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chore: import upstream snapshot with attribution
2026-07-13 12:37:31 +08:00

67 lines
2.4 KiB
Python

# Copyright (c) 2024 Microsoft Corporation.
# Licensed under the MIT License
import pandas as pd
from graphrag.index.run.utils import create_run_context
from graphrag.index.typing.context import PipelineRunContext
from pandas.testing import assert_series_equal
pd.set_option("display.max_columns", None)
async def create_test_context(storage: list[str] | None = None) -> PipelineRunContext:
"""Create a test context with tables loaded into storage storage."""
context = create_run_context()
# always set the input docs, but since our stored table is final, drop what wouldn't be in the original source input
input = load_test_table("documents")
input.drop(columns=["text_unit_ids"], inplace=True)
await context.output_table_provider.write_dataframe("documents", input)
if storage:
for name in storage:
table = load_test_table(name)
await context.output_table_provider.write_dataframe(name, table)
return context
def load_test_table(output: str) -> pd.DataFrame:
"""Pass in the workflow output (generally the workflow name)"""
return pd.read_parquet(f"tests/verbs/data/{output}.parquet")
def compare_outputs(
actual: pd.DataFrame, expected: pd.DataFrame, columns: list[str] | None = None
) -> None:
"""Compare the actual and expected dataframes, optionally specifying columns to compare.
This uses assert_series_equal since we are sometimes intentionally omitting columns from the actual output.
"""
cols = expected.columns if columns is None else columns
assert len(actual) == len(expected), (
f"Expected: {len(expected)} rows, Actual: {len(actual)} rows"
)
for column in cols:
try:
assert column in actual.columns
except AssertionError:
print(f"Column '{column}' not found in actual output.")
try:
# dtypes can differ since the test data is read from parquet and our workflow runs in memory
if column != "id": # don't check uuids
assert_series_equal(
actual[column],
expected[column],
check_dtype=False,
check_index=False,
)
except AssertionError:
print(f"Column '{column}' does not match.")
print("Expected:")
print(expected[column])
print("Actual:")
print(actual[column])
raise