pipekit/CLAUDE.md
Paul Trowbridge 595024eb52 Unify incremental sync config: inline watermarks + editable source query
Watermarks, merge strategy, merge key, and source query are now edited
together in one form on both the module edit page and wizard step 3.
A client-side placeholder warning fires when {name} tokens in the query
don't match the watermark rows on the page. The wizard now shows an
editable source query textarea pre-populated from column picks so WHERE
clauses can be added before module creation. Watermarks submitted via
wm_* arrays are processed by _save_inline_watermarks() in both
module_update and wizard_create.

Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
2026-05-18 21:31:55 -04:00

114 lines
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# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Running the Server
```bash
pipekit serve # default host/port from config.yaml
pipekit serve --host 0.0.0.0 --port 8080 --reload # dev mode with auto-reload
```
The user runs the server themselves in their own terminal — do not nohup or background it.
## Other CLI Commands
```bash
pipekit init # create/upgrade SQLite schema
pipekit doctor # health check (config, jrunner, DB)
pipekit run <module_name> # run a module synchronously (manual test)
pipekit set-password <username> # set HTTP Basic Auth credentials
pipekit secrets set KEY [VALUE] # add/update a secret (prompts if value omitted)
pipekit drivers list # show registered driver kinds
./deploy.sh # idempotent: venv, deps, launcher, driver registration
```
## Architecture
Pipekit is a database sync tool. A **module** defines a source query → dest table sync job. The engine runs a module by: resolving watermarks → materializing source SQL → staging data via jrunner → merging into dest.
**Layers (bottom to top):**
1. **SQLite** (`pipekit.db`) — single file, all state
2. **`repo.py`** — all CRUD for every table; ~1,900 LOC, the only layer that touches the DB
3. **`engine/`** — orchestrates a module run: lock acquisition, watermark resolution, jrunner calls, merge SQL, post-run hooks, run_log write, lock release
4. **jrunner** — external Java CLI; handles all JDBC access. Python never talks to remote DBs directly; it shells out to jrunner
5. **`api/`** — FastAPI REST endpoints under `/api/*`, HTTP Basic Auth (except `/health`)
6. **`web/`** — HTML pages (Jinja2 templates) at `/`; HTMX + Alpine.js for interactivity
## Key Data Model
- **driver** — JDBC driver registration (kind, jar, class, url_template)
- **connection** — named DB connection (jdbc_url, username, password as `$ENV_VAR` reference)
- **module** — sync job (source/dest connection, source query, merge strategy, merge key, enabled, running lock)
- **watermark** — named placeholder with resolver SQL; first column of first row used as opaque string; replaces `{watermark_name}` in source query
- **hook** — post-merge SQL (run_order, run_on: success/failure/always)
- **run_log** — immutable history record with resolved SQL, merge SQL, watermark values, stdout/stderr, timing, live_log (streamed jrunner output written during the run)
## Engine Flow
```
run_module(module_id)
→ atomic UPDATE module SET running=1 WHERE running=0 # fail if already locked
→ for each watermark: run resolver SQL via jrunner → capture first cell # always live, even dry runs
→ materialize source query (simple string replace {name} → value)
→ build merge SQL (engine/merge.py: full=truncate+insert, incremental=delete by key+insert, append=insert)
→ if dry_run: write run_log (status='dry_run'), return early — no data movement
→ DROP + CREATE staging table (pipekit_staging.{module_name}) # self-healing schema drift
→ jrunner migrate source → staging # uses Popen; each stdout line appended to run_log.live_log
→ run merge SQL via jrunner
→ run hooks in order
→ write run_log entry
→ UPDATE module SET running=0 (in finally)
```
## Run Statuses
- `running` — in progress
- `success` — completed, data moved
- `dry_run` — resolved watermarks + built SQL, no data movement
- `error` — failed
- `cancelled` — cancelled mid-run
## Credentials Pattern
Passwords in connections are stored as `$VAR_NAME` references. At run time they are resolved from `/etc/pipekit/secrets.env` (override with `PIPEKIT_SECRETS` env var). Config path override: `PIPEKIT_CONFIG`.
## Driver Abstraction
Each driver in `pipekit/drivers/` inherits from `base.py::Driver` and implements: `browse_fields`, `list_tables`, `list_schemas`, `get_columns`, `map_type`, `default_expression`, `quote_identifier`. The wizard UI calls `/api/introspect/*` which dispatches to the appropriate driver.
## Module Columns
Modules store their column mapping as `columns_json` — a JSON list of dicts with keys `source_name`, `source_type`, `dest_name`, `dest_type`. The engine uses this to build the staging CREATE TABLE and the merge INSERT column lists.
## Inline Watermark Editing
Watermarks are managed inline on both the module edit form and wizard step 3 (not just via the standalone `/watermarks/{id}/edit` page). The module edit form (`module_form.html`) renders existing watermarks as editable rows and submits them as parallel arrays (`wm_id[]`, `wm_name[]`, `wm_connection_id[]`, `wm_resolver_sql[]`, `wm_default_value[]`, `wm_deleted_id[]`). The `_save_inline_watermarks(form, module_id)` helper in `web/app.py` processes these arrays — updates existing rows, creates new ones, deletes removed ones. Both `module_update` and `wizard_create` call it after saving the module. A client-side placeholder warning checks that `{name}` tokens in the source query match the watermark names on the page.
## Merge Key
`merge_key` is stored as a comma-separated string (e.g., `"col1, col2"`). The engine parses it and generates a multi-column DELETE predicate for incremental strategy.
## Staging Table
Recreated on every run as `pipekit_staging.{module_name}` (DROP + CREATE, not IF NOT EXISTS). Ephemeral — exists only during the run.
## API vs. Web
- `/api/*` — JSON REST, HTTP Basic Auth, consumed by HTMX fragments and external callers
- `/` and other bare paths — full HTML pages (Jinja2), no auth currently
- `POST /modules/{id}/run` returns `{run_id}` immediately (both API and web); run is async via BackgroundTasks
- `GET /runs/{id}/live` — HTML fragment endpoint; HTMX polls this every 2 s while status=running to show live_log + status
## Tech Stack
- Python 3.10+, FastAPI, Uvicorn, Jinja2, PyYAML, SQLite3 (stdlib)
- `python-multipart` required for HTML form POSTs (not auto-installed as a FastAPI transitive dep)
- Frontend: HTMX (CDN) + vanilla JS; Alpine.js is NOT loaded despite being listed in older docs
- jrunner: separate Java tool, must be on PATH
## Full Spec
`/opt/pipekit/SPEC.md` is the authoritative design document. Read it for deep rationale on any architectural decision.