Go Library Data Generation Timings

Recently I put together some quick code to give some timings on the various data generation libraries available for Go. For each library there were a few key pieces of data generation I wanted to time:

  • First Name – basically a first name of some sort, like Adam, Nancy, or Frank.
  • Full Name – something like Jason McCormick or Sally Smith.
  • Address – A basic street address, or whatever the generator might provide.
  • User Agent – Such as that which is sent along with the browser response.
  • Color – Something like red, blue, green, or other color beyond the basics.
  • Email – A fully formed, albeit faked email address.
  • Phone – A phone number, ideally with area code and prefix too.
  • Credit Card Number – Ideally a properly formed one, which many of the generators seem to provide based on VISA, Mastercard, or related company specifications.
  • Sentence – A stand multi-word lorem ipsum based sentence would be perfect.

I went through and searched for libraries that I wanted to try out. Of all the libraries I found I narrowed it down to three specific libraries. When I add theĀ imports for these libraries, by way of how Go works, it gives you the repo locations:

  • “github.com/bxcodec/faker” – faker – Faker generates data based on a Struct, which is a pretty cool way to determine what type of data you want and to get it returned in a particularly useful format.
  • “github.com/icrowley/fake” – fake – Fake is a library inspired by the ffaker and forgery Ruby gems. Not that you’d be familiar with those, but if you are you have instant insight into how this library works.
  • “github.com/malisit/kolpa” – kolpa – This is another data generator that creates fake data for various types of data, structures, strings, sentences, and more.

Continue reading “Go Library Data Generation Timings”

A Collection of Links & Tour of DataStax Docker Images

Another way to get up and running with a DataStax Enterprise 6 setup on your local machine is to use the available (and supported by DataStax) Docker images. For additional description of what each of the images is, what is contained on the images, I read up on via Kathryn Erickson’s (@012345) blog entry “DataStax Now Offering Docker Images for Development“. Also there’s a video Jeff Carpenter (@jscarp) put together which talks from the 5.x version of the release (since v6 wasn’t released at the time).

Continue reading “A Collection of Links & Tour of DataStax Docker Images”

Cassandra / DataStax Enterprise 6 Clusters: Marketplace Options

As I have stepped full speed into work and research at DataStax there were a few things I needed as soon as I could possibly get them put together. Before even diving into development, use case examples, or reference application development I needed to have some clusters built up. The Docker image is great for some simple local development, but beyond that I wanted to have some live 3+ node clusters to work with. The specific deployed and configured use cases I had included:

  1. I wanted to have a DataStax Enterprise 6 Cassandra Cluster up and running ASAP. A cluster that would be long lived that I could developer sample applications against, use for testing purposes, and generally develop against from a Cassandra and DSE purpose.
  2. I wanted to have an easy to use cluster setup for Cassandra – just the OSS deployment – possibly coded and configured for deployment with Terraform and related scripts necessary to get a 3 node cluster up and running in Google Cloud Platform, Azure, or AWS.
  3. I wanted a DataStax Enterprise 6 enabled deployment, that would showcase some of the excellent tooling DataStax has built around the database itself.

I immediately set out to build solutions for these three requirements.

The first cluster system I decided to aim for was figuring out a way to get some reasonably priced hardware to actually build a physical cluster. Something that would make it absurdly easy to just have something to work with anytime I want without incurring additional expenses. Kind of the ultimate local development environment. With that I began scouring the interwebs and checking out where or how I could get some boxes to build this cluster with. I also reached out to a few people to see if I could be gifted some boxes from Dell or another manufacturer.

I lucked out and found some cheap boxes someone was willing to send over my way for almost nothing. But in the meantime since shipping will take a week or two. I began scouring the easy to get started options on AWS, Google Cloud Platform, and Azure. Continue reading “Cassandra / DataStax Enterprise 6 Clusters: Marketplace Options”

How Long do You Code Per Coding Session?

I was working on getting the latest DataStax Enterprise 6 up and running via the Docker Image offerings today and I stumbled across a site called hashnode.com. On that site was a harmless little question but something I realized I ponder a lot, and even find myself in conversation about on a regular basis. The question (link) is posed,

“How many minutes/hours do you really sit to write code at a particular moment?

I’m not saying the total summation of hours you code a day. When you really sit down to write a code for a particular task at a moment, how many minutes/hours (at worst case) do you normally sit down before you get tired? I know some take break, some say it depends on the task or the individual, I would love to hear them all, and what you do to keep your brain refreshed before getting back to coding. Thanks…”

This question, in normal coder fashion, has one simple answer the belies the actual complexity of the individual complex answers, “it depends“. So that’s the first answer, but here are some of the other answers for me. As with many of these types of questions and answers, many individual characteristics come into play for each of us, so this is indeed anecdotal scenarios for myself and very specifically YMMV for yourself! Continue reading “How Long do You Code Per Coding Session?”

DevXcon San Francisco

I just finished attending DevXcon in San Francisco at the beginning of the week before last. It’s the way the DataStax crew welcomed me into the family. It was a solidly awesome time, a great way to get started, and I’ve rated it “would do again!” Tamao (@mewzherder), Matthew (@matthewrevell), and fellow organizers did a great job putting things together!

The DevXcon is kidn of a sibling or parallel of sorts to the DevRelCon presented by Github. These events are organized by Hoopy, a consultancy of Matthew’s that specializes in helping companies around developer relations and marketing. Both of these conferences focus around this, the developer relations of software companies and how to improve that relationship companies have with their prospective developers. Continue reading “DevXcon San Francisco”