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

Here's a Python script that will merge the contents of the files listed in `/tmp/files` into 16 files named `/tmp/merged_0` through `/tmp/merged_15`, ensuring that each merged file is approximately the same size: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize variables
current_merged_file = 0
current_size = 0

# Open the first merged file
output = open(f'/tmp/merged_{current_merged_file}', 'wb')

# Process each file
for file_path in file_paths:
    # Read the content of the current file
    with open(file_path, 'rb') as f:
        content = f.read()
    
    # Write content to the current merged file
    output.write(content)
    current_size += len(content)
    
    # If current merged file exceeds target size, move to next merged file
    if current_size >= target_size and current_merged_file < 15:
        output.close()
        current_merged_file += 1
        current_size = 0
        output = open(f'/tmp/merged_{current_merged_file}', 'wb')

# Close the last merged file
output.close()

print(f"Merged contents into 16 files: /tmp/merged_0 through /tmp/merged_15")
This script does the following: 1. It reads the list of file paths from `/tmp/files`. 2. It calculates the total size of all files to determine the target size for each merged file. 3. It iterates through each file path, reading its content and writing it to the current merged file. 4. When the current merged file reaches or exceeds the target size, it closes that file and opens the next one (unless it's already at the last file). 5. It continues this process until all files have been processed. 6. Finally, it closes the last merged file. This approach ensures that each merged file is as close to the same size as possible, given the constraint of 16 output files. Note that the last file might be slightly smaller than the others if the total content doesn't divide evenly. Make sure you have read and write permissions for the `/tmp` directory and all the files listed in `/tmp/files`. Also, ensure that you have enough disk space in the `/tmp` directory to store the merged files.

Extract Code

I extracted the following code from that output: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize variables
current_merged_file = 0
current_size = 0

# Open the first merged file
output = open(f'/tmp/merged_{current_merged_file}', 'wb')

# Process each file
for file_path in file_paths:
    # Read the content of the current file
    with open(file_path, 'rb') as f:
        content = f.read()
    
    # Write content to the current merged file
    output.write(content)
    current_size += len(content)
    
    # If current merged file exceeds target size, move to next merged file
    if current_size >= target_size and current_merged_file < 15:
        output.close()
        current_merged_file += 1
        current_size = 0
        output = open(f'/tmp/merged_{current_merged_file}', 'wb')

# Close the last merged file
output.close()

print(f"Merged contents into 16 files: /tmp/merged_0 through /tmp/merged_15")

Run Code Interpreter

Running the following program: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize variables
current_merged_file = 0
current_size = 0

# Open the first merged file
output = open(f'/tmp/merged_{current_merged_file}', 'wb')

# Process each file
for file_path in file_paths:
    # Read the content of the current file
    with open(file_path, 'rb') as f:
        content = f.read()
    
    # Write content to the current merged file
    output.write(content)
    current_size += len(content)
    
    # If current merged file exceeds target size, move to next merged file
    if current_size >= target_size and current_merged_file < 15:
        output.close()
        current_merged_file += 1
        current_size = 0
        output = open(f'/tmp/merged_{current_merged_file}', 'wb')

# Close the last merged file
output.close()

print(f"Merged contents into 16 files: /tmp/merged_0 through /tmp/merged_15")
And got the output: Merged contents into 16 files: /tmp/merged_0 through /tmp/merged_15

PyFunc

final: False Resulting in output: False

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

Here's a Python script that will merge the contents of the files listed in `/tmp/files` into 16 approximately equal-sized files named `/tmp/merged_0` through `/tmp/merged_15`: 

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import os
from itertools import cycle

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = total_size // 16

# Create 16 output files
output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(16)]
output_sizes = [0] * 16

# Use cycle to round-robin through output files
output_cycle = cycle(range(16))

# Merge files
for file_path in file_paths:
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        
        while content:
            i = next(output_cycle)
            
            # If this output file is at or over the target size, move to the next one
            while output_sizes[i] >= target_size and content:
                i = next(output_cycle)
            
            # Write to the selected output file
            chunk_size = min(len(content), target_size - output_sizes[i])
            output_files[i].write(content[:chunk_size])
            output_sizes[i] += chunk_size
            content = content[chunk_size:]

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

print("Merging complete.")
print("Sizes of merged files:")
for i in range(16):
    print(f"/tmp/merged_{i}: {output_sizes[i]} bytes")
This script does the following: 1. Reads the list of file paths from `/tmp/files`. 2. Calculates the total size of all input files. 3. Determines the target size for each output file (total size divided by 16). 4. Creates 16 output files named `/tmp/merged_0` through `/tmp/merged_15`. 5. Iterates through each input file: - Reads the content of the file. - Distributes the content among the output files in a round-robin fashion. - Ensures that each output file doesn't exceed the target size (unless necessary). 6. Closes all output files. 7. Prints the sizes of the merged files for verification. This approach ensures that: - All input files are processed. - The content is distributed as evenly as possible among the 16 output files. - The script handles large files efficiently by reading and writing in chunks. Note: This script assumes that you have read and write permissions for the input and output files. Also, make sure you have enough disk space to store the merged files.

Extract Code

I extracted the following code from that output: 

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import os
from itertools import cycle

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = total_size // 16

# Create 16 output files
output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(16)]
output_sizes = [0] * 16

# Use cycle to round-robin through output files
output_cycle = cycle(range(16))

# Merge files
for file_path in file_paths:
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        
        while content:
            i = next(output_cycle)
            
            # If this output file is at or over the target size, move to the next one
            while output_sizes[i] >= target_size and content:
                i = next(output_cycle)
            
            # Write to the selected output file
            chunk_size = min(len(content), target_size - output_sizes[i])
            output_files[i].write(content[:chunk_size])
            output_sizes[i] += chunk_size
            content = content[chunk_size:]

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

print("Merging complete.")
print("Sizes of merged files:")
for i in range(16):
    print(f"/tmp/merged_{i}: {output_sizes[i]} bytes")

Run Code Interpreter

Running the following program: 

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import os
from itertools import cycle

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = total_size // 16

# Create 16 output files
output_files = [open(f'/tmp/merged_{i}', 'wb') for i in range(16)]
output_sizes = [0] * 16

# Use cycle to round-robin through output files
output_cycle = cycle(range(16))

# Merge files
for file_path in file_paths:
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        
        while content:
            i = next(output_cycle)
            
            # If this output file is at or over the target size, move to the next one
            while output_sizes[i] >= target_size and content:
                i = next(output_cycle)
            
            # Write to the selected output file
            chunk_size = min(len(content), target_size - output_sizes[i])
            output_files[i].write(content[:chunk_size])
            output_sizes[i] += chunk_size
            content = content[chunk_size:]

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

print("Merging complete.")
print("Sizes of merged files:")
for i in range(16):
    print(f"/tmp/merged_{i}: {output_sizes[i]} bytes")
And got the output: Timeout: function took too long to complete

PyFunc

final: False Resulting in output: False

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

Here's a Python script that merges the content of the files listed in `/tmp/files` into 16 files named `/tmp/merged_0` through `/tmp/merged_15`, ensuring that each merged file is approximately the same size: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize variables
current_file = 0
current_size = 0

# Open the first output file
output = open(f'/tmp/merged_{current_file}', 'wb')

# Process each input file
for file_path in file_paths:
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        
        # If adding this file would exceed the target size, move to next output file
        if current_size + len(content) > target_size and current_file < 15:
            output.close()
            current_file += 1
            current_size = 0
            output = open(f'/tmp/merged_{current_file}', 'wb')
        
        # Write content to current output file
        output.write(content)
        current_size += len(content)

# Close the last output file
output.close()

print(f"Merged files into 16 files: /tmp/merged_0 through /tmp/merged_15")
This script does the following: 1. It reads the list of file paths from `/tmp/files`. 2. It calculates the total size of all input files. 3. It determines the target size for each merged file by dividing the total size by 16 and rounding up. 4. It then processes each input file: - It reads the content of the input file. - If adding this content to the current output file would exceed the target size (and we haven't reached the last output file), it closes the current output file and opens the next one. - It writes the content to the current output file. 5. Finally, it closes the last output file. This approach ensures that: - All content from the input files is preserved. - The content is distributed across 16 files. - Each merged file is as close to the target size as possible, making them approximately equal in size. Note: This script assumes that you have permission to read the input files and write to the `/tmp` directory. Also, it reads entire files into memory, which could be an issue for very large files. For extremely large files or datasets, you might need to modify the script to read and write in smaller chunks.

Extract Code

I extracted the following code from that output: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize variables
current_file = 0
current_size = 0

# Open the first output file
output = open(f'/tmp/merged_{current_file}', 'wb')

# Process each input file
for file_path in file_paths:
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        
        # If adding this file would exceed the target size, move to next output file
        if current_size + len(content) > target_size and current_file < 15:
            output.close()
            current_file += 1
            current_size = 0
            output = open(f'/tmp/merged_{current_file}', 'wb')
        
        # Write content to current output file
        output.write(content)
        current_size += len(content)

# Close the last output file
output.close()

print(f"Merged files into 16 files: /tmp/merged_0 through /tmp/merged_15")

Run Code Interpreter

Running the following program: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize variables
current_file = 0
current_size = 0

# Open the first output file
output = open(f'/tmp/merged_{current_file}', 'wb')

# Process each input file
for file_path in file_paths:
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        
        # If adding this file would exceed the target size, move to next output file
        if current_size + len(content) > target_size and current_file < 15:
            output.close()
            current_file += 1
            current_size = 0
            output = open(f'/tmp/merged_{current_file}', 'wb')
        
        # Write content to current output file
        output.write(content)
        current_size += len(content)

# Close the last output file
output.close()

print(f"Merged files into 16 files: /tmp/merged_0 through /tmp/merged_15")
And got the output: Merged files into 16 files: /tmp/merged_0 through /tmp/merged_15

PyFunc

final: False Resulting in output: False

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

Here's a Python script that will merge the contents of the files listed in /tmp/files into 16 files named /tmp/merged_0 through /tmp/merged_15, ensuring that each merged file is approximately the same size: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize counters and current merged file
current_size = 0
current_file_index = 0
output_file = None

# Process each file
for file_path in file_paths:
    # Open a new merged file if necessary
    if output_file is None:
        output_file = open(f'/tmp/merged_{current_file_index}', 'wb')

    # Read and write the content of the current file
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        output_file.write(content)

    # Update current size
    current_size += len(content)

    # Check if we need to start a new merged file
    if current_size >= target_size:
        output_file.close()
        current_file_index += 1
        current_size = 0
        output_file = None

        # Break if we've created all 16 files
        if current_file_index >= 16:
            break

# Close the last file if it's still open
if output_file is not None:
    output_file.close()

print(f"Merged contents into {current_file_index + 1} files.")
This script does the following: 1. It reads the list of file paths from '/tmp/files'. 2. It calculates the total size of all files to determine the target size for each merged file. 3. It iterates through each file path, reading its content and writing it to the current merged file. 4. When the current merged file reaches or exceeds the target size, it closes that file and starts a new one. 5. It continues this process until all input files have been processed or all 16 merged files have been created. 6. If the last merged file is still open after processing all input files, it closes it. 7. Finally, it prints how many merged files were created. This approach ensures that the merged files are as close to the same size as possible, given the sizes of the input files. Note that if there are fewer than 16 files worth of content in the input, fewer than 16 merged files will be created. Also, this script uses binary mode ('rb' and 'wb') for reading and writing files to handle both text and binary files correctly. If you're certain all your files are text files, you can change 'rb' to 'r' and 'wb' to 'w'. Remember to run this script with appropriate permissions to read from '/tmp/files' and write to '/tmp/merged_*'.

Extract Code

I extracted the following code from that output: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize counters and current merged file
current_size = 0
current_file_index = 0
output_file = None

# Process each file
for file_path in file_paths:
    # Open a new merged file if necessary
    if output_file is None:
        output_file = open(f'/tmp/merged_{current_file_index}', 'wb')

    # Read and write the content of the current file
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        output_file.write(content)

    # Update current size
    current_size += len(content)

    # Check if we need to start a new merged file
    if current_size >= target_size:
        output_file.close()
        current_file_index += 1
        current_size = 0
        output_file = None

        # Break if we've created all 16 files
        if current_file_index >= 16:
            break

# Close the last file if it's still open
if output_file is not None:
    output_file.close()

print(f"Merged contents into {current_file_index + 1} files.")

Run Code Interpreter

Running the following program: 

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import os
import math

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

# Calculate total size of all files
total_size = sum(os.path.getsize(file_path) for file_path in file_paths)

# Calculate target size for each merged file
target_size = math.ceil(total_size / 16)

# Initialize counters and current merged file
current_size = 0
current_file_index = 0
output_file = None

# Process each file
for file_path in file_paths:
    # Open a new merged file if necessary
    if output_file is None:
        output_file = open(f'/tmp/merged_{current_file_index}', 'wb')

    # Read and write the content of the current file
    with open(file_path, 'rb') as input_file:
        content = input_file.read()
        output_file.write(content)

    # Update current size
    current_size += len(content)

    # Check if we need to start a new merged file
    if current_size >= target_size:
        output_file.close()
        current_file_index += 1
        current_size = 0
        output_file = None

        # Break if we've created all 16 files
        if current_file_index >= 16:
            break

# Close the last file if it's still open
if output_file is not None:
    output_file.close()

print(f"Merged contents into {current_file_index + 1} files.")
And got the output: Merged contents into 16 files.

PyFunc

final: False Resulting in output: False

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

Here's a Python script that will merge the contents of the files listed in /tmp/files into 16 approximately equal-sized files named /tmp/merged_0 through /tmp/merged_15: 

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import os
from itertools import cycle

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

# Calculate total size of all files
total_size = sum(os.path.getsize(path) for path in file_paths)

# Calculate target size for each merged file
target_size = total_size // 16

# Create 16 output files
output_files = [open(f'/tmp/merged_{i}', 'w') for i in range(16)]
output_sizes = [0] * 16
output_cycle = cycle(range(16))

# Distribute content to output files
for path in file_paths:
    with open(path, 'r') as input_file:
        content = input_file.read()
        
        while content:
            i = next(output_cycle)
            space_left = target_size - output_sizes[i]
            
            if len(content) <= space_left:
                output_files[i].write(content)
                output_sizes[i] += len(content)
                content = ''
            else:
                output_files[i].write(content[:space_left])
                output_sizes[i] += space_left
                content = content[space_left:]

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

print("Merging complete.")
This script does the following: 1. Reads the list of file paths from /tmp/files. 2. Calculates the total size of all input files. 3. Determines the target size for each of the 16 output files. 4. Creates 16 output files named /tmp/merged_0 through /tmp/merged_15. 5. Iterates through each input file: - Reads its content. - Distributes the content among the output files, cycling through them. - Fills each output file up to the target size before moving to the next. 6. Closes all output files when done. This approach ensures that: - All input files are processed. - The content is distributed as evenly as possible among the 16 output files. - Each output file is as close as possible to the target size. Note: This script assumes that the input files are text files. If you're dealing with binary files, you'll need to open them in binary mode ('rb' for reading and 'wb' for writing) and adjust the content handling accordingly. Also, make sure you have write permissions in the /tmp directory and that there's enough space to store the merged files.

Extract Code

I extracted the following code from that output: 

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import os
from itertools import cycle

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

# Calculate total size of all files
total_size = sum(os.path.getsize(path) for path in file_paths)

# Calculate target size for each merged file
target_size = total_size // 16

# Create 16 output files
output_files = [open(f'/tmp/merged_{i}', 'w') for i in range(16)]
output_sizes = [0] * 16
output_cycle = cycle(range(16))

# Distribute content to output files
for path in file_paths:
    with open(path, 'r') as input_file:
        content = input_file.read()
        
        while content:
            i = next(output_cycle)
            space_left = target_size - output_sizes[i]
            
            if len(content) <= space_left:
                output_files[i].write(content)
                output_sizes[i] += len(content)
                content = ''
            else:
                output_files[i].write(content[:space_left])
                output_sizes[i] += space_left
                content = content[space_left:]

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

print("Merging complete.")

Run Code Interpreter

Running the following program: 

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import os
from itertools import cycle

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

# Calculate total size of all files
total_size = sum(os.path.getsize(path) for path in file_paths)

# Calculate target size for each merged file
target_size = total_size // 16

# Create 16 output files
output_files = [open(f'/tmp/merged_{i}', 'w') for i in range(16)]
output_sizes = [0] * 16
output_cycle = cycle(range(16))

# Distribute content to output files
for path in file_paths:
    with open(path, 'r') as input_file:
        content = input_file.read()
        
        while content:
            i = next(output_cycle)
            space_left = target_size - output_sizes[i]
            
            if len(content) <= space_left:
                output_files[i].write(content)
                output_sizes[i] += len(content)
                content = ''
            else:
                output_files[i].write(content[:space_left])
                output_sizes[i] += space_left
                content = content[space_left:]

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

print("Merging complete.")
And got the output: Timeout: function took too long to complete

PyFunc

final: False Resulting in output: False