When learning a new skill it’s important to practice along the way. In order for me to show up to practice I need to make it easy to show up. An easy way to show up to practice with python is to use an online repl. With these you can try out something quick. Sometimes I see snippets from blogs or tweets and I need to try the out for myself to really understand.

When learning a new skill it’s important to practice along the way. In order for me to show up to practice I need to make it easy to show up. An easy way to show up to practice with python is to use an online repl. With these, you can try out something quick. Sometimes I see snippets from blogs or tweets and I need to try them out for myself to really understand.

Here are three different options that I have used in the past to try out something at some various levels. I am sure there are plenty more, but these are three that I have tried. I am not covering all of them, because It’s been a while since I have used one other than replit.com

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I am exploring a kedro catalog meta data hook, these are some notes about what I am thinking.

try pandas method -> try spark -> try dict/list -> none

Is there an easy way to create a nosql database in memory from a a list of dictionaries?

Mypy’s config parser seems to be one of the most complex. This is likely in part to it having the largest backwards compatability of all projects that I looked at.

mypy/config_parser

options/config.py

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I recently added a button to my blog, and subsequently my posts on DEV.to. It’s the best thing that I have done for it in a while. It makes it so easy to do quick edits.

I refer back to my old posts quite a bit, sometimes I find errors in them. Honestly most of the time its too much effort to load up my editor make the change and git add and git commit. It’s not much, but when I am referring to my own post generally I am just trying to get something done and don’t have time for that.

The slug that I am getting from gatsby is formatted as /blog/this-post/. Note the trailing slash and missing file extension, thats where the ${slug.slice(0, -1)}.md comes in.

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When first learning to code its very common to hard code everything right into the code. This happens with most folks in just about any language. Whether its HTML or markdown for front end content, or even hardcoding parameters in our backend languages like python, or node.js.

Hard coding everything right into your code makes it really hard for non-technical collaborators to join. It makes it nearly impossible to hand websites off to clients without needing to come back for routine updates.

The cms generally come with a rich content editor that feels more like something most folks are used to. There are buttons for changing the font, font-size, adding images, bold, italics, etc.

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I am looking into a way to replace my google reader experience that I had back in 2013 before google took it from us. I am starting by learning how to parse feeds with python, and without much previous knowledge, it proved to be much easier than anticipated thanks to the feedparser library.

This is how I used python to parse rss and setup my own custom feed.

Install the feedparser library.

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The input will be a yaml file containing a list of Items you want to stay up to date with. Inside each item will be a url, and weight.

email: max-entries: 10 recipients: - [email protected] markdown: max-entries: 100 output: - README.md json: max-entries: 1000 output: - feeds/feed.json rss: max-entries: 1000 output: - feeds/feed.xml html: max-entries: 100 output: index.html items: Waylon Walker: weight: 5 url: https://waylonwalker.com/rss.xml @_WaylonWalker: weight: 3 twitter: https://twitter.com/_waylonwalker DEV Waylon Walker: weight: 8 url: https://dev.to/waylonwalker Stack Overflow Kedro: weight: 5 url: https://stackoverflow.com/questions/tagged/kedro Kedro GitHub: weight: 4 url: https://github.com/kedro-org/kedro Kedro Pypi weight: 10 url: https://pypi.org/project/kedro/

Types ¶ #

• rss feed (primary source)
• youtube feed
• Stack Overflow tags
• GitHub repo activity
• pypi release
• dev.to post
• Twitter Search # user will need an api key

Methodology ¶

Each url will be pulled in and parsed into a standard data scructure. Some items may yield special feaures, a schemaless/nosql datastructure may be best. Pipeline will decide to how to weight posts based on users weight, recent position on feed, .

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I ran this post on dev.to and got a great response of great examples, check it out.

The GitHub profile feature just went live for a subset of users. Simply creating a repo named after your username, and clicking share to Profile on the sidebar will create a custom profile that shows up just above your pinned projects.

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Can someone explain how or why twitter cards render differently from device to device? I do understand that twitter cards a built from meta tags, the full list can be found in their docs

Mobile Looks fine.

On Desktop it is not picking up the image.

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I ran a discussion on dev that collected quite a list of examples in the comment section. So many great calls to action, animations, memes, and weird tricks.

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Python *args and **kwargs are super useful tools, that when used properly can make you code much simpler and easier to maintain. Large manual conversions from a dataset to function arguments can be packed and unpacked into lists or dictionaries. Beware though, this power can lead to some really unreadable/unusable code if done wrong.

I generally post these as a carousel on LinkedIn based on a full article. Let mw know what you think of it shown inside of a blog @_waylonwalker.

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While using the catalog alone will not reap all of the benefits of the framework, it does get you and your project ready for the full framework eventually. For me the full benefit of the catalog comes when you combine it with the pipeline and dont even touch read/write steps at all.

Taking a step into kedro by adopting the catalog first will give you a way to organize all of your data loads in one place, and stop manually writing read/write code, which can be different for each data and storage type. You just don’t need to think about it.

“can be dropped into kedro later” Let’s talk a bit more about that

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kedro 0.16.2 just dropped last week with a long-awaited feature… catalog search! I went as far as monkey patching this into each of my projects. I work jump between a few really big projects that have tons of datasets. Being able to quickly search for what I need is so useful.

The kedro data catalog is a key component to the kedro framework. It handles all data loading and saving for you. It is configurable and hackable. Having all your data connections listed in one place make it so easy to pick your project up and move it to a completely new environment. That sweet imperative loading style saves so much read/write overhead. I can load all my data with a single command whether it’s in amazon s3, google cloud platform, or a local file.

Just like with most of these articles, I am going to create a conda environment so that I don’t break any existing projects and scaffold up a toy project to learn from.

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This day 8 years ago I started my first day as a Mechanical Engineer. I am so grateful for this journey that I have been able to have. There is no way that I could have planned this journey from the beginning.

My initial career plans were down a completely different path. I have been very flexible in taking on a new career path. I have been eager to learn new things and respond to life changes that I never would have imagined.

Very severe chronic health issues from my family restricted my ability to travel to the facilities I served as a Mechanical Engineer. I was able to stay strong and make it work. But in the meantime, I was learning new skills that enabled me to be more effective remotely.

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Passing inputs into kedro is a key concept. Understanding how it accepts a single catalog key as input is quite trivial that easily makes sense, but passing a list or dictionary of catalog entries can be a bit confusing.

Check out this post for a review of how *args **kwargs work in python.

understanding python *args and **kwargs

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