Show HN: A realtime node-based audio synth based on LLVM

A synth built in the current version of Axiom

Axiom is an extremely flexible node-based realtime audio synthesizer. It was originally designed for size-constrained environments such as PC intros in the demoscene, but is entirely open source and is becoming an excellent free tool for any musician.
Musician-friendly (ie knobs and sliders) interface
Highly customizable and flexible through a node editor and custom scripting language, named Maxim
Export to replayer with no dependencies (not even the standard library)
Use any DAW with VSTi support for note editing and automation
There are currently pre-packaged versions available for Windows and macOS (alpha, let us know of any issues) on the Releases page. Stay tuned for Linux builds!
Usage Guide · Example Projects · Release Notes
Axiom currently supports the following audio backends:
Standalone with PortAudio – doesn’t require a DAW or host, allowing experimentation with the editor. MIDI input can be entered with a regular computer keyboard (no actual MIDI

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October Brings Node.js 10.x to LTS and Node.js 11 to Current

October is always a busy month for the Node.js Project. Node.js 10.x becomes the latest long term support (LTS) release on October 30. Node.js 11 becomes the current release line starting later today (October 23) and for the next six months.If you are unfamiliar with the Node.js release cycle:Even numbered releases are LTS; they generally receive 30 months of support once they become LTS.Odd numbered releases are current releases and are supported for six months.For more details on releases, check out this video or read about them here.The general themes for both of these releases focus on performance enhancements, security, new JavaScript features, and expanded tracing and diagnostics thanks to improved integration with the V8 team and contributions from the community.What version should I use?If you are using Node.js in production use an LTS version. LTS release lines focus on stability, extended support and provide a reliable platform for applications

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A Gentle Visual Intro to Data Analysis in Python Using Pandas

If you’re planning to learn data analysis, machine learning, or data science tools in python, you’re most likely going to be using the wonderful pandas library. Pandas is an open source library for data manipulation and analysis in python.

Loading Data
One of the easiest ways to think about that, is that you can load tables (and excel files) and then slice and dice them in multiple ways:

Pandas allows us to load a spreadsheet and manipulate it programmatically in python. The central concept in pandas is the type of object called a DataFrame – basically a table of values which has a label for each row and column. Let’s load this basic CSV file containing data from a music streaming service:

df = pandas.read_csv(‘music.csv’)

Now the variable df is a pandas DataFrame:

We can select any column using its label:

We can select one or multiple rows using their numbers (inclusive of both bounding row numbers):


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It’s a powerful machine, but not THAT powerful

It’s a dark and stormy night when this IT pilot fish gets a call from an older customer with a departmental system.”This company keeps the system in a ventilated closet, and it turns out the caller is now in the closet with the machine,” says fish.”The caller describes how he started the regular backup, and the computer suddenly stopped responding.”I ask what the computer looks like. The caller responds that it’s completely dark, and won’t turn on. The caller says he’s very worried he has broken something important.”Then he volunteers that he’s very deeply worried that he really caused serious damage, because all the lights in the office are now out.To read this article in full, please click here

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