![]() Image 2 - Vertical space for code and code editors (image by author) Take a look at the following image and you’ll immediately get the gist: Say what you want, but writing code on a vertical monitor is not something you can easily let go of. Image 1–2X Dell U2419H monitors (image by author) One of them is in a normal horizontal position, while the other is pivoted vertically, as you can see from the following image: Sure, work from home means work from bed on some days, but you’ll need that extra screen real estate more often than not. External Display Supportįeel free to skip this section if you’re using a single external display.ġ3" isn’t enough for comfortable 8+ hours work sessions. I’m sure any other tech professional can add issues to the list. ![]() This was just a short list of things that didn’t work or didn’t work as expected. The only sane way to do so with Python is through Oracle Instant Client, which isn’t ported to the new chip. Still, it’s not native support.įor my daily job, I need to communicate with cloud databases a lot, mainly Oracle. This means the entire distribution runs through an emulator called Rosetta 2, which does a terrific job. Kind of a hassle if you want TensorFlow always available.Īnaconda worked fine, but there wasn’t an official release for the M1 chip at the time of testing. Needless to say, but these versions get overridden when installing other packages if you don’t specify some extra parameters (or if you don’t install them in a virtual environment). Want to install TensorFlow? Great, but please install a specific version of Numpy and five other packages beforehand. Even after the downgrade, the only consistent thing I saw when installing libraries natively was a bunch of red lines in the Terminal. Not a big deal, but an extra step for sure. The default Python 3 on M1 was 3.9.x, which you’ll first have to downgrade to 3.8.x to make some libraries work. Still, Anaconda seemed like a go-to way on the M1 chip. Overall, it’s a great idea, but I prefer a clean installation of Python 3 and dependency management on the fly. I’m not a big fan of Anaconda Python distribution. ![]() That’s precisely how the article is structure, so feel free to navigate to a section that interests you the most: In case you want a single sentence summary- some data science libraries are either impossible or near to impossible to run natively, connecting two external displays is a nightmare, and finally, eGPUs aren’t supported. Imagine a blazingly fast processor, all-day battery life, and no thermal issues. ![]()
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