2026-06-18 10:41:38 +00:00
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[build-system]
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requires = ["setuptools>=61"]
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build-backend = "setuptools.build_meta"
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2026-06-11 17:13:50 +00:00
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[project]
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name = "fleettickets"
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version = "0.1.0"
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description = "Field-ops INC/CRQ ticket ingestion, geocoding, and read-schema for the FleetOps Tickets map"
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requires-python = ">=3.12"
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dependencies = [
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"psycopg2-binary>=2.9.9", # DB driver
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"requests>=2.32.3", # geocoder HTTP
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2026-06-15 17:08:05 +00:00
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"boto3>=1.34", # S3 (rustfs) access — no aws-CLI dependency
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2026-06-11 17:13:50 +00:00
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]
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[project.optional-dependencies]
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dev = [
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"ruff>=0.4",
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]
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feat(crq): add CRQ ingestion via shared engine + thin inc/crq entrypoints
Split the INC-only loader into a dataset-agnostic engine (pipeline.py, renamed
from import_tickets.py) parameterized by a Dataset config, with thin per-type
entrypoints inc/import_inc.py and crq/import_crq.py. CRQ shares INC's identical
32-column source schema and CDC change stream, so the engine is fully shared.
- pipeline.py: Dataset config (name/table/prefixes/key_regex/post_apply); INC
keeps the capture_history post-apply hook, CRQ has none yet. geocode_locations
now unions tickets.crq (geocoding is cross-dataset: one gazetteer/budget).
- crq/import_crq.py: drains automations/crq/changes/ from isptickets into
tickets.crq (data layer + map; SLA/dashboard/history deferred).
- migrations/13_crq_columns.sql: CRQ mirror of 03 — typed STORED generated
columns + indexes on tickets.crq (reuses tickets.eat_ts()).
- Deployment: Dockerfile/run_ingest.sh run both via `python -m`; pyproject
packages inc/crq. Docs (README, implementation, deployment-and-operations,
n8n export ref, phase-1) updated for the split + the one-time CRQ seed runbook.
tickets.crq already exists (mig 01, LIKE tickets.inc) and is unioned into
reporting.fn_tickets_for_map + resolve_ticket_geoms, so CRQ appears on the
existing Tickets map once seeded. Verified locally: ruff-clean new files, engine
lists/parses both streams against live S3 (crq=52 files, inc unaffected).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-25 20:16:38 +00:00
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# Shared engine (pipeline) + helpers as top-level modules, plus the thin per-type
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# entrypoint packages (inc/, crq/). Listed explicitly so `pip install .` works (the
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# Docker image installs the project to pull its deps; runtime runs from /app via -m).
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2026-06-18 10:41:38 +00:00
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[tool.setuptools]
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feat(crq): add CRQ ingestion via shared engine + thin inc/crq entrypoints
Split the INC-only loader into a dataset-agnostic engine (pipeline.py, renamed
from import_tickets.py) parameterized by a Dataset config, with thin per-type
entrypoints inc/import_inc.py and crq/import_crq.py. CRQ shares INC's identical
32-column source schema and CDC change stream, so the engine is fully shared.
- pipeline.py: Dataset config (name/table/prefixes/key_regex/post_apply); INC
keeps the capture_history post-apply hook, CRQ has none yet. geocode_locations
now unions tickets.crq (geocoding is cross-dataset: one gazetteer/budget).
- crq/import_crq.py: drains automations/crq/changes/ from isptickets into
tickets.crq (data layer + map; SLA/dashboard/history deferred).
- migrations/13_crq_columns.sql: CRQ mirror of 03 — typed STORED generated
columns + indexes on tickets.crq (reuses tickets.eat_ts()).
- Deployment: Dockerfile/run_ingest.sh run both via `python -m`; pyproject
packages inc/crq. Docs (README, implementation, deployment-and-operations,
n8n export ref, phase-1) updated for the split + the one-time CRQ seed runbook.
tickets.crq already exists (mig 01, LIKE tickets.inc) and is unioned into
reporting.fn_tickets_for_map + resolve_ticket_geoms, so CRQ appears on the
existing Tickets map once seeded. Verified locally: ruff-clean new files, engine
lists/parses both streams against live S3 (crq=52 files, inc unaffected).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-25 20:16:38 +00:00
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py-modules = ["pipeline", "shared", "run_migrations"]
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packages = ["inc", "crq"]
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2026-06-18 10:41:38 +00:00
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2026-06-11 17:13:50 +00:00
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[tool.uv]
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managed = true
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[tool.ruff]
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target-version = "py312"
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line-length = 100
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lint.select = ["E", "W", "F", "B", "UP"]
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