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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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Concurrently Download Large Files from GCS.

There is nothing more annoying than sitting around waiting for files to download. That was true while I was in high school staring at LimeWire, it’s still true today. Especially when you’re a data engineer who’s supposed to make data pipelines fast. You’re in luck! Yes, it is possible to download a large file from […]

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Data Engineering vs Data Science – Where’s The Love??

It seems like a never ending battle for supremacy. Articles about Data Science being the bee’s knees, then more articles about how Data Engineering holds up the world of Data Science like Atlas. Whenever I read something in one of these two categories on Medium or wherever, it just seems more like ego clash to […]

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Thoughts on Distributed Data Pipelines – Spark vs Kubernetes

Data gets bigger and teams want to process data faster, what else can you do? There is only so much code tweaking you can do, threads, processes, asyncio, it’s only going to get you so far. At some point you have terabytes of data to process, and it requires a decision about some sort of […]

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You Have to Try This… from io import StringIO, BytesIO

Ever heard of something called a File Object in Python? Ever heard of BytesIO or StringIO? Your missing out. It’s easy, fast, and wonderful, in short, it’s the best. For some reason IO streams are a totally underused feature that rarely comes up in most code. We all know that memory if faster than disk […]

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Concurrency in Python Data Pipelines – Async, Threads, Processes … Oh My.

Concurrency in Python is like the awkward group of middleschool boys gathered in the corner of the dance floor all pointing to the girls in the other corner. Everyone talks a big game, pretending like they totally understand the other group and could easily handle the pickup if they wanted to. Mmmhmmm. When push comes […]

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