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Programming Leftovers (LLVM Clang, R, Perl and Python)

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  • Arm Cortex-A77 Support Upstreamed Finally To LLVM Clang 11

    While the Arm Cortex-A77 was announced last year and already has been succeeded by the Cortex-A78 announcement, support for the A77 has finally been upstreamed to the LLVM Clang compiler.

    The Cortex-A77 support was added to the GCC compiler last year while seemingly as an oversight the A77 support wasn't added to LLVM/Clang until this week.

  • Dirk Eddelbuettel: Rcpp now used by 2000 CRAN packages–and one in eight!

    As of yesterday, Rcpp stands at exactly 2000 reverse-dependencies on CRAN. The graph on the left depicts the growth of Rcpp usage (as measured by Depends, Imports and LinkingTo, but excluding Suggests) over time.

    Rcpp was first released in November 2008. It probably cleared 50 packages around three years later in December 2011, 100 packages in January 2013, 200 packages in April 2014, and 300 packages in November 2014. It passed 400 packages in June 2015 (when I tweeted about it), 500 packages in late October 2015, 600 packages in March 2016, 700 packages last July 2016, 800 packages last October 2016, 900 packages early January 2017, 1000 packages in April 2017, 1250 packages in November 2017, 1500 packages in November 2018 and then 1750 packages last August. The chart extends to the very beginning via manually compiled data from CRANberries and checked with crandb. The next part uses manually saved entries. The core (and by far largest) part of the data set was generated semi-automatically via a short script appending updates to a small file-based backend. A list of packages using Rcpp is available too.

  • YouTube: The [Perl] Weekly Challenge - 067
  • The [Perl] Weekly Challenge #067

    This week both tasks had one thing in common i.e. pairing two or more list. In the past, I have taken the help from CPAN module Algorithm::Combinatorics for such tasks.

  • Weekly Python StackOverflow Report: (ccxxxiv) stackoverflow python report
  • Flask project setup: TDD, Docker, Postgres and more - Part 1

    There are tons of tutorials on Internet that tech you how to use a web framework and how to create Web applications, and many of these cover Flask, first of all the impressive Flask Mega-Tutorial by Miguel Grinberg (thanks Miguel!).
    Why another tutorial, then? Recently I started working on a small personal project and decided that it was a good chance to refresh my knowledge of the framework. For this reason I temporarily dropped the clean architecture I often recommend, and started from scratch following some tutorials. My development environment quickly became very messy, and after a while I realised I was very unsatisfied by the global setup.
    So, I decided to start from scratch again, this time writing down some requirements I want from my development setup. I also know very well how complicated the deploy of an application in production can be, so I want my setup to be "deploy-friendly" as much as possible. Having seen too many project suffer from legacy setups, and knowing that many times such issues can be avoided with a minimum amount of planning, I thought this might be interesting for other developers as well. I consider this setup by no means better than others, it simply addresses different concerns.

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