community[patch]: add NotebookLoader unit test (#17721)

Thank you for contributing to LangChain!

- **Description:** added unit tests for NotebookLoader. Linked PR:
https://github.com/langchain-ai/langchain/pull/17614
- **Issue:**
[#17614](https://github.com/langchain-ai/langchain/pull/17614)
    - **Twitter handle:** @paulodoestech
- [x] Pass lint and test: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified to check that you're
passing lint and testing. See contribution guidelines for more
information on how to write/run tests, lint, etc:
https://python.langchain.com/docs/contributing/
- [x] Add tests and docs: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.

---------

Co-authored-by: lachiewalker <lachiewalker1@hotmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
pull/17614/head^2
Paulo Nascimento 3 months ago committed by GitHub
parent 4c3a67122f
commit 44a3484503
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@ -25,7 +25,11 @@ def concatenate_cells(
"""
cell_type = cell["cell_type"]
source = cell["source"]
output = cell["outputs"]
if include_outputs:
try:
output = cell["outputs"]
except KeyError:
pass
if include_outputs and cell_type == "code" and output:
if "ename" in output[0].keys():
@ -58,14 +62,13 @@ def concatenate_cells(
def remove_newlines(x: Any) -> Any:
"""Recursively remove newlines, no matter the data structure they are stored in."""
import pandas as pd
if isinstance(x, str):
return x.replace("\n", "")
elif isinstance(x, list):
return [remove_newlines(elem) for elem in x]
elif isinstance(x, pd.DataFrame):
return x.applymap(remove_newlines)
elif isinstance(x, dict):
return {k: remove_newlines(v) for (k, v) in x.items()}
else:
return x
@ -104,29 +107,29 @@ class NotebookLoader(BaseLoader):
self,
) -> List[Document]:
"""Load documents."""
try:
import pandas as pd
except ImportError:
raise ImportError(
"pandas is needed for Notebook Loader, "
"please install with `pip install pandas`"
)
p = Path(self.file_path)
with open(p, encoding="utf8") as f:
d = json.load(f)
data = pd.json_normalize(d["cells"])
filtered_data = data[["cell_type", "source", "outputs"]]
filtered_data = [
{k: v for (k, v) in cell.items() if k in ["cell_type", "source", "outputs"]}
for cell in d["cells"]
]
if self.remove_newline:
filtered_data = filtered_data.applymap(remove_newlines)
text = filtered_data.apply(
lambda x: concatenate_cells(
x, self.include_outputs, self.max_output_length, self.traceback
),
axis=1,
).str.cat(sep=" ")
filtered_data = list(map(remove_newlines, filtered_data))
text = "".join(
list(
map(
lambda x: concatenate_cells(
x, self.include_outputs, self.max_output_length, self.traceback
),
filtered_data,
)
)
)
metadata = {"source": str(p)}

@ -0,0 +1,85 @@
import json
from pytest_mock import MockerFixture
from langchain_community.document_loaders.notebook import NotebookLoader
def test_initialization() -> None:
loader = NotebookLoader(path="./testfile.ipynb")
assert loader.file_path == "./testfile.ipynb"
def test_load_no_outputs(mocker: MockerFixture) -> None:
mock_notebook_content = {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": ["# Test notebook\n", "This is a test notebook."],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": ["Hello World!\n"],
}
],
}
]
}
mocked_cell_type = mock_notebook_content["cells"][0]["cell_type"]
mocked_source = mock_notebook_content["cells"][0]["source"]
# Convert the mock notebook content to a JSON string
mock_notebook_content_str = json.dumps(mock_notebook_content)
# Mock the open function & json.load functions
mocker.patch("builtins.open", mocker.mock_open(read_data=mock_notebook_content_str))
mocker.patch("json.load", return_value=mock_notebook_content)
loader = NotebookLoader(path="./testfile.ipynb")
docs = loader.load()
assert len(docs) == 1
assert docs[0].page_content == f"'{mocked_cell_type}' cell: '{mocked_source}'\n\n"
assert docs[0].metadata == {"source": "testfile.ipynb"}
def test_load_with_outputs(mocker: MockerFixture) -> None:
mock_notebook_content: dict = {
"cells": [
{
"cell_type": "code",
"metadata": {},
"source": ["# Test notebook\n", "This is a test notebook."],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": ["Hello World!\n"],
}
],
}
]
}
mocked_cell_type = mock_notebook_content["cells"][0]["cell_type"]
mocked_source = mock_notebook_content["cells"][0]["source"]
mocked_output = mock_notebook_content["cells"][0]["outputs"][0]["text"]
# Convert the mock notebook content to a JSON string
mock_notebook_content_str = json.dumps(mock_notebook_content)
# Mock the open function & json.load functions
mocker.patch("builtins.open", mocker.mock_open(read_data=mock_notebook_content_str))
mocker.patch("json.load", return_value=mock_notebook_content)
loader = NotebookLoader(path="./testfile.ipynb", include_outputs=True)
docs = loader.load()
assert len(docs) == 1
expected_content = (
f"'{mocked_cell_type}' cell: '{mocked_source}'\n"
f" with output: '{mocked_output}'\n\n"
)
assert docs[0].page_content == expected_content
assert docs[0].metadata == {"source": "testfile.ipynb"}
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