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authorVincent Ambo <tazjin@google.com>2019-08-15T15·11+0100
committerVincent Ambo <tazjin@google.com>2019-08-15T15·11+0100
commit128875b501bc2989617ae553317b80faa556d752 (patch)
tree9b32d12123801179ebe900980556486ad4803482 /third_party/bazel/rules_haskell/docs/why-bazel.rst
parenta20daf87265a62b494d67f86d4a5199f14394973 (diff)
chore: Remove remaining Bazel-related files r/31
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-.. _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