From f723b8b878a3c4a4687b9e337a875500bebb39b1 Mon Sep 17 00:00:00 2001 From: Vincent Ambo Date: Thu, 4 Jul 2019 11:18:12 +0100 Subject: feat(third_party/bazel): Check in rules_haskell from Tweag --- third_party/bazel/rules_haskell/docs/why-bazel.rst | 102 +++++++++++++++++++++ 1 file changed, 102 insertions(+) create mode 100644 third_party/bazel/rules_haskell/docs/why-bazel.rst (limited to 'third_party/bazel/rules_haskell/docs/why-bazel.rst') diff --git a/third_party/bazel/rules_haskell/docs/why-bazel.rst b/third_party/bazel/rules_haskell/docs/why-bazel.rst new file mode 100644 index 000000000000..2ad4bc598be3 --- /dev/null +++ b/third_party/bazel/rules_haskell/docs/why-bazel.rst @@ -0,0 +1,102 @@ +.. _why-bazel: + +Is Bazel right for me? +====================== + +Nearly as many build tools exist as there are programming languages +out there. C++ has Autotools_/Make_, CMake_ and many others. Java has +Ant_, Maven_, Gradle_ and several more. Haskell has Cabal_, Stack_, +Shake_ and several more. Each of these originated in a given language +community but are in some cases generic enough to support building any +language. Are any of them the right choice for your use case? Should +you be combining several systems? That's what this document should +help you answer. + +Rule of thumb +------------- + +If a combination of the following apply, then you're better off using +Cabal_ or Stack_: + +* your project is an independently publishable single library, or + small set of libraries; +* your project is open source code and has at most small static + assets (hence publishable on Hackage); +* your project is nearly entirely Haskell code with perhaps a little + bit of C; +* your project has many dependencies on other packages found on + Hackage but few if any system dependencies (like zlib, libpng etc); + +Bazel works well for the following use cases: + +* projects that cannot be hosted on Hackage (games with large static + assets, proprietary code etc); +* projects with a very large amount of code hosted in a single + repository; +* projects in which you or your team are writing code in two or more + languages (e.g. Haskell/PureScript, or Haskell/Java, or + Haskell/C++/FORTRAN); + +Rationale +--------- + +For all the benefits it can bring, Bazel also has an upfront cost. +Don't pay that cost if the benefits don't justify it. + +If you don't have much code to build, any build tool will do. Build +issues like lack of complete reproducibility are comparatively easier +to debug, and working around build system bugs by wiping the entire +build cache first is entirely viable in this particular case. So might +as well use low-powered Haskell-native build tools that ship with GHC. +You won't *need* sandboxed build actions to guarantee build system +correctness, completely hermetic builds for good reproducibility, +build caching, test result caching or distributed builds for faster +build and test times. Those features start to matter for larger +projects, and become essential for very large monorepos_. + +Why exactly do these features matter? + +* **Hermetic builds** are builds that do not take any part of the + host's system configuration (set of installed system libraries and + their versions, content of ``/etc``, OS version, etc) as an input. + If all build actions are deterministic, hermeticity guarantees that + builds are reproducible anywhere, anytime. More developers on + a project means more subtly different system configurations to cope + with. The more system configurations, the more likely that the build + will fail in one of these configurations but not in others... Unless + the build is completely hermetic. +* **Sandboxing build actions** guarantees that all inputs to all build + actions are properly declared. This helps prevent build system + correctness bugs, which are surprisingly and exceedingly common in + most non-sandboxing build systems, especially as the build system + becomes more complex. When a build system *might* be incorrect, + users regularly have to wipe the entire build cache to work around + issues. As the codebase becomes very large, rebuilding from scratch + can cost a lot of CPU time. +* **Distributed build caches** make building the code from a fresh + checkout trivially fast. Continuous integration populates the build + cache at every branch push, so that building all artifacts from + fresh checkouts seldom needs to actually build anything at all + locally. In the common case, builds become network-bound instead of + CPU-bound. +* **Distributed build action execution** mean that average build times + can stay constant even as the codebase grows, because you can + seamlessly distribute the build on more machines. +* **Test result caching** is the key to keeping continuous + integration times very low. Only those tests that depend on code + that was modified need be rerun. + +On their own hermetic and sandboxed builds can already save quite +a few headaches. But crucially, without them one can't even hope to +have any of the other features that follow them above. + +.. _Autotools: https://en.wikipedia.org/wiki/GNU_Build_System +.. _Make: https://en.wikipedia.org/wiki/Make_(software) +.. _CMake: https://cmake.org/ +.. _Ant: https://ant.apache.org/ +.. _Maven: https://maven.apache.org/index.html +.. _Gradle: https://gradle.org/ +.. _Cabal: https://www.haskell.org/cabal/ +.. _Stack: http://haskellstack.org/ +.. _Shake: https://shakebuild.com/ +.. _monorepos: https://en.wikipedia.org/wiki/Monorepo -- cgit 1.4.1