Code generation

Code generation inputs (*.zap files)

Matter code relies on code generation for cluster-specific data types and callbacks. Generally this is split into:

  • Data serialization for structures/lists/commands. This applies to both client-side and server-side structures and objects
  • Callback setup using the Ember-based framework. This generally applies to server-side processing and the code generation defines what processing needs to be done when a specific command is received or an attribute is read and what memory should be allocated for storing cluster attributes

Code generation depends on the clusters that are needed by an application. Every application configures the specific set of endpoints and clusters it needs based on the device type it supports. The selection of the supported clusters and attributes (as optional attributes may be omitted to save memory) is generally stored in *.zap files.

The selection of enabled clusters and files is done using ZAP. You can download a recent release of zap from its releases page. It is recommended to download a release that is in sync with the currently in use version by the SDK (see integrations/docker/images/chip-build/Dockerfile and check the ZAP_VERSION setting).

Beyond basic zap file selection, there are also .json zap settings that define additional cluster info: source XML files, sdk-access methods and data types. There are only two such files currently in use:

  • src/app/zap-templates/zcl/zcl.json is the default one
  • src/app/zap-templates/zcl/zcl-with-test-extensions.json is used by all-clusters-app to show how a cluster extension may be configured with minimal changes from zcl.json (but it is different)

Installing zap and environment variables

Matter scripts may need to invoke zap-cli (for code generation) or zap (to start the UI tool). For this, scrips need to know where to find the commands. In the following order, the scripts process these environment variables:

  • if $ZAP_DEVELOPMENT_PATH is set, code assumes you are running zap from source. Use this if you develop zap. Zap has to be bootstrapped (generally npm ci but check zap documentation for this. Some scripts have a --run-bootstrap command line argument to do this for you)

  • if $ZAP_INSTALL_PATH is set, code assumes that zap or zap-cli is available in the given path. This is generally an unpacked release.

  • otherwise, scripts will assume zap/zap-cli is in $PATH

Using a UI to edit .zap files

Generally you need to invoke zap with appropriate zcl and generate arguments. Most of code generation is app specific, so you generally want something of the form --gen src/app/zap-templates/app-templates.json --zcl $ZCL_JSON_FILE $ZAP_FILE_TO_EDIT

Since this is tedious to type, the SDK provides a scripts/tools/zap/run_zaptool.sh script to automate this:

# Ensure zap is in $PATH or set $ZAP_INSTALL_PATH or $ZAP_DEVELOPMENT_PATH
./scripts/tools/zap/run_zaptool.sh examples/lighting-app/lighting-common/lighting-app.zap

Human-readable code generation inputs (*.matter)

.zap files are large json files that are generally not human readable. As a result, the Matter SDK also keeps an equivalent *.matter file along side .zap files that contain the same data as .zap files, targeted specifically for matter:

  • They are designed to be human readable, looking like a IDL (think protobuf or android aidl, thrift idl etc.)

  • We strive to make them contain only Matter-specific data (.zap files contain more generic data and is designed to be ZigBee backwards compatible)

Currently .matter files are generated from .zap files during the application specific codegen.

*.matter parsing and codegen

*.matter files are both human and machine readable. Code that can process these files is available at scripts/py_matter_idl and scripts/codegen.py. You can read the scripts/py_matter_idl/matter_idl/README.md for details of how things work.

scripts/codegen.py can generate various outputs based on an input *.matter file.

The split between .zap and .matter currently exists as an experiment of code generation technologies. Currently .matter-based Python code generation:

  • has fewer third party dependencies than zap, which installs a significant number of npm packages.
  • runs significantly faster than zap
  • offers more flexible code generation (can generate multiple files per cluster for example, without which some compiles would run out of RAM on large compilations)
  • has a more flexible templating language
  • has human readable (and potentially editable) input
  • is more easily provable deterministic (zap uses an underlying sqlite database and some legacy assumptions from zigbee have historically caused non-determinism)
  • uses a synchronous processing model which is potentially easier to develop for
  • has lower complexity, is unit tested and uses typing extensively

Ideally, the project would be to have a single code generation method in the long term that has all the benefits and none of the drawbacks. We are not there yet, however we likely want:

  • Flexible codegen (we will need to split output by clusters or other rules)
  • Human-readable inputs that enable code reviews and audits
  • Rules that a script can validate based on CSA data model (ensure mandatory attribute settings are followed, ensure proper device type adherence, ensure correct cluster and data type definitions)
  • Easy to maintain and develop for chosen languages/templates/codegen in general

Code generation outputs and templates

Code that is generated:

  • Application-specific:

    • ZAP generation is based on .zap files in examples/ and generates server-side processing data: what cluster callbacks to set up, what RAM to reserve for attribute storage etc.

    • Codegen.py will also generate a subset of application-specific files

  • Automated tests: embedded client-side tools (chip-tool and darwin-framework-tool) generate test-definition data. Each use their own examples/${TOOL}/templates/tests/templates.json to drive what gets generated.

  • Controller clusters target: the file src/controller/data_model/controller-clusters.zap contains a set of cluster selections to which all applications would potentially have access. These are generally used as all clusters selection and the intent is to allow any application to access any cluster as a client side.

    Client/controllers will codegen based on this, like tools, tests, java, python etc.

Running codegen

ZAP file generation

Generating all possible code (all categories above) using zap tool can be done via:

./scripts/tools/zap_regen_all.py

This can be slow (several minutes). The regen tool allows selection of only tests so that yaml test development goes faster.

./scripts/tools/zap_regen_all.py --type tests
./scripts/tools/zap_regen_all.py --type tests --tests chip-tool

Additionally, individual code regeneration can be done using ./scripts/tools/zap/generate.py:

/scripts/tools/zap/generate.py                       \
    examples/bridge-app/bridge-common/bridge-app.zap \
    -o zzz_generated/bridge-app/zap-generated

Compile-time code generation / pre-generated code

A subset of code generation (both codegen.py and zap-cli) is done at compile time or can use pre-generated output (based on gn/cmake arguments)

Rules for how generate.py/codegen.py is invoked at compile time are defined at:

  • src/app/chip_data_model.cmake
  • src/app/chip_data_model.gni

Additionally, build/chip/esp32/esp32_codegen.cmake adds processing support for the 2-pass cmake builds used by the Espressif idf.py build system.

Pre-generation

Code pre-generation can be used:

  • when compile-time code generation is not desirable. This may be for importing into build systems that do not have the pre-requisites to run code generation at build time or to save the code generation time at the expense of running code generation for every possible zap/generation type
  • To check changes in generated code across versions, beyond the comparisons of golden image tests in scripts/py_matter_idl/matter_idl/tests

The script to trigger code pre-generation is scripts/codepregen.py and requires the pre-generation output directory as an argument

scripts/codepregen.py ${OUTPUT_DIRECTORY:-./zzz_pregenerated/}

# To generate a single output you can use `--input-glob`:

scripts/codepregen.py --input-glob "*all-clusters*" ${OUTPUT_DIRECTORY:-./zzz_pregenerated/}

Using pre-generated code

Instead of generating code at compile time, the chip build system accepts usage of a pre-generated folder. It assumes the structure that codepregen.py creates. To invoke use:

  • build_examples.py builds accept --pregen-dir as an argument, such as:

    ./scripts/build/build_examples.py --target $TARGET --pregen-dir $PREGEN_DIR build

  • gn builds allow setting chip_code_pre_generated_directory as an argument, such as:

    gn gen --check --fail-on-unused-args --args='chip_code_pre_generated_directory="/some/pregen/dir"'

  • cmake builds allow setting CHIP_CODEGEN_PREGEN_DIR variable (which will get propagated to the underlying gn builds as needed), such as:


    west build --cmake-only \
    -d /workspace/out/nrf-nrf5340dk-light \
    -b nrf5340dk_nrf5340_cpuapp \
    /workspace/examples/lighting-app/nrfconnect
    -- -DCHIP_CODEGEN_PREGEN_DIR=/some/pregen/dir

idf.py -C examples/all-clusters-app/esp32 \
    -B /workspace/out/esp32-m5stack-all-clusters \
    -DCHIP_CODEGEN_PREGEN_DIR=/some/pregen/dir \
    reconfigure

cmake -S /workspace/examples/lighting-app/mbed \
      -B /workspace/out/mbed-cy8cproto_062_4343w-light \
      -GNinja \
      -DMBED_OS_PATH=/workspace/third_party/mbed-os/repo \
      -DMBED_OS_PATH=/workspace/third_party/mbed-os/repo \
      -DMBED_OS_POSIX_SOCKET_PATH=/workspace/third_party/mbed-os-posix-socket/repo \
      -DCHIP_CODEGEN_PREGEN_DIR=/some/pregen/dir

Code generation unit testing

Code generation is assumed stable between builds and the build system aims to detect changes in code gen using golden image tests.

codegen.py tests

These tests run against golden inputs/outputs from scripts/idl/tests.

available_tests.yaml contains the full list of expected generators and outputs and the test is run via test_generators.py. Use the environment variable IDL_GOLDEN_REGENERATE to force golden image replacement during running of ninja check:

IDL_GOLDEN_REGENERATE=1 ninja check

generate.py tests

These tests run against golden inputs/outputs from scripts/tools/zap/tests.

available_tests.yaml contains the full list of expected generators and outputs and the test is run via scripts/tools/zap/test_generate.py. Use the environment variable ZAP_GENERATE_GOLDEN_REGENERATE to force golden image replacement during running of ninja check.

ZAP_GENERATE_GOLDEN_REGENERATE=1 ninja check

Alternatively, the golden image can also be re-generated by running the stand-alone test in a bootstrapped environment:

./scripts/tools/zap/test_generate.py --output out/gen --regenerate