2023-07-25 21:09:26 -07:00
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from dataclasses import dataclass
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from pathlib import Path
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2024-01-04 13:33:16 -06:00
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import pytest
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2023-12-11 12:37:49 -05:00
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from unstructured.ingest.connector.fsspec.dropbox import (
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2023-07-25 21:09:26 -07:00
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DropboxIngestDoc,
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)
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2023-12-11 12:37:49 -05:00
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from unstructured.ingest.connector.fsspec.fsspec import (
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2023-07-25 21:09:26 -07:00
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FsspecIngestDoc,
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)
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2024-01-04 13:33:16 -06:00
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from unstructured.ingest.connector.fsspec.sftp import SftpAccessConfig, SimpleSftpConfig
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from unstructured.ingest.interfaces import (
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FsspecConfig,
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)
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2023-07-25 21:09:26 -07:00
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@dataclass
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class FakeConfigDropboxRoot:
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output_dir = "/fakeuser/fake_output"
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dir_path = " "
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download_dir = "/fakeuser/fake_download"
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2023-11-28 09:19:42 -05:00
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path_without_protocol = " "
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2023-07-25 21:09:26 -07:00
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@dataclass
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class FakeConfigFolder:
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output_dir = "/fakeuser/fake_output"
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dir_path = "fake_folder"
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download_dir = "/fakeuser/fake_download"
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2023-11-28 09:19:42 -05:00
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path_without_protocol = "fake_folder"
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2023-07-25 21:09:26 -07:00
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def test_dropbox_root_succeeds():
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2023-09-11 11:40:56 -04:00
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"""
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Test that path joining method works for Dropbox root folder.
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Note slash in front of remote_file_path.
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"""
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2023-07-25 21:09:26 -07:00
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dbox = DropboxIngestDoc(
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2023-09-11 11:40:56 -04:00
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connector_config=FakeConfigDropboxRoot,
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read_config=FakeConfigDropboxRoot,
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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

2023-10-06 14:49:29 -04:00
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processor_config=FakeConfigDropboxRoot,
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2023-07-25 21:09:26 -07:00
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remote_file_path="/fake_file.txt",
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)
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output_filename = dbox._output_filename
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download_filename = dbox._tmp_download_file()
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assert output_filename == Path("/fakeuser/fake_output/fake_file.txt.json")
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assert download_filename == Path("/fakeuser/fake_download/fake_file.txt")
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def test_dropbox_root_succeeds2():
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2023-09-11 11:40:56 -04:00
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"""
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Test that path joining method works for Dropbox root folder.
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Note lack of slash in front of remote_file_path. This still works.
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"""
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2023-07-25 21:09:26 -07:00
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dbox = DropboxIngestDoc(
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2023-09-11 11:40:56 -04:00
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connector_config=FakeConfigDropboxRoot,
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read_config=FakeConfigDropboxRoot,
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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

2023-10-06 14:49:29 -04:00
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processor_config=FakeConfigDropboxRoot,
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2023-07-25 21:09:26 -07:00
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remote_file_path="fake_file.txt",
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)
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output_filename = dbox._output_filename
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download_filename = dbox._tmp_download_file()
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assert output_filename == Path("/fakeuser/fake_output/fake_file.txt.json")
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assert download_filename == Path("/fakeuser/fake_download/fake_file.txt")
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def test_dropbox_folder_succeeds():
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2023-09-11 11:40:56 -04:00
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"""
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Test that path joining method works for Dropbox root folder.
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Note no slash in front of remote_file_path.
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"""
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2023-07-25 21:09:26 -07:00
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dbox = DropboxIngestDoc(
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2023-09-11 11:40:56 -04:00
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connector_config=FakeConfigFolder,
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read_config=FakeConfigFolder,
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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

2023-10-06 14:49:29 -04:00
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processor_config=FakeConfigFolder,
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2023-07-25 21:09:26 -07:00
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remote_file_path="fake_file2.txt",
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)
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output_filename = dbox._output_filename
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download_filename = dbox._tmp_download_file()
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assert output_filename == Path("/fakeuser/fake_output/fake_file2.txt.json")
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assert download_filename == Path("/fakeuser/fake_download/fake_file2.txt")
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def test_dropbox_folder_fails():
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2023-09-11 11:40:56 -04:00
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"""Test that path joining method gives WRONG path. Note slash in front of remote_file_path.
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2023-07-25 21:09:26 -07:00
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Path joining is sensitive. Note that the path is MISSING the folders."""
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dbox = DropboxIngestDoc(
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2023-09-11 11:40:56 -04:00
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connector_config=FakeConfigFolder,
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read_config=FakeConfigFolder,
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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

2023-10-06 14:49:29 -04:00
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processor_config=FakeConfigFolder,
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2023-07-25 21:09:26 -07:00
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remote_file_path="/fake_file2.txt",
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)
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output_filename = dbox._output_filename
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download_filename = dbox._tmp_download_file()
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assert output_filename == Path("/fake_file2.txt.json")
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assert download_filename == Path("/fake_file2.txt")
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def test_fsspec_folder_succeeds():
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2023-09-11 11:40:56 -04:00
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"""
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Test that path joining method works for root folder.
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Note no slash in front of remote_file_path.
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"""
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2023-07-25 21:09:26 -07:00
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dbox = FsspecIngestDoc(
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2023-09-11 11:40:56 -04:00
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connector_config=FakeConfigFolder,
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read_config=FakeConfigFolder,
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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

2023-10-06 14:49:29 -04:00
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processor_config=FakeConfigFolder,
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2023-07-25 21:09:26 -07:00
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remote_file_path="fake_file2.txt",
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)
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output_filename = dbox._output_filename
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download_filename = dbox._tmp_download_file()
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assert output_filename == Path("/fakeuser/fake_output/fake_file2.txt.json")
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assert download_filename == Path("/fakeuser/fake_download/fake_file2.txt")
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def test_fsspec_folder_fails():
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2023-09-11 11:40:56 -04:00
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"""Test that path joining method gives WRONG path. Note slash in front of remote_file_path.
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2023-07-25 21:09:26 -07:00
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Path joining is sensitive. Note that the path is MISSING the folders."""
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fstest = FsspecIngestDoc(
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2023-09-11 11:40:56 -04:00
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connector_config=FakeConfigFolder,
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read_config=FakeConfigFolder,
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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

2023-10-06 14:49:29 -04:00
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processor_config=FakeConfigFolder,
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2023-07-25 21:09:26 -07:00
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remote_file_path="/fake_file2.txt",
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)
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output_filename = fstest._output_filename
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download_filename = fstest._tmp_download_file()
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assert output_filename == Path("/fake_file2.txt.json")
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2023-09-11 11:40:56 -04:00
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assert download_filename == Path("/fake_file2.txt")
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2024-01-04 13:33:16 -06:00
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def test_post_init_invalid_protocol():
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"""Validate that an invalid protocol raises a ValueError"""
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with pytest.raises(ValueError):
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FsspecConfig(remote_url="ftp://example.com/path/to/file.txt")
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def test_fsspec_path_extraction_dropbox_root():
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"""Validate that the path extraction works for dropbox root"""
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config = FsspecConfig(remote_url="dropbox:// /")
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assert config.protocol == "dropbox"
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assert config.path_without_protocol == " /"
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assert config.dir_path == " "
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assert config.file_path == ""
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def test_fsspec_path_extraction_dropbox_subfolder():
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"""Validate that the path extraction works for dropbox subfolder"""
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config = FsspecConfig(remote_url="dropbox://path")
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assert config.protocol == "dropbox"
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assert config.path_without_protocol == "path"
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assert config.dir_path == "path"
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assert config.file_path == ""
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def test_fsspec_path_extraction_s3_bucket_only():
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"""Validate that the path extraction works for s3 bucket without filename"""
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config = FsspecConfig(remote_url="s3://bucket-name")
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assert config.protocol == "s3"
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assert config.path_without_protocol == "bucket-name"
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assert config.dir_path == "bucket-name"
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assert config.file_path == ""
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def test_fsspec_path_extraction_s3_valid_path():
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"""Validate that the path extraction works for s3 bucket with filename"""
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config = FsspecConfig(remote_url="s3://bucket-name/path/to/file.txt")
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assert config.protocol == "s3"
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assert config.path_without_protocol == "bucket-name/path/to/file.txt"
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assert config.dir_path == "bucket-name"
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assert config.file_path == "path/to/file.txt"
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def test_fsspec_path_extraction_s3_invalid_path():
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"""Validate that an invalid s3 path (that mimics triple slash for dropbox)
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raises a ValueError"""
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with pytest.raises(ValueError):
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FsspecConfig(remote_url="s3:///bucket-name/path/to")
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def test_sftp_path_extraction_post_init_with_extension():
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"""Validate that the path extraction works for sftp with file extension"""
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config = SimpleSftpConfig(
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remote_url="sftp://example.com/path/to/file.txt",
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access_config=SftpAccessConfig(username="username", password="password", host="", port=22),
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)
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assert config.file_path == "file.txt"
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assert config.dir_path == "path/to"
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assert config.path_without_protocol == "path/to"
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assert config.access_config.host == "example.com"
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assert config.access_config.port == 22
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def test_sftp_path_extraction_without_extension():
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"""Validate that the path extraction works for sftp without extension"""
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config = SimpleSftpConfig(
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remote_url="sftp://example.com/path/to/directory",
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access_config=SftpAccessConfig(username="username", password="password", host="", port=22),
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)
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assert config.file_path == ""
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assert config.dir_path == "path/to/directory"
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assert config.path_without_protocol == "path/to/directory"
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assert config.access_config.host == "example.com"
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assert config.access_config.port == 22
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def test_sftp_path_extraction_with_port():
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"""Validate that the path extraction works for sftp with a non-default port"""
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config = SimpleSftpConfig(
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remote_url="sftp://example.com:47474/path/to/file.txt",
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access_config=SftpAccessConfig(username="username", password="password", host="", port=22),
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)
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assert config.file_path == "file.txt"
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assert config.dir_path == "path/to"
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assert config.path_without_protocol == "path/to"
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assert config.access_config.host == "example.com"
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assert config.access_config.port == 47474
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