Troubleshooting Python 3.6 AttributeError: module ‘asyncio’ has no attribute ‘run’

Troubleshooting Python 3.6 AttributeError: module 'asyncio' has no attribute 'run'

Are you struggling with the ‘Python 3.6 AttributeError: module asyncio has no attribute run’ issue? This error stems from the absence of the function in Python 3.6, which was introduced in Python 3.7. In this article, we will delve into the evolution of the asyncio library in Python and explore how the run method simplifies event loop management. Stay tuned to discover practical solutions to overcome this error and enhance your asynchronous programming skills.

Resolving AttributeError: module ‘asyncio’ has no attribute ‘run’

The error you’re encountering, “AttributeError: module ‘asyncio’ has no attribute ‘run'”, occurs because the function was introduced in Python 3.7 and is not available in Python 3.6 or earlier versions . To resolve this issue, you have a couple of options:

  1. Upgrade Python Version:

    • The simplest solution is to upgrade your Python version to 3.7 or later. This way, you’ll have access to the function.
    • To check your current Python version, open your command prompt or terminal and enter the command:
      python --version
    • If you’re using Python 3.6 or below, consider upgrading to a newer version.
  2. Alternative Approach (for Python 3.6):

    • In Python 3.6, you can achieve similar functionality by using the event loop directly.
    • Replace the line in your code with the following:
      import asyncio
      # Your existing code
      urls = ['', '', '']
      async def call_url(url):
          print('Starting {}'.format(url))
          response = await aiohttp.ClientSession().get(url)
          data = await response.text()
          print('{}: {} bytes: {}'.format(url, len(data), data))
          return data
      futures = [call_url(url) for url in urls]
      # Use the event loop directly
      loop = asyncio.get_event_loop()
    • This approach is roughly equivalent to using in Python 3.7.

Remember that the function was added provisionally in Python 3.7, so its API may change in future versions

Evolution of asyncio in Python

Let’s delve into the evolution of asyncio in Python and explore the introduction of the run method in Python 3.7.

  1. Asyncio in Python 3.6:

    • In Python 3.6, the asyncio library was already available for asynchronous programming. It allowed developers to write concurrent code using coroutines and event loops.
    • One common issue faced by developers was that tasks scheduled with create_task would not wait for their completion. For example, if you used create_task to spin up EC2 instances, the function would return immediately without waiting for the instances to be fully created.
    • To address this, Python 3.6 developers needed to explicitly handle waiting for tasks to complete. The solution was to use asyncio.gather to await multiple tasks concurrently. Here’s an example:
    import asyncio
    async def run_new_vm(manager, loop, vm_name):
        new_instance = manager.launch_ec2_instance(vm_name)
        task = loop.create_task(new_instance)
        task.add_done_callback(lambda f: do_something(manager, f.result()))
    async def one_service_per_vm(n, manager, loop):
        tasks = [run_new_vm(manager, loop, n) for _ in range(n)]
        await asyncio.gather(*tasks, loop=loop)
    def run_tests():
        loop = asyncio.get_event_loop()
        m = Manager()
        loop.run_until_complete(one_service_per_vm(2, m, loop))
  2. Introduction of run Method in Python 3.7:

    • Python 3.7 introduced the method, which simplified managing the event loop.
    • With, you no longer need to explicitly create and close the event loop. It takes care of setting up the event loop, running tasks until they complete, and then closing the loop.
    • The typical pattern using looks like this:
    import asyncio
    async def main():
        # Your asynchronous code here
    if __name__ == "__main__":

    This approach is more concise and easier to work with compared to manually managing the event loop using get_event_loop().

In summary, Python 3.6 laid the groundwork for asynchronous programming with asyncio, and Python 3.7 introduced the convenient run method to simplify event loop management. If you’re working with Python 3.7 or later, I recommend using

: Stack Overflow: Run tasks asynchronously with Python 3.6 asyncio
: Python 3.12.2 documentation:
: Stack Overflow: How can I periodically execute a function with asyncio?
: Real Python: Async IO in Python: A Complete Walkthrough

Troubleshooting AttributeError in Python

Let’s tackle the AttributeError in Python. This error occurs when you try to access an attribute that doesn’t exist on a variable or object. Here are some steps to troubleshoot and fix it:

  1. Check for Typos:

    • Verify that there are no typos in the attribute name you’re trying to access. Even a small typo can lead to an AttributeError.
  2. Correct Syntax:

    • Ensure that you’re using the correct syntax to access the attribute. Use the dot notation (object.attribute) to access attributes.
  3. Data Type Compatibility:

    • Confirm that the object you’re trying to access the attribute from is of the correct data type. For instance, calling a method on a string that isn’t supported by the string data type will result in an AttributeError.
  4. Inspect the Traceback:

    • When an AttributeError occurs, the traceback provides valuable information. It includes the line of code where the error occurred and the name of the invalid attribute.
    • Identify the variable causing the error by examining the traceback.
  5. Generic Approach:

    • To avoid the AttributeError, perform a check before referencing an attribute on an object. Ensure that the attribute exists.
    • You can use the help() function to find all attributes and methods related to an object.
  6. Try-Except Block:

    • Use a try-except block to handle the error gracefully. This way, your program won’t crash if an invalid attribute is accessed.

Let’s illustrate with an example:

# Example: AttributeError with an integer
number = 5
    total = number.add(4)  # This method doesn't exist for integers
    print("The total is", total)
except AttributeError as e:
    print(f"AttributeError: {e}")

Remember, understanding the traceback and identifying the root cause will help you fix AttributeError

For more detailed explanations and examples, you can refer to the following resources:

Handling AttributeError in Python 3.6

In Python 3.6, the method is not available. This method was introduced in Python 3.7 and provides a convenient way to run an asynchronous event loop. If you encounter an AttributeError related to, here’s how you can handle it:

  1. Python 3.6 Compatibility:

    • In Python 3.6, you can achieve similar functionality by using the event loop directly. Here’s an alternative approach to your code snippet:
      import asyncio
      import aiohttp
      urls = ['', '', '']
      async def call_url(url):
          print('Starting {}'.format(url))
          response = await aiohttp.ClientSession().get(url)
          data = await response.text()
          print('{}: {} bytes: {}'.format(url, len(data), data))
          return data
      futures = [call_url(url) for url in urls]
      loop = asyncio.get_event_loop()
    • Replace with the above snippet to achieve the same result in Python 3.6.
  2. Upgrade to Python 3.7 or Later:

    • If possible, consider upgrading your Python version to 3.7 or later to take advantage of
    • Keep in mind that was added provisionally, and its API may change in future Python versions.

Common Asyncio Pitfalls and Solutions

Asyncio is a powerful library in Python for asynchronous programming using coroutines. However, it can be tricky for beginners. Let’s explore some common pitfalls and version compatibility issues:

  1. Trying to Run Coroutines by Calling Them:

    • A common mistake is treating coroutines like regular functions. When defining a coroutine using async def, avoid calling it directly as if it were a function. Instead, create a coroutine object and either run it using or await it using await custom_coro().
    • Example:
      # Custom coroutine
      async def custom_coro():
          print('hi there')
      # Incorrect: Calling a coroutine like a function won't execute its body
      # Correct: Run the coroutine using or await it
  2. Not Letting Coroutines Run in the Event Loop:

    • If you create a coroutine object but don’t schedule it for execution within the asyncio event loop, you’ll get a runtime warning.
    • Always ensure that your coroutines are awaited or scheduled for execution.
    • Example:
      # Incorrect: Coroutine not scheduled for execution
      sys:1: RuntimeWarning: coroutine 'custom_coro' was never awaited
      # Correct: Schedule the coroutine within the event loop
      await custom_coro()
  3. Using the Low-Level Asyncio API:

    • Avoid using the low-level asyncio API directly unless you have specific requirements. Instead, work with higher-level constructs like and await.
    • The high-level API simplifies common tasks and reduces errors.
  4. Exiting the Main Coroutine Too Early:

    • Be cautious when exiting the main coroutine. If it finishes before other coroutines, they might not complete their work.
    • Use await asyncio.gather(...) or other synchronization mechanisms to ensure all coroutines finish.
  5. Assuming Race Conditions and Deadlocks Are Impossible:

    • Asynchronous code can introduce race conditions and deadlocks. Always consider synchronization and thread safety.
    • Use locks, semaphores, and other tools to prevent issues.

Further reading:

In conclusion, the ‘Python 3.6 AttributeError: module asyncio has no attribute run’ error can be a roadblock for developers working with asynchronous programming. By understanding the differences between Python 3.6 and 3.7 asyncio functionalities, you can adapt your code to run smoothly across both versions. Whether through upgrading Python versions, utilizing alternative approaches in Python 3.6, or embracing the method in later versions, there are avenues to tackle this error effectively.

Remember, staying informed about the nuances of asyncio and Python enhancements is key to navigating such challenges seamlessly in your development journey.


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