Open Source Directions hosted by OpenTeams

Open Source Directions hosted by OpenTeams

By Quansight, LLCTechnologyTech News
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Open Source Directions hosted by OpenTeams episodes

  • Episode 45: Julia
    In this episode of Open Source Directions we were joined by Jeff Bezanson and Katie Hyatt who talk about the work they have been doing with Julia. Julia is a programming language that was designed from the beginning for high performance. It programs compile to native code for multiple platforms via LLVM. Julia is dynamically typed, feels like a scripting language, and has good support for interactive use.
    Julia has a rich language of descriptive datatypes, and type declarations can be used to clarify and solidify programs. This language uses multiple dispatch as a paradigm, making it easy to express many object-oriented and functional programming patterns. It provides asynchronous I/O, debugging, logging, profiling, a package manager, and more.
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  • Episode 44: RecallGraph
    In this episode of Open Source Directions we were joined by Aditya Mukhopadhyay who talked about the work he has been doing with RecallGraph. RecallGraph is a versioned-graph data store - it retains all changes that its data (vertices and edges) have gone through to reach their current state. It supports point-in-time graph traversals, letting the user query any past state of the graph just as easily as the present.
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  • Episode 43: Jupyter & Nteract
    In this episode of Open Source Directions we were joined by Matthew Seal who talked about the work he has been doing with Jupyter and Nteract. Matthew also discussed a particular topic: common Jupyter tools and their adoption for various use cases in the wild.
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  • Episode 41: Spyder
    Spyder is a powerful scientific environment written in Python, for Python, and
    designed by and for scientists, engineers and data analysts. It offers a unique
    combination of the advanced editing, analysis, debugging, and profiling functionality
    of a comprehensive development tool with the data exploration, interactive execution,
    deep inspection, and beautiful visualization capabilities of a scientific package.
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  • Episode 40: Fortran
    Fortran is a compiled language which means that once written,
    the source code must be passed through a compiler to produce
    a machine executable that can be run.
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  • Episode 39: Apache Arrow
    Apache Arrow is a cross-language development platform for in-memory data.
    It supports zero-copy streaming messaging and has support for a number of
    languages, including C, C++, Python, R, Rust, and many others.
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  • Episode 38: Jupyter Book
    Jupyter Book lets you build an online book using a collection of
    Jupyter Notebooks and Markdown files. Its output is similar to the
    excellent Bookdown tool, and adds extra functionality for people
    running a Jupyter stack.
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  • Episode 37: PyJanitor
    Originally a port of the R package, pyjanitor has evolved from a set of convenient data cleaning
    routines into an experiment with the method chaining paradigm. Data preprocessing usually consists
    of a series of steps that involve transforming raw data into an understandable/usable format.
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  • Episode 36: Bokeh 2.0
    Bokeh is an interactive visualization library for modern web browsers.
    It provides elegant, concise construction of versatile graphics, and
    affords high-performance interactivity over large or streaming datasets.
    Bokeh can help anyone who would like to quickly and easily make interactive
    plots, dashboards, and data applications.
    This is our second time visiting Bokeh, in preperation for the v2.0 release!
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