To set up async logging, we first create a logger object with `getLogger(__name__)`, which creates a new logger instance for our current module or package. We then configure the logger by setting its level using `setLevel(logging.INFO)` and adding a handler to it using `addHandler()`. In this example, we’re creating an asynchronous function that performs logging operations using the `logging` module and aiohttp library to handle HTTP requests in a non-blocking way:
# Import necessary libraries
import asyncio # Importing asyncio library for asynchronous operations
from aiohttp import ClientSession # Importing ClientSession from aiohttp library for handling HTTP requests
import logging # Importing logging library for logging operations
# Define an asynchronous function
async def my_function():
logger = logging.getLogger(__name__) # Creating a logger object with the name of the current module
logger.setLevel(logging.INFO) # Setting the logging level to INFO
# Set up formatting for the log messages using %-style format string or str.format() with {} placeholders
handler = logging.FileHandler('myapp.log') # Creating a FileHandler object to handle logging to a file
formatter = logging.Formatter('%(asctime)s [%(name)s] %(message)s', style='{') # Creating a formatter object with a custom format for log messages
handler.setFormatter(formatter) # Setting the formatter for the FileHandler object
# Add the handler to the logger object
logger.addHandler(handler) # Adding the FileHandler object to the logger
# Perform HTTP request using aiohttp library
async with ClientSession() as session: # Creating a ClientSession object for handling HTTP requests
response = await session.get('https://example.com') # Sending a GET request to the specified URL
if response.status == 200: # Checking if the response status code is 200 (OK)
logger.info("Response status code is {}".format(response.status)) # Logging the response status code
data = await response.text() # Retrieving the response data
logger.debug("[my_function] Data received from server: {}".format(data)) # Logging the response data with a debug level message
In this example, we’re using the `%(name)s` format string to include the name of the function that generated the log message in each log entry. This can be useful for debugging and identifying which part of our application is generating a particular log message.
To ensure better performance when logging, we should avoid blocking by performing asynchronous operations whenever possible. For example, instead of using `logging.basicConfig()` to configure the logger in a synchronous way, we can use an asynchronous function that performs configuration and returns immediately:
# Import necessary libraries
import asyncio # Importing asyncio library for asynchronous operations
from aiohttp import ClientSession # Importing ClientSession from aiohttp library for making HTTP requests
import logging # Importing logging library for logging messages
# Asynchronous function for setting up logger
async def setup_logger():
logger = logging.getLogger(__name__) # Creating a logger object with the name of the current module
logger.setLevel(logging.INFO) # Setting the logging level to INFO
# Set up formatting for the log messages using %-style format string or str.format() with {} placeholders
handler = logging.FileHandler('myapp.log') # Creating a file handler to write log messages to a file
formatter = logging.Formatter('%(asctime)s [%(name)s] %(message)s', style='{') # Creating a formatter with a custom format for log messages
handler.setFormatter(formatter) # Setting the formatter for the file handler
# Add the handler to the logger object
logger.addHandler(handler) # Adding the file handler to the logger object
return logger # Returning the logger object
# Asynchronous function for performing a task
async def my_function():
logger = await setup_logger() # Calling the setup_logger function to get the logger object
async with ClientSession() as session: # Using the ClientSession to make an HTTP request
response = await session.get('https://example.com') # Making a GET request to the specified URL
if response.status == 200: # Checking if the response status code is 200 (OK)
logger.info("Response status code is {}".format(response.status)) # Logging an INFO message with the response status code
data = await response.text() # Getting the response data as text
logger.debug("[my_function] Data received from server: {}".format(data)) # Logging a DEBUG message with the received data
In this example, we’re using an asynchronous function `setup_logger()` to configure the logger and return it immediately. This allows us to perform logging operations in a non-blocking way without waiting for configuration to complete.
To further improve performance, we can use the `logging.captureWarnings(False)` function to turn off capturing of warnings by the logging system:
# Import necessary modules
import asyncio # Import asyncio module for asynchronous operations
from aiohttp import ClientSession # Import ClientSession from aiohttp module for making HTTP requests
import logging # Import logging module for logging operations
# Set up logger
async def setup_logger():
logger = logging.getLogger(__name__) # Create a logger object with the name of the current module
logger.setLevel(logging.INFO) # Set the logging level to INFO
# Set up formatting for the log messages using %-style format string or str.format() with {} placeholders
handler = logging.FileHandler('myapp.log') # Create a FileHandler object to write log messages to a file
formatter = logging.Formatter('%(asctime)s [%(name)s] %(message)s', style='{') # Create a formatter object with a custom format
handler.setFormatter(formatter) # Set the formatter for the FileHandler
# Add the handler to the logger object
logger.addHandler(handler) # Add the FileHandler to the logger object
# Turn off capturing of warnings by logging system
logging.captureWarnings(False) # Disable capturing of warnings by the logging system
return logger # Return the logger object
# Define a function to make HTTP request and log the response
async def my_function():
logger = await setup_logger() # Call the setup_logger function to get the logger object
async with ClientSession() as session: # Use the ClientSession to make an HTTP request
response = await session.get('https://example.com') # Make a GET request to the specified URL
if response.status == 200: # Check if the response status code is 200 (OK)
logger.info("Response status code is {}".format(response.status)) # Log the response status code
data = await response.text() # Get the response data as text
logger.debug("[my_function] Data received from server: {}".format(data)) # Log the response data with a debug level
In this example, we’re turning off capturing of warnings by the logging system using `logging.captureWarnings(False)`. This can improve performance and reduce overhead when handling large volumes of log messages. However, be careful not to turn off capturing of warnings entirely if you need them for debugging purposes or other reasons.
To ensure that our application remains responsive even when performing intensive logging operations, we should also consider using a non-blocking logger implementation such as `logging.AsyncLogger` provided by the asyncio_loggers package:
# Import necessary libraries
import asyncio # Importing asyncio library for asynchronous operations
from aiohttp import ClientSession # Importing ClientSession from aiohttp library for making HTTP requests
import logging # Importing logging library for logging operations
from asyncio_loggers import AsyncLogger # Importing AsyncLogger from asyncio_loggers library for non-blocking logging
# Define a function to set up the logger
async def setup_logger():
logger = AsyncLogger(name='myapp') # Creating an AsyncLogger object with name 'myapp'
logger.setLevel(logging.INFO) # Setting the logging level to INFO
# Set up formatting for the log messages using %-style format string or str.format() with {} placeholders
handler = logging.FileHandler('myapp.log') # Creating a FileHandler object to write logs to a file
formatter = logging.Formatter('%(asctime)s [%(name)s] %(message)s', style='{') # Creating a formatter with a custom format
handler.setFormatter(formatter) # Setting the formatter for the handler
# Add the handler to the logger object
logger.addHandler(handler) # Adding the handler to the logger
return logger # Returning the logger object
# Define a function to perform some task
async def my_function():
logger = await setup_logger() # Calling the setup_logger function to get the logger object
async with ClientSession() as session: # Using the ClientSession to make an HTTP request
response = await session.get('https://example.com') # Making a GET request to 'https://example.com'
if response.status == 200: # Checking if the response status code is 200 (OK)
logger.info("Response status code is {}".format(response.status)) # Logging the response status code
data = await response.text() # Getting the response data
logger.debug("[my_function] Data received from server: {}".format(data)) # Logging the data received from the server with a custom message
In this example, we’re using `AsyncLogger` provided by the asyncio_loggers package to create a non-blocking logger implementation that can handle logging operations in a more efficient way than traditional synchronous loggers. This allows us to perform logging operations without blocking our application and ensures better performance and responsiveness for our end-users.