diff --git a/CHANGELOG.md b/CHANGELOG.md index 525db12..30b1c5a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -2,6 +2,13 @@ All notable changes to this project will be documented in this file. +## [0.5.0] - 2023-04-26 + +### Added + +- Added tasks `begin_sql_transaction` and `end_sql_transaction` to the `utils`module. These enable the management of SQL + transactions in flows. It also allows for dry running SQL statements. + ## [0.4.0] - 2023-02-08 ### Added diff --git a/README.md b/README.md index f5b5876..e3abcf9 100644 --- a/README.md +++ b/README.md @@ -120,6 +120,31 @@ with Flow(...) as flow: close_ssh_tunnel.run(tunnel=tunnel, upstream_tasks=[mysql_closed]) ``` +**Use SQL transactions and dry running** + +```python +from lolafect.connections import connect_to_mysql, close_mysql_connection +from lolafect.utils import begin_sql_transaction, end_sql_transaction + +with Flow(...) as flow: + connection = connect_to_mysql( + mysql_credentials={...}, # You probably want to get this from TEST_LOLACONFIG.DW_CREDENTIALS + ) + transaction_started = begin_sql_transaction(connection) + task_result = some_task_that_needs_mysql( + connection=connection, + upstream_task=[transaction_started] + ) + transaction_finished = end_sql_transaction( + connection, + dry_run=False, # True means rollback, False means commit changes + upstream_tasks=[task_result] + ) + + close_mysql_connection(connection=connection, upstream_tasks=[transaction_finished]) + +``` + ### Use Great Expectations **Run a Great Expectations validation on a MySQL query** @@ -164,6 +189,13 @@ with Flow(...) as flow: ) ``` +## Gallery + +This repo also contains a gallery of example flows that you can user to better +understand `lolafect` or as templates to kickstart your own flows. You can +find these in `docs/gallery`. + + ## How to test There are two test suites: unit tests and integration tests. Integration tests are prepared to plug to some of our diff --git a/docs/gallery/data_testing/README.md b/docs/gallery/data_testing/README.md new file mode 100644 index 0000000..a1de4b0 --- /dev/null +++ b/docs/gallery/data_testing/README.md @@ -0,0 +1,7 @@ +# Data Testing Gallery + +In this folder, you can find a sample flow project that showcases how you can +do data testing with Lolafect. + +You can also take a look at our GE best practices and guidelines +[here](https://pdofonte.atlassian.net/wiki/spaces/DATA/pages/2484797445/Usage+Guidelines+and+Best+Practices). \ No newline at end of file diff --git a/docs/gallery/data_testing/data_testing_flow.py b/docs/gallery/data_testing/data_testing_flow.py new file mode 100644 index 0000000..683237c --- /dev/null +++ b/docs/gallery/data_testing/data_testing_flow.py @@ -0,0 +1,238 @@ +### INTRO + +# This is an example flow to showcase data testing. + +# There are several ways you can use this: +# 1. If you simply want to copy paste useful recipes... the flow is yours. +# 2. If you want to learn, I would advice: +# - Skim through the whole script. +# - Now read the flow block carefully and refer to other parts of the +# script when needed. +# - Try to run the flow as-is. It should succeed. +# - Try to intentionally break the data test by changing the data or the +# expectations. + +### HOW TO RUN +# The flow is packed with comments to guide you through what's happening. +# The flow is also runnable. To run it: +# - Make a virtual environment with the requirements.txt that live in the same +# folder as this script. +# - Start a shell, activate the venv, login to AWS and turn on your Mercadão +# VPN. +# - In the shell, run the command: prefect run -p docs/gallery/data_testing/data_testing_flow.py +# +# Note: this flow is designed to run in your laptop. It won't work in the +# prefect server. Don't bother uploading it. + +# The flow connects to DW and makes a silly check on a silly query. You can use +# it as a reference on how to set up a data test in your serious flows. + + +### IMPORTS + +import datetime + +from prefect import Flow, task, case +from prefect.run_configs import KubernetesRun + +# ↑↑↑ Standard prefect stuff for the flow. + +from great_expectations.core.expectation_configuration import ExpectationConfiguration + +# ↑↑↑ ExpectationConfiguration is the class that allows us to define a single +# expectation. We use it once for every expectation we define. + +from lolafect.lolaconfig import build_lolaconfig + +# ↑↑↑ Usual lolaconfig import to get all the env data. +from lolafect.connections import ( + open_ssh_tunnel_with_s3_pkey, # ←←← We connect through an SSH tunnel + close_ssh_tunnel, # ←←← Which we will have to close + connect_to_mysql, # ←←← For quarantine purposes + close_mysql_connection, # ←←← To close the previous connection +) +from lolafect.slack import SendSlackMessageTask + +# ↑↑↑ The task class to send slack messages. +from lolafect.data_testing import ( + run_data_test_on_mysql, +) # ←←← The task to run a data test + +### PREP + +LOLACONFIG = build_lolaconfig(flow_name="lolafect-gallery-data-testing-demo") +# ↑↑↑ Get env from S3 and prepare everything related to it + + +DATA_TEST_NAME = "gallery-example-test" +# ↑↑↑ Our data test must have a name. We will need this if we want to look for +# its logs in S3. + +DATA_TEST_QUERY = """ + SELECT "hi" AS some_string, + 1 AS some_number, + NULL as some_null +""" +# ↑↑↑ Our query defines what data do we want to test. This is a silly select +# with hardcoded values because this is a demo, but in a real environment, you +# most probably will want to have a common SELECT [...] FROM [...] query that +# fetches the data your want to test. + +DATA_TEST_EXPECTATIONS = [ + ExpectationConfiguration( + expectation_type="expect_column_values_to_match_like_pattern", + kwargs={"column": "some_string", "like_pattern": "%hi%"}, + ), + ExpectationConfiguration( + expectation_type="expect_column_values_to_be_between", + kwargs={"column": "some_number", "min_value": 1, "max_value": 1}, + ), + ExpectationConfiguration( + expectation_type="expect_column_values_to_be_null", + kwargs={"column": "some_null"}, + ), +] + +# ↑↑↑ Our expectations define what data should be like. Each expectation is +# defined with a call to ExpectationConfiguration. You can check a reference +# of available expectations and how to call them here: +# https://legacy.docs.greatexpectations.io/en/latest/reference/glossary_of_expectations.html + + +@task +def fetch_tunnel_host_and_port(ssh_tunnel): + host = ssh_tunnel.local_bind_address[0] + port = ssh_tunnel.local_bind_address[1] + + return host, port + + +# ↑↑↑ A small helper function to get the host and the port where the SSH +# tunnel is listening inside this host. + + +@task +def fail(exception, message): + raise exception(message) + + +# ↑↑↑ A small helper function to cause a task failure with a custom message. + + +@task +def quarantine_failed_data(connection, query_to_get_quarantine_data): + cursor = connection.cursor() + + cursor.execute( + f""" + CREATE TABLE quarantine.{LOLACONFIG.FLOW_NAME_UDCS}_{datetime.datetime.now().strftime("%Y%m%d_%H%M%S")} AS + {query_to_get_quarantine_data} + """ + ) + # ↑↑↑ This query will store the faulty data in a quarantine schema in DW + # It creates a new table on each run, and uses the flow name and the current time + # to give the table a unique and informative name. + + +send_slack_message = SendSlackMessageTask() +# ↑↑↑ Simply making an instance of the task class. send_slack_message will be +# the task we use in the flow. + +### FLOW + +with Flow( + LOLACONFIG.FLOW_NAME_UDCS, + storage=LOLACONFIG.STORAGE, + run_config=KubernetesRun( + labels=LOLACONFIG.KUBERNETES_LABELS, + image=LOLACONFIG.KUBERNETES_IMAGE, + ), +) as flow: + + ssh_tunnel = open_ssh_tunnel_with_s3_pkey( + s3_bucket_name=LOLACONFIG.S3_BUCKET_NAME, + ssh_tunnel_credentials=LOLACONFIG.SSH_TUNNEL_CREDENTIALS, + remote_target_host=LOLACONFIG.DW_CREDENTIALS["host"], + remote_target_port=LOLACONFIG.DW_CREDENTIALS["port"], + ) + # ↑↑↑ We open an SSH tunnel pointing to DW + + # ↓↓↓ This is where we actually run the data test. The result of the test + # gets stored in data_test_result. + data_test_result = run_data_test_on_mysql( + name=DATA_TEST_NAME, # ←←← The name we set earlier + # ↓↓↓ The credentials to the MySQL where the data lives. We pass the + # ssh tunnel host and port instead of the true MySQL because we want + # to pass through the tunnel. If it was a direct connection, we would + # simply use the MySQL true host and port. + mysql_credentials={ + "host": fetch_tunnel_host_and_port(ssh_tunnel)[0], + "port": fetch_tunnel_host_and_port(ssh_tunnel)[1], + "user": LOLACONFIG.DW_CREDENTIALS["user"], + "password": LOLACONFIG.DW_CREDENTIALS["password"], + "db": "sandbox", # ←←← We always need to pass a default db, but it + # is recommended to always specify your schemas + }, # in the queries regardless. + query=DATA_TEST_QUERY, # ←←← The query we set earlier + expectation_configurations=DATA_TEST_EXPECTATIONS, # ←←← Idem + upstream_tasks=[ssh_tunnel], # ←←← We must wait for the tunnel to be ready + ) + + # ↑↑↑ will take care of everything: connecting to S3 and DW, generate all + # the necessary configurations, run the actual test and store results both + # in memory and in S3. + # + # What to do from here is up to you. You can easily check if the test + # passed or not by accessing data_test_result["success"]. If it equals + # True, the test passed. If it equals False, at least one expectation + # failed. + # + # The following snippets are optional. You should judge if you want to do + # something similar or not in your flow based on your needs. + + ### RAISING AN EXCEPTION + # When a test with run_data_test_on_mysql fails, it's important that you + # keep in mind that this will not cause a failure, in the sense of a + # prefect task failing. This is intentional: we didn't want to assume that + # a failing data test always translates into a failed flow. + # + # Nevertheless, it might be the case that you want your flow to fail if + # the data test didn't pass. To do so, you can use a simple helper task and + # a case, just like this: + + with case(data_test_result["success"], False): + fail(ValueError, "Woops, the test didn't pass.") + + ### SENDING A SLACK WARNING + # You might also want to send a slack message to a channel if the test + # does not pass. You can do so like this: + + with case(data_test_result["success"], False): + send_slack_message( + LOLACONFIG.SLACK_WEBHOOKS["data-team-alerts-testing"], # ←←← A webhook URL + "Uh oh, the demo flow failed.", # ←←← Your warning message + ) + + ### QUARANTINE THE TESTED DATA + # Another common practice is to store the data that doesn't pass a test. + # This provides a lot of benefits that are discussed in our best practices + # docs in Confluence. Here is an example of you can quarantine the data + # that made your test fail: + + dw_connection = connect_to_mysql( + mysql_credentials=LOLACONFIG.DW_CREDENTIALS, + overriding_host_and_port=fetch_tunnel_host_and_port(ssh_tunnel), + upstream_tasks=[data_test_result], + ) + # ↑↑↑ We connect to DW, and since we are using the SSH tunnel, we + # override DWs host and port and instead use the listening ones from + # the tunnel. + + with case(data_test_result["success"], False): + quarantined = quarantine_failed_data(dw_connection, DATA_TEST_QUERY) + # ↑↑↑ We call the quarantine_failed_data task. You can review the + # actions of this task in the definition that appears earlier in this + # file. + + mysql_closed = close_mysql_connection(dw_connection) + tunnel_closed = close_ssh_tunnel(ssh_tunnel, upstream_tasks=[mysql_closed]) diff --git a/docs/gallery/data_testing/requirements.txt b/docs/gallery/data_testing/requirements.txt new file mode 100644 index 0000000..245292b --- /dev/null +++ b/docs/gallery/data_testing/requirements.txt @@ -0,0 +1,4 @@ +prefect==1.2.2 +great_expectations==0.15.45 +SQLAlchemy==1.4.46 +lolafect==0.4.0 \ No newline at end of file diff --git a/lolafect/__version__.py b/lolafect/__version__.py index 6a9beea..3d18726 100644 --- a/lolafect/__version__.py +++ b/lolafect/__version__.py @@ -1 +1 @@ -__version__ = "0.4.0" +__version__ = "0.5.0" diff --git a/lolafect/utils.py b/lolafect/utils.py index 621e59d..2b7e460 100644 --- a/lolafect/utils.py +++ b/lolafect/utils.py @@ -1,5 +1,8 @@ import json +from typing import Any +import prefect +from prefect import task class S3FileReader: """ @@ -22,3 +25,41 @@ class S3FileReader: .read() .decode("utf-8") ) + +@task() +def begin_sql_transaction(connection: Any) -> None: + """ + Start a SQL transaction in the passed connection. The task is agnostic to + the SQL engine being used. As long as the connection object implements a + begin() method, this task will work. + + :param connection: the connection to some database. + :return: None + """ + logger = prefect.context.get("logger") + logger.info(f"Starting SQL transaction with connection: {connection}.") + connection.begin() + + +@task() +def end_sql_transaction(connection: Any, dry_run: bool = False) -> None: + """ + Finish a SQL transaction, either by rolling it back or by committing it. + The task is agnostic to the SQL engine being used. As long as the + connection object implements a `commit` and a `rollback` method, this task + will work. + + :param connection: the connection to some database. + :param dry_run: a flag indicating if persistence is desired. If dry_run + is True, changes will be rolledback. Otherwise, they will be committed. + :return: None + """ + logger = prefect.context.get("logger") + logger.info(f"Using connection: {connection}.") + + if dry_run: + connection.rollback() + logger.info("Dry-run mode activated. Rolling back the transaction.") + else: + logger.info("Committing the transaction.") + connection.commit() diff --git a/tests/test_integration/test_utils.py b/tests/test_integration/test_utils.py new file mode 100644 index 0000000..1ce5f85 --- /dev/null +++ b/tests/test_integration/test_utils.py @@ -0,0 +1,123 @@ +import pytest + +from lolafect.lolaconfig import build_lolaconfig +from lolafect.connections import ( + open_ssh_tunnel_with_s3_pkey, + get_local_bind_address_from_ssh_tunnel, + close_ssh_tunnel, + connect_to_mysql, + close_mysql_connection, +) +from lolafect.utils import begin_sql_transaction, end_sql_transaction + +# __ __ _____ _ _ _____ _ _ _____ _ +# \ \ / /\ | __ \| \ | |_ _| \ | |/ ____| | +# \ \ /\ / / \ | |__) | \| | | | | \| | | __| | +# \ \/ \/ / /\ \ | _ /| . ` | | | | . ` | | |_ | | +# \ /\ / ____ \| | \ \| |\ |_| |_| |\ | |__| |_| +# \/ \/_/ \_\_| \_\_| \_|_____|_| \_|\_____(_) +# This testing suite requires: +# - The calling shell to have permission in AWS +# - The calling shell to be within the Mercadão network +# - Do not use this tests as part of CI/CD pipelines since they are not idempotent and +# rely external resources. Instead, use them manually to check yourself that things +# are working properly. + + +TEST_LOLACONFIG = build_lolaconfig(flow_name="testing-suite") + + +@pytest.fixture +def connection_with_test_table(): + """ + Connects to DW, creates a test table in the sandbox env, and yields the + connection to the test. + + After the test, the table is dropped and the connection is closed. + """ + test_local_bind_host = "127.0.0.1" + test_local_bind_port = 12345 + + tunnel = open_ssh_tunnel_with_s3_pkey.run( + s3_bucket_name=TEST_LOLACONFIG.S3_BUCKET_NAME, + ssh_tunnel_credentials=TEST_LOLACONFIG.SSH_TUNNEL_CREDENTIALS, + remote_target_host=TEST_LOLACONFIG.DW_CREDENTIALS["host"], + remote_target_port=TEST_LOLACONFIG.DW_CREDENTIALS["port"], + local_bind_host=test_local_bind_host, + local_bind_port=test_local_bind_port, + ) + + connection = connect_to_mysql.run( + mysql_credentials=TEST_LOLACONFIG.DW_CREDENTIALS, + overriding_host_and_port=get_local_bind_address_from_ssh_tunnel.run( + tunnel=tunnel + ), + ) + cursor = connection.cursor() + cursor.execute(""" + CREATE TABLE sandbox.lolafect_transaction_test_table + ( + a_test_column INT + ) + """) + + # Connection and table ready for tests + yield connection # Test happens now + # Test finished, time to remove stuff and close connection + + cursor.execute(""" + DROP TABLE sandbox.lolafect_transaction_test_table + """ + ) + close_mysql_connection.run(connection=connection) + close_ssh_tunnel.run(tunnel=tunnel) + + +def test_sql_transaction_persists_changes_properly(connection_with_test_table): + cursor = connection_with_test_table.cursor() + + cursor.execute(""" + SELECT a_test_column + FROM sandbox.lolafect_transaction_test_table + """) + table_is_empty_at_first = not bool(cursor.fetchall()) # An empty tuple yields False + + begin_sql_transaction.run(connection=connection_with_test_table) + cursor.execute(""" + INSERT INTO sandbox.lolafect_transaction_test_table (a_test_column) + VALUES (1) + """) + end_sql_transaction.run(connection=connection_with_test_table, dry_run=False) + + cursor.execute(""" + SELECT a_test_column + FROM sandbox.lolafect_transaction_test_table + """) + table_has_a_record_after_commit = bool(cursor.fetchall()) # A non-empty tuple yields True + + assert table_is_empty_at_first and table_has_a_record_after_commit + + +def test_sql_transaction_rollbacks_changes_properly(connection_with_test_table): + cursor = connection_with_test_table.cursor() + + cursor.execute(""" + SELECT a_test_column + FROM sandbox.lolafect_transaction_test_table + """) + table_is_empty_at_first = not bool(cursor.fetchall()) # An empty tuple yields False + + begin_sql_transaction.run(connection=connection_with_test_table) + cursor.execute(""" + INSERT INTO sandbox.lolafect_transaction_test_table (a_test_column) + VALUES (1) + """) + end_sql_transaction.run(connection=connection_with_test_table, dry_run=True) + + cursor.execute(""" + SELECT a_test_column + FROM sandbox.lolafect_transaction_test_table + """) + table_is_still_empty_after_rollback = not bool(cursor.fetchall()) # A tuple yields False + + assert table_is_empty_at_first and table_is_still_empty_after_rollback