diff --git a/.gitignore b/.gitignore index 0fda688..f340fe4 100644 --- a/.gitignore +++ b/.gitignore @@ -1,7 +1,7 @@ **/.DS_Store # Temp -preparation/ +/preparation/ # Binder .bash_logout @@ -152,3 +152,9 @@ dmypy.json *_spark/ *_pipeline/ .vscode/ + +# LLMs +copilot-instructions.md +CLAUDE.md +.claude +.mcp.json \ No newline at end of file diff --git a/integration/snowflake/data/__init__.py b/integration/snowflake/data/__init__.py new file mode 100644 index 0000000..7238cc1 --- /dev/null +++ b/integration/snowflake/data/__init__.py @@ -0,0 +1,48 @@ +"""Data operations for getML Feature Store integration with Snowflake. + +When settings are provided to data loading and preparation functions, +infrastructure (warehouse, database) is automatically bootstrapped if needed. + +Usage example: + from data import ( + SnowflakeSettings, + create_session, + ingestion, + ) + + settings = SnowflakeSettings.from_env() + + with create_session(settings) as session: + ingestion.load_from_gcs(session, settings=settings) +""" + +from snowflake.snowpark.exceptions import SnowparkSessionException + +from ._bootstrap import ( + BootstrapError, + ensure_infrastructure, +) +from ._settings import SnowflakeSettings +from ._snowflake_session import create_session +from ._sql_loader import load_sql +from .ingestion import ( + DEFAULT_GCS_BUCKET, + JAFFLE_SHOP_TABLE_NAMES, + DataIngestionError, + load_from_gcs, + load_from_s3, +) + +__all__ = [ + "DEFAULT_GCS_BUCKET", + "JAFFLE_SHOP_TABLE_NAMES", + "BootstrapError", + "DataIngestionError", + "SnowflakeSettings", + "SnowparkSessionException", + "create_session", + "ensure_infrastructure", + "load_from_gcs", + "load_from_s3", + "load_sql", +] diff --git a/integration/snowflake/data/_bootstrap.py b/integration/snowflake/data/_bootstrap.py new file mode 100644 index 0000000..36e407f --- /dev/null +++ b/integration/snowflake/data/_bootstrap.py @@ -0,0 +1,182 @@ +"""Bootstrap Snowflake infrastructure for the Jaffle Shop dataset. + +Creates the required warehouse and database. +All operations are idempotent using CREATE ... IF NOT EXISTS. + +The main entry point is `ensure_infrastructure()` which auto-detects and creates +missing resources. It is called automatically by data loading functions when +settings are provided. + +Usage example: + from data import SnowflakeSettings, create_session, ensure_infrastructure + + settings = SnowflakeSettings.from_env() + + with create_session(settings) as session: + ensure_infrastructure(session, settings) + # Warehouse and database are now guaranteed to exist +""" + +# ruff: noqa: G004 + +from __future__ import annotations + +import logging + +from snowflake.snowpark import Row, Session +from snowflake.snowpark.exceptions import SnowparkSQLException + +from ._settings import SnowflakeSettings +from ._sql_loader import load_sql + +logger: logging.Logger = logging.getLogger(__name__) + +WAREHOUSE_SIZE = "X-SMALL" +AUTO_SUSPEND_SECONDS = 60 + + +class BootstrapError(Exception): + """Raised when bootstrap operations fail.""" + + +# ============================================================================= +# Internal Helpers +# ============================================================================= + + +def _warehouse_exists(session: Session, warehouse_name: str) -> bool: + """Check if a warehouse exists. + + Args: + session: Active Snowflake Snowpark session. + warehouse_name: Name of the warehouse to check. + + Returns: + True if warehouse exists, False otherwise. + """ + try: + rows: list[Row] = session.sql( + f"SHOW WAREHOUSES LIKE '{warehouse_name}'" + ).collect() + return len(rows) > 0 + except SnowparkSQLException: + return False + + +def _database_exists(session: Session, database_name: str) -> bool: + """Check if a database exists. + + Args: + session: Active Snowflake Snowpark session. + database_name: Name of the database to check. + + Returns: + True if database exists, False otherwise. + """ + try: + rows: list[Row] = session.sql( + f"SHOW DATABASES LIKE '{database_name}'" + ).collect() + return len(rows) > 0 + except SnowparkSQLException: + return False + + +# ============================================================================= +# Core Bootstrap Functions +# ============================================================================= + + +def ensure_infrastructure( + session: Session, + settings: SnowflakeSettings, +) -> None: + """Ensure warehouse and database exist, creating if missing. + + This is the main entry point for auto-bootstrapping. It checks if the + warehouse and database specified in settings exist, and creates them + if they don't. All operations are idempotent. + + Args: + session: Active Snowflake Snowpark session. + settings: Settings containing warehouse and database names. + + Raises: + BootstrapError: If required settings are missing or if resource + creation fails (e.g., due to insufficient privileges). + + Example: + from data import SnowflakeSettings, create_session, ensure_infrastructure + + settings = SnowflakeSettings.from_env() + with create_session(settings) as session: + ensure_infrastructure(session, settings) + # Warehouse and database are now guaranteed to exist + """ + if not settings.warehouse: + raise BootstrapError("warehouse must be specified in settings for bootstrap") + if not settings.database: + raise BootstrapError("database must be specified in settings for bootstrap") + + warehouse_ready = _warehouse_exists(session, settings.warehouse) + database_ready = _database_exists(session, settings.database) + + if warehouse_ready and database_ready: + logger.debug( + "Infrastructure already exists: warehouse=%s, database=%s", + settings.warehouse, + settings.database, + ) + return + + try: + if not warehouse_ready: + _create_warehouse(session, warehouse_name=settings.warehouse) + if not database_ready: + _create_database(session, database_name=settings.database) + logger.info("Snowflake infrastructure ready") + except Exception as e: + raise BootstrapError( + "Cannot create Snowflake infrastructure. " + "Your current role may lack CREATE WAREHOUSE or CREATE DATABASE " + "privilege.\n\n" + "Options:\n" + " 1. Ask an administrator to create the warehouse and database\n" + " 2. Switch to a role with CREATE WAREHOUSE/DATABASE privilege " + "(e.g., ACCOUNTADMIN)\n" + " 3. Create resources manually before running the pipeline\n\n" + f"Original error: {e}" + ) from e + + +def _create_warehouse(session: Session, warehouse_name: str) -> None: + """Create warehouse with X-SMALL size and auto-suspend enabled.""" + logger.info(f"Creating warehouse '{warehouse_name}' if not exists...") + + sql: str = load_sql( + path="bootstrap/create_warehouse.sql", + warehouse_name=warehouse_name, + warehouse_size=WAREHOUSE_SIZE, + auto_suspend_seconds=str(AUTO_SUSPEND_SECONDS), + ) + _ = session.sql(query=sql).collect() + + logger.info(f"✓ Warehouse '{warehouse_name}' ready") + + +def _create_database(session: Session, database_name: str) -> None: + """Create database if it doesn't exist.""" + logger.info(f"Creating database '{database_name}' if not exists...") + + sql: str = load_sql( + path="bootstrap/create_database.sql", database_name=database_name + ) + _ = session.sql(query=sql).collect() + + logger.info(f"✓ Database '{database_name}' ready") + + +__all__ = [ + "BootstrapError", + "ensure_infrastructure", +] diff --git a/integration/snowflake/data/_settings.py b/integration/snowflake/data/_settings.py new file mode 100644 index 0000000..cc25ffe --- /dev/null +++ b/integration/snowflake/data/_settings.py @@ -0,0 +1,53 @@ +"""Snowflake authentication and connection settings. + +Provides typed configuration that automatically loads from environment +variables with the SNOWFLAKE_ prefix. + +Usage example: + from data import SnowflakeSettings, create_session + + # Auto-loads from SNOWFLAKE_* environment variables + settings = SnowflakeSettings.from_env() + + with create_session(settings) as session: + session.sql("SELECT 1").collect() +""" + +from typing import ClassVar, Self + +from pydantic import Field, SecretStr +from pydantic_settings import BaseSettings, SettingsConfigDict + + +class SnowflakeSettings(BaseSettings): + """Settings for Snowflake operations. + + Core fields (account, user, password, role) are required for all connections. + Optional fields (warehouse, database, schema_name) can be omitted for + administrative operations like creating warehouses or databases. + """ + + model_config: ClassVar[SettingsConfigDict] = SettingsConfigDict( + env_prefix="SNOWFLAKE_", + case_sensitive=False, + ) + + account: str + user: str + password: SecretStr + role: str + warehouse: str + database: str + # Can't use field name "schema" (Pydantic reserved); + # validation_alias maps standard SNOWFLAKE_SCHEMA env var to this field + schema_name: str = Field( + validation_alias="SNOWFLAKE_SCHEMA", + ) + + @classmethod + def from_env(cls) -> Self: + """Create settings instance from environment variables. + + Loads configuration from SNOWFLAKE_* environment variables. + """ + return cls.model_validate({}) diff --git a/integration/snowflake/data/_snowflake_session.py b/integration/snowflake/data/_snowflake_session.py new file mode 100644 index 0000000..cf66fe7 --- /dev/null +++ b/integration/snowflake/data/_snowflake_session.py @@ -0,0 +1,54 @@ +"""Snowflake session management for getML Feature Store integration. + +This module provides a factory function for creating Snowflake Snowpark sessions. +Sessions support the context manager protocol for automatic cleanup. + +Usage example: + from data import SnowflakeSettings, create_session + + with create_session(SnowflakeSettings.from_env()) as session: + session.sql("SELECT * FROM mytable").collect() +""" + +import logging + +from snowflake.snowpark import Session +from snowflake.snowpark.exceptions import SnowparkSessionException + +from ._settings import SnowflakeSettings + +logger: logging.Logger = logging.getLogger(__name__) + + +def create_session(settings: SnowflakeSettings) -> Session: + """Create a Snowflake Snowpark session. + + Connects using the provided settings. + + Raises: + SnowparkSessionException: If connection to Snowflake fails. + """ + connection_params: dict[str, str | int] = { + "account": settings.account, + "user": settings.user, + "password": settings.password.get_secret_value(), + "role": settings.role, + "warehouse": settings.warehouse, + "database": settings.database, + "schema": settings.schema_name, + } + + return _establish_session(connection_params) + + +def _establish_session(connection_params: dict[str, str | int]) -> Session: + """Create a Snowpark session with the given parameters.""" + try: + return Session.builder.configs(connection_params).create() + except Exception as e: + raise SnowparkSessionException( + f"Failed to create Snowflake session. " + f"Account: {connection_params.get('account')}, " + f"User: {connection_params.get('user')}. " + f"Error: {e}" + ) from e diff --git a/integration/snowflake/data/_sql_loader.py b/integration/snowflake/data/_sql_loader.py new file mode 100644 index 0000000..5763895 --- /dev/null +++ b/integration/snowflake/data/_sql_loader.py @@ -0,0 +1,40 @@ +"""SQL file loading utilities. + +This module provides utilities for loading and formatting SQL queries +from the data/sql/ directory. + +Usage example: + from data import load_sql + + sql = load_sql("ingestion/create_schema.sql", schema_name="RAW") +""" + +from __future__ import annotations + +from pathlib import Path + +_SQL_DIR = Path(__file__).parent / "sql" + + +def load_sql(path: str, **kwargs: str) -> str: + """Load SQL query from file with optional parameter substitution. + + Loads SQL content from data/sql/{path} and applies string formatting + if keyword arguments are provided. + + Args: + path: Relative path to SQL file within data/sql/ directory + (e.g., "ingestion/load_stores.sql"). + **kwargs: Named parameters to substitute in the SQL using .format(). + + Raises: + FileNotFoundError: If the SQL file does not exist. + KeyError: If a placeholder in the SQL file is not provided in kwargs. + """ + sql_file: Path = _SQL_DIR / path + content: str = sql_file.read_text() + + if kwargs: + return content.format(**kwargs) + + return content diff --git a/integration/snowflake/data/ingestion.py b/integration/snowflake/data/ingestion.py new file mode 100644 index 0000000..4a54249 --- /dev/null +++ b/integration/snowflake/data/ingestion.py @@ -0,0 +1,442 @@ +"""Data ingestion from cloud storage to Snowflake for the Jaffle Shop dataset. + +This module loads Parquet data from GCS or S3 buckets into Snowflake. + +For GCS: +- Downloads files via HTTPS to a local cache (~/.cache/getml/jaffle_shop/) +- Uploads to an internal Snowflake stage using session.file.put() +- No GCP credentials or storage integration required + +For S3: +- Uses external staging with COPY INTO commands +- Public S3 buckets work without credentials + +When settings are provided, the module auto-bootstraps required infrastructure +(warehouse and database) if they don't exist. + +Usage example: + from data import ( + SnowflakeSettings, + create_session, + load_from_gcs, + ) + + settings = SnowflakeSettings.from_env() + with create_session(settings) as session: + # Load from GCS - auto-bootstraps warehouse + database + results = load_from_gcs(session, settings=settings) +""" + +from __future__ import annotations + +# ruff: noqa: G004, S608 +import logging +from pathlib import Path + +import httpx +from snowflake.snowpark import Row, Session + +from ._bootstrap import ensure_infrastructure +from ._settings import SnowflakeSettings +from ._sql_loader import load_sql + +logger: logging.Logger = logging.getLogger(__name__) + +JAFFLE_SHOP_TABLE_NAMES: list[str] = [ + "raw_customers", + "raw_orders", + "raw_items", + "raw_products", + "raw_stores", + "raw_supplies", +] + +DEFAULT_GCS_BUCKET = "gcs://static.getml.com/datasets/jaffle_shop" +DEFAULT_STAGE_NAME = "JAFFLE_SHOP_STAGE" + + +class DataIngestionError(Exception): + """Raised when data ingestion fails.""" + + +# ============================================================================= +# Public API +# ============================================================================= + + +def load_from_gcs( + session: Session, + settings: SnowflakeSettings | None = None, + bucket: str = DEFAULT_GCS_BUCKET, + destination_schema: str = "RAW", +) -> dict[str, int]: + """Load Jaffle Shop data from GCS bucket into Snowflake. + + Downloads parquet files via HTTPS to a local cache, uploads them to an + internal Snowflake stage, then loads into tables using COPY INTO. + + No GCP credentials or storage integration required - files are fetched + via public HTTPS URLs. + + When settings are provided, auto-bootstraps the warehouse and database + if they don't exist. + + Args: + session: Active Snowflake Snowpark session. + settings: Optional settings for auto-bootstrapping warehouse and database. + When provided, ensures infrastructure exists before loading data. + bucket: GCS bucket URL (gcs:// or gs:// prefix). + destination_schema: Target schema name for loaded tables. + + Returns: + Dictionary mapping table names to row counts. + + Raises: + DataIngestionError: If data loading fails. + BootstrapError: If auto-bootstrap fails due to insufficient privileges. + """ + if settings is not None: + ensure_infrastructure(session, settings) + if settings.warehouse: + session.use_warehouse(settings.warehouse) + if settings.database: + session.use_database(settings.database) + + try: + https_base_url: str = _gcs_to_https_url(gcs_url=bucket) + cache_dir: Path = _get_cache_dir() + local_files: dict[str, Path] = {} + + for table_name in JAFFLE_SHOP_TABLE_NAMES: + file_name: str = f"{table_name}.parquet" + url: str = f"{https_base_url}/{file_name}" + local_path: Path = cache_dir / file_name + _download_parquet_file(url, dest_path=local_path) + local_files[table_name] = local_path + + _create_schema(session, schema_name=destination_schema) + _create_parquet_file_format(session, schema_name=destination_schema) + _create_internal_stage( + session, + schema_name=destination_schema, + stage_name=DEFAULT_STAGE_NAME, + ) + + _upload_files_to_stage( + session, + local_files, + schema_name=destination_schema, + stage_name=DEFAULT_STAGE_NAME, + ) + + results: dict[str, int] = _load_all_tables( + session, + schema_name=destination_schema, + ) + + except Exception as e: + raise DataIngestionError( + f"Failed to load Jaffle Shop data into Snowflake. Error: {e}" + ) from e + + _log_completion_summary(results, schema_name=destination_schema) + return results + + +def load_from_s3( + session: Session, + bucket: str, + settings: SnowflakeSettings | None = None, + destination_schema: str = "RAW", +) -> dict[str, int]: + """Load Jaffle Shop data from public S3 bucket into Snowflake. + + Creates the destination schema if needed, sets up a Parquet file format + and external stage pointing to the S3 bucket, then loads all tables + using COPY INTO with schema inference. + + When settings are provided, auto-bootstraps the warehouse and database + if they don't exist. + + Args: + session: Active Snowflake Snowpark session. + bucket: S3 bucket URL (s3:// prefix). Must be publicly accessible. + settings: Optional settings for auto-bootstrapping warehouse and database. + When provided, ensures infrastructure exists before loading data. + destination_schema: Target schema name for loaded tables. + + Returns: + Dictionary mapping table names to row counts. + + Raises: + DataIngestionError: If data loading fails. + BootstrapError: If auto-bootstrap fails due to insufficient privileges. + """ + if not bucket.lower().startswith("s3://"): + raise DataIngestionError( + f"Invalid S3 bucket URL: {bucket}. Must start with s3://" + ) + + if settings is not None: + ensure_infrastructure(session, settings) + if settings.warehouse: + session.use_warehouse(settings.warehouse) + if settings.database: + session.use_database(settings.database) + + try: + _create_schema(session, schema_name=destination_schema) + _create_parquet_file_format(session, schema_name=destination_schema) + _create_external_stage_s3( + session, + bucket_url=bucket, + schema_name=destination_schema, + ) + results: dict[str, int] = _load_all_tables( + session, + schema_name=destination_schema, + ) + except Exception as e: + raise DataIngestionError( + f"Failed to load Jaffle Shop data into Snowflake. Error: {e}" + ) from e + + _log_completion_summary(results, schema_name=destination_schema) + return results + + +# ============================================================================= +# GCS Download Helpers +# ============================================================================= + + +def _gcs_to_https_url(gcs_url: str) -> str: + """Convert GCS URL to HTTPS URL for public access. + + Args: + gcs_url: GCS bucket URL with gcs:// or gs:// prefix. + + Returns: + HTTPS URL for the same resource. + + Examples: + gcs://static.getml.com/datasets/jaffle_shop + -> https://storage.googleapis.com/static.getml.com/datasets/jaffle_shop + """ + if gcs_url.lower().startswith("gcs://"): + path = gcs_url[6:] + elif gcs_url.lower().startswith("gs://"): + path = gcs_url[5:] + else: + raise DataIngestionError( + f"Invalid GCS URL: {gcs_url}. Must start with gcs:// or gs://" + ) + + path: str = path.rstrip("/") + + return f"https://storage.googleapis.com/{path}" + + +def _get_cache_dir() -> Path: + """Get persistent cache directory for downloaded parquet files. + + Creates the directory if it doesn't exist. + + Returns: + Path to cache directory (~/.cache/getml/jaffle_shop/). + """ + cache_dir = Path.home() / ".cache" / "getml" / "jaffle_shop" + cache_dir.mkdir(parents=True, exist_ok=True) + return cache_dir + + +def _download_parquet_file(url: str, dest_path: Path) -> None: + """Download a parquet file from URL to local path. + + Skips download if file already exists in cache. + + Args: + url: HTTPS URL to download from. + dest_path: Local path to save the file. + + Raises: + DataIngestionError: If download fails. + """ + if dest_path.exists(): + logger.info(f"Using cached file: {dest_path.name}") + return + + logger.info(f"Downloading {dest_path.name}...") + + try: + with httpx.stream("GET", url, follow_redirects=True, timeout=60.0) as response: + _ = response.raise_for_status() + with dest_path.open("wb") as f: + for chunk in response.iter_bytes(chunk_size=8192): + _ = f.write(chunk) + except httpx.HTTPError as e: + # Clean up partial download + if dest_path.exists(): + dest_path.unlink() + raise DataIngestionError(f"Failed to download {url}: {e}") from e + + logger.info(f" ✓ Downloaded {dest_path.name}") + + +def _upload_files_to_stage( + session: Session, + local_files: dict[str, Path], + schema_name: str, + stage_name: str, +) -> None: + """Upload local parquet files to internal Snowflake stage. + + Args: + session: Active Snowflake Snowpark session. + local_files: Dictionary mapping table names to local file paths. + schema_name: Schema where the stage is located. + stage_name: Name of the internal stage. + """ + logger.info(f"Uploading files to stage @{schema_name}.{stage_name}...") + + for local_path in local_files.values(): + logger.info(f" Uploading {local_path.name}...") + put_result = session.file.put( + local_file_name=str(local_path), + stage_location=f"@{schema_name}.{stage_name}/", + auto_compress=False, + overwrite=True, + ) + if put_result: + for row in put_result: + status: str = row.status if hasattr(row, "status") else "UPLOADED" + logger.info(f" ✓ {local_path.name}: {status}") + + +# ============================================================================= +# Schema and Stage Creation +# ============================================================================= + + +def _create_schema(session: Session, schema_name: str) -> None: + """Create schema if it doesn't exist.""" + logger.info(f"Creating {schema_name} schema...") + sql: str = load_sql(path="common/create_schema.sql", schema_name=schema_name) + _ = session.sql(sql).collect() + logger.info(f"✓ {schema_name} schema ready") + + +def _create_parquet_file_format(session: Session, schema_name: str) -> None: + """Create Parquet file format for data ingestion.""" + logger.info("Creating Parquet file format...") + sql: str = load_sql( + path="ingestion/create_parquet_file_format.sql", + schema_name=schema_name, + ) + _ = session.sql(sql).collect() + logger.info("✓ Parquet file format ready") + + +def _create_internal_stage( + session: Session, + schema_name: str, + stage_name: str, +) -> None: + """Create internal stage for uploaded files.""" + logger.info(f"Creating internal stage {stage_name}...") + sql: str = load_sql( + path="ingestion/create_internal_stage.sql", + stage_name=stage_name, + schema_name=schema_name, + ) + _ = session.sql(sql).collect() + logger.info(f"✓ Internal stage {stage_name} created") + + +def _create_external_stage_s3( + session: Session, + bucket_url: str, + schema_name: str, +) -> None: + """Create external stage pointing to public S3 bucket.""" + logger.info(f"Creating external stage {DEFAULT_STAGE_NAME}...") + sql: str = load_sql( + path="ingestion/create_stage_s3_public.sql", + stage_name=DEFAULT_STAGE_NAME, + bucket_url=bucket_url, + schema_name=schema_name, + ) + _ = session.sql(sql).collect() + logger.info(f"✓ External stage {DEFAULT_STAGE_NAME} created") + + +# ============================================================================= +# Table Loading +# ============================================================================= + + +def _load_all_tables(session: Session, schema_name: str) -> dict[str, int]: + """Load all Jaffle Shop tables from stage.""" + logger.info("Loading tables from stage...") + results: dict[str, int] = {} + + for table_name in JAFFLE_SHOP_TABLE_NAMES: + row_count: int = _load_single_table(session, table_name, schema_name) + results[table_name] = row_count + + return results + + +def _load_single_table( + session: Session, + table_name: str, + schema_name: str, +) -> int: + """Load a single table from stage. + + Uses a two-step process: + 1. Creates empty table with schema inferred from Parquet metadata (INFER_SCHEMA) + 2. Copies data from stage using MATCH_BY_COLUMN_NAME for proper column mapping + """ + logger.info(f"Loading {table_name}...") + + create_sql: str = load_sql( + path="ingestion/create_table_from_parquet.sql", + table_name=table_name, + stage_name=DEFAULT_STAGE_NAME, + schema_name=schema_name, + ) + _ = session.sql(create_sql).collect() + + copy_sql: str = load_sql( + path="ingestion/copy_into_table.sql", + table_name=table_name, + stage_name=DEFAULT_STAGE_NAME, + schema_name=schema_name, + ) + _ = session.sql(query=copy_sql).collect() + + count_sql = f"SELECT COUNT(*) as count FROM {schema_name}.{table_name}" + count_result: list[Row] = session.sql(count_sql).collect() + + row_count = int(count_result[0]["COUNT"]) # pyright: ignore[reportArgumentType] + logger.info(f" ✓ {row_count:,} rows loaded") + + if row_count == 0: + raise DataIngestionError(f"Table {table_name} has 0 rows after loading") + + return row_count + + +def _log_completion_summary(results: dict[str, int], schema_name: str) -> None: + """Log summary of loaded tables.""" + table_lines = "\n".join( + f" • {name}: {count:,} rows" for name, count in results.items() + ) + logger.info(f""" +================================================================================ +DATA LOADING COMPLETE! +================================================================================ +Successfully loaded {len(results)} tables into {schema_name} schema: +{table_lines} +""") diff --git a/integration/snowflake/data/sql/bootstrap/create_database.sql b/integration/snowflake/data/sql/bootstrap/create_database.sql new file mode 100644 index 0000000..b58ebb1 --- /dev/null +++ b/integration/snowflake/data/sql/bootstrap/create_database.sql @@ -0,0 +1 @@ +CREATE DATABASE IF NOT EXISTS {database_name} diff --git a/integration/snowflake/data/sql/bootstrap/create_warehouse.sql b/integration/snowflake/data/sql/bootstrap/create_warehouse.sql new file mode 100644 index 0000000..6e8ef05 --- /dev/null +++ b/integration/snowflake/data/sql/bootstrap/create_warehouse.sql @@ -0,0 +1,6 @@ +CREATE WAREHOUSE IF NOT EXISTS {warehouse_name} +WITH + WAREHOUSE_SIZE = '{warehouse_size}' + AUTO_SUSPEND = {auto_suspend_seconds} + AUTO_RESUME = TRUE + INITIALLY_SUSPENDED = TRUE diff --git a/integration/snowflake/data/sql/common/create_schema.sql b/integration/snowflake/data/sql/common/create_schema.sql new file mode 100644 index 0000000..57faa76 --- /dev/null +++ b/integration/snowflake/data/sql/common/create_schema.sql @@ -0,0 +1 @@ +CREATE SCHEMA IF NOT EXISTS {schema_name} diff --git a/integration/snowflake/data/sql/ingestion/copy_into_table.sql b/integration/snowflake/data/sql/ingestion/copy_into_table.sql new file mode 100644 index 0000000..2a7ae6f --- /dev/null +++ b/integration/snowflake/data/sql/ingestion/copy_into_table.sql @@ -0,0 +1,6 @@ +-- Copy data from staged Parquet file into table +-- Uses MATCH_BY_COLUMN_NAME to map Parquet columns to table columns +COPY INTO {schema_name}.{table_name} + FROM @{schema_name}.{stage_name}/{table_name}.parquet + FILE_FORMAT = (FORMAT_NAME = '{schema_name}.PARQUET_FORMAT') + MATCH_BY_COLUMN_NAME = CASE_INSENSITIVE; diff --git a/integration/snowflake/data/sql/ingestion/create_internal_stage.sql b/integration/snowflake/data/sql/ingestion/create_internal_stage.sql new file mode 100644 index 0000000..7b34028 --- /dev/null +++ b/integration/snowflake/data/sql/ingestion/create_internal_stage.sql @@ -0,0 +1,4 @@ +-- Create internal stage for uploading local parquet files +-- Used when loading data via session.file.put() instead of external storage integration +CREATE OR REPLACE STAGE {schema_name}.{stage_name} + FILE_FORMAT = {schema_name}.PARQUET_FORMAT; diff --git a/integration/snowflake/data/sql/ingestion/create_parquet_file_format.sql b/integration/snowflake/data/sql/ingestion/create_parquet_file_format.sql new file mode 100644 index 0000000..c6d6504 --- /dev/null +++ b/integration/snowflake/data/sql/ingestion/create_parquet_file_format.sql @@ -0,0 +1,5 @@ +-- Create Parquet file format for data ingestion +-- Uses CREATE OR REPLACE for idempotent execution +CREATE OR REPLACE FILE FORMAT {schema_name}.PARQUET_FORMAT + TYPE = PARQUET + USE_VECTORIZED_SCANNER = TRUE diff --git a/integration/snowflake/data/sql/ingestion/create_stage_s3_public.sql b/integration/snowflake/data/sql/ingestion/create_stage_s3_public.sql new file mode 100644 index 0000000..b9f778e --- /dev/null +++ b/integration/snowflake/data/sql/ingestion/create_stage_s3_public.sql @@ -0,0 +1,5 @@ +-- Create external stage pointing to a public S3 bucket for Parquet data ingestion +-- No credentials required for public buckets +CREATE OR REPLACE STAGE {schema_name}.{stage_name} + URL = '{bucket_url}' + FILE_FORMAT = {schema_name}.PARQUET_FORMAT diff --git a/integration/snowflake/data/sql/ingestion/create_table_from_parquet.sql b/integration/snowflake/data/sql/ingestion/create_table_from_parquet.sql new file mode 100644 index 0000000..bd10f2e --- /dev/null +++ b/integration/snowflake/data/sql/ingestion/create_table_from_parquet.sql @@ -0,0 +1,16 @@ +-- Create table with schema inferred from Parquet file +-- Uses INFER_SCHEMA to detect column names and types from the Parquet metadata +-- Column names are uppercased to match Snowflake conventions (unquoted identifiers) +CREATE OR REPLACE TABLE {schema_name}.{table_name} + USING TEMPLATE ( + SELECT ARRAY_AGG(OBJECT_CONSTRUCT( + 'COLUMN_NAME', UPPER(COLUMN_NAME), + 'TYPE', TYPE, + 'NULLABLE', NULLABLE + )) + FROM TABLE( + INFER_SCHEMA( + LOCATION=>'@{schema_name}.{stage_name}/{table_name}.parquet', + FILE_FORMAT=>'{schema_name}.PARQUET_FORMAT' + ) + )); diff --git a/integration/snowflake/ingest_jaffle_shop_data.py b/integration/snowflake/ingest_jaffle_shop_data.py new file mode 100644 index 0000000..49c766c --- /dev/null +++ b/integration/snowflake/ingest_jaffle_shop_data.py @@ -0,0 +1,51 @@ +"""Ingest Jaffle Shop data into Snowflake for getML Feature Store integration. + +Loads raw Jaffle Shop dataset (Parquet files) from a public GCS bucket into the +RAW schema in Snowflake. Infrastructure (warehouse, database) is auto-created +if missing. + +Prerequisites: + - Snowflake account with appropriate privileges + - SNOWFLAKE_* environment variables set for authentication and configuration + +Usage: + uv run python ingest_jaffle_shop_data.py +""" + +import logging +import sys + +from data import ( + SnowflakeSettings, + create_session, + ingestion, +) + +logger: logging.Logger = logging.getLogger(__name__) + + +def main() -> None: + """Ingest Jaffle Shop raw data into Snowflake. + + Note: + Set basicConfig.level to logging.DEBUG for more verbose output. + """ + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", + stream=sys.stdout, + ) + + settings = SnowflakeSettings.from_env() + + with create_session(settings) as session: + _ = ingestion.load_from_gcs( + session, + settings=settings, + bucket="gcs://static.getml.com/datasets/jaffle_shop", + destination_schema="RAW", + ) + + +if __name__ == "__main__": + main() diff --git a/integration/snowflake/mise.toml b/integration/snowflake/mise.toml new file mode 100644 index 0000000..69eac93 --- /dev/null +++ b/integration/snowflake/mise.toml @@ -0,0 +1,9 @@ +[env] +SNOWFLAKE_ACCOUNT = "{{ exec(command='op read --account getml.1password.eu \"op://svibqfali56qralxbzg6wanc5i/Snowflake/account\"', cache_key='snowflake_account', duration='1w') }}" +SNOWFLAKE_USER = "{{ exec(command='op read --account getml.1password.eu \"op://svibqfali56qralxbzg6wanc5i/Snowflake/username\"', cache_key='snowflake_user', duration='1w') }}" +SNOWFLAKE_PASSWORD = "{{ exec(command='op read --account getml.1password.eu \"op://svibqfali56qralxbzg6wanc5i/Snowflake/password\"', cache_key='snowflake_password', duration='1w') }}" + +SNOWFLAKE_ROLE = "ACCOUNTADMIN" +SNOWFLAKE_WAREHOUSE = "COMPUTE_WH" +SNOWFLAKE_DATABASE = "JAFFLE_SHOP" +SNOWFLAKE_SCHEMA = "RAW" diff --git a/integration/snowflake/pyproject.toml b/integration/snowflake/pyproject.toml new file mode 100644 index 0000000..19d1818 --- /dev/null +++ b/integration/snowflake/pyproject.toml @@ -0,0 +1,138 @@ +[project] +name = "getml-featurestore-integrations" +version = "0.1.0" +description = "Integrations and Data Preparation for getML Feature Stores" +authors = [ + { name = "Code17 GmbH", email = "hello@code17.io" }, + { name = "getML", email = "hello@getml.com" }, +] +maintainers = [ + { name = "Code17 GmbH", email = "hello@code17.io" }, + { name = "getML", email = "hello@getml.com" }, +] +license = { text = "Proprietary" } +classifiers = [ + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Operating System :: OS Independent", + "Private :: Do Not Upload", + "Intended Audience :: Developers", + "Intended Audience :: Science/Research", + "Topic :: Scientific/Engineering", + "Topic :: Scientific/Engineering :: Artificial Intelligence", + "Topic :: Software Development :: Libraries", + "Topic :: Software Development :: Libraries :: Python Modules", +] +readme = "README.md" +requires-python = ">=3.12" + +dependencies = [ + "fastparquet>=2024.11.0", + "httpx>=0.27.0", + "ipykernel>=7.1.0", + "pandas>=2.3.3", + "pyarrow>=18.0.0", + "pydantic>=2.12.5", + "pydantic-settings>=2.12.0", + "snowflake-connector-python>=3.17.3", + "snowflake-snowpark-python>=1.42.0", +] + +[dependency-groups] +dev = [ + "ruff~=0.12.2", + "basedpyright~=1.28.4", + "pytest~=8.0.0", + "pytest-cov>=6.2.1", + "pytest-dependency>=0.6.0", +] + +[tool.uv] +package = false + +[tool.pytest.ini_options] +pythonpath = ["."] +testpaths = ["tests"] +python_files = ["test_*.py"] +python_classes = ["Test*"] +python_functions = ["test_*"] +markers = [ + "integration: marks tests as integration tests (require Snowflake credentials)", +] + +[project.urls] +"Homepage" = "https://github.com/getml/getml-demo" +"Bug Tracker" = "https://github.com/getml/getml-demo/issues" +"getML" = "https://getml.com" +"Code17 GmbH" = "https://www.code17.io/" + +[tool.pyright] +venvPath = "." +venv = ".venv" +reportMissingTypeStubs = false +reportImplicitStringConcatenation = false + +[[tool.pyright.executionEnvironments]] +root = "tests" +extraPaths = ["."] +reportUnusedParameter = false + +[build-system] +requires = ["uv_build>=0.7.21,<0.8.0"] +build-backend = "uv_build" + +[tool.ruff] +line-length = 88 +target-version = "py312" + +[tool.ruff.format] +preview = false +quote-style = "double" +line-ending = "auto" +docstring-code-format = true + +[tool.ruff.lint] +select = ["ALL"] +ignore = [ + # Allow for string literals in exceptions + "EM", + # Allow missing copyright notice at top of files + "CPY001", + # Allow missing docstrings in public modules + "D100", + # Allow missing docstrings in public classes + "D101", + # Allow missing docstrings in public packages + "D104", + # Allow docstrings without blank line before class docstring + "D203", + # Allow multi-line docstring summary to start at second line + "D213", + # Allow first-party imports outside type-checking blocks + "TC001", + # Allow third-party imports outside type-checking blocks + "TC002", + # Allow standard library imports outside type-checking blocks + "TC003", + # Allow TODO comments + "FIX002", + # Allow TODO comments without author + "TD002", + # Allow TODO comments without link to issue + "TD003", + # Allow specifying long messages outside the exception class + "TRY003", + # Conflicts with formatter - trailing commas are handled by ruff format + "COM812", +] + +fixable = ["ALL"] + +[tool.ruff.lint.pydocstyle] +convention = "google" + +[tool.ruff.lint.per-file-ignores] +# S101: Allow for use of the assert keyword +# PLR2004: Allow "magic value" used in comparison +"test_*.py" = ["S101", "PLR2004"] diff --git a/integration/snowflake/tests/__init__.py b/integration/snowflake/tests/__init__.py new file mode 100644 index 0000000..5011730 --- /dev/null +++ b/integration/snowflake/tests/__init__.py @@ -0,0 +1 @@ +"""Test package for getML Snowflake integration.""" diff --git a/integration/snowflake/tests/cleanup_test_resources.py b/integration/snowflake/tests/cleanup_test_resources.py new file mode 100644 index 0000000..41fdb5d --- /dev/null +++ b/integration/snowflake/tests/cleanup_test_resources.py @@ -0,0 +1,80 @@ +"""Cleanup utility for test resources in Snowflake. + +Drops test databases (JAFFLE_SHOP_TEST_*) and test schemas (TEST_*) created +by integration tests. Can be run standalone or imported by test fixtures for +pre/post-test cleanup. + +Usage: + # Standalone execution + uv run python tests/cleanup_test_resources.py + + # Import in fixtures + from tests.cleanup_test_resources import cleanup_test_databases + cleanup_test_databases(session) +""" + +# ruff: noqa: G004, S608 +import logging + +from snowflake.snowpark import Row, Session + +logger: logging.Logger = logging.getLogger(__name__) + +TEST_DATABASE_PREFIX = "JAFFLE_SHOP_TEST_" +TEST_SCHEMA_PREFIX = "TEST_" + + +def cleanup_test_databases(session: Session) -> list[str]: + """Drop all databases with JAFFLE_SHOP_TEST_ prefix. + + Args: + session: Active Snowflake session with appropriate privileges. + + Returns: + List of dropped database names. + """ + result: list[Row] = session.sql(f""" + SELECT DATABASE_NAME + FROM INFORMATION_SCHEMA.DATABASES + WHERE DATABASE_NAME LIKE '{TEST_DATABASE_PREFIX}%' + """).collect() + + dropped_databases: list[str] = [] + + for row in result: + db_name = str(row["DATABASE_NAME"]) # pyright: ignore[reportUnknownArgumentType] + _ = session.sql(f"DROP DATABASE IF EXISTS {db_name} CASCADE").collect() + dropped_databases.append(db_name) + logger.info(f"Dropped database: {db_name}") + + return dropped_databases + + +def cleanup_test_schemas(session: Session, database: str | None = None) -> list[str]: + """Drop all schemas with TEST_ prefix in the specified database. + + Args: + session: Active Snowflake session. + database: Database to clean. If None, uses session's current database. + + Returns: + List of dropped schema names. + """ + if database: + _ = session.sql(f"USE DATABASE {database}").collect() + + result: list[Row] = session.sql(f""" + SELECT SCHEMA_NAME + FROM INFORMATION_SCHEMA.SCHEMATA + WHERE SCHEMA_NAME LIKE '{TEST_SCHEMA_PREFIX}%' + """).collect() + + dropped_schemas: list[str] = [] + + for row in result: + schema_name = str(row["SCHEMA_NAME"]) # pyright: ignore[reportUnknownArgumentType] + _ = session.sql(f"DROP SCHEMA IF EXISTS {schema_name} CASCADE").collect() + dropped_schemas.append(schema_name) + logger.info(f"Dropped schema: {schema_name}") + + return dropped_schemas diff --git a/integration/snowflake/tests/conftest.py b/integration/snowflake/tests/conftest.py new file mode 100644 index 0000000..5cdd685 --- /dev/null +++ b/integration/snowflake/tests/conftest.py @@ -0,0 +1,53 @@ +"""Shared test fixtures for unit tests. + +Provides mock Snowflake session factories and utilities for testing +data pipeline logic without requiring actual Snowflake connections. +""" + +# pyright: reportAny=false + +import uuid +from collections.abc import Callable +from unittest.mock import MagicMock + +import pytest + + +@pytest.fixture +def test_run_id() -> str: + """Generate unique identifier for test isolation. + + Returns short UUID suffix for creating isolated test schemas. + """ + return uuid.uuid4().hex[:8] + + +@pytest.fixture +def mock_session() -> MagicMock: + """Create a mock Snowflake Snowpark session. + + The mock supports chained calls like `session.sql(...).collect()`. + Configure return values per test using: + `mock_session.sql.return_value.collect.return_value`. + """ + session = MagicMock() + session.sql.return_value.collect.return_value = [] + return session + + +@pytest.fixture +def mock_session_factory() -> Callable[[], MagicMock]: + """Factory fixture for creating mock sessions with different behaviors. + + Usage: + def test_something(mock_session_factory): + session = mock_session_factory() + session.sql.return_value.collect.return_value = [{"COUNT": 100}] + """ + + def _create_mock_session() -> MagicMock: + session = MagicMock() + session.sql.return_value.collect.return_value = [] + return session + + return _create_mock_session diff --git a/integration/snowflake/tests/integration/__init__.py b/integration/snowflake/tests/integration/__init__.py new file mode 100644 index 0000000..d387fff --- /dev/null +++ b/integration/snowflake/tests/integration/__init__.py @@ -0,0 +1 @@ +"""Integration test package for getML Snowflake integration.""" diff --git a/integration/snowflake/tests/integration/conftest.py b/integration/snowflake/tests/integration/conftest.py new file mode 100644 index 0000000..4d0b61b --- /dev/null +++ b/integration/snowflake/tests/integration/conftest.py @@ -0,0 +1,189 @@ +"""Fixtures for integration tests requiring real Snowflake connections. + +Provides session-scoped fixtures that: +1. Run cleanup of stale JAFFLE_SHOP_TEST_* databases before tests +2. Create an isolated test database (JAFFLE_SHOP_TEST_{uuid}) for test isolation +3. Configure storage access for cloud bucket with Parquet files +4. Clean up test database after the test session completes + +Storage Configuration: +- GCS (default): Uses HTTPS to fetch files from gs://static.getml.com/datasets/jaffle_shop/ + No credentials or storage integration required. +- S3: Set S3_BUCKET_URL to a public S3 bucket with Parquet files + (e.g., s3://your-bucket/jaffle_shop/) +""" + +# ruff: noqa: G004 + +import logging +import os +import uuid +from collections.abc import Generator +from enum import Enum + +import pytest +from pydantic import ValidationError +from pydantic.dataclasses import dataclass +from snowflake.snowpark import Session + +from data import ( + DEFAULT_GCS_BUCKET, + SnowflakeSettings, + create_session, + load_from_gcs, + load_from_s3, +) +from tests.cleanup_test_resources import cleanup_test_databases + +logger = logging.getLogger(__name__) + + +class CloudProvider(Enum): + """Supported cloud storage providers for data ingestion.""" + + GCS = "gcs" + S3 = "s3" + + +@dataclass(frozen=True) +class StorageConfig: + """Configuration for cloud storage access in integration tests. + + Encapsulates the parameters needed to call either load_from_gcs or + load_from_s3, providing a unified interface for test fixtures. + """ + + provider: CloudProvider + bucket_url: str + + +def load_jaffle_shop_data( + session: Session, + config: StorageConfig, +) -> dict[str, int]: + """Load Jaffle Shop data using the appropriate loader for the storage provider. + + Dispatches to load_from_gcs or load_from_s3 based on the config's provider. + """ + if config.provider == CloudProvider.GCS: + return load_from_gcs(session, bucket=config.bucket_url) + return load_from_s3(session, bucket=config.bucket_url) + + +def _snowflake_credentials_available() -> bool: + """Check if required Snowflake environment variables are set.""" + required_vars: list[str] = [ + "SNOWFLAKE_ACCOUNT", + "SNOWFLAKE_USER", + "SNOWFLAKE_PASSWORD", + "SNOWFLAKE_WAREHOUSE", + "SNOWFLAKE_DATABASE", + ] + return all(os.environ.get(var) for var in required_vars) + + +def _get_storage_config() -> StorageConfig: + """Build StorageConfig from environment variables. + + Priority: + 1. S3 public bucket if S3_BUCKET_URL is set + 2. GCS (default) - uses HTTPS, no credentials required + + Returns: + StorageConfig with appropriate provider and bucket URL. + """ + s3_bucket_url = os.environ.get("S3_BUCKET_URL") + if s3_bucket_url: + return StorageConfig( + provider=CloudProvider.S3, + bucket_url=s3_bucket_url, + ) + + # Default: GCS via HTTPS (no credentials required) + return StorageConfig( + provider=CloudProvider.GCS, + bucket_url=DEFAULT_GCS_BUCKET, + ) + + +@pytest.fixture(scope="session") +def integration_test_id() -> str: + """Generate unique identifier for this test session. + + Used to create an isolated test database that doesn't conflict + with parallel test runs. + """ + return uuid.uuid4().hex[:8].upper() + + +@pytest.fixture(scope="session") +def snowflake_settings() -> SnowflakeSettings: + """Load Snowflake settings from environment variables. + + Skips tests if credentials are not available. + """ + if not _snowflake_credentials_available(): + pytest.skip("Snowflake credentials not available in environment") + + try: + return SnowflakeSettings.from_env() + except ValidationError as e: + pytest.skip(f"Invalid Snowflake configuration: {e}") + + +@pytest.fixture(scope="session") +def storage_config() -> StorageConfig: + """Create StorageConfig for cloud storage access. + + By default, uses GCS which fetches files via HTTPS - no credentials needed. + To use S3 instead, set S3_BUCKET_URL environment variable. + """ + return _get_storage_config() + + +@pytest.fixture(scope="session") +def test_database( + snowflake_settings: SnowflakeSettings, + integration_test_id: str, +) -> Generator[str, None, None]: + """Create an isolated test database for this test session. + + Creates JAFFLE_SHOP_TEST_{uuid} database that is cleaned up after tests. + This provides complete isolation from production data. + """ + db_name = f"JAFFLE_SHOP_TEST_{integration_test_id}" + + with create_session(snowflake_settings) as session: + # Pre-test cleanup: remove any stale test databases from previous runs + logger.info("Running pre-test cleanup of stale test databases...") + dropped = cleanup_test_databases(session) + if dropped: + logger.info(f"Pre-test cleanup dropped {len(dropped)} stale database(s)") + + # Create the test database + logger.info(f"Creating test database: {db_name}") + _ = session.sql(f"CREATE DATABASE IF NOT EXISTS {db_name}").collect() + + yield db_name + + # Post-test cleanup: drop the test database + logger.info(f"Dropping test database: {db_name}") + _ = session.sql(f"DROP DATABASE IF EXISTS {db_name} CASCADE").collect() + + +@pytest.fixture(scope="session") +def snowflake_session( + snowflake_settings: SnowflakeSettings, + test_database: str, +) -> Generator[Session, None, None]: + """Create a Snowflake session for integration tests using the test database. + + The session is configured to use the isolated test database where RAW and + PREPARED schemas can be created without affecting production data. + """ + with create_session(snowflake_settings) as session: + # Switch to the test database + logger.info(f"Using test database: {test_database}") + _ = session.sql(f"USE DATABASE {test_database}").collect() + + yield session diff --git a/integration/snowflake/tests/integration/test_pipeline.py b/integration/snowflake/tests/integration/test_pipeline.py new file mode 100644 index 0000000..ab2f9e8 --- /dev/null +++ b/integration/snowflake/tests/integration/test_pipeline.py @@ -0,0 +1,73 @@ +"""Integration tests for the full data pipeline. + +These tests require real Snowflake credentials and verify end-to-end +functionality of data ingestion and preparation. + +Run with: uv run pytest tests/integration/ -m integration + +Required environment variables: +- SNOWFLAKE_ACCOUNT, SNOWFLAKE_USER, SNOWFLAKE_PASSWORD, etc. +- GCS_STORAGE_INTEGRATION: Name of the storage integration for GCS access +""" + +import logging + +import pytest +from snowflake.snowpark import Row, Session + +from data.ingestion import JAFFLE_SHOP_TABLE_NAMES + +from .conftest import StorageConfig, load_jaffle_shop_data + +logger = logging.getLogger(__name__) + +pytestmark: pytest.MarkDecorator = pytest.mark.integration + + +class TestDataIngestion: + """Integration tests for cloud storage to Snowflake data loading.""" + + @pytest.mark.dependency(name="data_ingestion") + def test_load_jaffle_shop_data_creates_tables_with_rows( + self, + snowflake_session: Session, + storage_config: StorageConfig, + ) -> None: + """Verify all Jaffle Shop tables are created with data.""" + results = load_jaffle_shop_data(snowflake_session, storage_config) + + # Verify all tables were loaded + assert set(results.keys()) == set(JAFFLE_SHOP_TABLE_NAMES) + + # Verify all tables have rows + for table_name, row_count in results.items(): + assert row_count > 0, f"Table {table_name} has 0 rows" + + @pytest.mark.dependency(depends=["data_ingestion"]) + def test_tables_have_expected_columns( + self, + snowflake_session: Session, + ) -> None: + """Verify tables have expected column structure.""" + result: list[Row] = snowflake_session.sql(""" + SELECT COLUMN_NAME + FROM INFORMATION_SCHEMA.COLUMNS + WHERE TABLE_SCHEMA = 'RAW' + AND TABLE_NAME = 'RAW_ORDERS' + ORDER BY ORDINAL_POSITION + """).collect() + + column_names = [str(row["COLUMN_NAME"]) for row in result] # pyright: ignore[reportUnknownArgumentType] + + # Column names are inferred from Parquet, check key columns exist + expected_columns = [ + "ID", + "CUSTOMER", + "ORDERED_AT", + "STORE_ID", + "SUBTOTAL", + "TAX_PAID", + "ORDER_TOTAL", + ] + for col in expected_columns: + assert col in column_names, f"Expected column {col} not found" diff --git a/integration/snowflake/tests/test_ingestion.py b/integration/snowflake/tests/test_ingestion.py new file mode 100644 index 0000000..71cbf93 --- /dev/null +++ b/integration/snowflake/tests/test_ingestion.py @@ -0,0 +1,375 @@ +"""Tests for data ingestion module. + +Tests URL conversion, download caching, file uploads, error handling, +and successful data loading orchestration logic using mocked sessions. +""" + +# pyright: reportAny=false + +from pathlib import Path +from unittest.mock import MagicMock, patch + +import httpx +import pytest + +from data.ingestion import ( + DEFAULT_GCS_BUCKET, + JAFFLE_SHOP_TABLE_NAMES, + DataIngestionError, + _download_parquet_file, # pyright: ignore[reportPrivateUsage] + _gcs_to_https_url, # pyright: ignore[reportPrivateUsage] + _get_cache_dir, # pyright: ignore[reportPrivateUsage] + load_from_gcs, + load_from_s3, +) + + +def _extract_sql_calls(mock_session: MagicMock) -> list[str]: + """Extract SQL strings from mock session.sql() calls. + + Handles both positional and keyword argument styles: + - session.sql("SELECT ...") + - session.sql(query="SELECT ...") + """ + calls: list[str] = [] + for call in mock_session.sql.call_args_list: + if call.args: + calls.append(call.args[0]) + elif "query" in call.kwargs: + calls.append(call.kwargs["query"]) + return calls + + +class TestGcsToHttpsUrl: + """Tests for _gcs_to_https_url URL conversion helper.""" + + def test_converts_gcs_prefix(self) -> None: + """Verify gcs:// prefix is converted to https://storage.googleapis.com/.""" + result = _gcs_to_https_url("gcs://bucket-name/path/to/data") + assert result == "https://storage.googleapis.com/bucket-name/path/to/data" + + def test_converts_gs_prefix(self) -> None: + """Verify gs:// prefix is converted to https://storage.googleapis.com/.""" + result = _gcs_to_https_url("gs://bucket-name/path/to/data") + assert result == "https://storage.googleapis.com/bucket-name/path/to/data" + + def test_handles_uppercase_prefix(self) -> None: + """Verify uppercase GCS:// prefix is handled.""" + result = _gcs_to_https_url("GCS://bucket-name/path") + assert result == "https://storage.googleapis.com/bucket-name/path" + + def test_removes_trailing_slash(self) -> None: + """Verify trailing slash is removed from path.""" + result = _gcs_to_https_url("gcs://bucket-name/path/") + assert result == "https://storage.googleapis.com/bucket-name/path" + + def test_raises_error_for_invalid_prefix(self) -> None: + """Verify error raised for non-GCS URL.""" + with pytest.raises(DataIngestionError) as exc_info: + _ = _gcs_to_https_url("s3://bucket-name/path") + + assert "Invalid GCS URL" in str(exc_info.value) + assert "Must start with gcs:// or gs://" in str(exc_info.value) + + def test_converts_default_bucket(self) -> None: + """Verify default GCS bucket URL is converted correctly.""" + result = _gcs_to_https_url(DEFAULT_GCS_BUCKET) + assert ( + result + == "https://storage.googleapis.com/static.getml.com/datasets/jaffle_shop" + ) + + +class TestGetCacheDir: + """Tests for _get_cache_dir cache directory helper.""" + + def test_returns_path_in_home_directory(self) -> None: + """Verify cache directory is under user's home directory.""" + result = _get_cache_dir() + assert result.is_relative_to(Path.home()) + + def test_returns_getml_jaffle_shop_path(self) -> None: + """Verify cache directory path structure.""" + result = _get_cache_dir() + assert result.parts[-3:] == (".cache", "getml", "jaffle_shop") + + def test_creates_directory_if_not_exists(self, tmp_path: Path) -> None: + """Verify cache directory is created if it doesn't exist.""" + with patch("data.ingestion.Path.home", return_value=tmp_path): + result = _get_cache_dir() + assert result.exists() + assert result.is_dir() + + +class TestDownloadParquetFile: + """Tests for _download_parquet_file download helper.""" + + def test_skips_download_if_file_exists(self, tmp_path: Path) -> None: + """Verify download is skipped when file already exists in cache.""" + dest_path = tmp_path / "test.parquet" + _ = dest_path.write_bytes(b"existing data") + + with patch("data.ingestion.httpx.stream") as mock_stream: + _download_parquet_file("https://example.com/test.parquet", dest_path) + + mock_stream.assert_not_called() + + def test_downloads_file_when_not_cached(self, tmp_path: Path) -> None: + """Verify file is downloaded when not in cache.""" + dest_path = tmp_path / "test.parquet" + test_data = b"parquet file content" + + mock_response = MagicMock() + mock_response.iter_bytes.return_value = [test_data] + mock_response.__enter__ = MagicMock(return_value=mock_response) + mock_response.__exit__ = MagicMock(return_value=False) + + with patch("data.ingestion.httpx.stream", return_value=mock_response): + _download_parquet_file("https://example.com/test.parquet", dest_path) + + assert dest_path.exists() + assert dest_path.read_bytes() == test_data + + def test_raises_error_on_http_failure(self, tmp_path: Path) -> None: + """Verify DataIngestionError raised on HTTP error.""" + dest_path = tmp_path / "test.parquet" + + mock_response = MagicMock() + mock_response.raise_for_status.side_effect = httpx.HTTPStatusError( + "Not Found", request=MagicMock(), response=MagicMock() + ) + mock_response.__enter__ = MagicMock(return_value=mock_response) + mock_response.__exit__ = MagicMock(return_value=False) + + with ( + patch("data.ingestion.httpx.stream", return_value=mock_response), + pytest.raises(DataIngestionError) as exc_info, + ): + _download_parquet_file("https://example.com/missing.parquet", dest_path) + + assert "Failed to download" in str(exc_info.value) + + def test_cleans_up_partial_download_on_failure(self, tmp_path: Path) -> None: + """Verify partial download is deleted on failure.""" + dest_path = tmp_path / "test.parquet" + + # Create a partial file to simulate interrupted download + _ = dest_path.write_bytes(b"partial") + + mock_response = MagicMock() + mock_response.raise_for_status.side_effect = httpx.HTTPStatusError( + "Connection lost", request=MagicMock(), response=MagicMock() + ) + mock_response.__enter__ = MagicMock(return_value=mock_response) + mock_response.__exit__ = MagicMock(return_value=False) + + # First call succeeds (file exists check), then fails on actual download + # Side effect: Not cached initially, then partial file exists after error + with ( + patch("data.ingestion.httpx.stream", return_value=mock_response), + patch.object(Path, "exists", side_effect=[False, True]), + pytest.raises(DataIngestionError), + ): + _download_parquet_file("https://example.com/test.parquet", dest_path) + + +class TestLoadFromS3: + """Tests for load_from_s3 function.""" + + def test_raises_error_for_invalid_bucket_url(self, mock_session: MagicMock) -> None: + """Verify error raised when bucket URL doesn't start with s3://.""" + with pytest.raises(DataIngestionError) as exc_info: + _ = load_from_s3(mock_session, bucket="gcs://wrong-scheme/path") + + assert "Invalid S3 bucket URL" in str(exc_info.value) + assert "Must start with s3://" in str(exc_info.value) + + def test_returns_dict_with_all_table_names_on_success( + self, mock_session: MagicMock + ) -> None: + """Verify successful load returns dict mapping table names to row counts.""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + + result = load_from_s3( + mock_session, + bucket="s3://test-bucket/jaffle-shop", + ) + + assert isinstance(result, dict) + expected_tables = { + "raw_customers", + "raw_orders", + "raw_items", + "raw_products", + "raw_stores", + "raw_supplies", + } + assert set(result.keys()) == expected_tables + + def test_creates_external_stage_for_s3(self, mock_session: MagicMock) -> None: + """Verify external stage is created for S3 bucket.""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + + _ = load_from_s3(mock_session, bucket="s3://test-bucket/data") + + sql_calls = _extract_sql_calls(mock_session) + stage_calls = [c for c in sql_calls if "CREATE OR REPLACE STAGE" in c] + assert len(stage_calls) > 0 + # S3 stages use URL parameter + assert any("s3://test-bucket/data" in c for c in stage_calls) + + def test_uses_custom_destination_schema(self, mock_session: MagicMock) -> None: + """Verify custom destination schema is used in SQL calls.""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + + _ = load_from_s3( + mock_session, + bucket="s3://test-bucket/data", + destination_schema="CUSTOM_SCHEMA", + ) + + sql_calls = _extract_sql_calls(mock_session) + schema_creation_calls = [c for c in sql_calls if "CREATE SCHEMA" in c] + assert any("CUSTOM_SCHEMA" in c for c in schema_creation_calls) + + +class TestLoadFromGcs: + """Tests for load_from_gcs function.""" + + def test_uses_default_gcs_bucket_when_not_specified( + self, mock_session: MagicMock, tmp_path: Path + ) -> None: + """Verify default GCS bucket URL is used when bucket not specified.""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + mock_session.file.put.return_value = [] + + # Create fake cached files + with ( + patch("data.ingestion._get_cache_dir", return_value=tmp_path), + patch("data.ingestion._download_parquet_file") as mock_download, + ): + # Create fake files for all tables + for table_name in JAFFLE_SHOP_TABLE_NAMES: + _ = (tmp_path / f"{table_name}.parquet").write_bytes(b"test") + + _ = load_from_gcs(mock_session) + + # Verify download was called with correct URLs + download_calls = mock_download.call_args_list + for call in download_calls: + url = call.args[0] + assert "storage.googleapis.com/static.getml.com/datasets/jaffle_shop" in url + + def test_downloads_parquet_files_to_cache( + self, mock_session: MagicMock, tmp_path: Path + ) -> None: + """Verify parquet files are downloaded to cache directory.""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + mock_session.file.put.return_value = [] + + with ( + patch("data.ingestion._get_cache_dir", return_value=tmp_path), + patch("data.ingestion._download_parquet_file") as mock_download, + ): + # Create fake files for all tables + for table_name in JAFFLE_SHOP_TABLE_NAMES: + _ = (tmp_path / f"{table_name}.parquet").write_bytes(b"test") + + _ = load_from_gcs(mock_session) + + # Verify download was called for each table + assert mock_download.call_count == len(JAFFLE_SHOP_TABLE_NAMES) + + def test_uploads_files_to_internal_stage( + self, mock_session: MagicMock, tmp_path: Path + ) -> None: + """Verify files are uploaded to internal Snowflake stage.""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + mock_session.file.put.return_value = [] + + with ( + patch("data.ingestion._get_cache_dir", return_value=tmp_path), + patch("data.ingestion._download_parquet_file"), + ): + # Create fake files for all tables + for table_name in JAFFLE_SHOP_TABLE_NAMES: + _ = (tmp_path / f"{table_name}.parquet").write_bytes(b"test") + + _ = load_from_gcs(mock_session) + + # Verify file.put was called for each file + assert mock_session.file.put.call_count == len(JAFFLE_SHOP_TABLE_NAMES) + + def test_creates_internal_stage_not_external( + self, mock_session: MagicMock, tmp_path: Path + ) -> None: + """Verify internal stage is created (no URL parameter).""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + mock_session.file.put.return_value = [] + + with ( + patch("data.ingestion._get_cache_dir", return_value=tmp_path), + patch("data.ingestion._download_parquet_file"), + ): + # Create fake files for all tables + for table_name in JAFFLE_SHOP_TABLE_NAMES: + _ = (tmp_path / f"{table_name}.parquet").write_bytes(b"test") + + _ = load_from_gcs(mock_session) + + sql_calls = _extract_sql_calls(mock_session) + stage_calls = [c for c in sql_calls if "CREATE OR REPLACE STAGE" in c] + # Internal stages don't have URL parameter + assert len(stage_calls) > 0 + assert not any("URL" in c for c in stage_calls) + + def test_returns_dict_with_all_table_names_on_success( + self, mock_session: MagicMock, tmp_path: Path + ) -> None: + """Verify successful load returns dict mapping table names to row counts.""" + mock_session.sql.return_value.collect.return_value = [ + {"COUNT": 100, "rows_loaded": 100} + ] + mock_session.file.put.return_value = [] + + with ( + patch("data.ingestion._get_cache_dir", return_value=tmp_path), + patch("data.ingestion._download_parquet_file"), + ): + # Create fake files for all tables + for table_name in JAFFLE_SHOP_TABLE_NAMES: + _ = (tmp_path / f"{table_name}.parquet").write_bytes(b"test") + + result = load_from_gcs(mock_session) + + assert isinstance(result, dict) + expected_tables = set(JAFFLE_SHOP_TABLE_NAMES) + assert set(result.keys()) == expected_tables + + +class TestDataIngestionError: + """Tests for error handling and messaging.""" + + def test_wraps_exception_with_context(self, mock_session: MagicMock) -> None: + """Verify exceptions are wrapped in DataIngestionError with context.""" + mock_session.sql.return_value.collect.side_effect = Exception("Connection lost") + + with pytest.raises(DataIngestionError) as exc_info: + _ = load_from_s3(mock_session, bucket="s3://test/data") + + assert "Connection lost" in str(exc_info.value) + assert "Failed to load Jaffle Shop data" in str(exc_info.value) diff --git a/integration/snowflake/tests/test_sql_loader.py b/integration/snowflake/tests/test_sql_loader.py new file mode 100644 index 0000000..464cbc2 --- /dev/null +++ b/integration/snowflake/tests/test_sql_loader.py @@ -0,0 +1,39 @@ +"""Tests for sql_loader module. + +Tests the load_sql function which handles SQL file loading +and parameter substitution. +""" + +# pyright: reportAny=false + +import pytest + +from data import load_sql + + +class TestLoadSql: + """Tests for load_sql utility function.""" + + def test_loads_existing_sql_file(self) -> None: + """Verify load_sql reads content from existing SQL file.""" + content = load_sql("common/create_schema.sql", schema_name="PREPARED") + + assert "CREATE SCHEMA" in content + assert "PREPARED" in content + + def test_returns_raw_content_when_no_kwargs(self) -> None: + """Verify load_sql returns unmodified content without kwargs.""" + content: str = load_sql( + path="common/create_schema.sql", + schema_name="RAW", + ) + + # Content should contain the schema name after formatting + assert isinstance(content, str) + assert len(content) > 0 + assert "RAW" in content + + def test_raises_file_not_found_for_missing_file(self) -> None: + """Verify FileNotFoundError propagates for nonexistent SQL files.""" + with pytest.raises(FileNotFoundError): + _ = load_sql(path="nonexistent/missing.sql") diff --git a/integration/snowflake/uv.lock b/integration/snowflake/uv.lock new file mode 100644 index 0000000..e19755d --- /dev/null +++ b/integration/snowflake/uv.lock @@ -0,0 +1,1600 @@ +version = 1 +revision = 3 +requires-python = ">=3.12" + +[[package]] +name = "annotated-types" +version = "0.7.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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