pytest fixtures for PostgreSQL
Project description
Lathorp - PostgreSQL Testing Fixtures
Lathorp provides handy pytest fixtures for test code that involves access to a PostgreSQL database.
For example, if the code under test writes data to a database, or queries it for data, you want to write tests to see that it writes and reads the data as you expect. You need an isolated and controlled environment for testing, so you need to set up a temporary database just for testing and fill it up with known data. Setting up a new database is a relatively time consuming operation that slows your tests down. You want to do this just once per testing session and let multiple tests share the same temporary database instance. However, many tests should be isolated from each other - you don't want side effects from a test (say, data written to the database) leaking to another test. The solution is to write known data before each test and delete it all after the test has finished.
The Fixtures
The pg
fixture is a session-scoped fixture that creates a new temporary database once per test session and deletes
it after the session is done.
The pg_connect
fixture is a function-scoped fixture that you use to establish a connection to the temporary database.
You can optionally load data into the database before the test begins, by pointing to data files that PostgreSQL can
read. The data is automatically deleted after the test function returns, so that it doesn't leak to other tests that
may expect different data.
Utility Functions
A utility function called load_schema_definitions
can be used to create the database structure by reading SQL DDL
files that you provide. Embed it in your own session-scoped fixture and call that together with pg_connect
.
Another utility, copy_data
, copies data from files in CSV or text format (as supported by PostgreSQL).
It can be used directly, or automatically by passing a path to the files to the pg_connect
fixture.
A third utility, delete_data
, deletes all data from a set of tables.
It is used automatically by pg_connect
to remove data from tables that it loaded with copy_data
.
You can also use it directly to clean up any changes made by your test.
Using Lathorp in Your Project
- Include the
lathorp
package with the development packages of your projects. Withpipenv
:
pipenv install --dev lathorp
-
Import fixtures from
lathorp
in your tests. You can also import them inconftest.py
to make them available to all your tests. Seetests/conftest.py
in this project for an example. -
Add either
pg
orpg_connect
as arguments to your test functions, as shown below. There's no point in adding both, sincepg_connect
itself usespg
.
def my_test(pg_connect):
"""A test that connects to the temporary test database."""
with pg_connect() as conn:
with conn.cursor() as cursor:
cursor.execute("SELECT 'Hello, world!' AS hello;")
For more examples, see tests/test_fixtures.py
in this project.
-
Lathorp truly shines when you use it together with schema definitions (SQL DDL) files and test data files (CSV or PostgreSQL-readable text). Create a session-scoped fixture that calls
load_schema_definitions
and give it the path to your schema definitions. Then use this fixture along withpg_connect
and give it the path to your data files.# In conftest.py import pathlib from lathorp import load_schema_definitions from lathorp.fixtures import pg from lathorp.fixtures import pg_connect def init_schema(pg): load_schema_definitions(pathlib.Path('path/to/my/ddl/file_or_directory')) # In your test module def test_my_fun(init_schema, pg_connect): conn = pg_connect(pathlib.Path('path/to/my_table.csv')) # loads data into my_table with conn.cursor() as cursor: cursor.execute('SELECT * FROM my_table;')
Now every test can have access to an initialized database with test-specific data.
Why "Lathorp?
The name is a reference to Dr. Emmett Lathorp "Doc" Brown, the crazy scientist and inventor of the DeLorean time machine from Back to the Future trilogy.
The Lathorp library too lets you go back in time to a fresh database after every test.
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