Transferring files using asyncio

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Alright ! Let’s talk about how to transfer files using asyncio in Python for the best practices and patterns when writing asynchronous code. If you have a file called “example.txt” located in your downloads folder, let’s get started!

First, import the necessary modules and create a function to handle sending the data:

# Import necessary modules
import asyncio # Importing the asyncio module for asynchronous programming
from typing import List # Importing the List type from the typing module
import os.path # Importing the os.path module for file path operations

# Define a function to handle sending the data
async def send_file(filename):
    # Check if file exists
    if not os.path.isfile(filename): # Using the isfile() function to check if the given file exists
        print("Error: File does not exist.")
        return # Returning from the function if the file does not exist
    
    # Open the file in read-only binary mode
    with open(filename, 'rb') as f:
        data = f.read() # Reading the file data into a variable
        
    # Create a TCP/IP socket and connect to the server
    reader, writer = await asyncio.open_connection('example.com', 80) # Using the open_connection() function to establish a connection with the server
    
    # Send file size and filename
    writer.write(f"{len(data)} {filename}\r\n".encode()) # Encoding the file size and name into bytes and sending it to the server
    await writer.drain() # Waiting for the data to be sent
    
    # Write the data to the socket in chunks of 16KB
    chunk_size = 16 * 1024 # Setting the chunk size to 16KB
    while True:
        chunk = data[len(data) chunk_size:] # Slicing the data into chunks of 16KB
        if len(chunk) < chunk_size: # Checking if the remaining data is less than 16KB
            writer.write(chunk) # Writing the remaining data to the socket
            break # Exiting the loop
        writer.write(chunk[:chunk_size]) # Writing the first 16KB of data to the socket
        await writer.drain() # Waiting for the data to be sent
        
    # Close the connection and print confirmation message
    writer.close() # Closing the connection
    print("File sent successfully!") # Printing a confirmation message

Let’s go over what this function does:

1. Check if file exists, otherwise return an error message. 2. Open the file in binary mode (read-only) and read its contents into a variable called `data`. 3. Create a TCP/IP socket using asyncio’s “open_connection()” method and connect to the server at example.com on port 80. 4. Send the size of the data and filename to the server, followed by a newline character (`\r\n`) to indicate end-of-message. 5. Write the data in chunks of 16KB using “write()” method and “drain()” method to ensure that all data is sent before moving on to the next chunk. 6. Close the connection and print a confirmation message when done.

When writing asynchronous code, it’s essential to follow best practices and patterns for optimal performance and maintainability. Here are some tips:

1. Use asyncio instead of threads or processes whenever possible. This allows you to take advantage of Python’s built-in event loop and avoid the overhead associated with creating new threads or processes. 2. Avoid blocking I/O operations by using non-blocking functions like “read()” and “write()”. Instead, use asyncio’s “asyncio.open_connection()” to create a socket connection that can handle multiple requests simultaneously. 3. Use coroutines instead of callbacks whenever possible. Coroutines allow you to write more concise and readable code by eliminating the need for nested function calls and callback functions. 4. Avoid using global variables or shared state between tasks, as this can lead to race conditions and other synchronization issues. Instead, use local variables or pass data between tasks via arguments or return values. 5. Use asyncio’s “Task” class to manage multiple concurrent tasks. This allows you to easily cancel or pause tasks if necessary, and provides a more intuitive way of handling errors and exceptions. By following these best practices and patterns when writing asynchronous code with asyncio in Python, you can create highly efficient and maintainable applications that take full advantage of the power of non-blocking I/O operations.

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