InfoQ Homepage Dynamic Languages Content on InfoQ
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Avoiding React Performance Pitfalls
Alex Grigoryan discusses the performance problems found and their solutions moving from Backbone/Java to React/Node.js at @WalmartLabs.
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Billions of Events Per Day with Elixir
Danni Friedland shares insights Node.js and JavaScript developers need to know before deciding to jump into the Elixir boat.
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Parasitic Programming Languages
David Nolen examines the benefits and tradeoffs associated with creating a language based on an existing runtime, with a special focus on the Clojure and ClojureScript projects.
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Ember and the State of Web Frameworks
Yehuda Katz discusses the big changes on the web in the past five years and how they affected Ember, plus Ember’s latest project Glimmer, which allows using Ember’s view layer standalone.
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A Practical Road to SaaS in Python
Armin Ronacher discusses his experiences building SaaS businesses on a Python technology stack from a security and scalability point of view, and what other technologies work well with Python.
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Full-Scale Elm in Production
Richard Feldman introduces Elm, how it works, what differentiates it from the other front-end technologies, and gives practical advice for introducing it to an existing JavaScript codebase.
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The Hitchhiker's Guide to Serverless JavaScript
Steve Faulkner discusses Bustle's entire serverless stack. He talks about the good, the bad, and the ugly, sharing real numbers from production systems.
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Building Hypermedia Clients
Todd Brackley demonstrates provisioning a network of data through a JavaScript client to show that there is no magic and talks through some of the major design issues.
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Building Data Pipelines in Python
Marco Bonzanini discusses the process of building data pipelines and all the steps necessary to prepare data, focusing on data plumbing and going from prototype to production.
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Data Driven Products Now!
Dan McKinley discusses how Etsy is using data to validate their ideas and prototypes, turning some into real products.
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Build to Learn: Rapid Prototyping Methods
Sara Bayless da Costa discusses several prototyping methods helping to learn about product, gather quality feedback, and get the best version of a product out there as quickly as possible.
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Machine Learning and End-to-End Data Analysis Processes in Spark Using Python and R
Debraj GuhaThakurta discusses ML and data analysis processes in Spark using examples written in Python and R.
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