The boa recipe spec#

Boa implements a new recipe spec, different from the traditional “meta.yaml” used in conda-build. A boa recipe has to be stored as recipe.yaml file.

History#

A discussion was started on what a new recipe spec could or should look like. The fragments of this discussion can be found here: https://github.com/mamba-org/conda-specs/blob/master/proposed_specs/recipe.md The reason for a new spec are:

Make it easier to parse (“pure yaml”). conda-build uses a mix of comments and jinja to achieve a great deal of flexibility, but it’s hard to parse the recipe with a computer
iron out some inconsistencies around multiple outputs (build vs. build/script and more)
remove any need for recursive parsing & solving

Spec#

The boa spec has the following parts:

context: to set up variables that can later be used in Jinja string interpolation
package: defines name, version etc. of the top-level package
source: points to the sources that need to be downloaded in order to build the recipe
build: defines how to build the recipe and what build number to use
requirements: defines requirements of the top-level package
test: defines tests for the top-level package
outputs: a recipe can have multiple outputs. Each output can and should have a package, requirements and test section

Major differences with conda-build#

recipe filename is recipe.yaml, not meta.yaml
outputs have less complicated behavior, keys are same as top-level recipe (e.g. build/script, not just script), same for package/name, not just name)
no implicit meta-packages in outputs
no full Jinja2 support: no conditional or {% set ... support, only string interpolation. Variables can be set in the toplevel “context” which is valid YAML
Jinja string interpolation needs to be quoted at the beginning of a string, e.g. - "{{ version }}" in order for it to be valid YAML
Selectors use a YAML dictionary style (vs. comments in conda-build). E.g. - sel(osx): somepkg instead of - somepkg # [osx]
Skip instruction uses a list of skip conditions and not the selector syntax from conda-build (e.g. skip: ["osx", "win and py37"])

Spec reference#

The spec is also made availalble through a JSON Schema (which is used for validation). The autogenerated docs can be found here.

Quick start (from conda-build)#

You can use boa convert meta.yaml to convert an existing recipe from conda-build syntax to boa. The command will output the new recipe to stdout. To quickly save the result, you can use boa convert meta.yaml > recipe.yaml and run boa build .. Please note that the conversion process is working fine only for “simple” recipes and there will be some needed manual work to convert complex recipes.

Examples#

# this sets up "context variables" (in this case name and version) that
# can later be used in Jinja expressions
context:
  version: 1.1.0
  name: imagesize

# top level package information (name and version)
package:
  name: "{{ name }}"
  version: "{{ version }}"

# location to get the source from
source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
  sha256: f3832918bc3c66617f92e35f5d70729187676313caa60c187eb0f28b8fe5e3b5

# build number (should be incremented if a new build is made, but version is not incrementing)
build:
  number: 1
  script: python -m pip install --no-deps --ignore-installed .

# the requirements at build and runtime
requirements:
  host:
    - python
    - pip
  run:
    - python

# tests to validate that the package works as expected
test:
  imports:
    - imagesize

# information about the package
about:
  home: https://github.com/shibukawa/imagesize_py
  license: MIT
  summary: 'Getting image size from png/jpeg/jpeg2000/gif file'
  description: |
    This module analyzes jpeg/jpeg2000/png/gif image header and
    return image size.
  dev_url: https://github.com/shibukawa/imagesize_py
  doc_url: https://pypi.python.org/pypi/imagesize
  doc_source_url: https://github.com/shibukawa/imagesize_py/blob/master/README.rst

# the below is conda-forge specific!
extra:
  recipe-maintainers:
    - somemaintainer

Package section#

Specifies package information.

package:
  name: bsdiff4
  version: "2.1.4"

name: The lower case name of the package. It may contain “-”, but no spaces.
version: The version number of the package. Use the PEP-386 verlib conventions. Cannot contain “-”. YAML interprets version numbers such as 1.0 as floats, meaning that 0.10 will be the same as 0.1. To avoid this, put the version number in quotes so that it is interpreted as a string.

Source section#

Specifies where the source code of the package is coming from. The source may come from a tarball file, git, hg, or svn. It may be a local path and it may contain patches.

Source from tarball or zip archive#

source:
  url: https://pypi.python.org/packages/source/b/bsdiff4/bsdiff4-1.1.4.tar.gz
  md5: 29f6089290505fc1a852e176bd276c43
  sha1: f0a2c9a30073449cfb7d171c57552f3109d93894
  sha256: 5a022ff4c1d1de87232b1c70bde50afbb98212fd246be4a867d8737173cf1f8f

If an extracted archive contains only 1 folder at its top level, its contents will be moved 1 level up, so that the extracted package contents sit in the root of the work folder.

Source from git#

The git_url can also be a relative path to the recipe directory.

source:
  git_url: https://github.com/ilanschnell/bsdiff4.git
  git_rev: 1.1.4
  git_depth: 1 # (Defaults to -1/not shallow)

The depth argument relates to the ability to perform a shallow clone. A shallow clone means that you only download part of the history from Git. If you know that you only need the most recent changes, you can say, git_depth: 1, which is faster than cloning the entire repo. The downside to setting it at 1 is that, unless the tag is on that specific commit, then you won’t have that tag when you go to reference it in git_rev (for example). If your git_depth is insufficient to capture the tag in git_rev, you’ll encounter an error. So in the example above, unless the 1.1.4 is the very head commit and the one that you’re going to grab, you may encounter an error.

Source from hg#

source:
  hg_url: ssh://hg@bitbucket.org/ilanschnell/bsdiff4
  hg_tag: 1.1.4

Source from svn#

source:
  svn_url: https://github.com/ilanschnell/bsdiff
  svn_rev: 1.1.4
  svn_ignore_externals: True # (defaults to False)

Source from a local path#

If the path is relative, it is taken relative to the recipe directory. The source is copied to the work directory before building.

  source:
    path: ../src

If the local path is a git or svn repository, you get the corresponding environment variables defined in your build environment. The only practical difference between git_url or hg_url and path as source arguments is that git_url and hg_url would be clones of a repository, while path would be a copy of the repository. Using path allows you to build packages with unstaged and uncommitted changes in the working directory. git_url can build only up to the latest commit.

Patches#

Patches may optionally be applied to the source.

  source:
    #[source information here]
    patches:
      - my.patch # the patch file is expected to be found in the recipe

boa (conda-build) automatically determines the patch strip level.

Destination path#

Within boa’s work directory, you may specify a particular folder to place source into. Boa will always drop you into the same folder (build folder/work), but it’s up to you whether you want your source extracted into that folder, or nested deeper. This feature is particularly useful when dealing with multiple sources, but can apply to recipes with single sources as well.

source:
  #[source information here]
  folder: my-destination/folder

Source from multiple sources#

Some software is most easily built by aggregating several pieces.

The syntax is a list of source dictionaries. Each member of this list follows the same rules as the single source. All features for each member are supported.

Example:

  source:
    - url: https://package1.com/a.tar.bz2
      folder: stuff
    - url: https://package1.com/b.tar.bz2
      folder: stuff
    - git_url: https://github.com/mamba-org/boa
      folder: boa

Here, the two URL tarballs will go into one folder, and the git repo is checked out into its own space. Git will not clone into a non-empty folder.

Build section#

Specifies build information.

Each field that expects a path can also handle a glob pattern. The matching is performed from the top of the build environment, so to match files inside your project you can use a pattern similar to the following one: "**/myproject/**/*.txt". This pattern will match any .txt file found in your project. Quotation marks ("") are required for patterns that start with a *.

Recursive globbing using ** is also supported.

Build number and string#

The build number should be incremented for new builds of the same version. The number defaults to 0. The build string cannot contain “-”. The string defaults to the default boa build string plus the build number.

  build:
    number: 1
    string: abc

A hash will appear when the package is affected by one or more variables from the conda_build_config.yaml file. The hash is made up from the “used” variables

if anything is used, you have a hash. If you don’t use these variables then you won’t have a hash. There are a few special cases that do not affect the hash, such as Python and R or anything that already had a place in the build string.

The build hash will be added to the build string if these are true for any dependency:

package is an explicit dependency in build, host, or run deps
package has a matching entry in conda_build_config.yaml which is a pin to a specific version, not a lower bound
that package is not ignored by ignore_version

package uses {{ compiler() }} jinja2 function

Python entry points#

The following example creates a Python entry point named “bsdiff4” that calls bsdiff4.cli.main_bsdiff4().

build:
  entry_points:
    - bsdiff4 = bsdiff4.cli:main_bsdiff4
    - bspatch4 = bsdiff4.cli:main_bspatch4

Script#

By default, boa uses a build.sh file on Unix (macOS and Linux) and a bld.bat file on Linux, if they exist in the same folder as the recipe.yaml file. With the script parameter you can either supply a different filename or write out short build scripts. You may need to use selectors to use different scripts for different platforms.

build:
  script: python setup.py install --single-version-externally-managed --record=record.txt

Skipping builds#

List conditions under which boa should skip the build of this recipe. Particularly useful for defining recipes that are platform specific. By default, a build is never skipped.

build:
  skip:
    - win
    - osx and py36
    ...

Architecture independent packages#

Allows you to specify “no architecture” when building a package, thus making it compatible with all platforms and architectures. Noarch packages can be installed on any platform.

Assigning the noarch key as generic tells conda to not try any manipulation of the contents.

build:
  noarch: generic

noarch: generic is most useful for packages such as static javascript assets and source archives. For pure Python packages that can run on any Python version, you can use the noarch: python value instead:

build:
  noarch: python

Warning

At the time of this writing, noarch packages should not make use of preprocess-selectors: noarch packages are built with the directives which evaluate to true in the platform it is built on, which probably will result in incorrect/incomplete installation in other platforms.

Include build recipe#

The full boa recipe and rendered recipe.yaml file is included in the package_metadata by default. You can disable this with:

build:
  include_recipe: false

Requirements section#

Specifies the build and runtime requirements. Dependencies of these requirements are included automatically.

Versions for requirements must follow the conda/mamba match specification. See build-version-spec.

Build#

Tools required to build the package. These packages are run on the build system and include things such as revision control systems (Git, SVN) make tools (GNU make, Autotool, CMake) and compilers (real cross, pseudo-cross, or native when not cross-compiling), and any source pre-processors.

Packages which provide “sysroot” files, like the CDT packages (see below) also belong in the build section.

requirements:
  build:
    - git
    - cmake

Host#

It represents packages that need to be specific to the target platform when the target platform is not necessarily the same as the native build platform. For example, in order for a recipe to be “cross-capable”, shared libraries requirements must be listed in the host section, rather than the build section, so that the shared libraries that get linked are ones for the target platform, rather than the native build platform. You should also include the base interpreter for packages that need one. In other words, a Python package would list python here and an R package would list mro-base or r-base.

requirements:
  build:
    - "{{ compiler('c') }}"
    - sel(linux): "{{ cdt('xorg-x11-proto-devel') }}"
  host:
    - python

Note

When both build and host sections are defined, the build section can be thought of as “build tools” - things that run on the native platform, but output results for the target platform. For example, a cross-compiler that runs on linux-64, but targets linux-armv7.

The PREFIX environment variable points to the host prefix. With respect to activation during builds, both the host and build environments are activated. The build prefix is activated before the host prefix so that the host prefix has priority over the build prefix. Executables that don’t exist in the host prefix should be found in the build prefix.

The build and host prefixes are always separate when both are defined, or when {{ compiler() }} Jinja2 functions are used. The only time that build and host are merged is when the host section is absent, and no {{ compiler() }} Jinja2 functions are used in meta.yaml.

Run#

Packages required to run the package. These are the dependencies that are installed automatically whenever the package is installed. Package names should follow the package match specifications.

requirements:
  run:
    - python
    - sel(py26): argparse
    - six >=1.8.0

To build a recipe against different versions of NumPy and ensure that each version is part of the package dependencies, list numpy as a requirement in recipe.yaml and use a conda_build_config.yaml file with multiple NumPy versions.

Run_constrained#

Packages that are optional at runtime but must obey the supplied additional constraint if they are installed.

Package names should follow the package match specifications.

requirements:
  run_constrained:
    - optional-subpackage =={{ version }}

For example, let’s say we have an environment that has package “a” installed at version 1.0. If we install package “b” that has a run_constrained entry of “a>1.0”, then mamba would need to upgrade “a” in the environment in order to install “b”.

This is especially useful in the context of virtual packages, where the run_constrained dependency is not a package that mamba manages, but rather a virtual package that represents a system property that mamba can’t change. For example, a package on linux may impose a run_constrained dependency on __glibc>=2.12. This is the version bound consistent with CentOS 6. Software built against glibc 2.12 will be compatible with CentOS 6. This run_constrained dependency helps mamba tell the user that a given package can’t be installed if their system glibc version is too old.

Test section#

If this section exists or if there is a run_test.[py,pl,sh,bat] file in the recipe, the package is installed into a test environment after the build is finished and the tests are run there.

Test files#

Test files that are copied from the recipe into the temporary test directory and are needed during testing.

test:
  files:
    - test-data.txt

Source files#

Test files that are copied from the source work directory into the temporary test directory and are needed during testing (note that the source work directory is otherwise not available at all during testing).

test:
  source_files:
    - test-data.txt
    - some/directory
    - some/directory/pattern*.sh

Test requirements#

In addition to the runtime requirements, you can specify requirements needed during testing. The runtime requirements that you specified in the “run” section described above are automatically included during testing.

test:
  requires:
    - nose

Test commands#

Commands that are run as part of the test.

test:
  commands:
    - bsdiff4 -h
    - bspatch4 -h

Python imports#

List of Python modules or packages that will be imported in the test environment.

test:
  imports:
    - bsdiff4

This would be equivalent to having a run_test.py with the following:

import bsdiff4

Run test script#

The script run_test.sh—or .bat, .py, or .pl—is run automatically if it is part of the recipe.

Note

Python .py and Perl .pl scripts are valid only as part of Python and Perl packages, respectively.

Check for file existence in the final package#

Boa comes with some helpers to check for commonly used files in the final package. These helpers are clever and adjust for things like shared-library extensions and installation prefixes automatically.

test:
  exists:
    # checks for the existence of files inside $PREFIX or %PREFIX%
    files:
      - etc/libmamba/test.txt
      - etc/libmamba

    # checks for the existence of `mamba/api/__init__.py` inside of the
    # Python site-packages directory (note: also see Python import checks)
    site_packages:
      - mamba.api

    # checks that there is at least one file matching the specified `glob`
    # pattern inside the prefix
    glob:
      - etc/libmamba/*.mamba.txt

    # looks in $PREFIX/bin/mamba for unix and %PREFIX%\Library\bin\mamba.exe on Windows
    # note: also check the `commands` and execute something like `mamba --help` to make
    # sure things work fine
    bin:
      - mamba

    # searches for `$PREFIX/lib/libmamba.so` or `$PREFIX/lib/libmamba.dylib` on Linux or macOS,
    # on Windows for %PREFIX%\Library\lib\mamba.dll & %PREFIX%\Library\bin\mamba.bin
    lib:
      - mamba

    # searches for `$PREFIX/include/libmamba/mamba.hpp` on unix, and
    # on Windows for `%PREFIX%\Library\include\mamba.hpp`
    include:
      - libmamba/mamba.hpp

    # executes cmake `find_package(libmamba REQUIRED)` and checks that it works
    cmake_find:
      - libmamba

    # executes `pkg-config --exists libmamba` and `pkg-config --validate libmamba`
    pkg_config:
      - libmamba

Outputs section#

Explicitly specifies packaging steps. This section supports multiple outputs, as well as different package output types. The format is a list of mappings. Build strings for subpackages are determined by their runtime dependencies.

outputs:
  - package:
      name: some-subpackage
      version: 1.0
  - package:
      name: some-other-subpackage
      version: 2.0

Scripts that create or move files into the build prefix can be any kind of script. Known script types need only specify the script name. Currently the list of recognized extensions is py, bat, ps1, and sh.

outputs:
  - name: subpackage-name
    build:
      script: install-subpackage.sh

For scripts that move or create files, a fresh copy of the working directory is provided at the start of each script execution. This ensures that results between scripts are independent of one another. You should take care of not packaging the same files twice.

Subpackage requirements#

Like a top-level recipe, a subpackage may have zero or more dependencies listed as build, host or run requirements.

The dependencies listed as subpackage build requirements are available only during the packaging phase of that subpackage.

A subpackage does not automatically inherit any dependencies from its top-level recipe, so any build or run requirements needed by the subpackage must be explicitly specified.

outputs:
  - package:
      name: subpackage-name
    requirements:
      build:
        - some-dep
      run:
        - some-dep

You can also impose runtime dependencies whenever a given (sub)package is installed as a build dependency. For example, if we had an overarching “compilers” package, and within that, had gcc and libgcc outputs, we could force recipes that use GCC to include a matching libgcc runtime requirement:

outputs:
  - package:
      name: gcc
    build:
      run_exports:
        - libgcc 2.*
  - package:
      name: libgcc

See the run_exports section for additional information.

Subpackage tests#

You can test subpackages independently of the top-level package. Independent test script files for each separate package are specified under the subpackage’s test section. These files support the same formats as the top-level run_test.* scripts, which are .py, .pl, .bat, and .sh. These may be extended to support other script types in the future.

outputs:
  - package:
      name: subpackage-name
    test:
      script: some-other-script.py

By default, the run_test.* scripts apply only to the top-level package. To apply them also to subpackages, list them explicitly in the script section:

outputs:
  - package:
      name: subpackage-name
    test:
      script: run_test.py

Test requirements for subpackages are not supported. Instead, subpackage tests install their runtime requirements—but not the run requirements for the top-level package—and the test-time requirements of the top-level package.

EXAMPLE: In this example, the test for subpackage-name installs some-test-dep and subpackage-run-req, but not some-top-level-run-req.

requirements:
  run:
    - some-top-level-run-req

test:
  requires:
    - some-test-dep

outputs:
  - name: subpackage-name
    requirements:
      run:
        - subpackage-run-req
    test:
      script: run_test.py

About section#

Specifies identifying information about the package. The information displays in the package server.

about:
  home: https://github.com/ilanschnell/bsdiff4
  license: BSD
  license_file: LICENSE
  summary: binary diff and patch using the BSDIFF4-format

License file#

Add a file containing the software license to the package metadata. Many licenses require the license statement to be distributed with the package. The filename is relative to the source or recipe directory. The value can be a single filename or a YAML list for multiple license files. Values can also point to directories with license information. Directory entries must end with a / suffix (this is to lessen unintentional inclusion of non-license files; all of the directory’s contents will be unconditionally and recursively added).

about:
  license_file:
    - LICENSE
    - vendor-licenses/

Extra section#

A schema-free area for storing non-conda-specific metadata in standard YAML form.

EXAMPLE: To store recipe maintainer information:

extra:
  maintainers:
   - name of maintainer

Templating with Jinja#

Boa supports simple Jinja templating in the meta.yaml file.

You can set up Jinja variables in the context yaml section:

context:
  name: "test"
  version: "5.1.2"
  major_version: "{{ version.split('.')[0] }}"

Later in your recipe.yaml you can use these values in string interpolation with Jinja. For example:

source:
  url: https://github.com/mamba-org/{{ name }}/v{{ version }}.tar.gz

Jinja has built-in support for some common string manipulations.

In boa, complex Jinja is completely disallowed as we try to produce YAML that is valid at all times. So you should not use any {% if ... %} or similar Jinja constructs that produce invalid yaml. Furthermore, quotes need to be applied when starting a value with double-curly brackets like so:

package:
  name: {{ name }}   # WRONG: invalid yaml
  name: "{{ name }}" # correct

For more information, see the Jinja2 template documentation and the list of available environment variables <env-vars>.

Jinja templates are evaluated during the build process. To retrieve a fully rendered recipe.yaml, use the commands/boa-render command.

Additional Jinja2 functionality in Boa#

Besides the default Jinja2 functionality, additional Jinja functions are available during the conda-build process: pin_compatible, pin_subpackage, and compiler.

The compiler function takes c, cxx, fortran and other values as argument and automatically selects the right (cross-)compiler for the target platform.

build:
  - "{{ compiler('c') }}"

The pin_subpackage function pins another package produced by the recipe with the supplied parameters.

Similarly, the pin_compatible function will pin a package according to the specified rules.

Preprocessing selectors#

You can add selectors to any item, and the selector is evaluated in a preprocessing stage. If a selector evaluates to true, the item is flattened into the parent element. If a selector evaluates to false, the item is removed.

source:
  - sel(not win):
      url: http://path/to/unix/source
  - sel(win):
      url: http://path/to/windows/source

A selector is a valid Python statement that is executed. The following variables are defined. Unless otherwise stated, the variables are booleans.

The use of the Python version selectors, py27, py34, etc. is discouraged in favor of the more general comparison operators. Additional selectors in this series will not be added to conda-build.

Because the selector is any valid Python expression, complicated logic is possible:

source:
  - sel(win):
      url: http://path/to/windows/source
  - sel(unix and py2k):
      url: http://path/to/python2/unix/source
  - sel(unix and py>=35):
      url: http://path/to/python3/unix/source

Lists are automatically “merged” upwards, so it is possible to group multiple items under a single selector:

test:
  commands:
    - sel(unix):
      - test -d ${PREFIX}/include/xtensor
      - test -f ${PREFIX}/include/xtensor/xarray.hpp
      - test -f ${PREFIX}/lib/cmake/xtensor/xtensorConfig.cmake
      - test -f ${PREFIX}/lib/cmake/xtensor/xtensorConfigVersion.cmake
    - sel(win):
      - if not exist %LIBRARY_PREFIX%\include\xtensor\xarray.hpp (exit 1)
      - if not exist %LIBRARY_PREFIX%\lib\cmake\xtensor\xtensorConfig.cmake (exit 1)
      - if not exist %LIBRARY_PREFIX%\lib\cmake\xtensor\xtensorConfigVersion.cmake (exit 1)

# On unix this is rendered to:
test:
  commands:
    - test -d ${PREFIX}/include/xtensor
    ...

Experimental features#

Build time features#

Warning

This is an experimental feature of boa and may change or go away completely

With boa, you can add “build-time” features. That makes building packages from source much more flexible and powerful and is a first step to enable a true “source”-distribution on top of conda packages.

name: libarchive

...

features:
  - name: zlib
    default: true
    requirements:
      host:
        - zlib
      run:
        - zlib

  - name: bzip2
    default: true
    requirements:
      host:
        - bzip2
      run:
        - bzip2

This adds two “features” to the boa recipe. These features can be enabled / disabled when invoking boa:

boa build . --features [zlib, ~bzip2]

This would compile libarchive with the zlib compression mechanism enabled, and bzip2 disabled. If a feature is not specified, the default value is used. A feature can add additional requirements to the build/host/run section, and adds some environment variables to the build script invokation. In our example, the FEATURE_ZLIB environment variable will be set to 1. This information can be used in the build script to enable or disable configuration and compilation flags.

For this libarchive recipe, the ./configure call might look like this:

${SRC_DIR}/configure --prefix=${PREFIX}                                           \
                     $(feature $FEATURE_ZLIB --with-zlib --without-zlib)          \
                     $(feature $FEATURE_BZIP2 --with-bz2lib --without-bz2lib) ...

In this case we’re using a special shell function feature to select between the enabled and disabled flag (similar to a ternary operator). The feature shell function is automatically added by boa into the shell environment.

One could similary use bash if / else to set flags based on the $FEATURE_... variable.

If you want to depend on packages and require a specific set of features, you can use the following syntax:

requirements:
  host:
    - libarchive [static, zlib, bzip2]

Sometimes you might want to depend on the static build only if the package we are compiling is also compiled as a static package. In that case, you can use the & modifier:

package:
  name:
  - libarchive

requirements:
  host:
    - bzip2 [&static]
    # - bzip2 1.2.3 [&static] is also valid

features:
  - name: static
    default: false

Now, by default building libarchive will use the dynamic build of bzip2. When building libarchive --features="[static]" boa will instead use the bzip2-static package as requirement.

How we think features will work#

Features work by requiring a special build string. When compiling with features, the build string will be composed of all features and the build hash. For example, the following active features [zlib, bzip2] will be first alphabetically sorted and then concatenated to a build string of the form +bzip2+zlib_h123123_0. A deactivated feature will be prefixed with a -. To match packages against required build time features boa will compose a regex-based match string. E.g. when asking for at least [bzip2], boa will use a build string of the form +bzip2*.

documentation

The boa recipe spec

Contents

The boa recipe spec#

History#

Spec#

Major differences with conda-build#

Spec reference#

Quick start (from conda-build)#

Examples#

Package section#

Source section#

Source from tarball or zip archive#

Source from git#

Source from hg#

Source from svn#

Source from a local path#

Patches#

Destination path#

Source from multiple sources#

Build section#

Build number and string#

Python entry points#

Script#

Skipping builds#

Architecture independent packages#

Include build recipe#

Requirements section#

Build#

Host#

Run#

Run_constrained#

Test section#

Test files#

Source files#

Test requirements#

Test commands#

Python imports#

Run test script#

Check for file existence in the final package#

Outputs section#

Subpackage requirements#

Subpackage tests#

About section#

License file#

Extra section#

Templating with Jinja#

Additional Jinja2 functionality in Boa#

Preprocessing selectors#

Experimental features#

Build time features#

How we think features will work#