Introduction

Algorithms & Data Structures interviews are notoriously difficult. Coming up with an optimal approach to a problem is already time-consuming. So, if you become stuck on the implementation, you may not even finish the problem! As a result, understanding how to use each of the core data structures and knowing the Python-specific caveats about them will make the implementation seamless.

Agenda

• Stack
• Queue
• Priority Queue/Heap
• Dictionary (Default Dict)

Stack

Huge shoutout to Codú Community for inspiring this blog. All the code for this project is linked on GitHub.

Introduction

There are multiple ways of optimizing server performance. One way is to make the client do some of the work. Consider uploading images for profile pictures. Since high-quality images take up several MB, it is costly to send them over the network to the server. Also, since profile pictures don’t need to be extremely detailed, it would be nice to compress them and save space. Thankfully, with HTML Canvas, we can compress our images right upon an upload by resizing them…

Introduction

Most of the time, there is no need for us to optimize memory usage in Python. Either our programs are too small to consume significant memory or we are are storing the data in databases outside the program. Regardless, there may exist cases where we must retain excessively large structures or a large number of objects in memory. As a result, I hope to illustrate practices that can decrease program memory usage.

Agenda

• Restrict class fields with __slots__
• Lazily evaluate with generators
• Constrain element types with array

Restrict class fields with __slots__

By default, whenever you create an object in Python, you will have the ability…

Introduction

Although building software projects can be challenging, deployment can be a pain. In fact, in situations where speed is necessary, deployment must be seamless. For that reason, I want to show you how to deploy Redis for free and use Redis remotely. Redis Labs, a Redis cloud hosting service, offers a free plan with simple deployment steps. We will leverage that plan to create an instance and integrate that instance with Node.js.

Walk Through

Do everything quickly and well.
― G.I. Gurdjieff

To start, head over to https://redislabs.com/ and sign up.

Introduction

Asynchronous programming is incredible! With it, we can run our IO-intensive tasks without having to block the execution of other code. However, in situations where the code after a blocking task depends on the task’s result, we must wait. Now, imagine if the blocking task took a long time to finish or it never finished. This could be problematic in the context of the application. We can solve this issue by setting a time limit on our task. If our task doesn’t finish in the span of the time limit, we can return a failure value instead. Let me elaborate.

Concept

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Introduction

Performance is a must when it comes to building software. However, in certain situations, the speed to set up and integrate new services for proof of concept evaluation or infrastructure is overlooked. Specifically, in the realm of databases, there are many options, but I find Deta to be most seamless to set up and use. Deta offers Deta Base (I will refer to it as Base), a NoSQL data store optimized for developer simplicity. In this article, I aim to show how to set up a Deta project and interact with your Base to store and manipulate Pokemon data.

This article is the prequel to Visualize Website Usage with a React Dashboard. In this article, we build out a service to track and store usage. In Visualize Website Usage with a React Dashboard, we build a dashboard to put the usage data in perspective.

Introduction

What is the most valuable resource in the modern era? Personally, I think that data triumphs in value over any other entity in the current world. In fact, data is the primary driver of decisions and actions in many lucrative industries of the present world.

To provide a bit of context, I created a personal…

This article is the sequel to Track Website Usage with PostgreSQL and Flask. In that article, we created a service to record the usage data. However, in this article, we will bring life to the usage data with a dashboard.

Introduction

It is important to collect data, but the main insight from the data is extracted through visualization. To recap, in the prequel, Track Website Usage with PostgreSQL and Flask, our goal was to track the number of views, reads (user stays on the website for at least ten seconds), and unique viewers for each day. We could track these metrics…