Roman Isecke 2e1404e02c
refactor: unstructured ingest as a pipeline (#1551)
### Description
As we add more and more steps to the pipeline (i.e. chunking, embedding,
table manipulation), it would help seperate the responsibility of each
of these into their own processes, running each in parallel using json
files to share data across. This will also help guarantee data is
serializable if this code was used in an actual pipeline. Following is a
flow diagram of the proposed changes. As part of this change:
* A parent pipeline class will be responsible for running each `node`,
which can optionally be run via multiprocessing if it supports it, or
not. Possible nodes at this moment:
  * Doc factory: creates all the ingest docs via the source connector
* Source: reads/downloads all of the content to process to the local
filesystem to the location set by the `download_dir` parameter.
* Partition: runs partition on all of the downloaded content in json
format.
* Any number of reformat nodes that modify the partitioned content. This
can include chunking, embedding, etc.
* Write: push the final json into the destination via the destination
connector
* This pipeline relies on the information of the ingest docs to be
available via their serialization. An optimization was introduced with
the `IngestDocJsonMixin` which adds in all the `@property` fields to the
serialized json already being created via the `DataClassJsonMixin`
* For all intermediate steps (partitioning, reformatting), the content
is saved to a dedicated location on the local filesystem. Right now it's
set to `$HOME/.cache/unstructured/ingest/pipeline/STEP_NAME/`.
* Minor changes: made sense to move some of the config parameters
between the read and partition configs when I explicitly divided the
responsibility to download vs partition the content in the pipeline.
* The pipeline class only makes the doc factory, source and partition
nodes required, keeping with the logic that has been supported so far.
All reformatting nodes and write node are optional.
* Long term, there should also be some changes to the base configs
supported by the CLI to support pipeline specific configs, but for now
what exists was used to minimize changes in this PR.
* Final step to copy the final output to the location designated by the
`_output_filename` value of the ingest doc.
* Hashing occurs at each step by hashing the parameters of that step
(i.e. partition configs) along with the previous step via the filename
used. This allows each step to be the same _if_ all the parameters for
it have not changed and the content so far is the same.
* The only data that is shared and has writes to across processes is the
dictionary of ingest json data. This dict is created using the
`multiprocessing.manager.DictProxy` to make sure any interaction with it
is behind a lock.

### Minor refactors included:
* Utility methods added to extract configs from the click options
* Utility method to add common options to click commands.
* All writers moved to using the class approach which extracts a lot of
the common code so there's less copy-paste when new runners are added.
* Use `@property` for source metadata on base ingest doc to add logic to
call `update_source_metadata` if it's still `None` at the time it's
fetched.


### Additional bug fixes included
* Fsspec connectors were not serializable due to the `ingest_doc_cls`.
This was removed from the fields captured by the `@dataclass` decorator
and added in a `__post_init__` method.
* Various reddit connector params were missing. This doesn't have an
explicit ingest test at the moment so was never caught.
* Fsspec connector had the parent `update_source_metadata` misnamed as
`update_source_metadata_metadata` so it was never being called.

### Flow Diagram


![ingest_pipeline](https://github.com/Unstructured-IO/unstructured/assets/136338424/be485606-cfe0-4931-8b81-c2bf569cf1e2)
2023-10-06 18:49:29 +00:00

258 lines
8.4 KiB
Python

import os
import pathlib
from dataclasses import dataclass
from typing import Any, Dict
import pytest
from unstructured.documents.elements import DataSourceMetadata
from unstructured.ingest.interfaces import (
BaseConnectorConfig,
BaseIngestDoc,
PartitionConfig,
ProcessorConfig,
ReadConfig,
)
from unstructured.partition.auto import partition
from unstructured.staging.base import convert_to_dict
DIRECTORY = pathlib.Path(__file__).parent.resolve()
EXAMPLE_DOCS_DIRECTORY = os.path.join(DIRECTORY, "../..", "example-docs")
TEST_DOWNLOAD_DIR = "/tmp"
TEST_OUTPUT_DIR = "/tmp"
TEST_ID = "test"
TEST_FILE_PATH = os.path.join(EXAMPLE_DOCS_DIRECTORY, "book-war-and-peace-1p.txt")
@dataclass
class TestConfig(BaseConnectorConfig):
id: str
path: str
TEST_CONFIG = TestConfig(id=TEST_ID, path=TEST_FILE_PATH)
TEST_SOURCE_URL = "test-source-url"
TEST_VERSION = "1.1.1"
TEST_RECORD_LOCATOR = {"id": "data-source-id"}
TEST_DATE_CREATED = "2021-01-01T00:00:00"
TEST_DATE_MODIFIED = "2021-01-02T00:00:00"
TEST_DATE_PROCESSSED = "2022-12-13T15:44:08"
@dataclass
class TestIngestDoc(BaseIngestDoc):
connector_config: TestConfig
@property
def filename(self):
return TEST_FILE_PATH
@property
def _output_filename(self):
return TEST_FILE_PATH + ".json"
@property
def source_url(self) -> str:
return TEST_SOURCE_URL
@property
def version(self) -> str:
return TEST_VERSION
@property
def record_locator(self) -> Dict[str, Any]:
return TEST_RECORD_LOCATOR
@property
def date_created(self) -> str:
return TEST_DATE_CREATED
@property
def date_modified(self) -> str:
return TEST_DATE_MODIFIED
@property
def exists(self) -> bool:
return True
def cleanup_file(self):
pass
def get_file(self):
pass
def has_output(self):
return True
def write_result(self, result):
pass
@pytest.fixture()
def partition_test_results():
# Reusable partition test results, calculated only once
result = partition(
filename=str(TEST_FILE_PATH),
data_source_metadata=DataSourceMetadata(
url=TEST_SOURCE_URL,
version=TEST_VERSION,
record_locator=TEST_RECORD_LOCATOR,
date_created=TEST_DATE_CREATED,
date_modified=TEST_DATE_MODIFIED,
date_processed=TEST_DATE_PROCESSSED,
),
)
return result
@pytest.fixture()
def partition_file_test_results(partition_test_results):
# Reusable partition_file test results, calculated only once
return convert_to_dict(partition_test_results)
def test_partition_file():
"""Validate partition_file returns a list of dictionaries with the expected keys,
metadatakeys, and data source metadata values."""
test_ingest_doc = TestIngestDoc(
connector_config=TEST_CONFIG,
read_config=ReadConfig(download_dir=TEST_DOWNLOAD_DIR),
processor_config=ProcessorConfig(output_dir=TEST_OUTPUT_DIR),
)
test_ingest_doc._date_processed = TEST_DATE_PROCESSSED
isd_elems_raw = test_ingest_doc.partition_file(partition_config=PartitionConfig())
isd_elems = convert_to_dict(isd_elems_raw)
assert len(isd_elems)
expected_keys = {
"element_id",
"text",
"type",
"metadata",
}
# The document in TEST_FILE_PATH does not have elements with coordinates so
# partition is not expected to return coordinates metadata.
expected_metadata_keys = {
"data_source",
"filename",
"file_directory",
"filetype",
"languages",
"last_modified",
}
for elem in isd_elems:
# Parent IDs are non-deterministic - remove them from the test
elem["metadata"].pop("parent_id", None)
assert expected_keys == set(elem.keys())
assert expected_metadata_keys == set(elem["metadata"].keys())
data_source_metadata = elem["metadata"]["data_source"]
assert data_source_metadata["url"] == TEST_SOURCE_URL
assert data_source_metadata["version"] == TEST_VERSION
assert data_source_metadata["record_locator"] == TEST_RECORD_LOCATOR
assert data_source_metadata["date_created"] == TEST_DATE_CREATED
assert data_source_metadata["date_modified"] == TEST_DATE_MODIFIED
assert data_source_metadata["date_processed"] == TEST_DATE_PROCESSSED
def test_process_file_fields_include_default(mocker, partition_test_results):
"""Validate when metadata_include and metadata_exclude are not set, all fields:
("element_id", "text", "type", "metadata") are included"""
mock_partition = mocker.patch(
"unstructured.ingest.interfaces.partition",
return_value=partition_test_results,
)
test_ingest_doc = TestIngestDoc(
connector_config=TEST_CONFIG,
read_config=ReadConfig(download_dir=TEST_DOWNLOAD_DIR),
processor_config=ProcessorConfig(output_dir=TEST_OUTPUT_DIR),
)
isd_elems_raw = test_ingest_doc.partition_file(partition_config=PartitionConfig())
isd_elems = convert_to_dict(isd_elems_raw)
assert len(isd_elems)
assert mock_partition.call_count == 1
for elem in isd_elems:
# Parent IDs are non-deterministic - remove them from the test
elem["metadata"].pop("parent_id", None)
assert {"element_id", "text", "type", "metadata"} == set(elem.keys())
data_source_metadata = elem["metadata"]["data_source"]
assert data_source_metadata["url"] == TEST_SOURCE_URL
assert data_source_metadata["version"] == TEST_VERSION
assert data_source_metadata["record_locator"] == TEST_RECORD_LOCATOR
assert data_source_metadata["date_created"] == TEST_DATE_CREATED
assert data_source_metadata["date_modified"] == TEST_DATE_MODIFIED
assert data_source_metadata["date_processed"] == TEST_DATE_PROCESSSED
def test_process_file_metadata_includes_filename_and_filetype(
mocker,
partition_test_results,
):
"""Validate when metadata_include is set to "filename,filetype",
only filename is included in metadata"""
mocker.patch(
"unstructured.ingest.interfaces.partition",
return_value=partition_test_results,
)
partition_config = PartitionConfig(
metadata_include=["filename", "filetype"],
)
test_ingest_doc = TestIngestDoc(
connector_config=TEST_CONFIG,
read_config=ReadConfig(download_dir=TEST_DOWNLOAD_DIR),
processor_config=ProcessorConfig(output_dir=TEST_OUTPUT_DIR),
)
isd_elems = test_ingest_doc.process_file(partition_config=partition_config)
assert len(isd_elems)
for elem in isd_elems:
# Parent IDs are non-deterministic - remove them from the test
elem["metadata"].pop("parent_id", None)
assert set(elem["metadata"].keys()) == {"filename", "filetype"}
def test_process_file_metadata_exclude_filename_pagenum(mocker, partition_test_results):
"""Validate when metadata_exclude is set to "filename,page_number",
neither filename nor page_number are included in metadata"""
mocker.patch(
"unstructured.ingest.interfaces.partition",
return_value=partition_test_results,
)
partition_config = PartitionConfig(
metadata_exclude=["filename", "page_number"],
)
test_ingest_doc = TestIngestDoc(
connector_config=TEST_CONFIG,
read_config=ReadConfig(download_dir=TEST_DOWNLOAD_DIR),
processor_config=ProcessorConfig(
output_dir=TEST_OUTPUT_DIR,
),
)
isd_elems = test_ingest_doc.process_file(partition_config=partition_config)
assert len(isd_elems)
for elem in isd_elems:
assert "filename" not in elem["metadata"]
assert "page_number" not in elem["metadata"]
def test_process_file_flatten_metadata(mocker, partition_test_results):
mocker.patch(
"unstructured.ingest.interfaces.partition",
return_value=partition_test_results,
)
partition_config = PartitionConfig(
metadata_include=["filename", "data_source"],
flatten_metadata=True,
)
test_ingest_doc = TestIngestDoc(
connector_config=TEST_CONFIG,
read_config=ReadConfig(download_dir=TEST_DOWNLOAD_DIR),
processor_config=ProcessorConfig(
output_dir=TEST_OUTPUT_DIR,
),
)
isd_elems = test_ingest_doc.process_file(partition_config=partition_config)
expected_keys = {"element_id", "text", "type", "filename", "data_source"}
for elem in isd_elems:
assert expected_keys == set(elem.keys())