pw_build

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 build.gn 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 //BUILDCONFIG.gn)

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

Build system philosophies

While Pigweed’s GN build is not hermetic, it strives to adhere to principles of hermeticity. Some guidelines to move towards the ideal of hermeticity include:

• Only rely on pre-compiled tools provided by CIPD (or some other versioned, pre-compiled binary distribution mechanism). This eliminates build artifact differences caused by different tool versions or variations (e.g. same tool version built with slightly different compilation flags).

• Do not use absolute paths in Ninja commands. Typically, these appear when using rebase_path("//path/to/my_script.py"). Most of the time, Ninja steps should be passed paths rebased relative to the build directory (i.e. rebase_path("//path/to/my_script.py", root_build_dir)). This ensures build commands are the same across different machines.

• Prevent produced artifacts from relying on or referencing system state. This includes time stamps, writing absolute paths to generated artifacts, or producing artifacts that reference system state in a way that prevents them from working the same way on a different machine.

• Isolate build actions to the build directory. In general, the build system should not add or modify files outside of the build directory. This can cause confusion to users, and makes the concept of a clean build more ambiguous.

Target types

import("$dir_pw_build/target_types.gni")

pw_source_set("my_library") {
  sources = [ "lib.cc" ]
}

Pigweed defines wrappers around the four basic GN binary types source_set, executable, static_library, and shared_library. These templates do several things:

1. Add default configs/deps

   Rather than binding the majority of compiler flags related to C++ standard, cross-compilation, warning/error policy, etc. directly to toolchain invocations, these flags are applied as configs to all pw_* C/C++ target types. The primary motivations for this are to allow some targets to modify the default set of flags when needed by specifying remove_configs, and to reduce the complexity of building novel toolchains.

   Pigweed’s global default configs are set in pw_build/default.gni, and individual platform-specific toolchains extend the list by appending to the default_configs build argument.

   Default deps were added to support polyfill, which has since been deprecated. Default dependency functionality continues to exist for backwards compatibility.

2. Optionally add link-time binding

   Some libraries like pw_assert and pw_log are borderline impossible to implement well without introducing circular dependencies. One solution for addressing this is to break apart the libraries into an interface with minimal dependencies, and an implementation with the bulk of the dependencies that would typically create dependency cycles. In order for the implementation to be linked in, it must be added to the dependency tree of linked artifacts (e.g. pw_executable, pw_static_library). Since there’s no way for the libraries themselves to just happily pull in the implementation if someone depends on the interface, the implementation is instead late-bound by adding it as a direct dependency of the final linked artifact. This is all managed through pw_build_LINK_DEPS, which is global for each toolchain and applied to every pw_executable, pw_static_library, and pw_shared_library.

3. Apply a default visibility policy

   Projects can globally control the default visibility of pw_* target types by specifying pw_build_DEFAULT_VISIBILITY. This template applies that as the default visibility for any pw_* targets that do not explicitly specify a visibility.

4. Add source file names as metadata

   All source file names are collected as GN metadata. This list can be writen to a file at build time using generated_file. The primary use case for this is to generate a token database containing all the source files. This allows PW_ASSERT to emit filename tokens even though it can’t add them to the elf file because of the reasons described at Assert API.

   Note

   pw_source_files, if not rebased will default to outputing module relative paths from a generated_file target. This is likely not useful. Adding a rebase argument to generated_file such as rebase = root_build_dir will result in usable paths. For an example, see //pw_tokenizer/database.gni’s pw_tokenizer_filename_database template.

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.

In some uncommon cases, a project’s pw_executable template definition may need to stamp out some pw_source_sets. Since a pw_executable template can’t import $dir_pw_build/target_types.gni due to circular imports, it should import $dir_pw_build/cc_library.gni instead.

Tip

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

Arguments

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

Additionally, the following arguments are also supported:

• remove_configs: (optional) A list of configs / config patterns to remove from the set of default configs specified by the current toolchain configuration.

• remove_public_deps: (optional) A list of targets to remove from the set of default public_deps specified by the current toolchain configuration.

Link-only deps

It may be necessary to specify additional link-time dependencies that may not be explicitly depended on elsewhere in the build. One example of this is a pw_assert backend, which may need to leave out dependencies to avoid circular dependencies. Its dependencies need to be linked for executables and libraries, even if they aren’t pulled in elsewhere.

The pw_build_LINK_DEPS build arg is a list of dependencies to add to all pw_executable, pw_static_library, and pw_shared_library targets. This should only be used as a last resort when dependencies cannot be properly expressed in the build.

Python packages

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

pw_cc_blob_library

The pw_cc_blob_library template is useful for embedding binary data into a program. The template takes in a mapping of symbol names to file paths, and generates a set of C++ source and header files that embed the contents of the passed-in files as arrays of std::byte.

The blob byte arrays are constant initialized and are safe to access at any time, including before main().

pw_cc_blob_library is also available in the CMake build. It is provided by pw_build/cc_blob_library.cmake.

Arguments

• blobs: A list of GN scopes, where each scope corresponds to a binary blob to be transformed from file to byte array. This is a required field. Blob fields include:

  • symbol_name: The C++ symbol for the byte array.

  • file_path: The file path for the binary blob.

  • linker_section: If present, places the byte array in the specified linker section.

  • alignas: If present, uses the specified string or integer verbatim in the alignas() specifier for the byte array.

• out_header: The header file to generate. Users will include this file exactly as it is written here to reference the byte arrays.

• namespace: An optional (but highly recommended!) C++ namespace to place the generated blobs within.

Example

BUILD.gn

pw_cc_blob_library("foo_bar_blobs") {
  blobs: [
    {
      symbol_name: "kFooBlob"
      file_path: "${target_out_dir}/stuff/bin/foo.bin"
    },
    {
      symbol_name: "kBarBlob"
      file_path: "//stuff/bin/bar.bin"
      linker_section: ".bar_section"
    },
  ]
  out_header: "my/stuff/foo_bar_blobs.h"
  namespace: "my::stuff"
  deps = [ ":generate_foo_bin" ]
}

Note

If the binary blobs are generated as part of the build, be sure to list them as deps to the pw_cc_blob_library target.

Generated Header

#pragma once

#include <array>
#include <cstddef>

namespace my::stuff {

extern const std::array<std::byte, 100> kFooBlob;

extern const std::array<std::byte, 50> kBarBlob;

}  // namespace my::stuff

Generated Source

#include "my/stuff/foo_bar_blobs.h"

#include <array>
#include <cstddef>

#include "pw_preprocessor/compiler.h"

namespace my::stuff {

const std::array<std::byte, 100> kFooBlob = { ... };

PW_PLACE_IN_SECTION(".bar_section")
const std::array<std::byte, 50> kBarBlob = { ... };

}  // namespace my::stuff

pw_facade

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.

pw_python_action

The pw_python_action template is a convenience wrapper around GN’s action function 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 placeholder output file for the action.

Arguments

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 placeholder 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.

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

• working_directory: Optional file path. When provided the current working directory will be set to this location before the Python module or script is run.

• command_launcher: Optional string. Arguments to prepend to the Python command, e.g. '/usr/bin/fakeroot --' will run the Python script within a fakeroot environment.

• venv: Optional gn target of the pw_python_venv that should be used to run this action.

Expressions

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 BUILD.gn files. This allows build code to use GN labels without having to worry about converting them to files.

Note

We intend to replace these expressions with native GN features when possible. See b/234886742.

The following expressions are supported:

<TARGET_FILE(gn_target)>

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

"<TARGET_FILE(//foo/bar:static_lib)>"

might expand to

"/home/User/project_root/out/obj/foo/bar/static_lib.a"

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, root_build_dir) function. This function 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(gn_target)>

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:

"--database=<TARGET_FILE_IF_EXISTS(//alpha/bravo)>"

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

"--database=/home/User/project/out/obj/alpha/bravo/bravo.elf"

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

<TARGET_OBJECTS(gn_target)>

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

"<TARGET_OBJECTS(//foo/bar:a_source_set)>"

might expand to multiple separate arguments:

"/home/User/project_root/out/obj/foo/bar/a_source_set.file_a.cc.o"
"/home/User/project_root/out/obj/foo/bar/a_source_set.file_b.cc.o"
"/home/User/project_root/out/obj/foo/bar/a_source_set.file_c.cc.o"

Example

import("$dir_pw_build/python_action.gni")

pw_python_action("postprocess_main_image") {
  script = "py/postprocess_binary.py"
  args = [
    "--database",
    rebase_path("my/database.csv", root_build_dir),
    "--binary=<TARGET_FILE(//firmware/images:main)>",
  ]
  stamp = true
}

pw_evaluate_path_expressions

It is not always feasible to pass information to a script through command line arguments. If a script requires a large amount of input data, writing to a file is often more convenient. However, doing so bypasses pw_python_action’s GN target label resolution, preventing such scripts from working with build artifacts in a build system-agnostic manner.

pw_evaluate_path_expressions is designed to address this use case. It takes a list of input files and resolves target expressions within them, modifying the files in-place.

Refer to pw_python_action’s Expressions section for the list of supported expressions.

Note

pw_evaluate_path_expressions is typically used as an intermediate sub-target of a larger template, rather than a standalone build target.

Arguments

• files: A list of scopes, each containing a source file to process and a dest file to which to write the result.

Example

The following template defines an executable target which additionally outputs the list of object files from which it was compiled, making use of pw_evaluate_path_expressions to resolve their paths.

import("$dir_pw_build/evaluate_path_expressions.gni")

template("executable_with_artifacts") {
  executable("${target_name}.exe") {
    sources = invoker.sources
    if defined(invoker.deps) {
      deps = invoker.deps
    }
  }

  _artifacts_input = "$target_gen_dir/${target_name}_artifacts.json.in"
  _artifacts_output = "$target_gen_dir/${target_name}_artifacts.json"
  _artifacts = {
    binary = "<TARGET_FILE(:${target_name}.exe)>"
    objects = "<TARGET_OBJECTS(:${target_name}.exe)>"
  }
  write_file(_artifacts_input, _artifacts, "json")

  pw_evaluate_path_expressions("${target_name}.evaluate") {
    files = [
      {
        source = _artifacts_input
        dest = _artifacts_output
      },
    ]
  }

  group(target_name) {
    deps = [
      ":${target_name}.exe",
      ":${target_name}.evaluate",
    ]
  }
}

pw_exec

pw_exec allows for execution of arbitrary programs. It is a wrapper around pw_python_action but allows for specifying the program to execute.

Note

Prefer to use pw_python_action instead of calling out to shell scripts, as the Python will be more portable. pw_exec should generally only be used for interacting with legacy/existing scripts.

Arguments

• program: The program to run. Can be a full path or just a name (in which case $PATH is searched).

• args: Optional list of arguments to the program.

• deps: Dependencies for this target.

• public_deps: Public dependencies for this target. In addition to outputs from this target, outputs generated by public dependencies can be used as inputs from targets that depend on this one. This is not the case for private deps.

• inputs: Optional list of build inputs to the program.

• outputs: Optional list of artifacts produced by the program’s execution.

• env: Optional list of key-value pairs defining environment variables for the program.

• env_file: Optional path to a file containing a list of newline-separated key-value pairs defining environment variables for the program.

• args_file: Optional path to a file containing additional positional arguments to the program. Each line of the file is appended to the invocation. Useful for specifying arguments from GN metadata.

• skip_empty_args: If args_file is provided, boolean indicating whether to skip running the program if the file is empty. Used to avoid running commands which error when called without arguments.

• capture_output: If true, output from the program is hidden unless the program exits with an error. Defaults to true.

• working_directory: The working directory to execute the subprocess with. If not specified it will not be set and the subprocess will have whatever the parent current working directory is.

• venv: Python virtualenv to pass along to the underlying pw_python_action.

• visibility: GN visibility to apply to the underlying target.

Example

import("$dir_pw_build/exec.gni")

pw_exec("hello_world") {
  program = "/bin/sh"
  args = [
    "-c",
    "echo hello \$WORLD",
  ]
  env = [
    "WORLD=world",
  ]
}

pw_input_group

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.

Arguments

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.

Example

import("$dir_pw_build/input_group.gni")

pw_input_group("foo_metadata") {
  metadata = {
    files = [
      "x.foo",
      "y.foo",
      "z.foo",
    ]
  }
  inputs = metadata.files
}

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

pw_zip

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.

Arguments

• 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] > /".

Example

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

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

And we create the following build target:

import("$dir_pw_build/zip.gni")

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 = "zoo.zip") then the .zip will output to the
  # same directory as the BUILD.gn file that called the target.
  output = "//$target_out_dir/foo.zip"  # Where the foo.zip will end up
}

This will result in a .zip file called foo.zip stored in //$target_out_dir with the following structure:

foo.zip
├── bar/
│   ├── file3.txt
│   └── some_dir/
│       ├── file4.txt
│       └── some_other_dir/
│           └── file5.txt
├── file1.txt
└── renamed.txt

pw_relative_source_file_names

This template recursively walks the listed dependencies and collects the names of all the headers and source files required by the targets, and then transforms them such that they reflect the __FILE__ when pw_build’s relative_paths config is applied. This is primarily intended for side-band generation of pw_tokenizer tokens so file name tokens can be utilized in places where pw_tokenizer is unable to embed token information as part of C/C++ compilation.

This template produces a JSON file containing an array of strings (file paths with -ffile-prefix-map-like transformations applied) that can be used to generate a token database.

Arguments

• deps: A required list of targets to recursively extract file names from.

• outputs: A required array with a single element: the path to write the final JSON file to.

Example

Let’s say we have the following project structure:

project root
├── foo/
│   ├── foo.h
│   └── foo.cc
├── bar/
│   ├── bar.h
│   └── bar.cc
├── unused/
│   ├── unused.h
│   └── unused.cc
└── main.cc

And a BUILD.gn at the root:

pw_source_set("bar") {
  public_configs = [ ":bar_headers" ]
  public = [ "bar/bar.h" ]
  sources = [ "bar/bar.cc" ]
}

pw_source_set("foo") {
  public_configs = [ ":foo_headers" ]
  public = [ "foo/foo.h" ]
  sources = [ "foo/foo.cc" ]
  deps = [ ":bar" ]
}


pw_source_set("unused") {
  public_configs = [ ":unused_headers" ]
  public = [ "unused/unused.h" ]
  sources = [ "unused/unused.cc" ]
  deps = [ ":bar" ]
}

pw_executable("main") {
  sources = [ "main.cc" ]
  deps = [ ":foo" ]
}

pw_relative_source_file_names("main_source_files") {
  deps = [ ":main" ]
  outputs = [ "$target_gen_dir/main_source_files.json" ]
}

The json file written to out/gen/main_source_files.json will contain:

[
  "bar/bar.cc",
  "bar/bar.h",
  "foo/foo.cc",
  "foo/foo.h",
  "main.cc"
]

Since unused isn’t a transitive dependency of main, its source files are not included. Similarly, even though bar is not a direct dependency of main, its source files are included because foo brings in bar as a transitive dependency.

Note how the file paths in this example are relative to the project root rather than being absolute paths (e.g. /home/user/ralph/coding/my_proj/main.cc). This is a result of transformations applied to strip absolute pathing prefixes, matching the behavior of pw_build’s $dir_pw_build:relative_paths config.

Build time errors: pw_error and pw_build_assert

In Pigweed’s complex, multi-toolchain GN build it is not possible to build every target in every configuration. GN’s assert statement is not ideal for enforcing the correct configuration because it may prevent the GN build files or targets from being referred to at all, even if they aren’t used.

The pw_error GN template results in an error if it is executed during the build. These error targets can exist in the build graph, but cannot be depended on without an error.

pw_build_assert evaluates to a pw_error if a condition fails or nothing (an empty group) if the condition passes. Targets can add a dependency on a pw_build_assert to enforce a condition at build time.

The templates for build time errors are defined in pw_build/error.gni.

Improved Ninja interface

Ninja includes a basic progress display, showing in a single line the number of targets finished, the total number of targets, and the name of the most recent target it has either started or finished.

For additional insight into the status of the build, Pigweed includes a Ninja wrapper, pw-wrap-ninja, that displays additional real-time information about the progress of the build. The wrapper is invoked the same way you’d normally invoke Ninja:

pw-wrap-ninja -C out

The script lists the progress of the build, as well as the list of targets that Ninja is currently building, along with a timer that measures how long each target has been building for:

[51.3s] Building [8924/10690] ...
  [10.4s] c++ pw_strict_host_clang_debug/obj/pw_string/string_test.lib.string_test.cc.o
  [ 9.5s] ACTION //pw_console/py:py.lint.mypy(//pw_build/python_toolchain:python)
  [ 9.4s] ACTION //pw_console/py:py.lint.pylint(//pw_build/python_toolchain:python)
  [ 6.1s] clang-tidy ../pw_log_rpc/log_service.cc
  [ 6.1s] clang-tidy ../pw_log_rpc/log_service_test.cc
  [ 6.1s] clang-tidy ../pw_log_rpc/rpc_log_drain.cc
  [ 6.1s] clang-tidy ../pw_log_rpc/rpc_log_drain_test.cc
  [ 5.4s] c++ pw_strict_host_clang_debug/obj/BUILD_DIR/pw_strict_host_clang_debug/gen/pw...
  ... and 109 more

This allows you to, at a glance, know what Ninja’s currently building, which targets are bottlenecking the rest of the build, and which targets are taking an unusually long time to complete.

pw-wrap-ninja includes other useful functionality as well. The --write-trace option writes a build trace to the specified path, which can be viewed in the Perfetto UI, or via Chrome’s built-in chrome://tracing tool.

CMake

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_add_library_generic – The base helper used to instantiate CMake libraries. This is meant for use in downstream projects as upstream Pigweed modules are expected to use pw_add_library.

• pw_add_library – Add an upstream Pigweed library.

• pw_add_facade_generic – The base helper used to instantiate facade libraries. This is meant for use in downstream projects as upstream Pigweed modules are expected to use pw_add_facade.

• pw_add_facade – Declare an upstream Pigweed facade.

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

• pw_add_test_generic – The base helper used to instantiate test targets. This is meant for use in downstrema projects as upstream Pigweed modules are expected to use pw_add_test.

• pw_add_test – Declare an upstream Pigweed test target.

• pw_add_test_group – Declare a target to group and bundle test targets.

• pw_target_link_targets – Helper wrapper around target_link_libraries which only supports CMake targets and detects when the target does not exist. Note that generator expressions are not supported.

• pw_add_global_compile_options – Applies compilation options to all targets in the build. This should only be used to add essential compilation options, such as those that affect the ABI. Use pw_add_library or target_compile_options to apply other compile options.

• pw_add_error_target – Declares target which reports a message and causes a build failure only when compiled. This is useful when FATAL_ERROR messages cannot be used to catch problems during the CMake configuration phase.

• pw_parse_arguments – Helper to parse CMake function arguments.

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_module_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:

• Prior to setting a backend, your application should include $ENV{PW_ROOT}/backends.cmake. This file will setup all the backend targets such that any misspelling of a facade or backend will yield a warning.

  Note

  Zephyr developers do not need to do this, backends can be set automatically by enabling the appropriate Kconfig options.

• 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 \
      -Dpw_log_BACKEND=pw_log_basic
  

• Temporarily override a backend by setting it interactively with ccmake or cmake-gui.

If the backend is set to a build target that does not exist, there will be an error message like the following:

CMake Error at pw_build/pigweed.cmake:257 (message):
  my_module.my_facade's INTERFACE dep "my_nonexistent_backend" is not
  a target.
Call Stack (most recent call first):
  pw_build/pigweed.cmake:238:EVAL:1 (_pw_target_link_targets_deferred_check)
  CMakeLists.txt:DEFERRED

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 ("").

Toolchains may set the pw_build_WARNINGS variable to a list of INTERFACE libraries with compilation options for Pigweed’s upstream libraries. This defaults to a strict set of warnings. Projects may need to use less strict compilation warnings to compile backends exposed to Pigweed code (such as pw_log) that cannot compile with Pigweed’s flags. If desired, Projects can access these warnings by depending on pw_build.warnings.

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 \
      -Ddir_pw_third_party_nanopb=/path/to/nanopb
  

• 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

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.

In addition to wrapping the built-in rules, Pigweed also provides a custom rule for handling linker scripts with Bazel. e.g.

pw_linker_script(
  name = "some_linker_script",
  linker_script = ":some_configurable_linker_script.ld",
  defines = [
      "PW_BOOT_FLASH_BEGIN=0x08000200",
      "PW_BOOT_FLASH_SIZE=1024K",
      "PW_BOOT_HEAP_SIZE=112K",
      "PW_BOOT_MIN_STACK_SIZE=1K",
      "PW_BOOT_RAM_BEGIN=0x20000000",
      "PW_BOOT_RAM_SIZE=192K",
      "PW_BOOT_VECTOR_TABLE_BEGIN=0x08000000",
      "PW_BOOT_VECTOR_TABLE_SIZE=512",
  ],
)

pw_cc_binary(
  name = "some_binary",
  srcs = ["some_source.c"],
  additional_linker_inputs = [":some_linker_script"],
  linkopts = ["-T $(location :some_linker_script)"],
)

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 ‘libtinfo.so.5’ 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 \
  --platforms=@pigweed//pw_build/platforms:cortex_m4_fpu
bazel build //:your_target \
  --platforms=@pigweed//pw_build/platforms:cortex_m7_fpu

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:

#your_repo/build_settings/constraints/board/BUILD
constraint_value(
  name = "nucleo_l432kc",
  constraint_setting = "@pigweed//pw_build/constraints/board",
)

New chipset constraint_value:

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

New platforms for chipset and board:

#your_repo/build_settings/platforms/BUILD
# Works with all stm32l432kc
platforms(
  name = "stm32l432kc",
  parents = ["@pigweed//pw_build/platforms:cortex_m4"],
  constraint_values =
    ["@your_repo//build_settings/constraints/chipset:stm32l432kc"],
)

# Works with only the nucleo_l432kc
platforms(
  name = "nucleo_l432kc",
  parents = [":stm32l432kc"],
  constraint_values =
    ["@your_repo//build_settings/constraints/board:nucleo_l432kc"],
)

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

bazel build //:your_target_for_nucleo_l432kc \
  --platforms=@your_repo//build_settings:nucleo_l432kc

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

cc_library(
  name = "compatible_with_all_stm32l432kc",
  srcs = ["tomato_src.c"],
  target_compatible_with =
    ["@your_repo//build_settings/constraints/chipset:stm32l432kc"],
)

cc_library(
  name = "compatible_with_only_nucleo_l432kc",
  srcs = ["bbq_src.c"],
  target_compatible_with =
    ["@your_repo//build_settings/constraints/board:nucleo_l432kc"],
)