Search Results: "edd"

11 March 2024

Dirk Eddelbuettel: digest 0.6.35 on CRAN: New xxhash code

Release 0.6.35 of the digest package arrived at CRAN today and has also been uploaded to Debian already. digest creates hash digests of arbitrary R objects. It can use a number different hashing algorithms (md5, sha-1, sha-256, sha-512, crc32, xxhash32, xxhash64, murmur32, spookyhash, blake3,crc32c and now also xxh3_64 and xxh3_128), and enables easy comparison of (potentially large and nested) R language objects as it relies on the native serialization in R. It is a mature and widely-used package (with 65.8 million downloads just on the partial cloud mirrors of CRAN which keep logs) as many tasks may involve caching of objects for which it provides convenient general-purpose hash key generation to quickly identify the various objects. This release updates the included xxHash version to the current verion 0.8.2 updating the existing xxhash32 and xxhash64 hash functions and also adding the newer xxh3_64 and xxh3_128 ones. We have a project at work using xxh3_128 from Python which made me realize having it from R would be nice too, and given the existing infrastructure in the package actually doing so was fairly quick and straightforward. My CRANberries provides a summary of changes to the previous version. For questions or comments use the issue tracker off the GitHub repo. For documentation (including the changelog) see the documentation site. If you like this or other open-source work I do, you can now sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

9 March 2024

Reproducible Builds: Reproducible Builds in February 2024

Welcome to the February 2024 report from the Reproducible Builds project! In our reports, we try to outline what we have been up to over the past month as well as mentioning some of the important things happening in software supply-chain security.

Reproducible Builds at FOSDEM 2024 Core Reproducible Builds developer Holger Levsen presented at the main track at FOSDEM on Saturday 3rd February this year in Brussels, Belgium. However, that wasn t the only talk related to Reproducible Builds. However, please see our comprehensive FOSDEM 2024 news post for the full details and links.

Maintainer Perspectives on Open Source Software Security Bernhard M. Wiedemann spotted that a recent report entitled Maintainer Perspectives on Open Source Software Security written by Stephen Hendrick and Ashwin Ramaswami of the Linux Foundation sports an infographic which mentions that 56% of [polled] projects support reproducible builds .

Mailing list highlights From our mailing list this month:

Distribution work In Debian this month, 5 reviews of Debian packages were added, 22 were updated and 8 were removed this month adding to Debian s knowledge about identified issues. A number of issue types were updated as well. [ ][ ][ ][ ] In addition, Roland Clobus posted his 23rd update of the status of reproducible ISO images on our mailing list. In particular, Roland helpfully summarised that all major desktops build reproducibly with bullseye, bookworm, trixie and sid provided they are built for a second time within the same DAK run (i.e. [within] 6 hours) and that there will likely be further work at a MiniDebCamp in Hamburg. Furthermore, Roland also responded in-depth to a query about a previous report
Fedora developer Zbigniew J drzejewski-Szmek announced a work-in-progress script called fedora-repro-build that attempts to reproduce an existing package within a koji build environment. Although the projects README file lists a number of fields will always or almost always vary and there is a non-zero list of other known issues, this is an excellent first step towards full Fedora reproducibility.
Jelle van der Waa introduced a new linter rule for Arch Linux packages in order to detect cache files leftover by the Sphinx documentation generator which are unreproducible by nature and should not be packaged. At the time of writing, 7 packages in the Arch repository are affected by this.
Elsewhere, Bernhard M. Wiedemann posted another monthly update for his work elsewhere in openSUSE.

diffoscope diffoscope is our in-depth and content-aware diff utility that can locate and diagnose reproducibility issues. This month, Chris Lamb made a number of changes such as uploading versions 256, 257 and 258 to Debian and made the following additional changes:
  • Use a deterministic name instead of trusting gpg s use-embedded-filenames. Many thanks to Daniel Kahn Gillmor dkg@debian.org for reporting this issue and providing feedback. [ ][ ]
  • Don t error-out with a traceback if we encounter struct.unpack-related errors when parsing Python .pyc files. (#1064973). [ ]
  • Don t try and compare rdb_expected_diff on non-GNU systems as %p formatting can vary, especially with respect to MacOS. [ ]
  • Fix compatibility with pytest 8.0. [ ]
  • Temporarily fix support for Python 3.11.8. [ ]
  • Use the 7zip package (over p7zip-full) after a Debian package transition. (#1063559). [ ]
  • Bump the minimum Black source code reformatter requirement to 24.1.1+. [ ]
  • Expand an older changelog entry with a CVE reference. [ ]
  • Make test_zip black clean. [ ]
In addition, James Addison contributed a patch to parse the headers from the diff(1) correctly [ ][ ] thanks! And lastly, Vagrant Cascadian pushed updates in GNU Guix for diffoscope to version 255, 256, and 258, and updated trydiffoscope to 67.0.6.

reprotest reprotest is our tool for building the same source code twice in different environments and then checking the binaries produced by each build for any differences. This month, Vagrant Cascadian made a number of changes, including:
  • Create a (working) proof of concept for enabling a specific number of CPUs. [ ][ ]
  • Consistently use 398 days for time variation rather than choosing randomly and update README.rst to match. [ ][ ]
  • Support a new --vary=build_path.path option. [ ][ ][ ][ ]

Website updates There were made a number of improvements to our website this month, including:

Reproducibility testing framework The Reproducible Builds project operates a comprehensive testing framework (available at tests.reproducible-builds.org) in order to check packages and other artifacts for reproducibility. In February, a number of changes were made by Holger Levsen:
  • Debian-related changes:
    • Temporarily disable upgrading/bootstrapping Debian unstable and experimental as they are currently broken. [ ][ ]
    • Use the 64-bit amd64 kernel on all i386 nodes; no more 686 PAE kernels. [ ]
    • Add an Erlang package set. [ ]
  • Other changes:
    • Grant Jan-Benedict Glaw shell access to the Jenkins node. [ ]
    • Enable debugging for NetBSD reproducibility testing. [ ]
    • Use /usr/bin/du --apparent-size in the Jenkins shell monitor. [ ]
    • Revert reproducible nodes: mark osuosl2 as down . [ ]
    • Thanks again to Codethink, for they have doubled the RAM on our arm64 nodes. [ ]
    • Only set /proc/$pid/oom_score_adj to -1000 if it has not already been done. [ ]
    • Add the opemwrt-target-tegra and jtx task to the list of zombie jobs. [ ][ ]
Vagrant Cascadian also made the following changes:
  • Overhaul the handling of OpenSSH configuration files after updating from Debian bookworm. [ ][ ][ ]
  • Add two new armhf architecture build nodes, virt32z and virt64z, and insert them into the Munin monitoring. [ ][ ] [ ][ ]
In addition, Alexander Couzens updated the OpenWrt configuration in order to replace the tegra target with mpc85xx [ ], Jan-Benedict Glaw updated the NetBSD build script to use a separate $TMPDIR to mitigate out of space issues on a tmpfs-backed /tmp [ ] and Zheng Junjie added a link to the GNU Guix tests [ ]. Lastly, node maintenance was performed by Holger Levsen [ ][ ][ ][ ][ ][ ] and Vagrant Cascadian [ ][ ][ ][ ].

Upstream patches The Reproducible Builds project detects, dissects and attempts to fix as many currently-unreproducible packages as possible. We endeavour to send all of our patches upstream where appropriate. This month, we wrote a large number of such patches, including:

If you are interested in contributing to the Reproducible Builds project, please visit our Contribute page on our website. However, you can get in touch with us via:

7 March 2024

Dirk Eddelbuettel: prrd 0.0.6 at CRAN: Several Improvements

Thrilled to share that a new version of prrd arrived at CRAN yesterday in a first update in two and a half years. prrd facilitates the parallel running [of] reverse dependency [checks] when preparing R packages. It is used extensively for releases I make of Rcpp, RcppArmadillo, RcppEigen, BH, and others. prrd screenshot image The key idea of prrd is simple, and described in some more detail on its webpage and its GitHub repo. Reverse dependency checks are an important part of package development that is easily done in a (serial) loop. But these checks are also generally embarassingly parallel as there is no or little interdependency between them (besides maybe shared build depedencies). See the (dated) screenshot (running six parallel workers, arranged in a split byobu session). This release, the first since 2021, brings a number of enhancments. In particular, the summary function is now improved in several ways. Josh also put in a nice PR that generalizes some setup defaults and values. The release is summarised in the NEWS entry:

Changes in prrd version 0.0.6 (2024-03-06)
  • The summary function has received several enhancements:
    • Extended summary is only running when failures are seen.
    • The summariseQueue function now displays an anticipated completion time and remaining duration.
    • The use of optional package foghorn has been refined, and refactored, when running summaries.
  • The dequeueJobs.r scripts can receive a date argument, the date can be parse via anydate if anytime ins present.
  • The enqueeJobs.r now considers skipped package when running 'addfailed' while ensuring selecting packages are still on CRAN.
  • The CI setup has been updated (twice),
  • Enqueing and dequing functions and scripts now support relative directories, updated documentation (#18 by Joshua Ulrich).

Courtesy of my CRANberries, there is also a diffstat report for this release. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

4 March 2024

Dirk Eddelbuettel: tinythemes 0.0.2 at CRAN: Maintenance

A first maintenance of the still fairly new package tinythemes arrived on CRAN today. tinythemes provides the theme_ipsum_rc() function from hrbrthemes by Bob Rudis in a zero (added) dependency way. A simple example is (also available as a demo inside the package) contrasts the default style (on left) with the one added by this package (on the right): This version mostly just updates to the newest releases of ggplot2 as one must, and takes advantage of Bob s update to hrbrthemes yesterday. The full set of changes since the initial CRAN release follows.

Changes in spdl version 0.0.2 (2024-03-04)
  • Added continuous integrations action based on r2u
  • Added demo/ directory and a READNE.md
  • Minor edits to help page content
  • Synchronised with ggplot2 3.5.0 via hrbrthemes

Courtesy of my CRANberries, there is a diffstat report relative to previous release. More detailed information is on the repo where comments and suggestions are welcome. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

3 March 2024

Dirk Eddelbuettel: RcppArmadillo 0.12.8.1.0 on CRAN: Upstream Fix, Interface Polish

armadillo image Armadillo is a powerful and expressive C++ template library for linear algebra and scientific computing. It aims towards a good balance between speed and ease of use, has a syntax deliberately close to Matlab, and is useful for algorithm development directly in C++, or quick conversion of research code into production environments. RcppArmadillo integrates this library with the R environment and language and is widely used by (currently) 1130 other packages on CRAN, downloaded 32.8 million times (per the partial logs from the cloud mirrors of CRAN), and the CSDA paper (preprint / vignette) by Conrad and myself has been cited 578 times according to Google Scholar. This release brings a new upstream bugfix release Armadillo 12.8.1 prepared by Conrad yesterday. It was delayed for a few hours as CRAN noticed an error in one package which we all concluded was spurious as it could be reproduced outside of the one run there. Following from the previous release, we also use the slighty faster Lighter header in the examples. And once it got to CRAN I also updated the Debian package. The set of changes since the last CRAN release follows.

Changes in RcppArmadillo version 0.12.8.1.0 (2024-03-02)
  • Upgraded to Armadillo release 12.8.1 (Cortisol Injector)
    • Workaround in norm() for yet another bug in macOS accelerate framework
  • Update README for RcppArmadillo usage counts
  • Update examples to use '#include <RcppArmadillo/Lighter>' for faster compilation excluding unused Rcpp features

Courtesy of my CRANberries, there is a diffstat report relative to previous release. More detailed information is on the RcppArmadillo page. Questions, comments etc should go to the rcpp-devel mailing list off the Rcpp R-Forge page. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

28 February 2024

Dirk Eddelbuettel: RcppEigen 0.3.4.0.0 on CRAN: New Upstream, At Last

We are thrilled to share that RcppEigen has now upgraded to Eigen release 3.4.0! The new release 0.3.4.0.0 arrived on CRAN earlier today, and has been shipped to Debian as well. Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. This update has been in the works for a full two and a half years! It all started with a PR #102 by Yixuan bringing the package-local changes for R integration forward to usptream release 3.4.0. We opened issue #103 to steer possible changes from reverse-dependency checking through. Lo and behold, this just stalled because a few substantial changes were needed and not coming. But after a long wait, and like a bolt out of a perfectly blue sky, Andrew revived it in January with a reverse depends run of his own along with a set of PRs. That was the push that was needed, and I steered it along with a number of reverse dependency checks, and occassional emails to maintainers. We managed to bring it down to only three packages having a hickup, and all three had received PRs thanks to Andrew and even merged them. So the plan became to release today following a final fourteen day window. And CRAN was convinced by our arguments that we followed due process. So there it is! Big big thanks to all who helped it along, especially Yixuan and Andrew but also Mikael who updated another patch set he had prepared for the previous release series. The complete NEWS file entry follows.

Changes in RcppEigen version 0.3.4.0.0 (2024-02-28)
  • The Eigen version has been upgrade to release 3.4.0 (Yixuan)
  • Extensive reverse-dependency checks ensure only three out of over 400 packages at CRAN are affected; PRs and patches helped other packages
  • The long-running branch also contains substantial contributions from Mikael Jagan (for the lme4 interface) and Andrew Johnson (revdep PRs)

Courtesy of CRANberries, there is also a diffstat report for the most recent release. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

9 February 2024

Abhijith PA: A new(kind of) phone

I was using a refurbished Xiaomi Redmi 6 Pro (codename: sakura . I do remember buying this phone to run LineageOS as I found this model had support. But by the time I bought it (there was a quite a gap between my research and the actual purchase) lineageOS ended the suport for this device. The maintainer might ve ended this port, I don t blame them. Its a non rewarding work. Later I found there is a DotOS custom rom available. I did a week of test run. There seems lot of bugs and it all was minor and I can live with that. Since there is no other official port for redmi 6 pro at the time, I settled on this buggy DotOS nightly build. The phone was doing fine all these(3+) years, but recently the camera started showing greyish dots on some areas to a point that I can t even properly take a photo. The outer body of the phone wasn t original, as it was a refurbished, thus the colors started to peel off and wasn t aesthetically pleasing. Then there is the Location detection issue which took a while to figure out location and battery drains fast. I recently started mapping public transportation routes, and the GPS issue was a problem for me. With all these problems combined, I decided to buy a new phone. But choosing a phone wasn t easy. There are far too many options in the market. However, one thing I was quite sure of was that I wouldn t be buying a brand new phone, but a refurbished one. It is my protest against all these phone manufacturers who have convinced the general public that a mobile phone s lifespan is only 2 years. Of course, there are a few exceptions, but the majority of players in the Indian market are not. Now I think about it, I haven t bought any brand new computing device, be it phones or laptops since 2015. All are refurbished devices except for an Orange pi. My Samsung R439 laptop which I already blogged about is still going strong. Back to picking phone. So I began by comparing LineageOS website to an online refurbished store to pick a phone that has an official lineage support then to reddit search for any reported hardware failures Google Pixel phones are well-known in the custom ROM community for ease of installation, good hardware and Android security releases. My above claims are from privacyguides.org and XDA-developers. I was convinced to go with this choice. But I have some one at home who is at the age of throwing things. So I didn t want to risk buying an expensive Pixel phone only to have it end up with a broken screen and edges. Perhaps I will consider buying a Pixel next time. After doing some more research and cross comparison I landed up on Redmi note 9. Codename: merlinx. Based on my previous experience I knew it is going to be a pain to unlock the bootloader of Xiaomi phones and I was prepared for that but this time there was an extra hoop. The phone came with ROM MIUI version 13. A small search on XDA forums and reddit told unless we downgrade to 12 or so it is difficult to unlock bootloader for this device. And performing this wasn t exactly easy as we need tools like SP Flash etc. It took some time, but I ve completed the downgrade process. From there, the rest was cakewalk as everything was perfectly documented in LineageOS wiki. And ta-da, I have a phone running lineageOS. I been using it for some time and honestly I haven t come across any bug in my way of usage. One advice I will give to you if you are going to flash a custom ROM. There are plenty of videos about unlocking bootloader, installing ROMs in Youtube. Please REFRAIN from watching and experimenting it on your phone unless you figured a way to un brick your device first.

Reproducible Builds (diffoscope): diffoscope 256 released

The diffoscope maintainers are pleased to announce the release of diffoscope version 256. This version includes the following changes:
* CVE-2024-25711: Use a determistic name when extracting content from GPG
  artifacts instead of trusting the value of gpg's --use-embedded-filenames.
  This prevents a potential information disclosure vulnerability that could
  have been exploited by providing a specially-crafted GPG file with an
  embedded filename of, say, "../../.ssh/id_rsa".
  Many thanks to Daniel Kahn Gillmor <dkg@debian.org> for reporting this
  issue and providing feedback.
  (Closes: reproducible-builds/diffoscope#361)
* Temporarily fix support for Python 3.11.8 re. a potential regression
  with the handling of ZIP files. (See reproducible-builds/diffoscope#362)
You find out more by visiting the project homepage.

8 February 2024

Dirk Eddelbuettel: RcppArmadillo 0.12.8.0.0 on CRAN: New Upstream, Interface Polish

armadillo image Armadillo is a powerful and expressive C++ template library for linear algebra and scientific computing. It aims towards a good balance between speed and ease of use, has a syntax deliberately close to Matlab, and is useful for algorithm development directly in C++, or quick conversion of research code into production environments. RcppArmadillo integrates this library with the R environment and language and is widely used by (currently) 1119 other packages on CRAN, downloaded 32.5 million times (per the partial logs from the cloud mirrors of CRAN), and the CSDA paper (preprint / vignette) by Conrad and myself has been cited 575 times according to Google Scholar. This release brings a new (stable) upstream (minor) release Armadillo 12.8.0 prepared by Conrad two days ago. We, as usual, prepared a release candidate which we tested against the over 1100 CRAN packages using RcppArmadillo. This found no issues, which was confirmed by CRAN once we uploaded and so it arrived as a new release today in a fully automated fashion. We also made a small change that had been prepared by GitHub issue #400: a few internal header files that were cluttering the top-level of the include directory have been moved to internal directories. The standard header is of course unaffected, and the set of full / light / lighter / lightest headers (matching we did a while back in Rcpp) also continue to work as one expects. This change was also tested in a full reverse-dependency check in January but had not been released to CRAN yet. The set of changes since the last CRAN release follows.

Changes in RcppArmadillo version 0.12.8.0.0 (2024-02-06)
  • Upgraded to Armadillo release 12.8.0 (Cortisol Injector)
    • Faster detection of symmetric expressions by pinv() and rank()
    • Expanded shift() to handle sparse matrices
    • Expanded conv_to for more flexible conversions between sparse and dense matrices
    • Added cbrt()
    • More compact representation of integers when saving matrices in CSV format
  • Five non-user facing top-level include files have been removed (#432 closing #400 and building on #395 and #396)

Courtesy of my CRANberries, there is a diffstat report relative to previous release. More detailed information is on the RcppArmadillo page. Questions, comments etc should go to the rcpp-devel mailing list off the Rcpp R-Forge page. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

7 February 2024

Reproducible Builds: Reproducible Builds in January 2024

Welcome to the January 2024 report from the Reproducible Builds project. In these reports we outline the most important things that we have been up to over the past month. If you are interested in contributing to the project, please visit our Contribute page on our website.

How we executed a critical supply chain attack on PyTorch John Stawinski and Adnan Khan published a lengthy blog post detailing how they executed a supply-chain attack against PyTorch, a popular machine learning platform used by titans like Google, Meta, Boeing, and Lockheed Martin :
Our exploit path resulted in the ability to upload malicious PyTorch releases to GitHub, upload releases to [Amazon Web Services], potentially add code to the main repository branch, backdoor PyTorch dependencies the list goes on. In short, it was bad. Quite bad.
The attack pivoted on PyTorch s use of self-hosted runners as well as submitting a pull request to address a trivial typo in the project s README file to gain access to repository secrets and API keys that could subsequently be used for malicious purposes.

New Arch Linux forensic filesystem tool On our mailing list this month, long-time Reproducible Builds developer kpcyrd announced a new tool designed to forensically analyse Arch Linux filesystem images. Called archlinux-userland-fs-cmp, the tool is supposed to be used from a rescue image (any Linux) with an Arch install mounted to, [for example], /mnt. Crucially, however, at no point is any file from the mounted filesystem eval d or otherwise executed. Parsers are written in a memory safe language. More information about the tool can be found on their announcement message, as well as on the tool s homepage. A GIF of the tool in action is also available.

Issues with our SOURCE_DATE_EPOCH code? Chris Lamb started a thread on our mailing list summarising some potential problems with the source code snippet the Reproducible Builds project has been using to parse the SOURCE_DATE_EPOCH environment variable:
I m not 100% sure who originally wrote this code, but it was probably sometime in the ~2015 era, and it must be in a huge number of codebases by now. Anyway, Alejandro Colomar was working on the shadow security tool and pinged me regarding some potential issues with the code. You can see this conversation here.
Chris ends his message with a request that those with intimate or low-level knowledge of time_t, C types, overflows and the various parsing libraries in the C standard library (etc.) contribute with further info.

Distribution updates In Debian this month, Roland Clobus posted another detailed update of the status of reproducible ISO images on our mailing list. In particular, Roland helpfully summarised that all major desktops build reproducibly with bullseye, bookworm, trixie and sid provided they are built for a second time within the same DAK run (i.e. [within] 6 hours) . Additionally 7 of the 8 bookworm images from the official download link build reproducibly at any later time. In addition to this, three reviews of Debian packages were added, 17 were updated and 15 were removed this month adding to our knowledge about identified issues. Elsewhere, Bernhard posted another monthly update for his work elsewhere in openSUSE.

Community updates There were made a number of improvements to our website, including Bernhard M. Wiedemann fixing a number of typos of the term nondeterministic . [ ] and Jan Zerebecki adding a substantial and highly welcome section to our page about SOURCE_DATE_EPOCH to document its interaction with distribution rebuilds. [ ].
diffoscope is our in-depth and content-aware diff utility that can locate and diagnose reproducibility issues. This month, Chris Lamb made a number of changes such as uploading versions 254 and 255 to Debian but focusing on triaging and/or merging code from other contributors. This included adding support for comparing eXtensible ARchive (.XAR/.PKG) files courtesy of Seth Michael Larson [ ][ ], as well considerable work from Vekhir in order to fix compatibility between various and subtle incompatible versions of the progressbar libraries in Python [ ][ ][ ][ ]. Thanks!

Reproducibility testing framework The Reproducible Builds project operates a comprehensive testing framework (available at tests.reproducible-builds.org) in order to check packages and other artifacts for reproducibility. In January, a number of changes were made by Holger Levsen:
  • Debian-related changes:
    • Reduce the number of arm64 architecture workers from 24 to 16. [ ]
    • Use diffoscope from the Debian release being tested again. [ ]
    • Improve the handling when killing unwanted processes [ ][ ][ ] and be more verbose about it, too [ ].
    • Don t mark a job as failed if process marked as to-be-killed is already gone. [ ]
    • Display the architecture of builds that have been running for more than 48 hours. [ ]
    • Reboot arm64 nodes when they hit an OOM (out of memory) state. [ ]
  • Package rescheduling changes:
    • Reduce IRC notifications to 1 when rescheduling due to package status changes. [ ]
    • Correctly set SUDO_USER when rescheduling packages. [ ]
    • Automatically reschedule packages regressing to FTBFS (build failure) or FTBR (build success, but unreproducible). [ ]
  • OpenWrt-related changes:
    • Install the python3-dev and python3-pyelftools packages as they are now needed for the sunxi target. [ ][ ]
    • Also install the libpam0g-dev which is needed by some OpenWrt hardware targets. [ ]
  • Misc:
    • As it s January, set the real_year variable to 2024 [ ] and bump various copyright years as well [ ].
    • Fix a large (!) number of spelling mistakes in various scripts. [ ][ ][ ]
    • Prevent Squid and Systemd processes from being killed by the kernel s OOM killer. [ ]
    • Install the iptables tool everywhere, else our custom rc.local script fails. [ ]
    • Cleanup the /srv/workspace/pbuilder directory on boot. [ ]
    • Automatically restart Squid if it fails. [ ]
    • Limit the execution of chroot-installation jobs to a maximum of 4 concurrent runs. [ ][ ]
Significant amounts of node maintenance was performed by Holger Levsen (eg. [ ][ ][ ][ ][ ][ ][ ] etc.) and Vagrant Cascadian (eg. [ ][ ][ ][ ][ ][ ][ ][ ]). Indeed, Vagrant Cascadian handled an extended power outage for the network running the Debian armhf architecture test infrastructure. This provided the incentive to replace the UPS batteries and consolidate infrastructure to reduce future UPS load. [ ] Elsewhere in our infrastructure, however, Holger Levsen also adjusted the email configuration for @reproducible-builds.org to deal with a new SMTP email attack. [ ]

Upstream patches The Reproducible Builds project tries to detects, dissects and fix as many (currently) unreproducible packages as possible. We endeavour to send all of our patches upstream where appropriate. This month, we wrote a large number of such patches, including: Separate to this, Vagrant Cascadian followed up with the relevant maintainers when reproducibility fixes were not included in newly-uploaded versions of the mm-common package in Debian this was quickly fixed, however. [ ]

If you are interested in contributing to the Reproducible Builds project, please visit our Contribute page on our website. However, you can get in touch with us via:

2 February 2024

Dirk Eddelbuettel: RQuantLib 0.4.21 on CRAN: Maintenance

A new minor release 0.4.21 of RQuantLib arrived at CRAN this afternoon, and has already been uploaded to Debian as well. QuantLib is a rather comprehensice free/open-source library for quantitative finance. RQuantLib connects (some parts of) it to the R environment and language, and has been part of CRAN for more than twenty years (!!) as it was one of the first packages I uploaded there. This release of RQuantLib benefits from some kind attention that Jeroen has been paying to how we build (especially at CRAN) on both macOS and Windows. So the build processes are a little better now, and no internal code changed. QuantLib 1.33 built unchanged.

Changes in RQuantLib version 0.4.21 (2024-02-01)
  • Generalize macOS build to universal build (Jeroen in #179)
  • Generalize Windows build to arm64 (Jeroen in #181)
  • Generalize version string use to support cmake use (Jeroen in #181 fixing #180)
  • Minor update to 'ci.yaml' github action (Dirk)

Courtesy of my CRANberries, there is also a diffstat report for the this release. As always, more detailed information is on the RQuantLib page. Questions, comments etc should go to the rquantlib-devel mailing list. Issue tickets can be filed at the GitHub repo. If you like this or other open-source work I do, you can now sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

31 January 2024

Dirk Eddelbuettel: dtts 0.1.2 on CRAN: Maintenance

Leonardo and I are happy to announce the release of a very minor maintenance release 0.1.2 of our dtts package which has been on CRAN for a little under two years now. dtts builds upon our nanotime package as well as the beloved data.table to bring high-performance and high-resolution indexing at the nanosecond level to data frames. dtts aims to offers the time-series indexing versatility of xts (and zoo) to the immense power of data.table while supporting highest nanosecond resolution. This release follows yesterday s long-awaited release of data.table version 1.5.0 which had been some time in the making as the first new major.minor release since Matt drifted into being less active and the forefront. The release also renamed the one C-level API accessor to data.table (which was added, if memory serves, by Leonardo with our use in mind). So we have to catch up to the renamed identifier; this release does that, and adds a versioned imports statement on data.table. The short list of changes follows.

Changes in version 0.1.2 (2024-01-31)
  • Update the one exported C-level identifier from data.table following its 1.5.0 release and a renaming
  • Routine continuous integration updates

Courtesy of my CRANberries, there is also a report with diffstat for this release. Questions, comments, issue tickets can be brought to the GitHub repo. If you like this or other open-source work I do, you can now sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

25 January 2024

Dirk Eddelbuettel: qlcal 0.0.10 on CRAN: Calendar Updates

The tenth release of the qlcal package arrivied at CRAN today. qlcal delivers the calendaring parts of QuantLib. It is provided (for the R package) as a set of included files, so the package is self-contained and does not depend on an external QuantLib library (which can be demanding to build). qlcal covers over sixty country / market calendars and can compute holiday lists, its complement (i.e. business day lists) and much more. Examples are in the README at the repository, the package page, and course at the CRAN package page. This releases synchronizes qlcal with the QuantLib release 1.33 and its updates to 2024 calendars.

Changes in version 0.0.10 (2024-01-24)
  • Synchronized with QuantLib 1.33

Courtesy of my CRANberries, there is a diffstat report for this release. See the project page and package documentation for more details, and more examples. If you like this or other open-source work I do, you can now sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

24 January 2024

Dirk Eddelbuettel: RApiDatetime 0.0.9 on CRAN: Maintenance

A new maintenance release of our RApiDatetime package is now on CRAN RApiDatetime provides a number of entry points for C-level functions of the R API for Date and Datetime calculations. The functions asPOSIXlt and asPOSIXct convert between long and compact datetime representation, formatPOSIXlt and Rstrptime convert to and from character strings, and POSIXlt2D and D2POSIXlt convert between Date and POSIXlt datetime. Lastly, asDatePOSIXct converts to a date type. All these functions are rather useful, but were not previously exported by R for C-level use by other packages. Which this package aims to change. This release responds to a CRAN request to clean up empty macros and sections in Rd files. Moreover, because the windows portion of the corresponding R-internal code underwent some changes, our (#ifdef conditional) coverage here is a little behind and created a warning under the newer UCRT setup. So starting with this release we are back to OS_type: unix meaning there will not be any Windows builds at CRAN. If you would like that to change, and ideally can work in the Windows portion, do not hesitate to get in touch. Details of the release follow based on the NEWS file.

Changes in RApiDatetime version 0.0.9 (2024-01-23)
  • Replace auto-generated stale RApitDatetime-package.Rd with macro-filled stanza to satisfy CRAN request.

Courtesy of my CRANberries, there is also a diffstat report for this release. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

Dirk Eddelbuettel: RcppAnnoy 0.0.22 on CRAN: Maintenance

annoy image A very minor maintenance release, now at version 0.0.22, of RcppAnnoy has arrived on CRAN. RcppAnnoy is the Rcpp-based R integration of the nifty Annoy library by Erik Bernhardsson. Annoy is a small and lightweight C++ template header library for very fast approximate nearest neighbours originally developed to drive the Spotify music discovery algorithm. It had all the buzzwords already a decade ago: it is one of the algorithms behind (drum roll ) vector search as it finds approximate matches very quickly and also allows to persist the data. This release responds to a CRAN request to clean up empty macros and sections in Rd files. Details of the release follow based on the NEWS file.

Changes in version 0.0.22 (2024-01-23)
  • Replace empty examples macro to satisfy CRAN request.

Courtesy of my CRANberries, there is also a diffstat report for this release. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

22 January 2024

Dirk Eddelbuettel: x13binary 1.1.60 on CRAN: Upstream Update, Updated Build

The x13binary team is thrilled to share the availability of Release 1.1.60-1 of the x13binary package providing the X-13ARIMA-SEATS program by the US Census Bureau which arrived on CRAN earlier today. This release brings the package up to speed with the most current release by the Census Bureau. More importantly, we finally made good on an old promise to ourselves and now install the binary by compiling from its Fortran sources! No more pre-made binaries. This required some work by Kirill, Michael, and Jeroen to finalize matter because, as we all know, the CRAN build processes and tool chains can be a little byzantine in their details. Use on platforms not covered by binaries from CRAN (or r-universe) should just work too as the demands on the (Fortran) compiler are fairly standard. All in all the build is fairly lightweight and quick even when rebuilding from source. Courtesy of my CRANberries, there is also a diffstat report for this release showing changes to the previous release. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

Dirk Eddelbuettel: RProtoBuf 0.4.22 on CRAN: Updated Windows Support!

A new maintenance release 0.4.22 of RProtoBuf arrived on CRAN earlier today. RProtoBuf provides R with bindings for the Google Protocol Buffers ( ProtoBuf ) data encoding and serialization library used and released by Google, and deployed very widely in numerous projects as a language and operating-system agnostic protocol. This release matches the recent 0.4.21 release which enabled use of the package with newer ProtoBuf releases. Tomas has been updating the Windows / rtools side of things, and supplied us with simple PR that will enable building with those updated versions once finalised. The following section from the NEWS.Rd file has full details.

Changes in RProtoBuf version 0.4.22 (2022-12-13)
  • Apply patch by Tomas Kalibera to support updated rtools to build with newer ProtoBuf releases on windows

Thanks to my CRANberries, there is a diff to the previous release. The RProtoBuf page has copies of the (older) package vignette, the quick overview vignette, and the pre-print of our JSS paper. Questions, comments etc should go to the GitHub issue tracker off the GitHub repo. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

20 January 2024

Niels Thykier: Making debputy: Writing declarative parsing logic

In this blog post, I will cover how debputy parses its manifest and the conceptual improvements I did to make parsing of the manifest easier. All instructions to debputy are provided via the debian/debputy.manifest file and said manifest is written in the YAML format. After the YAML parser has read the basic file structure, debputy does another pass over the data to extract the information from the basic structure. As an example, the following YAML file:
manifest-version: "0.1"
installations:
  - install:
      source: foo
      dest-dir: usr/bin
would be transformed by the YAML parser into a structure resembling:
 
  "manifest-version": "0.1",
  "installations": [
      
       "install":  
         "source": "foo",
         "dest-dir": "usr/bin",
        
      
  ]
 
This structure is then what debputy does a pass on to translate this into an even higher level format where the "install" part is translated into an InstallRule. In the original prototype of debputy, I would hand-write functions to extract the data that should be transformed into the internal in-memory high level format. However, it was quite tedious. Especially because I wanted to catch every possible error condition and report "You are missing the required field X at Y" rather than the opaque KeyError: X message that would have been the default. Beyond being tedious, it was also quite error prone. As an example, in debputy/0.1.4 I added support for the install rule and you should allegedly have been able to add a dest-dir: or an as: inside it. Except I crewed up the code and debputy was attempting to look up these keywords from a dict that could never have them. Hand-writing these parsers were so annoying that it demotivated me from making manifest related changes to debputy simply because I did not want to code the parsing logic. When I got this realization, I figured I had to solve this problem better. While reflecting on this, I also considered that I eventually wanted plugins to be able to add vocabulary to the manifest. If the API was "provide a callback to extract the details of whatever the user provided here", then the result would be bad.
  1. Most plugins would probably throw KeyError: X or ValueError style errors for quite a while. Worst case, they would end on my table because the user would have a hard time telling where debputy ends and where the plugins starts. "Best" case, I would teach debputy to say "This poor error message was brought to you by plugin foo. Go complain to them". Either way, it would be a bad user experience.
  2. This even assumes plugin providers would actually bother writing manifest parsing code. If it is that difficult, then just providing a custom file in debian might tempt plugin providers and that would undermine the idea of having the manifest be the sole input for debputy.
So beyond me being unsatisfied with the current situation, it was also clear to me that I needed to come up with a better solution if I wanted externally provided plugins for debputy. To put a bit more perspective on what I expected from the end result:
  1. It had to cover as many parsing errors as possible. An error case this code would handle for you, would be an error where I could ensure it sufficient degree of detail and context for the user.
  2. It should be type-safe / provide typing support such that IDEs/mypy could help you when you work on the parsed result.
  3. It had to support "normalization" of the input, such as
           # User provides
           - install: "foo"
           # Which is normalized into:
           - install:
               source: "foo"
4) It must be simple to tell  debputy  what input you expected.
At this point, I remembered that I had seen a Python (PYPI) package where you could give it a TypedDict and an arbitrary input (Sadly, I do not remember the name). The package would then validate the said input against the TypedDict. If the match was successful, you would get the result back casted as the TypedDict. If the match was unsuccessful, the code would raise an error for you. Conceptually, this seemed to be a good starting point for where I wanted to be. Then I looked a bit on the normalization requirement (point 3). What is really going on here is that you have two "schemas" for the input. One is what the programmer will see (the normalized form) and the other is what the user can input (the manifest form). The problem is providing an automatic normalization from the user input to the simplified programmer structure. To expand a bit on the following example:
# User provides
- install: "foo"
# Which is normalized into:
- install:
    source: "foo"
Given that install has the attributes source, sources, dest-dir, as, into, and when, how exactly would you automatically normalize "foo" (str) into source: "foo"? Even if the code filtered by "type" for these attributes, you would end up with at least source, dest-dir, and as as candidates. Turns out that TypedDict actually got this covered. But the Python package was not going in this direction, so I parked it here and started looking into doing my own. At this point, I had a general idea of what I wanted. When defining an extension to the manifest, the plugin would provide debputy with one or two definitions of TypedDict. The first one would be the "parsed" or "target" format, which would be the normalized form that plugin provider wanted to work on. For this example, lets look at an earlier version of the install-examples rule:
# Example input matching this typed dict.
#    
#       "source": ["foo"]
#       "into": ["pkg"]
#    
class InstallExamplesTargetFormat(TypedDict):
    # Which source files to install (dest-dir is fixed)
    sources: List[str]
    # Which package(s) that should have these files installed.
    into: NotRequired[List[str]]
In this form, the install-examples has two attributes - both are list of strings. On the flip side, what the user can input would look something like this:
# Example input matching this typed dict.
#    
#       "source": "foo"
#       "into": "pkg"
#    
#
class InstallExamplesManifestFormat(TypedDict):
    # Note that sources here is split into source (str) vs. sources (List[str])
    sources: NotRequired[List[str]]
    source: NotRequired[str]
    # We allow the user to write  into: foo  in addition to  into: [foo] 
    into: Union[str, List[str]]
FullInstallExamplesManifestFormat = Union[
    InstallExamplesManifestFormat,
    List[str],
    str,
]
The idea was that the plugin provider would use these two definitions to tell debputy how to parse install-examples. Pseudo-registration code could look something like:
def _handler(
    normalized_form: InstallExamplesTargetFormat,
) -> InstallRule:
    ...  # Do something with the normalized form and return an InstallRule.
concept_debputy_api.add_install_rule(
  keyword="install-examples",
  target_form=InstallExamplesTargetFormat,
  manifest_form=FullInstallExamplesManifestFormat,
  handler=_handler,
)
This was my conceptual target and while the current actual API ended up being slightly different, the core concept remains the same.
From concept to basic implementation Building this code is kind like swallowing an elephant. There was no way I would just sit down and write it from one end to the other. So the first prototype of this did not have all the features it has now. Spoiler warning, these next couple of sections will contain some Python typing details. When reading this, it might be helpful to know things such as Union[str, List[str]] being the Python type for either a str (string) or a List[str] (list of strings). If typing makes your head spin, these sections might less interesting for you. To build this required a lot of playing around with Python's introspection and typing APIs. My very first draft only had one "schema" (the normalized form) and had the following features:
  • Read TypedDict.__required_attributes__ and TypedDict.__optional_attributes__ to determine which attributes where present and which were required. This was used for reporting errors when the input did not match.
  • Read the types of the provided TypedDict, strip the Required / NotRequired markers and use basic isinstance checks based on the resulting type for str and List[str]. Again, used for reporting errors when the input did not match.
This prototype did not take a long (I remember it being within a day) and worked surprisingly well though with some poor error messages here and there. Now came the first challenge, adding the manifest format schema plus relevant normalization rules. The very first normalization I did was transforming into: Union[str, List[str]] into into: List[str]. At that time, source was not a separate attribute. Instead, sources was a Union[str, List[str]], so it was the only normalization I needed for all my use-cases at the time. There are two problems when writing a normalization. First is determining what the "source" type is, what the target type is and how they relate. The second is providing a runtime rule for normalizing from the manifest format into the target format. Keeping it simple, the runtime normalizer for Union[str, List[str]] -> List[str] was written as:
def normalize_into_list(x: Union[str, List[str]]) -> List[str]:
    return x if isinstance(x, list) else [x]
This basic form basically works for all types (assuming none of the types will have List[List[...]]). The logic for determining when this rule is applicable is slightly more involved. My current code is about 100 lines of Python code that would probably lose most of the casual readers. For the interested, you are looking for _union_narrowing in declarative_parser.py With this, when the manifest format had Union[str, List[str]] and the target format had List[str] the generated parser would silently map a string into a list of strings for the plugin provider. But with that in place, I had covered the basics of what I needed to get started. I was quite excited about this milestone of having my first keyword parsed without handwriting the parser logic (at the expense of writing a more generic parse-generator framework).
Adding the first parse hint With the basic implementation done, I looked at what to do next. As mentioned, at the time sources in the manifest format was Union[str, List[str]] and I considered to split into a source: str and a sources: List[str] on the manifest side while keeping the normalized form as sources: List[str]. I ended up committing to this change and that meant I had to solve the problem getting my parser generator to understand the situation:
# Map from
class InstallExamplesManifestFormat(TypedDict):
    # Note that sources here is split into source (str) vs. sources (List[str])
    sources: NotRequired[List[str]]
    source: NotRequired[str]
    # We allow the user to write  into: foo  in addition to  into: [foo] 
    into: Union[str, List[str]]
# ... into
class InstallExamplesTargetFormat(TypedDict):
    # Which source files to install (dest-dir is fixed)
    sources: List[str]
    # Which package(s) that should have these files installed.
    into: NotRequired[List[str]]
There are two related problems to solve here:
  1. How will the parser generator understand that source should be normalized and then mapped into sources?
  2. Once that is solved, the parser generator has to understand that while source and sources are declared as NotRequired, they are part of a exactly one of rule (since sources in the target form is Required). This mainly came down to extra book keeping and an extra layer of validation once the previous step is solved.
While working on all of this type introspection for Python, I had noted the Annotated[X, ...] type. It is basically a fake type that enables you to attach metadata into the type system. A very random example:
# For all intents and purposes,  foo  is a string despite all the  Annotated  stuff.
foo: Annotated[str, "hello world"] = "my string here"
The exciting thing is that you can put arbitrary details into the type field and read it out again in your introspection code. Which meant, I could add "parse hints" into the type. Some "quick" prototyping later (a day or so), I got the following to work:
# Map from
#      
#        "source": "foo"  # (or "sources": ["foo"])
#        "into": "pkg"
#      
class InstallExamplesManifestFormat(TypedDict):
    # Note that sources here is split into source (str) vs. sources (List[str])
    sources: NotRequired[List[str]]
    source: NotRequired[
        Annotated[
            str,
            DebputyParseHint.target_attribute("sources")
        ]
    ]
    # We allow the user to write  into: foo  in addition to  into: [foo] 
    into: Union[str, List[str]]
# ... into
#      
#        "source": ["foo"]
#        "into": ["pkg"]
#      
class InstallExamplesTargetFormat(TypedDict):
    # Which source files to install (dest-dir is fixed)
    sources: List[str]
    # Which package(s) that should have these files installed.
    into: NotRequired[List[str]]
Without me (as a plugin provider) writing a line of code, I can have debputy rename or "merge" attributes from the manifest form into the normalized form. Obviously, this required me (as the debputy maintainer) to write a lot code so other me and future plugin providers did not have to write it.
High level typing At this point, basic normalization between one mapping to another mapping form worked. But one thing irked me with these install rules. The into was a list of strings when the parser handed them over to me. However, I needed to map them to the actual BinaryPackage (for technical reasons). While I felt I was careful with my manual mapping, I knew this was exactly the kind of case where a busy programmer would skip the "is this a known package name" check and some user would typo their package resulting in an opaque KeyError: foo. Side note: "Some user" was me today and I was super glad to see debputy tell me that I had typoed a package name (I would have been more happy if I had remembered to use debputy check-manifest, so I did not have to wait through the upstream part of the build that happened before debhelper passed control to debputy...) I thought adding this feature would be simple enough. It basically needs two things:
  1. Conversion table where the parser generator can tell that BinaryPackage requires an input of str and a callback to map from str to BinaryPackage. (That is probably lie. I think the conversion table came later, but honestly I do remember and I am not digging into the git history for this one)
  2. At runtime, said callback needed access to the list of known packages, so it could resolve the provided string.
It was not super difficult given the existing infrastructure, but it did take some hours of coding and debugging. Additionally, I added a parse hint to support making the into conditional based on whether it was a single binary package. With this done, you could now write something like:
# Map from
class InstallExamplesManifestFormat(TypedDict):
    # Note that sources here is split into source (str) vs. sources (List[str])
    sources: NotRequired[List[str]]
    source: NotRequired[
        Annotated[
            str,
            DebputyParseHint.target_attribute("sources")
        ]
    ]
    # We allow the user to write  into: foo  in addition to  into: [foo] 
    into: Union[BinaryPackage, List[BinaryPackage]]
# ... into
class InstallExamplesTargetFormat(TypedDict):
    # Which source files to install (dest-dir is fixed)
    sources: List[str]
    # Which package(s) that should have these files installed.
    into: NotRequired[
        Annotated[
            List[BinaryPackage],
            DebputyParseHint.required_when_multi_binary()
        ]
    ]
Code-wise, I still had to check for into being absent and providing a default for that case (that is still true in the current codebase - I will hopefully fix that eventually). But I now had less room for mistakes and a standardized error message when you misspell the package name, which was a plus.
The added side-effect - Introspection A lovely side-effect of all the parsing logic being provided to debputy in a declarative form was that the generated parser snippets had fields containing all expected attributes with their types, which attributes were required, etc. This meant that adding an introspection feature where you can ask debputy "What does an install rule look like?" was quite easy. The code base already knew all of this, so the "hard" part was resolving the input the to concrete rule and then rendering it to the user. I added this feature recently along with the ability to provide online documentation for parser rules. I covered that in more details in my blog post Providing online reference documentation for debputy in case you are interested. :)
Wrapping it up This was a short insight into how debputy parses your input. With this declarative technique:
  • The parser engine handles most of the error reporting meaning users get most of the errors in a standard format without the plugin provider having to spend any effort on it. There will be some effort in more complex cases. But the common cases are done for you.
  • It is easy to provide flexibility to users while avoiding having to write code to normalize the user input into a simplified programmer oriented format.
  • The parser handles mapping from basic types into higher forms for you. These days, we have high level types like FileSystemMode (either an octal or a symbolic mode), different kind of file system matches depending on whether globs should be performed, etc. These types includes their own validation and parsing rules that debputy handles for you.
  • Introspection and support for providing online reference documentation. Also, debputy checks that the provided attribute documentation covers all the attributes in the manifest form. If you add a new attribute, debputy will remind you if you forget to document it as well. :)
In this way everybody wins. Yes, writing this parser generator code was more enjoyable than writing the ad-hoc manual parsers it replaced. :)

18 January 2024

Russell Coker: LicheePi 4A (RISC-V) First Look

I Just bought a LicheePi 4A RISC-V embedded computer (like a RaspberryPi but with a RISC-V CPU) for $322.68 from Aliexpress (the official site for buying LicheePi devices). Here is the Sipheed web page about it and their other recent offerings [1]. I got the version with 16G of RAM and 128G of storage, I probably don t need that much storage (I can use NFS or USB) but 16G of RAM is good for VMs. Here is the Wiki about this board [2]. Configuration When you get one of these devices you should make setting up ssh server your first priority. I found the HDMI output to be very unreliable. The first monitor I tried was a Samsung 4K monitor dating from when 4K was a new thing, the LicheePi initially refused to operate at a resolution higher than 1024*768 but later on switched to 4K resolution when resuming from screen-blank for no apparent reason (and the window manager didn t support this properly). On the Dell 4K monitor I use on my main workstation it sometimes refused to talk to it and occasionally worked. I got it running at 1920*1080 without problems and then switched it to 4K and it lost video sync and never talked to that monitor again. On my Desklab portabable 4K monitor I got it to display in 4K resolution but only the top left 1/4 of the screen displayed. The issues with HDMI monitor support greatly limit the immediate potential for using this as a workstation. It doesn t make it impossible but would be fiddly at best. It s quite likely that a future OS update will fix this. But at the moment it s best used as a server. The LicheePi has a custom Linux distribution based on Ubuntu so you want too put something like the following in /etc/network/interfaces to make it automatically connect to the ethernet when plugged in:
auto end0
iface end0 inet dhcp
Then to get sshd to start you have to run the following commands to generate ssh host keys that aren t zero bytes long:
rm /etc/ssh/ssh_host_*
systemctl restart ssh.service
It appears to have wifi hardware but the OS doesn t recognise it. This isn t a priority for me as I mostly want to use it as a server. Performance For the first test of performance I created a 100MB file from /dev/urandom and then tried compressing it on various systems. With zstd -9 it took 16.893 user seconds on the LicheePi4A, 0.428s on my Thinkpad X1 Carbon Gen5 with a i5-6300U CPU (Debian/Unstable), 1.288s on my E5-2696 v3 workstation (Debian/Bookworm), 0.467s on the E5-2696 v3 running Debian/Unstable, 2.067s on a E3-1271 v3 server, and 7.179s on the E3-1271 v3 system emulating a RISC-V system via QEMU running Debian/Unstable. It s very impressive that the QEMU emulation is fast enough that emulating a different CPU architecture is only 3.5* slower for this test (or maybe 10* slower if it was running Debian/Unstable on the AMD64 code)! The emulated RISC-V is also more than twice as fast as real RISC-V hardware and probably of comparable speed to real RISC-V hardware when running the same versions (and might be slightly slower if running the same version of zstd) which is a tribute to the quality of emulation. One performance issue that most people don t notice is the time taken to negotiate ssh sessions. It s usually not noticed because the common CPUs have got faster at about the same rate as the algorithms for encryption and authentication have become more complex. On my i5-6300U laptop it takes 0m0.384s to run ssh -i ~/.ssh/id_ed25519 localhost id with the below server settings (taken from advice on ssh-audit.com [3] for a secure ssh configuration). On the E3-1271 v3 server it is 0.336s, on the QMU system it is 28.022s, and on the LicheePi it is 0.592s. By this metric the LicheePi is about 80% slower than decent x86 systems and the QEMU emulation of RISC-V is 73* slower than the x86 system it runs on. Does crypto depend on instructions that are difficult to emulate?
HostKey /etc/ssh/ssh_host_ed25519_key
KexAlgorithms -ecdh-sha2-nistp256,ecdh-sha2-nistp384,ecdh-sha2-nistp521,diffie-hellman-group14-sha256
MACs -umac-64-etm@openssh.com,hmac-sha1-etm@openssh.com,umac-64@openssh.com,umac-128@openssh.com,hmac-sha2-256,hmac-sha2-512,hmac-sha1
I haven t yet tested the performance of Ethernet (what routing speed can you get through the 2 gigabit ports?), emmc storage, and USB. At the moment I ve been focused on using RISC-V as a test and development platform. My conclusion is that I m glad I don t plan to compile many kernels or anything large like LibreOffice. But that for typical development that I do it will be quite adequate. The speed of Chromium seems adequate in basic tests, but the video output hasn t worked reliably enough to do advanced tests. Hardware Features Having two Gigabit Ethernet ports, 4 USB-3 ports, and Wifi on board gives some great options for using this as a router. It s disappointing that they didn t go with 2.5Gbit as everyone seems to be doing that nowadays but Gigabit is enough for most things. Having only a single HDMI port and not supporting USB-C docks (the USB-C port appears to be power only) limits what can be done for workstation use and for controlling displays. I know of people using small ARM computers attached to the back of large TVs for advertising purposes and that isn t going to be a great option for this. The CPU and RAM apparently uses a lot of power (which is relative the entire system draws up to 2A at 5V so the CPU would be something below 5W). To get this working a cooling fan has to be stuck to the CPU and RAM chips via a layer of thermal stuff that resembles a fine sheet of blu-tack in both color and stickyness. I am disappointed that there isn t any more solid form of construction, to mount this on a wall or ceiling some extra hardware would be needed to secure this. Also if they just had a really big copper heatsink I think that would be better. 80386 CPUs with similar TDP were able to run without a fan. I wonder how things would work with all USB ports in use. It s expected that a USB port can supply a minimum of 2.5W which means that all the ports could require 10W if they were active. Presumably something significantly less than 5W is available for the USB ports. Other Devices Sipheed has a range of other devices in the works. They currently sell the LicheeCluster4A which support 7 compute modules for a cluster in a box. This has some interesting potential for testing and demonstrating cluster software but you could probably buy an AMD64 system with more compute power for less money. The Lichee Console 4A is a tiny laptop which could be useful for people who like the 7 laptop form factor, unfortunately it only has a 1280*800 display if it had the same resolution display as a typical 7 phone I would have bought one. The next device that appeals to me is the soon to be released Lichee Pad 4A which is a 10.1 tablet with 1920*1200 display, Wifi6, Bluetooth 5.4, and 16G of RAM. It also has 1 USB-C connection, 2*USB-3 sockets, and support for an external card with 2*Gigabit ethernet. It s a tablet as a laptop without keyboard instead of the more common larger phone design model. They are also about to release the LicheePadMax4A which is similar to the other tablet but with a 14 2240*1400 display and which ships with a keyboard to make it essentially a laptop with detachable keyboard. Conclusion At this time I wouldn t recommend that this device be used as a workstation or laptop, although the people who want to do such things will probably do it anyway regardless of my recommendations. I think it will be very useful as a test system for RISC-V development. I have some friends who are interested in this sort of thing and I can give them VMs. It is a bit expensive. The Sipheed web site boasts about the LicheePi4 being faster than the RaspberryPi4, but it s not a lot faster and the RaspberryPi4 is much cheaper ($127 or $129 for one with 8G of RAM). The RaspberryPi4 has two HDMI ports but a limit of 8G of RAM while the LicheePi has up to 16G of RAM and two Gigabit Ethernet ports but only a single HDMI port. It seems that the RaspberryPi4 might win if you want a cheap low power desktop system. At this time I think the reason for this device is testing out RISC-V as an alternative to the AMD64 and ARM64 architectures. An open CPU architecture goes well with free software, but it isn t just people who are into FOSS who are testing such things. I know some corporations are trying out RISC-V as a way of getting other options for embedded systems that don t involve paying monopolists. The Lichee Console 4A is probably a usable tiny laptop if the resolution is sufficient for your needs. As an aside I predict that the tiny laptop or pocket computer segment will take off in the near future. There are some AMD64 systems the size of a phone but thicker that run Windows and go for reasonable prices on AliExpress. Hopefully in the near future this device will have better video drivers and be usable as a small and quiet workstation. I won t rule out the possibility of making this my main workstation in the not too distant future, all it needs is reliable 4K display and the ability to decode 4K video. It s performance for web browsing and as an ssh client seems adequate, and that s what matters for my workstation use. But for the moment it s just for server use.

12 January 2024

Dirk Eddelbuettel: RcppSpdlog 0.0.16 on CRAN: New Upstream

Version 0.0.16 of RcppSpdlog is now on CRAN and will be uploaded to Debian. RcppSpdlog bundles spdlog, a wonderful header-only C++ logging library with all the bells and whistles you would want that was written by Gabi Melman, and also includes fmt by Victor Zverovich. You can learn more at the nice package documention site. This releases updates the code to the version 1.13 of spdlog which was release this morning. The NEWS entry for this release follows.

Changes in RcppSpdlog version 0.0.16 (2024-01-12)
  • Upgraded to upstream releases spdlog 1.13.0

Courtesy of my CRANberries, there is also a diffstat report. More detailed information is on the RcppSpdlog page, or the package documention site. If you like this or other open-source work I do, you can sponsor me at GitHub.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

Next.

Previous.