Move all Jira-specific code into a self-contained connector module: - 22 files moved via git mv (transform, service, webhook, scripts, systemd units, tests, docs, bin helper) - All imports updated to use connectors.jira.* paths - Jira is now conditional: auto-detected via JIRA_DOMAIN env var - Webapp registers Jira blueprint only when available - Health service monitors Jira timers only when enabled - Profiler loads Jira tables dynamically from filesystem - Sync settings uses config-driven dependency validation - Renamed keboola_platform_url -> custom_url in transform - Updated deploy.sh, sudoers-deploy, backfill_gap.sh paths - Fixed pytest.ini to skip live tests by default |
||
|---|---|---|
| .. | ||
| activate_venv.sh | ||
| backfill_gap.sh | ||
| collect_session.py | ||
| duckdb_manager.py | ||
| generate_user_sync_configs.py | ||
| init.sh | ||
| README.md | ||
| setup_views.sh | ||
| sync_config_template.yaml | ||
| sync_data.sh | ||
| update.sh | ||
Scripts
Helper scripts for working with AI Data Analyst project.
These scripts are synced from the server into server/scripts/ on the analyst's machine.
Available Scripts
setup_views.sh
Initialize or refresh DuckDB views on Parquet files.
bash server/scripts/setup_views.sh
sync_data.sh
Synchronize data from server, upload user files, and refresh DuckDB.
# Recommended: update scripts first, then sync
rsync -avz data-analyst:server/scripts/ ./server/scripts/ # Linux/macOS
scp -r data-analyst:server/scripts/* ./server/scripts/ # Windows fallback
bash server/scripts/sync_data.sh
# Other options:
bash server/scripts/sync_data.sh --dry-run # Preview what would be synced (no changes)
bash server/scripts/sync_data.sh --push # Only upload user/ to server
What sync does:
- Self-update check - detects if sync_data.sh changed, asks to re-run if so
- Downloads
server/docs/,server/scripts/,server/metadata/from server - Updates
CLAUDE.mdfrom latest template - Downloads
server/parquet/data files (with--deleteto remove old files) - Uploads
user/directory to server (backup, no--delete) - Syncs Python environment to server
- Validates DuckDB - if corrupted, deletes and recreates from parquets
- Reinitializes DuckDB views (
CREATE OR REPLACE VIEWfor all tables)
Self-update mechanism: The script checks its own checksum before and after syncing scripts. If it detects it was updated, it exits with a message asking you to run sync again. This ensures you always run the latest sync logic.
DuckDB corruption recovery: If DuckDB file is corrupted (e.g., interrupted sync), it's automatically detected and recreated. All data is safe in parquet files - DuckDB only contains VIEW definitions.
Typical Workflow
- First time setup: Follow bootstrap.yaml instructions
- Before analysis: Sync latest data
bash server/scripts/sync_data.sh - Analyze: Use DuckDB database at
user/duckdb/analytics.duckdb