Python retry!

May 12, 2020
 · 4 min read

In programming it's quite often you need to wait for an action to complete or some service availability. There are many ways and tools which able to do that. I would like to tell about two python libraries I've worked with.


It's a small library originally created by my colleague Pete Savage @psav. wait_for is heavily used in web UI tests. When you click some button you not always get the result immediately. Request processing can take some time. Some application will show the result after page refresh, more modern applications use XHR and tons of scripts 🤑 to update the page. In both cases you cannot just perform button clicking in the python code. You have to wait until the result appears and only after that continue execution. Let me provide some examples of usage:
    lambda: view.flash.is_displayed,

Here test automation clicks a button and then wait for another element appearing in the UI. wait_for just executes lambda: view.flash.is_displayed over and over again until result will be True or time out.

wait_for has a nice decorator:

@wait_for_decorator(delay=10, timeout=300)
def volume_type_is_displayed():
    return volume_type.exists


Everything gets a lot more fun when you start to use asyncio. First of all you'll find out that time.sleep() blocks the main thread and you cannot use it in your asynchronous code. But wait wait_for uses time.sleep() underneath. I wanted to add asyncio support but before I started I decided to search if someone already did it (yeah I'm lazy I know). This is how I discovered tenacity (credits to Julien Danjou). You can use it in both synchronous and asynchronous code under the same API. My task was to upload a payload to a server and wait for the result from some REST API endpoint. But I wanted to upload a lot of payloads and check the results after that. tenacity and asyncio fit perfectly for that task. Here is an example:

import asyncio
from tenacity import retry
from tenacity import retry_if_exception_type
from tenacity import retry_if_result
from tenacity import stop_after_delay
from tenacity import wait_fixed

    retry_error_callback=lambda retry_state: False,
    retry=(retry_if_result(lambda value: value is False) | retry_if_exception_type(Exception)),
async def find_host(session, hostname):
    url = f"{hostname}"
    resp = await session.get(url)
    if resp.status != 200
        return False
    resp_json = await resp.json()
    return bool(resp_json["data"])

async def upload_payload(session, hostname):
    data = f"some_payload_with_{hostname}"
    resp = await"", data=data)
    is_host_found = await find_host(session, hostname)
    message = "host %s was found!" if is_host_found else "host %s wasn't found in time", hostname)

async def scheduler(session, base_hostname, num_uploads):
    tasks = []
    for i in range(num_uploads):
        hostname = f"{i}.{base_hostname}"
        task = upload_payload(session, hostname)
        task = asyncio.ensure_future(task)
    await asyncio.wait(tasks)
    await session.close()

What's happening in this piece of code?

  1. scheduler creates number of tasks upload_payload equals to num_uploads.
  2. upload_payload uploads a payload ans waits for the result in find_host
  3. find_host every 4 seconds checks f"{hostname}" endpoint and returns True if it's found. Otherwise it fails with timeout after 5 minutes.


tenacity is a powerful library and if you need to retry operations in asynchronous code it's the best choice. In other cases wait_for will be more than enough. In my opinion it has simpler API and doesn't force you to decorate functions.