Datasets:
Formats:
parquet
Languages:
English
Size:
10M - 100M
Tags:
biology
chemistry
drug-discovery
clinical-trials
protein-protein-interaction
gene-essentiality
License:
| """Database connection and migration runner for NegBioDB.""" | |
| import glob | |
| import os | |
| import sqlite3 | |
| from contextlib import contextmanager | |
| from pathlib import Path | |
| _PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent | |
| DEFAULT_DB_PATH = _PROJECT_ROOT / "data" / "negbiodb.db" | |
| DEFAULT_MIGRATIONS_DIR = _PROJECT_ROOT / "migrations" | |
| def get_connection(db_path: str | Path) -> sqlite3.Connection: | |
| """Open a SQLite connection with NegBioDB-standard PRAGMAs. | |
| Sets WAL journal mode and enables foreign key enforcement. | |
| The caller is responsible for closing the connection. | |
| """ | |
| conn = sqlite3.connect(str(db_path)) | |
| conn.execute("PRAGMA journal_mode = WAL") | |
| conn.execute("PRAGMA foreign_keys = ON") | |
| return conn | |
| def connect(db_path: str | Path): | |
| """Context manager for NegBioDB database connections. | |
| Usage: | |
| with connect("data/negbiodb.db") as conn: | |
| conn.execute("SELECT ...") | |
| """ | |
| conn = get_connection(db_path) | |
| try: | |
| yield conn | |
| finally: | |
| conn.close() | |
| def get_applied_versions(conn: sqlite3.Connection) -> set[str]: | |
| """Return the set of migration versions already applied.""" | |
| try: | |
| rows = conn.execute("SELECT version FROM schema_migrations").fetchall() | |
| return {row[0] for row in rows} | |
| except sqlite3.OperationalError: | |
| return set() | |
| def run_migrations(db_path: str | Path, | |
| migrations_dir: str | Path | None = None) -> list[str]: | |
| """Apply pending SQL migrations to the database. | |
| Migrations are .sql files in migrations_dir, sorted by filename prefix. | |
| Version is extracted from filename: "001_initial_schema.sql" -> "001". | |
| Already-applied versions (in schema_migrations) are skipped. | |
| Returns: | |
| List of version strings applied in this run. | |
| """ | |
| if migrations_dir is None: | |
| migrations_dir = DEFAULT_MIGRATIONS_DIR | |
| db_path = Path(db_path) | |
| migrations_dir = Path(migrations_dir) | |
| db_path.parent.mkdir(parents=True, exist_ok=True) | |
| conn = get_connection(db_path) | |
| try: | |
| applied = get_applied_versions(conn) | |
| migration_files = sorted(glob.glob(str(migrations_dir / "*.sql"))) | |
| newly_applied = [] | |
| for mf in migration_files: | |
| version = os.path.basename(mf).split("_")[0] | |
| if version not in applied: | |
| with open(mf) as f: | |
| sql = f.read() | |
| conn.executescript(sql) | |
| newly_applied.append(version) | |
| return newly_applied | |
| finally: | |
| conn.close() | |
| def refresh_all_pairs(conn: sqlite3.Connection) -> int: | |
| """Refresh compound_target_pairs aggregation across ALL sources. | |
| Deletes all existing pairs and re-aggregates from negative_results, | |
| merging cross-source data with best confidence tier and result type | |
| selection. After inserting pairs, computes compound_degree and | |
| target_degree using temp-table joins for performance. | |
| Note: median_pchembl uses AVG (SQLite lacks MEDIAN). This is | |
| acceptable since the column is informational, not used for | |
| thresholding. | |
| """ | |
| conn.execute("DELETE FROM compound_target_pairs") | |
| conn.execute( | |
| """INSERT INTO compound_target_pairs | |
| (compound_id, target_id, num_assays, num_sources, | |
| best_confidence, best_result_type, earliest_year, | |
| median_pchembl, min_activity_value, max_activity_value) | |
| SELECT | |
| compound_id, | |
| target_id, | |
| COUNT(DISTINCT COALESCE(assay_id, -1)), | |
| COUNT(DISTINCT source_db), | |
| CASE MIN(CASE confidence_tier | |
| WHEN 'gold' THEN 1 WHEN 'silver' THEN 2 | |
| WHEN 'bronze' THEN 3 WHEN 'copper' THEN 4 END) | |
| WHEN 1 THEN 'gold' WHEN 2 THEN 'silver' | |
| WHEN 3 THEN 'bronze' WHEN 4 THEN 'copper' END, | |
| CASE | |
| WHEN SUM(CASE WHEN result_type = 'hard_negative' | |
| THEN 1 ELSE 0 END) > 0 | |
| THEN 'hard_negative' | |
| WHEN SUM(CASE WHEN result_type = 'conditional_negative' | |
| THEN 1 ELSE 0 END) > 0 | |
| THEN 'conditional_negative' | |
| WHEN SUM(CASE WHEN result_type = 'methodological_negative' | |
| THEN 1 ELSE 0 END) > 0 | |
| THEN 'methodological_negative' | |
| WHEN SUM(CASE WHEN result_type = 'dose_time_negative' | |
| THEN 1 ELSE 0 END) > 0 | |
| THEN 'dose_time_negative' | |
| ELSE 'hypothesis_negative' | |
| END, | |
| MIN(publication_year), | |
| AVG(pchembl_value), | |
| MIN(activity_value), | |
| MAX(activity_value) | |
| FROM negative_results | |
| GROUP BY compound_id, target_id""" | |
| ) | |
| # Compute compound_degree (number of distinct targets per compound) | |
| conn.execute("DROP TABLE IF EXISTS _cdeg") | |
| conn.execute( | |
| """CREATE TEMP TABLE _cdeg ( | |
| compound_id INTEGER PRIMARY KEY, deg INTEGER)""" | |
| ) | |
| conn.execute( | |
| """INSERT INTO _cdeg | |
| SELECT compound_id, COUNT(DISTINCT target_id) | |
| FROM compound_target_pairs GROUP BY compound_id""" | |
| ) | |
| conn.execute( | |
| """UPDATE compound_target_pairs SET compound_degree = ( | |
| SELECT deg FROM _cdeg d | |
| WHERE d.compound_id = compound_target_pairs.compound_id | |
| )""" | |
| ) | |
| conn.execute("DROP TABLE _cdeg") | |
| # Compute target_degree (number of distinct compounds per target) | |
| conn.execute("DROP TABLE IF EXISTS _tdeg") | |
| conn.execute( | |
| """CREATE TEMP TABLE _tdeg ( | |
| target_id INTEGER PRIMARY KEY, deg INTEGER)""" | |
| ) | |
| conn.execute( | |
| """INSERT INTO _tdeg | |
| SELECT target_id, COUNT(DISTINCT compound_id) | |
| FROM compound_target_pairs GROUP BY target_id""" | |
| ) | |
| conn.execute( | |
| """UPDATE compound_target_pairs SET target_degree = ( | |
| SELECT deg FROM _tdeg d | |
| WHERE d.target_id = compound_target_pairs.target_id | |
| )""" | |
| ) | |
| conn.execute("DROP TABLE _tdeg") | |
| count = conn.execute("SELECT COUNT(*) FROM compound_target_pairs").fetchone()[0] | |
| return count | |
| def create_database(db_path: str | Path | None = None, | |
| migrations_dir: str | Path | None = None) -> Path: | |
| """Create a new NegBioDB database by running all migrations. | |
| Convenience wrapper around run_migrations with sensible defaults. | |
| """ | |
| if db_path is None: | |
| db_path = DEFAULT_DB_PATH | |
| db_path = Path(db_path) | |
| applied = run_migrations(db_path, migrations_dir) | |
| if applied: | |
| print(f"Applied {len(applied)} migration(s): {', '.join(applied)}") | |
| else: | |
| print("Database is up to date (no pending migrations).") | |
| return db_path | |