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Here is one useful thing that you can do with GitHub actions no matter what language you use, send email. You might want to know right away when your ci passes. You might want to give your team a nice pat on the back when a new release is deployed. There might be subscribers wanting to see the latest release notes in their inbox as soon as the latest version is deployed. Whatever it is, its pretty easy to do with an action right out of the actions marketplace. Mail on Star # Here is a silly example that sends an email to yourself anytime someone stars your repo.

GitHub actions are an amazing tool that allows us to run code based on triggers inside of our repo. Their is a large and growing community of actions inside the marketplace to use with very little effort. Best of all they are free for public repositories, and private repos have a very generous free tier. I have been diving deep into Github actions for about a month now and they are wicked good! They allow you to run any sort of arbitrary code based on events in your repo, webhooks, or schedules. They are very reasonably priced. The interface that GitHub hs developed for them is top-notch! It’s so good I have done 90% of my editing of them right from github.com. TLDR # some interaction to your repository triggers code to run. # The online editor for actions is pretty amazing. When creating a new workflow it automatically sets up a new blank workflow or a workflow from the marketplace for you in your directory. This is all it takes to get an action running, a or file in the directory. Th…

Github actions are written in configuration files using the YAML syntax. YAML is a superset of JSON. Most YAML can be expressed inline with JSON syntax. Similar to python YAML is whitespace driven by whitespace rather than brackets tags. The argument for using YAML for configuration files such as actions is that it is more human-readable and editable. It’s much easier to see the whitespace layout than it is to get closing brackets correct. For actions, I believe this is mostly true. I don’t see any use case to get past 3-5 indents, which is completely manageable. Can I just say that I learned more than I realized about YAML by writing this article Arrays and Objects # In YAML or JSON, the most basic containers for data are arrays, a 1D list of things, and objects, for key-value pairs. Arrays # The start of an array container is signified with a leading. This is probably one of the big things I didn’t understand about YAML before writing this post, but hats off to the GitHub actions edi…

Today I learned how to diff between two branches. Sometimes we get a little happy and mistakenly commit something that we just can’t figure out. This is a good way to figure out what the heck has changed on the current branch compared to any other branch. Example # Let’s create a new directory, initialize git and toss some content into a readme. After all of that, we have a git repository on our local machine with a single file that contains the following. Create a branch and ✍ edit # Let’s checkout a new branch called Waylon and change the word to in our file, then diff it. At this point we have one commit. Things are really straightforward, and our diff will be the same between the last commit and the main branch since. Let’s make another commit by adding the date. 👆 At this point, our diff doesn’t tell us the whole story between our current state and main, only between our current state and our last commit. Let’s commit our changes and compare our branch to main. Git is powerful # I…

This is a quickstart to getting a new kedro pipeline up and running. After this article you should be able to understand how to get started with kedro. You can learn more about this Hello World Example in the docs 🧹 Install Kedro 🛢 Create the Example Pipeline 💨 Run the example 📉 Show the pipeline visualization Create a Virtual Environment # I use conda to control my virtual environments and will create a new environment called with the following command. note the latest compatible version of python is 3.7. EDIT: as of kedro 0.16.0 kedro supports up to 3.8 Options Activate your conda environment # I try to keep my base environment as clean as possible. I have ran into too many issues installing things in the base environment. Almost always its some dependency that starts causing issues making it even harder to realize where its coming from as I never even installed it in base. Install Kedro # Currently is available on pypi and can be pip installed. EDIT kedro is up to Make sure you are…

Learn the business Learn Git Your code does not need to be amazing Keep Learning Learn Git # You dont have to start out as a git wizard with the cleanest possible commit history. At first dont let yourself get too wrapped up in it, the most important part is that you make commits. You will find needs for more advanced stuff later. Get comfortable with this, then learn how to,,, etc… Your code does not need to be amazing # Get the job done. Keep it in small bite size pieces. Make readable function definitions and variable names. You will thank yourself for naming things well later. Readability counts more than performance in most cases of data science. If it gets the job done try not to over worry about things like performance. A few extra seconds to clean a dataset or build a model is not worth hours of your time. As you go you will have cases that performance is more critical and you will learn what to do from the start to avoid them.