Pigweed’s modules aim to be easily integratable into both new and existing embedded projects. To that goal, the pw_build module provides support for multiple build systems. Our personal favorite is GN/Ninja, which is used by upstream developers for its speed and flexibility. CMake and Bazel build files are also provided by all modules, allowing Pigweed to be added to a project with minimal effort.

Beyond just compiling code, Pigweed’s GN build system can also:

  • Generate HTML documentation, via our Sphinx integration (with pw_docgen)

  • Display memory usage report cards (with pw_bloat)

  • Incrementally run unit tests after code changes (with pw_target_runner)

  • And more!

These are only supported in the GN build, so we recommend using it if possible.

GN / Ninja

The GN / Ninja build system is the primary build system used for upstream Pigweed development, and is the most tested and feature-rich build system Pigweed offers.

This module’s file contains a number of C/C++ config declarations that are used by upstream Pigweed to set some architecture-agnostic compiler defaults. (See Pigweed’s //

pw_build also provides several useful GN templates that are used throughout Pigweed.

Target types


pw_source_set("my_library") {
  sources = [ "" ]

Pigweed defines wrappers around the four basic GN binary types source_set, executable, static_library, and shared_library. These wrappers apply default arguments to each target as specified in the default_configs and default_public_deps build args. Additionally, they allow defaults to be removed on a per-target basis using remove_configs and remove_public_deps variables, respectively.

The pw_executable template provides additional functionality around building complete binaries. As Pigweed is a collection of libraries, it does not know how its final targets are built. pw_executable solves this by letting each user of Pigweed specify a global executable template for their target, and have Pigweed build against it. This is controlled by the build variable pw_executable_config.target_type, specifying the name of the executable template for a project.


Prefer to use pw_executable over plain executable targets to allow cleanly building the same code for multiple target configs.


All of the pw_* target type overrides accept any arguments, as they simply forward them through to the underlying target.

Python packages

GN templates for Python build automation are described in Python GN templates.


In their simplest form, a facade is a GN build arg used to change a dependency at compile time. Pigweed targets configure these facades as needed.

The pw_facade template bundles a pw_source_set with a facade build arg. This allows the facade to provide header files, compilation options or anything else a GN source_set provides.

The pw_facade template declares two targets:

  • $target_name: the public-facing pw_source_set, with a public_dep on the backend

  • $target_name.facade: target used by the backend to avoid circular dependencies

# Declares ":foo" and ":foo.facade" GN targets
pw_facade("foo") {
  backend = pw_log_BACKEND
  public_configs = [ ":public_include_path" ]
  public = [ "public/pw_foo/foo.h" ]

Low-level facades like pw_assert cannot express all of their dependencies due to the potential for dependency cycles. Facades with this issue may require backends to place their implementations in a separate build target to be listed in pw_build_LINK_DEPS (see Link-only deps). The require_link_deps variable in pw_facade asserts that all specified build targets are present in pw_build_LINK_DEPS if the facade’s backend variable is set.


The pw_python_action template is a convenience wrapper around action for running Python scripts. The main benefit it provides is resolution of GN target labels to compiled binary files. This allows Python scripts to be written independently of GN, taking only filesystem paths as arguments.

Another convenience provided by the template is to allow running scripts without any outputs. Sometimes scripts run in a build do not directly produce output files, but GN requires that all actions have an output. pw_python_action solves this by accepting a boolean stamp argument which tells it to create a dummy output file for the action.


pw_python_action accepts all of the arguments of a regular action target. Additionally, it has some of its own arguments:

  • module: Run the specified Python module instead of a script. Either script or module must be specified, but not both.

  • capture_output: Optional boolean. If true, script output is hidden unless the script fails with an error. Defaults to true.

  • stamp: Optional variable indicating whether to automatically create a dummy output file for the script. This allows running scripts without specifying outputs. If stamp is true, a generic output file is used. If stamp is a file path, that file is used as a stamp file. Like any output file, stamp must be in the build directory. Defaults to false.

  • directory: Optional path. Change to this directory before executing the command. Paths in arguments may need to be adjusted.

  • environment: Optional list of strings. Environment variables to set, passed as NAME=VALUE strings.


pw_python_action evaluates expressions in args, the arguments passed to the script. These expressions function similarly to generator expressions in CMake. Expressions may be passed as a standalone argument or as part of another argument. A single argument may contain multiple expressions.

Generally, these expressions are used within templates rather than directly in files. This allows build code to use GN labels without having to worry about converting them to files.


We intend to replace these expressions with native GN features when possible. See pwbug/347.

The following expressions are supported:


Evaluates to the output file of the provided GN target. For example, the expression


might expand to


TARGET_FILE parses the .ninja file for the GN target, so it should always find the correct output file, regardless of the toolchain’s or target’s configuration. Some targets, such as source_set and group targets, do not have an output file, and attempting to use TARGET_FILE with them results in an error.

TARGET_FILE only resolves GN target labels to their outputs. To resolve paths generally, use the standard GN approach of applying the rebase_path(path) function. With default arguments, rebase_path converts the provided GN path or list of paths to be relative to the build directory, from which all build commands and scripts are executed.


TARGET_FILE_IF_EXISTS evaluates to the output file of the provided GN target, if the output file exists. If the output file does not exist, the entire argument that includes this expression is omitted, even if there is other text or another expression.

For example, consider this expression:


If the //alpha/bravo target file exists, this might expand to the following:


If the //alpha/bravo target file does not exist, the entire --database= argument is omitted from the script arguments.


Evaluates to the object files of the provided GN target. Expands to a separate argument for each object file. If the target has no object files, the argument is omitted entirely. Because it does not expand to a single expression, the <TARGET_OBJECTS(...)> expression may not have leading or trailing text.

For example, the expression


might expand to multiple separate arguments:




pw_python_action("postprocess_main_image") {
  script = "py/"
  args = [
  stamp = true


pw_input_group defines a group of input files which are not directly processed by the build but are still important dependencies of later build steps. This is commonly used alongside metadata to propagate file dependencies through the build graph and force rebuilds on file modifications.

For example pw_docgen defines a pw_doc_group template which outputs metadata from a list of input files. The metadata file is not actually part of the build, and so changes to any of the input files do not trigger a rebuild. This is problematic, as targets that depend on the metadata should rebuild when the inputs are modified but GN cannot express this dependency.

pw_input_group solves this problem by allowing a list of files to be listed in a target that does not output any build artifacts, causing all dependent targets to correctly rebuild.


pw_input_group accepts all arguments that can be passed to a group target, as well as requiring one extra:

  • inputs: List of input files.



pw_input_group("foo_metadata") {
  metadata = {
    files = [
  inputs = metadata.files

Targets depending on foo_metadata will rebuild when any of the .foo files are modified.


pw_zip is a target that allows users to zip up a set of input files and directories into a single output .zip file—a simple automation of a potentially repetitive task.


  • inputs: List of source files as well as the desired relative zip destination. See below for the input syntax.

  • dirs: List of entire directories to be zipped as well as the desired relative zip destination. See below for the input syntax.

  • output: Filename of output .zip file.

  • deps: List of dependencies for the target.

Input Syntax

Inputs all need to follow the correct syntax:

  1. Path to source file or directory. Directories must end with a /.

  2. The delimiter (defaults to >).

  3. The desired destination of the contents within the .zip. Must start with / to indicate the zip root. Any number of subdirectories are allowed. If the source is a file it can be put into any subdirectory of the root. If the source is a file, the zip copy can also be renamed by ending the zip destination with a filename (no trailing /).

Thus, it should look like the following: "[source file or dir] > /".


Let’s say we have the following structure for a //source/ directory:

├── file1.txt
├── file2.txt
├── file3.txt
└── some_dir/
    ├── file4.txt
    └── some_other_dir/
        └── file5.txt

And we create the following build target:


pw_zip("target_name") {
  inputs = [
    "//source/file1.txt > /",             # Copied to the zip root dir.
    "//source/file2.txt > /renamed.txt",  # File renamed.
    "//source/file3.txt > /bar/",         # File moved to the /bar/ dir.

  dirs = [
    "//source/some_dir/ > /bar/some_dir/",  # All /some_dir/ contents copied
                                            # as /bar/some_dir/.

  # Note on output: if the specific output directory isn't defined
  # (such as output = "") then the .zip will output to the
  # same directory as the file that called the target.
  output = "//$target_out_dir/"  # Where the will end up

This will result in a .zip file called stored in //$target_out_dir with the following structure:
├── bar/
│   ├── file3.txt
│   └── some_dir/
│       ├── file4.txt
│       └── some_other_dir/
│           └── file5.txt
├── file1.txt
└── renamed.txt

CMake / Ninja

Pigweed’s CMake support is provided primarily for projects that have an existing CMake build and wish to integrate Pigweed without switching to a new build system.

The following command generates Ninja build files for a host build in the out/cmake_host directory:

cmake -B out/cmake_host -S "$PW_ROOT" -G Ninja -DCMAKE_TOOLCHAIN_FILE=$PW_ROOT/pw_toolchain/host_clang/toolchain.cmake

The PW_ROOT environment variable must point to the root of the Pigweed directory. This variable is set by Pigweed’s environment setup.

Tests can be executed with the pw_run_tests.GROUP targets. To run Pigweed module tests, execute pw_run_tests.modules:

ninja -C out/cmake_host pw_run_tests.modules

pw_watch supports CMake, so you can also run

pw watch -C out/cmake_host pw_run_tests.modules

CMake functions

CMake convenience functions are defined in pw_build/pigweed.cmake.

  • pw_auto_add_simple_module – For modules with only one library, automatically declare the library and its tests.

  • pw_auto_add_module_tests – Create test targets for all tests in a module.

  • pw_add_facade – Declare a module facade.

  • pw_set_backend – Set the backend library to use for a facade.

  • pw_add_module_library – Add a library that is part of a module.

  • pw_add_test – Declare a test target.

See pw_build/pigweed.cmake for the complete documentation of these functions.

Special libraries that do not fit well with these functions are created with the standard CMake functions, such as add_library and target_link_libraries.

Facades and backends

The CMake build uses CMake cache variables for configuring facades and backends. Cache variables are similar to GN’s build args set with gn args. Unlike GN, CMake does not support multi-toolchain builds, so these variables have a single global value per build directory.

The pw_add_facade function declares a cache variable named <module_name>_BACKEND for each facade. Cache variables can be awkward to work with, since their values only change when they’re assigned, but then persist accross CMake invocations. These variables should be set in one of the following ways:

  • Call pw_set_backend to set backends appropriate for the target in the target’s toolchain file. The toolchain file is provided to cmake with -DCMAKE_TOOLCHAIN_FILE=<toolchain file>.

  • Call pw_set_backend in the top-level CMakeLists.txt before other CMake code executes.

  • Set the backend variable at the command line with the -D option.

    cmake -B out/cmake_host -S "$PW_ROOT" -G Ninja \
        -DCMAKE_TOOLCHAIN_FILE=$PW_ROOT/pw_toolchain/host_clang/toolchain.cmake \
  • Temporarily override a backend by setting it interactively with ccmake or cmake-gui.

Toolchain setup

In CMake, the toolchain is configured by setting CMake variables, as described in the CMake documentation. These variables are typically set in a toolchain CMake file passed to cmake with the -D option (-DCMAKE_TOOLCHAIN_FILE=path/to/file.cmake). For Pigweed embedded builds, set CMAKE_SYSTEM_NAME to the empty string ("").

Third party libraries

The CMake build includes third-party libraries similarly to the GN build. A dir_pw_third_party_<library> cache variable is defined for each third-party dependency. The variable must be set to the absolute path of the library in order to use it. If the variable is empty (if("${dir_pw_third_party_<library>}" STREQUAL "")), the dependency is not available.

Third-party dependencies are not automatically added to the build. They can be manually added with add_subdirectory or by setting the pw_third_party_<library>_ADD_SUBDIRECTORY option to ON.

Third party variables are set like any other cache global variable in CMake. It is recommended to set these in one of the following ways:

  • Set with the CMake set function in the toolchain file or a CMakeLists.txt before other CMake code executes.

    set(dir_pw_third_party_nanopb ${CMAKE_CURRENT_SOURCE_DIR}/external/nanopb CACHE PATH "" FORCE)
  • Set the variable at the command line with the -D option.

    cmake -B out/cmake_host -S "$PW_ROOT" -G Ninja \
        -DCMAKE_TOOLCHAIN_FILE=$PW_ROOT/pw_toolchain/host_clang/toolchain.cmake \
  • Set the variable interactively with ccmake or cmake-gui.

Use Pigweed from an existing CMake project

To use Pigweed libraries form a CMake-based project, simply include the Pigweed repository from a CMakeLists.txt.

add_subdirectory(path/to/pigweed pigweed)

All module libraries will be available as module_name or module_name.sublibrary.

If desired, modules can be included individually.

add_subdirectory(path/to/pigweed/pw_some_module pw_some_module)
add_subdirectory(path/to/pigweed/pw_another_module pw_another_module)


Bazel is currently very experimental, and only builds for host and ARM Cortex-M microcontrollers.

The common configuration for Bazel for all modules is in the pigweed.bzl file. The built-in Bazel rules cc_binary, cc_library, and cc_test are wrapped with pw_cc_binary, pw_cc_library, and pw_cc_test. These wrappers add parameters to calls to the compiler and linker.

Currently Pigweed is making use of a set of [open source]( toolchains. The host builds are only supported on Linux/Mac based systems. Additionally the host builds are not entirely hermetic, and will make use of system libraries and headers. This is close to the default configuration for Bazel, though slightly more hermetic. The host toolchain is based around clang-11 which has a system dependency on ‘’ which is often included as part of the libncurses packages. On Debian based systems this can be installed using the command below:

sudo apt install libncurses5

The host toolchain does not currently support native Windows, though using WSL is a viable alternative.

The ARM Cortex-M Bazel toolchains are based around gcc-arm-non-eabi and are entirely hermetic. You can target Cortex-M, by using the platforms command line option. This set of toolchains is supported from hosts; Windows, Mac and Linux. The platforms that are currently supported are listed below:

bazel build //:your_target --platforms=@pigweed//pw_build/platforms:cortex_m0
bazel build //:your_target --platforms=@pigweed//pw_build/platforms:cortex_m1
bazel build //:your_target --platforms=@pigweed//pw_build/platforms:cortex_m3
bazel build //:your_target --platforms=@pigweed//pw_build/platforms:cortex_m4
bazel build //:your_target --platforms=@pigweed//pw_build/platforms:cortex_m7
bazel build //:your_target \
bazel build //:your_target \

The above examples are cpu/fpu oriented platforms and can be used where applicable for your application. There some more specific platforms for the types of boards that are included as examples in Pigweed. It is strongly encouraged that you create your own set of platforms specific for your project, that implement the constraint_settings in this repository. e.g.

New board constraint_value:

  name = "nucleo_l432kc",
  constraint_setting = "@pigweed//pw_build/constraints/board",

New chipset constraint_value:

# your_repo/build_settings/constraints/chipset/BUILD
  name = "stm32l432kc",
  constraint_setting = "@pigweed//pw_build/constraints/chipset",

New platforms for chipset and board:

# Works with all stm32l432kc
  name = "stm32l432kc",
  parents = ["@pigweed//pw_build/platforms:cortex_m4"],
  constraint_values =

# Works with only the nucleo_l432kc
  name = "nucleo_l432kc",
  parents = [":stm32l432kc"],
  constraint_values =

In the above example you can build your code with the command line:

bazel build //:your_target_for_nucleo_l432kc \

You can also specify that a specific target is only compatible with one platform:

  name = "compatible_with_all_stm32l432kc",
  srcs = ["tomato_src.c"],
  target_compatible_with =

  name = "compatible_with_only_nucleo_l432kc",
  srcs = ["bbq_src.c"],
  target_compatible_with =