This blog series from Sheroy Marker cover the principles of CD of microservices. Get a practical guide on designing CD workflows for microservices, testing strategies, trunk based development, feature toggles and environment plans.
Several modern programming languages have so-called “null-coalescing” or “null- aware” operators, including C# , Dart, Perl, Swift, and PHP (starting in version 7). These operators provide syntactic sugar for common patterns involving null references.
In this review, we’ll be taking a look at our favorite options and explain which ones to use.
Recently, I was given a dataset that contained sensitive information about customers and that should not under any circumstance be made public. The dataset resided on one of our servers which I deem to be a reasonably secure location. I wanted to copy the data to my local drive, in order to work with the data more comfortably and at the same time not having to fear that the data is less save. So, I wrote a little script that changes the data, while still preserving some key information. I will detail all the steps that I have taken, and highlight some handy tricks along the way.
I am creating a series of blog posts to help you develop, deploy and run (mostly) Python applications on AWS Lambda using Serverless Framwork.
Implementer’s Guide to Scalable and Robust Internet Telephony with Session Initiation Protocol in ClientServer and Peer-to-Peer modes in Python
Python extends its lead, and Assembly enters the Top Ten
We illustrate the application of two linear compression algorithms in python: Principal component analysis (PCA) and least-squares feature selection. Both can be used to compress a passed array, and they both work by stripping out redundant columns from the array. The two differ in that PCA operates in a particular rotated frame, while the feature selection solution operates directly on the original columns. As we illustrate below, PCA always gives a stronger compression. However, the feature selection solution is often comparably strong, and its output has the benefit of being relatively easy to interpret — a virtue that is important for many applications.
In this tutorial you will learn how to build a “people counter” with OpenCV and Python. Using OpenCV, we’ll count the number of people who are heading “in” or “out” of a department store in real-time.
I have been experimenting with keyword extraction techniques against the NIPS Papers dataset, consisting of titles, abstracts and full text of all papers from the Neural Information Processing Systems (NIPS) conference from 1987-2017, and contributed by Ben Hamner. The collection has 7239 papers written by 9785 authors. The reason I preferred this dataset to others such as Reuters or Medline is because it is smaller, and I can be both programmer and domain expert, and because I might learn interesting things while combing through the text of the papers looking for patterns to exploit.
In this article, we will be going through building queries for Wikidata with Python and SPARQL by taking a look where mayors in Europe are born.
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Display image and video camera in your ANSI terminal!
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A code gallery for person re-identification with mxnet-gluon, and I will reproduce many STOA algorithm.
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Cookiecutter django-SHOP is a blueprint for an e-commerce site based on django-CMS.
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Ethereum Web Service