buster-dev / tests /test_documents.py
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PR: DocumentsManager interface (#57)
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import numpy as np
import pandas as pd
import pytest
from buster.documents import DocumentsDB, DocumentsPickle
@pytest.mark.parametrize("documents_manager, extension", [(DocumentsDB, "db"), (DocumentsPickle, "tar.gz")])
def test_write_read(tmp_path, documents_manager, extension):
db = documents_manager(tmp_path / f"test.{extension}")
data = pd.DataFrame.from_dict(
{
"title": ["test"],
"url": ["http://url.com"],
"content": ["cool text"],
"embedding": [np.arange(10, dtype=np.float32) - 0.3],
"n_tokens": [10],
}
)
db.add(source="test", df=data)
db_data = db.get_documents("test")
assert db_data["title"].iloc[0] == data["title"].iloc[0]
assert db_data["url"].iloc[0] == data["url"].iloc[0]
assert db_data["content"].iloc[0] == data["content"].iloc[0]
assert np.allclose(db_data["embedding"].iloc[0], data["embedding"].iloc[0])
assert db_data["n_tokens"].iloc[0] == data["n_tokens"].iloc[0]
@pytest.mark.parametrize("documents_manager, extension", [(DocumentsDB, "db"), (DocumentsPickle, "tar.gz")])
def test_write_write_read(tmp_path, documents_manager, extension):
db = documents_manager(tmp_path / f"test.{extension}")
data_1 = pd.DataFrame.from_dict(
{
"title": ["test"],
"url": ["http://url.com"],
"content": ["cool text"],
"embedding": [np.arange(10, dtype=np.float32) - 0.3],
"n_tokens": [10],
}
)
db.add(source="test", df=data_1)
data_2 = pd.DataFrame.from_dict(
{
"title": ["other"],
"url": ["http://url.com/page.html"],
"content": ["lorem ipsum"],
"embedding": [np.arange(20, dtype=np.float32) / 10 - 2.3],
"n_tokens": [20],
}
)
db.add(source="test", df=data_2)
db_data = db.get_documents("test")
assert len(db_data) == len(data_2)
assert db_data["title"].iloc[0] == data_2["title"].iloc[0]
assert db_data["url"].iloc[0] == data_2["url"].iloc[0]
assert db_data["content"].iloc[0] == data_2["content"].iloc[0]
assert np.allclose(db_data["embedding"].iloc[0], data_2["embedding"].iloc[0])
assert db_data["n_tokens"].iloc[0] == data_2["n_tokens"].iloc[0]