CCC / PartsTrader
PartsTrader Monthly Reporting Pipeline & Changed-Only Orchestrator
Monthly reporting orchestrator that uses a stage registry, dependency graph, manifests, dry-run planning, and JSON state to run only the work that needs to be refreshed.
Monthly reporting command view
PartsTrader Monthly Pipeline
Stage registry, dependency graph, changed-only execution, manifests, and run history
Plan
Run request
Detect
Manifests
Resolve
Dependencies
Execute
Stages
Record
JSON history
Stage execution plan
dry-run ready| Stage | Dependency | Mode | Output |
|---|---|---|---|
| Quote | Monthly source | Changed-only | Quote summary |
| Items | Quote stage | Required | Item detail |
| Match | Inventory xref | Conditional | Matched parts |
| Excel | All stages | Publish | Workbook |
Control layer
Monthly reporting flow
Business problem
Monthly PartsTrader reporting required repeatable execution across multiple dependent stages, but running every step manually made the workflow harder to control, review, and scale.
The process needed a smarter orchestration layer that could understand dependencies, detect what changed, support dry-run planning, and rebuild only what was necessary.
System built
Built a CLI-oriented monthly reporting orchestrator with a stage registry, dependency control, changed-only execution, dry-run mode, force rebuild mode, file and folder manifests, optional hashing, JSON state, and run history.
Instead of treating each monthly report as an isolated script, the system turns the reporting workflow into a controlled pipeline with planning, dependency resolution, execution, and state tracking.
Orchestration signals
Signals reviewed
The orchestrator checks run context, dependency needs, input readiness, and prior state before deciding which monthly stages should execute.
Monthly flow
How it works
Plan
Build an execution plan from the requested month, stage registry, rebuild mode, and run options.
The runner determines whether the workflow should operate in changed-only mode, dry-run mode, force rebuild mode, or targeted stage execution.
Detect
Review input manifests, source folders, and output markers to determine what actually needs to run.
Instead of assuming every report needs to rebuild, the pipeline checks file/folder readiness and prior state before committing processing time.
Resolve
Use the stage registry and dependency graph to determine the correct execution order.
Dependent stages can be included automatically so downstream reports are refreshed with the right upstream context.
Execute
Run the selected reporting stages and produce updated artifacts only where needed.
The orchestrator controls stage-level execution, supports rebuild overrides, and keeps the monthly process repeatable.
Record
Write run history, state updates, output markers, and reporting artifacts for future review.
The final layer gives the next run a memory of what happened, what changed, and what can be skipped.
Pipeline layers
What the orchestrator coordinates
Stage registry
Defines the available monthly reporting stages and how each stage should be executed.
Dependency control
Resolves upstream and downstream requirements so the correct stages run in the correct order.
Changed-only logic
Compares current inputs and prior state so unchanged work can be skipped.
Run history
Stores JSON execution records so future runs can be reviewed, repeated, or debugged.
Impact signals
What the pipeline improved
Changed-only execution instead of unnecessary full rebuilds
Dry-run and force rebuild modes for controlled operation
Stage registry and dependency control
JSON state and run history for repeatable reporting
Monthly workbook outputs with stronger orchestration discipline
Operational value
Monthly reporting with more control
Less manual coordination
The monthly process becomes a controlled runner instead of a collection of manually triggered scripts.
More predictable rebuilds
Stages can run based on dependency rules, changed inputs, targeted requests, or force rebuild needs.
Better run visibility
JSON state and output markers make it easier to understand what ran, why it ran, and what was produced.
Reporting scalability
New stages can be added to the registry without redesigning the entire monthly pipeline.
Why this project matters
Monthly reporting turned into a controlled pipeline.
This project moves monthly reporting away from manual script-by-script execution and toward a repeatable orchestration pattern. The runner can plan, detect, resolve dependencies, execute only what is needed, and record run history for the next cycle.
The result is a more maintainable reporting workflow that supports changed-only processing, controlled rebuilds, and scalable stage expansion.
Confidentiality note
Visuals and descriptions are sanitized conceptual representations. They do not expose private company data, customer records, credentials, raw exports, internal pricing, operational screenshots, or proprietary source files.