diff --git a/.github/workflows/automated_tests.yml b/.github/workflows/automated_tests.yml deleted file mode 100644 index a154eb0..0000000 --- a/.github/workflows/automated_tests.yml +++ /dev/null @@ -1,68 +0,0 @@ -name: ci_cd_checks - -on: - pull_request: - branches: "*" - push: - branches: "*" - -jobs: - ruff: - runs-on: macos-latest - steps: - - - name: Checkout branch - uses: actions/checkout@v3 - with: - fetch-depth: 0 - - - name: Get changed files - id: changed-python-files - uses: tj-actions/changed-files@v41 - with: - files: | - **.py - - - name: Setup Python environment - if: steps.changed-python-files.outputs.any_changed == 'true' - uses: actions/setup-python@v3 - with: - python-version: "3.10" - - - name: Installs - if: steps.changed-python-files.outputs.any_changed == 'true' - run: | - python -m pip install ruff - - - name: Ruff - if: steps.changed-python-files.outputs.any_changed == 'true' - run: | - ruff check --output-format=github . - - unit_tests: - runs-on: macos-latest - steps: - - name: Checkout branch - uses: actions/checkout@v3 - with: - fetch-depth: 0 - - - name: Setup Python environment - uses: actions/setup-python@v3 - with: - python-version: "3.10" - - - name: Installs - run: | - # Install Poetry - curl -sSL https://install.python-poetry.org | python3 - - - # Update PATH - echo "$HOME/.local/bin" >> $GITHUB_PATH - - # Install dependencies - poetry install --no-root - - - name: Run Unit Tests - run: | - poetry run pytest -rf tests/* \ No newline at end of file diff --git a/.github/workflows/pr_checks.yml b/.github/workflows/pr_checks.yml new file mode 100644 index 0000000..0b72d9e --- /dev/null +++ b/.github/workflows/pr_checks.yml @@ -0,0 +1,94 @@ +name: PR Checks + +on: + pull_request: + types: [opened, synchronize, reopened, ready_for_review] + +jobs: + ruff-lint: + if: github.event.pull_request.draft == false + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install uv + uses: astral-sh/setup-uv@v4 + + - name: Install dependencies + run: uv sync + + - name: Run ruff linting + run: uv run ruff check . + + ruff-format: + if: github.event.pull_request.draft == false + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install uv + uses: astral-sh/setup-uv@v4 + + - name: Install dependencies + run: uv sync + + - name: Run ruff formatting check + run: uv run ruff format --check . + + mypy: + if: github.event.pull_request.draft == false + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install uv + uses: astral-sh/setup-uv@v4 + + - name: Install dependencies + run: uv sync + + - name: Run mypy type checking + run: uv run mypy klondike/ + + pytest: + if: github.event.pull_request.draft == false + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install uv + uses: astral-sh/setup-uv@v4 + + - name: Install dependencies + run: uv sync + + - name: Run pytest + run: uv run pytest -rf tests/ \ No newline at end of file diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml new file mode 100644 index 0000000..c741774 --- /dev/null +++ b/.github/workflows/publish.yml @@ -0,0 +1,36 @@ +name: Publish to PyPI + +on: + push: + branches: + - main # This triggers when a PR is merged into main + +jobs: + build-n-publish: + name: Build and publish Klondike to PyPI + runs-on: ubuntu-latest + environment: + url: https://pypi.org/p/klondike + permissions: + id-token: write # MANDATORY for Trusted Publishers + contents: read # Required to check out the code + + steps: + - uses: actions/checkout@v4 + + - name: Set up uv + uses: astral-sh/setup-uv@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.12" + + - name: Install build dependencies + run: uv run python -m pip install build + + - name: Build distributions + run: uv run python -m build + + - name: Publish to PyPI + uses: pypa/gh-action-pypi-publish@release/v1 \ No newline at end of file diff --git a/.gitignore b/.gitignore index ea34492..f9e879b 100644 --- a/.gitignore +++ b/.gitignore @@ -8,6 +8,7 @@ venv/ .vscode/ dev/ service_accounts/ +development/ build/ dist/ diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 2ccdadf..1d6724e 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,8 +1,7 @@ repos: - repo: https://github.com/astral-sh/ruff-pre-commit - # Ruff version. - rev: v0.9.2 + rev: v0.11.2 hooks: - # Run the linter. - id: ruff + - id: ruff-format \ No newline at end of file diff --git a/Makefile b/Makefile index 3ecc0be..067e480 100644 --- a/Makefile +++ b/Makefile @@ -5,6 +5,20 @@ push: setup: @bash run_setup.sh -clean: - @ruff check --fix . - @pytest -rf tests/* \ No newline at end of file + +### CI Checks (these run locally in the CI pipeline, but can be run locally with `make all-checks`) ### + +ruff: + @uv run ruff check --fix . + @uv run ruff format . + +pytest: + @uv run pytest -rf tests + +mypy: + @uv run mypy klondike + +all-checks: + @make ruff + @make pytest + @make mypy diff --git a/README.md b/README.md index 876f2e1..5c53404 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,8 @@ # Klondike -Klondike offers a lightweight API to read and write data to Google BigQuery using Polars DataFrames. +![Klondike Logo](https://raw.githubusercontent.com/IanRFerguson/klondike/main/assets/logo.png) + +Klondike offers a lightweight, unified API to read and write data to and from various database and data warehouse types using Polars DataFrames. ## Installation diff --git a/assets/logo.png b/assets/logo.png new file mode 100644 index 0000000..baedfb4 Binary files /dev/null and b/assets/logo.png differ diff --git a/assets/logo2.png b/assets/logo2.png new file mode 100644 index 0000000..7d2d49d Binary files /dev/null and b/assets/logo2.png differ diff --git a/klondike/__init__.py b/klondike/__init__.py index 064199d..e8e94f6 100644 --- a/klondike/__init__.py +++ b/klondike/__init__.py @@ -1,35 +1,19 @@ import importlib -import logging -import os -# Define project logger -logger = logging.getLogger(__name__) +from klondike.utilities.logger import logger -_handler = logging.StreamHandler() -_formatter = logging.Formatter("%(module)s %(levelname)s %(message)s") -_handler.setFormatter(_formatter) - -logger.addHandler(_handler) - -# Define logging behavior -if any([os.environ.get("TESTING"), os.environ.get("TEST")]): - logger.setLevel("WARNING") -elif os.environ.get("DEBUG"): - logger.setLevel("DEBUG") - logger.debug("Debugger active...") -else: - logger.setLevel("INFO") - -##### - -__all__ = [] +__all__: list[str] = [] POLAR_OBJECTS = [ ("klondike.gcp.bigquery", "BigQueryConnector"), + ("klondike.gcp.cloud_storage", "CloudStorageConnector"), ("klondike.snowflake.snowflake", "SnowflakeConnector"), + ("klondike.scripts.stream_csv_to_database", "stream_csv_to_database"), ] for module_, object_ in POLAR_OBJECTS: try: globals()[object_] = getattr(importlib.import_module(module_), object_) except ImportError: - logger.debug(f"Could not import {module_}.{object_} ... skipping") + logger.warning( + f"Could not import {object_} from {module_}. It will not be available." + ) diff --git a/klondike/aws/redshift.py b/klondike/aws/redshift.py index 6281660..5163736 100644 --- a/klondike/aws/redshift.py +++ b/klondike/aws/redshift.py @@ -1,8 +1,6 @@ -from klondike.base.abc_klondike import KlondikeBaseDBConnector - -##### +from klondike.base.abc_klondike import KlondikeBaseDatabaseConnector # TODO -class RedshiftConnector(KlondikeBaseDBConnector): +class RedshiftConnector(KlondikeBaseDatabaseConnector): pass diff --git a/klondike/aws/s3.py b/klondike/aws/s3.py index 1aff979..b6f5ddf 100644 --- a/klondike/aws/s3.py +++ b/klondike/aws/s3.py @@ -1,8 +1,6 @@ -from klondike.base.abc_klondike import KlondikeBaseFlatFileConnector - -##### +from klondike.base.abc_klondike import KlondikeBaseStorageConnector # TODO -class S3Connector(KlondikeBaseFlatFileConnector): +class S3Connector(KlondikeBaseStorageConnector): pass diff --git a/klondike/base/abc_klondike.py b/klondike/base/abc_klondike.py index 61a0565..33d84b0 100644 --- a/klondike/base/abc_klondike.py +++ b/klondike/base/abc_klondike.py @@ -1,56 +1,154 @@ from abc import ABC, abstractmethod -from typing import Union +from typing import Any, Union import polars as pl -########## - -class KlondikeBaseDBConnector(ABC): +class KlondikeBaseDatabaseConnector(ABC): """ - This is the abstract class that all Klondike Database - connectors inherit from + Abstract base class for all Klondike database connectors. + + Defines the standard interface that all database implementations + (Snowflake, BigQuery, Postgres, Redshift) must implement. """ @property @abstractmethod def dialect(self) -> str: - pass + """Return the SQL dialect name for this connector (e.g., 'snowflake', 'bigquery').""" + ... @abstractmethod - def query(self) -> Union[pl.DataFrame, None]: + def query( + self, sql: str, timeout: int = 60, return_results: bool = True, **kwargs: Any + ) -> Union[pl.DataFrame, None]: + """ + Execute a SQL query and return results as a Polars DataFrame. + + Args: + sql: SQL query string to execute + timeout: Query timeout in seconds + return_results: Whether to return query results (True) or not (False) + **kwargs: Additional connector-specific query parameters + + Returns: + Polars DataFrame with query results, or None for DDL operations + """ pass @abstractmethod - def table_exists(self) -> bool: + def table_exists(self, table_name: str, **kwargs: Any) -> bool: + """ + Check if a table exists in the database. + + Args: + table_name: Name of the table to check + **kwargs: Additional connector-specific parameters (schema, database, etc.) + + Returns: + True if table exists, False otherwise + """ pass @abstractmethod - def list_tables(self) -> list: + def list_tables(self, schema_name: str, **kwargs: Any) -> list[str]: + """ + List all tables in a given schema. + + Args: + schema_name: Name of the schema to list tables from + **kwargs: Additional connector-specific parameters + + Returns: + List of table names + """ pass @abstractmethod - def read_dataframe(self) -> pl.DataFrame: + def read_dataframe(self, sql: str, **kwargs: Any) -> pl.DataFrame: + """ + Read data from the database into a Polars DataFrame. + + Args: + sql: SQL query to execute + **kwargs: Additional connector-specific parameters + + Returns: + Polars DataFrame containing query results + """ pass @abstractmethod - def write_dataframe(self) -> None: + def write_dataframe(self, df: pl.DataFrame, table_name: str, **kwargs: Any) -> None: + """ + Write a Polars DataFrame to the database. + + Args: + df: Polars DataFrame to write + table_name: Destination table name + **kwargs: Additional connector-specific parameters (if_exists, schema, etc.) + """ pass -class KlondikeBaseFlatFileConnector(ABC): +class KlondikeBaseStorageConnector(ABC): + """ + Abstract base class for all Klondike flat file storage connectors. + + Defines the standard interface for cloud storage implementations + (S3, Cloud Storage, etc.). + """ + @abstractmethod - def list_buckets(self) -> list: + def list_buckets(self, **kwargs: Any) -> list[str]: + """ + List all available buckets/containers. + + Returns: + List of bucket names + """ pass @abstractmethod - def list_blobs(self) -> list: + def list_blobs(self, bucket_name: str, **kwargs: Any) -> list[str]: + """ + List all blobs/objects in a bucket. + + Args: + bucket_name: Name of the bucket to list + **kwargs: Additional connector-specific parameters + + Returns: + List of blob/object names + """ pass @abstractmethod - def get_blob(self) -> pl.DataFrame: + def get_blob(self, bucket_name: str, blob_name: str, **kwargs: Any) -> pl.DataFrame: + """ + Read a blob/object from storage into a Polars DataFrame. + + Args: + bucket_name: Name of the bucket containing the blob + blob_name: Name of the blob to read + **kwargs: Additional connector-specific parameters + + Returns: + Polars DataFrame with blob contents + """ pass @abstractmethod - def put_blob(self) -> None: + def put_blob( + self, df: pl.DataFrame, bucket_name: str, blob_name: str, **kwargs: Any + ) -> None: + """ + Write a Polars DataFrame to storage as a blob/object. + + Args: + df: Polars DataFrame to write + bucket_name: Destination bucket name + blob_name: Destination blob name + **kwargs: Additional connector-specific parameters + """ pass diff --git a/klondike/gcp/bigquery.py b/klondike/gcp/bigquery.py index 3715553..eff703b 100644 --- a/klondike/gcp/bigquery.py +++ b/klondike/gcp/bigquery.py @@ -2,19 +2,17 @@ import json import os import tempfile -from typing import Optional, Union +from typing import Any, Optional, Union import polars as pl from google.cloud import bigquery from google.cloud.bigquery import LoadJobConfig from google.cloud.exceptions import NotFound -from klondike import logger -from klondike.base.abc_klondike import KlondikeBaseDBConnector +from klondike.base.abc_klondike import KlondikeBaseDatabaseConnector +from klondike.utilities.logger import logger from klondike.utilities.utilities import validate_if_exists_behavior -########## - SCOPES = ( { "scopes": [ @@ -24,7 +22,7 @@ )[0] -class BigQueryConnector(KlondikeBaseDBConnector): +class BigQueryConnector(KlondikeBaseDatabaseConnector): """ Establish and authenticate a connection to a BigQuery warehouse @@ -49,11 +47,11 @@ class BigQueryConnector(KlondikeBaseDBConnector): def __init__( self, - app_creds: Optional[Union[str, dict]] = None, + app_creds: Optional[Union[str, dict[str, Any]]] = None, project: Optional[str] = None, location: Optional[str] = None, timeout: int = 60, - client_options: dict = SCOPES, + client_options: dict[str, Any] = SCOPES, google_environment_variable: str = "GOOGLE_APPLICATION_CREDENTIALS", bypass_env_variable: bool = False, ): @@ -62,9 +60,9 @@ def __init__( self.location = location self.client_options = client_options - self.__dialect = "bigquery" - self.__client = None - self.__timeout = timeout + self._dialect = "bigquery" + self._client: Optional[bigquery.Client] = None + self._timeout = timeout if not self.app_creds: if ( @@ -89,34 +87,36 @@ def __init__( ) @property - def dialect(self): - return self.__dialect + def dialect(self) -> str: + return self._dialect @property - def client(self): + def client(self) -> bigquery.Client: """ Instantiate BigQuery client and assign it as class property """ - if not self.__client: - self.__client = bigquery.Client( + if self._client is None: + self._client = bigquery.Client( project=self.project, location=self.location, client_options=self.client_options, ) - return self.__client + return self._client @property - def timeout(self): - return self.__timeout + def timeout(self) -> int: + return self._timeout @timeout.setter - def timeout(self, timeout): - self.__timeout = timeout + def timeout(self, timeout: int) -> None: + self._timeout = timeout - def __setup_google_app_creds(self, app_creds: Union[str, dict], env_variable: str): + def __setup_google_app_creds( + self, app_creds: Union[str, dict[str, Any]], env_variable: str + ) -> None: "Sets runtime environment variable for Google SDK" if isinstance(app_creds, dict): @@ -135,14 +135,14 @@ def __set_load_job_config( self, base_job_config: Optional[LoadJobConfig] = None, max_bad_records: int = 0, - table_schema: list = None, + table_schema: Optional[list[dict[str, Any]]] = None, if_exists: str = "fail", - **kwargs, - ): + **kwargs: Any, + ) -> LoadJobConfig: "Defines `LoadConfigJob` when writing to BigQuery" - def set_write_disposition(if_exists: str): - DISPOSITION_MAP = { + def set_write_disposition(if_exists: str) -> str: + DISPOSITION_MAP: dict[str, str] = { "fail": bigquery.WriteDisposition.WRITE_EMPTY, "append": bigquery.WriteDisposition.WRITE_APPEND, "truncate": bigquery.WriteDisposition.WRITE_TRUNCATE, @@ -150,11 +150,11 @@ def set_write_disposition(if_exists: str): return DISPOSITION_MAP[if_exists] - def set_table_schema(table_schema: list): + def set_table_schema( + table_schema: list[dict[str, Any]], + ) -> list[bigquery.SchemaField]: return [bigquery.SchemaField(**x) for x in table_schema] - ### - if not base_job_config: logger.debug("No job config provided, starting fresh") base_job_config = LoadJobConfig() @@ -171,8 +171,6 @@ def set_table_schema(table_schema: list): base_job_config.max_bad_records = max_bad_records base_job_config.write_disposition = set_write_disposition(if_exists=if_exists) - ### - # List of available LoadJobConfig attributes _attributes = [x for x in dict(vars(LoadJobConfig)).keys()] @@ -188,11 +186,11 @@ def set_table_schema(table_schema: list): for k, v in kwargs.items(): if k in _attributes and k not in _reserved_attributes: logger.debug(f"Updating {k} parameter in job config [value={v}]") - base_job_config[k] = v + setattr(base_job_config, k, v) return base_job_config - def read_dataframe(self, sql: str) -> pl.DataFrame: + def read_dataframe(self, sql: str, **kwargs: Any) -> pl.DataFrame: """ Reads a Polars DataFrame based on a SQL query @@ -204,7 +202,10 @@ def read_dataframe(self, sql: str) -> pl.DataFrame: Polars DataFrame object """ - df = self.query(sql=sql, return_results=True) + df = self.query(sql=sql, return_results=True, **kwargs) + + if df is None: + return pl.DataFrame() return df @@ -214,9 +215,9 @@ def write_dataframe( table_name: str, load_job_config: Optional[LoadJobConfig] = None, max_bad_records: int = 0, - table_schema: list = None, + table_schema: Optional[list[dict[str, Any]]] = None, if_exists: str = "fail", - **load_kwargs, + **load_kwargs: Any, ) -> None: """ Writes a Polars DataFrame to BigQuery @@ -247,7 +248,7 @@ def write_dataframe( if_exists = "fail" load_job_config = self.__set_load_job_config( - base_load_conifg=load_job_config, + base_job_config=load_job_config, max_bad_records=max_bad_records, table_schema=table_schema, if_exists=if_exists, @@ -265,7 +266,7 @@ def write_dataframe( load_job.result() logger.info(f"Successfuly wrote {len(df)} rows to {table_name}") - def table_exists(self, table_name: str) -> bool: + def table_exists(self, table_name: str, **kwargs: Any) -> bool: """ Determines if a BigQuery table exists @@ -281,7 +282,7 @@ def table_exists(self, table_name: str) -> bool: except NotFound: return False - def list_tables(self, schema_name: str) -> list: + def list_tables(self, schema_name: str, **kwargs: Any) -> list[str]: """ Gets a list of available tables in a BigQuery schema @@ -299,8 +300,12 @@ def list_tables(self, schema_name: str) -> list: ] def query( - self, sql: str, timeout: Optional[int] = None, return_results: bool = True - ) -> pl.DataFrame: + self, + sql: str, + timeout: Optional[int] = None, + return_results: bool = True, + **kwargs: Any, + ) -> Union[pl.DataFrame, None]: """ Executes a SQL query and returns a Polars DataFrame. @@ -326,16 +331,21 @@ def query( result = query_job.result() # Read as arrow stream into Polars DataFrame - df = pl.from_arrow(result.to_arrow()) + result_arrow = result.to_arrow() + df = pl.from_arrow(result_arrow) + + # Ensure we return a DataFrame, not a Series + if isinstance(df, pl.Series): + df = df.to_frame() # Query yielded no results - if df.is_empty(): + if df.is_empty() and return_results: logger.warning("No results returned") return pl.DataFrame() # Intended for DDL calls (adding columns, creating views, etc.) elif not return_results: - return + return None # Query returned results else: diff --git a/klondike/gcp/cloud_storage.py b/klondike/gcp/cloud_storage.py index 8aeaf9d..2a4fca6 100644 --- a/klondike/gcp/cloud_storage.py +++ b/klondike/gcp/cloud_storage.py @@ -1,8 +1,157 @@ -from klondike.base.abc_klondike import KlondikeBaseFlatFileConnector +import os +from typing import Any, Optional, Union -########## +import polars as pl +from google.cloud.storage import Client +from klondike.base.abc_klondike import KlondikeBaseStorageConnector -# TODO -class CloudStorageConnector(KlondikeBaseFlatFileConnector): - pass + +class CloudStorageConnector(KlondikeBaseStorageConnector): + def __init__( + self, + app_creds: Optional[Union[str, dict[str, Any]]] = None, + project: Optional[str] = None, + location: Optional[str] = None, + google_environment_variable: str = "GOOGLE_APPLICATION_CREDENTIALS", + bypass_env_var_check: bool = False, + ): + """ + Initialize the Cloud Storage connector. + + Args: + app_creds: Optional credentials for authentication. + Can be a path to a JSON key file or a dictionary of credentials. + project: Optional GCP project name. + location: Optional GCP location/region. + google_environment_variable: Name of the environment variable to check for credentials if app_creds is not provided. + bypass_env_var_check: If True, will not check for environment variable if app_creds is None. Useful for cases where credentials are provided through other means (e.g., metadata server in GCP). + """ + + self.app_creds = app_creds + self.project = project + self.location = location + self.google_environment_variable = google_environment_variable + self.bypass_env_var_check = bypass_env_var_check + + self._client = None + + @property + def client(self) -> Client: + if self._client is None: + if self.app_creds is not None: + self._client = ( + Client.from_service_account_info(self.app_creds) + if isinstance(self.app_creds, dict) + else Client.from_service_account_json(self.app_creds) + ) + elif self.bypass_env_var_check: + self._client = Client() + elif ( + not self.bypass_env_var_check + and self.google_environment_variable in os.environ + ): + self._client = Client() + else: + raise ValueError( + "No credentials provided for Cloud Storage Connector. Please provide app_creds or set the appropriate environment variable." + ) + return self._client + + def list_blobs( + self, + bucket_name: str, + prefix: Optional[str] = None, + pattern: Optional[str] = None, + **kwargs: Any, + ) -> list[str]: + """ + List blobs in a specified bucket, with optional filtering by prefix and pattern. + + Args: + bucket_name: Name of the bucket to list blobs from. + prefix: Optional prefix to filter blobs (e.g., folder path). + pattern: Optional pattern to filter blobs (e.g., file extension). + + Returns: + List of blob names matching the specified criteria. + """ + + bucket = self.client.bucket(bucket_name) + blobs = bucket.list_blobs(prefix=prefix) + + if pattern: + blobs = [blob for blob in blobs if pattern in blob.name] + + return [blob.name for blob in blobs] + + def list_buckets(self, **kwargs: Any) -> list[str]: + """ + List all buckets in the project. + Returns: + List of bucket names in the project. + """ + + return [bucket.name for bucket in self.client.list_buckets()] + + def get_blob( + self, + bucket_name: str, + blob_name: str, + local_path: Optional[str] = None, + **kwargs: Any, + ) -> pl.DataFrame: + """ + Download a blob from Cloud Storage and read it as a Polars DataFrame. + + Args: + bucket_name: Name of the bucket containing the blob. + blob_name: Name of the blob to download. + local_path: Optional local file path to save the downloaded blob. If not provided, will save to a temp file. + Returns: + Polars DataFrame read from the blob. + """ + + bucket = self.client.bucket(bucket_name) + blob = bucket.blob(blob_name) + + if local_path is None: + local_path = f"/tmp/{os.path.basename(blob_name)}" + + blob.download_to_filename(local_path) + + # Read the file as a DataFrame (assuming CSV format, adjust as needed) + df = pl.read_csv(local_path) + + # Clean up temp file if we created it + if local_path.startswith("/tmp/"): + os.remove(local_path) + + return df + + def put_blob( + self, df: pl.DataFrame, bucket_name: str, blob_name: str, **kwargs: Any + ) -> None: + """ + Upload a Polars DataFrame to Cloud Storage as a blob. + + Args: + df: Polars DataFrame to upload. + bucket_name: Name of the destination bucket. + blob_name: Name of the destination blob (including any desired folder path). + """ + + bucket = self.client.bucket(bucket_name) + blob = bucket.blob(blob_name) + + # Save DataFrame to a temporary CSV file + temp_file_path = f"/tmp/{blob_name.replace('/', '_')}" + df.write_csv(temp_file_path) + + try: + # Upload the temporary file to Cloud Storage + blob.upload_from_filename(temp_file_path) + + finally: + # Clean up the temporary file + os.remove(temp_file_path) diff --git a/klondike/postgres/postgres.py b/klondike/postgres/postgres.py index f0f4717..d3d5529 100644 --- a/klondike/postgres/postgres.py +++ b/klondike/postgres/postgres.py @@ -1,8 +1,6 @@ -from klondike.base.abc_klondike import KlondikeBaseDBConnector - -########## +from klondike.base.abc_klondike import KlondikeBaseDatabaseConnector # TODO -class PostgresConnector(KlondikeBaseDBConnector): +class PostgresConnector(KlondikeBaseDatabaseConnector): pass diff --git a/klondike/scripts/__init__.py b/klondike/scripts/__init__.py new file mode 100644 index 0000000..76dfb67 --- /dev/null +++ b/klondike/scripts/__init__.py @@ -0,0 +1 @@ +from .stream_csv_to_database import stream_csv_to_database diff --git a/klondike/scripts/stream_csv_to_database.py b/klondike/scripts/stream_csv_to_database.py new file mode 100644 index 0000000..7bc0f6a --- /dev/null +++ b/klondike/scripts/stream_csv_to_database.py @@ -0,0 +1,56 @@ +from typing import Any, Union + +import polars as pl + +from klondike.aws.redshift import RedshiftConnector +from klondike.gcp.bigquery import BigQueryConnector +from klondike.snowflake.snowflake import SnowflakeConnector +from klondike.utilities.logger import logger + +##### + + +def stream_csv_to_database( + connector: Union[BigQueryConnector, SnowflakeConnector, RedshiftConnector], + csv_path: str, + destination_table_name: str, + batch_size: int = 10_000, + infer_schema_length: int = 0, + csv_separator: str = ",", + **bigquery_kwargs: Any, +) -> None: + """ + Stream a CSV file to a database in batches. + + Args: + connector: An instance of a database connector (BigQueryConnector, SnowflakeConnector, or RedshiftConnector) to use for uploading data. + csv_path: Path to the CSV file to be uploaded. + destination_table_name: Name of the destination table where the data will be created/overwritten. + batch_size: Number of rows to include in each batch upload (default: 10,000). + infer_schema_length: Number of rows to read for inferring schema (default: 0, which means no inference and all columns will be treated as strings). + csv_separator: The delimiter used in the CSV file (default: ","). + **bigquery_kwargs: Additional keyword arguments to pass to the BigQuery upload method (e.g., write_disposition, etc.). + """ + + lazy_df = pl.scan_csv( + csv_path, + separator=csv_separator, + infer_schema_length=infer_schema_length, + ) + + records_written = 0 + logger.info( + f"Streaming data from {csv_path} to table {destination_table_name} in batches of {batch_size}..." + ) + for batch_df in lazy_df.collect().iter_slices(n_rows=batch_size): + logger.debug(f"Uploading batch to table {destination_table_name}...") + connector.write_dataframe( + df=batch_df, + table_name=destination_table_name, + **bigquery_kwargs, + ) + records_written += len(batch_df) + + logger.info( + f"Finished streaming {records_written} rows to {destination_table_name}" + ) diff --git a/klondike/snowflake/snowflake.py b/klondike/snowflake/snowflake.py index d10f987..730fa4e 100644 --- a/klondike/snowflake/snowflake.py +++ b/klondike/snowflake/snowflake.py @@ -1,19 +1,17 @@ import os from contextlib import contextmanager -from typing import Optional +from typing import Any, Generator, Optional, Union import polars as pl import snowflake.connector as sf from snowflake.connector.pandas_tools import write_pandas -from klondike import logger -from klondike.base.abc_klondike import KlondikeBaseDBConnector -from klondike.utilities.utilities import validate_if_exists_behavior +from klondike.base.abc_klondike import KlondikeBaseDatabaseConnector +from klondike.utilities.logger import logger +from klondike.utilities.utilities import get_env_or_value, validate_if_exists_behavior -########## - -class SnowflakeConnector(KlondikeBaseDBConnector): +class SnowflakeConnector(KlondikeBaseDatabaseConnector): """ Leverages connection to Snowflake to read and write Polars DataFrame objects to the data warehouse @@ -48,38 +46,26 @@ def __init__( will be raised """ - self.snowflake_user = ( - snowflake_user if snowflake_user else os.getenv("SNOWFLAKE_USER") - ) - self.snowflake_password = ( - snowflake_password - if snowflake_password - else os.getenv("SNOWFLAKE_PASSWORD") + self.snowflake_user = get_env_or_value(snowflake_user, "SNOWFLAKE_USER") + self.snowflake_password = get_env_or_value( + snowflake_password, "SNOWFLAKE_PASSWORD" ) - self.snowflake_account = ( - snowflake_account if snowflake_account else os.getenv("SNOWFLAKE_ACCOUNT") + self.snowflake_account = get_env_or_value( + snowflake_account, "SNOWFLAKE_ACCOUNT" ) - self.__snowflake_warehouse = ( - snowflake_warehouse - if snowflake_warehouse - else os.getenv("SNOWFLAKE_WAREHOUSE") + self._snowflake_warehouse = get_env_or_value( + snowflake_warehouse, "SNOWFLAKE_WAREHOUSE" ) - self.__snowflake_database = ( - snowflake_database - if snowflake_database - else os.getenv("SNOWFLAKE_DATABASE") + self._snowflake_database = get_env_or_value( + snowflake_database, "SNOWFLAKE_DATABASE" ) - ### - - self.__validate_authentication() - - ### + self._validate_authentication() - self.__dialect = "snowflake" - self.row_chunk_size = row_chunk_size + self._dialect = "snowflake" + self._row_chunk_size = row_chunk_size - def __validate_authentication(self): + def _validate_authentication(self) -> None: _auth_vals = [ self.snowflake_user, self.snowflake_password, @@ -94,35 +80,35 @@ def __validate_authentication(self): ) @property - def dialect(self): - return self.__dialect + def dialect(self) -> str: + return self._dialect @property - def snowflake_warehouse(self): - return self.__snowflake_warehouse + def snowflake_warehouse(self) -> Optional[str]: + return self._snowflake_warehouse @snowflake_warehouse.setter - def snowflake_warehouse(self, warehouse): - self.__snowflake_warehouse = warehouse + def snowflake_warehouse(self, warehouse: str) -> None: + self._snowflake_warehouse = warehouse @property - def snowflake_database(self): - return self.__snowflake_database + def snowflake_database(self) -> Optional[str]: + return self._snowflake_database @snowflake_database.setter - def snowflake_database(self, database): - self.__snowflake_database = database + def snowflake_database(self, database: str) -> None: + self._snowflake_database = database @property - def row_chunk_size(self): - return self.__row_chunk_size + def row_chunk_size(self) -> int: + return self._row_chunk_size @row_chunk_size.setter - def row_chunk_size(self, row_chunk_size): - self.__row_chunk_size = row_chunk_size + def row_chunk_size(self, row_chunk_size: int) -> None: + self._row_chunk_size = row_chunk_size @contextmanager - def connection(self): + def connection(self) -> Generator[Any, None, None]: """ Creates a connection to Snowflake """ @@ -141,7 +127,7 @@ def connection(self): conn.close() @contextmanager - def cursor(self, connection): + def cursor(self, connection: Any) -> Generator[Any, None, None]: """ Leverages Snowflake connection to execute SQL transactions """ @@ -153,25 +139,34 @@ def cursor(self, connection): finally: cur.close() - def query(self, sql: str): + def query( + self, sql: str, timeout: int = 90, return_results: bool = True, **kwargs: Any + ) -> Union[pl.DataFrame, None]: """ Executes SQL command against Snowflake warehouse Args: - sql: `str` - SQL query in string format + sql (str): SQL command to be executed + return_results (bool): If True, returns query results as Polars DataFrame. + If False, returns None. + + Returns: + Polars DataFrame containing query results, or None for DDL operations """ with self.connection() as _conn: with self.cursor(_conn) as _cursor: - # TODO - Ugly! Clean this up _cursor.execute(f"USE DATABASE {self.snowflake_database};") _cursor.execute(f"USE WAREHOUSE {self.snowflake_warehouse};") _cursor.execute(sql) _resp = _cursor.fetch_arrow_batches() try: - return pl.from_arrow(_resp) + result = pl.from_arrow(_resp) + # Ensure we return a DataFrame, not a Series + if isinstance(result, pl.Series): + return result.to_frame() + return result except ValueError as ve: # NOTE - This appears to be Polars response to empty fetch_arrow_batches() # This should be interrogated more, but is functional @@ -180,7 +175,7 @@ def query(self, sql: str): return pl.DataFrame() raise - def read_dataframe(self, sql: str) -> pl.DataFrame: + def read_dataframe(self, sql: str, **kwargs: Any) -> pl.DataFrame: """ Executes a SQL query against the Snowflake warehouse and returns the result as a Polars DataFrame object @@ -194,22 +189,26 @@ def read_dataframe(self, sql: str) -> pl.DataFrame: """ # Execute SQL against warehouse - logger.debug("Running SQL...", sql) - df = self.query(sql=sql) + logger.debug("Running SQL...%s", sql) + result = self.query(sql=sql, **kwargs) - logger.info(f"Successfully read {len(df)} rows from Snowflake") + if result is None: + return pl.DataFrame() - return df + logger.info("Successfully read %d rows from Snowflake", len(result)) + + return result def write_dataframe( self, df: pl.DataFrame, table_name: str, - schema_name: str, + schema_name: str = "", database_name: Optional[str] = None, if_exists: str = "append", auto_create_table: bool = True, chunk_output: bool = False, + **kwargs: Any, ) -> None: """ Writes a Polars DataFrame to Snowflake @@ -257,16 +256,12 @@ def write_dataframe( auto_create_table = False elif if_exists == "fail": - if self.table_exists(schema_name=schema_name, table_name=table_name): + if self.table_exists(table_name=table_name, database_name=database_name): raise sf.errors.DatabaseError(f"{table_name} already exists") database = database_name if database_name else self.snowflake_database - ### - - logger.info( - f"Writing to {self.snowflake_database}.{schema_name}.{table_name}..." - ) + logger.info("Writing to %s.%s.%s...", database, schema_name, table_name) with self.connection() as conn: resp, num_chunks, num_rows, output = write_pandas( conn=conn, @@ -279,16 +274,14 @@ def write_dataframe( overwrite=overwrite, ) - ### - if resp: - logger.info(f"Successfully wrote {num_rows} rows to {table_name}") + logger.info("Successfully wrote %d rows to %s", num_rows, table_name) else: - logger.error(f"Failed to write to {table_name}", resp) + logger.error("Failed to write to %s", table_name, resp) raise def table_exists( - self, table_name: str, database_name: Optional[str] = None + self, table_name: str, database_name: Optional[str] = None, **kwargs: Any ) -> bool: """ Determines if a Snowflake table exists in the warehouse @@ -318,11 +311,14 @@ def table_exists( resp = self.query(sql=sql) + if resp is None: + return False + return not resp.is_empty() def list_tables( - self, schema_name: str, database_name: Optional[str] = None - ) -> list: + self, schema_name: str, database_name: Optional[str] = None, **kwargs: Any + ) -> list[str]: """ Gets a list of available tables in a Snowflake schema @@ -349,6 +345,9 @@ def list_tables( resp = self.query(sql=sql) + if resp is None: + return [] + resp = resp.select(table_name=pl.concat_str(resp.columns, separator=".")) return pl.Series(resp["table_name"]).to_list() diff --git a/klondike/utilities/logger.py b/klondike/utilities/logger.py new file mode 100644 index 0000000..70c7d1e --- /dev/null +++ b/klondike/utilities/logger.py @@ -0,0 +1,28 @@ +import logging +import os +import sys + +from colorlogger import ColoredFormatter + +logger = logging.getLogger(__name__) +_handler = logging.StreamHandler(sys.stdout) +_formatter = ColoredFormatter( + "%(log_color)s%(levelname)s%(reset)s %(message)s", + reset=True, + log_colors={ + "DEBUG": "cyan", + "INFO": "green", + "WARNING": "yellow", + "ERROR": "red", + "CRITICAL": "red,bg_white", + }, + style="%", +) + +_handler.setFormatter(_formatter) +logger.addHandler(_handler) +logger.setLevel("INFO") + +if os.environ.get("DEBUG") == "true": + logger.setLevel("DEBUG") + logger.debug("** Debugger Active **") diff --git a/klondike/utilities/utilities.py b/klondike/utilities/utilities.py index 7323d76..6bb4232 100644 --- a/klondike/utilities/utilities.py +++ b/klondike/utilities/utilities.py @@ -1,13 +1,38 @@ """ -General utilites to use across all database connections +General utilities to use across all database connections """ +import os +from typing import Optional + IF_EXISTS_BEHAVIOR = ["fail", "append", "truncate", "drop"] -def validate_if_exists_behavior(user_input: str, acceptable_values: list = IF_EXISTS_BEHAVIOR): +def validate_if_exists_behavior( + user_input: str, acceptable_values: list[str] = IF_EXISTS_BEHAVIOR +) -> bool: """ Ensures that user input to `write_dataframe` function is valid - 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-[tool.poetry] +[project] name = "klondike" -version = "0.2.3" +version = "0.3.0" +authors = [{ "name" = "Ian Richard Ferguson", "email" = "IAN@ianferguson.dev" }] description = "Klondike is a suite of database connectors, powered by Polars" -authors = ["Ian Ferguson "] +requires-python = "~=3.12.0" license = "MIT" - -repository = "https://github.com/IanRFerguson/klondike" -keywords = ["polars", "bigquery", "snowflake", "redshift"] +keywords = [ + "polars", + "bigquery", + "snowflake", + "redshift", + "elt", + "data engineering", + "data processing", +] readme = "./README.md" +dependencies = [ + "google-cloud-bigquery==3.40.0", + "google-cloud-storage==3.9.0", + "snowflake-connector-python==4.2.0", + "polars==1.38.1", + "pyarrow==23.0.0", + "colorlogger>=1.0", +] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" -[tool.poetry.dependencies] -python = "^3.8" -google-cloud-bigquery = "3.19.0" -snowflake-connector-python = "3.10.1" -polars = "0.20.16" -pyarrow = "15.0.2" +[tool.hatch.build.targets.wheel] +packages = ["klondike"] -[tool.poetry.dev-dependencies] -ruff = "0.9.1" -pytest = "8.3.3" +[dependency-groups] +dev = [ + "pytest~=8.0.0", + "pytest-cov~=4.1.0", + "pytest-watcher~=0.4.0", + "ruff~=0.4.0", + "mypy~=1.9.0", # Strict static type checking + "pre-commit~=3.4.0", + "jupyter>=1.1.1", +] [tool.ruff] -target-version = "py310" -line-length = 120 +line-length = 88 +indent-width = 4 +target-version = "py312" [tool.ruff.lint] +extend-ignore = [ + "F401", + "E203", + "E266", + "E402", + "E501", + "E711", + "E712", + "F403", + "F821", +] select = ["E", "F", "I"] -fixable = ["ALL"] + +[tool.ruff.format] +quote-style = "double" +indent-style = "space" +skip-magic-trailing-comma = false +line-ending = "auto" +docstring-code-format = false +docstring-code-line-length = "dynamic" + +[tool.mypy] +# Strict type checking configuration +strict = true +ignore_missing_imports = true +mypy_path = "." +explicit_package_bases = true + +[tool.pytest.ini_options] +testpaths = ["tests"] +pythonpath = ["."] diff --git a/tests/gcp/test_cloud_storage.py b/tests/gcp/test_cloud_storage.py index c324053..9343598 100644 --- a/tests/gcp/test_cloud_storage.py +++ b/tests/gcp/test_cloud_storage.py @@ -1,7 +1,290 @@ +import os import unittest +from unittest.mock import MagicMock, patch -########## +import polars as pl + +from klondike.gcp.cloud_storage import CloudStorageConnector +from tests.common.tests_common import MOCK_DATAFRAME_RESP class TestCloudStorageConnector(unittest.TestCase): - pass + def test_init_cloud_storage__app_creds_dict(self): + """ + Test for valid construction with explicit + application credentials as dictionary + """ + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + + assert isinstance(cs, CloudStorageConnector) + assert cs.app_creds == {"foo": "bar"} + + def test_init_cloud_storage__app_creds_path(self): + """ + Test for valid construction with explicit + application credentials as file path + """ + + cs = CloudStorageConnector(app_creds="/path/to/creds.json") + + assert isinstance(cs, CloudStorageConnector) + assert cs.app_creds == "/path/to/creds.json" + + @patch.dict( + os.environ, {"GOOGLE_APPLICATION_CREDENTIALS": "/path/to/env/creds.json"} + ) + def test_init_cloud_storage__env_variable(self): + """ + Test for valid construction when credentials are + provided via environment variable + """ + + cs = CloudStorageConnector() + + assert isinstance(cs, CloudStorageConnector) + assert cs.google_environment_variable in os.environ + + def test_init_cloud_storage__bypass_env_check(self): + """ + Test for valid construction when bypassing + environment variable check + """ + + cs = CloudStorageConnector(bypass_env_var_check=True) + + assert isinstance(cs, CloudStorageConnector) + assert cs.bypass_env_var_check is True + + @patch("klondike.gcp.cloud_storage.Client") + def test_list_buckets(self, MockClient): + """ + Test for list_buckets method + """ + + # Mock the client and buckets + mock_client = MagicMock() + MockClient.from_service_account_info.return_value = mock_client + + # Create mock bucket objects + mock_bucket_1 = MagicMock() + mock_bucket_1.name = "bucket-1" + + mock_bucket_2 = MagicMock() + mock_bucket_2.name = "bucket-2" + + mock_bucket_3 = MagicMock() + mock_bucket_3.name = "bucket-3" + + mock_client.list_buckets.return_value = [ + mock_bucket_1, + mock_bucket_2, + mock_bucket_3, + ] + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + buckets = cs.list_buckets() + + mock_client.list_buckets.assert_called_once() + + self.assertEqual(buckets, ["bucket-1", "bucket-2", "bucket-3"]) + + @patch("klondike.gcp.cloud_storage.Client") + def test_list_blobs__no_filter(self, MockClient): + """ + Test for list_blobs method without prefix or pattern + """ + + # Mock the client and bucket + mock_client = MagicMock() + MockClient.from_service_account_info.return_value = mock_client + + mock_bucket = MagicMock() + mock_client.bucket.return_value = mock_bucket + + # Create mock blob objects + mock_blob_1 = MagicMock() + mock_blob_1.name = "file1.csv" + + mock_blob_2 = MagicMock() + mock_blob_2.name = "file2.csv" + + mock_blob_3 = MagicMock() + mock_blob_3.name = "folder/file3.csv" + + mock_bucket.list_blobs.return_value = [ + mock_blob_1, + mock_blob_2, + mock_blob_3, + ] + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + blobs = cs.list_blobs(bucket_name="test-bucket") + + mock_client.bucket.assert_called_once_with("test-bucket") + mock_bucket.list_blobs.assert_called_once_with(prefix=None) + + self.assertEqual(blobs, ["file1.csv", "file2.csv", "folder/file3.csv"]) + + @patch("klondike.gcp.cloud_storage.Client") + def test_list_blobs__with_prefix(self, MockClient): + """ + Test for list_blobs method with prefix filter + """ + + # Mock the client and bucket + mock_client = MagicMock() + MockClient.from_service_account_info.return_value = mock_client + + mock_bucket = MagicMock() + mock_client.bucket.return_value = mock_bucket + + # Create mock blob objects (already filtered by prefix) + mock_blob_1 = MagicMock() + mock_blob_1.name = "folder/file1.csv" + + mock_blob_2 = MagicMock() + mock_blob_2.name = "folder/file2.csv" + + mock_bucket.list_blobs.return_value = [mock_blob_1, mock_blob_2] + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + blobs = cs.list_blobs(bucket_name="test-bucket", prefix="folder/") + + mock_client.bucket.assert_called_once_with("test-bucket") + mock_bucket.list_blobs.assert_called_once_with(prefix="folder/") + + self.assertEqual(blobs, ["folder/file1.csv", "folder/file2.csv"]) + + @patch("klondike.gcp.cloud_storage.Client") + def test_list_blobs__with_pattern(self, MockClient): + """ + Test for list_blobs method with pattern filter + """ + + # Mock the client and bucket + mock_client = MagicMock() + MockClient.from_service_account_info.return_value = mock_client + + mock_bucket = MagicMock() + mock_client.bucket.return_value = mock_bucket + + # Create mock blob objects + mock_blob_1 = MagicMock() + mock_blob_1.name = "file1.csv" + + mock_blob_2 = MagicMock() + mock_blob_2.name = "file2.parquet" + + mock_blob_3 = MagicMock() + mock_blob_3.name = "file3.csv" + + mock_bucket.list_blobs.return_value = [ + mock_blob_1, + mock_blob_2, + mock_blob_3, + ] + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + blobs = cs.list_blobs(bucket_name="test-bucket", pattern=".csv") + + mock_client.bucket.assert_called_once_with("test-bucket") + + # Should only return CSV files + self.assertEqual(blobs, ["file1.csv", "file3.csv"]) + + @patch("klondike.gcp.cloud_storage.Client") + @patch("polars.read_csv") + @patch("os.remove") + def test_get_blob(self, MockOsRemove, MockPolarsReadCsv, MockClient): + """ + Test for get_blob method + """ + + # Mock the client, bucket, and blob + mock_client = MagicMock() + MockClient.from_service_account_info.return_value = mock_client + + mock_bucket = MagicMock() + mock_client.bucket.return_value = mock_bucket + + mock_blob = MagicMock() + mock_bucket.blob.return_value = mock_blob + + # Mock Polars DataFrame + MockPolarsReadCsv.return_value = MOCK_DATAFRAME_RESP + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + df = cs.get_blob(bucket_name="test-bucket", blob_name="data/file.csv") + + # Assert correct method calls + mock_client.bucket.assert_called_once_with("test-bucket") + mock_bucket.blob.assert_called_once_with("data/file.csv") + mock_blob.download_to_filename.assert_called_once() + + # Assert DataFrame is returned + assert isinstance(df, pl.DataFrame) + assert "name" in df.columns + + # Assert temp file cleanup + MockOsRemove.assert_called_once() + + @patch("klondike.gcp.cloud_storage.Client") + @patch("polars.DataFrame.write_csv") + @patch("os.remove") + def test_put_blob(self, MockOsRemove, MockWriteCsv, MockClient): + """ + Test for put_blob method + """ + + # Mock the client, bucket, and blob + mock_client = MagicMock() + MockClient.from_service_account_info.return_value = mock_client + + mock_bucket = MagicMock() + mock_client.bucket.return_value = mock_bucket + + mock_blob = MagicMock() + mock_bucket.blob.return_value = mock_blob + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + cs.put_blob( + df=MOCK_DATAFRAME_RESP, + bucket_name="test-bucket", + blob_name="data/output.csv", + ) + + # Assert correct method calls + mock_client.bucket.assert_called_once_with("test-bucket") + mock_bucket.blob.assert_called_once_with("data/output.csv") + mock_blob.upload_from_filename.assert_called_once() + + # Assert temp file cleanup + MockOsRemove.assert_called_once() + + def test_client_lazy_initialization(self): + """ + Test that the client property is lazily initialized + """ + + cs = CloudStorageConnector(app_creds={"foo": "bar"}) + + # Client should be None before first access + assert cs._client is None + + @patch.dict(os.environ, {}, clear=True) + def test_client_no_credentials_error(self): + """ + Test that an error is raised when no credentials are provided + """ + + cs = CloudStorageConnector() + + with self.assertRaises(ValueError) as context: + _ = cs.client + + self.assertIn("No credentials provided", str(context.exception)) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/scripts/test_stream_csv_to_bigquery.py b/tests/scripts/test_stream_csv_to_bigquery.py new file mode 100644 index 0000000..b4675d0 --- /dev/null +++ b/tests/scripts/test_stream_csv_to_bigquery.py @@ -0,0 +1,339 @@ +import unittest +from unittest.mock import MagicMock, Mock, patch + +import polars as pl + +from klondike.gcp.bigquery import BigQueryConnector +from klondike.scripts.stream_csv_to_database import stream_csv_to_database + + +class TestStreamCsvToDatabase(unittest.TestCase): + def setUp(self): + """Set up test fixtures""" + # Create mock BigQueryConnector + self.mock_bq_connector = Mock(spec=BigQueryConnector) + + # Create test dataframes for batching + self.batch_1 = pl.DataFrame( + [ + {"id": 1, "name": "Alice", "value": 100}, + {"id": 2, "name": "Bob", "value": 200}, + ] + ) + self.batch_2 = pl.DataFrame( + [ + {"id": 3, "name": "Charlie", "value": 300}, + {"id": 4, "name": "David", "value": 400}, + ] + ) + self.batch_3 = pl.DataFrame( + [ + {"id": 5, "name": "Eve", "value": 500}, + ] + ) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_basic(self, mock_scan_csv): + """ + Test basic CSV streaming with default parameters + """ + # Mock the lazy dataframe and batches + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [self.batch_1, self.batch_2] + mock_scan_csv.return_value = mock_lazy_df + + # Execute the function + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.csv", + destination_table_name="test_dataset.test_table", + ) + + # Verify scan_csv was called with correct parameters + mock_scan_csv.assert_called_once_with( + "/path/to/test.csv", + separator=",", + infer_schema_length=0, + ) + + # Verify iter_slices was called with default batch size + mock_lazy_df.collect().iter_slices.assert_called_once_with(n_rows=10_000) + + # Verify write_dataframe was called twice (once per batch) + self.assertEqual(self.mock_bq_connector.write_dataframe.call_count, 2) + + # Verify the calls to write_dataframe + calls = self.mock_bq_connector.write_dataframe.call_args_list + self.assertEqual(calls[0][1]["table_name"], "test_dataset.test_table") + self.assertEqual(calls[1][1]["table_name"], "test_dataset.test_table") + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_custom_batch_size(self, mock_scan_csv): + """ + Test CSV streaming with custom batch size + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [ + self.batch_1, + self.batch_2, + self.batch_3, + ] + mock_scan_csv.return_value = mock_lazy_df + + # Execute with custom batch size + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.csv", + destination_table_name="test_dataset.test_table", + batch_size=500, + ) + + # Verify iter_slices was called with custom batch size + mock_lazy_df.collect().iter_slices.assert_called_once_with(n_rows=500) + + # Verify write_dataframe was called three times + self.assertEqual(self.mock_bq_connector.write_dataframe.call_count, 3) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_custom_separator(self, mock_scan_csv): + """ + Test CSV streaming with custom separator + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [self.batch_1] + mock_scan_csv.return_value = mock_lazy_df + + # Execute with custom separator + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.tsv", + destination_table_name="test_dataset.test_table", + csv_separator="\t", + ) + + # Verify scan_csv was called with tab separator + mock_scan_csv.assert_called_once_with( + "/path/to/test.tsv", + separator="\t", + infer_schema_length=0, + ) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_with_schema_inference(self, mock_scan_csv): + """ + Test CSV streaming with schema inference + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [self.batch_1] + mock_scan_csv.return_value = mock_lazy_df + + # Execute with schema inference + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.csv", + destination_table_name="test_dataset.test_table", + infer_schema_length=1000, + ) + + # Verify scan_csv was called with infer_schema_length + mock_scan_csv.assert_called_once_with( + "/path/to/test.csv", + separator=",", + infer_schema_length=1000, + ) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_with_bigquery_kwargs(self, mock_scan_csv): + """ + Test CSV streaming with additional BigQuery kwargs + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [self.batch_1, self.batch_2] + mock_scan_csv.return_value = mock_lazy_df + + # Execute with BigQuery kwargs + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.csv", + destination_table_name="test_dataset.test_table", + if_exists="append", + max_bad_records=10, + ) + + # Verify write_dataframe was called with kwargs + calls = self.mock_bq_connector.write_dataframe.call_args_list + for call_args in calls: + self.assertEqual(call_args[1]["if_exists"], "append") + self.assertEqual(call_args[1]["max_bad_records"], 10) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_single_batch(self, mock_scan_csv): + """ + Test CSV streaming with single batch (small file) + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [self.batch_1] + mock_scan_csv.return_value = mock_lazy_df + + # Execute + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/small.csv", + destination_table_name="test_dataset.test_table", + ) + + # Verify write_dataframe was called only once + self.assertEqual(self.mock_bq_connector.write_dataframe.call_count, 1) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_empty_batches(self, mock_scan_csv): + """ + Test CSV streaming with no batches (empty file) + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [] + mock_scan_csv.return_value = mock_lazy_df + + # Execute + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/empty.csv", + destination_table_name="test_dataset.test_table", + ) + + # Verify write_dataframe was never called + self.mock_bq_connector.write_dataframe.assert_not_called() + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_qualified_table_name(self, mock_scan_csv): + """ + Test that table name is correctly qualified with dataset + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [self.batch_1] + mock_scan_csv.return_value = mock_lazy_df + + # Execute with different dataset and table names + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.csv", + destination_table_name="my_dataset.my_table", + ) + + # Verify qualified table name + call_args = self.mock_bq_connector.write_dataframe.call_args + self.assertEqual(call_args[1]["table_name"], "my_dataset.my_table") + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_batch_ordering(self, mock_scan_csv): + """ + Test that batches are processed in correct order + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [ + self.batch_1, + self.batch_2, + self.batch_3, + ] + mock_scan_csv.return_value = mock_lazy_df + + # Execute + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.csv", + destination_table_name="test_dataset.test_table", + ) + + # Verify batches were processed in order + calls = self.mock_bq_connector.write_dataframe.call_args_list + self.assertEqual(len(calls), 3) + + # Check that each batch was written (checking the df parameter) + # Note: We can't directly compare DataFrames in mock calls easily, + # but we can verify the number of calls matches the number of batches + self.assertEqual(len(calls), 3) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_large_batch_count(self, mock_scan_csv): + """ + Test streaming with many batches + """ + mock_lazy_df = MagicMock() + # Simulate 100 batches + batches = [self.batch_1 for _ in range(100)] + mock_lazy_df.collect().iter_slices.return_value = batches + mock_scan_csv.return_value = mock_lazy_df + + # Execute + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/large.csv", + destination_table_name="test_dataset.test_table", + batch_size=1000, + ) + + # Verify write_dataframe was called 100 times + self.assertEqual(self.mock_bq_connector.write_dataframe.call_count, 100) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_different_file_paths(self, mock_scan_csv): + """ + Test with various file path formats + """ + mock_lazy_df = MagicMock() + mock_lazy_df.collect().iter_slices.return_value = [self.batch_1] + mock_scan_csv.return_value = mock_lazy_df + + test_paths = [ + "/absolute/path/to/file.csv", + "relative/path/file.csv", + "./current/dir/file.csv", + "../parent/dir/file.csv", + "gs://bucket/path/file.csv", # Cloud storage path + ] + + for path in test_paths: + mock_scan_csv.reset_mock() + self.mock_bq_connector.reset_mock() + + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path=path, + destination_table_name="test_dataset.test_table", + ) + + # Verify scan_csv was called with the correct path + mock_scan_csv.assert_called_once() + self.assertEqual(mock_scan_csv.call_args[0][0], path) + + @patch("klondike.scripts.stream_csv_to_database.pl.scan_csv") + def test_stream_csv_preserves_dataframe_content(self, mock_scan_csv): + """ + Test that dataframe content is preserved during streaming + """ + mock_lazy_df = MagicMock() + test_df = pl.DataFrame( + [ + {"id": 99, "name": "Test", "value": 999, "active": True}, + ] + ) + mock_lazy_df.collect().iter_slices.return_value = [test_df] + mock_scan_csv.return_value = mock_lazy_df + + # Execute + stream_csv_to_database( + connector=self.mock_bq_connector, + csv_path="/path/to/test.csv", + destination_table_name="test_dataset.test_table", + ) + + # Verify the dataframe passed to write_dataframe + call_args = self.mock_bq_connector.write_dataframe.call_args + written_df = call_args[1]["df"] + + # Check that we received a DataFrame + self.assertIsInstance(written_df, pl.DataFrame) + + +if __name__ == "__main__": + unittest.main() diff --git 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