""" Builds the application """ import io import json import logging import os import pathlib from pathlib import Path from typing import Dict, List, NamedTuple, Optional, cast import docker import docker.errors from aws_lambda_builders import ( RPC_PROTOCOL_VERSION as lambda_builders_protocol_version, ) from aws_lambda_builders.builder import LambdaBuilder from aws_lambda_builders.exceptions import LambdaBuilderError from samcli.commands._utils.experimental import get_enabled_experimental_flags from samcli.lib.build.build_graph import BuildGraph, FunctionBuildDefinition, LayerBuildDefinition from samcli.lib.build.build_strategy import ( BuildStrategy, CachedOrIncrementalBuildStrategyWrapper, DefaultBuildStrategy, ParallelBuildStrategy, ) from samcli.lib.build.constants import BUILD_PROPERTIES, DEPRECATED_RUNTIMES from samcli.lib.build.exceptions import ( BuildError, BuildInsideContainerError, DockerBuildFailed, DockerConnectionError, DockerfileOutSideOfContext, UnsupportedBuilderLibraryVersionError, ) from samcli.lib.build.utils import _make_env_vars from samcli.lib.build.workflow_config import ( CONFIG, UnsupportedRuntimeException, get_layer_subfolder, get_workflow_config, supports_specified_workflow, ) from samcli.lib.constants import DOCKER_MIN_API_VERSION from samcli.lib.docker.log_streamer import LogStreamer, LogStreamError from samcli.lib.providers.provider import ResourcesToBuildCollector, Stack, get_full_path from samcli.lib.samlib.resource_metadata_normalizer import ResourceMetadataNormalizer from samcli.lib.utils import osutils from samcli.lib.utils.colors import Colored, Colors from samcli.lib.utils.lambda_builders import patch_runtime from samcli.lib.utils.packagetype import IMAGE, ZIP from samcli.lib.utils.path_utils import check_path_valid_type, convert_path_to_unix_path from samcli.lib.utils.resources import ( AWS_CLOUDFORMATION_STACK, AWS_LAMBDA_FUNCTION, AWS_LAMBDA_LAYERVERSION, AWS_SERVERLESS_APPLICATION, AWS_SERVERLESS_FUNCTION, AWS_SERVERLESS_LAYERVERSION, ) from samcli.lib.utils.stream_writer import StreamWriter from samcli.local.docker.container import ContainerContext from samcli.local.docker.lambda_build_container import LambdaBuildContainer from samcli.local.docker.manager import ContainerManager, DockerImagePullFailedException from samcli.local.docker.utils import get_docker_platform, is_docker_reachable LOG = logging.getLogger(__name__) FIRST_COMPATIBLE_RUNTIME_INDEX = 0 HTTP_400 = 400 HTTP_500 = 500 HTTP_505 = 505 JSON_RPC_CODE = -32601 class ApplicationBuildResult(NamedTuple): """ Result of the application build, build_graph and the built artifacts in dictionary """ build_graph: BuildGraph artifacts: Dict[str, str] class ApplicationBuilder: """ Class to build an entire application. Currently, this class builds Lambda functions only, but there is nothing that is stopping this class from supporting other resource types. Building in context of Lambda functions refer to converting source code into artifacts that can be run on AWS Lambda """ def __init__( self, resources_to_build: ResourcesToBuildCollector, build_dir: str, base_dir: str, cache_dir: str, cached: bool = False, is_building_specific_resource: bool = False, manifest_path_override: Optional[str] = None, container_manager: Optional[ContainerManager] = None, parallel: bool = False, mode: Optional[str] = None, stream_writer: Optional[StreamWriter] = None, docker_client: Optional[docker.DockerClient] = None, container_env_var: Optional[Dict] = None, container_env_var_file: Optional[str] = None, build_images: Optional[Dict] = None, combine_dependencies: bool = True, build_in_source: Optional[bool] = None, mount_with_write: bool = False, mount_symlinks: Optional[bool] = False, ) -> None: """ Initialize the class Parameters ---------- resources_to_build: Iterator Iterator that can vend out resources available in the SAM template build_dir : str Path to the directory where we will be storing built artifacts base_dir : str Path to a folder. Use this folder as the root to resolve relative source code paths against cache_dir : str Path to a the directory where we will be caching built artifacts cached: Optional. Set to True to build each function with cache to improve performance is_building_specific_resource : boolean Whether customer requested to build a specific resource alone in isolation, by specifying function_identifier to the build command. Ex: sam build MyServerlessFunction manifest_path_override : Optional[str] Optional path to manifest file to replace the default one container_manager : samcli.local.docker.manager.ContainerManager Optional. If provided, we will attempt to build inside a Docker Container parallel : bool Optional. Set to True to build each function in parallel to improve performance mode : str Optional, name of the build mode to use ex: 'debug' stream_writer : Optional[StreamWriter] An optional stream writer to accept stderr output docker_client : Optional[docker.DockerClient] An optional Docker client object to replace the default one loaded from env container_env_var : Optional[Dict] An optional dictionary of environment variables to pass to the container container_env_var_file : Optional[str] An optional path to file that contains environment variables to pass to the container build_images : Optional[Dict] An optional dictionary of build images to be used for building functions combine_dependencies: bool An optional bool parameter to inform lambda builders whether we should separate the source code and dependencies or not. build_in_source: Optional[bool] Set to True to build in the source directory. mount_with_write: bool Mount source code directory with write permissions when building inside container. mount_symlinks: Optional[bool] True if symlinks should be mounted in the container. """ self._resources_to_build = resources_to_build self._build_dir = build_dir self._base_dir = base_dir self._cache_dir = cache_dir self._cached = cached self._manifest_path_override = manifest_path_override self._is_building_specific_resource = is_building_specific_resource self._container_manager = container_manager self._parallel = parallel self._mode = mode self._stream_writer = stream_writer if stream_writer else StreamWriter(stream=osutils.stderr(), auto_flush=True) self._docker_client = docker_client if docker_client else docker.from_env(version=DOCKER_MIN_API_VERSION) self._deprecated_runtimes = DEPRECATED_RUNTIMES self._colored = Colored() self._container_env_var = container_env_var self._container_env_var_file = container_env_var_file self._build_images = build_images or {} self._combine_dependencies = combine_dependencies self._build_in_source = build_in_source self._mount_with_write = mount_with_write self._mount_symlinks = mount_symlinks def build(self) -> ApplicationBuildResult: """ Build the entire application Returns ------- ApplicationBuildResult Returns the build graph and the path to where each resource was built as a map of resource's LogicalId to the path string """ build_graph = self._get_build_graph(self._container_env_var, self._container_env_var_file) build_strategy: BuildStrategy = DefaultBuildStrategy( build_graph, self._build_dir, self._build_function, self._build_layer, self._cached ) if self._parallel: if self._cached: build_strategy = ParallelBuildStrategy( build_graph, CachedOrIncrementalBuildStrategyWrapper( build_graph, build_strategy, self._base_dir, self._build_dir, self._cache_dir, self._manifest_path_override, self._is_building_specific_resource, bool(self._container_manager), ), ) else: build_strategy = ParallelBuildStrategy(build_graph, build_strategy) elif self._cached: build_strategy = CachedOrIncrementalBuildStrategyWrapper( build_graph, build_strategy, self._base_dir, self._build_dir, self._cache_dir, self._manifest_path_override, self._is_building_specific_resource, bool(self._container_manager), ) return ApplicationBuildResult(build_graph, build_strategy.build()) def _get_build_graph( self, inline_env_vars: Optional[Dict] = None, env_vars_file: Optional[str] = None ) -> BuildGraph: """ Converts list of functions and layers into a build graph, where we can iterate on each unique build and trigger build :return: BuildGraph, which represents list of unique build definitions """ build_graph = BuildGraph(self._build_dir) functions = self._resources_to_build.functions layers = self._resources_to_build.layers file_env_vars = {} if env_vars_file: try: with open(env_vars_file, "r", encoding="utf-8") as fp: file_env_vars = json.load(fp) except Exception as ex: raise IOError( "Could not read environment variables overrides from file {}: {}".format(env_vars_file, str(ex)) ) from ex for function in functions: container_env_vars = _make_env_vars(function, file_env_vars, inline_env_vars) function_build_details = FunctionBuildDefinition( function.runtime, function.codeuri, function.imageuri, function.packagetype, function.architecture, function.metadata, function.handler, env_vars=container_env_vars, ) build_graph.put_function_build_definition(function_build_details, function) for layer in layers: container_env_vars = _make_env_vars(layer, file_env_vars, inline_env_vars) layer_build_details = LayerBuildDefinition( layer.full_path, layer.codeuri, layer.build_method, layer.compatible_runtimes, layer.build_architecture, env_vars=container_env_vars, ) build_graph.put_layer_build_definition(layer_build_details, layer) build_graph.clean_redundant_definitions_and_update(not self._is_building_specific_resource) return build_graph @staticmethod def update_template( stack: Stack, built_artifacts: Dict[str, str], stack_output_template_path_by_stack_path: Dict[str, str], ) -> Dict: """ Given the path to built artifacts, update the template to point appropriate resource CodeUris to the artifacts folder Parameters ---------- stack: Stack The stack object representing the template built_artifacts : dict Map of LogicalId of a resource to the path where the the built artifacts for this resource lives stack_output_template_path_by_stack_path: Dict[str, str] A dictionary contains where the template of each stack will be written to Returns ------- dict Updated template """ original_dir = pathlib.Path(stack.location).parent.resolve() template_dict = stack.template_dict normalized_resources = stack.resources for logical_id, resource in template_dict.get("Resources", {}).items(): resource_iac_id = ResourceMetadataNormalizer.get_resource_id(resource, logical_id) full_path = get_full_path(stack.stack_path, resource_iac_id) has_build_artifact = full_path in built_artifacts is_stack = full_path in stack_output_template_path_by_stack_path if not has_build_artifact and not is_stack: # this resource was not built or a nested stack. # So skip it because there is no path/uri to update continue # clone normalized metadata from stack.resources only to built resources normalized_metadata = normalized_resources.get(logical_id, {}).get("Metadata") if normalized_metadata: resource["Metadata"] = normalized_metadata resource_type = resource.get("Type") properties = resource.setdefault("Properties", {}) absolute_output_path = pathlib.Path( built_artifacts[full_path] if has_build_artifact else stack_output_template_path_by_stack_path[full_path] ).resolve() # Default path to absolute path of the artifact store_path = str(absolute_output_path) # In Windows, if template and artifacts are in two different drives, relpath will fail if original_dir.drive == absolute_output_path.drive: # Artifacts are written relative the template because it makes the template portable # Ex: A CI/CD pipeline build stage could zip the output folder and pass to a # package stage running on a different machine store_path = os.path.relpath(absolute_output_path, original_dir) if has_build_artifact: ApplicationBuilder._update_built_resource( built_artifacts[full_path], properties, resource_type, store_path ) if is_stack: if resource_type == AWS_SERVERLESS_APPLICATION: properties["Location"] = store_path if resource_type == AWS_CLOUDFORMATION_STACK: properties["TemplateURL"] = store_path return template_dict @staticmethod def _update_built_resource(path: str, resource_properties: Dict, resource_type: str, absolute_path: str) -> None: if resource_type == AWS_SERVERLESS_FUNCTION and resource_properties.get("PackageType", ZIP) == ZIP: resource_properties["CodeUri"] = absolute_path if resource_type == AWS_LAMBDA_FUNCTION and resource_properties.get("PackageType", ZIP) == ZIP: resource_properties["Code"] = absolute_path if resource_type == AWS_LAMBDA_LAYERVERSION: resource_properties["Content"] = absolute_path if resource_type == AWS_SERVERLESS_LAYERVERSION: resource_properties["ContentUri"] = absolute_path if resource_type == AWS_LAMBDA_FUNCTION and resource_properties.get("PackageType", ZIP) == IMAGE: resource_properties["Code"] = {"ImageUri": path} if resource_type == AWS_SERVERLESS_FUNCTION and resource_properties.get("PackageType", ZIP) == IMAGE: resource_properties["ImageUri"] = path def _build_lambda_image(self, function_name: str, metadata: Dict, architecture: str) -> str: """ Build an Lambda image Parameters ---------- function_name str Name of the function (logical id or function name) metadata dict Dictionary representing the Metadata attached to the Resource in the template architecture : str The architecture type 'x86_64' and 'arm64' in AWS Returns ------- str The full tag (org/repo:tag) of the image that was built """ LOG.info("Building image for %s function", function_name) dockerfile = cast(str, metadata.get("Dockerfile")) docker_context = cast(str, metadata.get("DockerContext")) # Have a default tag if not present. tag = metadata.get("DockerTag", "latest") docker_tag = f"{function_name.lower()}:{tag}" docker_build_target = metadata.get("DockerBuildTarget", None) docker_build_args = metadata.get("DockerBuildArgs", {}) if not dockerfile or not docker_context: raise DockerBuildFailed("Docker file or Docker context metadata are missed.") if not isinstance(docker_build_args, dict): raise DockerBuildFailed("DockerBuildArgs needs to be a dictionary!") docker_context_dir = pathlib.Path(self._base_dir, docker_context).resolve() if not is_docker_reachable(self._docker_client): raise DockerConnectionError(msg=f"Building image for {function_name} requires Docker. is Docker running?") if os.environ.get("SAM_BUILD_MODE") and isinstance(docker_build_args, dict): docker_build_args["SAM_BUILD_MODE"] = os.environ.get("SAM_BUILD_MODE") docker_tag = "-".join([docker_tag, docker_build_args["SAM_BUILD_MODE"]]) if isinstance(docker_build_args, dict): LOG.info("Setting DockerBuildArgs for %s function", function_name) build_args = { "path": str(docker_context_dir), "dockerfile": str(pathlib.Path(dockerfile).as_posix()), "tag": docker_tag, "buildargs": docker_build_args, "platform": get_docker_platform(architecture), "rm": True, } if docker_build_target: build_args["target"] = cast(str, docker_build_target) try: (build_image, build_logs) = self._docker_client.images.build(**build_args) LOG.debug("%s image is built for %s function", build_image, function_name) except docker.errors.BuildError as ex: LOG.error("Failed building function %s", function_name) self._stream_lambda_image_build_logs(ex.build_log, function_name, False) raise DockerBuildFailed(str(ex)) from ex # The Docker-py low level api will stream logs back but if an exception is raised by the api # this is raised when accessing the generator. So we need to wrap accessing build_logs in a try: except. try: self._stream_lambda_image_build_logs(build_logs, function_name) except docker.errors.APIError as e: if e.is_server_error and "Cannot locate specified Dockerfile" in e.explanation: raise DockerfileOutSideOfContext(e.explanation) from e # Not sure what else can be raise that we should be catching but re-raising for now raise return docker_tag def _stream_lambda_image_build_logs( self, build_logs: List[Dict[str, str]], function_name: str, throw_on_error: bool = True ) -> None: """ Stream logs to the console from an Lambda image build. Parameters ---------- build_logs generator A generator for the build output. function_name str Name of the function that is being built """ build_log_streamer = LogStreamer(self._stream_writer, throw_on_error) try: build_log_streamer.stream_progress(build_logs) except LogStreamError as ex: raise DockerBuildFailed(msg=f"{function_name} failed to build: {str(ex)}") from ex def _load_lambda_image(self, image_archive_path: str) -> str: try: with open(image_archive_path, mode="rb") as image_archive: [image, *rest] = self._docker_client.images.load(image_archive) if len(rest) != 0: raise DockerBuildFailed("Archive must represent a single image") return f"{image.id}" except (docker.errors.APIError, OSError) as ex: raise DockerBuildFailed(msg=str(ex)) from ex def _build_layer( self, layer_name: str, codeuri: str, specified_workflow: str, compatible_runtimes: List[str], architecture: str, artifact_dir: str, container_env_vars: Optional[Dict] = None, dependencies_dir: Optional[str] = None, download_dependencies: bool = True, layer_metadata: Optional[Dict] = None, ) -> str: """ Given the layer information, this method will build the Lambda layer. Depending on the configuration it will either build the function in process or by spinning up a Docker container. Parameters ---------- layer_name : str Name or LogicalId of the function codeuri : str Path to where the code lives specified_workflow : str The specified workflow compatible_runtimes : List[str] List of runtimes the layer build is compatible with architecture : str The architecture type 'x86_64' and 'arm64' in AWS artifact_dir : str Path to where layer will be build into. A subfolder will be created in this directory depending on the specified workflow. container_env_vars : Optional[Dict] An optional dictionary of environment variables to pass to the container. dependencies_dir: Optional[str] An optional string parameter which will be used in lambda builders for downloading dependencies into separate folder download_dependencies: bool An optional boolean parameter to inform lambda builders whether download dependencies or use previously downloaded ones. Default value is True. layer_metadata: Optional[Dict] An optional dictionary that contain the layer version metadata information. Returns ------- str Path to the location where built artifacts are available """ # Create the arguments to pass to the builder # Code is always relative to the given base directory. code_dir = str(pathlib.Path(self._base_dir, codeuri).resolve()) config = get_workflow_config(None, code_dir, self._base_dir, specified_workflow) subfolder = get_layer_subfolder(specified_workflow) if ( config.language == "provided" and isinstance(layer_metadata, dict) and layer_metadata.get("ProjectRootDirectory") ): code_dir = str(pathlib.Path(self._base_dir, layer_metadata.get("ProjectRootDirectory", code_dir)).resolve()) # artifacts directory will be created by the builder artifact_subdir = str(pathlib.Path(artifact_dir, subfolder)) with osutils.mkdir_temp() as scratch_dir: manifest_context_path = code_dir if config.language == "provided" and isinstance(layer_metadata, dict) and layer_metadata.get("ContextPath"): manifest_context_path = str( pathlib.Path(self._base_dir, layer_metadata.get("ContextPath", code_dir)).resolve() ) manifest_path = self._manifest_path_override or os.path.join(manifest_context_path, config.manifest_name) # By default prefer to build in-process for speed scratch_dir_path = ( LambdaBuildContainer.get_container_dirs(code_dir, manifest_path)["scratch_dir"] if self._container_manager else scratch_dir ) build_runtime = specified_workflow options = ApplicationBuilder._get_build_options( layer_name, config.language, self._base_dir, None, metadata=layer_metadata, source_code_path=code_dir, scratch_dir=scratch_dir_path, ) if self._container_manager: # None key represents the global build image for all functions/layers if config.language == "provided": LOG.warning( "For container layer build, first compatible runtime is chosen as build target for container." ) # Only set to this value if specified workflow is makefile # which will result in config language as provided build_runtime = ( compatible_runtimes[FIRST_COMPATIBLE_RUNTIME_INDEX] if compatible_runtimes else config.language ) global_image = self._build_images.get(None) image = self._build_images.get(layer_name, global_image) # pass to container only when specified workflow is supported to overwrite runtime to get image supported_specified_workflow = supports_specified_workflow(specified_workflow) self._build_function_on_container( config, code_dir, artifact_subdir, manifest_path, build_runtime, architecture, options, container_env_vars, image, is_building_layer=True, specified_workflow=specified_workflow if supported_specified_workflow else None, ) else: self._build_function_in_process( config, code_dir, artifact_subdir, scratch_dir, manifest_path, build_runtime, architecture, options, dependencies_dir, download_dependencies, True, # dependencies for layer should always be combined is_building_layer=True, ) # Not including subfolder in return so that we copy subfolder, instead of copying artifacts inside it. return artifact_dir def _build_function( # pylint: disable=R1710 self, function_name: str, codeuri: str, imageuri: Optional[str], packagetype: str, runtime: str, architecture: str, handler: Optional[str], artifact_dir: str, metadata: Optional[Dict] = None, container_env_vars: Optional[Dict] = None, dependencies_dir: Optional[str] = None, download_dependencies: bool = True, ) -> str: """ Given the function information, this method will build the Lambda function. Depending on the configuration it will either build the function in process or by spinning up a Docker container. Parameters ---------- function_name : str Name or LogicalId of the function codeuri : str Path to where the code lives imageuri : str Location of the Lambda Image which is of the form {image}:{tag}, sha256:{digest}, or a path to a local archive packagetype : str The package type, 'Zip' or 'Image', see samcli/lib/utils/packagetype.py runtime : str AWS Lambda function runtime architecture : str The architecture type 'x86_64' and 'arm64' in AWS handler : Optional[str] An optional string to specify which function the handler should be artifact_dir: str Path to where function will be build into metadata : dict AWS Lambda function metadata container_env_vars : Optional[Dict] An optional dictionary of environment variables to pass to the container. dependencies_dir: Optional[str] An optional string parameter which will be used in lambda builders for downloading dependencies into separate folder download_dependencies: bool An optional boolean parameter to inform lambda builders whether download dependencies or use previously downloaded ones. Default value is True. Returns ------- str Path to the location where built artifacts are available """ if packagetype == IMAGE: if ( imageuri and check_path_valid_type(imageuri) and Path(imageuri).is_file() ): # something exists at this path and what exists is a file return self._load_lambda_image(imageuri) # should be an image archive – load it instead of building it # pylint: disable=fixme # FIXME: _build_lambda_image assumes metadata is not None, we need to throw an exception here return self._build_lambda_image( function_name=function_name, metadata=metadata, architecture=architecture # type: ignore ) if packagetype == ZIP: if runtime in self._deprecated_runtimes: message = ( f"Building functions with {runtime} is no longer supported by AWS SAM CLI, please " f"update to a newer supported runtime. For more information please check AWS Lambda Runtime " f"Support Policy: https://docs.aws.amazon.com/lambda/latest/dg/runtime-support-policy.html" ) LOG.warning(self._colored.color_log(msg=message, color=Colors.WARNING), extra=dict(markup=True)) raise UnsupportedRuntimeException(f"Building functions with {runtime} is no longer supported") # Create the arguments to pass to the builder # Code is always relative to the given base directory. code_dir = str(pathlib.Path(self._base_dir, codeuri).resolve()) # Determine if there was a build workflow that was specified directly in the template. specified_workflow = metadata.get("BuildMethod", None) if metadata else None config = get_workflow_config(runtime, code_dir, self._base_dir, specified_workflow=specified_workflow) if config.language == "provided" and isinstance(metadata, dict) and metadata.get("ProjectRootDirectory"): code_dir = str(pathlib.Path(self._base_dir, metadata.get("ProjectRootDirectory", code_dir)).resolve()) with osutils.mkdir_temp() as scratch_dir: manifest_context_path = code_dir if config.language == "provided" and isinstance(metadata, dict) and metadata.get("ContextPath"): manifest_context_path = str( pathlib.Path(self._base_dir, metadata.get("ContextPath", code_dir)).resolve() ) manifest_path = self._manifest_path_override or os.path.join( manifest_context_path, config.manifest_name ) scratch_dir_path = ( LambdaBuildContainer.get_container_dirs(code_dir, manifest_path)["scratch_dir"] if self._container_manager else scratch_dir ) options = ApplicationBuilder._get_build_options( function_name, config.language, self._base_dir, handler, config.dependency_manager, metadata, source_code_path=code_dir, scratch_dir=scratch_dir_path, ) # By default prefer to build in-process for speed if self._container_manager: # None represents the global build image for all functions/layers global_image = self._build_images.get(None) image = self._build_images.get(function_name, global_image) # pass to container only when specified workflow is supported to overwrite runtime to get image supported_specified_workflow = supports_specified_workflow(specified_workflow) return self._build_function_on_container( config, code_dir, artifact_dir, manifest_path, runtime, architecture, options, container_env_vars, image, specified_workflow=specified_workflow if supported_specified_workflow else None, ) return self._build_function_in_process( config, code_dir, artifact_dir, scratch_dir, manifest_path, runtime, architecture, options, dependencies_dir, download_dependencies, self._combine_dependencies, ) # pylint: disable=fixme # FIXME: we need to throw an exception here, packagetype could be something else return # type: ignore @staticmethod def _get_build_options( function_name: str, language: str, base_dir: str, handler: Optional[str], dependency_manager: Optional[str] = None, metadata: Optional[dict] = None, source_code_path: Optional[str] = None, scratch_dir: Optional[str] = None, ) -> Optional[Dict]: """ Parameters ---------- function_name str current function resource name language str language of the runtime base_dir str Path to a folder. Use this folder as the root to resolve relative source code paths against handler str Handler value of the Lambda Function Resource dependency_manager str Dependency manager to check in addition to language metadata Dict Metadata object to search for build properties source_code_path str The lambda function source code path that will be used to calculate the working directory scratch_dir str The temporary directory path where the lambda function code will be copied to. Returns ------- dict Dictionary that represents the options to pass to the builder workflow or None if options are not needed """ build_props = {} if metadata and isinstance(metadata, dict): build_props = metadata.get(BUILD_PROPERTIES, {}) if metadata and dependency_manager and dependency_manager == "npm-esbuild": # Esbuild takes an array of entry points from which to start bundling # as a required argument. This corresponds to the lambda function handler. normalized_build_props = ResourceMetadataNormalizer.normalize_build_properties(build_props) if handler and not build_props.get("EntryPoints"): entry_points = [handler.split(".")[0]] normalized_build_props["entry_points"] = entry_points return normalized_build_props _build_options: Dict[str, Dict] = { "go": { "artifact_executable_name": handler, "trim_go_path": build_props.get("TrimGoPath", False), }, "provided": {"build_logical_id": function_name}, "nodejs": {"use_npm_ci": build_props.get("UseNpmCi", False)}, } options = _build_options.get(language, None) if language == "provided": options = options if options else {} working_directory = ApplicationBuilder._get_working_directory_path( base_dir, metadata, source_code_path, scratch_dir ) if working_directory: options = {**options, "working_directory": convert_path_to_unix_path(working_directory)} if language == "rust" and "Binary" in build_props: options = options if options else {} options["artifact_executable_name"] = build_props["Binary"] return options @staticmethod def _get_working_directory_path( base_dir: str, metadata: Optional[Dict], source_code_path: Optional[str], scratch_dir: Optional[str] ) -> Optional[str]: """ Get the working directory from the lambda resource metadata information, and check if it is not None, and it is a child path to the source directory path, then return the working directory as a child to the scratch directory. Parameters ---------- base_dir : str Path to a folder. Use this folder as the root to resolve relative source code paths against metadata Dict Lambda resource metadata object to search for build properties source_code_path str The lambda resource source code path that will be used to calculate the working directory scratch_dir str The temporary directory path where the lambda resource code will be copied to. Returns ------- str The working directory path or None if there is no working_dir metadata info. """ working_directory = None if metadata and isinstance(metadata, dict): working_directory = metadata.get("WorkingDirectory") if working_directory: working_directory = str(pathlib.Path(base_dir, working_directory).resolve()) # check if the working directory is a child of the lambda resource source code path, to update the # working directory to be child of the scratch directory if ( source_code_path and scratch_dir and os.path.commonpath([source_code_path, working_directory]) == os.path.normpath(source_code_path) ): working_directory = os.path.relpath(working_directory, source_code_path) working_directory = os.path.normpath(os.path.join(scratch_dir, working_directory)) return working_directory def _build_function_in_process( self, config: CONFIG, source_dir: str, artifacts_dir: str, scratch_dir: str, manifest_path: str, runtime: str, architecture: str, options: Optional[Dict], dependencies_dir: Optional[str], download_dependencies: bool, combine_dependencies: bool, is_building_layer: bool = False, ) -> str: builder = LambdaBuilder( language=config.language, dependency_manager=config.dependency_manager, application_framework=config.application_framework, ) runtime_patched = patch_runtime(runtime) try: builder.build( source_dir, artifacts_dir, scratch_dir, manifest_path, runtime=runtime_patched, unpatched_runtime=runtime, executable_search_paths=config.executable_search_paths, mode=self._mode, options=options, architecture=architecture, dependencies_dir=dependencies_dir, download_dependencies=download_dependencies, combine_dependencies=combine_dependencies, is_building_layer=is_building_layer, experimental_flags=get_enabled_experimental_flags(), build_in_source=self._build_in_source, ) except LambdaBuilderError as ex: raise BuildError(wrapped_from=ex.__class__.__name__, msg=str(ex)) from ex return artifacts_dir def _build_function_on_container( self, # pylint: disable=too-many-locals config: CONFIG, source_dir: str, artifacts_dir: str, manifest_path: str, runtime: str, architecture: str, options: Optional[Dict], container_env_vars: Optional[Dict] = None, build_image: Optional[str] = None, is_building_layer: bool = False, specified_workflow: Optional[str] = None, ) -> str: # _build_function_on_container() is only called when self._container_manager if not None if not self._container_manager: raise RuntimeError("_build_function_on_container() is called when self._container_manager is None.") if not self._container_manager.is_docker_reachable: raise BuildInsideContainerError( "Docker is unreachable. Docker needs to be running to build inside a container." ) # If we are printing debug logs in SAM CLI, the builder library should also print debug logs log_level = LOG.getEffectiveLevel() container_env_vars = container_env_vars or {} container = LambdaBuildContainer( lambda_builders_protocol_version, config.language, config.dependency_manager, config.application_framework, source_dir, manifest_path, runtime, architecture, specified_workflow=specified_workflow, log_level=log_level, optimizations=None, options=options, executable_search_paths=config.executable_search_paths, mode=self._mode, env_vars=container_env_vars, image=build_image, is_building_layer=is_building_layer, build_in_source=self._build_in_source, mount_with_write=self._mount_with_write, build_dir=self._build_dir, mount_symlinks=self._mount_symlinks, ) try: try: self._container_manager.run(container, context=ContainerContext.BUILD) except docker.errors.APIError as ex: if "executable file not found in $PATH" in str(ex): raise UnsupportedBuilderLibraryVersionError( container.image, "{} executable not found in container".format(container.executable_name) ) from ex # Container's output provides status of whether the build succeeded or failed # stdout contains the result of JSON-RPC call stdout_stream = io.BytesIO() # stderr contains logs printed by the builder. Stream it directly to terminal stderr_stream = osutils.stderr() container.wait_for_logs(stdout=stdout_stream, stderr=stderr_stream) stdout_data = stdout_stream.getvalue().decode("utf-8") LOG.debug("Build inside container returned response %s", stdout_data) response = self._parse_builder_response(stdout_data, container.image) # Request is successful. Now copy the artifacts back to the host LOG.debug("Build inside container was successful. Copying artifacts from container to host") # "/." is a Docker thing that instructions the copy command to download contents of the folder only result_dir_in_container = response["result"]["artifacts_dir"] + "/." container.copy(result_dir_in_container, artifacts_dir) except DockerImagePullFailedException as ex: raise BuildInsideContainerError(ex) finally: self._container_manager.stop(container) LOG.debug("Build inside container succeeded") return artifacts_dir @staticmethod def _parse_builder_response(stdout_data: str, image_name: str) -> Dict: try: response = json.loads(stdout_data) except Exception: # Invalid JSON is produced as an output only when the builder process crashed for some reason. # Report this as a crash LOG.error("Builder crashed: %s", stdout_data) raise if "error" in response: error = response.get("error", {}) err_code = error.get("code") msg = error.get("message") if HTTP_400 <= err_code < HTTP_500: # Like HTTP 4xx - customer error raise BuildInsideContainerError(msg) if err_code == HTTP_505: # Like HTTP 505 error code: Version of the protocol is not supported # In this case, this error means that the Builder Library within the container is # not compatible with the version of protocol expected SAM CLI installation supports. # This can happen when customers have a newer container image or an older SAM CLI version. # https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/505 raise UnsupportedBuilderLibraryVersionError(image_name, msg) if err_code == JSON_RPC_CODE: # Default JSON Rpc Code for Method Unavailable https://www.jsonrpc.org/specification # This can happen if customers are using an incompatible version of builder library within the # container LOG.debug("Builder library does not support the supplied method") raise UnsupportedBuilderLibraryVersionError(image_name, msg) LOG.debug("Builder crashed") raise ValueError(msg) return cast(Dict, response)