agnes-the-ai-analyst/tests/test_db_schema_version.py
ZdenekSrotyr f01eb4143d feat(db,repo,renderer): schema v23 + claude_md_template + ClaudeMd renderer
- Bump SCHEMA_VERSION 22 → 23; add claude_md_template singleton table to
  _SYSTEM_SCHEMA and _V22_TO_V23_MIGRATIONS; wire migration + fresh-install seed
- src/repositories/claude_md_template.py: ClaudeMdTemplateRepository (get/set/reset)
  mirroring WelcomeTemplateRepository; defensive re-seed in get()
- src/claude_md.py: compute_default_claude_md / render_claude_md /
  build_claude_md_context — rich renderer with RBAC-filtered tables, metrics,
  and marketplaces; reads override from claude_md_template or falls back to
  config/claude_md_template.txt; raises TemplateError on broken override
- config/claude_md_template.txt: default Jinja2 markdown template restored from
  PR #167 history (tables, metrics, marketplaces, BQ guidance, corporate memory,
  directory structure, per-user footer)
2026-05-03 22:43:56 +02:00

99 lines
3.5 KiB
Python

"""v20 adds source_query column to table_registry.
Backs query_mode='materialized' for BigQuery: admin registers a SQL body
that the scheduler runs through the DuckDB BQ extension and writes as a
parquet to /data/extracts/bigquery/data/<id>.parquet.
The v19 step (#150) drops dataset_permissions, access_requests tables and
users.role, table_registry.is_public columns; v20 then ALTERs the post-v19
table_registry to add the source_query column.
"""
import duckdb
from src.db import SCHEMA_VERSION, _ensure_schema, get_schema_version
def test_schema_version_is_23():
assert SCHEMA_VERSION == 23
def test_v20_adds_source_query(tmp_path):
db_path = tmp_path / "system.duckdb"
conn = duckdb.connect(str(db_path))
_ensure_schema(conn)
cols = {
r[0] for r in conn.execute(
"SELECT column_name FROM information_schema.columns "
"WHERE table_name = 'table_registry'"
).fetchall()
}
assert "source_query" in cols, f"source_query missing from {cols}"
assert get_schema_version(conn) == 23
conn.close()
def test_v23_adds_claude_md_template(tmp_path):
"""v23 must create the claude_md_template singleton table."""
db_path = tmp_path / "system.duckdb"
conn = duckdb.connect(str(db_path))
_ensure_schema(conn)
tables = {
r[0] for r in conn.execute(
"SELECT table_name FROM information_schema.tables "
"WHERE table_schema = 'main'"
).fetchall()
}
assert "claude_md_template" in tables, f"claude_md_template missing from {tables}"
# Singleton row seeded
row = conn.execute("SELECT id, content FROM claude_md_template WHERE id = 1").fetchone()
assert row is not None
assert row[0] == 1
assert row[1] is None # default = no override
conn.close()
def test_v19_db_migrates_to_v20(tmp_path):
"""Pre-existing v19 DB (post-RBAC-drop) without source_query upgrades
cleanly without losing data."""
db_path = tmp_path / "system.duckdb"
conn = duckdb.connect(str(db_path))
# Simulate a v19 DB at minimal but realistic shape: schema_version row +
# a table_registry row in the post-v19 column shape (no is_public column,
# since v19 finalize dropped it via the table-rebuild idiom).
conn.execute(
"CREATE TABLE schema_version (version INTEGER, "
"applied_at TIMESTAMP DEFAULT current_timestamp)"
)
conn.execute("INSERT INTO schema_version (version) VALUES (19)")
conn.execute("""CREATE TABLE table_registry (
id VARCHAR PRIMARY KEY, name VARCHAR NOT NULL,
source_type VARCHAR, bucket VARCHAR, source_table VARCHAR,
sync_strategy VARCHAR DEFAULT 'full_refresh',
query_mode VARCHAR DEFAULT 'local',
sync_schedule VARCHAR, profile_after_sync BOOLEAN DEFAULT true,
primary_key VARCHAR, folder VARCHAR, description TEXT,
registered_by VARCHAR,
registered_at TIMESTAMP DEFAULT current_timestamp
)""")
conn.execute("INSERT INTO table_registry (id, name) VALUES ('foo', 'foo')")
_ensure_schema(conn)
assert get_schema_version(conn) == 23
cols = {
r[0] for r in conn.execute(
"SELECT column_name FROM information_schema.columns "
"WHERE table_name = 'table_registry'"
).fetchall()
}
assert "source_query" in cols
# Existing row preserved, new column NULL
row = conn.execute(
"SELECT id, source_query FROM table_registry WHERE id='foo'"
).fetchone()
assert row == ("foo", None)
conn.close()