Without a doubt my beloved Python is the Lingua Franca for machine learning these days. Tons of create tools by Google, Facebook and other big players make it easy to learn about machine learning. All offer a great Python API. At Amazon you find 200+ books teaching you stuff about machine learning using Python. A lot of material to choose from. And from my point of view, also a lot of material to fail with. Let me recommend two books I find particularly helpful, when you want to learn something about these fascinating fields and start to dive into one of the hottest topics in tech at the moment.
After my first steps with Lambda, Zappa and Flask I created some small applications to try various Zappa configuration options and play with some AWS services. Setting up the project got pretty boring after the second or third toy project. But for python developers there is a solution to automate these tasks – cookiecutter.
Here is a short video that demostrates how to use cookiecutter-flask-lambda and create, deploy and undeploy a new project. It won’t get any easier to deploy your Flask based web application.
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Image credit: Luke Loughead. Shared under the Creative Commons Attribution-ShareAlike 2.0 Generic license.
Update: After receiving some feedback, that it is not obvious if you need to use Python 2 or 3 for this article, I decided, that I want to update it all the way for Python 3. AWS Lambda supports it, Zappa supports it and we all want Python 3!
I wanted to try out AWS Lambda for a while now. But it took some time to find a reasonable development task that fits this infrastructure. Serverless deployment is very intriguing, escpecially for someone like me that doesn’t enjoy to fiddle with servers, operating systems and stuff.
No, I won’t reveal any detals about my project yet. But I want to share my experiences building a simple webapp – the good old hello world example – and deploy it on AWS Lambda.
Python 3.6 has been released just before Christmas. A great new release of my favorite programming language!
It includes some nice additions to the language: f-strings, asynchronous generators, asynchronous comprehensions, asyncio has been stabilized and a lot more.
Here are some handy links to get up to date with this new release.
- Of course I have to link to the official release notes. Personally I find them a bit to detailed to get a good overview about the big changes. But as always they include the best examples to demonstrate the new features.
- Infoworld published a nice article about the bigger changes – Python 3.6 is packed with goodness. It provides no examples, but a lot more context for the big changes and also some links to follow up.
- If you are more into videos, Brett Cannon (@brettsky) has given a nice talk about what is new and hot in 3.6 on PyCon Canada – What’s new in Python 3.6.
- And for a Django developer it is now about time to drop Python 2. Django 2.0 will drop support for Python 2.
- Armin Ronacher posted an important security advice, why you should be careful when using the new f-strings – Be Careful with Python’s New-Style String Format.
- David Beazley (@dabeaz) showed of some nice f-string magic on Twitter.
- And here is a nice addition for all people still thinking, it is a bad idea to switch – 10 awesome features of Python that you can’t use because you refuse to upgrade to Python 3.
Image credit: Quinn Dombrowski. Shared under the Creative Commons Attribution-ShareAlike 2.0 Generic license.