April 19th, 2020
Interesting Aspects of Pandas
In my previous article I walked through interesting aspects of numpy. I first learned numpy back in college during a course on Artificial Intelligence. With my daytime work becoming more Python based these past few months, I took numpy back up.
Before this winter, I never used pandas. Pandas is a data analysis library similar to numpy. In fact, pandas uses numpy arrays in many of its exposed methods. While numpy exposes an array data structure, pandas has two main data structures:
DataFrame. In general, pandas is commonly used for manipulating and analysing time series or table data (think SQL table or excel spreadsheet)1.
March 31st, 2020
Interesting Aspects of Numpy
In my new role at work, a good chunk of my programming is Python based and revolves around data analysis. I already knew Python, however I wanted a review libraries such as numpy and learn libraries such as pandas and matplotlib. This article discusses numpy, short for "Numerical Python". The goal of this article isn't to teach numpy to beginners, instead focusing on library aspects I found most interesting.
February 15th, 2020
Hosting a Static React Application on Amazon S3
Amazon S3 (Simple Storage Service) is an AWS service for storing objects. Since objects are files, S3 can be viewed as a filesystem accessible over HTTP. I often use S3 for storing images, fonts, and other assets for my applications. Some examples include my jarombek.com assets and my global shared assets.
Since Amazon S3 stores files and acts as a filesystem, it can also be used to host static websites.
February 5th, 2020
Unit, Integration, and Snapshot Testing in React with Jest and Enzyme
In an article last fall I spoke about my change in mindset towards unit testing. In my early programming days I thought unit tests slowed down development to a fault. Nowadays they are mandatory in all my applications. Unit tests are assertions that a unit of code is working as expected in isolation of other components in the codebase. They promote code review, help catch recurring bugs, and ease the burden of upgrading and switching technologies.
For React applications, the de facto testing framework is Jest. Jest was written by Facebook with React unit testing in mind, making it a natural fit. Alongside Jest, Enzyme is used to test React components. Enzyme was created by AirBnB to render components for testing. It provides an API to traverse the rendered DOM nodes in a component and hook into stateful component instances.
January 31st, 2020
Exploring New Features in React 16.3
When I was interviewing for jobs in the fall, one interviewer asked me if I had React 16 experience. I said "yes", figuring I must have worked on React 16 features during my year and a half experience. I've worked with React since I created a React and Webpack seed application in March 2018. Since then I wrote jarombek.com (the website you are currently viewing) in React along with contributing to a client-facing React application for seven months at my job.
As the interview questions rolled on, it became obvious that I wasn't utilizing the latest React features. Luckily I aced the coding assignment and other technology questions, so the interview ended up going well.
December 28th, 2019
Basic Elasticsearch Queries
Elasticsearch is a search and analytics engine. It's also a NoSQL database that holds JSON documents. These documents are stored in an inverted index and are queried with JSON syntax. In my previous article I explored analyzers and the process of storing documents in an inverted index. This article focuses on querying documents with JSON.
November 10th, 2019
The Basics of Programming Language Garbage Collection
While reading a book on C#, I came across a section about garbage collection. I always knew that programming languages such as Java performed garbage collection, but I never researched how garbage collectors (GCs) worked. The book mentioned that C# uses a tracing GC with generations and marking. These were foreign concepts to me, so I decided to conduct additional research on the topic. This article gives a high-level overview of garbage collectors and the APIs available to interact with them in Java and C#.
October 28th, 2019
Unit Testing AWS Infrastructure with Python
From October 2018 to May 2019, I moved the infrastructure for both my websites to AWS. The process for building and tearing down this infrastructure is automated with IaC, specifically Terraform. I've had a lot of fun working with Terraform and learning the different design patterns for infrastructure in the cloud.
After my infrastructure was built, I realized I needed a way to test that my IaC was behaving as expected. The obvious solution to this requirement was a unit test suite. I implemented this unit test suite in Python with the help of the AWS SDK. This article explains why I took the time to write unit tests and walks through of the basics of testing AWS infrastructure in Python.
October 18th, 2019
Writing Elasticsearch Analyzers
One of the biggest strengths of Elasticsearch is text searching. Elasticsearch holds strings for text searching in
text data types. A document can contain one or more fields of type
When strings are placed into a field of type
text they are processed by an analyzer. Elasticsearch analyzers can be viewed as a pipeline that takes text as an input, breaks it into terms, and returns the terms as output1. These terms are placed in an inverted index which makes an index searchable.
September 30th, 2019
Integrated Queries with LINQ and SQL Server
My previous article explored LINQ, a module that brings query syntax to C#. All the examples in that article queried local data structures. While using LINQ on local data is valuable in itself, LINQ can do much more. LINQ really shines when used to query remote data sources. Queries on remote data sources such as relational databases are known as integrated queries. In this article, I explore integrated queries with a SQL Server database. First I create the SQL Server database instance with Docker and then query it using LINQ.
September 17th, 2019
Using LINQ in C#
During free time at work, I've been reading a book called C# 7.0 In a Nutshell. When I get home, I write C# programs based on what I learned. One of the really interesting topics I read about was LINQ (Language Integrated Query), which is the integration of query functions and keywords in the C# language1. LINQ can be used to query remote data sources such as an RDBMS or local data structures.
LINQ reminds me of writing PL/SQL, which is a procedural language provided for the Oracle database. PL/SQL is a superset of SQL, allowing for looping, variable declarations, conditional logic, error handling, and more. The best feature of PL/SQL is the integration of SQL queries directly into an imperative programming language. Unfortunately, PL/SQL is strictly tied to the Oracle database and has clunky syntax in my opinion. LINQ on the other hand can be used with multiple different databases along with local data structures. Also, in my opinion, C# has much nicer syntax.
September 15th, 2019
Introduction to Elasticsearch
Over the past few months I've read a book about the ELK stack. ELK stands for Elasticsearch, Logstash, and Kibana. Together these three technologies provide the ability to search, stream, and visualize data. In this article I discuss Elasticsearch, which is the core technology of ELK Stack. First I'll define Elasticsearch and provide details about what its used for. Second I'll create AWS infrastructure for Elasticsearch using Amazon Elasticsearch Service. Third and finally I'll populate Elasticsearch with data and show some basic queries.