1,312 Matching Annotations
  1. Sep 2020
  2. docs.google.com docs.google.com
    Metaphysics and JavaScript
    2
    1. TylerRick 16 Sep 2020

      It turns out that even the length of time an element has been mounted is an important piece of state that determines what pixels the user sees. And some of this state can’t simply be lifted into our application state.

      What this means is that our desire to express UI using pure functions is in direct conflict with the very nature of the DOM. It’s a great way to describe a state => pixels transformation — perfect for game rendering or generative art — but when we’re building apps on the web, the idea chafes against the reality of a stateful medium.

      state management state (software) functional programming conflict
    2. TylerRick 16 Sep 2020

      Functions have lots of interesting and useful properties. You can isolate them. You can compose them. You can memoize them. In other words, functional UI feels correct, and powerful, in a way that wasn’t true of whatever came before it. I think this is why people get quasi-religious about React. It’s not that it’s Just JavaScript. It’s that it’s Just Functions. It’s profound.

      it's just _ functions functional programming
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    docs.google.com/presentation/d/1PUvpXMBEDS45rd0wHu6tF3j_8wmGC6cOLtOw2hzU-mw/edit
  3. www.codingwithjesse.com www.codingwithjesse.com
    The simplest Svelte component is an empty file - DEV
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    codingwithjesse.com/blog/the-simplest-svelte-component-is-an-empty-file/
  4. jsreport.io jsreport.io
    Why Is React More Popular Than Angular?
    1
    1. TylerRick 15 Sep 2020
      A paradigm is a model or pattern. In JavaScript, there are a number of popular paradigms including object-oriented programming (OOP) and functional programming (FP). Paradigms are more important than is sometimes recognized. They help form mental models for solving problems. Becoming well-versed in the principles of a given paradigm can help accelerate development by providing mental shortcuts for solving the challenges that arise while building applications. They can also help produce higher quality software.
      object-oriented vs. functional programming programming paradigm
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    jsreport.io/why-is-react-more-popular-than-angular/
  5. enterprisecraftsmanship.com enterprisecraftsmanship.com
    DRY vs DAMP in Unit Tests
    1
    1. skrajewski 15 Sep 2020
      we need to step back and make a closer look at the DRY principle. As I mentioned earlier, it stands for "Don’t Repeat Yourself" and requires that any piece of domain knowledge has a single representation in your code base. The words domain knowledge are key here. DRY is not about duplicating code. It is specifically about duplicating domain knowledge

      This is actually a good point – to have a single representation of specific piece of domain knowledge in the code.

      DRY is not about duplicating code.

      programming design patterns programming rules
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    enterprisecraftsmanship.com/posts/dry-damp-unit-tests/
  6. ramdajs.com ramdajs.com
    Ramda Documentation
    1
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    ramdajs.com/
  7. github.com github.com
    codecheckers/covid-uk
    1
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    github.com/codecheckers/covid-uk
  8. github.com github.com
    aaronpeikert/reproducible-research
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    github.com/aaronpeikert/reproducible-research
  9. zenodo.org zenodo.org
    CODECHECK certificate 2020-008
    1
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    zenodo.org/record/3746024
  10. www.reddit.com www.reddit.com
    r/BehSciMeta - Comment by u/nick_chater on ”Programming errors and their implications”
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    reddit.com/r/BehSciMeta/comments/gsowog/programming_errors_and_their_implications/
  11. www.reddit.com www.reddit.com
    r/BehSciMeta - No appeasement of bad faith actors
    1
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    reddit.com/r/BehSciMeta/comments/gv0y99/no_appeasement_of_bad_faith_actors/
  12. Aug 2020
  13. pragmaticpineapple.com pragmaticpineapple.com
    Do Not Follow JavaScript Trends
    1
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    pragmaticpineapple.com/do-not-follow-javascript-trends/
  14. www.alec.fyi www.alec.fyi
    dorking (how to find anything on the Internet)
    1
    1. pyxelr 14 Aug 2020
      find every email on a web page that you're on. The big kahuna - this works for every website. Inject it into a site with Chrome DevTools (more here)

      Use this code below to find every e-mail on a webpage:

      var elems = document.body.getElementsByTagName("*");
var re = new RegExp("(^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$)");
for (var i = 0; i < elems.length; i++) {
    if (re.test(elems[i].innerHTML)) {
        console.log(elems[i].innerHTML);
    }
}
      JavaScript programming
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    alec.fyi/dorking-how-to-find-anything-on-the-internet.html
  15. stackoverflow.blog stackoverflow.blog
    Why the developers who use Rust love it so much · Magpie
    2
    1. TylerRick 03 Aug 2020
      “I came to Rust from Haskell, and I feel that Haskell is a very elegant and safe language. The biggest differentiator for me is that there is a greater difference between high-performance code and idiomatic ‘clean’ code in Haskell than in Rust. Most Rust code looks like most other Rust code, even when it performs well. Haskell can become unfamiliar real quick if someone is operating under different libraries and goals from what you are typically doing. Small differences in syntax can result in huge differences in behavior, and Rust has more uniformity on that axis.”
      idiomatic code style (programming languages) uniformity consistency coding style
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    stackoverflow.blog/2020/06/05/why-the-developers-who-use-rust-love-it-so-much/
  16. unix.meta.stackexchange.com unix.meta.stackexchange.com
    Which programming languages are appropriate here?
    1
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    unix.meta.stackexchange.com/questions/5622/which-programming-languages-are-appropriate-here
  17. Jul 2020
  18. devhints.io devhints.io
    Go cheatsheet
    1
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    devhints.io/go
  19. amp.dev amp.dev
    Resolving validation errors
    1
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    amp.dev/documentation/guides-and-tutorials/start/converting/resolving-errors/
  20. amp.dev amp.dev
    Create your AMP HTML page
    1
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    amp.dev/documentation/guides-and-tutorials/start/create/basic_markup/
  21. amp.dev amp.dev
    Create your first AMP Email
    1
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    amp.dev/documentation/guides-and-tutorials/start/create_email/
  22. bugs.ruby-lang.org bugs.ruby-lang.org
    Feature #15580: Proposal: method addition to class String called .indices ( String#indices ) - Ruby master - Ruby Issue Tracking System
    1
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    bugs.ruby-lang.org/issues/15580
  23. bugs.ruby-lang.org bugs.ruby-lang.org
    Feature #6596: New method for Arrays : Array#indexes - Ruby master - Ruby Issue Tracking System
    1
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    bugs.ruby-lang.org/issues/6596
  24. lamport.azurewebsites.net lamport.azurewebsites.net
    The TLA+ Home Page
    1
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    lamport.azurewebsites.net/tla/tla.html
  25. www.benkuhn.net www.benkuhn.net
    Essays on programming I think about a lot
    1
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    benkuhn.net/progessays/
  26. sourcediving.com sourcediving.com
    Less known changes in Ruby 2.7
    2
    2. TylerRick 21 Jul 2020
      When FrozenError is raised, it is usually difficult to determine from the context which was the frozen object that a modification was attempted on.Ruby 2.7 introduces FrozenError#receiver which will return the frozen object that modification was attempted on, similar to NameError#receiver. This can help pinpoint exactly what is the frozen object.
      introspection (programming)
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    sourcediving.com/less-known-changes-in-ruby-2-7-8d5db660370f
  27. www.ruby-lang.org www.ruby-lang.org
    Ruby 2.7.0 Released
    1
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    ruby-lang.org/en/news/2019/12/25/ruby-2-7-0-released/
  28. egghead.io egghead.io
    Learn JavaScript
    2
    1. svs_inthehouse 15 Jul 2020
      dynamic

      A dynamic language (Lisp, Perl, Python, Ruby) is designed to optimize programmer efficiency, so you can implement functionality with less code. A static language (C, C++, etc) is designed to optimize hardware efficiency, so that the code you write executes as quickly as possible. https://stackoverflow.com/questions/20563433/difference-between-static-and-dynamic-programming-languages#:~:text=A%20dynamic%20language%20(Lisp%2C%20Perl,executes%20as%20quickly%20as%20possible.

      dynamic programming
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    egghead.io/browse/frameworks/javascript
  29. bugs.ruby-lang.org bugs.ruby-lang.org
    Feature #16155: Add an Array#intersection method - Ruby master - Ruby Issue Tracking System
    1
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    bugs.ruby-lang.org/issues/16155
  30. en.wikipedia.org en.wikipedia.org
    Operator overloading - Wikipedia
    1
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    en.wikipedia.org/wiki/Operator_overloading
  31. en.wikipedia.org en.wikipedia.org
    ALGOL 68 - Wikipedia
    1
    1. TylerRick 13 Jul 2020
      Most of Algol's "special" characters (⊂, ≡, ␣, ×, ÷, ≤, ≥, ≠, ¬, ⊃, ≡, ∨, ∧, →, ↓, ↑, ⌊, ⌈, ⎩, ⎧, ⊥, ⏨, ¢, ○ and □) can be found on the IBM 2741 keyboard with the APL "golf-ball" print head inserted; these became available in the mid-1960s while ALGOL 68 was being drafted. These characters are also part of the Unicode standard and most of them are available in several popular fonts.
      innovative programming languages: use of special/mathematical symbols
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    en.wikipedia.org/wiki/ALGOL_68
  32. www.cleveroad.com www.cleveroad.com
    How to Find Programmers for Your Project?
    1
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    cleveroad.com/blog/find-programmers
  33. docdrop.org docdrop.org
    Rich Harris - Rethinking reactivity
    1
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    docdrop.org/video/AdNJ3fydeao/
  34. Jun 2020
  35. media-exp1.licdn.com media-exp1.licdn.com
    The use of R statistical package in controlled infrastructure. The case of Clinical Research industry
    1
    1. pyxelr 19 Jun 2020
      Typical software requirements specify the following
      • All software system inputs
      • All software system outputs
      • All functions that the software system will perform
      • All performance requirements that the software will meet, (e.g., data throughput, reliability, and timing)
      • The definition of all external and user interfaces, as well as any internal software-to-system interfaces
      • How users will interact with the system
      • What constitutes an error and how errors should be handled
      • Required response times
      • The intended operating environment for the software, if this is a design constraint (e.g. hardware platform, operating system)
      • All ranges, limits, defaults, and specific values that the software will accept
      • All safety related requirements, specifications, features, or functions that will be implemented in software
      softwarerequirements programming
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    media-exp1.licdn.com/dms/document/C4E1FAQHEnx6DMSkPWQ/feedshare-document-pdf-analyzed/0
  36. github.com github.com
    goby-lang/goby
    1
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    github.com/goby-lang/goby
  37. www.tutlane.com www.tutlane.com
    Android Tutorial - Tutlane
    1
    1. tutlane 11 Jun 2020
      Android is an operating system based on Linux with a Java programming interface for mobile devices such as Smartphone (Touch Screen Devices who supports Android OS) as well for Tablets too.  

      Android is an operating system based on Linux with a Java programming interface for mobile devices such as Smartphone (Touch Screen Devices who supports Android OS) as well for Tablets too.

      To learn more about android visit Android Tutorial

      tutlane programming learning android education
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    tutlane.com/tutorial/android
  38. www.tutlane.com www.tutlane.com
    Bootstrap Tutorial - Tutlane
    1
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    tutlane.com/tutorial/bootstrap
  39. www.tutlane.com www.tutlane.com
    LINQ Tutorial - Tutlane
    1
    1. tutlane 11 Jun 2020
      LINQ means Language Integrated Query and it was introduced in .NET Framework 3.5 to query the data from different data sources such as collections, generics, XML Documents, ADO.NET Datasets, SQL, Web Service, etc. in C# and VB.NET. 

      LINQ means Language Integrated Query and it was introduced in .NET Framework 3.5 to query the data from different data sources such as collections, generics, XML Documents, ADO.NET Datasets, SQL, Web Service, etc. in C# and VB.NET. To learn more about LINQ visit LINQ Tutorial

      linq .net tutlane programming learning education
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    tutlane.com/tutorial/linq
  40. www.tutlane.com www.tutlane.com
    Visual Basic (VB) Tutorial - Tutlane
    1
    1. tutlane 11 Jun 2020
      Visual Basic (VB) is an object-oriented programming language and that enables the developers to build a variety of secure and robust applications that run on the .NET Framework.

      Visual Basic (VB) is an object-oriented programming language and that enables the developers to build a variety of secure and robust applications that run on the .NET Framework.

      To learn more about visual basic refer Visual Basic (VB.NET) Tutorial

      tutlane programming visual basic .net learning
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    tutlane.com/tutorial/visual-basic/visual-basic-tutorial
  41. androidrookies.com androidrookies.com
    Where does a Programmer's brain store all the coding? - AndroidRookies
    1
    1. pyxelr 10 Jun 2020
      The brain uses the same area to save coding as it does to save our speech. They found that programming is like talking. The research found out that the brain regions that are most active during coding are those that are also relevant in the processing of natural language.
      • Study shows that programming knowledge is stored in the same area of the brain as speech.
      • Using fMRIs, researchers analysed which parts of the brain are activated during programming.
      • The results essentially show that programming is like talking - the same regions that are active when processing natural language are active during programming.
      • In the study, professional programmers were asked to repeatedly write some code and check other chunks of code for mistakes.
      programming science
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    androidrookies.com/where-does-a-programmers-brain-store-all-the-coding/
  42. martinheinz.dev martinheinz.dev
    Martin Heinz - Personal Website & Blog
    1
    1. pyxelr 05 Jun 2020
      in Python - setting up basic logger is very simple

      Apart from printing the result, it is better to debug with logging.

      Sample logger:

      import logging
logging.basicConfig(
    filename='application.log',
    level=logging.WARNING,
    format= '[%(asctime)s] {%(pathname)s:%(lineno)d} %(levelname)s - %(message)s',
    datefmt='%H:%M:%S'
)

logging.error("Some serious error occurred.")
logging.warning('Function you are using is deprecated.')

      the sample result:

      [12:52:35] {<stdin>:1} ERROR - Some serious error occurred.
[12:52:35] {<stdin>:1} WARNING - Function you are using is deprecated.

      to find its location, type:

      logging.getLoggerClass().root.handlers[0].baseFilename
      Python debugging programming
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    martinheinz.dev/blog/24
  43. May 2020
  44. medium.com medium.com
    The S.O.L.I.D Principles in Pictures
    5
    1. pyxelr 31 May 2020
      - High-level modules should not depend on low-level modules. Both should depend on the abstraction.- Abstractions should not depend on details. Details should depend on abstractions.

      SOLI(D)

      Dependency Inversion

      programming
    3. pyxelr 31 May 2020
      If S is a subtype of T, then objects of type T in a program may be replaced with objects of type S without altering any of the desirable properties of that program.

      SO(L)ID

      Liskov Substitution

      programming
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    medium.com/backticks-tildes/the-s-o-l-i-d-principles-in-pictures-b34ce2f1e898
  45. psyarxiv.com psyarxiv.com
    A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker
    1
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    psyarxiv.com/8xzqy/
  46. github.com github.com
    phusion/traveling-ruby
    1
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    github.com/phusion/traveling-ruby
  47. www.digital-democracy.org www.digital-democracy.org
    The effect of surviellance capitalism on social change efforts, with Allen Gunn
    1
    1. TylerRick 22 May 2020
      Don’t go to code academy, go to design academy. Be advocates of the user & consumer. It’s not about learning how to code, it’s about translating real-world needs to technological specifications in just ways that give end users agency and equity in design, development and delivery. Be a champion of user-centric design. Learn how to steward data and offer your help.

      The importance of learning to design, and interpreting/translating real-world needs.

      user agency programming comparison with: design (general) contrast needs specification stewardship user-centric helping others equity development
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    digital-democracy.org/blog/surveillance/
  48. www.reddit.com www.reddit.com
    index - swift
    1
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    reddit.com/r/swift/wiki/index/
  49. learning.oreilly.com learning.oreilly.com
    Lesson 12. Creating your own types
    2
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    learning.oreilly.com/library/view/get-programming-with/9781617293764/kindle_split_022.html
  50. onlinelibrary.wiley.com onlinelibrary.wiley.com
    A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19
    1
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    onlinelibrary.wiley.com/doi/10.1002/nav.21905
  51. fire.ci fire.ci
    The real difference between CI and CD
    9
    1. pyxelr 09 May 2020
      Continuous Delivery of Deployment is about running as thorough checks as you can to catch issues on your code. Completeness of the checks is the most important factor. It is usually measured in terms code coverage or functional coverage of your tests. Catching errors early on prevents broken code to get deployed to any environment and saves the precious time of your test team.

      Continuous Delivery of Deployment (quick summary)

      programming DevOps
    2. pyxelr 09 May 2020
      Continuous Integration is a trade off between speed of feedback loop to developers and relevance of the checks your perform (build and test). No code that would impede the team progress should make it to the main branch.

      Continuous Integration (quick summary)

      programming DevOps
    4. pyxelr 09 May 2020
      A good CI build: Ensures no code that breaks basic stuff and prevents other team members to work is introduced to the main branch Is fast enough to provide feedback to developers within minutes to prevent context switching between tasks

      Good CI build

      programming DevOps
    5. pyxelr 09 May 2020
      The idea of Continuous Delivery is to prepare artefacts as close as possible from what you want to run in your environment. These can be jar or war files if you are working with Java, executables if you are working with .NET. These can also be folders of transpiled JS code or even Docker containers, whatever makes deploy shorter (i.e. you have pre built in advance as much as you can).

      Idea of Continuous Delivery

      programming DevOps
    8. pyxelr 09 May 2020
      The app should build and start Most critical features should be functional at all times (user signup/login journey and key business features) Common layers of the application that all the developers rely on, should be stable. This means unit tests on those parts.

      Things to be checked by Continous Integration

      programming DevOps
    9. pyxelr 09 May 2020
      Continuous Integration is all about preventing the main branch of being broken so your team is not stuck. That’s it. It is not about having all your tests green all the time and the main branch deployable to production at every commit.

      Continuous Integration prevents other team members from wasting time through a pull of faulty code

      programming DevOps
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    fire.ci/blog/the-difference-between-ci-and-cd/
  52. www.sitepoint.com www.sitepoint.com
    ES6 in Action: Enhanced Object Literals — SitePoint
    1
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    sitepoint.com/es6-enhanced-object-literals/
  53. muldoon.cloud muldoon.cloud
    Rules of thumb for a 1x developer
    10
    2. pyxelr 03 May 2020
      What people will say is that estimates are for planning – that their purpose is to figure out how long some piece of work is going to take, so that everybody can plan accordingly. In all my five years shipping stuff, I can only recall one project where things really worked that way.

      Project estimations are just energy drainers and stress producers

      management programming
    3. pyxelr 03 May 2020
      Be explicit about the difference between hard deadlines

      Different types of deadlines:

      • Hard deadline - something seriously bad to the business will happen if the deadline isn’t met
      • Soft deadline - somebody will look bad if the deadline isn’t met
      • Internal deadline - target internal to the team that will not affect anybody outside of the team
      • Expected completion date - team currently predicts that work will be completed
      management programming
    5. pyxelr 02 May 2020
      you should always advocate for having a dedicated SRE if there’s any real risk of after-hours pages that are out of your control.

      Site Reliability Engineers (ideally from different time zones) should've been settled when we might expect after-hours errors

      programming career
    6. pyxelr 02 May 2020
      I try to write a unit test any time the expected value of a defect is non-trivial.

      Write unit tests at least for the most important parts of code, but every chunk of code should have a trivial unit test around it – this verifies that the code is written in a testable way, which indeed is extremely important

      programming testing
    10. pyxelr 02 May 2020
      Programming languages These will probably expose my ignorance pretty nicely.

      When to use different programming languages (advice from an Amazon employee):

      • Java - enterprise applications
      • C# - Microsoft's spin on Java (useful in the Microsoft's ecosystem)
      • Ruby - when speed is more important then legibility or debugging
      • Python - same as Ruby but also for ML/AI (don't forget to use type hinting to make life a little saner)
      • Go/Rust - fresh web service where latency and performance were more important than community/library support
      • Haskell/Erlang - for very elegant/mathematical functional approach without a lot of business logic
      • Clojure - in situation when you love Lisp (?)
      • Kotlin/Scala - languages compiling to JVM bytecode (preferable over Clojure). Kotlin works with Java and has great IntelliJ support
      • C - classes of applications (operating systems, language design, low-level programming and hardware)
      • C++ - robotics, video games and high frequency trading where the performance gains from no garbage collection make it preferable to Java
      • PHP/Hack - testing server changes without rebuilding. PHP is banned at Amazon due to security reasons, but its successor, Hack, runs a lot of Facebook and Slack's backends
      programming Java C# Ruby Python Go Rust Haskell Erlang Clojure Kotlin Scala C C++ PHP Hack
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    muldoon.cloud/programming/2020/04/17/programming-rules-thumb.html
  54. p.migdal.pl p.migdal.pl
    How I Learned to Stop Worrying and Love the Types & Tests
    1
    1. pyxelr 02 May 2020
      A few takeaways

      Summarising the article:

      • Types and tests save you from stupid mistakes; these're gifts for your future self!
      • Use ESLint and configure it to be your strict, but fair, friend.
      • Think of tests as a permanent console.
      • Types: It is not only about checks. It is also about code readability.
      • Testing with each commit makes fewer surprises when merging Pull Requests.
      programming testing
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    p.migdal.pl/2020/03/02/types-tests-typescript.html
  55. Apr 2020
  56. p.migdal.pl p.migdal.pl
    How I Learned to Stop Worrying and Love the Types & Tests
    16
    1. pyxelr 30 Apr 2020
      I set it with a few clicks at Travis CI, and by creating a .travis.yml file in the repo

      You can set CI with a few clicks using Travis CI and creating a .travis.yml file in your repo:

      language: node_js
node_js: node

before_script:
  - npm install -g typescript
  - npm install codecov -g

script:
  - yarn lint
  - yarn build
  - yarn test
  - yarn build-docs

after_success:
  - codecov
      programming DevOps
    2. pyxelr 30 Apr 2020
      I set it with a few clicks at Travis CI, and by creating a .travis.yml file in the repo

      You can set CI with a few clicks using Travis CI and creating a .travis.yml file in your repo:

      language: node_js
node_js: node

before_script:
  - npm install -g typescript
  - npm install codecov -g

script:
  - yarn lint
  - yarn build
  - yarn test
  - yarn build-docs

after_success:
  - codecov
      programming DevOps
    3. pyxelr 30 Apr 2020
      Continuous integration makes it easy to check against cases when the code: does not work (but someone didn’t test it and pushed haphazardly), does work only locally, as it is based on local installations, does work only locally, as not all files were committed.

      CI - Continuous Integration helps to check the code when it :

      • does not work (but someone didn’t test it and pushed haphazardly),
      • does work only locally, as it is based on local installations,
      • does work only locally, as not all files were committed.
      programming DevOps
    4. pyxelr 30 Apr 2020
      In Python, when trying to do a dubious operation, you get an error pretty soon. In JavaScript… an undefined can fly through a few layers of abstraction, causing an error in a seemingly unrelated piece of code.

      Undefined nature of JavaScript can hide an error for a long time. For example,

      function add(a,b) { return + (a + b) }
add(2,2)
add('2', 2)

      will result in a number, but is it the same one?

      JavaScript Python programming
    7. pyxelr 29 Apr 2020
      It is fine to start adding tests gradually, by adding a few tests to things that are the most difficult (ones you need to keep fingers crossed so they work) or most critical (simple but with many other dependent components).

      Start small by adding tests to the most crucial parts

      programming
    9. pyxelr 29 Apr 2020
      I need to specify types of input and output. But then I get speedup due to autocompletion, hints, and linting if for any reason I make a mistake.

      In TypeScript, you spend a bit more time in the variable definition, but then autocompletion, hints, and linting will reward you. It also boosts code readability

      TypeScript programming
    12. pyxelr 29 Apr 2020
      Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it.

      According to the Kernighan's Law, writing code is not as hard as debugging

      programming testing
    16. pyxelr 29 Apr 2020
      Creating meticulous tests before exploring the data is a big mistake, and will result in a well-crafted garbage-in, garbage-out pipeline. We need an environment flexible enough to encourage experiments, especially in the initial place.

      Overzealous nature of TDD may discourage from explorable data science

      DataScience programming testing
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    p.migdal.pl/2020/03/02/types-tests-typescript.html
  57. en.wikipedia.org en.wikipedia.org
    Pseudocode - Wikipedia
    1
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    en.wikipedia.org/wiki/Pseudocode
  58. www.figma.com www.figma.com
    Best practices: component, styles, and shared libraries
    17
    2. pyxelr 29 Apr 2020
      Some of our main takeaways:CRDT literature can be relevant even if you're not creating a decentralized systemMultiplayer for a visual editor like ours wasn't as intimidating as we thoughtTaking time to research and prototype in the beginning really paid off

      Key takeaways of developing a live editing tool

      programming multiplayertechnology
    4. pyxelr 29 Apr 2020
      CRDTs refer to a collection of different data structures commonly used in distributed systems. All CRDTs satisfy certain mathematical properties which guarantee eventual consistency. If no more updates are made, eventually everyone accessing the data structure will see the same thing. This constraint is required for correctness; we cannot allow two clients editing the same Figma document to diverge and never converge again

      CRDTs (Conflict-free Replicated Data Types)

      programming multiplayertechnology
    7. pyxelr 29 Apr 2020
      Figma’s multiplayer servers keep track of the latest value that any client has sent for a given property on a given object

      ✅ No conflict:

      • two clients changing unrelated properties on the same object
      • two clients changing the same property on unrelated objects.

      ❎ Conflict:

      • two clients changing the same property on the same object (document will end up with the last value sent)
      programming multiplayertechnology
    8. pyxelr 29 Apr 2020
      Figma doesn’t store any properties of deleted objects on the server. That data is instead stored in the undo buffer of the client that performed the delete. If that client wants to undo the delete, then it’s also responsible for restoring all properties of the deleted objects. This helps keep long-lived documents from continuing to grow in size as they are edited

      Undo option

      programming multiplayertechnology
    9. pyxelr 29 Apr 2020
      it's important to be able to iterate quickly and experiment before committing to an approach. That's why we first created a prototype environment to test our ideas instead of working in the real codebase

      First work with a prototype, then the real codebase

      programming
    11. pyxelr 29 Apr 2020
      We had a lot of trouble until we settled on a principle to help guide us: if you undo a lot, copy something, and redo back to the present (a common operation), the document should not change. This may seem obvious but the single-player implementation of redo means “put back what I did” which may end up overwriting what other people did next if you’re not careful. This is why in Figma an undo operation modifies redo history at the time of the undo, and likewise a redo operation modifies undo history at the time of the redo

      Undo/Redo working

      programming multiplayertechnology
    12. pyxelr 29 Apr 2020
      operational transforms (a.k.a. OTs), the standard multiplayer algorithm popularized by apps like Google Docs. As a startup we value the ability to ship features quickly, and OTs were unnecessarily complex for our problem space

      Operational Transforms (OT) are unnecessarily complex for problems unlike Google Docs

      programming multiplayertechnology
    13. pyxelr 29 Apr 2020
      Every Figma document is a tree of objects, similar to the HTML DOM. There is a single root object that represents the entire document. Underneath the root object are page objects, and underneath each page object is a hierarchy of objects representing the contents of the page. This tree is is presented in the layers panel on the left-hand side of the Figma editor.

      Structure of Figma documents

      programming multiplayertechnology
    14. pyxelr 29 Apr 2020
      When a document is opened, the client starts by downloading a copy of the file. From that point on, updates to that document in both directions are synced over the WebSocket connection. Figma lets you go offline for an arbitrary amount of time and continue editing. When you come back online, the client downloads a fresh copy of the document, reapplies any offline edits on top of this latest state, and then continues syncing updates over a new WebSocket connection

      Offline editing isn't a problem, unlike the online one

      programming multiplayertechnology
    15. pyxelr 29 Apr 2020
      An important consequence of this is that changes are atomic at the property value boundary. The eventually consistent value for a given property is always a value sent by one of the clients. This is why simultaneous editing of the same text value doesn’t work in Figma. If the text value is B and someone changes it to AB at the same time as someone else changes it to BC, the end result will be either AB or BC but never ABC

      Consequence of approaches like last-writer-wins

      programming multiplayertechnology
    16. pyxelr 29 Apr 2020
      We use a client/server architecture where Figma clients are web pages that talk with a cluster of servers over WebSockets. Our servers currently spin up a separate process for each multiplayer document which everyone editing that document connects to

      Way Figma approaches client/server architecture

      programming multiplayertechnology
    17. pyxelr 29 Apr 2020
      CRDTs are designed for decentralized systems where there is no single central authority to decide what the final state should be. There is some unavoidable performance and memory overhead with doing this. Since Figma is centralized (our server is the central authority), we can simplify our system by removing this extra overhead and benefit from a faster and leaner implementation

      CRDTs are designed for decentralized systems

      programming multiplayertechnology
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    figma.com/blog/how-figmas-multiplayer-technology-works/
  59. dev.to dev.to
    Identifying the dirt in our code
    11
    1. pyxelr 29 Apr 2020
      Sometimes it's interesting to explain some code (How many time you spend trying to figure out a regex pattern when you see one?), but, in 99% of the time, comments could be avoided.

      Generally try to avoid (avoid != forbid) comments.

      Comments:

      1. Become outdated, confusing your future self (Yesterday I lost some precious time because of an outdated comment)
      2. Could be replaced for some better named variable/function/class.
      3. They pollute the code unnecessarily.
      programming
    2. pyxelr 29 Apr 2020
      When we talk about abstraction levels, we can classify the code in 3 levels: high: getAdress medium: inactiveUsers = Users.findInactives low: .split(" ")

      3 abstraction levels:

      1. high: getAdress
      2. medium: inactiveUsers = Users.findInactives
      3. low: .split(" ")

      Explanation:

      • The high level abstraction are functions that you create, like searchForsomething()
      • The medium level are methods in your object, like account.unverifyAccount
      • The low level are methods that the language provides, like map, to_downncase and so on
      programming
    4. pyxelr 29 Apr 2020
      There is another maxim also that says: you must write the same code a maximum of 3 times. The third time you should consider refactoring and reducing duplication

      Avoid repeating the same code over and over

      programming
    6. pyxelr 29 Apr 2020
      Uncle Bob, in clean code, defends that the best order to write code is: Write unit tests. Create code that works. Refactor to clean the code.

      Best order to write code (according to Uncle Bob):

      1. Write unit tests.
      2. Create code that works.
      3. Refactor to clean the code.
      programming
    8. pyxelr 29 Apr 2020
      naming things, write better functions and a little about comments. Next, I intend to talk about formatting, objects and data structures, how to handle with errors, about boundaries (how to deal with another's one code), unit testing and how to organize your class better. I know that it'll be missing an important topic about code smells

      Ideas to consider while developing clean code:

      • naming things
      • better functions
      • comments
      • formatting
      • objects and data structures
      • handling error
      • boundaries (handling another's one code)
      • unit testing
      • organising classes
      • code smells
      programming
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    dev.to/rachc/identifying-the-dirt-in-our-code-2f3h
  60. dev.to dev.to
    I Read 21 Articles About How to Become a Senior Developer So You Don't Have To
    4
    1. pyxelr 29 Apr 2020
      "The Big Picture" is one of those things that people say a whole lot but can mean so many different things. Going through all of these articles, they tend to mean any (or all) of these things

      Thinking about The Big Picture:

      1. The Business Stuff - how to meet KPIs or the current big deadline or whatever.
      2. The User Stuff - how to actually provide value to the people who use what you make.
      3. The Technology Stuff - how to build something that will last a long time.
      programming
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    dev.to/mibzman/i-read-21-articles-about-how-to-become-a-senior-developer-so-you-don-t-have-to-4dap
  61. www.fast.ai www.fast.ai
    nbdev: use Jupyter Notebooks for everything
    8
    1. pyxelr 29 Apr 2020
      In recent years we’ve also begun to see increasing interest in exploratory testing as an important part of the agile toolbox

      Waterfall software development ---> agile ---> exploratory testing

      programming
    3. pyxelr 29 Apr 2020
      Mathematica didn’t really help me build anything useful, because I couldn’t distribute my code or applications to colleagues (unless they spent thousands of dollars for a Mathematica license to use it), and I couldn’t easily create web applications for people to access from the browser. In addition, I found my Mathematica code would often end up much slower and more memory hungry than code I wrote in other languages.

      Disadvantages of Mathematica:

      • memory hungry, slow code
      • expensive code
      • non-distributable license
      programming
    5. pyxelr 29 Apr 2020
      a methodology that combines a programming language with a documentation language, thereby making programs more robust, more portable, more easily maintained, and arguably more fun to write than programs that are written only in a high-level language. The main idea is to treat a program as a piece of literature, addressed to human beings rather than to a computer.

      Exploratory testing described by Donald Knuth

      programming
    7. pyxelr 29 Apr 2020
      This kind of “exploring” is easiest when you develop on the prompt (or REPL), or using a notebook-oriented development system like Jupyter Notebooks

      It's easier to explore the code:

      • when you develop on the prompt (or REPL)
      • in notebook-oriented system like Jupyter

      but, it's not efficient to develop in them

      programming Jupyter
    8. pyxelr 29 Apr 2020
      notebook contains an actual running Python interpreter instance that you’re fully in control of. So Jupyter can provide auto-completions, parameter lists, and context-sensitive documentation based on the actual state of your code

      Notebook makes it easier to handle dynamic Python features

      programming Jupyter
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    fast.ai/2019/12/02/nbdev/
  62. dev.to dev.to
    What software technologies will earn you the highest pay?
    6
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    dev.to/educative/what-software-technologies-will-earn-you-the-highest-pay-3fc3
  63. www.alexhudson.com www.alexhudson.com
    The 'No Code' Delusion
    4
    1. pyxelr 29 Apr 2020
      First, you’ve spread the logic across a variety of different systems, so it becomes more difficult to reason about the application as a whole. Second, more importantly, the logic has been implemented as configuration as opposed to code. The logic is constrained by the ability of the applications which have been wired together, but it’s still there.

      Why "no code" trend is dangerous in some way (on the example of Zapier):

      1. You spread the logic across multiple systems.
      2. Logic is maintained in configuration rather than code.
      programming
    2. pyxelr 29 Apr 2020
      the developer doesn’t need to worry about allocating memory, or the character set encoding of the string, or a host of other things.

      Comparison of C (1972) and TypeScript (2012) code.

      (check the code above)

      programming
    4. pyxelr 29 Apr 2020
      With someone else’s platform, you often end up needing to construct elaborate work-arounds for missing functionality, or indeed cannot implement a required feature at all.

      You can quickly implement 80% of the solution in Salesforce using a mix of visual programming (basic rule setting and configuration), but later it's not so straightforward to add the missing 20%

      programming
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    alexhudson.com/2020/01/13/the-no-code-delusion/
  64. google.github.io google.github.io
    What to look for in a code review
    1
    1. pyxelr 29 Apr 2020
      Summary

      In doing a code review, you should make sure that:

      • The code is well-designed.
      • The functionality is good for the users of the code.
      • Any UI changes are sensible and look good.
      • Any parallel programming is done safely.
      • The code isn’t more complex than it needs to be.
      • The developer isn’t implementing things they might need in the future but don’t know they need now.
      • Code has appropriate unit tests.
      • Tests are well-designed.
      • The developer used clear names for everything.
      • Comments are clear and useful, and mostly explain why instead of what.
      • Code is appropriately documented (generally in g3doc).
      • The code conforms to our style guides.
      codereview programming
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    google.github.io/eng-practices/review/reviewer/looking-for.html
  65. martinfowler.com martinfowler.com
    Continuous Delivery for Machine Learning
    12
    1. pyxelr 29 Apr 2020
      "Continuous Delivery is the ability to get changes of all types — including new features, configuration changes, bug fixes, and experiments — into production, or into the hands of users, safely and quickly in a sustainable way". -- Jez Humble and Dave Farley

      Continuous Delivery

      programming
    2. pyxelr 29 Apr 2020
      Another approach is to use a tool like H2O to export the model as a POJO in a JAR Java library, which you can then add as a dependency in your application. The benefit of this approach is that you can train the models in a language familiar to Data Scientists, such as Python or R, and export the model as a compiled binary that runs in a different target environment (JVM), which can be faster at inference time

      H2O - export models trained in Python/R as a POJO in JAR

      MachineLearning programming
    3. pyxelr 29 Apr 2020
      Continuous Delivery for Machine Learning (CD4ML) is a software engineering approach in which a cross-functional team produces machine learning applications based on code, data, and models in small and safe increments that can be reproduced and reliably released at any time, in short adaptation cycles.

      Continuous Delivery for Machine Learning (CD4ML) (long definition)

      Basic principles:

      • software engineering approach
      • cross-functional team
      • producing software based on code, data, and ml models
      • small and safe increments
      • reproducible and reliable software release
      • short adaptation cycles
      MachineLearning programming
    4. pyxelr 29 Apr 2020
      In order to formalise the model training process in code, we used an open source tool called DVC (Data Science Version Control). It provides similar semantics to Git, but also solves a few ML-specific problems:

      DVC - transform model training process into code.

      Advantages:

      • it has multiple backend plugins to fetch and store large files on an external storage outside of the source control repository;
      • it can keep track of those files' versions, allowing us to retrain our models when the data changes;
      • it keeps track of the dependency graph and commands used to execute the ML pipeline, allowing the process to be reproduced in other environments;
      • it can integrate with Git branches to allow multiple experiments to co-exist
      MachineLearning programming
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    martinfowler.com/articles/cd4ml.html
  66. realpython.com realpython.com
    Documenting Python Code: A Complete Guide – Real Python
    24
    4. pyxelr 29 Apr 2020
      Class method docstrings should contain the following: A brief description of what the method is and what it’s used for Any arguments (both required and optional) that are passed including keyword arguments Label any arguments that are considered optional or have a default value Any side effects that occur when executing the method Any exceptions that are raised Any restrictions on when the method can be called

      Class method should contain:

      • brief description
      • arguments
      • label on default/optional arguments
      • side effects description
      • raised exceptions
      • restrictions on when the method can be called

      (check example below)

      Python documentation programming
    5. pyxelr 29 Apr 2020
      Comments to your code should be kept brief and focused. Avoid using long comments when possible. Additionally, you should use the following four essential rules as suggested by Jeff Atwood:

      Comments should be as concise as possible. Moreover, you should follow 4 rules of Jeff Atwood:

      1. Keep comments close to the code being described.
      2. Don't use complex formatting (such as tables).
      3. Don't comment obvious things.
      4. Design code in a way it comments itself.
      documentation programming
    6. pyxelr 29 Apr 2020
      From examining the type hinting, you can immediately tell that the function expects the input name to be of a type str, or string. You can also tell that the expected output of the function will be of a type str, or string, as well.

      Type hinting introduced in Python 3.5 extends 4 rules of Jeff Atwood and comments the code itself, such as this example:

      def hello_name(name: str) -> str:
    return(f"Hello {name}")
      • user knows that the code expects input of type str
      • the same about output
      documentation Python programming
    10. pyxelr 29 Apr 2020
      All multi-lined docstrings have the following parts: A one-line summary line A blank line proceeding the summary Any further elaboration for the docstring Another blank line

      Multi-line docstring example:

      """This is the summary line

This is the further elaboration of the docstring. Within this section,
you can elaborate further on details as appropriate for the situation.
Notice that the summary and the elaboration is separated by a blank new
line.

# Notice the blank line above. Code should continue on this line.
      Python documentation programming
    11. pyxelr 29 Apr 2020
      say_hello.__doc__ = "A simple function that says hello... Richie style"

      Example of using __doc:

      Code (version 1):

      def say_hello(name):
    print(f"Hello {name}, is it me you're looking for?")

say_hello.__doc__ = "A simple function that says hello... Richie style"

      Code (alternative version):

      def say_hello(name):
    """A simple function that says hello... Richie style"""
    print(f"Hello {name}, is it me you're looking for?")

      Input:

      >>> help(say_hello)

      Returns:

      Help on function say_hello in module __main__:

say_hello(name)
    A simple function that says hello... Richie style
      Python documentation programming
    15. pyxelr 29 Apr 2020
      Commenting your code serves multiple purposes

      Multiple purposes of commenting:

      • planning and reviewing code - setting up a code template
      • code description
      • algorithmic description - for example, explaining the work of an algorithm or the reason of its choice
      • tagging - BUG, FIXME, TODO
      programming documentation
    16. pyxelr 29 Apr 2020
      In general, commenting is describing your code to/for developers. The intended main audience is the maintainers and developers of the Python code. In conjunction with well-written code, comments help to guide the reader to better understand your code and its purpose and design

      Commenting code:

      • describing code to/for developers
      • help to guide the reader to better understand your code, its purpose/design
      programming documentation
    18. pyxelr 29 Apr 2020
      If you use argparse, then you can omit parameter-specific documentation, assuming it’s correctly been documented within the help parameter of the argparser.parser.add_argument function. It is recommended to use the __doc__ for the description parameter within argparse.ArgumentParser’s constructor.

      argparse

      Python documentation programming
    20. pyxelr 29 Apr 2020
      Daniele Procida gave a wonderful PyCon 2017 talk and subsequent blog post about documenting Python projects. He mentions that all projects should have the following four major sections to help you focus your work:

      Public and Open Source Python projects should have the docs folder, and inside of it:

      • Tutorials
      • How-To Guides
      • References
      • Explanations

      (check the table below for a summary)

      Python documentation programming
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    realpython.com/documenting-python-code/
  67. engineering.instawork.com engineering.instawork.com
    When XML beats JSON: UI layouts
    1
    1. pyxelr 29 Apr 2020
      Each format makes tradeoffs in encoding, flexibility, and expressiveness to best suit a specific use case.

      Each data format brings different tradeoffs:

      • A format optimized for size will use a binary encoding that won’t be human-readable.
      • A format optimized for extensibility will take longer to decode than a format designed for a narrow use case.
      • A format designed for flat data (like CSV) will struggle to represent nested data.
      programming
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    engineering.instawork.com/when-xml-beats-json-ui-layouts-53c7f1d3fdb7
  68. 0.30000000000000004.com 0.30000000000000004.com
    Untitled document
    1
    1. pyxelr 29 Apr 2020
      Computers can only natively store integers, so they need some way of representing decimal numbers. This representation comes with some degree of inaccuracy. That's why, more often than not, .1 + .2 != .3

      Computers make up their way to store decimal numbers

      programming math
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    0.30000000000000004.com/
  69. medium.com medium.com
    How is computer programming different today than 20 years ago?
    8
    2. pyxelr 29 Apr 2020
      A package management ecosystem is essential for programming languages now. People simply don’t want to go through the hassle of finding, downloading and installing libraries anymore. 20 years ago we used to visit web sites, downloaded zip files, copied them to correct locations, added them to the paths in the build configuration and prayed that they worked.

      How library management changed in 20 years

      programming
    3. pyxelr 29 Apr 2020
      IDEs and the programming languages are getting more and more distant from each other. 20 years ago an IDE was specifically developed for a single language, like Eclipse for Java, Visual Basic, Delphi for Pascal etc. Now, we have text editors like VS Code that can support any programming language with IDE like features.

      How IDEs "unified" in comparison to the last 20 years

      programming
    4. pyxelr 29 Apr 2020
      Your project has no business value today unless it includes blockchain and AI, although a centralized and rule-based version would be much faster and more efficient.

      Comparing current project needs to those 20 years ago

      programming
    5. pyxelr 29 Apr 2020
      Being a software development team now involves all team members performing a mysterious ritual of standing up together for 15 minutes in the morning and drawing occult symbols with post-its.

      In comparison to 20 years ago ;)

      programming funny
    6. pyxelr 29 Apr 2020
      Language tooling is richer today. A programming language was usually a compiler and perhaps a debugger. Today, they usually come with the linter, source code formatter, template creators, self-update ability and a list of arguments that you can use in a debate against the competing language.

      How coding became much more supported in comparison to the last 20 years

      programming
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    medium.com/swlh/how-is-computer-programming-different-today-than-20-years-ago-9d0154d1b6ce
  70. roadmap.sh roadmap.sh
    Levels of Seniority
    2
    1. pyxelr 29 Apr 2020
      I am not sure how but one kind soul somehow found the project, forked it, refactored it, "modernized" it, added linting, code sniffing, added CI and opened the pull request.

      It's worth sharing your code, since someone can always find it and improve it, so that you can learn from it

      github programming
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    roadmap.sh/guides/levels-of-seniority
  71. dev.to dev.to
    What is Memoization? - DEV Community 👩‍💻👨‍💻
    2
    1. pyxelr 29 Apr 2020
      Let's reason through our memoizer before we write any code.

      Operations performed by a memoizer:

      • Takes a reference to a function as an input
      • Returns a function (so it can be used as it normally would be)
      • Creates a cache of some sort to hold the results of previous function calls
      • Any future time calling the function, returns a cached result if it exists
      • If the cached value doesn't exist, calls the function and store that result in the cache

      Which is written as:

      // Takes a reference to a function
const memoize = func => {
  // Creates a cache of results
  const results = {};
  // Returns a function
  return (...args) => {
    // Create a key for results cache
    const argsKey = JSON.stringify(args);
    // Only execute func if no cached value
    if (!results[argsKey]) {
      // Store function call result in cache
      results[argsKey] = func(...args);
    }
    // Return cached value
    return results[argsKey];
  };
};
      programming JavaScript
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    dev.to/nas5w/what-is-memoization-4lod
  72. code.visualstudio.com code.visualstudio.com
    Debugging in Visual Studio Code
    3
    1. pyxelr 29 Apr 2020
      The best way to explain the difference between launch and attach is to think of a launch configuration as a recipe for how to start your app in debug mode before VS Code attaches to it, while an attach configuration is a recipe for how to connect VS Code's debugger to an app or process that's already running.

      Simple difference between two core debugging modes: Launch and Attach available in VS Code.

      Depending on the request (attach or launch), different attributes are required, and VS Code's launch.json validation and suggestions should help with that.

      VSCode programming
    2. pyxelr 29 Apr 2020
      Logpoint is a variant of a breakpoint that does not "break" into the debugger but instead logs a message to the console. Logpoints are especially useful for injecting logging while debugging production servers that cannot be paused or stopped. A Logpoint is represented by a "diamond" shaped icon. Log messages are plain text but can include expressions to be evaluated within curly braces ('{}').

      Logpoints - log messages to the console when breakpoint is hit.

      Can include expressions to be evaluated with {}, e.g.:

      fib({num}): {result}

      (animation)

      VSCode programming
    3. pyxelr 29 Apr 2020
      Here are some optional attributes available to all launch configurations

      Optional arguments for launch.json:

      • presentation ("order", "group" or "hidden")
      • preLaunchTask
      • postDebugTask
      • internalConsoleOptions
      • debugServer
      • serverReadyAction
      VSCode programming
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    code.visualstudio.com/docs/editor/debugging
  73. towardsdatascience.com towardsdatascience.com
    Why we do machine learning engineering with YAML, not notebooks
    3
    2. pyxelr 29 Apr 2020
      The priorities in building a production machine learning pipeline—the series of steps that take you from raw data to product—are not fundamentally different from those of general software engineering.
      1. Your pipeline should be reproducible
      2. Collaborating on your pipeline should be easy
      3. All code in your pipeline should be testable
      DataScience programming
    3. pyxelr 29 Apr 2020
      Reproducibility is an issue with notebooks. Because of the hidden state and the potential for arbitrary execution order, generating a result in a notebook isn’t always as simple as clicking “Run All.”

      Problem of reproducibility in notebooks

      Jupyter programming
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    Guide for the daily JavaScripter - DEV Community 👩‍💻👨‍💻
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