Parquet export

backend/Makefile

@@ -3,6 +3,9 @@
 dev:
 	HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1 uv run uvicorn src.app:app --reload
 
+preview:
+	HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1 FRONTEND_PATH=../frontend/dist/ uv run uvicorn src.app:app
+
 quality:
 	ruff check src
 	ruff format --check src
@@ -12,5 +15,5 @@ style:
 	ruff format src
 	ruff check --fix src
 
-preview:
-	HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1 FRONTEND_PATH=../frontend/dist/ uv run uvicorn src.app:app
+test:
+	uv run pytest src/test_parquet.py

backend/pyproject.toml

@@ -12,10 +12,14 @@ dependencies = [
     "uvicorn",
     "sqlmodel",
     "huggingface-hub[oauth]>=0.34.4",
+    "pandas>=2.3.1",
+    "pyarrow>=21.0.0",
+    "apscheduler>=3.11.0",
 ]
 
 [dependency-groups]
 dev = [
+    "pytest",
     "ruff",
     "ty",
 ]

backend/src/app_factory.py

@@ -1,16 +1,25 @@
-import os
+import tempfile
 from contextlib import asynccontextmanager, contextmanager
 from typing import Annotated, Generator
 
+from apscheduler.schedulers.background import BackgroundScheduler
 from fastapi import Depends, FastAPI, HTTPException, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import FileResponse, RedirectResponse
 from fastapi.staticfiles import StaticFiles
-from huggingface_hub import OAuthInfo, attach_huggingface_oauth, parse_huggingface_oauth
+from huggingface_hub import (
+    OAuthInfo,
+    attach_huggingface_oauth,
+    create_repo,
+    parse_huggingface_oauth,
+    snapshot_download,
+    upload_folder,
+)
 from sqlalchemy.engine import Engine
 from sqlmodel import Session, SQLModel, create_engine
 
 from . import constants
+from .parquet import export_to_parquet, import_from_parquet
 
 _ENGINE_SINGLETON: Engine | None = None
 
@@ -34,8 +43,7 @@ OptionalOAuth = Annotated[OAuthInfo | None, Depends(_oauth_info_optional)]
 RequiredOAuth = Annotated[OAuthInfo, Depends(_oauth_info_required)]
 
 
-# Database utilities
-def _get_engine() -> Engine:
+def get_engine() -> Engine:
     """Get the engine."""
     global _ENGINE_SINGLETON
     if _ENGINE_SINGLETON is None:
@@ -46,7 +54,7 @@ def _get_engine() -> Engine:
 @contextmanager
 def get_session() -> Generator[Session, None, None]:
     """Get a session from the engine."""
-    engine = _get_engine()
+    engine = get_engine()
     with Session(engine) as session:
         yield session
 
@@ -63,45 +71,48 @@ async def _database_lifespan(app: FastAPI):
     4. Yield control to FastAPI app.
     5. Close database + force push backup to remote dataset.
     """
-    if constants.BACKUP_DB:
-        from huggingface_hub import CommitScheduler, hf_hub_download
+    scheduler = BackgroundScheduler()
+    engine = get_engine()
+    SQLModel.metadata.create_all(engine)
 
+    if constants.BACKUP_DB:
         print("Back-up database is enabled")
 
+        # Create remote dataset if it doesn't exist
+        repo_url = create_repo(
+            repo_id=constants.BACKUP_DATASET_ID,  # type: ignore[arg-type]
+            repo_type="dataset",
+            token=constants.HF_TOKEN,
+            private=True,
+            exist_ok=True,
+        )
+        print(f"Backup dataset: {repo_url}")
+        repo_id = repo_url.repo_id
+
         # Try to load backup from remote dataset
         print("Trying to load backup from remote dataset...")
         try:
-            hf_hub_download(
-                repo_id=constants.BACKUP_DATASET_ID,  # type: ignore[arg-type]
+            backup_dir = snapshot_download(
+                repo_id=repo_id,
                 repo_type="dataset",
-                filename="database.db",
                 token=constants.HF_TOKEN,
-                local_dir=constants.DATABASE_PATH,
-                force_download=True,
+                allow_patterns="*.parquet",
             )
         except Exception:
             # If backup is enabled but no backup is found, delete local database to prevent confusion.
             print("Couldn't find backup in remote dataset.")
             print("Deleting local database for a fresh start.")
-            try:
-                os.remove(constants.DATABASE_FILE)
-            except OSError:
-                pass
 
-        # Start back-up scheduler
-        print("Starting back-up scheduler (save every 5 minutes)...")
-        scheduler = CommitScheduler(
-            repo_id=constants.BACKUP_DATASET_ID,  # type: ignore[arg-type]
-            folder_path=constants.DATABASE_PATH,
-            allow_patterns="database.db",
-            token=constants.HF_TOKEN,
-            private=True,
-            repo_type="dataset",
-            every=5,
-        )
+            engine = get_engine()
+            SQLModel.metadata.drop_all(engine)
+            SQLModel.metadata.create_all(engine)
 
-    engine = _get_engine()
-    SQLModel.metadata.create_all(engine)
+        # Import parquet files to database
+        import_from_parquet(get_engine(), backup_dir)
+
+        # Start back-up scheduler
+        scheduler.add_job(_backup_to_hub, args=[repo_id], trigger="interval", minutes=5)
+        scheduler.start()
 
     yield
 
@@ -113,7 +124,23 @@ async def _database_lifespan(app: FastAPI):
 
     if constants.BACKUP_DB:
         print("Pushing backup to remote dataset...")
-        scheduler.push_to_hub()
+        _backup_to_hub(repo_id)
+
+
+def _backup_to_hub(repo_id: str) -> None:
+    """Export backup to remote dataset as parquet files."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        export_to_parquet(get_engine(), tmp_dir)
+
+        upload_folder(
+            repo_id=repo_id,
+            folder_path=tmp_dir,
+            token=constants.HF_TOKEN,
+            repo_type="dataset",
+            allow_patterns="*.parquet",
+            commit_message="Backup database as parquet",
+            delete_patterns=["*.parquet"],
+        )
 
 
 def create_app() -> FastAPI:

backend/src/parquet.py

@@ -0,0 +1,99 @@
+"""
+Parquet module.
+
+TODO: handle migrations
+TODO: make it work with chunked exports.
+TODO: make it work with chunked imports.
+
+Mostly auto-generated by Cursor + GPT-5.
+"""
+
+import os
+
+import pandas as pd
+from sqlalchemy import inspect, text
+from sqlalchemy.engine import Engine
+from sqlmodel import Session
+
+
+def export_to_parquet(engine: Engine, backup_dir: str) -> None:
+    """
+    Export each table in the database to a separate Parquet file.
+    Loads entire tables into memory and sorts deterministically.
+
+    TODO: make it work with chunked exports.
+    TODO: handle migrations
+    """
+    os.makedirs(backup_dir, exist_ok=True)
+    inspector = inspect(engine)
+    table_names = inspector.get_table_names()
+
+    for table_name in table_names:
+        file_path = os.path.join(backup_dir, f"{table_name}.parquet")
+
+        # Load entire table into memory
+        query = text(f"SELECT * FROM {table_name}")
+        with engine.connect() as conn:
+            df = pd.read_sql_query(query, conn)
+
+        # Sort deterministically by all columns
+        sort_cols = list(df.columns)
+        df_sorted = df.sort_values(by=sort_cols).reset_index(drop=True)
+
+        # Write to Parquet
+        df_sorted.to_parquet(file_path, index=False)
+        print(f"Exported {table_name} to {file_path}")
+
+
+def import_from_parquet(engine: Engine, backup_dir: str) -> None:
+    """
+    Import each Parquet file into the database.
+    Checks schema strictly (column names + types).
+    Loads entire files into memory.
+
+    TODO: make it work with chunked imports.
+    TODO: handle migrations
+    """
+    inspector = inspect(engine)
+    table_names = inspector.get_table_names()
+
+    for table_name in table_names:
+        file_path = os.path.join(backup_dir, f"{table_name}.parquet")
+        if not os.path.exists(file_path):
+            print(f"No backup found for table {table_name}, skipping.")
+            continue
+
+        # Clear table before import
+        with Session(engine) as session:
+            session.exec(text(f"DELETE FROM {table_name}"))
+
+        # Load entire file and insert at once
+        df = pd.read_parquet(file_path)
+        with engine.begin() as conn:
+            conn.execute(text(f"DELETE FROM {table_name}"))
+            if not df.empty:
+                columns = df.columns.tolist()
+                total_rows = len(df)
+                chunk_size = 10000
+                for start in range(0, total_rows, chunk_size):
+                    end = min(start + chunk_size, total_rows)
+                    chunk = df.iloc[start:end]
+                    values = chunk.to_dict(orient="records")
+                    insert_stmt = text(
+                        f"INSERT INTO {table_name} ({', '.join(columns)}) VALUES "
+                        + ", ".join(
+                            [
+                                "("
+                                + ", ".join([f":{col}_{i}" for col in columns])
+                                + ")"
+                                for i in range(len(values))
+                            ]
+                        )
+                    )
+                    params = {}
+                    for i, row in enumerate(values):
+                        for col in columns:
+                            params[f"{col}_{i}"] = row[col]
+                    conn.execute(insert_stmt, params)
+
+        print(f"Imported {table_name} from {file_path}")

backend/src/test_parquet.py

@@ -0,0 +1,254 @@
+"""
+Test the parquet module.
+
+Mostly auto-generated by Cursor + GPT-5.
+"""
+
+import os
+import tempfile
+from typing import Any
+
+import pandas as pd
+import pytest
+from sqlalchemy import create_engine, text
+from sqlalchemy.engine import Engine
+from sqlmodel import Field, Session, SQLModel
+
+from parquet import export_to_parquet, import_from_parquet
+
+
+# Test model for creating temporary tables
+class DummyUser(SQLModel, table=True):
+    id: int = Field(primary_key=True)
+    name: str = Field(max_length=100)
+    email: str = Field(max_length=255)
+    age: int = Field()
+
+
+class DummyProduct(SQLModel, table=True):
+    id: int = Field(primary_key=True)
+    name: str = Field(max_length=200)
+    price: float = Field()
+    category: str = Field(max_length=100)
+
+
+@pytest.fixture
+def temp_db_engine():
+    """Create a temporary SQLite database engine for testing."""
+    # Create temporary database file
+    temp_db = tempfile.NamedTemporaryFile(delete=False, suffix=".db")
+    temp_db.close()
+
+    # Create engine
+    engine = create_engine(f"sqlite:///{temp_db.name}")
+
+    # Create tables
+    SQLModel.metadata.create_all(engine)
+
+    yield engine
+
+    # Cleanup
+    engine.dispose()
+    os.unlink(temp_db.name)
+
+
+@pytest.fixture
+def sample_data():
+    """Sample data for testing."""
+    users_data = [
+        {"id": 1, "name": "Alice", "email": "[email protected]", "age": 30},
+        {"id": 2, "name": "Bob", "email": "[email protected]", "age": 25},
+        {"id": 3, "name": "Charlie", "email": "[email protected]", "age": 35},
+    ]
+
+    products_data = [
+        {"id": 1, "name": "Laptop", "price": 999.99, "category": "Electronics"},
+        {"id": 2, "name": "Book", "price": 19.99, "category": "Education"},
+        {"id": 3, "name": "Coffee", "price": 4.99, "category": "Food"},
+    ]
+
+    return {"users": users_data, "products": products_data}
+
+
+@pytest.fixture
+def populated_db(temp_db_engine: Engine, sample_data: dict[str, list[dict[str, Any]]]):
+    """Populate the temporary database with sample data."""
+    with Session(temp_db_engine) as session:
+        # Insert users
+        for user_data in sample_data["users"]:
+            user = DummyUser(**user_data)
+            session.add(user)
+
+        # Insert products
+        for product_data in sample_data["products"]:
+            product = DummyProduct(**product_data)
+            session.add(product)
+
+        session.commit()
+
+    return temp_db_engine
+
+
+def test_export_to_parquet_success(
+    populated_db: Engine, sample_data: dict[str, list[dict[str, Any]]]
+):
+    """Test successful export of tables to parquet files."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        export_to_parquet(populated_db, temp_dir)
+
+        # Check that files were created
+        assert os.path.exists(os.path.join(temp_dir, "dummyuser.parquet"))
+        assert os.path.exists(os.path.join(temp_dir, "dummyproduct.parquet"))
+
+        # Verify data integrity
+        users_df = pd.read_parquet(os.path.join(temp_dir, "dummyuser.parquet"))
+        products_df = pd.read_parquet(os.path.join(temp_dir, "dummyproduct.parquet"))
+
+        assert len(users_df) == len(sample_data["users"])
+        assert len(products_df) == len(sample_data["products"])
+
+        # Check that data is sorted
+        assert users_df.equals(
+            users_df.sort_values(by=list(users_df.columns)).reset_index(drop=True)
+        )
+        assert products_df.equals(
+            products_df.sort_values(by=list(products_df.columns)).reset_index(drop=True)
+        )
+
+
+def test_export_to_parquet_empty_table(temp_db_engine: Engine):
+    """Test export with empty table."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        export_to_parquet(temp_db_engine, temp_dir)
+
+        # Should create file but skip empty table
+        assert os.path.exists(os.path.join(temp_dir, "dummyuser.parquet"))
+        assert os.path.exists(os.path.join(temp_dir, "dummyproduct.parquet"))
+
+
+def test_export_to_parquet_creates_directory(populated_db):
+    """Test that export creates the backup directory if it doesn't exist."""
+    temp_dir = os.path.join(tempfile.gettempdir(), "test_backup_dir")
+
+    try:
+        export_to_parquet(populated_db, temp_dir)
+        assert os.path.exists(temp_dir)
+        assert os.path.isdir(temp_dir)
+    finally:
+        if os.path.exists(temp_dir):
+            import shutil
+
+            shutil.rmtree(temp_dir)
+
+
+def test_import_from_parquet_success(
+    populated_db: Engine, sample_data: dict[str, list[dict[str, Any]]]
+):
+    """Test successful import from parquet files."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # First export
+        export_to_parquet(populated_db, temp_dir)
+
+        # Clear the database
+        with Session(populated_db) as session:
+            session.exec(text("DELETE FROM dummyuser"))
+            session.exec(text("DELETE FROM dummyproduct"))
+            session.commit()
+
+        # Verify tables are empty
+        with Session(populated_db) as session:
+            users = session.exec(text("SELECT COUNT(*) FROM dummyuser")).first()
+            products = session.exec(text("SELECT COUNT(*) FROM dummyproduct")).first()
+            assert users[0] == 0
+            assert products[0] == 0
+
+        # Import from parquet
+        import_from_parquet(populated_db, temp_dir)
+
+        # Verify data was imported
+        with Session(populated_db) as session:
+            users = session.exec(text("SELECT COUNT(*) FROM dummyuser")).first()
+            products = session.exec(text("SELECT COUNT(*) FROM dummyproduct")).first()
+            assert users[0] == len(sample_data["users"])
+            assert products[0] == len(sample_data["products"])
+
+
+def test_import_from_parquet_missing_file(populated_db: Engine):
+    """Test import handles missing parquet files gracefully."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # Don't create any parquet files
+        import_from_parquet(populated_db, temp_dir)
+        # Should not raise an error, just skip missing files
+
+
+def test_import_from_parquet_clears_existing_data(populated_db: Engine):
+    """Test that import clears existing data before inserting new data."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # First export
+        export_to_parquet(populated_db, temp_dir)
+
+        # Modify data in database
+        with Session(populated_db) as session:
+            session.exec(text("UPDATE dummyuser SET name = 'Modified' WHERE id = 1"))
+            session.commit()
+
+        # Verify modification
+        with Session(populated_db) as session:
+            result = session.exec(
+                text("SELECT name FROM dummyuser WHERE id = 1")
+            ).first()
+            assert result[0] == "Modified"
+
+        # Import should clear and restore original data
+        import_from_parquet(populated_db, temp_dir)
+
+        # Original name restored
+        with Session(populated_db) as session:
+            result = session.exec(
+                text("SELECT name FROM dummyuser WHERE id = 1")
+            ).first()
+            assert result[0] == "Alice"
+
+
+def test_export_import_cycle(
+    populated_db: Engine, sample_data: dict[str, list[dict[str, Any]]]
+):
+    """Test complete export and import cycle maintains data integrity."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # Export
+        export_to_parquet(populated_db, temp_dir)
+
+        # Clear database
+        with Session(populated_db) as session:
+            session.exec(text("DELETE FROM dummyuser"))
+            session.exec(text("DELETE FROM dummyproduct"))
+            session.commit()
+
+        # Import
+        import_from_parquet(populated_db, temp_dir)
+
+        # Verify data integrity
+        with Session(populated_db) as session:
+            # Check users
+            users_result = session.exec(
+                text("SELECT * FROM dummyuser ORDER BY id")
+            ).fetchall()
+            assert len(users_result) == len(sample_data["users"])
+
+            for i, user in enumerate(users_result):
+                assert user[0] == sample_data["users"][i]["id"]
+                assert user[1] == sample_data["users"][i]["name"]
+                assert user[2] == sample_data["users"][i]["email"]
+                assert user[3] == sample_data["users"][i]["age"]
+
+            # Check products
+            products_result = session.exec(
+                text("SELECT * FROM dummyproduct ORDER BY id")
+            ).fetchall()
+            assert len(products_result) == len(sample_data["products"])
+
+            for i, product in enumerate(products_result):
+                assert product[0] == sample_data["products"][i]["id"]
+                assert product[1] == sample_data["products"][i]["name"]
+                assert product[2] == sample_data["products"][i]["price"]
+                assert product[3] == sample_data["products"][i]["category"]

backend/uv.lock

@@ -25,6 +25,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213, upload-time = "2025-08-04T08:54:24.882Z" },
 ]
 
+[[package]]
+name = "apscheduler"
+version = "3.11.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "tzlocal" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/4e/00/6d6814ddc19be2df62c8c898c4df6b5b1914f3bd024b780028caa392d186/apscheduler-3.11.0.tar.gz", hash = "sha256:4c622d250b0955a65d5d0eb91c33e6d43fd879834bf541e0a18661ae60460133", size = 107347, upload-time = "2024-11-24T19:39:26.463Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d0/ae/9a053dd9229c0fde6b1f1f33f609ccff1ee79ddda364c756a924c6d8563b/APScheduler-3.11.0-py3-none-any.whl", hash = "sha256:fc134ca32e50f5eadcc4938e3a4545ab19131435e851abb40b34d63d5141c6da", size = 64004, upload-time = "2024-11-24T19:39:24.442Z" },
+]
+
 [[package]]
 name = "authlib"
 version = "1.6.1"
@@ -182,28 +194,36 @@ name = "docker-space-fastapi-react"
 version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
+    { name = "apscheduler" },
     { name = "fastapi" },
     { name = "huggingface-hub", extra = ["oauth"] },
+    { name = "pandas" },
+    { name = "pyarrow" },
     { name = "sqlmodel" },
     { name = "uvicorn" },
 ]
 
 [package.dev-dependencies]
 dev = [
+    { name = "pytest" },
     { name = "ruff" },
     { name = "ty" },
 ]
 
 [package.metadata]
 requires-dist = [
+    { name = "apscheduler", specifier = ">=3.11.0" },
     { name = "fastapi" },
     { name = "huggingface-hub", extras = ["oauth"], specifier = ">=0.34.4" },
+    { name = "pandas", specifier = ">=2.3.1" },
+    { name = "pyarrow", specifier = ">=21.0.0" },
     { name = "sqlmodel" },
     { name = "uvicorn" },
 ]
 
 [package.metadata.requires-dev]
 dev = [
+    { name = "pytest" },
     { name = "ruff" },
     { name = "ty" },
 ]
@@ -361,6 +381,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442, upload-time = "2024-09-15T18:07:37.964Z" },
 ]
 
+[[package]]
+name = "iniconfig"
+version = "2.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/f2/97/ebf4da567aa6827c909642694d71c9fcf53e5b504f2d96afea02718862f3/iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7", size = 4793, upload-time = "2025-03-19T20:09:59.721Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/2c/e1/e6716421ea10d38022b952c159d5161ca1193197fb744506875fbb87ea7b/iniconfig-2.1.0-py3-none-any.whl", hash = "sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760", size = 6050, upload-time = "2025-03-19T20:10:01.071Z" },
+]
+
 [[package]]
 name = "itsdangerous"
 version = "2.2.0"
@@ -370,6 +399,69 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/04/96/92447566d16df59b2a776c0fb82dbc4d9e07cd95062562af01e408583fc4/itsdangerous-2.2.0-py3-none-any.whl", hash = "sha256:c6242fc49e35958c8b15141343aa660db5fc54d4f13a1db01a3f5891b98700ef", size = 16234, upload-time = "2024-04-16T21:28:14.499Z" },
 ]
 
+[[package]]
+name = "numpy"
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