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OSS Leftovers

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OSS
  • Letter of Recommendation: Bug Fixes

    I wouldn’t expect a nonprogrammer to understand the above, but you can intuit some of what’s going on: that we don’t need ImageMagick to scale images anymore, because the text editor can scale images on its own; that it’s bad form to spell-check hex values, which specify colors; that the bell is doing something peculiar if someone holds down the alt key; and so forth.

    But there’s also something larger, more gladdening, about reading bug fixes.

    My text editor, Emacs, is a free software project with a history going back more than 40 years; the codebase itself starts in the 1980s, and as I write this there are 136,586 different commits that get you from then to now. More than 600 contributors have worked on it. I find those numbers magical: A huge, complex system that edits all kinds of files started from nothing and then, with nearly 140,000 documented human actions, arrived at its current state. It has leaders but no owner, and it will move along the path in which people take it. It’s the ship of Theseus in code form. I’ve probably used Emacs every day for more than two decades. It has changed me, too. It will outlive me.

    Open source is a movement, and even the charitably inclined would call it an extreme brofest. So there’s drama. People fight it out in comments, over everything from semicolons to codes of conduct. But in the end, the software works or it doesn’t. Politics, our personal health, our careers or lives in general — these do not provide a narrative of unalloyed progress. But software, dammit, can and does. It’s a pleasure to watch the code change and improve, and it’s also fascinating to see big companies, paid programmers and volunteers learning to work together (the Defense Department is way into open source) to make those changes and improvements. I read the change logs, and I think: Humans can do things.

  • The Top 17 Free and Open Source Network Monitoring Tools

    Choosing the right network monitoring solution for your enterprise is not easy.

  • Hedge-fund managers are overwhelmed by data, and they're turning to an unlikely source: random people on the internet

    Alternative data streams of satellite images and cellphone-location data are where managers are now digging for alpha, as new datasets are created every day. And hedge funds have been spending serious cash searching for those who can take all this information and quickly find the important pieces.

    Now, as margins shrink and returns are under the microscope, hedge funds are beginning to consider a cheaper, potentially more efficient way to crunch all this data: open-source platforms, where hundreds of thousands of people ranging from finance professionals to students, scientists, and developers worldwide scour datasets — and don't get paid unless they find something that a fund finds useful.

  • TD Ameritrade Is Taking Its First Steps Towards Major Open Source Contributions

    STUMPY is a python library to identify the patterns and anomalies in time series data. STUMPY has benefited from open source as a means to shorten development roadmaps since the early 2000s and it represents a new opportunity for TD Ameritrade to give back to the developer community.

  • The Future of Open Source Big Data Platforms

    Three well-funded startups – Cloudera Inc., Hortonworks Inc., and MapR Technologies Inc. — emerged a decade ago to commercialize products and services in the open-source ecosystem around Hadoop, a popular software framework for processing huge amounts of data. The hype peaked in early 2014 when Cloudera raised a massive $900 million funding round, valuing it at $4.1 billion.

  • No Easy Way Forward For Commercial Open Source Software Vendors

    While still a student in 1995, Kimball developed the first version of GNU Image Manipulation Program (GIMP) as a class project, along with Peter Mattis. Later on as a Google engineer, he worked on a new version of the Google File System, and the Google Servlet Engine. In 2012, Kimball, Mattis, and Brian McGinnis launched the company Viewfinder, later selling it to Square.

  • 6 Reasons Why Developers Should Contribute More To Open Source

    Even by fixing minor things like a bug in a library or writing a piece of documentation can also help the developers to write readable or maintainable code. They can independently suggest to the community and generally tend to stick by the rules of writing a code that is easy to understand. The fact that the code will be exposed to everyone naturally makes them write focus on making it readable.

  • WIDE Project, KDDI develop router with open-source software, 3.2T-packet transmission

    The WIDE Project has adopted a router developed by Japanese operator KDDI. The router runs open-source software, and will be used with the networks operated and managed by the WIDE Project. The router will use open-source software with up to 3.2T-packet transmission.

    For this project, KDDI plans to start tests this month to verify the practical utility and interoperability of these routers when put to use in the actual service environment. The WIDE Project will be in charge of network administration and definition of requirements for router implementation.

  • Lack of progress in open source adoption hindering global custody’s digitisation

    Custody industry is lagging behind the rest of the financial services sector for open source projects, according to industry experts.

  • TNF: Industry should be focusing on open source development

    According to O'Shea, open source and the community are helping firms to find and attract experienced technology talent “uber engineers”.

  • Google Open Sources TensorNetwork , A Library For Faster ML And Physics Tasks

    “Every evolving intelligence will eventually encounter certain very special ideas – e.g., about arithmetic, causal reasoning and economics–because these particular ideas are very much simpler than other ideas with similar uses,” said the AI maverick Marvin Minsky four decades ago.

    Mathematics as a tool to interpret nature’s most confounding problems from molecular biology to quantum mechanics has so far been successful. Though there aren’t any complete answers to these problems, the techniques within domain help throw some light on the obscure corners of reality.

  • Open source to become a ‘best practice’

    There are many magic rings in this world… and none of them should be used lightly. This is true.

    It is also true that organisations in every vertical are now having to work hard and find automation streams that they can digitise (on the road to *yawn* digital transformation, obviously) and start to apply AI and machine learning to.

    Another key truth lies in the amount of codified best practices that organisations now have the opportunity to lay down.

    One we can denote a particular set of workflows in a particular department (or team, or group, or any other collective) to be deemed to be as efficient as possible, then we can lay that process down as a best practice.

  • 10 Open-Source and Free CAD Software You Can Download Right Now

    Many CAD software products exist today for anyone interested in 2D or 3D designing.

    From browser tools to open-source programs, the market is full of free options available for hobbyists or small companies just starting out.

More in Tux Machines

Announcing coreboot 4.10

The 4.10 release covers commit a2faaa9a2 to commit ae317695e3 There is a pgp signed 4.10 tag in the git repository, and a branch will be created as needed. In nearly 8 months since 4.9 we had 198 authors commit 2538 changes to master. Of these, 85 authors made their first commit to coreboot: Welcome! Between the releases the tree grew by about 11000 lines of code plus 5000 lines of comments. Read more Also: Coreboot 4.10 Released With New Support For Many Chromebooks & Random Motherboards

Red Hat and Fedora Leftovers

  • Building an organization that's always learning: Tips for leaders

    In open organizations, informal learning is critical to success. "Informal learning" accounts for all learning that occurs outside a training program, a classroom, or another formalized instruction setting. Unlike the learning in these formalized learning settings, informal learning is unstructured, personal, and voluntary. As a result, systematic study of it is difficult. But due to the prevalence and importance of informal learning in workplaces, several researchers have called for additional research into the subject—and particularly for the design of instruments to actually measure informal learning. Such instruments could likewise be useful in open organizations hoping to measure and foster informal learning practices among employees.

  • 9 people for sysadmins to follow on Twitter

    While Twitter certainly isn't the most open source platform, the open source community on the social network brings a lot of great minds together on a daily basis. The site, as I see it, also democratizes access to these brilliant minds since we're all just one @ away. Here are nine people whose Twitter accounts are making my pursuit of sysadmin knowledge, and its continued evolution, better. They fall across the spectrum of technology with the one thing they have in common being their passionate, informative, and thoughtful perspective. They share a wealth of knowledge from explaining Linux commands through comics, to applying a PhD's worth of knowledge to making DevOps make sense.

  • Fedora 32 System-Wide Change proposal: x86-64 micro-architecture update
    Fedora currently uses the original K8 micro-architecture (without 3DNow! and other AMD-specific parts) as the baseline....
    
  • Fedora Developers Discuss Raising Base Requirement To AVX2 CPU Support

    An early change being talked about for Fedora 32, due out in the spring of next year, is raising the x86_64 CPU requirements for running Fedora Linux. When initially hearing of this plan, the goal is even more ambitious than I was initially thinking: AVX2. A feature proposal for Fedora 32 would raise the x86_64 base-line for their compiler builds to needing AVX2. Advanced Vector Extensions 2 is Intel Sandy Bridge and newer or AMD Jaguar/Bulldozer and newer. This came as quite a surprise even to myself that Fedora is planning to jump straight from their existing AMD K8 baseline to now AVX2-supportive CPUs.

  • Stable docker CE for Fedora 30 are available!

    Do you use docker? If you are using Fedora 30 then I have good news for you. They officially relesed stable docker CE for Fedora 30, yay! Most of us have been waiting for stable docker since February, OMG! You can check issue #600 how frustrating most of docker users because we don’t have stable release and unable to use testing or nightly release because of missing containerd.io and forced dev to seek alternatives using old repo (F29) or using Podman as workaround.

  • Outreachy FHP week 7: Pytest, UI enhancements, FAS search

    From Outreachy.org: The theme for this week is “Modifying Expectations”. Outreachy mentors and interns start the internship with a specific set of project goals. However, usually those goals need to be modified, and that’s perfectly fine! Delays to projects happen. Maybe your project turned out to be more complicated than you or your mentor anticipated. Maybe you needed to learn some concepts before you could tackle project tasks. Maybe the community documention wasn’t up-to-date or was wrong. These are all perfectly valid reasons for projects to be a bit behind schedule, as long as you’ve been working full-time on the project. In fact, free and open source contributors have to deal with these kinds of issues all the time. Projects often seem simple until you start working on them. Project timelines are ususally a very optimistic view of what could happen if everything goes exactly as planned. It often doesn’t, but people still make optimistic plans. Modifying your project timeline to set more realistic goals is a skill all contributors need to learn. [....] I was a beginner in Django when I started working on this project. Earlier I worked on JavaScript-based framework, and switching to Python was a big change for me. So, it was always learning and implementing on my part. Since Django was new to me, I had to learn it fast, at least the core concept. I found some good resources but they were so detailed that at the end of the document, I would have lost interest in some of the topics. Then I found this tutorial, which turned out to be the perfect platform to have an overall grasp of the widely used python framework. I learned about containers, their importance and concept of virtualization. How Docker can also be used when we want to deploy an application to an environment. Understood the concept behind it, learned the basic commands and how to deal with multiple Docker containers. In the second half of my internship, I improved and wrote tests of the project without having any prior knowledge of the concept at the beginning.

Programming Leftovers

  • Excellent Free Books to Learn Java

    Java is a general-purpose, concurrent, class-based, object-oriented, high-level programming language and computing platform first released by Sun Microsystems in 1995. It is related in some ways to C and C++, in particular with regard to its syntax, and borrows a few ideas from other languages. Java applications are compiled to bytecode that can run on any Java virtual machine (JVM) regardless of computer architecture. Java is designed to be simple enough that many programmers can quickly become proficient in the language. It’s one of the most popular programming languages especially for client-server web applications.

  • GFX-RS Portability 0.7 Released With Vulkan Events, Binding Model Improvements

    The GFX-RS high performance graphics API for the Rust programming language and based on Vulkan while mapping to Metal when on Apple systems is out with a new release. GFX-RS continues to be about being a cross-platform API for Rust that is bindless and high performance while retaining the traits of Vulkan but with back-ends as well for Direct3D 11/12, Metal, and even OpenGL 2 / GLES2.

  • Use the Requests module to directly retrieve the market data

    Hello and welcome back to our cryptocurrency project. In the previous article I had mentioned before that I want to use the cryptocompy module to create our new cryptocurrency project, however, after a closer look at the CriptoCompare API I think we have better used the original API to make the rest call instead of using the wrapper module because the original API seems to provide more returned data type than the one offered by the cryptocompy module.

  • Eli Bendersky: Faster XML stream processing in Go

    XML processing was all the rage 15 years ago; while it's less prominent these days, it's still an important task in some application domains. In this post I'm going to compare the speed of stream-processing huge XML files in Go, Python and C and finish up with a new, minimal module that uses C to accelerate this task for Go. All the code shown throughout this post is available in this Github repository the new Go module is here.

  • How to Use Binder and Python for Repoducible Research

    In this post we will learn how to create a binder so that our data analysis, for instance, can be fully reproduced by other researchers. That is, in this post we will learn how to use binder for reproducible research. In previous posts, we have learned how to carry out data analysis (e.g., ANOVA) and visualization (e.g., Raincloud plots) using Python. The code we have used have been uploaded in the forms of Jupyter Notebooks.

  • Wingware Blog: Introducing Functions and Methods with Refactoring in Wing Pro

    In this issue of Wing Tips we explain how to quickly create new functions and methods out of existing blocks of Python code, using Wing Pro's Extract Method/Function refactoring operation. This is useful whenever you have some existing code that you want to reuse in other places, or in cases where code gets out of hand and needs to be split up to make it more readable, testable, and maintainable. Wing supports extracting functions and methods for any selected code, so long as that code does not contain return or yield statements. In that case automatic extraction is not possible, since Wing cannot determine how the extracted function should be called from or interact with the original code.

  • How to Use Binder and Python for Reproducible Research

    In this post we will learn how to create a binder so that our data analysis, for instance, can be fully reproduced by other researchers. That is, in this post we will learn how to use binder for reproducible research. In previous posts, we have learned how to carry out data analysis (e.g., ANOVA) and visualization (e.g., Raincloud plots) using Python. The code we have used have been uploaded in the forms of Jupyter Notebooks. Although this is great, we also need to make sure that we share our computational environment so our code can be re-run and produce the same output. That is, to have a fully reproducible example, we need a way to capture the different versions of the Python packages we’re using.

  • NumPy arange(): How to Use np.arange()

    NumPy is the fundamental Python library for numerical computing. Its most important type is an array type called ndarray. NumPy offers a lot of array creation routines for different circumstances. arange() is one such function based on numerical ranges. It’s often referred to as np.arange() because np is a widely used abbreviation for NumPy. Creating NumPy arrays is important when you’re working with other Python libraries that rely on them, like SciPy, Pandas, Matplotlib, scikit-learn, and more. NumPy is suitable for creating and working with arrays because it offers useful routines, enables performance boosts, and allows you to write concise code.

  • Cogito, Ergo Sumana: Beautiful Soup is on Tidelift

    I've been doing a tiny bit of consulting for Tidelift for a little over a year now, mainly talking about them to open source maintainers in the Python world and vice versa. (See my October 2018 piece "Tidelift Is Paying Maintainers And, Potentially, Fixing the Economics of an Industry".) And lo, in my household, my spouse Leonard Richardson has signed up as a lifter for Beautiful Soup, his library that helps you with screen-scraping projects.

  • Chris Moffitt: Automated Report Generation with Papermill: Part 1

    This guest post that walks through a great example of using python to automate a report generating process. I think PB Python readers will enjoy learning from this real world example using python, jupyter notebooks, papermill and several other tools.

  • Cryptocurrency user interface set up

    As mentioned above, in this article we will start to create the user interface of our latest cryptocurrency project. Along the path we will also use the CryptoCompare API to retrieve data.

  • Python Snippet 2: Quick Sequence Reversal
  • 10x Evilgineers | Coder Radio 367

    Mike rekindles his youthful love affair with Emacs and we debate what makes a "10x engineer". Plus the latest Play store revolt and some of your feedback.

BlueStar Linux 5.2.1

Today we are looking at BlueStar Linux 5.2.1. This release of BlueStar is an Arch rolling distro and comes with Linux Kernel 5.2.1 and KDE Plasma 5.16.3 and uses about 700MB of ram when idling. Bluestar Linux is a beautiful Arch/KDE distro that works great out of the box and is receiving a lot of love from their very active developer. Read more Direct/video: BlueStar Linux 5.2.1 Run Through