Steve Canny 3bab9d93e6
rfctr(part): prepare for pluggable auto-partitioners 1 (#3655)
**Summary**
In preparation for pluggable auto-partitioners simplify metadata as
discussed.

**Additional Context**
- Pluggable auto-partitioners requires partitioners to have a consistent
call signature. An arbitrary partitioner provided at runtime needs to
have a call signature that is known and consistent. Basically
`partition_x(filename, *, file, **kwargs)`.
- The current `auto.partition()` is highly coupled to each distinct
file-type partitioner, deciding which arguments to forward to each.
- This is driven by the existence of "delegating" partitioners, those
that convert their file-type and then call a second partitioner to do
the actual partitioning. Both the delegating and proxy partitioners are
decorated with metadata-post-processing decorators and those decorators
are not idempotent. We call the situation where those decorators would
run twice "double-decorating". For example, EPUB converts to HTML and
calls `partition_html()` and both `partition_epub()` and
`partition_html()` are decorated.
- The way double-decorating has been avoided in the past is to avoid
sending the arguments the metadata decorators are sensitive to to the
proxy partitioner. This is very obscure, complex to reason about,
error-prone, and just overall not a viable strategy. The better solution
is to not decorate delegating partitioners and let the proxy partitioner
handle all the metadata.
- This first step in preparation for that is part of simplifying the
metadata processing by removing unused or unwanted legacy parameters.
- `date_from_file_object` is a misnomer because a file-object never
contains last-modified data.
- It can never produce useful results in the API where last-modified
information must be provided by `metadata_last_modified`.
- It is an undocumented parameter so not in use.
- Using it can produce incorrect metadata.
2024-09-23 22:23:10 +00:00

343 lines
13 KiB
Python

# pyright: reportPrivateUsage=false
from __future__ import annotations
import io
import pytest
from pytest_mock import MockFixture
from test_unstructured.partition.test_constants import (
EXPECTED_TABLE,
EXPECTED_TABLE_SEMICOLON_DELIMITER,
EXPECTED_TABLE_WITH_EMOJI,
EXPECTED_TEXT,
EXPECTED_TEXT_SEMICOLON_DELIMITER,
EXPECTED_TEXT_WITH_EMOJI,
EXPECTED_TEXT_XLSX,
)
from test_unstructured.unit_utils import (
FixtureRequest,
Mock,
assert_round_trips_through_JSON,
example_doc_path,
function_mock,
)
from unstructured.chunking.title import chunk_by_title
from unstructured.cleaners.core import clean_extra_whitespace
from unstructured.documents.elements import Table
from unstructured.partition.csv import _CsvPartitioningContext, partition_csv
from unstructured.partition.utils.constants import UNSTRUCTURED_INCLUDE_DEBUG_METADATA
EXPECTED_FILETYPE = "text/csv"
@pytest.mark.parametrize(
("filename", "expected_text", "expected_table"),
[
("stanley-cups.csv", EXPECTED_TEXT, EXPECTED_TABLE),
("stanley-cups-with-emoji.csv", EXPECTED_TEXT_WITH_EMOJI, EXPECTED_TABLE_WITH_EMOJI),
(
"table-semicolon-delimiter.csv",
EXPECTED_TEXT_SEMICOLON_DELIMITER,
EXPECTED_TABLE_SEMICOLON_DELIMITER,
),
],
)
def test_partition_csv_from_filename(filename: str, expected_text: str, expected_table: str):
f_path = f"example-docs/{filename}"
elements = partition_csv(filename=f_path)
assert clean_extra_whitespace(elements[0].text) == expected_text
assert elements[0].metadata.text_as_html == expected_table
assert elements[0].metadata.filetype == EXPECTED_FILETYPE
assert elements[0].metadata.filename == filename
@pytest.mark.parametrize("infer_table_structure", [True, False])
def test_partition_csv_from_filename_infer_table_structure(infer_table_structure: bool):
f_path = "example-docs/stanley-cups.csv"
elements = partition_csv(filename=f_path, infer_table_structure=infer_table_structure)
table_element_has_text_as_html_field = (
hasattr(elements[0].metadata, "text_as_html")
and elements[0].metadata.text_as_html is not None
)
assert table_element_has_text_as_html_field == infer_table_structure
def test_partition_csv_from_filename_with_metadata_filename():
elements = partition_csv(example_doc_path("stanley-cups.csv"), metadata_filename="test")
assert clean_extra_whitespace(elements[0].text) == EXPECTED_TEXT
assert elements[0].metadata.filename == "test"
def test_partition_csv_with_encoding():
elements = partition_csv(example_doc_path("stanley-cups-utf-16.csv"), encoding="utf-16")
assert clean_extra_whitespace(elements[0].text) == EXPECTED_TEXT
@pytest.mark.parametrize(
("filename", "expected_text", "expected_table"),
[
("stanley-cups.csv", EXPECTED_TEXT, EXPECTED_TABLE),
("stanley-cups-with-emoji.csv", EXPECTED_TEXT_WITH_EMOJI, EXPECTED_TABLE_WITH_EMOJI),
],
)
def test_partition_csv_from_file(filename: str, expected_text: str, expected_table: str):
f_path = f"example-docs/{filename}"
with open(f_path, "rb") as f:
elements = partition_csv(file=f)
assert clean_extra_whitespace(elements[0].text) == expected_text
assert isinstance(elements[0], Table)
assert elements[0].metadata.text_as_html == expected_table
assert elements[0].metadata.filetype == EXPECTED_FILETYPE
assert elements[0].metadata.filename is None
if UNSTRUCTURED_INCLUDE_DEBUG_METADATA:
assert {element.metadata.detection_origin for element in elements} == {"csv"}
def test_partition_csv_from_file_with_metadata_filename():
with open(example_doc_path("stanley-cups.csv"), "rb") as f:
elements = partition_csv(file=f, metadata_filename="test")
assert clean_extra_whitespace(elements[0].text) == EXPECTED_TEXT
assert elements[0].metadata.filename == "test"
def test_partition_csv_can_exclude_metadata():
elements = partition_csv(example_doc_path("stanley-cups.csv"), include_metadata=False)
assert clean_extra_whitespace(elements[0].text) == EXPECTED_TEXT
assert isinstance(elements[0], Table)
assert elements[0].metadata.text_as_html is None
assert elements[0].metadata.filetype is None
assert elements[0].metadata.filename is None
# -- .metadata.last_modified ---------------------------------------------------------------------
def test_partition_csv_from_file_path_gets_last_modified_from_filesystem(mocker: MockFixture):
filesystem_last_modified = "2029-07-05T09:24:28"
mocker.patch(
"unstructured.partition.csv.get_last_modified_date",
return_value=filesystem_last_modified,
)
elements = partition_csv(example_doc_path("stanley-cups.csv"))
assert elements[0].metadata.last_modified == filesystem_last_modified
def test_partition_csv_from_file_path_prefers_metadata_last_modified(mocker: MockFixture):
filesystem_last_modified = "2029-07-05T09:24:28"
metadata_last_modified = "2020-07-05T09:24:28"
mocker.patch(
"unstructured.partition.csv.get_last_modified_date", return_value=filesystem_last_modified
)
elements = partition_csv(
example_doc_path("stanley-cups.csv"), metadata_last_modified=metadata_last_modified
)
assert elements[0].metadata.last_modified == metadata_last_modified
def test_partition_csv_from_file_gets_last_modified_None():
with open(example_doc_path("stanley-cups.csv"), "rb") as f:
elements = partition_csv(file=f)
assert elements[0].metadata.last_modified is None
def test_partition_csv_from_file_prefers_metadata_last_modified():
metadata_last_modified = "2020-07-05T09:24:28"
with open(example_doc_path("stanley-cups.csv"), "rb") as f:
elements = partition_csv(file=f, metadata_last_modified=metadata_last_modified)
assert elements[0].metadata.last_modified == metadata_last_modified
# ------------------------------------------------------------------------------------------------
@pytest.mark.parametrize("filename", ["stanley-cups.csv", "stanley-cups-with-emoji.csv"])
def test_partition_csv_with_json(filename: str):
elements = partition_csv(filename=example_doc_path(filename))
assert_round_trips_through_JSON(elements)
def test_add_chunking_strategy_to_partition_csv_non_default():
filename = "example-docs/stanley-cups.csv"
elements = partition_csv(filename=filename)
chunk_elements = partition_csv(
filename,
chunking_strategy="by_title",
max_characters=9,
combine_text_under_n_chars=0,
include_header=False,
)
chunks = chunk_by_title(elements, max_characters=9, combine_text_under_n_chars=0)
assert chunk_elements != elements
assert chunk_elements == chunks
# NOTE (jennings) partition_csv returns a single TableElement per sheet,
# so leaving off additional tests for multiple languages like the other partitions
def test_partition_csv_element_metadata_has_languages():
filename = "example-docs/stanley-cups.csv"
elements = partition_csv(filename=filename, strategy="fast", include_header=False)
assert elements[0].metadata.languages == ["eng"]
def test_partition_csv_respects_languages_arg():
filename = "example-docs/stanley-cups.csv"
elements = partition_csv(
filename=filename, strategy="fast", languages=["deu"], include_header=False
)
assert elements[0].metadata.languages == ["deu"]
def test_partition_csv_header():
elements = partition_csv(
example_doc_path("stanley-cups.csv"), strategy="fast", include_header=True
)
table = elements[0]
assert clean_extra_whitespace(table.text) == (
"Stanley Cups Unnamed: 1 Unnamed: 2 " + EXPECTED_TEXT_XLSX
)
assert table.metadata.text_as_html is not None
assert "<thead>" in table.metadata.text_as_html
# ================================================================================================
# UNIT-TESTS
# ================================================================================================
class Describe_CsvPartitioningContext:
"""Unit-test suite for `unstructured.partition.csv._CsvPartitioningContext`."""
# -- .load() ------------------------------------------------
def it_provides_a_validating_alternate_constructor(self):
ctx = _CsvPartitioningContext.load(
file_path=example_doc_path("stanley-cups.csv"),
file=None,
encoding=None,
metadata_file_path=None,
metadata_last_modified=None,
include_header=True,
infer_table_structure=True,
)
assert isinstance(ctx, _CsvPartitioningContext)
def and_the_validating_constructor_raises_on_an_invalid_context(self):
with pytest.raises(ValueError, match="either file-path or file-like object must be prov"):
_CsvPartitioningContext.load(
file_path=None,
file=None,
encoding=None,
metadata_file_path=None,
metadata_last_modified=None,
include_header=True,
infer_table_structure=True,
)
# -- .delimiter ---------------------------------------------
@pytest.mark.parametrize(
"file_name",
[
"stanley-cups.csv",
# -- Issue #2643: previously raised `_csv.Error: Could not determine delimiter` on
# -- this file
"csv-with-long-lines.csv",
],
)
def it_auto_detects_the_delimiter_for_a_comma_delimited_CSV_file(self, file_name: str):
ctx = _CsvPartitioningContext(example_doc_path(file_name))
assert ctx.delimiter == ","
def and_it_auto_detects_the_delimiter_for_a_semicolon_delimited_CSV_file(self):
ctx = _CsvPartitioningContext(example_doc_path("semicolon-delimited.csv"))
assert ctx.delimiter == ";"
def but_it_returns_None_as_the_delimiter_for_a_single_column_CSV_file(self):
ctx = _CsvPartitioningContext(example_doc_path("single-column.csv"))
assert ctx.delimiter is None
# -- .header ------------------------------------------------
@pytest.mark.parametrize(("include_header", "expected_value"), [(False, None), (True, 0)])
def it_identifies_the_header_row_based_on_include_header_arg(
self, include_header: bool, expected_value: int | None
):
assert _CsvPartitioningContext(include_header=include_header).header == expected_value
# -- .last_modified --------------------------
def it_gets_the_last_modified_date_of_the_document_from_the_caller_when_provided(self):
ctx = _CsvPartitioningContext(metadata_last_modified="2024-08-04T13:12:35")
assert ctx.last_modified == "2024-08-04T13:12:35"
def and_it_falls_back_to_the_last_modified_date_of_the_file_when_a_path_is_provided(
self, get_last_modified_date_: Mock
):
get_last_modified_date_.return_value = "2024-08-04T02:23:53"
ctx = _CsvPartitioningContext(file_path="a/b/document.csv")
last_modified = ctx.last_modified
get_last_modified_date_.assert_called_once_with("a/b/document.csv")
assert last_modified == "2024-08-04T02:23:53"
def and_it_falls_back_to_None_for_the_last_modified_date_when_file_path_is_not_provided(self):
file = io.BytesIO(b"abcdefg")
ctx = _CsvPartitioningContext(file=file)
last_modified = ctx.last_modified
assert last_modified is None
# -- .open() ------------------------------------------------
def it_provides_transparent_access_to_the_source_file_when_it_is_a_file_like_object(self):
with open(example_doc_path("stanley-cups.csv"), "rb") as f:
# -- read so file cursor is at end of file --
f.read()
ctx = _CsvPartitioningContext(file=f)
with ctx.open() as file:
assert file is f
# -- read cursor is reset to 0 on .open() context entry --
assert f.tell() == 0
assert file.read(14) == b"Stanley Cups,,"
assert f.tell() == 14
# -- and read cursor is reset to 0 on .open() context exit --
assert f.tell() == 0
def it_provides_transparent_access_to_the_source_file_when_it_is_a_file_path(self):
ctx = _CsvPartitioningContext(example_doc_path("stanley-cups.csv"))
with ctx.open() as file:
assert file.read(14) == b"Stanley Cups,,"
# -- .validate() --------------------------------------------
def it_raises_when_neither_file_path_nor_file_is_provided(self):
with pytest.raises(ValueError, match="either file-path or file-like object must be prov"):
_CsvPartitioningContext()._validate()
# -- fixtures --------------------------------------------------------------------------------
@pytest.fixture()
def get_last_modified_date_(self, request: FixtureRequest) -> Mock:
return function_mock(request, "unstructured.partition.csv.get_last_modified_date")