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Introduction to Postgres with Python

If there was ever a match made in heaven, it’s using Python and Postgres together. They were made for each other. Both are fun and easy to use, addicting, both have so many surprises and hidden gems. Like Gandalf and Frodo, the two just go together. Today I want to go through the basics of […]

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Exploring ElasticSearch with Python

What’s Elasticsearch precious? I feel like Gollum when confronted by taters. Elasticsearch has been around for awhile now, based on Lucene, it’s become a well known name in the field of text and semi structured data storage, analysis and retrieve category. Even though it’s popular enough to get name recognition I’ve rarely run across it […]

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Approaching Software as a Craft, then as a Engineer.

Craft first, engineering second. There’s probably a lot of software programmers, developers, and engineers who will take issue with this. That’s kinda the point. Software should be approached as a craft first, then a engineering problem second. There are so many ways this is true, it’s going to be hard to touch them all. I […]

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3 (Or More) Ways to Open a CSV in Python

Ah. What a classic. The one piece of code that I end up writing over and over again, you would think I would have stashed it away by now. Not going to lie I usually have to Google it, while thinking, is this the right way? Should I just open the csv file and iterate […]

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How Smart Engineers Create Bad Software

You ever wonder how a room full of what appears to be smart engineers manage to build software that doesn’t work? Given more time and money, it appears to only get worse or no better. It doesn’t make that much sense does it? As someone who writes software it’s hard to see how bugs that […]

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Thunderdome for Geospatial Tools in Python. It’s to the Death.

It’s a fight to the death people… that’s why it’s called Thunderdome. This will be no different. Last time we talked about the very basics of the strange world of geo-spatial tools for data engineering. The next most obvious thing do of course is to see what tool is the best. By best I mean […]

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Gentle Introduction to Geospatial for Data Engineers

What does a data engineer need to know about working with geospatial data? I’m going to give my two cents on what is and is not important. First, prepare to be annoyed as you will most likely spend hours debugging strange and not obvious errors and bugs. You should run screaming the other way, but […]

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Python Async File Operations – Juice Worth the Squeeze?

What I’ve greatly feared has come to pass. I’ve come to love on of the most confusing parts of Python. AysncIO. It has this incredible ability for data engineers building pipelines in Python to take out so much wasted IO time. It saves money. It’s faster. People think you’re smarter than you are. Tutorials are […]

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Dask – To Distribute or Not To Distribute..Ahh..This Thing Sucks.

Raise your hand if you’ve every used Dask? ……. Me either. With tools like Spark, I’ve only recently started seeing some articles and podcasts pop up around Dask. Written in Python and claiming to be a distributed data processing framework I figured it was about time to check it out. Suprisingly when reading up on […]

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Data Engineering a Machine Learning Pipeline In Real Life.

It doesn’t take long reading articles on Medium or Towards Data Science to become enamored with Machine Learning. Especially the people and companies who do it in “production.” I always read about the big picture, the fancy algorithms, the cloud computing, but you have that feeling there is something missing. It’s all the details that […]

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