InfoQ Homepage Python Content on InfoQ
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Designing Secure Tenant Isolation in Python for Serverless Apps
Software as a Service (SaaS) has become a very common way to deliver software today. While providing the benefits of easy access to users without the overhead of having to manage the operations themselves, this flips the paradigm and places the responsibility on software providers for maintaining ironclad SLAs, as well as all of the security and data privacy requirements.
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How to Build Interactive Data Visualizations for Python with Bokeh
In this article, the author shows how to use one of the powerful Python tools Bokeh in creating data visualizations with custom charts.
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Programming Languages InfoQ Trends Report - October 2019
This article provides a summary of how the InfoQ editorial team currently sees the adoption of technology and emerging trends within the programming language space, as of Q3, 2019.
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How BuzzFeed Migrated from a Perl Monolith to Go and Python Microservices
Starting in 2016 BuzzFeed began a re-architecture project moving from a single monolithic application written in Perl to a set of microservices. The main reason for the move was that the Perl application was proving hard to scale, essential given that buzzfeed.com alone serves about 7 billion page views/month.
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Monitoring SRE's Golden Signals
Golden signals are increasingly popular these days due to the rise of SRE. This article outlines what golden signals are, and how to monitor and use them in the context of various common services.
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Transcrypt: Anatomy of a Python to JavaScript Compiler
On the web front end, web development is one size fits all: JavaScript. The Transcrypt Python to JavaScript compiler is a relatively new open source project, aiming at executing Python 3.6 at JavaScript speed, with comparable file sizes. In this article, Jacques de Hooge talks about the requirements in building a transpiler and how Transcrypt is built to meet those demands.
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Article Series: An Introduction to Machine Learning for Software Developers
Get an introduction to some powerful but generally applicable techniques in machine learning for software developers. These include deep learning but also more traditional methods that are often all the modern business needs. After reading the articles in the series, you should have the knowledge necessary to embark on concrete machine learning experiments in a variety of areas on your own.
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Introduction to Machine Learning with Python
This series will explore various topics and techniques in machine learning, arguably the most talked-about area of technology and computer science over the past several years. We’ll begin, in this article, with an extended “case study” in Python: how can we build a machine learning model to detect credit card fraud?
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Article Series: Getting a Handle on Data Science as a Software Developer
Software developers and managers are realizing that they need data science among their skills, to be able to tackle pressing problems. In this series, field experts provide guidance to help us navigate among the available data analysis options. They explore ways of understanding where data science is needed and where it’s not, and how to turn it into an asset.
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Getting Started with Machine Learning
A quick introduction to the machine learning field, exploring both supervised and unsupervised approaches.
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Pack Up the Wagon, We're Going Offline
Enterprise customers often have specific requirements and restrictions. Sometimes, an internet connection isn't always available, so traditional package management techniques don't work. Nir Cohen describes Wagon, which takes Python wheels, packages them together, adds metadata, and allows for offline extraction and installation.
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No Starch Press' Python Playground Review and Q&A with the Author
No Starch Press’ Python Playground provides a fairly large and varied collection of projects that aim to show how Python can be used in such different contexts as creating ASCII art, birds simulation, interfacing to Raspberry Pi, and more. InfoQ has spoken to the book’s author, Mahesh Venkitachalam.