 4. Iterate over the sorted list of files, adding each file's content to the output file with the smallest current size, and update the size tracking accordingly. Here's an example script that implements the above steps: 

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import os

def read_file_paths(file_list_path):
    """Read file paths from a given file and return a list of paths."""
    with open(file_list_path, 'r') as file:
        return [line.strip() for line in file.readlines()]

def get_file_sizes(file_paths):
    """Return a list of tuples (file_path, file_size) sorted by size descending."""
    file_sizes = [(file_path, os.path.getsize(file_path)) for file_path in file_paths]
    return sorted(file_sizes, key=lambda x: x[1], reverse=True)

def initialize_output_files(num_files):
    """Initialize output files and return their paths."""
    output_files = [f"/tmp/merged_{i}" for i in range(num_files)]
    # Ensure files are empty and exist
    for file_path in output_files:
        open(file_path, 'w').close()
    return output_files

def distribute_files(file_sizes, output_files):
    """Distribute files into output files based on size."""
    output_sizes = [0] * len(output_files)
    
    for file_path, size in file_sizes:
        # Find the index of the output file with the smallest current size
        smallest_idx = output_sizes.index(min(output_sizes))
        target_file = output_files[smallest_idx]
        
        # Append the content of the current file to the selected output file
        with open(file_path, 'rb') as source_file:
            content = source_file.read()
            with open(target_file, 'ab') as target:
                target.write(content)
        
        # Update the size tracking
        output_sizes[smallest_idx] += size

def main():
    file_list_path = '/tmp/files'
    num_output_files = 16
    
    # Step 1: Read file paths
    file_paths = read_file_paths(file_list_path)
    
    # Step 2: Get sorted file sizes
    file_sizes = get_file_sizes(file_paths)
    
    # Step 3: Initialize output files
    output_files = initialize_output_files(num_output_files)
    
    # Step 4: Distribute files
    distribute_files(file_sizes, output_files)
    
    print("Distribution complete.")

if __name__ == '__main__':
    main()
Notes: - This script assumes all files are readable and fit into memory, as it reads entire files to distribute their contents. If you're working with very large files, you might need to adapt the script to read and write in chunks. - The script initializes the output files to ensure they exist and are empty before starting to append content. - It uses binary mode (`'rb'` and `'ab'`) for reading and writing files to handle all types of files correctly, including binary files. - The script evenly distributes files based on their size to achieve approximately equal-sized output files, but depending on the sizes of your input files, the resulting files might not be perfectly equal in size.

Extract Code

I extracted the following code from that output: 

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import os

def read_file_paths(file_list_path):
    """Read file paths from a given file and return a list of paths."""
    with open(file_list_path, 'r') as file:
        return [line.strip() for line in file.readlines()]

def get_file_sizes(file_paths):
    """Return a list of tuples (file_path, file_size) sorted by size descending."""
    file_sizes = [(file_path, os.path.getsize(file_path)) for file_path in file_paths]
    return sorted(file_sizes, key=lambda x: x[1], reverse=True)

def initialize_output_files(num_files):
    """Initialize output files and return their paths."""
    output_files = [f"/tmp/merged_{i}" for i in range(num_files)]
    # Ensure files are empty and exist
    for file_path in output_files:
        open(file_path, 'w').close()
    return output_files

def distribute_files(file_sizes, output_files):
    """Distribute files into output files based on size."""
    output_sizes = [0] * len(output_files)
    
    for file_path, size in file_sizes:
        # Find the index of the output file with the smallest current size
        smallest_idx = output_sizes.index(min(output_sizes))
        target_file = output_files[smallest_idx]
        
        # Append the content of the current file to the selected output file
        with open(file_path, 'rb') as source_file:
            content = source_file.read()
            with open(target_file, 'ab') as target:
                target.write(content)
        
        # Update the size tracking
        output_sizes[smallest_idx] += size

def main():
    file_list_path = '/tmp/files'
    num_output_files = 16
    
    # Step 1: Read file paths
    file_paths = read_file_paths(file_list_path)
    
    # Step 2: Get sorted file sizes
    file_sizes = get_file_sizes(file_paths)
    
    # Step 3: Initialize output files
    output_files = initialize_output_files(num_output_files)
    
    # Step 4: Distribute files
    distribute_files(file_sizes, output_files)
    
    print("Distribution complete.")

if __name__ == '__main__':
    main()

Run Code Interpreter

Running the following program: 

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import os

def read_file_paths(file_list_path):
    """Read file paths from a given file and return a list of paths."""
    with open(file_list_path, 'r') as file:
        return [line.strip() for line in file.readlines()]

def get_file_sizes(file_paths):
    """Return a list of tuples (file_path, file_size) sorted by size descending."""
    file_sizes = [(file_path, os.path.getsize(file_path)) for file_path in file_paths]
    return sorted(file_sizes, key=lambda x: x[1], reverse=True)

def initialize_output_files(num_files):
    """Initialize output files and return their paths."""
    output_files = [f"/tmp/merged_{i}" for i in range(num_files)]
    # Ensure files are empty and exist
    for file_path in output_files:
        open(file_path, 'w').close()
    return output_files

def distribute_files(file_sizes, output_files):
    """Distribute files into output files based on size."""
    output_sizes = [0] * len(output_files)
    
    for file_path, size in file_sizes:
        # Find the index of the output file with the smallest current size
        smallest_idx = output_sizes.index(min(output_sizes))
        target_file = output_files[smallest_idx]
        
        # Append the content of the current file to the selected output file
        with open(file_path, 'rb') as source_file:
            content = source_file.read()
            with open(target_file, 'ab') as target:
                target.write(content)
        
        # Update the size tracking
        output_sizes[smallest_idx] += size

def main():
    file_list_path = '/tmp/files'
    num_output_files = 16
    
    # Step 1: Read file paths
    file_paths = read_file_paths(file_list_path)
    
    # Step 2: Get sorted file sizes
    file_sizes = get_file_sizes(file_paths)
    
    # Step 3: Initialize output files
    output_files = initialize_output_files(num_output_files)
    
    # Step 4: Distribute files
    distribute_files(file_sizes, output_files)
    
    print("Distribution complete.")

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

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

To accomplish this task, we will follow these steps: 1. Read the file paths from `/tmp/files`. 2. Determine the size of each file and sort them by size in descending order. 3. Initialize 16 output files and keep track of their sizes. 4. Iterate over the sorted list of file paths and append each file's content to the currently smallest output file. 5. Ensure the output files are approximately the same size by always adding to the smallest one. Here's a Python script that does this: 

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import os

# Step 1: Read the file paths
with open('/tmp/files', 'r') as file_list:
    files = file_list.read().splitlines()

# Step 2: Sort files by size in descending order
files_with_sizes = [(file_path, os.path.getsize(file_path)) for file_path in files]
sorted_files_with_sizes = sorted(files_with_sizes, key=lambda x: x[1], reverse=True)

# Step 3: Initialize 16 output files and keep track of their sizes
output_files = ['/tmp/merged_%d' % i for i in range(16)]
output_files_sizes = {output_file: 0 for output_file in output_files}

def get_smallest_file():
    """Returns the path of the smallest file."""
    return min(output_files_sizes, key=output_files_sizes.get)

# Step 4: Append each file's content to the smallest output file
for file_path, size in sorted_files_with_sizes:
    smallest_output_file = get_smallest_file()
    with open(file_path, 'r') as input_file:
        with open(smallest_output_file, 'a') as output_file:
            output_file.write(input_file.read())
    output_files_sizes[smallest_output_file] += size

print("Merge and split task completed.")
Important notes: - This script reads each file entirely into memory before writing it out. For very large files, this might not be efficient or even possible due to memory constraints. If you're dealing with extremely large files, consider reading and writing in chunks. - The script assumes that all files are text files and can be read with the default encoding. If you have binary files or files with a specific encoding, you'll need to adjust the file reading/writing mode and possibly specify encoding parameters. - The script sorts files by size to ensure a more balanced distribution across the output files. However, depending on the exact sizes and distribution of your input files, the output files might not be perfectly equal in size, but they should be approximately the same size. - The script appends to the output files in 'append' mode ('a'). If you run the script multiple times, it will continue adding to the existing output files. If you intend to run this script multiple times with different sets of input files, you might want to clear the output files at the beginning of the script or use a different naming scheme to avoid mixing different batches of input files.

Extract Code

I extracted the following code from that output: 

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import os

# Step 1: Read the file paths
with open('/tmp/files', 'r') as file_list:
    files = file_list.read().splitlines()

# Step 2: Sort files by size in descending order
files_with_sizes = [(file_path, os.path.getsize(file_path)) for file_path in files]
sorted_files_with_sizes = sorted(files_with_sizes, key=lambda x: x[1], reverse=True)

# Step 3: Initialize 16 output files and keep track of their sizes
output_files = ['/tmp/merged_%d' % i for i in range(16)]
output_files_sizes = {output_file: 0 for output_file in output_files}

def get_smallest_file():
    """Returns the path of the smallest file."""
    return min(output_files_sizes, key=output_files_sizes.get)

# Step 4: Append each file's content to the smallest output file
for file_path, size in sorted_files_with_sizes:
    smallest_output_file = get_smallest_file()
    with open(file_path, 'r') as input_file:
        with open(smallest_output_file, 'a') as output_file:
            output_file.write(input_file.read())
    output_files_sizes[smallest_output_file] += size

print("Merge and split task completed.")

Run Code Interpreter

Running the following program: 

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import os

# Step 1: Read the file paths
with open('/tmp/files', 'r') as file_list:
    files = file_list.read().splitlines()

# Step 2: Sort files by size in descending order
files_with_sizes = [(file_path, os.path.getsize(file_path)) for file_path in files]
sorted_files_with_sizes = sorted(files_with_sizes, key=lambda x: x[1], reverse=True)

# Step 3: Initialize 16 output files and keep track of their sizes
output_files = ['/tmp/merged_%d' % i for i in range(16)]
output_files_sizes = {output_file: 0 for output_file in output_files}

def get_smallest_file():
    """Returns the path of the smallest file."""
    return min(output_files_sizes, key=output_files_sizes.get)

# Step 4: Append each file's content to the smallest output file
for file_path, size in sorted_files_with_sizes:
    smallest_output_file = get_smallest_file()
    with open(file_path, 'r') as input_file:
        with open(smallest_output_file, 'a') as output_file:
            output_file.write(input_file.read())
    output_files_sizes[smallest_output_file] += size

print("Merge and split task completed.")
And got the output: Merge and split task completed.

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

To create a Python script that achieves the task you've outlined, you will need to follow these steps: 1. **Read the list of file paths** from `/tmp/files`. 2. **Calculate the size of each file** and sort them by size in descending order. 3. **Distribute the files** across 16 output files in a way that the total size of each output file is approximately equal. This can be achieved by always appending to the currently smallest output file (a variation of the bin packing problem). 4. **Merge the contents** of the files into the 16 output files accordingly. Below is a Python script that implements the above logic: 

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import os

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

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

def sort_files_by_size(file_paths):
    return sorted(file_paths, key=get_file_size, reverse=True)

def initialize_output_files(base_path, count=16):
    return {i: {'path': f'{base_path}_{i}', 'size': 0} for i in range(count)}

def find_smallest_file(output_files):
    return min(output_files, key=lambda x: output_files[x]['size'])

def distribute_files(sorted_files, output_files):
    for file_path in sorted_files:
        smallest_file_index = find_smallest_file(output_files)
        with open(file_path, 'rb') as src, open(output_files[smallest_file_index]['path'], 'ab') as dest:
            contents = src.read()
            dest.write(contents)
        output_files[smallest_file_index]['size'] += get_file_size(file_path)

def main():
    file_list_path = '/tmp/files'
    output_base_path = '/tmp/merged'
    
    file_paths = read_file_paths(file_list_path)
    sorted_files = sort_files_by_size(file_paths)
    output_files = initialize_output_files(output_base_path)
    
    distribute_files(sorted_files, output_files)
    print("Files have been successfully distributed and merged.")

if __name__ == "__main__":
    main()
This script does the following: - Reads the list of file paths from `/tmp/files`. - Sorts these files by size in descending order. - Initializes 16 output files (in a conceptual sense, as it prepares a dictionary to track their paths and sizes). - Finds the currently smallest output file and appends the next file in the sorted list to it. - Continues this process until all files have been distributed. Please be aware that this script opens multiple files for appending in binary mode (`'ab'`). If any of the output files already exist, this script will append to them. If you want to start from scratch every time, you might want to add a step to delete or truncate the existing output files at the beginning of the script. Also, keep in mind that "approximately the same size" is an approximate target due to the nature of the bin packing problem, especially given the varying sizes of the input files and the approach used to distribute them. Depending on your specific requirements, you may need to adjust the logic to better fit your needs.

Extract Code

I extracted the following code from that output: 

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import os

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

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

def sort_files_by_size(file_paths):
    return sorted(file_paths, key=get_file_size, reverse=True)

def initialize_output_files(base_path, count=16):
    return {i: {'path': f'{base_path}_{i}', 'size': 0} for i in range(count)}

def find_smallest_file(output_files):
    return min(output_files, key=lambda x: output_files[x]['size'])

def distribute_files(sorted_files, output_files):
    for file_path in sorted_files:
        smallest_file_index = find_smallest_file(output_files)
        with open(file_path, 'rb') as src, open(output_files[smallest_file_index]['path'], 'ab') as dest:
            contents = src.read()
            dest.write(contents)
        output_files[smallest_file_index]['size'] += get_file_size(file_path)

def main():
    file_list_path = '/tmp/files'
    output_base_path = '/tmp/merged'
    
    file_paths = read_file_paths(file_list_path)
    sorted_files = sort_files_by_size(file_paths)
    output_files = initialize_output_files(output_base_path)
    
    distribute_files(sorted_files, output_files)
    print("Files have been successfully distributed and merged.")

if __name__ == "__main__":
    main()

Run Code Interpreter

Running the following program: 

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import os

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

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

def sort_files_by_size(file_paths):
    return sorted(file_paths, key=get_file_size, reverse=True)

def initialize_output_files(base_path, count=16):
    return {i: {'path': f'{base_path}_{i}', 'size': 0} for i in range(count)}

def find_smallest_file(output_files):
    return min(output_files, key=lambda x: output_files[x]['size'])

def distribute_files(sorted_files, output_files):
    for file_path in sorted_files:
        smallest_file_index = find_smallest_file(output_files)
        with open(file_path, 'rb') as src, open(output_files[smallest_file_index]['path'], 'ab') as dest:
            contents = src.read()
            dest.write(contents)
        output_files[smallest_file_index]['size'] += get_file_size(file_path)

def main():
    file_list_path = '/tmp/files'
    output_base_path = '/tmp/merged'
    
    file_paths = read_file_paths(file_list_path)
    sorted_files = sort_files_by_size(file_paths)
    output_files = initialize_output_files(output_base_path)
    
    distribute_files(sorted_files, output_files)
    print("Files have been successfully distributed and merged.")

if __name__ == "__main__":
    main()
And got the output: Files have been successfully distributed and merged.

PyFunc

final: True Resulting in output: True