Your GitHub Portfolio

In my last post, I talked about how to setup your GitHub profile when looking for a job. Now that your GitHub profile page is looking good, shape up the details of your top repositories. You can customize the six popular repositories that appear on your profile page. These repositories should show off your best work and match the skills needed for the position you’re currently seeking.

When I’m reviewing a candidate, I sometimes skip the popular repositories and go to the repositories tab. I like to see what the candidate is currently doing. Projects appear in order by most recent commit on here. Since a recruiter or hiring manager might only look at one or two projects, be sure those at the top of the list look good.

Once I click on a project, it should be pretty easy to see what you’re trying to accomplish. Include a brief description at the top of the repo. Explain what the project does in simple terms. A few sentences is enough. You’ll provide complete details later in the README file.

Next, include a website. If this is a web application, this should probably be the address of a live demo. Even better, link to a post on your site that describes the project. That post should then link to the live demo. A demo running on a free Heroku site is fine.

As the reviewer scans down the list of files, there should be a clear structure. Most frameworks, such as Ruby on Rails, provide this structure for you. Things I look for include a breakdown of the application into components, usually following the model-view-controller pattern, and a test or spec directory.

After the list of files in the project, include a detailed README file. This is your chance to elaborate on the purpose of the project. What is special about this application? What technologies did you use to build it? What did you learn from this project?

Finally, explain how to run the project locally. What are the requirements, and how do I install the correct versions? Again, the framework and tools you use should make this easy. Hopefully everything is just a bundle or yarn command away.

Now that I know what your project is all about, it’s time to dig into the code. I’ll cover what I look for in a code review in my next post.

Looking For Engineers

We’re currently looking to hire two more experienced Ruby / JavaScript engineers here in the Sharethrough Austin office. This is one of the hardest parts of my job as an Engineering Manager. If you’re interested, I thought I’d offer a few tips to make it easier for recruiters and hiring managers to pick you out of the crowd of applicants.

After I look over an applicant’s resume or LinkedIn profile, the next place I go is their GitHub page. I have some advice about other parts of an engineering candidate’s application, and I’m already working on a few more posts like this one. Since GitHub is basically the first place I look, I’ll start here.

As someone looking for a job writing code, GitHub can be one of your most valuable assets. The most important question that a potential employer has about you is “can this person code?” If you can’t code, nothing else really matters. Even if you’re a perfect culture fit for the team, if you can’t contribute you won’t get the job.

Your GitHub profile and your code repositories should demonstrate your ability to get things done by writing code. The fastest way to learn programming is by doing. The best way to improve your ability is consistent practice. Write lots of code and share it publicly.

Your Profile

As with all profiles, I recommend you use your real, full name on GitHub. This isn’t required, of course, but be sure that your username is fairly easy to pronounce and remember. Imagine telling it to someone over the phone. Also, don’t use anything that someone might find offensive.

The same goes for your profile photo. A recent photo of yourself is best. It doesn’t have to be a professional headshot. A picture of you doing something you enjoy is fine. Almost anything is better than the default pixel art face.

Write a short bio about yourself. This doesn’t have to be anything fancy, just a few sentences about your interests and experiences. This could even be simply your job title and your current company. Add your real email address. This should be the same address you use on LinkedIn. If you have a personal website, link to it on your profile. If not, link to your profile on LinkedIn.

Your profile is also a great place to show off things that you’re passionate about other than coding. Maybe you’re on a mountain bike or climbing wall. If you’re wearing headphones in your photo, I might ask you about music. Feel free to show off your personality and interests, but do it in a way that still looks good to potential employers.

After the profile, I head over to the repositories tab next. I’ll finish up a post with my tips for polishing up your repositories in a few days.

Getting Started With D&D

Halfway through my 5th grade year, my family moved over 100 miles away from the small town where I was born to the Dallas / Fort Worth area. This was before the internet or any other cheap long distance communication. As an already nerdy kid, this was fairly traumatic for me.

One day, while bored in math class, I started drawing a dungeon on the graph paper we were supposed to be using for plotting points. Another kid noticed what I was doing and asked if I played D&D. I answered “yes” and made a friend. Even better, that kid bought a few of my maps with his lunch money.

These days, thanks in part to its appearance on shows like Stranger Things, lots of people are curious about Dungeons & Dragons. This, combined with the fairly recent release of the Fifth Edition rules means there’s no better time to get started playing Dungeons & Dragons.

The Starter Set

If you’re interested in playing, I recommend buying the Dungeons & Dragons Starter Set. Other than a few friends and some snacks, this box has everything you need.

For about $20 you get 5 pre-generated characters, a set of 6 dice, a 32-page rulebook, and a 64-page adventure. The included adventure, Lost Minds of Phandelver, is perfect for a new Dungeon Master.

Playing a few hours a week, the starter adventure usually takes 6-8 weeks to get through. At this point, you and your friends should be eager for more.

Beyond the Starter Set

Players wanting more options for making characters should buy the Player’s Handbook for about $30. This large, hard-cover book contains all of the rules and many more options for building characters.

The Dungeon Master will want to pick up the Monster Manual which details hundreds of monsters for the game. The Dungeon Master’s Guide contains more guidance for running adventures and rules around creating your own adventures and campaigns.

If you’d rather not build your own adventures, there are many campaign books. The latest release is Tomb of Annihilation, which takes place in the jungle region of Chult. Other popular choices are Storm King’s Thunder, which has the players face off against giants and Curse of Strahd, a gothic themed adventure which pits the players against the vampire Strahd.

Dungeons & Dragons is played by people around the world. You’ll find a thriving community on your social network of choice. There are Facebook groups, several popular subreddits, various groups live-streaming on Twitch, and many D&D personalities on Twitter. Hopefully this is the beginning of a lifetime of enjoyment in role playing games.

2018 Goals and Habits

Last year I focused mainly on my weight. I developed healthy habits around diet and exercise and I plan to continue those through 2018, and hopefully for the rest of my life.

My overall focus for 2018 is going to be creativity. I have lists of unstarted ideas and folders full of unfinished projects. I have ideas for books, websites, a tabletop game, screencasts, and other programs. I always said I would get back to these some day. This year, I’m going to find “some day.”

My secondary focus for 2018 is learning. Some of my ideas will require me to learn some new skills. I plan to use my creative projects to reinforce and grow my abilities in Python, data science, and machine learning.

I’m over half way through Python for Data Science and Machine Learning on Udemy. After that I’m either going to work through Practical Deep Learning for Coders on fast.ai or enroll in Andrew Ng’s Machine Learning Coursera Course. If I have time I might do both.

I truly believe that data science and machine learning are the future. I got lucky and learned Ruby on Rails at exactly the right time to make web development my career. I hope to catch the AI wave before it passes me by. Not that I think Ruby on Rails is going away any time soon.

So my goal for 2018 is to develop habits around writing, both prose and code, and learning via online classes and books. Carving out time for these new habits might be a challenge, but hopefully I can work on something creative every week. I’ll continue to work on the good ideas and scratch out the bad ones. All while continuing to learn and grow as a developer.

Looking Back on 2018

As we move forward into 2018, I can’t help but reflect on the previous year. So much has changed in our country and in society in general. It seems like there’s so much negativity in the world, but I try not to dwell on those things. Instead, I’d rather talk about a few positive things that I personally accomplished last year.

NaNoWriMo

In the month of November I wrote 21,288 words of a novel. That’s far short of the 50,000 word goal, but it’s over twenty-one thousand words I didn’t have in October. I started the month pretty strong, but then struggled and didn’t write at all around the Thanksgiving holiday. Even with the missed days I averaged over 700 words per day. Writing at that rate every day, I would have over 250,000 words by the end of this year.

Health

Starting in March 2017, I decided to finally get back in shape. I started counting calories and tracking my weight in the [Lose It!] app. I also started walking on the trail behind our house every day. I track my steps and daily workouts on my Apple Watch.

Doing this, I averaged about 10 pounds of weight loss per month for the first few months. By the end of the year I was eating around 1,500-1,600 calories and jogging 2-3 miles per day. Since March I’ve lost 65 pounds. I’ve continued counting calories and exercising for at least 30 minutes every day and don’t plan on ever stopping.

Habits

Most people that hear about my weight loss say I must have amazing willpower, but I don’t think that I do. Instead of mentally forcing myself to exercise every day, I made it a habit. It’s just something that I do every evening, usually right after dinner.

So much of what we do in life is based on what we’ve always done before. If you sit around and play video games every evening or watch Netflix, then you’ll probably continue to do those things. Trust me, I know.

One day I just decided to go for a walk instead of goofing off. I didn’t walk for very long, but I felt good afterwards. I kept going for walks every evening. Soon, I started seeing results. I could walk a bit farther each time. More importantly, I started losing weight. That’s very motivating.

This also explains why I failed at NaNoWriMo. I never really made it a habit. Instead of scheduling time for writing every day, I tried to squeeze the writing into my free time. Once my free time started getting shorter, I stopped writing. I hope to avoid making this mistake again this year.

NaNoWriMo 2017

About this time tomorrow I’ll hopefully be typing much faster than I am right now. November 1 is the first day of National Novel Writing Month, also known as NaNoWriMo 2017.

The goal is to type a 50,000 word novel from beginning to end in the month of November. That’s around 1,677 words per day, every day. That’s a lofty goal, but it’s not impossible. I’ve tried NaNoWriMo once before, in 2013 while I was writing Rails Crash Course, but you can’t really write a non-fiction book that quickly. I only hit 16,359 words. It required too much research and testing.

I’ve outlined my novel pretty well, and written lists of characters, scenes, and settings. I’ve also been doing a lot of research and reading leading up to the start. A quick Google search will turn up many blog posts and other online articles promising to prepare you for the event.

Blog posts are great, but I still enjoy old-fashioned books. My favorite is On Writing by Stephen King. He’s not my favorite author, but this book really speaks to me. I don’t follow his approach to writing. He’s more of a pantser, where as I’ve always been a plotter, but I still find his stories funny and inspirational.

In addition to King’s book, I’m listening to the Writing Excuses podcast. I can’t believe I just discovered this podcast. It’s been around for years – since 2008! It has a great cast. Brandon Sanderson usually leads the discussion. This season he’s joined by Mary, Dan, and Howard. New episodes come out weekly, and each is around 15 minutes of advice and inspiration.

When it comes time to actually put words on the page, my current tool of choice is Ulysses. It syncs to all of my devices via iCloud and makes it easy to organize projects into folders and quickly switch between them. It uses Markdown for formatting which is how I write everything, even the post you’re reading right now.

My plan is to try to total 1,200 words per weekday in two sprints – one in the morning and one in the evening. There are 22 weekdays and 8 weekend days in November. That means I’ll need to hit around 3,000 words per weekend day to hit 50,000.

This may be tough, but if it was easy everyone would write a novel.

A Mining and Machine Learning PC for $500

In my never-ending quest for the “next big thing” in technology, I’ve been dividing my time between cryptocurrency and machine learning. I’m still not sure about the long-term value of Bitcoin and other altcoins, but the tech they’re built on, such as blockchain and smart contracts, is fascinating.

At the same time, it seems like machine learning is set to take over the world. I’ve been working my way through a couple of online data science / machine learning / deep learning courses. I’m particularly interested in learning more about TensorFlow, Google’s machine learning library.

In order to speed up processing with TensorFlow, I decided to build a PC with a decent graphics card. When I’m not using this PC to run machine learning programs, I could use the video card to mine a few altcoins. Finally, worst case scenario, if both of these technologies fail I’ll have a decent computer for gaming.

The Hardware

My first step was finding a video card. TensorFlow uses the CUDA Toolkit from NVIDIA so that seemed like a good place to start. I also knew that to mine Ethereum, I needed at least 4GB of memory on the card. With that in mind, I ended up choosing the EVGA GeForce GTX 1050ti Video Card for $157.99. Not exactly top-of-the-line, but good enough to get started on a budget.

Now I needed a PC to hold this card. Again, I was trying to go cheap so I looked into refurbished computers. There’s an off-lease, refurbished computer store near my house. I was able to pick up a Dell computer there with a keyboard, mouse, and monitor for about $350.

I went with the Dell Optiplex 7010. The 3.2 GHz i5 processor is plenty fast for my needs, and the mini-tower case provides plenty of room for the video card. I also bought a TP-Link N150 USB Wireless Adapter since this computer didn’t have built-in wireless.

The Software

The computer came with Windows 10 (which is actually not terrible), but I knew I wanted to run Linux for my purposes. So, I shrank the primary partition on the hard drive and downloaded a copy of Ubuntu Desktop 16.04.3 LTS and created a bootable USB flash drive.

There are already plenty of resources online explaining how to set up a dual-boot Windows / Ubuntu system so I won’t cover that here. Let me know if you run into trouble and I’ll try to point you in the right direction.

Once Ubuntu is installed, make sure the video card is using the proprietary drivers. The open-source drivers won’t cut it for mining or machine learning. To check, go to System Settings, then Software & Updates, and click the Additional Drivers tab. After the tab loads, you should see that your video card is using the NVIDIA binary driver. If not, select it and click the Apply Changes button.

Ethereum Mining

Now that the operating systems are installed, I was ready to start setting up the rest of the software. I decided to test mining first. You can’t mine Bitcoin on a regular computer, so it was out of the question, but you can mine Ethereum.

With that in mind, first install Ethereum. This is easy to do on Ubuntu using the Ethereum PPA (Personal Package Archive). These instructions are from the Go Ethereum Wiki. First, open a terminal and enter these commands:

sudo apt-get install software-properties-common
sudo add-apt-repository -y ppa:ethereum/ethereum
sudo apt-get update
sudo apt-get install ethereum

This adds the Ethereum PPA to your system, updates the list of available packages, and installs the Ethereum software. Once that’s complete, enter the following command to create a new Ethereum account:

geth account new

Be sure to write down your password and keep it in a safe place. This account holds all of your ether. Without the password you won’t be able to access your money. Also, make a note of your address. That’s the number returned by the command between curly braces.

Now it’s time to install the miner. There are several choices for mining on the Ethereum network. After trying a few different options, I chose Claymore.

First, download the Claymore Dual Miner v10.0 from their releases page on GitHub. Make a new directory named claymore for the miner inside your home directory. Now move the downloaded file from your Downloads directory to the claymore directory and extract it by double clicking it.

Rather than try to mine solo, I decided to join a mining pool. Again, there are many choices available, but after some research I went with nanopool.org. Their 1% fee seemed reasonable, and you can get payouts after mining as little as 0.05 ether.

The nanopool.org getting started guide includes instructions for setting up Claymore on Linux. After correcting a few typos everything worked perfectly. First, I replaced the contents of the file start.bash with this:

export GPU_FORCE_64BIT_PTR=0
export GPU_MAX_HEAP_SIZE=100
export GPU_USE_SYNC_OBJECTS=1
export GPU_MAX_ALLOC_PERCENT=100
export GPU_SINGLE_ALLOC_PERCENT=100

~/claymore/ethdcrminer64 -epool eth-us-east1.nanopool.org:9999 -ewal 0xa375d885105db5df1f2452ef9e347f261eb3f690/Atone01/me@anthonylewis.com -mode 1

The number starting with 0xa375... is my Ethereum address. You should replace this with your own, unless you want me to get all the ether you mine. Following that is my worker name and then my email address. nanopool.org will use this to email you if your worker goes. It’s also used as a password to update settings.

Next, update the file epools.txt to setup failover servers:

POOL: eth-eu1.nanopool.org:9999, WALLET: 0xa375d885105db5df1f2452ef9e347f261eb3f690.Atone01/me@anthonylewis.com, PSW: x, WORKER: , ESM: 0, ALLPOOLS: 0
POOL: eth-eu2.nanopool.org:9999, WALLET: 0xa375d885105db5df1f2452ef9e347f261eb3f690.Atone01/me@anthonylewis.com, PSW: x, WORKER: , ESM: 0, ALLPOOLS: 0
POOL: eth-us-east1.nanopool.org:9999, WALLET: 0xa375d885105db5df1f2452ef9e347f261eb3f690.Atone01/me@anthonylewis.com, PSW: x, WORKER: , ESM: 0, ALLPOOLS: 0
POOL: eth-us-west1.nanopool.org:9999, WALLET: 0xa375d885105db5df1f2452ef9e347f261eb3f690.Atone01/me@anthonylewis.com, PSW: x, WORKER: , ESM: 0, ALLPOOLS: 0
POOL: eth-asia1.nanopool.org:9999, WALLET: 0xa375d885105db5df1f2452ef9e347f261eb3f690.Atone01/me@anthonylewis.com, PSW: x, WORKER: , ESM: 0, ALLPOOLS: 0

The format is similar to start.bash but slightly different. These servers will be used if the server you entered in start.bash goes down.

Now that these files are updated, you can open a terminal and start the miner by entering this command:

~/claymore/start.bash

The command will first build a DAG on your video card which takes a few seconds, then it will start getting jobs from nanopool.org and attempting to mine ether. Occasionally, you will see text in green on your terminal that says “SHARE FOUND” and then “Share accepted”. This means your mining worked and you just earned a little ether.

You can see my results by looking at my worker on nanopool.org. At around 12 Mh/second I’m certainly not going to get rich off of this miner, but $10-15 USD per month is better than nothing. It’s not often that I actually get paid to learn about a new technology.

Machine Learning with TensorFlow

Now that Ethereum mining is working, I moved on to installing TensorFlow. The TensorFlow website has great documentation for Installing TensorFlow on Ubuntu, but there a few gotcha’s in the documentation.

Install NVIDIA Requirements

The first requirement for using TensorFlow with a GPU is the CUDA Toolkit from NVIDIA. The current required version is 8.0, but the latest version on NVIDIA’s site is 9.0. TensorFlow currently will not work with the latest version.

Once I had the versions worked out, CUDA is easy to install. The first step is to add the CUDA repository to your system. Rather than doing it manually as with Ethereum, CUDA provides a .deb package to do this for you.

You can download the base installer by going to CUDA Toolkit 8.0 Download Page and answering a few questions, or skip the questions and click this link to get the CUDA Repo for Ubuntu 16.04.

Once you download the file, open a terminal, go to the Downloads directory, and enter these commands:

sudo dpkg -i cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
sudo apt-get update
sudo apt-get install cuda

The next requirement is the CUDA Deep Neural Network library. This download requires a membership in the NVIDA Developer Program. Thankfully, it’s free. Go to the cuDNN Download page, and signup or login as required.

Click to expand the section labeled “Download cuDNN v6.0 (April 27, 2017), for CUDA 8.0”. In that section are three .deb files to download for Ubuntu 16.04:

  1. cuDNN v6.0 Runtime Library for Ubuntu16.04
  2. cuDNN v6.0 Developer Library for Ubuntu16.04
  3. cuDNN v6.0 Code Samples and User Guide for Ubuntu16.04

After downloading those three files, open a terminal, go to the Downloads directory, and enter these commands:

sudo dpkg -i libcudnn6_6.0.20-1+cuda8.0_amd64-deb
sudo dpkg -i libcudnn6-dev_6.0.20-1+cuda8.0_amd64-deb
sudo dpkg -i libcudnn6-doc_6.0.20-1%2Bcuda8.0_amd64-deb

Finally, install the NVIDIA CUDA Profile Tools Interface:

sudo apt-get install libcupti-dev

Now that CUDA is installed, edit the ~/.profile file to update the PATH and LD_LIBRARY_PATH environment variables with new paths. The last two lines of the file should look something like this:

# set PATH so it includes user's private bin directories
PATH="$HOME/bin:$HOME/.local/bin:/usr/local/cuda/bin:$PATH"

# add CUDA to LD_LIBRARY_PATH
export LD_LIBRARY_PATH="/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}"

If you’ve been following along, just add /usr/local/cuda/bin between colons to the PATH, and add the line with export LD_LIBRARY_PATH=... at the end of the file.

Install TensorFlow

With all of the NVIDIA requirements in place, it’s finally time to install and test TensorFlow. I decided to use the recommended virtualenv installation method.

First, install pip and virtualenv for Python 3 with this command:

sudo apt-get install python3-pip python3-dev python-virtualenv

Once the installation is done, create a virtualenv for TensorFlow with this command:

virtualenv --system-site-packages -p python3 ~/tensorflow

Then activate the newly created virtualenv.

source /tensorflow/bin/activate

The prompt should now start with (tensorflow). Remember to activate this virtualenv every time you want to work with TensorFlow.

Now ensure that pip is installed inside the virtualenv:

easy_install -U pip

And finally, install TensorFlow with GPU support:

pip3 install --upgrade tensorflow-gpu

Note that you don’t need to use sudo in front of the commands inside the virtualenv since these installations only affect the current user.

Now run a short program to verify TensorFlow is working. Launch the python interactive interpreter:

python

Then enter this short program:

import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))

If everything is setup correctly, this should simply print Hello, TensorFlow!.

And with that you have a $500 PC ready for learning about Ethereum mining and using TensorFlow for machine learning.

You Are the Product

I’m becoming more disillusioned with social media every day. I recently came across this article on the London Review of Books thanks to Longform.org. It does a great job of capturing and reenforcing many of my thoughts. Here are a few choice quotes:

… anyone on Facebook is in a sense working for Facebook, adding value to the company. In 2014, the New York Times did the arithmetic and found that humanity was spending 39,757 collective years on the site, every single day.

Everyone actively using Facebook provides content. Facebook makes money by selling ads next to content.

Since the Facebook button is pretty much ubiquitous on the net, this means that Facebook sees you, everywhere.

Search for something on Amazon, then visit Facebook. But maybe the targeted ads don’t bother you or you feel that it’s worth it to stay in touch with friends and family.

… researchers found quite simply that the more people use Facebook, the more unhappy they are. A 1 per cent increase in ‘likes’ and clicks and status updates was correlated with a 5 to 8 per cent decrease in mental health.

So, in an effort to maintain my mental health, I did this:

If you can’t join me, it might already be too late for you…

» You Are the Product

Chris Cornell

What a tragic loss for music fans everywhere. Especially fans around my age.

Here’s an acoustic performance by Chris Cornell of the U2 song One while he sings the lyrics from the
Metallica song One. Amazing.

I came across this video while browsing some of the live tributes to Chris Cornell performed
by other bands. Unfortunately, most of these are low-quality bootlegs, but he obviously touched
and inpired a lot of other musicians.

Seveneves

I finally finished Seveneves last night. I’ve been a fan of Neal Stephenson’s writing for years, going all the way back to Snow Crash. Seveneves did not disappoint.

If you’re familiar with Stephenson’s other work then you already know this is a dense, thick book. It’s 850+ pages filled with dizzying details about current and future technology. Stephenson does his homework. He deals with everything from robotics and orbital mechanics to nuclear power and even genetics. All of these complex subjects are seamlessly interwoven with a compelling story.

The book is divided into three parts. It might be better to think of it as a trilogy rather than a single book. Especially when you learn that part three starts with “Five thousand years later.” It’s here that Stephenson’s imagination runs wild and his talent really shines. His vision of the far future is fantastical, but explained so precisely and thoroughly that it is somehow still believable.

This is not a book to be undertaken lightly. It will take a while to finish, even for the fastest readers. But if the idea of an adventure spanning generations with a believable cast of characters and amazing settings sounds intriguing, you can’t go wrong with Seveneves.