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Get Started Free →Skill for the core infrastructure module providing logging, configuration, exception handling, progress tracking, checkpoints, retry logic, pipeline execution, performance monitoring, security, file operations, and multi-project orchestration. Use when setting up logging, loading config, handling errors, running pipelines, or monitoring performance.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-06 | ✗→✓ | ▲ Improved | 18% | 0% |
| case-01 | ✗→✓ | ▲ Improved | 22% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 23% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 2% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 0% | 0% |
Foundation utilities used across the entire infrastructure layer and all project scripts.
logging/utils.py)pythonfrom infrastructure.core import get_logger, log_operation, log_stage, format_duration from infrastructure.core.logging.setup import setup_logger from infrastructure.core.logging.utils import log_timing, log_substep logger = get_logger(__name__) logger.info("Processing started") # log_operation is a context manager (logs start, completion, failure) with log_operation("Processing data"): process() # Decorator for automatic timing and logging @log_timing def expensive_operation(): pass # Structured progress logging log_stage(1, 10, "Running Tests") log_substep("Unit tests passed") # ETA calculation from infrastructure.core.runtime import calculate_eta
config/loader.py)pythonfrom infrastructure.core.config.loader import load_config, find_config_file, get_config_as_dict # Load project config.yaml config = load_config(project_path / "manuscript" / "config.yaml") # Resolve a named project config; unqualified lookup is intentionally # ambiguous when a repository contains multiple project manuscripts. config_path = find_config_file(repo_root, project_name="templates/template_code_project")
exceptions.py)All exceptions extend TemplateError. Use context-preserving helpers:
pythonfrom infrastructure.core import TemplateError from infrastructure.core.exceptions import ( ConfigurationError, ValidationError, BuildError, RenderingError, LLMError, PublishingError, raise_with_context, chain_exceptions, format_file_context, ) # Raise with file context raise_with_context(ValidationError("Invalid format"), file_path="doc.md", line=42) # Chain exceptions try: render() except RenderingError as e: chain_exceptions(BuildError("Pipeline failed"), e)
Exception tree: TemplateError → ConfigurationError, ValidationError, BuildError, FileOperationError, DependencyError, TestError, IntegrationError, LLMError, RenderingError, PublishingError, LiteratureSearchError. Nested children: LLMError → LLMConnectionError, LLMTemplateError; RenderingError → FormatError; PublishingError → UploadError; LiteratureSearchError → APIRateLimitError.
pipeline/executor.py)pythonfrom pathlib import Path from infrastructure.core.pipeline import PipelineExecutor, PipelineConfig config = PipelineConfig(project_name="my_project", repo_root=Path("."), skip_llm=True) executor = PipelineExecutor(config) results = executor.execute_core_pipeline() # or execute_full_pipeline()
runtime/checkpoint.py)pythonimport time from infrastructure.core import CheckpointManager from infrastructure.core.runtime.checkpoint import PipelineCheckpoint manager = CheckpointManager(checkpoint_dir) manager.save_checkpoint( pipeline_start_time=time.time(), last_stage_completed=5, stage_results=[], total_stages=10, ) checkpoint = manager.load_checkpoint() # Resume from saved state
progress.py)pythonfrom infrastructure.core import ProgressBar from infrastructure.core.progress import SubStageProgress progress = ProgressBar(total=100, task="Rendering") progress.update(10)
runtime/retry.py)pythonfrom infrastructure.core.runtime import retry_with_backoff @retry_with_backoff(max_retries=3, base_delay=1.0) def flaky_operation(): pass
pipeline/stage_monitor.py, runtime/function_profiler.py)pythonfrom infrastructure.core.runtime.function_profiler import CodeProfiler, monitor_performance from infrastructure.core.pipeline.stage_monitor import PerformanceMonitor, get_system_resources resources = get_system_resources() monitor = PerformanceMonitor() profiler = CodeProfiler() def heavy_computation() -> None: pass with profiler.monitor("heavy_computation"): heavy_computation()
security.py)pythonfrom infrastructure.core.security import SecurityValidator, RateLimiter, rate_limit from infrastructure.llm.core.sanitization import sanitize_llm_input validator = SecurityValidator() validator.validate_filename(filename) validator.validate_file_path(path) validator.validate_content_size(content_bytes) sanitized = sanitize_llm_input(user_text) @rate_limit(max_requests=10, window_seconds=60) def api_call(): pass
runtime/environment.py)pythonfrom infrastructure.core.runtime.environment import ( check_python_version, check_dependencies, check_build_tools, setup_directories, verify_source_structure, )
files/operations.py)pythonfrom infrastructure.core.files.cleanup import clean_output_directory from infrastructure.core.files.operations import copy_final_deliverables clean_output_directory(output_path) copy_final_deliverables(source, destination)
pipeline/multi_project.py)pythonfrom infrastructure.core.pipeline.multi_project import MultiProjectConfig, MultiProjectOrchestrator config = MultiProjectConfig(projects=["proj_a", "proj_b"]) orchestrator = MultiProjectOrchestrator(config) result = orchestrator.execute_all_projects_core() # or execute_all_projects_full()
runtime/health_check.py)pythonfrom infrastructure.core import SystemHealthChecker checker = SystemHealthChecker() status = checker.get_health_status()
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