add python tests

Author: 1yefuwang1

pyproject.toml

@@ -4,6 +4,8 @@ requires = ["setuptools>=59", "wheel", "cmake", "ninja"]
 build-backend = "setuptools.build_meta"
 
 [tool.cibuildwheel]
+test-requires = ["pytest", "numpy", "apsw"]
+test-command = "pytest vectorlite_py/tests"
 skip = ["*-win32", "*-manylinux_i686", "*musllinux*", "pp*"]
 
 [tool.cibuildwheel.macos]

setup.py

@@ -82,7 +82,7 @@ def get_tag(self):
     url='https://github.com/1yefuwang1/vectorlite',
     license='Apache License, Version 2.0',
     version=VERSION,
-    packages=['vectorlite_py'],
+    packages=['vectorlite_py', 'vectorlite_py.test'],
     # package_data={"vectorlite_py": ['*.so', '*.dylib', '*.dll']},
     install_requires=[],
     ext_modules=[CMakeExtension('vectorlite')],

vectorlite_py/__init__.py

@@ -1,5 +1,7 @@
 import os
 
+__version__ = '0.1.0'
+
 def vectorlite_path():
     loadable_path = os.path.join(os.path.dirname(__file__), 'libvectorlite')
     return os.path.normpath(loadable_path)

vectorlite_py/test/__init__.py

@@ -0,0 +1,43 @@
+import vectorlite_py
+import apsw
+import pytest
+import numpy as np
+
+
+@pytest.fixture(scope='module')
+def conn() -> None:
+    conn = apsw.Connection(':memory:')
+    conn.enable_load_extension(True)
+    conn.load_extension(vectorlite_py.vectorlite_path())
+    return conn
+
+DIM = 32
+NUM_ELEMENTS = 1000
+
+# Generating sample data
+@pytest.fixture(scope='module')
+def random_vectors():
+    return np.float32(np.random.random((NUM_ELEMENTS, DIM)))
+
+def test_vectorlite_info(conn):
+    cur = conn.cursor()
+    cur.execute('select vectorlite_info()')
+    output = cur.fetchone()
+    assert f'vectorlite extension version {vectorlite_py.__version__}' in output[0]
+
+def test_l2_space_with_default_hnsw_param(conn, random_vectors):
+    cur = conn.cursor()
+    cur.execute('create virtual table x using vectorlite(my_embedding(32, "l2"), hnsw(max_elements=1000))')
+
+    for i in range(NUM_ELEMENTS):
+        cur.execute('insert into x (rowid, my_embedding) values (?, ?)', (i, random_vectors[i].tobytes()))
+    
+    result = cur.execute('select my_embedding from x where rowid = 0').fetchone()
+    assert result[0] == random_vectors[0].tobytes()
+
+    cur.execute('delete from x where rowid = 0')
+    result = cur.execute('select my_embedding from x where rowid = 0').fetchone()
+    assert result is None
+
+    result = cur.execute('select rowid, distance from x where knn_search(my_embedding, knn_param(?, ?))', (random_vectors[0].tobytes(), 10)).fetchall()
+    assert len(result) == 10