Clean JSON Toolkitv0.2.0

A support engineer receives a deeply nested customer API response and needs to find exactly where an order status field lives. Using inspect.py they see the full path tree and sample values per path, then query.py with a jq-style path extracts the failing fields without installing jq. This shortens root-cause analysis from hours to minutes.

A platform team maintains base defaults, per-user overrides, and environment-specific settings across separate JSON files. merge.py uses deep or array-concat strategies to produce a single resolved config, and patch.py applies RFC 6902 surgical overrides for hotfixes. This replaces brittle custom merge scripts with a stdlib-only, auditable tool.

A data engineer preprocesses event streams from mobile analytics stored as JSONL. They flatten nested event payloads into dot-notation columns for loading into a warehouse, validate item_type and required fields against a lightweight schema, and query specific fields with --lines output for spot checks. No external dependencies means it runs in restricted environments.

A healthcare data team loads patient JSON records, validates required fields, types, and regex patterns (e.g., patient IDs), then uses patch.py to replace sensitive values before sharing datasets with researchers. Strict exit codes and a no-eval, no-network safety model make it acceptable for regulated environments.

A DevOps engineer runs validate.py and merge.py in CI to compare deployed configurations against expected schema and merged source-of-truth. Non-zero exit code 1 or 2 fails the build when keys are missing or types drift, catching misconfigurations before they reach production.

The open-source toolkit stays free, but a paid cloud service syncs shared schemas, merge profiles, and patch libraries across a team. Developers get the local stdlib tool; teams pay for versioned schema registry and audit trails.

Offer an enterprise license bundling SLAs, security review documentation, FIPS-style audit logs, and priority fixes for regulated industries. The core remains MIT-licensed to preserve community adoption and trust.

Host a browser-based playground where users paste JSON or upload files to run inspect, query, flatten, and merge operations without installing Python. Convert power users into paid API users for programmatic batch operations.