I had to recently migrate the DNS configurations (A, AAAA CNAME, TXT, MX, etc. records) for a particular domain from DigitalOcean to Google Cloud Platform Cloud DNS. Doing it is really simple – you just need to export the zone file from DO and then import the same into GCP Cloud DNS (using the gcloud […]
Pydantic validators are great! The validation is performed as soon as you instantiate your model. But how do we perform validation on modification of a particular attribute or field of the (model) instance after its creation? When we instantiate our model, all the validators run. But when we change the value of a particular (model) […]
Everything in JavaScript is an object. When you try to access a property on the object, it is looked up on the object but if not found, then looked up on the object’s prototype. The prototype is another object accessible via ob.__proto__ or even better Object.getPrototypeOf(ob). This prototype is also an object which further has […]
Let’s say we have a simple Pydantic model that looks like this: When you instantiate a Pydantic model – post = Post(**data) – all the required attributes defined must be passed, i.e., id, title, body. What if you had one or more of the following requirements: This would mostly require us to have an attribute […]
The sort() array method sorts its elements in place (no copy is made) and returns a reference to the same array. Hence the array is mutated. The default sort order of this function is ascending but we can pass a compare function to define our own behaviour (like sorting in descending order). Here’s another example […]
The reverse() array method reverses its elements in place (no copy is made) and returns a reference to the same array. Hence, it mutates the array. The TC39 Change Array by copy proposal introduced a new method Array.prototype.toReversed() that does the same thing as reverse() but returns a new copy with the changes instead of […]
Virtualization (in computing) is the process of creating one or more completely isolated “virtualized” environments inside a physical computer/machine. Each of these environments behaves like a completely isolated “real” computer by emulating softwares and hardwares like operating systems, storage (disk), networking, peripheral devices, etc. If you’ve SSH’ed into small remote servers hosted by cloud providers […]
Dnspython is a robust DNS toolkit for Python that you can use to make DNS queries, resolve CNAMEs, test nameservers, do zone transfers, perform dynamic updates, and much more than you can imagine. In this tutorial, I will cover the basic usage for querying certain types of DNS records for a particular domain (or subdomains) […]
Airflow allows configuring and tuning the parallelism/concurrency of tasks at various levels (like DAGs) and via different approaches (like Pools). But at the top level, the father of all knobs provided that controls the overall number of task instances that the entire cluster can run simultaneously (running state), is the scheduler’s (or more appropriately the […]
The most common desired alerting mechanism when an Airflow task fails is slack notifications. This can be achieved simply with two different aspects or components of Airflow: Airflow Callbacks, and Airflow Slack provider package. Callbacks With Airflow Callback functions feature, one can run a particular Python function when a task fails, succeeds, is up for […]