With the web transitioning to a decentralized internet, new systems and applications are being built. In order to access them, we need tools that interact with the next version of web, web 3.0. In today’s post, we will take a look at Metamask, a gateway to the decentrailized internet. We will look at what functionalities it provides and how to use it.
When doing web development, we often use
JSON.stringify to print to the screen the value of a variable. But when the variable contains multiple attributes, the print could be quite dense. To cater for that
JSON.stringify has extra parameters that can be specified. In today’s post, we will look at each of them with example.
Last week we looked at how to setup an Apollo server to serve graphql requests. We went through the setup by defining a
TemplateStringArray for the schema and defining functions in an object map for the resolvers. In this week post, we will look at how to simplify this two areas by leveraging Typescript features using
A data class is a class which is identified by the value stored in their attributes. The most common way of holding values in Python is via tuples. Data classes make is easier to construct a class with a name and meaning while keeping the value aspect in term of equality. In today’s post we will see how we can define data classes using the
dataclass decorator from the
itertools module provides a set of iterator blocks that can be used to combine iterators into a new iterator which will apply some modifications during the iteration of the sequences. For example building blocks like
cycle allows infinitely cycling through a sequence, another example is
groupby which provides a new iterator giving the groups on each iteration. In today’s post, we will look at some of the functions provided by
itertools with examples.
Python comes with general purpose datatypes like
set. Those types are commonly used everywhere with the best tradeoff in term of performance and application scope. But there are times where we might see ourselves repeating a specific implementation, for example counting values while storing them in a
dict is one of those cases. To cater for those repeated scenarios, the
collections module gives us access to alternative types that can be used for specialized purposes. In today’s post we will look at some of those types with examples.