execute.py 文件源码

def collect_tasks(path, folders, matrix_base_dir, channels=None, steps=0, test=False,
                  max_downstream=5, variant_config_files=None):
    # runs = ['test']
    # not testing means build and test
    # if not test:
    #     runs.insert(0, 'build')
    runs = ['build']

    task_graph = nx.DiGraph()
    config = conda_build.api.Config()
    for run in runs:
        platforms = parse_platforms(matrix_base_dir, run)
        # loop over platforms here because each platform may have different dependencies
        # each platform will be submitted with a different label
        for platform in platforms:
            index_key = '-'.join([platform['platform'], str(platform['arch'])])
            config.channel_urls = channels or []
            config.variant_config_files = variant_config_files or []
            conda_resolve = Resolve(get_build_index(subdir=index_key,
                                                    bldpkgs_dir=config.bldpkgs_dir)[0])
            # this graph is potentially different for platform and for build or test mode ("run")
            g = construct_graph(path, worker=platform, folders=folders, run=run,
                                matrix_base_dir=matrix_base_dir, conda_resolve=conda_resolve,
                                config=config)
            # Apply the build label to any nodes that need (re)building or testing
            expand_run(g, conda_resolve=conda_resolve, worker=platform, run=run,
                       steps=steps, max_downstream=max_downstream, recipes_dir=path,
                       matrix_base_dir=matrix_base_dir)
            # merge this graph with the main one
            task_graph = nx.compose(task_graph, g)
    return task_graph