From 9e2f903f46b034521fc7713568d80a4f50384544 Mon Sep 17 00:00:00 2001 From: Joscha Gutjahr Date: Mon, 27 Mar 2023 13:45:50 +0100 Subject: [PATCH 01/18] refactor: Clean slate --- .gitignore | 1 + demo/__init__.py | 0 demo/resources/definitions/input.yaml | 32 - demo/resources/definitions/processed.yaml | 40 - demo/resources/definitions/raw.yaml | 26 - demo/resources/schemas/input/bar.yaml | 40 - demo/resources/schemas/input/foo.yaml | 40 - .../schemas/processed/final_bar.yaml | 40 - .../schemas/processed/final_foo.yaml | 40 - demo/src/__init__.py | 29 - demo/src/__main__.py | 21 - demo/src/constants.py | 8 - demo/src/environment.py | 18 - demo/src/io.py | 38 - demo/src/runner_selection.py | 57 - demo/src/runners/__init__.py | 0 demo/src/runners/staging.py | 35 - demo/src/runners/transform.py | 40 - demo/tests/__init__.py | 0 demo/tests/conftest.py | 25 - demo/tests/constants.py | 13 - demo/tests/data/input/bar.parquet | Bin 3690 -> 0 bytes demo/tests/data/input/foo.csv | 11 - 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-> 0 bytes docs/index.html | 230 ---- docs/metrics.html | 929 -------------- docs/mixins/index.html | 107 -- docs/mixins/utils.html | 388 ------ docs/mixins/with_kafka.html | 477 -------- docs/mixins/with_local.html | 698 ----------- docs/mixins/with_postgres.html | 504 -------- docs/mixins/with_s3.html | 659 ---------- docs/validations.html | 923 -------------- .../data/processed => dynamicio}/.gitkeep | 0 dynamicio/__init__.py | 53 - dynamicio/__main__.py | 4 - dynamicio/cli.py | 103 -- dynamicio/config/__init__.py | 4 - dynamicio/config/io_config.py | 273 ----- dynamicio/config/pydantic/__init__.py | 13 - dynamicio/config/pydantic/config.py | 38 - dynamicio/config/pydantic/io_resources.py | 220 ---- dynamicio/config/pydantic/table_schema.py | 131 -- dynamicio/core.py | 315 ----- dynamicio/errors.py | 96 -- dynamicio/metrics.py | 178 --- dynamicio/mixins/__init__.py | 16 - dynamicio/mixins/utils.py | 141 --- dynamicio/mixins/with_kafka.py | 162 --- dynamicio/mixins/with_local.py | 257 ---- dynamicio/mixins/with_postgres.py | 197 --- dynamicio/mixins/with_s3.py | 397 ------ dynamicio/py.typed | 0 dynamicio/validations.py | 347 ------ tests/__init__.py | 0 tests/conftest.py | 913 -------------- tests/constants.py | 17 - tests/mocking/__init__.py | 0 tests/mocking/io.py | 188 --- tests/mocking/models.py | 33 - .../data/external/h5_with_more_columns.h5 | Bin 1064184 -> 0 bytes .../data/external/json_with_more_columns.json | 104 -- .../resources/data/input/batch/hdf/part_01.h5 | Bin 1064184 -> 0 bytes .../resources/data/input/batch/hdf/part_02.h5 | Bin 1064184 -> 0 bytes .../data/input/batch/not_just_hdf/part_01.h5 | Bin 1064184 -> 0 bytes .../data/input/batch/not_just_hdf/part_02.h5 | Bin 1064184 -> 0 bytes .../not_just_hdf/something_to_ignore.txt | 0 .../batch/not_just_parquet/part_01.parquet | Bin 3538 -> 0 bytes .../batch/not_just_parquet/part_02.parquet | Bin 3555 -> 0 bytes .../not_just_parquet/something_to_ignore.txt | 0 .../data/input/batch/parquet/part_01.parquet | Bin 3538 -> 0 bytes .../data/input/batch/parquet/part_02.parquet | Bin 3555 -> 0 bytes .../parquet_w_empty_files/emptyfile.parquet | Bin 2262 -> 0 bytes .../parquet_w_empty_files/fullfile.parquet | Bin 3822 -> 0 bytes .../resources/data/input/some_csv_to_read.csv | 16 - .../resources/data/input/some_hdf_to_read.h5 | Bin 1064184 -> 0 bytes .../data/input/some_json_to_read.json | 53 - .../data/input/some_parquet_to_read.parquet | Bin 2999 -> 0 bytes .../input/some_pg_parquet_to_read.parquet | Bin 3233 -> 0 bytes tests/resources/data/temp/.gitkeep | 0 tests/resources/definitions/external.yaml | 83 -- tests/resources/definitions/input.yaml | 287 ----- tests/resources/definitions/processed.yaml | 81 -- tests/resources/definitions/test_input.yaml | 129 -- tests/resources/schemas/bar.yaml | 48 - tests/resources/schemas/foo.yaml | 46 - tests/resources/schemas/pg.yaml | 40 - tests/resources/schemas/read_from_s3_csv.yaml | 50 - tests/resources/schemas/some_csv_to_read.yaml | 14 - tests/resources/schemas/some_hdf_to_read.yaml | 14 - .../resources/schemas/some_json_to_read.yaml | 14 - .../schemas/some_parquet_to_read.yaml | 14 - .../schemas/some_pg_parquet_to_read.yaml | 18 - tests/resources/schemas/write_to_s3_csv.yaml | 42 - tests/test_cli.py | 346 ------ tests/test_config.py | 181 --- tests/test_core.py | 1002 --------------- tests/test_metrics.py | 169 --- tests/test_mixins/test_kafka_mixins.py | 310 ----- tests/test_mixins/test_local_mixins.py | 795 ------------ tests/test_mixins/test_mixin_utils.py | 159 --- tests/test_mixins/test_postgres_mixins.py | 214 ---- tests/test_mixins/test_s3_mixins.py | 831 ------------- tests/test_regressions/conftest.py | 26 - .../resources/missing_v430_validations.yaml | 13 - tests/test_regressions/test_v430.py | 26 - tests/test_validations.py | 450 ------- 127 files changed, 1 insertion(+), 18253 deletions(-) delete mode 100644 demo/__init__.py delete mode 100644 demo/resources/definitions/input.yaml delete mode 100644 demo/resources/definitions/processed.yaml delete mode 100644 demo/resources/definitions/raw.yaml delete mode 100644 demo/resources/schemas/input/bar.yaml delete mode 100644 demo/resources/schemas/input/foo.yaml delete mode 100644 demo/resources/schemas/processed/final_bar.yaml delete mode 100644 demo/resources/schemas/processed/final_foo.yaml delete mode 100644 demo/src/__init__.py delete mode 100644 demo/src/__main__.py delete mode 100644 demo/src/constants.py delete mode 100644 demo/src/environment.py delete mode 100644 demo/src/io.py delete mode 100644 demo/src/runner_selection.py delete mode 100644 demo/src/runners/__init__.py delete mode 100644 demo/src/runners/staging.py delete mode 100644 demo/src/runners/transform.py delete mode 100644 demo/tests/__init__.py delete mode 100644 demo/tests/conftest.py delete mode 100644 demo/tests/constants.py delete mode 100644 demo/tests/data/input/bar.parquet delete mode 100644 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latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore +v4/ # User-specific files *.rsuser *.suo diff --git a/demo/__init__.py b/demo/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/demo/resources/definitions/input.yaml b/demo/resources/definitions/input.yaml deleted file mode 100644 index 9ef2adb..0000000 --- a/demo/resources/definitions/input.yaml +++ /dev/null @@ -1,32 +0,0 @@ ---- -FOO: - sample: - type: "local" - local: - file_path: "[[ TEST_RESOURCES ]]/data/input/foo.csv" - file_type: "csv" - actual: - type: "s3" - s3: - bucket: "[[ S3_YOUR_INPUT_BUCKET ]]" - file_path: "data/foo.h5" - file_type: "hdf" - schema: - file_path: "[[ RESOURCES ]]/schemas/input/foo.yaml" - -BAR: - sample: - type: "local" - local: - file_path: "[[ TEST_RESOURCES ]]/data/input/bar.parquet" - file_type: "parquet" - actual: - type: "postgres" - postgres: - db_host: "[[ DB_HOST ]]" - db_port: "[[ DB_PORT ]]" - db_name: "[[ DB_NAME ]]" - db_user: "[[ DB_USER ]]" - db_password: "[[ DB_PASS ]]" - schema: - file_path: "[[ RESOURCES ]]/schemas/input/bar.yaml" diff --git a/demo/resources/definitions/processed.yaml b/demo/resources/definitions/processed.yaml deleted file mode 100644 index d71116e..0000000 --- a/demo/resources/definitions/processed.yaml +++ /dev/null @@ -1,40 +0,0 @@ ---- -FINAL_FOO: - sample: - type: "local" - local: - file_path: "[[ TEST_RESOURCES ]]/data/processed/final_foo.parquet" - file_type: "parquet" - actual: - type: "s3" - s3: - bucket: "[[ S3_YOUR_OUTPUT_BUCKET ]]" - file_path: "live/data/processed/final_foo.parquet" - file_type: "parquet" - schema: - file_path: "[[ RESOURCES ]]/schemas/processed/final_foo.yaml" - -FINAL_BAR: - sample: - type: "local" - local: - file_path: "[[ TEST_RESOURCES ]]/data/processed/final_bar.parquet" - file_type: "parquet" - options: - use_deprecated_int96_timestamps: true - coerce_timestamps: "ms" - allow_truncated_timestamps: false - row_group_size: 1000000 - actual: - type: "kafka" - kafka: - kafka_server: "[[ KAFKA_SERVER ]]" - kafka_topic: "[[ KAFKA_TOPIC ]]" - options: - compression_type: "snappy" - max_in_flight_requests_per_connection: 10 - batch_size: 262144 - request_timeout_ms: 60000 # 60s - buffer_memory: 134217728 # 128MB - schema: - file_path: "[[ RESOURCES ]]/schemas/processed/final_bar.yaml" diff --git a/demo/resources/definitions/raw.yaml b/demo/resources/definitions/raw.yaml deleted file mode 100644 index 51a680c..0000000 --- a/demo/resources/definitions/raw.yaml +++ /dev/null @@ -1,26 +0,0 @@ ---- -STAGED_FOO: - sample: - type: "local" - local: - file_path: "[[ TEST_RESOURCES ]]/data/raw/staged_foo.parquet" - file_type: "parquet" - actual: - type: "s3" - s3: - bucket: "[[ S3_YOUR_OUTPUT_BUCKET ]]" - file_path: "live/data/raw/staged_foo.parquet" - file_type: "parquet" - -STAGED_BAR: - sample: - type: "local" - local: - file_path: "[[ TEST_RESOURCES ]]/data/raw/staged_bar.parquet" - file_type: "parquet" - actual: - type: "s3" - s3: - bucket: "[[ S3_YOUR_OUTPUT_BUCKET ]]" - file_path: "live/data/raw/staged_bar.parquet" - file_type: "parquet" diff --git a/demo/resources/schemas/input/bar.yaml b/demo/resources/schemas/input/bar.yaml deleted file mode 100644 index ef87b49..0000000 --- a/demo/resources/schemas/input/bar.yaml +++ /dev/null @@ -1,40 +0,0 @@ ---- -name: bar -columns: - column_a: - type: "object" - validations: - has_unique_values: - apply: true - options: {} - metrics: - - Counts - column_b: - type: "object" - validations: - has_no_null_values: - apply: true - options: {} - metrics: - - CountsPerLabel - column_c: - type: float64 - validations: - is_greater_than: - apply: true - options: - threshold: 1000 - metrics: [] - column_d: - type: float64 - validations: - is_lower_than: - apply: true - options: - threshold: 1000 - metrics: - - Min - - Max - - Mean - - Std - - Variance diff --git a/demo/resources/schemas/input/foo.yaml b/demo/resources/schemas/input/foo.yaml deleted file mode 100644 index 66d2e27..0000000 --- a/demo/resources/schemas/input/foo.yaml +++ /dev/null @@ -1,40 +0,0 @@ ---- -name: foo -columns: - column_a: - type: "object" - validations: - has_unique_values: - apply: true - options: {} - metrics: - - Counts - column_b: - type: "object" - validations: - has_no_null_values: - apply: true - options: {} - metrics: - - CountsPerLabel - column_c: - type: float64 - validations: - is_greater_than: - apply: true - options: - threshold: 1000 - metrics: [] - column_d: - type: float64 - validations: - is_lower_than: - apply: true - options: - threshold: 1000 - metrics: - - Min - - Max - - Mean - - Std - - Variance diff --git a/demo/resources/schemas/processed/final_bar.yaml b/demo/resources/schemas/processed/final_bar.yaml deleted file mode 100644 index b3f9d8c..0000000 --- a/demo/resources/schemas/processed/final_bar.yaml +++ /dev/null @@ -1,40 +0,0 @@ ---- -name: bar -columns: - column_a: - type: "object" - validations: - has_unique_values: - apply: true - options: {} - metrics: - - Counts - column_b: - type: "object" - validations: - has_no_null_values: - apply: true - options: {} - metrics: - - CountsPerLabel - column_c: - type: float64 - validations: - is_greater_than: - apply: true - options: - threshold: 1000 - metrics: [] - column_d: - type: float64 - validations: - is_lower_than: - apply: true - options: - threshold: "[[ LOWER_THAN_LIMIT ]]" - metrics: - - Min - - Max - - Mean - - Std - - Variance diff --git a/demo/resources/schemas/processed/final_foo.yaml b/demo/resources/schemas/processed/final_foo.yaml deleted file mode 100644 index ef87b49..0000000 --- a/demo/resources/schemas/processed/final_foo.yaml +++ /dev/null @@ -1,40 +0,0 @@ ---- -name: bar -columns: - column_a: - type: "object" - validations: - has_unique_values: - apply: true - options: {} - metrics: - - Counts - column_b: - type: "object" - validations: - has_no_null_values: - apply: true - options: {} - metrics: - - CountsPerLabel - column_c: - type: float64 - validations: - is_greater_than: - apply: true - options: - threshold: 1000 - metrics: [] - column_d: - type: float64 - validations: - is_lower_than: - apply: true - options: - threshold: 1000 - metrics: - - Min - - Max - - Mean - - Std - - Variance diff --git a/demo/src/__init__.py b/demo/src/__init__.py deleted file mode 100644 index babc177..0000000 --- a/demo/src/__init__.py +++ /dev/null @@ -1,29 +0,0 @@ -"""Set config IOs.""" -__all__ = ["input_config", "raw_config", "processed_config"] - -import logging -import os - -from demo.src import environment -from demo.src.environment import ENVIRONMENT, RESOURCES -from dynamicio.config import IOConfig - -logging.basicConfig(level=logging.INFO) -logging.getLogger("kafka").setLevel(logging.WARNING) - - -input_config = IOConfig( - path_to_source_yaml=(os.path.join(RESOURCES, "definitions/input.yaml")), - env_identifier=ENVIRONMENT, - dynamic_vars=environment, -) -raw_config = IOConfig( - path_to_source_yaml=(os.path.join(RESOURCES, "definitions/raw.yaml")), - env_identifier=ENVIRONMENT, - dynamic_vars=environment, -) -processed_config = IOConfig( - path_to_source_yaml=(os.path.join(RESOURCES, "definitions/processed.yaml")), - env_identifier=ENVIRONMENT, - dynamic_vars=environment, -) diff --git a/demo/src/__main__.py b/demo/src/__main__.py deleted file mode 100644 index 610d826..0000000 --- a/demo/src/__main__.py +++ /dev/null @@ -1,21 +0,0 @@ -"""The main module that serves as the entry point for all the other sub-modules under the: loader, pre_process and the publish packages.""" -# pylint: disable=unused-argument - -from functools import partial -from signal import SIGINT, SIGTERM, getsignal, signal - -from demo.src.runner_selection import choose_module, create_parser, custom_signal_handler -from demo.src.runners import staging, transform - -AIRFLOW_TASK_MODULES = {"staging": staging, "transform": transform} - -# Run the respective handler() functions when SIGINT or SIGTERM is received -signal(SIGINT, partial(custom_signal_handler, default_func=(getsignal(SIGINT)))) -signal(SIGTERM, partial(custom_signal_handler, default_func=(getsignal(SIGTERM)))) - -# Load input args -parser = create_parser(AIRFLOW_TASK_MODULES) -args = parser.parse_args() - -func = choose_module(args.with_module, AIRFLOW_TASK_MODULES) -func.main() diff --git a/demo/src/constants.py b/demo/src/constants.py deleted file mode 100644 index 3d13c43..0000000 --- a/demo/src/constants.py +++ /dev/null @@ -1,8 +0,0 @@ -"""A module for configuring all constants:""" - -# Parquet -TO_PARQUET_KWARGS = { - "use_deprecated_int96_timestamps": False, - "coerce_timestamps": "ms", - "allow_truncated_timestamps": True, -} diff --git a/demo/src/environment.py b/demo/src/environment.py deleted file mode 100644 index cbc5a91..0000000 --- a/demo/src/environment.py +++ /dev/null @@ -1,18 +0,0 @@ -"""A module for configuring all environment variables.""" -import os - -ENVIRONMENT = "sample" -CLOUD_ENV = "DEV" -RESOURCES = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../resources") -TEST_RESOURCES = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../tests") -S3_YOUR_INPUT_BUCKET = None -S3_YOUR_OUTPUT_BUCKET = None -KAFKA_SERVER = None -KAFKA_TOPIC = None -DB_HOST = None -DB_PORT = None -DB_NAME = None -DB_USER = None -DB_PASS = None -REFERENCE_DATA_STATE_KEY = None -LOWER_THAN_LIMIT = 1000 diff --git a/demo/src/io.py b/demo/src/io.py deleted file mode 100644 index c7e0098..0000000 --- a/demo/src/io.py +++ /dev/null @@ -1,38 +0,0 @@ -"""Responsible for configuring io operations for input data.""" -# pylint: disable=too-few-public-methods -__all__ = ["InputIO", "StagedFoo", "StagedBar"] - -from sqlalchemy.ext.declarative import declarative_base - -from dynamicio import UnifiedIO, WithLocal, WithPostgres, WithS3File -from dynamicio.core import SCHEMA_FROM_FILE, DynamicDataIO - -Base = declarative_base() - - -class InputIO(UnifiedIO): - """UnifiedIO subclass for V6 data.""" - - schema = SCHEMA_FROM_FILE - - -class StagedFoo(WithS3File, WithLocal, DynamicDataIO): - """UnifiedIO subclass for staged foos.""" - - schema = { - "column_a": "object", - "column_b": "object", - "column_c": "int64", - "column_d": "int64", - } - - -class StagedBar(WithLocal, WithPostgres, DynamicDataIO): - """UnifiedIO subclass for cargo movements volumes data.""" - - schema = { - "column_a": "object", - "column_b": "object", - "column_c": "int64", - "column_d": "int64", - } diff --git a/demo/src/runner_selection.py b/demo/src/runner_selection.py deleted file mode 100644 index 137740f..0000000 --- a/demo/src/runner_selection.py +++ /dev/null @@ -1,57 +0,0 @@ -"""Pipeline utilities for all tasks.""" -import argparse -import logging -from signal import signal -from types import FrameType -from typing import Callable - -logger = logging.getLogger(__name__) - - -def custom_signal_handler(signal_received: int, frame: FrameType, default_func: Callable[[int, FrameType], None]): - """A custom signal handler for managing SIGINT and SIGTERM signals. - - Args: - signal_received: The signal received - frame: The frame from which the signal was sent. - default_func: The handler to delegate to. - """ - logger.info(f"Termination signal detected: {signal_received}. Exiting gracefully...") - default_func(signal, frame) - - -def create_parser(airflow_task_modules: dict) -> argparse.ArgumentParser: - """Generates an argument parser for the docker container's entry point, namely for `pipeline.src.main`. - - - Parameter name: `--with_module` - - Options: staging, transform or sink - Args: - airflow_task_modules: The names of the airflow tasks to be chosen - Returns: - argparse.ArgumentParser - """ - _parser = argparse.ArgumentParser() - _parser.add_argument("--with_module", type=str, choices=list(airflow_task_modules.keys())) - return _parser - - -def choose_module(module_arg: str, airflow_task_modules: dict): - """A function for choosing the a module to serve as the entry point for an Airflow task. - - A choice can be provided from the below list: - - - "staging" - - "transform" - - "sink" - - Args: - module_arg: str: The parsed argument provided as a parameter in an airflow task in the respective airflow dag. - airflow_task_modules: - - Returns: - func: Return the respective module, based on the provided input. - """ - try: - return airflow_task_modules[module_arg] - except KeyError as error_key: - raise ValueError("Invalid input argument...") from error_key diff --git a/demo/src/runners/__init__.py b/demo/src/runners/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/demo/src/runners/staging.py b/demo/src/runners/staging.py deleted file mode 100644 index 1327866..0000000 --- a/demo/src/runners/staging.py +++ /dev/null @@ -1,35 +0,0 @@ -"""Add module docstring....""" -import logging - -from demo.src import constants, input_config, raw_config -from demo.src.io import InputIO, StagedBar, StagedFoo - -logger = logging.getLogger(__name__) - - -def main() -> None: - """The entry point for the Airflow Staging task. - - Returns: - Void function. - """ - # LOAD DATA - logger.info("Loading data from live sources...") - - bar_df = InputIO(source_config=input_config.get(source_key="BAR"), apply_schema_validations=True, log_schema_metrics=True).read() - foo_df = InputIO(source_config=input_config.get(source_key="FOO"), apply_schema_validations=True, log_schema_metrics=True).read() - - logger.info("Data successfully loaded from live sources...") - - # TRANSFORM DATA - logger.info("Apply transformations...") - - # TODO: Apply your transformations - - logger.info("Transformations applied successfully...") - - # SINK DATA - logger.info("Begin sinking data to staging area:") - StagedFoo(source_config=raw_config.get(source_key="STAGED_FOO"), **constants.TO_PARQUET_KWARGS).write(foo_df) - StagedBar(source_config=raw_config.get(source_key="STAGED_BAR")).write(bar_df) - logger.info("Data staging is complete...") diff --git a/demo/src/runners/transform.py b/demo/src/runners/transform.py deleted file mode 100644 index 6d9d85a..0000000 --- a/demo/src/runners/transform.py +++ /dev/null @@ -1,40 +0,0 @@ -"""Add module docstring....""" -import asyncio -import logging - -import demo.src.environment -from demo.src import processed_config, raw_config -from demo.src.io import InputIO, StagedBar, StagedFoo - -logger = logging.getLogger(__name__) - - -async def main() -> None: - """The entry point for the Airflow Staging task. - - Returns: - Void function. - """ - # LOAD DATA - logger.info("Loading data from live sources...") - - [bar_df, foo_df] = await asyncio.gather( - StagedBar(source_config=raw_config.get(source_key="STAGED_BAR")).async_read(), StagedFoo(source_config=raw_config.get(source_key="STAGED_FOO")).async_read() - ) - - logger.info("Data successfully loaded from live sources...") - - # TRANSFORM DATA - logger.info("Apply transformations...") - - # TODO: Apply your transformations - - logger.info("Transformations applied successfully...") - - # SINK DATA - logger.info(f"Begin sinking data to staging area: S3:{demo.src.environment.S3_YOUR_OUTPUT_BUCKET}:live/data/raw") - await asyncio.gather( - InputIO(source_config=processed_config.get(source_key="FINAL_FOO"), apply_schema_validations=True, log_schema_metrics=True).async_write(foo_df), - InputIO(source_config=processed_config.get(source_key="FINAL_BAR"), apply_schema_validations=True, log_schema_metrics=True).async_write(bar_df), - ) - logger.info("Data staging is complete...") diff --git a/demo/tests/__init__.py b/demo/tests/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/demo/tests/conftest.py b/demo/tests/conftest.py deleted file mode 100644 index a0a2bd3..0000000 --- a/demo/tests/conftest.py +++ /dev/null @@ -1,25 +0,0 @@ -# pylint: disable=missing-module-docstring, missing-class-docstring, missing-function-docstring -import pandas as pd -import pytest - -from demo.tests import constants - - -@pytest.fixture(scope="class") -def expected_staged_foo_df(): - return pd.read_parquet(f"{constants.E2E_TEST_RESOURCES}/data/raw/expected/staged_foo.parquet") - - -@pytest.fixture(scope="class") -def expected_staged_bar_df(): - return pd.read_parquet(f"{constants.E2E_TEST_RESOURCES}/data/raw/expected/staged_bar.parquet") - - -@pytest.fixture(scope="class") -def expected_final_foo_df(): - return pd.read_parquet(f"{constants.E2E_TEST_RESOURCES}/data/processed/expected/final_foo.parquet") - - -@pytest.fixture(scope="class") -def expected_final_bar_df(): - return pd.read_parquet(f"{constants.E2E_TEST_RESOURCES}/data/processed/expected/final_bar.parquet") diff --git a/demo/tests/constants.py b/demo/tests/constants.py deleted file mode 100644 index a9020ce..0000000 --- a/demo/tests/constants.py +++ /dev/null @@ -1,13 +0,0 @@ -"""A module for configuring all dynamic environment variables for testing purposes""" -import os - -E2E_TEST_RESOURCES = os.path.join(os.path.dirname(os.path.realpath(__file__))) - -# Dynamic Vars -S3_INPUT_BUCKET = "mock-foo-input-bucket" -S3_OUTPUT_BUCKET = "mock-bar-output-bucket" -DB_HOST = "10.0.2.217" -DB_PORT = "5432" -DB_NAME = "backend" -DB_USER = "user" 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disable=missing-module-docstring, missing-class-docstring, missing-function-docstring -# noqa -import pytest - - -class TestStaging: - @pytest.mark.unit - def test_a_function(self): - # Given - - # When - - # Then - assert True - - @pytest.mark.integration - def test_a_combination_of_functions(self): - # Given - - # When - - # Then - assert True diff --git a/demo/tests/runners/test_transform.py b/demo/tests/runners/test_transform.py deleted file mode 100644 index 51f6640..0000000 --- a/demo/tests/runners/test_transform.py +++ /dev/null @@ -1,22 +0,0 @@ -# pylint: disable=missing-module-docstring, missing-class-docstring, missing-function-docstring, no-self-use -import pytest - - -class TestTransform: - @pytest.mark.unit - def test_a_function(self): - # Given - - # When - - # Then - assert True - - @pytest.mark.integration - def test_a_combination_of_functions(self): - # Given - - # When - - # Then - assert True diff --git a/demo/tests/test_pipeline.py b/demo/tests/test_pipeline.py deleted file mode 100644 index 185529b..0000000 --- a/demo/tests/test_pipeline.py +++ /dev/null @@ -1,55 +0,0 @@ -"""An example pipeline to showcase how dynamicio can bt used for setting up a local e2e testing!""" -# pylint: disable=missing-module-docstring, missing-class-docstring, missing-function-docstring, unused-argument, too-few-public-methods -# noqa -import asyncio -import os - -import pandas as pd -import pytest - -from demo.src import processed_config, raw_config -from demo.src.runners import staging, transform - - -class TestPipeline: - """Example e2e test.""" - - @pytest.mark.end_to_end - def test_dag_with_mock_sample_input_data( - self, - expected_staged_foo_df, - expected_staged_bar_df, - expected_final_foo_df, - expected_final_bar_df, - ): - """Showcases how you can leverage dynamicio to read local data for fast feedback when you want to run your pipelines locally.""" - # Given - # The src/resources/input.yaml - - # When - staging.main() - asyncio.run(transform.main()) - - # Then - try: - pd.testing.assert_frame_equal( - expected_staged_foo_df, - pd.read_parquet(raw_config.get(source_key="STAGED_FOO").local.file_path) - ) - pd.testing.assert_frame_equal( - expected_staged_bar_df, - pd.read_parquet(raw_config.get(source_key="STAGED_BAR").local.file_path) - ) - pd.testing.assert_frame_equal( - expected_final_foo_df, - pd.read_parquet(processed_config.get(source_key="FINAL_FOO").local.file_path) - ) - pd.testing.assert_frame_equal( - expected_final_bar_df, - pd.read_parquet(processed_config.get(source_key="FINAL_BAR").local.file_path) - ) - finally: - os.remove(raw_config.get(source_key="STAGED_FOO").local.file_path) - os.remove(raw_config.get(source_key="STAGED_BAR").local.file_path) - os.remove(processed_config.get(source_key="FINAL_FOO").local.file_path) - os.remove(processed_config.get(source_key="FINAL_BAR").local.file_path) diff --git a/demo/tests/test_runner_selection.py b/demo/tests/test_runner_selection.py deleted file mode 100644 index 821ea23..0000000 --- a/demo/tests/test_runner_selection.py +++ /dev/null @@ -1,41 +0,0 @@ -# pylint: disable=missing-module-docstring, missing-class-docstring, missing-function-docstring, no-self-use - -import pytest - -from demo.src.runner_selection import choose_module -from demo.src.runners import staging, transform - -AIRFLOW_TASK_MODULES = {"staging": staging, "transform": transform} - - -class TestUtilities: - @pytest.mark.unit - def test_choose_module_returns_the_staging_module_with_module_arg_set_to_staging(self): - # Given - module_arg = "staging" - - # When - func = choose_module(module_arg, AIRFLOW_TASK_MODULES) - - # Then - assert func == staging - - @pytest.mark.unit - def test_choose_module_returns_the_transform_module_with_module_arg_set_to_transform(self): - # Given - module_arg = "transform" - - # When - func = choose_module(module_arg, AIRFLOW_TASK_MODULES) - - # Then - assert func == transform - - @pytest.mark.unit - def test_choose_module_raises_value_error_with_module_arg_set_to_false_input(self): - # Given - module_arg = "whatever" - - # When/Then - with pytest.raises(ValueError): - choose_module(module_arg, AIRFLOW_TASK_MODULES) diff --git a/docs/cli.html b/docs/cli.html deleted file mode 100644 index ca7b4e3..0000000 --- a/docs/cli.html +++ /dev/null @@ -1,326 +0,0 @@ - - - - - - -dynamicio.cli API documentation - - - - - - - - - - - -
-
-
-

Module dynamicio.cli

-
-
-

Implements the dynamicio Command Line Interface (CLI).

-
- -Expand source code - -
"""Implements the dynamicio Command Line Interface (CLI)."""
-import argparse
-import glob
-import os
-import pprint
-from typing import Mapping, MutableMapping, Optional, Sequence
-
-import pandas as pd  # type: ignore
-import yaml
-
-from dynamicio.errors import InvalidDatasetTypeError
-
-
-def parse_args(args: Optional[Sequence] = None) -> argparse.Namespace:
-    """Arguments parser for dynamicio cli.py.
-
-    Args:
-        args: List of args to be parsed. Defaults to None, in which case
-            sys.argv[1:] is used.
-
-    Returns:
-        An instance of ArgumentParser populated with the provided args.
-    """
-    parser = argparse.ArgumentParser(prog="dynamicio", description="Generate dataset schemas")
-    group = parser.add_mutually_exclusive_group(required=True)
-    group.add_argument(
-        "-b",
-        "--batch",
-        action="store_true",
-        help="flag, used to generate multiple schemas provided a datasets directory.",
-    )
-    group.add_argument(
-        "-s",
-        "--single",
-        action="store_true",
-        help="flag, used to generate a schema provided a single dataset.",
-    )
-    parser.add_argument("-p", "--path", required=True, help="the path to the dataset/datasets-directory.", type=str)
-    parser.add_argument("-o", "--output", required=True, help="the path to the schemas output directory.", type=str)
-    return parser.parse_args(args)
-
-
-def generate_schema_for(dataset: str) -> Mapping:
-    """Generate a schema for a dataset.
-
-    Args:
-        dataset: The path to the dataset for which we want to generate a schema
-
-    Returns:
-        A dictionary containing the schema for the dataset, or None if the dataset is not valid.
-
-    Raises:
-        InvalidDatasetTypeError: If the dataset type is not supported by dynamicio.
-    """
-    dataset_name, file_type = os.path.splitext(os.path.basename(dataset))
-    if file_type == ".parquet":
-        df = pd.read_parquet(dataset)
-    elif file_type == ".csv":
-        df = pd.read_csv(dataset)
-    elif file_type == ".json":
-        df = pd.read_json(dataset)
-    elif file_type == ".h5":
-        df = pd.read_hdf(dataset)
-    else:
-        raise InvalidDatasetTypeError(dataset)
-
-    print(f"Generating schema for: {dataset}")
-    json_schema: MutableMapping = {"name": dataset_name, "columns": {}}
-    for column, d_type in zip(list(df.columns), list(df.dtypes)):
-        json_schema["columns"][column] = {"type": "", "validations": {}, "metrics": []}
-        json_schema["columns"][column]["type"] = d_type.name
-
-    return json_schema
-
-
-def main(args: argparse.Namespace):
-    """Main function for dynamicio cli.py.
-
-    Args:
-        args: Parsed args.
-    """
-    if args.batch:
-        dataset_files = glob.glob(os.path.join(args.path, "*.*"))
-        for dataset in dataset_files:
-            try:
-                json_schema = generate_schema_for(dataset)
-            except InvalidDatasetTypeError as exception:
-                print(f"Skipping {exception.message}! You may want to remove this file from the datasets directory")
-            else:
-                with open(os.path.join(args.output, f"{json_schema['name']}.yaml"), "w") as yml:  # pylint: disable=unspecified-encoding]
-                    yaml.safe_dump(json_schema, yml)
-
-    if args.single:
-        json_schema = generate_schema_for(str(args.path))
-        with open(os.path.join(args.output, f"{json_schema['name']}.yaml"), "w") as yml:  # pylint: disable=unspecified-encoding]
-            yaml.safe_dump(json_schema, yml)
-        pprint.pprint(json_schema)
-
-
-def run():
-    """Entry point for the dynamicio cli.py."""
-    args = parse_args()
-    main(args)
-
-
-
-
-
-
-
-

Functions

-
-
-def generate_schema_for(dataset: str) ‑> Mapping[~KT, +VT_co] -
-
-

Generate a schema for a dataset.

-

Args

-
-
dataset
-
The path to the dataset for which we want to generate a schema
-
-

Returns

-

A dictionary containing the schema for the dataset, or None if the dataset is not valid.

-

Raises

-
-
InvalidDatasetTypeError
-
If the dataset type is not supported by dynamicio.
-
-
- -Expand source code - -
def generate_schema_for(dataset: str) -> Mapping:
-    """Generate a schema for a dataset.
-
-    Args:
-        dataset: The path to the dataset for which we want to generate a schema
-
-    Returns:
-        A dictionary containing the schema for the dataset, or None if the dataset is not valid.
-
-    Raises:
-        InvalidDatasetTypeError: If the dataset type is not supported by dynamicio.
-    """
-    dataset_name, file_type = os.path.splitext(os.path.basename(dataset))
-    if file_type == ".parquet":
-        df = pd.read_parquet(dataset)
-    elif file_type == ".csv":
-        df = pd.read_csv(dataset)
-    elif file_type == ".json":
-        df = pd.read_json(dataset)
-    elif file_type == ".h5":
-        df = pd.read_hdf(dataset)
-    else:
-        raise InvalidDatasetTypeError(dataset)
-
-    print(f"Generating schema for: {dataset}")
-    json_schema: MutableMapping = {"name": dataset_name, "columns": {}}
-    for column, d_type in zip(list(df.columns), list(df.dtypes)):
-        json_schema["columns"][column] = {"type": "", "validations": {}, "metrics": []}
-        json_schema["columns"][column]["type"] = d_type.name
-
-    return json_schema
-
-
-
-def main(args: argparse.Namespace) -
-
-

Main function for dynamicio cli.py.

-

Args

-
-
args
-
Parsed args.
-
-
- -Expand source code - -
def main(args: argparse.Namespace):
-    """Main function for dynamicio cli.py.
-
-    Args:
-        args: Parsed args.
-    """
-    if args.batch:
-        dataset_files = glob.glob(os.path.join(args.path, "*.*"))
-        for dataset in dataset_files:
-            try:
-                json_schema = generate_schema_for(dataset)
-            except InvalidDatasetTypeError as exception:
-                print(f"Skipping {exception.message}! You may want to remove this file from the datasets directory")
-            else:
-                with open(os.path.join(args.output, f"{json_schema['name']}.yaml"), "w") as yml:  # pylint: disable=unspecified-encoding]
-                    yaml.safe_dump(json_schema, yml)
-
-    if args.single:
-        json_schema = generate_schema_for(str(args.path))
-        with open(os.path.join(args.output, f"{json_schema['name']}.yaml"), "w") as yml:  # pylint: disable=unspecified-encoding]
-            yaml.safe_dump(json_schema, yml)
-        pprint.pprint(json_schema)
-
-
-
-def parse_args(args: Optional[Sequence[+T_co]] = None) ‑> argparse.Namespace -
-
-

Arguments parser for dynamicio cli.py.

-

Args

-
-
args
-
List of args to be parsed. Defaults to None, in which case -sys.argv[1:] is used.
-
-

Returns

-

An instance of ArgumentParser populated with the provided args.

-
- -Expand source code - -
def parse_args(args: Optional[Sequence] = None) -> argparse.Namespace:
-    """Arguments parser for dynamicio cli.py.
-
-    Args:
-        args: List of args to be parsed. Defaults to None, in which case
-            sys.argv[1:] is used.
-
-    Returns:
-        An instance of ArgumentParser populated with the provided args.
-    """
-    parser = argparse.ArgumentParser(prog="dynamicio", description="Generate dataset schemas")
-    group = parser.add_mutually_exclusive_group(required=True)
-    group.add_argument(
-        "-b",
-        "--batch",
-        action="store_true",
-        help="flag, used to generate multiple schemas provided a datasets directory.",
-    )
-    group.add_argument(
-        "-s",
-        "--single",
-        action="store_true",
-        help="flag, used to generate a schema provided a single dataset.",
-    )
-    parser.add_argument("-p", "--path", required=True, help="the path to the dataset/datasets-directory.", type=str)
-    parser.add_argument("-o", "--output", required=True, help="the path to the schemas output directory.", type=str)
-    return parser.parse_args(args)
-
-
-
-def run() -
-
-

Entry point for the dynamicio cli.py.

-
- -Expand source code - -
def run():
-    """Entry point for the dynamicio cli.py."""
-    args = parse_args()
-    main(args)
-
-
-
-
-
-
-
- -
- - - \ No newline at end of file diff --git a/docs/config.html b/docs/config.html deleted file mode 100644 index 1978a61..0000000 --- a/docs/config.html +++ /dev/null @@ -1,1087 +0,0 @@ - - - - - - -dynamicio.config API documentation - - - - - - - - - - - -
-
-
-

Module dynamicio.config

-
-
-

Implements the IOConfig class, generating objects used as a configuration parameter for the instantiation ofsrc.utils.dynamicio.dataio.DynamicDataIO objects.

-

The IOConfig object, essentially parses a yaml file that contains a set of input sources that will be processed by a -task, converting filtering and converting them into dictionaries.

-

For example, suppose an input.yaml file, containing:

-
READ_FROM_S3_CSV:
-  LOCAL:
-    type: "local"
-    local:
-      file_path: "[[ TEST_RESOURCES ]]/data/input/some_csv_to_read.csv"
-      file_type: "csv"
-  CLOUD:
-    type: "s3"
-    s3:
-      bucket: "[[ MOCK_BUCKET ]]"
-      file_path: "[[ MOCK_KEY ]]"
-      file_type: "csv"
-
-

would be loaded with:

-
input_sources_config = IOConfig(
-        "path_to/input.yaml",
-        env_identifier="CLOUD",
-        dynamic_vars=config_module
-    )
-
-

and:

-
input_sources_config.config
-
-

would return:

-
    {
-        "READ_FROM_S3_CSV": {
-            "LOCAL": {
-                "type": "local",
-                "local": {
-                    "file_path": f"{test_global_vars.TEST_RESOURCES}/data/input/some_csv_to_read.csv",
-                    "file_type": "csv",
-                },
-            },
-            "CLOUD": {
-                "type": "s3",
-                "s3": {
-                    "bucket": "mock-bucket",
-                    "file_path": "mock-key",
-                    "file_type": "csv"
-                }
-            },
-        }
-    }
-
-
- -Expand source code - -
"""Implements the `IOConfig` class, generating objects used as a configuration parameter for the instantiation of`src.utils.dynamicio.dataio.DynamicDataIO` objects.
-
-The `IOConfig` object, essentially parses a yaml file that contains a set of input sources that will be processed by a
-task, converting filtering and converting them into dictionaries.
-
-For example, suppose an `input.yaml` file, containing:
-
-    READ_FROM_S3_CSV:
-      LOCAL:
-        type: "local"
-        local:
-          file_path: "[[ TEST_RESOURCES ]]/data/input/some_csv_to_read.csv"
-          file_type: "csv"
-      CLOUD:
-        type: "s3"
-        s3:
-          bucket: "[[ MOCK_BUCKET ]]"
-          file_path: "[[ MOCK_KEY ]]"
-          file_type: "csv"
-
-would be loaded with:
-
-    input_sources_config = IOConfig(
-            "path_to/input.yaml",
-            env_identifier="CLOUD",
-            dynamic_vars=config_module
-        )
-
-and:
-
-    input_sources_config.config
-
-would return:
-
-        {
-            "READ_FROM_S3_CSV": {
-                "LOCAL": {
-                    "type": "local",
-                    "local": {
-                        "file_path": f"{test_global_vars.TEST_RESOURCES}/data/input/some_csv_to_read.csv",
-                        "file_type": "csv",
-                    },
-                },
-                "CLOUD": {
-                    "type": "s3",
-                    "s3": {
-                        "bucket": "mock-bucket",
-                        "file_path": "mock-key",
-                        "file_type": "csv"
-                    }
-                },
-            }
-        }
-"""
-__all__ = ["IOConfig", "SafeDynamicResourceLoader", "SafeDynamicSchemaLoader"]
-
-import re
-from types import ModuleType
-from typing import Any, List, Mapping
-
-import yaml
-from magic_logger import logger
-
-
-class SafeDynamicResourceLoader(yaml.SafeLoader):
-    """Implements a dynamic yaml loader that parses yaml files and replaces strings that map to [[ DYNAMIC_VAR ]].
-
-    Dynamic variables defined in a provided module object.
-    """
-
-    module = None
-    dynamic_data_matcher = re.compile(r"(.*)(\[\[\s*(\S+)\s*]])(.*)")
-
-    @classmethod
-    def with_module(cls, module: ModuleType):
-        """Creates a dynamic subclass of SafeDynamicLoader with the `data_module` attribute set to `module`.
-
-        Args:
-            module: A global vars module with all the dynamic values defined in it.
-
-        Returns:
-            type
-        """
-        return type(f"{cls.__name__}_{module.__name__}", (cls,), {"module": module})
-
-    def dyn_str_constructor(self, node: yaml.nodes.ScalarNode) -> str:
-        """Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.
-
-        Args:
-            node: Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention
-                are replaced with the respective attributes in te provided module.
-
-        Returns:
-            Constructed `str` or numerical.
-        """
-        value = node.value
-
-        while result := self.dynamic_data_matcher.match(value):
-            ref = result.group(3)
-            replacement = getattr(self.module, ref)
-
-            value = self.dynamic_data_matcher.sub(f"\\g<1>{replacement}\\g<4>", value)
-
-        return value
-
-
-class SafeDynamicSchemaLoader(yaml.SafeLoader):
-    """Implements a dynamic yaml loader that parses yaml files and replaces strings that map to [[ DYNAMIC_VAR ]].
-
-    Dynamic variables defined in a provided module object.
-    """
-
-    module = None
-    dynamic_data_matcher = re.compile(r"(.*)(\[\[\s*(\S+)\s*]])(.*)")
-
-    @classmethod
-    def with_module(cls, module: ModuleType):
-        """Creates a dynamic subclass of SafeDynamicLoader with the `data_module` attribute set to `module`.
-
-        Args:
-            module: A global vars module with all the dynamic values defined in it.
-
-        Returns:
-            type
-        """
-        return type(f"{cls.__name__}_{module.__name__}", (cls,), {"module": module})
-
-    def dyn_value_constructor(self, node: yaml.nodes.ScalarNode) -> Any:
-        """Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.
-
-        Args:
-            node: Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention
-                are replaced with the respective attributes in te provided module.
-
-        Returns:
-            Constructed `str` or numerical.
-        """
-        value = node.value
-
-        while result := self.dynamic_data_matcher.match(value):
-            ref = result.group(3)
-            replacement = getattr(self.module, ref)
-
-            value = self.dynamic_data_matcher.sub(f"\\g<1>{replacement}\\g<4>", value)
-
-            try:
-                value = float(value)
-                return value
-            except ValueError:
-                pass
-
-        return value
-
-
-class IOConfig:
-    """Generates an object that returns a sub-dictionary of the elements of that yaml file.
-
-    The file serves as a config for setting up DynamicDataIO objects. Requires a resources yaml file,
-    an ENVIRONMENT value {CLOUD or LOCAL} and a vars module.
-
-    Example:
-        input_sources_config = IOConfig(
-            "path_to/input.yaml",
-            env_identifier="CLOUD",
-            dynamic_vars=config_module
-        )
-    """
-
-    YAML_TAG = "tag:yaml.org,2002:str"
-    SafeDynamicResourceLoader.add_constructor(YAML_TAG, SafeDynamicResourceLoader.dyn_str_constructor)
-    SafeDynamicSchemaLoader.add_constructor(YAML_TAG, SafeDynamicSchemaLoader.dyn_value_constructor)
-
-    def __init__(self, path_to_source_yaml: str, env_identifier: str, dynamic_vars: ModuleType):
-        """Class constructor.
-
-        Args:
-            path_to_source_yaml: Absolute file path to yaml file containing source definitions
-            env_identifier: "LOCAL" or "CLOUD".
-            dynamic_vars: module containing values for dynamic values that the source yaml
-                may reference.
-        """
-        self.path_to_source_yaml = path_to_source_yaml
-        self.env_identifier = env_identifier
-        self.dynamic_vars = dynamic_vars
-        self.config = self._parse_sources_config()
-
-    def _parse_sources_config(self) -> Mapping:
-        """Parses the yaml input and return a dictionary.
-
-        Returns:
-            A dictionary with the list of all file paths pointing to various input sources as those
-            are defined in their respective data/*.yaml files.
-        """
-        with open(self.path_to_source_yaml, "r") as stream:  # pylint: disable=unspecified-encoding]
-            logger.debug(f"Parsing {self.path_to_source_yaml}...")
-            return yaml.load(stream, SafeDynamicResourceLoader.with_module(self.dynamic_vars))
-
-    @property
-    def sources(self) -> List[str]:
-        """Class property for easy access to a list of sources.
-
-        Returns:
-            All top level names of the available resources for the used resources yaml config.
-        """
-        return list(self.config.keys())
-
-    def get(self, source_key: str) -> Mapping:
-        """A getter.
-
-        Args:
-            source_key: The name of the resource for which we want to create a config.
-
-        Returns:
-            A dictionary with the necessary fields for loading the data from a source.
-
-        Example:
-
-            Given:
-
-                VOYAGE_DATA:
-                  LOCAL:
-                    type: "local"
-                    local:
-                      file_path: "[[ TEST_RESOURCES ]]/data/processed/voyage_data.parquet"
-                      file_type: "parquet"
-                  CLOUD:
-                    type: "kafka"
-                    KAFKA:
-                      KAFKA_SERVER: "[[ KAFKA_SERVER ]]"
-                      KAFKA_TOPIC: "[[ KAFKA_TOPIC ]]"
-
-            If you do:
-
-                input_sources_config = IOConfig(
-                    "path_to/input.yaml",
-                    env_identifier="CLOUD",
-                    dynamic_vars=globals
-                )
-                voyage_data_cloud_mapping = input_config.get(source_key="VOYAGE_DATA")
-
-            then `voyage_data_cloud_mapping` is:
-
-                "KAFKA": {
-                    "KAFKA_SERVER": "mock-kafka-server",
-                    "KAFKA_TOPIC": "mock-kafka-topic"
-                }
-        """
-        source_config = self.config[source_key][self.env_identifier]
-        if self.config[source_key].get("schema"):
-            schema_definition = self._get_schema_definition(source_key)
-            source_config["name"] = schema_definition["name"]
-            source_config["schema"] = self._get_schema(schema_definition)
-            source_config["validations"] = self._get_validations(schema_definition)
-            source_config["metrics"] = self._get_metrics(schema_definition)
-        return source_config
-
-    def _get_schema_definition(self, source_key: str) -> Mapping:
-        """Retrieves the schema definition from a resource definition.
-
-        Returns:
-            The schema definition provided for a resource definition.
-        """
-        schema_file_path = self.config[source_key].get("schema")["file_path"]
-        with open(schema_file_path, "r") as stream:  # pylint: disable=unspecified-encoding]
-            logger.debug(f"Parsing schema: {schema_file_path}...")
-            return yaml.load(stream, SafeDynamicSchemaLoader.with_module(self.dynamic_vars))
-
-    @staticmethod
-    def _get_schema(schema_definition: Mapping) -> Mapping:
-        """Retrieve the schema from a schema definition.
-
-        Args:
-            schema_definition:
-
-        Returns:
-            The column types in the schema definition.
-        """
-        _schema = {}
-        for column in schema_definition["columns"].keys():
-            _schema[column] = schema_definition["columns"][column]["type"]
-        return _schema
-
-    @staticmethod
-    def _get_validations(schema_definition: Mapping) -> Mapping:
-        """Returns all validations for each column in a schema definition.
-
-        Args:
-            schema_definition: A dictionary with all columns in a dataset characterised by validations and metrics
-
-        Returns:
-            The validations applied to each column in the schema definition.
-        """
-        _validations = {}
-        for column in schema_definition["columns"].keys():
-            _validations[column] = schema_definition["columns"][column]["validations"]
-        return _validations
-
-    @staticmethod
-    def _get_metrics(schema_definition):
-        """Returns all metrics for each column in a schema definition.
-
-        Args:
-            schema_definition: A dictionary with all columns in a dataset characterised by validations and metrics
-
-        Returns:
-            The metrics applied to each column in the schema definition.
-        """
-        _metrics = {}
-        for column in schema_definition["columns"].keys():
-            _metrics[column] = schema_definition["columns"][column]["metrics"]
-        return _metrics
-
-
-
-
-
-
-
-
-
-

Classes

-
-
-class IOConfig -(path_to_source_yaml: str, env_identifier: str, dynamic_vars: module) -
-
-

Generates an object that returns a sub-dictionary of the elements of that yaml file.

-

The file serves as a config for setting up DynamicDataIO objects. Requires a resources yaml file, -an ENVIRONMENT value {CLOUD or LOCAL} and a vars module.

-

Example

-

input_sources_config = IOConfig( -"path_to/input.yaml", -env_identifier="CLOUD", -dynamic_vars=config_module -)

-

Class constructor.

-

Args

-
-
path_to_source_yaml
-
Absolute file path to yaml file containing source definitions
-
env_identifier
-
"LOCAL" or "CLOUD".
-
dynamic_vars
-
module containing values for dynamic values that the source yaml -may reference.
-
-
- -Expand source code - -
class IOConfig:
-    """Generates an object that returns a sub-dictionary of the elements of that yaml file.
-
-    The file serves as a config for setting up DynamicDataIO objects. Requires a resources yaml file,
-    an ENVIRONMENT value {CLOUD or LOCAL} and a vars module.
-
-    Example:
-        input_sources_config = IOConfig(
-            "path_to/input.yaml",
-            env_identifier="CLOUD",
-            dynamic_vars=config_module
-        )
-    """
-
-    YAML_TAG = "tag:yaml.org,2002:str"
-    SafeDynamicResourceLoader.add_constructor(YAML_TAG, SafeDynamicResourceLoader.dyn_str_constructor)
-    SafeDynamicSchemaLoader.add_constructor(YAML_TAG, SafeDynamicSchemaLoader.dyn_value_constructor)
-
-    def __init__(self, path_to_source_yaml: str, env_identifier: str, dynamic_vars: ModuleType):
-        """Class constructor.
-
-        Args:
-            path_to_source_yaml: Absolute file path to yaml file containing source definitions
-            env_identifier: "LOCAL" or "CLOUD".
-            dynamic_vars: module containing values for dynamic values that the source yaml
-                may reference.
-        """
-        self.path_to_source_yaml = path_to_source_yaml
-        self.env_identifier = env_identifier
-        self.dynamic_vars = dynamic_vars
-        self.config = self._parse_sources_config()
-
-    def _parse_sources_config(self) -> Mapping:
-        """Parses the yaml input and return a dictionary.
-
-        Returns:
-            A dictionary with the list of all file paths pointing to various input sources as those
-            are defined in their respective data/*.yaml files.
-        """
-        with open(self.path_to_source_yaml, "r") as stream:  # pylint: disable=unspecified-encoding]
-            logger.debug(f"Parsing {self.path_to_source_yaml}...")
-            return yaml.load(stream, SafeDynamicResourceLoader.with_module(self.dynamic_vars))
-
-    @property
-    def sources(self) -> List[str]:
-        """Class property for easy access to a list of sources.
-
-        Returns:
-            All top level names of the available resources for the used resources yaml config.
-        """
-        return list(self.config.keys())
-
-    def get(self, source_key: str) -> Mapping:
-        """A getter.
-
-        Args:
-            source_key: The name of the resource for which we want to create a config.
-
-        Returns:
-            A dictionary with the necessary fields for loading the data from a source.
-
-        Example:
-
-            Given:
-
-                VOYAGE_DATA:
-                  LOCAL:
-                    type: "local"
-                    local:
-                      file_path: "[[ TEST_RESOURCES ]]/data/processed/voyage_data.parquet"
-                      file_type: "parquet"
-                  CLOUD:
-                    type: "kafka"
-                    KAFKA:
-                      KAFKA_SERVER: "[[ KAFKA_SERVER ]]"
-                      KAFKA_TOPIC: "[[ KAFKA_TOPIC ]]"
-
-            If you do:
-
-                input_sources_config = IOConfig(
-                    "path_to/input.yaml",
-                    env_identifier="CLOUD",
-                    dynamic_vars=globals
-                )
-                voyage_data_cloud_mapping = input_config.get(source_key="VOYAGE_DATA")
-
-            then `voyage_data_cloud_mapping` is:
-
-                "KAFKA": {
-                    "KAFKA_SERVER": "mock-kafka-server",
-                    "KAFKA_TOPIC": "mock-kafka-topic"
-                }
-        """
-        source_config = self.config[source_key][self.env_identifier]
-        if self.config[source_key].get("schema"):
-            schema_definition = self._get_schema_definition(source_key)
-            source_config["name"] = schema_definition["name"]
-            source_config["schema"] = self._get_schema(schema_definition)
-            source_config["validations"] = self._get_validations(schema_definition)
-            source_config["metrics"] = self._get_metrics(schema_definition)
-        return source_config
-
-    def _get_schema_definition(self, source_key: str) -> Mapping:
-        """Retrieves the schema definition from a resource definition.
-
-        Returns:
-            The schema definition provided for a resource definition.
-        """
-        schema_file_path = self.config[source_key].get("schema")["file_path"]
-        with open(schema_file_path, "r") as stream:  # pylint: disable=unspecified-encoding]
-            logger.debug(f"Parsing schema: {schema_file_path}...")
-            return yaml.load(stream, SafeDynamicSchemaLoader.with_module(self.dynamic_vars))
-
-    @staticmethod
-    def _get_schema(schema_definition: Mapping) -> Mapping:
-        """Retrieve the schema from a schema definition.
-
-        Args:
-            schema_definition:
-
-        Returns:
-            The column types in the schema definition.
-        """
-        _schema = {}
-        for column in schema_definition["columns"].keys():
-            _schema[column] = schema_definition["columns"][column]["type"]
-        return _schema
-
-    @staticmethod
-    def _get_validations(schema_definition: Mapping) -> Mapping:
-        """Returns all validations for each column in a schema definition.
-
-        Args:
-            schema_definition: A dictionary with all columns in a dataset characterised by validations and metrics
-
-        Returns:
-            The validations applied to each column in the schema definition.
-        """
-        _validations = {}
-        for column in schema_definition["columns"].keys():
-            _validations[column] = schema_definition["columns"][column]["validations"]
-        return _validations
-
-    @staticmethod
-    def _get_metrics(schema_definition):
-        """Returns all metrics for each column in a schema definition.
-
-        Args:
-            schema_definition: A dictionary with all columns in a dataset characterised by validations and metrics
-
-        Returns:
-            The metrics applied to each column in the schema definition.
-        """
-        _metrics = {}
-        for column in schema_definition["columns"].keys():
-            _metrics[column] = schema_definition["columns"][column]["metrics"]
-        return _metrics
-
-

Class variables

-
-
var YAML_TAG
-
-
-
-
-

Instance variables

-
-
var sources : List[str]
-
-

Class property for easy access to a list of sources.

-

Returns

-

All top level names of the available resources for the used resources yaml config.

-
- -Expand source code - -
@property
-def sources(self) -> List[str]:
-    """Class property for easy access to a list of sources.
-
-    Returns:
-        All top level names of the available resources for the used resources yaml config.
-    """
-    return list(self.config.keys())
-
-
-
-

Methods

-
-
-def get(self, source_key: str) ‑> Mapping[~KT, +VT_co] -
-
-

A getter.

-

Args

-
-
source_key
-
The name of the resource for which we want to create a config.
-
-

Returns

-

A dictionary with the necessary fields for loading the data from a source.

-

Example

-

Given:

-
VOYAGE_DATA:
-  LOCAL:
-    type: "local"
-    local:
-      file_path: "[[ TEST_RESOURCES ]]/data/processed/voyage_data.parquet"
-      file_type: "parquet"
-  CLOUD:
-    type: "kafka"
-    KAFKA:
-      KAFKA_SERVER: "[[ KAFKA_SERVER ]]"
-      KAFKA_TOPIC: "[[ KAFKA_TOPIC ]]"
-
-

If you do:

-
input_sources_config = IOConfig(
-    "path_to/input.yaml",
-    env_identifier="CLOUD",
-    dynamic_vars=globals
-)
-voyage_data_cloud_mapping = input_config.get(source_key="VOYAGE_DATA")
-
-

then voyage_data_cloud_mapping is:

-
"KAFKA": {
-    "KAFKA_SERVER": "mock-kafka-server",
-    "KAFKA_TOPIC": "mock-kafka-topic"
-}
-
-
- -Expand source code - -
def get(self, source_key: str) -> Mapping:
-    """A getter.
-
-    Args:
-        source_key: The name of the resource for which we want to create a config.
-
-    Returns:
-        A dictionary with the necessary fields for loading the data from a source.
-
-    Example:
-
-        Given:
-
-            VOYAGE_DATA:
-              LOCAL:
-                type: "local"
-                local:
-                  file_path: "[[ TEST_RESOURCES ]]/data/processed/voyage_data.parquet"
-                  file_type: "parquet"
-              CLOUD:
-                type: "kafka"
-                KAFKA:
-                  KAFKA_SERVER: "[[ KAFKA_SERVER ]]"
-                  KAFKA_TOPIC: "[[ KAFKA_TOPIC ]]"
-
-        If you do:
-
-            input_sources_config = IOConfig(
-                "path_to/input.yaml",
-                env_identifier="CLOUD",
-                dynamic_vars=globals
-            )
-            voyage_data_cloud_mapping = input_config.get(source_key="VOYAGE_DATA")
-
-        then `voyage_data_cloud_mapping` is:
-
-            "KAFKA": {
-                "KAFKA_SERVER": "mock-kafka-server",
-                "KAFKA_TOPIC": "mock-kafka-topic"
-            }
-    """
-    source_config = self.config[source_key][self.env_identifier]
-    if self.config[source_key].get("schema"):
-        schema_definition = self._get_schema_definition(source_key)
-        source_config["name"] = schema_definition["name"]
-        source_config["schema"] = self._get_schema(schema_definition)
-        source_config["validations"] = self._get_validations(schema_definition)
-        source_config["metrics"] = self._get_metrics(schema_definition)
-    return source_config
-
-
-
-
-
-class SafeDynamicResourceLoader -(stream) -
-
-

Implements a dynamic yaml loader that parses yaml files and replaces strings that map to [[ DYNAMIC_VAR ]].

-

Dynamic variables defined in a provided module object.

-

Initialize the scanner.

-
- -Expand source code - -
class SafeDynamicResourceLoader(yaml.SafeLoader):
-    """Implements a dynamic yaml loader that parses yaml files and replaces strings that map to [[ DYNAMIC_VAR ]].
-
-    Dynamic variables defined in a provided module object.
-    """
-
-    module = None
-    dynamic_data_matcher = re.compile(r"(.*)(\[\[\s*(\S+)\s*]])(.*)")
-
-    @classmethod
-    def with_module(cls, module: ModuleType):
-        """Creates a dynamic subclass of SafeDynamicLoader with the `data_module` attribute set to `module`.
-
-        Args:
-            module: A global vars module with all the dynamic values defined in it.
-
-        Returns:
-            type
-        """
-        return type(f"{cls.__name__}_{module.__name__}", (cls,), {"module": module})
-
-    def dyn_str_constructor(self, node: yaml.nodes.ScalarNode) -> str:
-        """Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.
-
-        Args:
-            node: Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention
-                are replaced with the respective attributes in te provided module.
-
-        Returns:
-            Constructed `str` or numerical.
-        """
-        value = node.value
-
-        while result := self.dynamic_data_matcher.match(value):
-            ref = result.group(3)
-            replacement = getattr(self.module, ref)
-
-            value = self.dynamic_data_matcher.sub(f"\\g<1>{replacement}\\g<4>", value)
-
-        return value
-
-

Ancestors

-
    -
  • yaml.loader.SafeLoader
    • -
  • yaml.reader.Reader
    • -
  • yaml.scanner.Scanner
    • -
  • yaml.parser.Parser
    • -
  • yaml.composer.Composer
    • -
  • yaml.constructor.SafeConstructor
    • -
  • yaml.constructor.BaseConstructor
    • -
  • yaml.resolver.Resolver
    • -
  • yaml.resolver.BaseResolver
    • -
-

Class variables

-
-
var dynamic_data_matcher
-
-
-
-
var module
-
-
-
-
var yaml_constructors
-
-
-
-
-

Static methods

-
-
-def with_module(module: module) -
-
-

Creates a dynamic subclass of SafeDynamicLoader with the data_module attribute set to module.

-

Args

-
-
module
-
A global vars module with all the dynamic values defined in it.
-
-

Returns

-

type

-
- -Expand source code - -
@classmethod
-def with_module(cls, module: ModuleType):
-    """Creates a dynamic subclass of SafeDynamicLoader with the `data_module` attribute set to `module`.
-
-    Args:
-        module: A global vars module with all the dynamic values defined in it.
-
-    Returns:
-        type
-    """
-    return type(f"{cls.__name__}_{module.__name__}", (cls,), {"module": module})
-
-
-
-

Methods

-
-
-def dyn_str_constructor(self, node: yaml.nodes.ScalarNode) ‑> str -
-
-

Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.

-

Args

-
-
node
-
Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention -are replaced with the respective attributes in te provided module.
-
-

Returns

-

Constructed str or numerical.

-
- -Expand source code - -
def dyn_str_constructor(self, node: yaml.nodes.ScalarNode) -> str:
-    """Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.
-
-    Args:
-        node: Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention
-            are replaced with the respective attributes in te provided module.
-
-    Returns:
-        Constructed `str` or numerical.
-    """
-    value = node.value
-
-    while result := self.dynamic_data_matcher.match(value):
-        ref = result.group(3)
-        replacement = getattr(self.module, ref)
-
-        value = self.dynamic_data_matcher.sub(f"\\g<1>{replacement}\\g<4>", value)
-
-    return value
-
-
-
-
-
-class SafeDynamicSchemaLoader -(stream) -
-
-

Implements a dynamic yaml loader that parses yaml files and replaces strings that map to [[ DYNAMIC_VAR ]].

-

Dynamic variables defined in a provided module object.

-

Initialize the scanner.

-
- -Expand source code - -
class SafeDynamicSchemaLoader(yaml.SafeLoader):
-    """Implements a dynamic yaml loader that parses yaml files and replaces strings that map to [[ DYNAMIC_VAR ]].
-
-    Dynamic variables defined in a provided module object.
-    """
-
-    module = None
-    dynamic_data_matcher = re.compile(r"(.*)(\[\[\s*(\S+)\s*]])(.*)")
-
-    @classmethod
-    def with_module(cls, module: ModuleType):
-        """Creates a dynamic subclass of SafeDynamicLoader with the `data_module` attribute set to `module`.
-
-        Args:
-            module: A global vars module with all the dynamic values defined in it.
-
-        Returns:
-            type
-        """
-        return type(f"{cls.__name__}_{module.__name__}", (cls,), {"module": module})
-
-    def dyn_value_constructor(self, node: yaml.nodes.ScalarNode) -> Any:
-        """Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.
-
-        Args:
-            node: Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention
-                are replaced with the respective attributes in te provided module.
-
-        Returns:
-            Constructed `str` or numerical.
-        """
-        value = node.value
-
-        while result := self.dynamic_data_matcher.match(value):
-            ref = result.group(3)
-            replacement = getattr(self.module, ref)
-
-            value = self.dynamic_data_matcher.sub(f"\\g<1>{replacement}\\g<4>", value)
-
-            try:
-                value = float(value)
-                return value
-            except ValueError:
-                pass
-
-        return value
-
-

Ancestors

-
    -
  • yaml.loader.SafeLoader
    • -
  • yaml.reader.Reader
    • -
  • yaml.scanner.Scanner
    • -
  • yaml.parser.Parser
    • -
  • yaml.composer.Composer
    • -
  • yaml.constructor.SafeConstructor
    • -
  • yaml.constructor.BaseConstructor
    • -
  • yaml.resolver.Resolver
    • -
  • yaml.resolver.BaseResolver
    • -
-

Class variables

-
-
var dynamic_data_matcher
-
-
-
-
var module
-
-
-
-
var yaml_constructors
-
-
-
-
-

Static methods

-
-
-def with_module(module: module) -
-
-

Creates a dynamic subclass of SafeDynamicLoader with the data_module attribute set to module.

-

Args

-
-
module
-
A global vars module with all the dynamic values defined in it.
-
-

Returns

-

type

-
- -Expand source code - -
@classmethod
-def with_module(cls, module: ModuleType):
-    """Creates a dynamic subclass of SafeDynamicLoader with the `data_module` attribute set to `module`.
-
-    Args:
-        module: A global vars module with all the dynamic values defined in it.
-
-    Returns:
-        type
-    """
-    return type(f"{cls.__name__}_{module.__name__}", (cls,), {"module": module})
-
-
-
-

Methods

-
-
-def dyn_value_constructor(self, node: yaml.nodes.ScalarNode) ‑> Any -
-
-

Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.

-

Args

-
-
node
-
Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention -are replaced with the respective attributes in te provided module.
-
-

Returns

-

Constructed str or numerical.

-
- -Expand source code - -
def dyn_value_constructor(self, node: yaml.nodes.ScalarNode) -> Any:
-    """Responsible for the switching of one or more "[[ DYNAMIC_VAR ]]" strings with the respective attributes value in a given module.
-
-    Args:
-        node: Parsed item whose dynamic values that map to the "[[ DYNAMIC_VAR ]]" convention
-            are replaced with the respective attributes in te provided module.
-
-    Returns:
-        Constructed `str` or numerical.
-    """
-    value = node.value
-
-    while result := self.dynamic_data_matcher.match(value):
-        ref = result.group(3)
-        replacement = getattr(self.module, ref)
-
-        value = self.dynamic_data_matcher.sub(f"\\g<1>{replacement}\\g<4>", value)
-
-        try:
-            value = float(value)
-            return value
-        except ValueError:
-            pass
-
-    return value
-
-
-
-
-
-
-
- -
- - - \ No newline at end of file diff --git a/docs/core.html b/docs/core.html deleted file mode 100644 index 2de5292..0000000 --- a/docs/core.html +++ /dev/null @@ -1,855 +0,0 @@ - - - - - - -dynamicio.core API documentation - - - - - - - - - - - -
-
-
-

Module dynamicio.core

-
-
-

Implements the DynamicDataIO class which provides functionality for data: loading; sinking, and; schema validation.

-
- -Expand source code - -
"""Implements the DynamicDataIO class which provides functionality for data: loading; sinking, and; schema validation."""
-# pylint: disable=no-member
-__all__ = ["DynamicDataIO", "SCHEMA_FROM_FILE"]
-
-import asyncio
-import inspect
-import re
-from concurrent.futures import ThreadPoolExecutor
-from typing import Any, Mapping, MutableMapping, Optional
-
-import pandas as pd  # type: ignore
-from magic_logger import logger
-
-from dynamicio import validations
-from dynamicio.errors import CASTING_WARNING_MSG, ColumnsDataTypeError, MissingSchemaDefinition, NOTICE_MSG, SchemaNotFoundError, SchemaValidationError
-from dynamicio.metrics import get_metric
-
-SCHEMA_FROM_FILE = {"schema": object()}
-
-pool = ThreadPoolExecutor()
-
-
-class DynamicDataIO:
-    """Given a `src.utils.dynamicio.config.IOConfig` object, it generates an object with access to a series of methods for cloud I/O operations and data validations.
-
-    Example:
-       >>> input_sources_config = IOConfig(
-       >>>     "path_to/input.yaml",
-       >>>     os.getenv("ENVIRONMENT",default="LOCAL")
-       >>> )
-       >>>
-       >>> class IO(WithS3File, WithLocal, DynamicDataIO):
-       >>>     schema = S
-       >>>
-       >>> my_dataset_local_mapping = input_config.get(source_key="MY_DATASET")
-       >>> my_dataset_io = IO(my_dataset_local_mapping)
-       >>> my_dataset_df = my_dataset_io.read()
-    """
-
-    schema: Mapping
-
-    def __init__(
-        self,
-        source_config: Mapping,
-        apply_schema_validations: bool = False,
-        log_schema_metrics: bool = False,
-        show_casting_warnings: bool = False,
-        **options: MutableMapping[str, Any],
-    ):
-        """Class constructor.
-
-        Args:
-            source_config: Configuration to use when reading/writing data from/to a source
-            apply_schema_validations: Applies schema validations on either read() or write()
-            log_schema_metrics: Logs schema metrics on either read() or write()
-            show_casting_warnings: Logs casting warnings on either read() or write() if set to True
-            options: Any additional kwargs that may be used throughout the lifecycle of the object
-        """
-        if type(self) is DynamicDataIO:  # pylint: disable=unidiomatic-typecheck
-            raise TypeError("Abstract class DynamicDataIO cannot be used to instantiate an object...")
-
-        self.sources_config = source_config
-        self.name = self._transform_class_name_to_dataset_name(self.__class__.__name__)
-        self.apply_schema_validations = apply_schema_validations
-        self.log_schema_metrics = log_schema_metrics
-        self.show_casting_warnings = show_casting_warnings
-        self.options = self._get_options(options, source_config.get("options"))
-        source_name = self.sources_config.get("type")
-        if self.schema is SCHEMA_FROM_FILE:
-            try:
-                self.schema = self.sources_config["schema"]
-                self.name = self.sources_config["name"].upper()
-                self.schema_validations = self.sources_config["validations"]
-                self.schema_metrics = self.sources_config["metrics"]
-            except KeyError as _error:
-                raise SchemaNotFoundError() from _error
-
-        assert hasattr(self, f"_read_from_{source_name}") or hasattr(
-            self, f"_write_to_{source_name}"
-        ), f"No method '_read_from_{source_name}' or '_write_to_{source_name}'. Have you registered a mixin for {source_name}?"
-
-    def __init_subclass__(cls):
-        """Ensure that all subclasses have a `schema` attribute and a `validate` method.
-
-        Raises:
-            AssertionError: If either of the attributes is not implemented
-        """
-        if not inspect.getmodule(cls).__name__.startswith("dynamicio"):
-            assert "schema" in cls.__dict__
-
-            if cls.schema is None or (cls.schema is not SCHEMA_FROM_FILE and len(cls.schema) == 0):
-                raise ValueError(f"schema for class {cls} cannot be None or empty...")
-
-    async def async_read(self):
-        """Allows the use of asyncio to concurrently read files in memory.
-
-        Returns:
-            A pandas dataframe or an iterable.
-        """
-        loop = asyncio.get_running_loop()
-        return await loop.run_in_executor(pool, self.read)
-
-    def read(self) -> pd.DataFrame:
-        """Reads data source and returns a schema validated dataframe (by means of _apply_schema).
-
-        Returns:
-            A pandas dataframe or an iterable.
-        """
-        source_name = self.sources_config.get("type")
-        df = getattr(self, f"_read_from_{source_name}")()
-
-        df = self._apply_schema(df)
-        if self.apply_schema_validations:
-            self.validate_from_schema(df)
-        if self.log_schema_metrics:
-            self.log_metrics_from_schema(df)
-
-        return df
-
-    async def async_write(self, df: pd.DataFrame):
-        """Allows the use of asyncio to concurrently write files out.
-
-        Args:
-            df: The data to be written
-        """
-        loop = asyncio.get_running_loop()
-        return await loop.run_in_executor(pool, self.write, df)
-
-    def write(self, df: pd.DataFrame):
-        """Sink data to a given source based on the sources_config.
-
-        Args:
-            df: The data to be written
-        """
-        source_name = self.sources_config.get("type")
-        if set(df.columns) != set(self.schema.keys()):  # pylint: disable=E1101
-            columns = [column for column in df.columns.to_list() if column in self.schema.keys()]
-            df = df[columns]
-
-        if self.apply_schema_validations:
-            self.validate_from_schema(df)
-        if self.log_schema_metrics:
-            self.log_metrics_from_schema(df)
-
-        getattr(self, f"_write_to_{source_name}")(self._apply_schema(df))
-
-    def validate_from_schema(self, df: pd.DataFrame) -> "DynamicDataIO":
-        """Validates a dataframe based on the validations present in its schema definition.
-
-        All validations are checked and if any of them fails, a `SchemaValidationError` is raised.
-
-        Args:
-            df:
-
-        Returns:
-             self (to allow for method chaining).
-
-        Raises:
-            SchemaValidationError: if any of the validations failed. The `message` attribute of
-                the exception object is a `List[str]`, where each element is the name of a
-                validation that failed.
-        """
-        if not hasattr(self, "schema_validations"):
-            raise MissingSchemaDefinition(self.__class__)
-
-        failed_validations = {}
-        for column in self.schema_validations.keys():
-            for validation in self.schema_validations[column].keys():
-                if self.schema_validations[column][validation]["apply"] is True:
-                    validation_result = getattr(validations, validation)(self.name, df, column, **self.schema_validations[column][validation]["options"])
-                    if not validation_result.valid:
-                        failed_validations[validation] = validation_result.message
-
-        if len(failed_validations) > 0:
-            raise SchemaValidationError(failed_validations)
-
-        return self
-
-    def log_metrics_from_schema(self, df: pd.DataFrame) -> "DynamicDataIO":
-        """Calculates and logs metrics based on the metrics present in its schema definition.
-
-        Args:
-            df: A dataframe for which metrics are generated and logged
-
-        Returns:
-             self (to allow for method chaining).
-        """
-        if not hasattr(self, "schema_metrics"):
-            raise MissingSchemaDefinition(self.__class__)
-
-        for column in self.schema_metrics.keys():
-            for metric in self.schema_metrics[column]:
-                get_metric(metric)(self.name, df, column)()  # type: ignore
-
-        return self
-
-    def _apply_schema(self, df: pd.DataFrame) -> pd.DataFrame:
-        """Called by the `self.read()` and the `self._write_to_local()` methods.
-
-        Contrasts a dataframe's read from a given source against the class's schema dictionary,
-        checking that columns are the same (by means of _has_columns and _has_valid_dtypes). Then,
-        check if the columns are fine, it further validates if the types of columns conform to the
-        expected schema. Finally, if schema types are different, then it attempts to apply schema;
-        if possible then the schema validation is successful.
-
-        Args:
-            df: A pandas dataframe.
-
-        Returns:
-            A schema validated dataframe.
-        """
-        if not self._has_valid_dtypes(df):
-            raise ColumnsDataTypeError()
-        return df
-
-    @staticmethod
-    def _transform_class_name_to_dataset_name(string_to_transform: str) -> str:
-        """Called by the init function to fetch dataset names from class name.
-
-        Used to create dataset name from class name, turns camel case into upper snake case.
-        For example: 'ThisNameABC' -> 'THIS_NAME_ABC'.
-        """
-        words = re.findall(r"\d[A-Z]+|[A-Z]?[a-z\d]+|[A-Z]{2,}(?=[A-Z][a-z]|\d|\W|$)|\d+|[A-Z]{2,}|[A-Z]", string_to_transform)
-        return "_".join(map(str.lower, words)).upper()
-
-    def _has_valid_dtypes(self, df: pd.DataFrame) -> bool:
-        """Checks if `df` has the expected dtypes defined in `schema`.
-
-        Schema is a dictionary object where keys are column names and values are dtypes in string format as returned by e.g.
-        `df[column].dtype.name`.
-
-        This function issues `error` level logs describing the first column that caused the check to fail.
-
-        It is assumed that `df` only has the columns defined in `schema`.
-
-        Args:
-            df:
-
-        Returns:
-            bool - `True` if `df` has the given dtypes, `False` otherwise
-        """
-        dtypes = df.dtypes
-
-        for column_name, expected_dtype in self.schema.items():
-            found_dtype = dtypes[column_name].name
-            if found_dtype != expected_dtype:
-                if self.show_casting_warnings:
-                    logger.info(f"Expected: '{expected_dtype}' dtype for {self.name}['{column_name}]', found '{found_dtype}'")
-                try:
-                    if len(set(type(v) for v in df[column_name].values)) > 1:  # pylint: disable=consider-using-set-comprehension
-                        logger.warning(CASTING_WARNING_MSG.format(column_name, expected_dtype, found_dtype))  # pylint: disable=logging-format-interpolation
-                        logger.info(NOTICE_MSG.format(column_name))  # pylint: disable=logging-format-interpolation
-                    df[column_name] = df[column_name].astype(self.schema[column_name])
-                except (ValueError, TypeError):
-                    logger.error(f"ValueError: Tried casting column {self.name}['{column_name}]' to '{expected_dtype}' " f"from '{found_dtype}', but failed")
-                    return False
-        return True
-
-    @staticmethod
-    def _get_options(options_from_code: MutableMapping[str, Any], options_from_resource_definition: Optional[Mapping[str, Any]]) -> MutableMapping[str, Any]:
-        """Retrieves options either from code or from a resource-definition.
-
-        Options are merged if they are provided by both sources, while in the case of conflicts, the options from the code
-        take precedence.
-
-        Args:
-            options_from_code (Optional[Mapping])
-            options_from_resource_definition (Optional[Mapping])
-
-        Returns:
-            [Optional[Mapping]]: options that are going to be used
-        """
-        if options_from_resource_definition:
-            return {**options_from_resource_definition, **options_from_code}
-        return options_from_code
-
-
-
-
-
-
-
-
-
-

Classes

-
-
-class DynamicDataIO -(source_config: Mapping[~KT, +VT_co], apply_schema_validations: bool = False, log_schema_metrics: bool = False, show_casting_warnings: bool = False, **options: MutableMapping[str, Any]) -
-
-

Given a src.utils.dynamicio.config.IOConfig object, it generates an object with access to a series of methods for cloud I/O operations and data validations.

-

Example

-
>>> input_sources_config = IOConfig(
->>>     "path_to/input.yaml",
->>>     os.getenv("ENVIRONMENT",default="LOCAL")
->>> )
->>>
->>> class IO(WithS3File, WithLocal, DynamicDataIO):
->>>     schema = S
->>>
->>> my_dataset_local_mapping = input_config.get(source_key="MY_DATASET")
->>> my_dataset_io = IO(my_dataset_local_mapping)
->>> my_dataset_df = my_dataset_io.read()
-
-

Class constructor.

-

Args

-
-
source_config
-
Configuration to use when reading/writing data from/to a source
-
apply_schema_validations
-
Applies schema validations on either read() or write()
-
log_schema_metrics
-
Logs schema metrics on either read() or write()
-
show_casting_warnings
-
Logs casting warnings on either read() or write() if set to True
-
options
-
Any additional kwargs that may be used throughout the lifecycle of the object
-
-
- -Expand source code - -
class DynamicDataIO:
-    """Given a `src.utils.dynamicio.config.IOConfig` object, it generates an object with access to a series of methods for cloud I/O operations and data validations.
-
-    Example:
-       >>> input_sources_config = IOConfig(
-       >>>     "path_to/input.yaml",
-       >>>     os.getenv("ENVIRONMENT",default="LOCAL")
-       >>> )
-       >>>
-       >>> class IO(WithS3File, WithLocal, DynamicDataIO):
-       >>>     schema = S
-       >>>
-       >>> my_dataset_local_mapping = input_config.get(source_key="MY_DATASET")
-       >>> my_dataset_io = IO(my_dataset_local_mapping)
-       >>> my_dataset_df = my_dataset_io.read()
-    """
-
-    schema: Mapping
-
-    def __init__(
-        self,
-        source_config: Mapping,
-        apply_schema_validations: bool = False,
-        log_schema_metrics: bool = False,
-        show_casting_warnings: bool = False,
-        **options: MutableMapping[str, Any],
-    ):
-        """Class constructor.
-
-        Args:
-            source_config: Configuration to use when reading/writing data from/to a source
-            apply_schema_validations: Applies schema validations on either read() or write()
-            log_schema_metrics: Logs schema metrics on either read() or write()
-            show_casting_warnings: Logs casting warnings on either read() or write() if set to True
-            options: Any additional kwargs that may be used throughout the lifecycle of the object
-        """
-        if type(self) is DynamicDataIO:  # pylint: disable=unidiomatic-typecheck
-            raise TypeError("Abstract class DynamicDataIO cannot be used to instantiate an object...")
-
-        self.sources_config = source_config
-        self.name = self._transform_class_name_to_dataset_name(self.__class__.__name__)
-        self.apply_schema_validations = apply_schema_validations
-        self.log_schema_metrics = log_schema_metrics
-        self.show_casting_warnings = show_casting_warnings
-        self.options = self._get_options(options, source_config.get("options"))
-        source_name = self.sources_config.get("type")
-        if self.schema is SCHEMA_FROM_FILE:
-            try:
-                self.schema = self.sources_config["schema"]
-                self.name = self.sources_config["name"].upper()
-                self.schema_validations = self.sources_config["validations"]
-                self.schema_metrics = self.sources_config["metrics"]
-            except KeyError as _error:
-                raise SchemaNotFoundError() from _error
-
-        assert hasattr(self, f"_read_from_{source_name}") or hasattr(
-            self, f"_write_to_{source_name}"
-        ), f"No method '_read_from_{source_name}' or '_write_to_{source_name}'. Have you registered a mixin for {source_name}?"
-
-    def __init_subclass__(cls):
-        """Ensure that all subclasses have a `schema` attribute and a `validate` method.
-
-        Raises:
-            AssertionError: If either of the attributes is not implemented
-        """
-        if not inspect.getmodule(cls).__name__.startswith("dynamicio"):
-            assert "schema" in cls.__dict__
-
-            if cls.schema is None or (cls.schema is not SCHEMA_FROM_FILE and len(cls.schema) == 0):
-                raise ValueError(f"schema for class {cls} cannot be None or empty...")
-
-    async def async_read(self):
-        """Allows the use of asyncio to concurrently read files in memory.
-
-        Returns:
-            A pandas dataframe or an iterable.
-        """
-        loop = asyncio.get_running_loop()
-        return await loop.run_in_executor(pool, self.read)
-
-    def read(self) -> pd.DataFrame:
-        """Reads data source and returns a schema validated dataframe (by means of _apply_schema).
-
-        Returns:
-            A pandas dataframe or an iterable.
-        """
-        source_name = self.sources_config.get("type")
-        df = getattr(self, f"_read_from_{source_name}")()
-
-        df = self._apply_schema(df)
-        if self.apply_schema_validations:
-            self.validate_from_schema(df)
-        if self.log_schema_metrics:
-            self.log_metrics_from_schema(df)
-
-        return df
-
-    async def async_write(self, df: pd.DataFrame):
-        """Allows the use of asyncio to concurrently write files out.
-
-        Args:
-            df: The data to be written
-        """
-        loop = asyncio.get_running_loop()
-        return await loop.run_in_executor(pool, self.write, df)
-
-    def write(self, df: pd.DataFrame):
-        """Sink data to a given source based on the sources_config.
-
-        Args:
-            df: The data to be written
-        """
-        source_name = self.sources_config.get("type")
-        if set(df.columns) != set(self.schema.keys()):  # pylint: disable=E1101
-            columns = [column for column in df.columns.to_list() if column in self.schema.keys()]
-            df = df[columns]
-
-        if self.apply_schema_validations:
-            self.validate_from_schema(df)
-        if self.log_schema_metrics:
-            self.log_metrics_from_schema(df)
-
-        getattr(self, f"_write_to_{source_name}")(self._apply_schema(df))
-
-    def validate_from_schema(self, df: pd.DataFrame) -> "DynamicDataIO":
-        """Validates a dataframe based on the validations present in its schema definition.
-
-        All validations are checked and if any of them fails, a `SchemaValidationError` is raised.
-
-        Args:
-            df:
-
-        Returns:
-             self (to allow for method chaining).
-
-        Raises:
-            SchemaValidationError: if any of the validations failed. The `message` attribute of
-                the exception object is a `List[str]`, where each element is the name of a
-                validation that failed.
-        """
-        if not hasattr(self, "schema_validations"):
-            raise MissingSchemaDefinition(self.__class__)
-
-        failed_validations = {}
-        for column in self.schema_validations.keys():
-            for validation in self.schema_validations[column].keys():
-                if self.schema_validations[column][validation]["apply"] is True:
-                    validation_result = getattr(validations, validation)(self.name, df, column, **self.schema_validations[column][validation]["options"])
-                    if not validation_result.valid:
-                        failed_validations[validation] = validation_result.message
-
-        if len(failed_validations) > 0:
-            raise SchemaValidationError(failed_validations)
-
-        return self
-
-    def log_metrics_from_schema(self, df: pd.DataFrame) -> "DynamicDataIO":
-        """Calculates and logs metrics based on the metrics present in its schema definition.
-
-        Args:
-            df: A dataframe for which metrics are generated and logged
-
-        Returns:
-             self (to allow for method chaining).
-        """
-        if not hasattr(self, "schema_metrics"):
-            raise MissingSchemaDefinition(self.__class__)
-
-        for column in self.schema_metrics.keys():
-            for metric in self.schema_metrics[column]:
-                get_metric(metric)(self.name, df, column)()  # type: ignore
-
-        return self
-
-    def _apply_schema(self, df: pd.DataFrame) -> pd.DataFrame:
-        """Called by the `self.read()` and the `self._write_to_local()` methods.
-
-        Contrasts a dataframe's read from a given source against the class's schema dictionary,
-        checking that columns are the same (by means of _has_columns and _has_valid_dtypes). Then,
-        check if the columns are fine, it further validates if the types of columns conform to the
-        expected schema. Finally, if schema types are different, then it attempts to apply schema;
-        if possible then the schema validation is successful.
-
-        Args:
-            df: A pandas dataframe.
-
-        Returns:
-            A schema validated dataframe.
-        """
-        if not self._has_valid_dtypes(df):
-            raise ColumnsDataTypeError()
-        return df
-
-    @staticmethod
-    def _transform_class_name_to_dataset_name(string_to_transform: str) -> str:
-        """Called by the init function to fetch dataset names from class name.
-
-        Used to create dataset name from class name, turns camel case into upper snake case.
-        For example: 'ThisNameABC' -> 'THIS_NAME_ABC'.
-        """
-        words = re.findall(r"\d[A-Z]+|[A-Z]?[a-z\d]+|[A-Z]{2,}(?=[A-Z][a-z]|\d|\W|$)|\d+|[A-Z]{2,}|[A-Z]", string_to_transform)
-        return "_".join(map(str.lower, words)).upper()
-
-    def _has_valid_dtypes(self, df: pd.DataFrame) -> bool:
-        """Checks if `df` has the expected dtypes defined in `schema`.
-
-        Schema is a dictionary object where keys are column names and values are dtypes in string format as returned by e.g.
-        `df[column].dtype.name`.
-
-        This function issues `error` level logs describing the first column that caused the check to fail.
-
-        It is assumed that `df` only has the columns defined in `schema`.
-
-        Args:
-            df:
-
-        Returns:
-            bool - `True` if `df` has the given dtypes, `False` otherwise
-        """
-        dtypes = df.dtypes
-
-        for column_name, expected_dtype in self.schema.items():
-            found_dtype = dtypes[column_name].name
-            if found_dtype != expected_dtype:
-                if self.show_casting_warnings:
-                    logger.info(f"Expected: '{expected_dtype}' dtype for {self.name}['{column_name}]', found '{found_dtype}'")
-                try:
-                    if len(set(type(v) for v in df[column_name].values)) > 1:  # pylint: disable=consider-using-set-comprehension
-                        logger.warning(CASTING_WARNING_MSG.format(column_name, expected_dtype, found_dtype))  # pylint: disable=logging-format-interpolation
-                        logger.info(NOTICE_MSG.format(column_name))  # pylint: disable=logging-format-interpolation
-                    df[column_name] = df[column_name].astype(self.schema[column_name])
-                except (ValueError, TypeError):
-                    logger.error(f"ValueError: Tried casting column {self.name}['{column_name}]' to '{expected_dtype}' " f"from '{found_dtype}', but failed")
-                    return False
-        return True
-
-    @staticmethod
-    def _get_options(options_from_code: MutableMapping[str, Any], options_from_resource_definition: Optional[Mapping[str, Any]]) -> MutableMapping[str, Any]:
-        """Retrieves options either from code or from a resource-definition.
-
-        Options are merged if they are provided by both sources, while in the case of conflicts, the options from the code
-        take precedence.
-
-        Args:
-            options_from_code (Optional[Mapping])
-            options_from_resource_definition (Optional[Mapping])
-
-        Returns:
-            [Optional[Mapping]]: options that are going to be used
-        """
-        if options_from_resource_definition:
-            return {**options_from_resource_definition, **options_from_code}
-        return options_from_code
-
-

Subclasses

- -

Class variables

-
-
var schema : Mapping[~KT, +VT_co]
-
-
-
-
-

Methods

-
-
-async def async_read(self) -
-
-

Allows the use of asyncio to concurrently read files in memory.

-

Returns

-

A pandas dataframe or an iterable.

-
- -Expand source code - -
async def async_read(self):
-    """Allows the use of asyncio to concurrently read files in memory.
-
-    Returns:
-        A pandas dataframe or an iterable.
-    """
-    loop = asyncio.get_running_loop()
-    return await loop.run_in_executor(pool, self.read)
-
-
-
-async def async_write(self, df: pandas.core.frame.DataFrame) -
-
-

Allows the use of asyncio to concurrently write files out.

-

Args

-
-
df
-
The data to be written
-
-
- -Expand source code - -
async def async_write(self, df: pd.DataFrame):
-    """Allows the use of asyncio to concurrently write files out.
-
-    Args:
-        df: The data to be written
-    """
-    loop = asyncio.get_running_loop()
-    return await loop.run_in_executor(pool, self.write, df)
-
-
-
-def log_metrics_from_schema(self, df: pandas.core.frame.DataFrame) ‑> DynamicDataIO -
-
-

Calculates and logs metrics based on the metrics present in its schema definition.

-

Args

-
-
df
-
A dataframe for which metrics are generated and logged
-
-

Returns

-

self (to allow for method chaining).

-
- -Expand source code - -
def log_metrics_from_schema(self, df: pd.DataFrame) -> "DynamicDataIO":
-    """Calculates and logs metrics based on the metrics present in its schema definition.
-
-    Args:
-        df: A dataframe for which metrics are generated and logged
-
-    Returns:
-         self (to allow for method chaining).
-    """
-    if not hasattr(self, "schema_metrics"):
-        raise MissingSchemaDefinition(self.__class__)
-
-    for column in self.schema_metrics.keys():
-        for metric in self.schema_metrics[column]:
-            get_metric(metric)(self.name, df, column)()  # type: ignore
-
-    return self
-
-
-
-def read(self) ‑> pandas.core.frame.DataFrame -
-
-

Reads data source and returns a schema validated dataframe (by means of _apply_schema).

-

Returns

-

A pandas dataframe or an iterable.

-
- -Expand source code - -
def read(self) -> pd.DataFrame:
-    """Reads data source and returns a schema validated dataframe (by means of _apply_schema).
-
-    Returns:
-        A pandas dataframe or an iterable.
-    """
-    source_name = self.sources_config.get("type")
-    df = getattr(self, f"_read_from_{source_name}")()
-
-    df = self._apply_schema(df)
-    if self.apply_schema_validations:
-        self.validate_from_schema(df)
-    if self.log_schema_metrics:
-        self.log_metrics_from_schema(df)
-
-    return df
-
-
-
-def validate_from_schema(self, df: pandas.core.frame.DataFrame) ‑> DynamicDataIO -
-
-

Validates a dataframe based on the validations present in its schema definition.

-

All validations are checked and if any of them fails, a SchemaValidationError is raised.

-

Args

-

df:

-

Returns

-

self (to allow for method chaining).

-

Raises

-
-
SchemaValidationError
-
if any of the validations failed. The message attribute of -the exception object is a List[str], where each element is the name of a -validation that failed.
-
-
- -Expand source code - -
def validate_from_schema(self, df: pd.DataFrame) -> "DynamicDataIO":
-    """Validates a dataframe based on the validations present in its schema definition.
-
-    All validations are checked and if any of them fails, a `SchemaValidationError` is raised.
-
-    Args:
-        df:
-
-    Returns:
-         self (to allow for method chaining).
-
-    Raises:
-        SchemaValidationError: if any of the validations failed. The `message` attribute of
-            the exception object is a `List[str]`, where each element is the name of a
-            validation that failed.
-    """
-    if not hasattr(self, "schema_validations"):
-        raise MissingSchemaDefinition(self.__class__)
-
-    failed_validations = {}
-    for column in self.schema_validations.keys():
-        for validation in self.schema_validations[column].keys():
-            if self.schema_validations[column][validation]["apply"] is True:
-                validation_result = getattr(validations, validation)(self.name, df, column, **self.schema_validations[column][validation]["options"])
-                if not validation_result.valid:
-                    failed_validations[validation] = validation_result.message
-
-    if len(failed_validations) > 0:
-        raise SchemaValidationError(failed_validations)
-
-    return self
-
-
-
-def write(self, df: pandas.core.frame.DataFrame) -
-
-

Sink data to a given source based on the sources_config.

-

Args

-
-
df
-
The data to be written
-
-
- -Expand source code - -
def write(self, df: pd.DataFrame):
-    """Sink data to a given source based on the sources_config.
-
-    Args:
-        df: The data to be written
-    """
-    source_name = self.sources_config.get("type")
-    if set(df.columns) != set(self.schema.keys()):  # pylint: disable=E1101
-        columns = [column for column in df.columns.to_list() if column in self.schema.keys()]
-        df = df[columns]
-
-    if self.apply_schema_validations:
-        self.validate_from_schema(df)
-    if self.log_schema_metrics:
-        self.log_metrics_from_schema(df)
-
-    getattr(self, f"_write_to_{source_name}")(self._apply_schema(df))
-
-
-
-
-
-
-
- -
- - - \ No newline at end of file diff --git a/docs/coverage_report/coverage-badge.svg b/docs/coverage_report/coverage-badge.svg deleted file mode 100644 index fe06143..0000000 --- a/docs/coverage_report/coverage-badge.svg +++ /dev/null @@ -1,21 +0,0 @@ - - - - - - - - - - - - - - - - coverage - coverage - 94% - 94% - - diff --git a/docs/errors.html b/docs/errors.html deleted file mode 100644 index 755daa6..0000000 --- a/docs/errors.html +++ /dev/null @@ -1,684 +0,0 @@ - - - - - - -dynamicio.errors API documentation - - - - - - - - - - - -
-
-
-

Module dynamicio.errors

-
-
-

Hosts exception implementations for different errors.

-
- -Expand source code - -
"""Hosts exception implementations for different errors."""
-# pylint: disable=missing-module-docstring, missing-class-docstring, missing-function-docstring, super-init-not-called
-__all__ = [
-    "DynamicIOError",
-    "DataSourceError",
-    "ColumnsDataTypeError",
-    "NonUniqueIdColumnError",
-    "NullValueInColumnError",
-    "NotExpectedCategoricalValue",
-    "MissingSchemaDefinition",
-    "SchemaNotFoundError",
-    "SchemaValidationError",
-    "InvalidDatasetTypeError",
-    "CASTING_WARNING_MSG",
-    "NOTICE_MSG",
-]
-
-from typing import Any, Optional
-
-
-class DynamicIOError(Exception):
-    """Base class for DynamicIO errors."""
-
-    ERROR_STR: str = ""
-    ERROR_STR_DETAILED: str = "{0}"
-
-    @property
-    def message(self) -> Optional[Any]:
-        """Easy access for optional message argument.
-
-        Returns:
-            Message or `None` if not set
-        """
-        try:
-            return self.args[0]
-        except IndexError:
-            return None
-
-    def __str__(self):
-        """Enrich and return error message."""
-        message = self.message
-
-        if message is None:
-            return self.ERROR_STR
-
-        return self.ERROR_STR_DETAILED.format(message)
-
-
-class SchemaNotFoundError(DynamicIOError):
-    """Error raised when schema is not specified in the provided source."""
-
-    ERROR_STR = "Schema not specified in the provided source"
-    ERROR_STR_DETAILED = "Schema not specified in the provided source: {0} "
-
-
-class SchemaValidationError(DynamicIOError):
-    """Error raised when schema validation fails."""
-
-
-class MissingSchemaDefinition(DynamicIOError):
-    """Error raised when schema is not specified in the provided source."""
-
-    ERROR_STR = "The resource definition for this class is missing a schema definition"
-    ERROR_STR_DETAILED = "The resource definition for this class is missing a schema definition: {0}"
-
-
-class DataSourceError(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-
-class ColumnsDataTypeError(DynamicIOError):
-    """Error raised when the validated data does not have the expected data types."""
-
-
-class NonUniqueIdColumnError(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-
-class NullValueInColumnError(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-
-class NotExpectedCategoricalValue(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-
-class InvalidDatasetTypeError(DynamicIOError):
-    """Error raised when dataset type is not one of [parquet, json, csv, h5]."""
-
-    ERROR_STR = "The dataset provided is not amongst the supported types (parquet, json, csv, h5) handled by dynamicio."
-    ERROR_STR_DETAILED = "Dataset: {0} provided is not amongst the supported types (parquet, json, csv, h5) handled by dynamicio."
-
-
-# Warning messages
-CASTING_WARNING_MSG = "Applying casting column: '{0}' to: 'type:{1}' from 'type:{2}' though not advised, as `dtypes`>1 for {0}, which may lead to data corruption!"
-NOTICE_MSG = "Keeping the {0} as is, may anyway cause I/O errors or data corruption issues especially when using `pandas.DataFrame.to_parquet` or `pandas.DataFrame.to_json`."
-
-
-
-
-
-
-
-
-
-

Classes

-
-
-class ColumnsDataTypeError -(*args, **kwargs) -
-
-

Error raised when the validated data does not have the expected data types.

-
- -Expand source code - -
class ColumnsDataTypeError(DynamicIOError):
-    """Error raised when the validated data does not have the expected data types."""
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class DataSourceError -(*args, **kwargs) -
-
-

Error raised when the data source fails to load.

-
- -Expand source code - -
class DataSourceError(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class DynamicIOError -(*args, **kwargs) -
-
-

Base class for DynamicIO errors.

-
- -Expand source code - -
class DynamicIOError(Exception):
-    """Base class for DynamicIO errors."""
-
-    ERROR_STR: str = ""
-    ERROR_STR_DETAILED: str = "{0}"
-
-    @property
-    def message(self) -> Optional[Any]:
-        """Easy access for optional message argument.
-
-        Returns:
-            Message or `None` if not set
-        """
-        try:
-            return self.args[0]
-        except IndexError:
-            return None
-
-    def __str__(self):
-        """Enrich and return error message."""
-        message = self.message
-
-        if message is None:
-            return self.ERROR_STR
-
-        return self.ERROR_STR_DETAILED.format(message)
-
-

Ancestors

-
    -
  • builtins.Exception
    • -
  • builtins.BaseException
    • -
-

Subclasses

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Instance variables

-
-
var message : Optional[Any]
-
-

Easy access for optional message argument.

-

Returns

-

Message or None if not set

-
- -Expand source code - -
@property
-def message(self) -> Optional[Any]:
-    """Easy access for optional message argument.
-
-    Returns:
-        Message or `None` if not set
-    """
-    try:
-        return self.args[0]
-    except IndexError:
-        return None
-
-
-
-
-
-class InvalidDatasetTypeError -(*args, **kwargs) -
-
-

Error raised when dataset type is not one of [parquet, json, csv, h5].

-
- -Expand source code - -
class InvalidDatasetTypeError(DynamicIOError):
-    """Error raised when dataset type is not one of [parquet, json, csv, h5]."""
-
-    ERROR_STR = "The dataset provided is not amongst the supported types (parquet, json, csv, h5) handled by dynamicio."
-    ERROR_STR_DETAILED = "Dataset: {0} provided is not amongst the supported types (parquet, json, csv, h5) handled by dynamicio."
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class MissingSchemaDefinition -(*args, **kwargs) -
-
-

Error raised when schema is not specified in the provided source.

-
- -Expand source code - -
class MissingSchemaDefinition(DynamicIOError):
-    """Error raised when schema is not specified in the provided source."""
-
-    ERROR_STR = "The resource definition for this class is missing a schema definition"
-    ERROR_STR_DETAILED = "The resource definition for this class is missing a schema definition: {0}"
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class NonUniqueIdColumnError -(*args, **kwargs) -
-
-

Error raised when the data source fails to load.

-
- -Expand source code - -
class NonUniqueIdColumnError(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class NotExpectedCategoricalValue -(*args, **kwargs) -
-
-

Error raised when the data source fails to load.

-
- -Expand source code - -
class NotExpectedCategoricalValue(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class NullValueInColumnError -(*args, **kwargs) -
-
-

Error raised when the data source fails to load.

-
- -Expand source code - -
class NullValueInColumnError(DynamicIOError):
-    """Error raised when the data source fails to load."""
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class SchemaNotFoundError -(*args, **kwargs) -
-
-

Error raised when schema is not specified in the provided source.

-
- -Expand source code - -
class SchemaNotFoundError(DynamicIOError):
-    """Error raised when schema is not specified in the provided source."""
-
-    ERROR_STR = "Schema not specified in the provided source"
-    ERROR_STR_DETAILED = "Schema not specified in the provided source: {0} "
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-class SchemaValidationError -(*args, **kwargs) -
-
-

Error raised when schema validation fails.

-
- -Expand source code - -
class SchemaValidationError(DynamicIOError):
-    """Error raised when schema validation fails."""
-
-

Ancestors

- -

Class variables

-
-
var ERROR_STR : str
-
-
-
-
var ERROR_STR_DETAILED : str
-
-
-
-
-

Inherited members

- -
-
-
-
- -
- - - \ No newline at end of file diff --git a/docs/images/data-types.png b/docs/images/data-types.png deleted file mode 100644 index 106a2ef9688a6b048a240d34978bb495ae331c8a..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 47696 zcmcF~Ra6{Z(Cy&v4DQb065QPxU~snt4HBH-uE8BLgJmE=g9UdD4gmrL2=1;yF5my( zr~7`_>VD{6XZ5O6XP>G%yLQKcwUlu%DKG&50FJ7Pf-V4n0DQeA(NSODFcaMT002S( zstU3YKZ~P6G$Rtjo0p|d$F`-_92*TAQUsu%rTC({hMK)wHu z>0E!cAh5KO&-**`QqI%q>GS06M8U!aKTkUw{^-xkf_Hy>A0$6a>=u1EEhHBfcCKgn z|9b@t?i>26T=bS&%BXA?V*Mx+O%U!-sKmliQftNLgkoL{CJ>2Yfx;IOe> z2&M-lhBFx#&OKqJ8R_9_RHg}}S?=oS)XV~PSiOVZ7F)<$5L}Cy6MR=)Wf9P+VXTP_ zD4giet9R4|Iul>-l%@;0{(jua#=jOTh&3sC2fV)9SLm2n!M~<>ea`xSo=F7i%D?15 znBO|^9*paiX%&ifjpOJ{evJ=UMb#PGtAr1Y2(*U6cMTLfe9Y(gTR{gN{PQsZ9ir?9 zKlF8KOi3FPmFmhlH7YM=$P)wP=P1$ZmR!32F)Mb^2=wWW+2c1pYI!5*eEM2+oBb;$ zfa`7Runeu!Jyrqt&nsBgSm_bxuZ*5j5J%yLhycl^=H=PhT?eR4J^NYyeQbaQ$vdU( zaC%Xoq1UUeu_BcOH-5uTpvtsN5glc 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