#125: Logging in Celery
Errors happen, especially when you have a distributed application. Let's look how Celery allows us to log messages into the Celery logger.
Errors happen, especially when you have a distributed application. Let's look how Celery allows us to log messages into the Celery logger.
One big benefit of asynchronous jobs is that they do not need to be processed right away. Let's look how we can tell Celery to keep our jobs around for a while before starting the work.
If we try to run Celery on Windows, we will run into a problem: Windows is not officially supported by Celery. However, that does not mean that it will not work. Let's look what we need to do to run Celery on Windows.
RabbitMQ is a great tool for asynchronous jobs. It works well but we need to do all the infrastructure parts on our own. Celery can run on top of RabbitMQ and offers us a lot more comfort for our asynchronous jobs. However, that comfort comes with the price of additional complexity that we need to handle. In this post we start with the basic set-up and over the next weeks we take a deeper look at the features of Celery.
The series on Tweepy showed my that I have a big gap in my Python knowledge: How can I separate work in an asynchronous way? In this post I look at RabbitMQ and how we can use it to get more flexibility in our Python applications.
I wanted to test a Python script that puts files into folders based on their creation time. But how can I create files in the past without using a time machine?
Tweepy is not only good for housekeeping, but we can also use it for more positive interactions on Twitter. Let's see how we can like and retweet tweets.
Not everyone on Twitter is interested in a friendly conversation. Some people are just there for mischief and harassment. Let's look at how we can use Tweepy to block and mute accounts.
The number of tweets written on Twitter every second is massive. With the streaming clients we can get a glimpse on what is going on in near real-time. Let's find out what Tweepy offers and how the V1 and V2 endpoints differ.
Searching Twitter from Tweepy is a lot less troublesome than working with lists. Let's explore the search API of Twitter and the V2 client of Tweepy.