Python SDK for the Unstructured API
This is a Python client for the [Unstructured API](https://docs.unstructured.io/api-reference/api-services/overview). Please refer to the [Unstructured docs](https://docs.unstructured.io/api-reference/api-services/sdk) for a full guide to using the client. ## SDK Installation ```bash pip install unstructured-client ``` ## SDK Example Usage ### Example ```python import os import unstructured_client from unstructured_client.models import operations, shared client = unstructured_client.UnstructuredClient( api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"), server_url=os.getenv("UNSTRUCTURED_API_URL"), ) filename = "PATH_TO_FILE" with open(filename, "rb") as f: data = f.read() req = operations.PartitionRequest( partition_parameters=shared.PartitionParameters( files=shared.Files( content=data, file_name=filename, ), # --- Other partition parameters --- strategy=shared.Strategy.AUTO, languages=['eng'], ), ) try: res = client.general.partition(request=req) print(res.elements[0]) except Exception as e: print(e) ``` Refer to the [API parameters page](https://docs.unstructured.io/api-reference/api-services/api-parameters) for all available parameters. ### Configuration #### Splitting PDF by pages See [page splitting](https://docs.unstructured.io/api-reference/api-services/sdk#page-splitting) for more details. In order to speed up processing of large PDF files, the client splits up PDFs into smaller files, sends these to the API concurrently, and recombines the results. `split_pdf_page` can be set to `False` to disable this. The amount of workers utilized for splitting PDFs is dictated by the `split_pdf_concurrency_level` parameter, with a default of 5 and a maximum of 15 to keep resource usage and costs in check. The splitting process leverages `asyncio` to manage concurrency effectively. The size of each batch of pages (ranging from 2 to 20) is internally determined based on the concurrency level and the total number of pages in the document. Because the splitting process uses `asyncio` the client can encouter event loop issues if it is nested in another async runner, like running in a `gevent` spawned task. Instead, this is safe to run in multiprocessing workers (e.g., using `multiprocessing.Pool` with `fork` context). Example: ```python req = shared.PartitionParameters( files=files, strategy="fast", languages=["eng"], split_pdf_concurrency_level=8 ) ``` #### Sending specific page ranges When `split_pdf_page=True` (the default), you can optionally specify a page range to send only a portion of your PDF to be extracted. The parameter takes a list of two integers to specify the range, inclusive. A ValueError is thrown if the page range is invalid. Example: ```python req = shared.PartitionParameters( files=files, strategy="fast", languages=["eng"], split_pdf_page_range=[10,15], ) ``` #### Splitting PDF by pages - strict mode When `split_pdf_allow_failed=False` (the default), any errors encountered during sending parallel request will break the process and raise an exception. When `split_pdf_allow_failed=True`, the process will continue even if some requests fail, and the results will be combined at the end (the output from the errored pages will not be included). Example: ```python req = shared.PartitionParameters( files=files, strategy="fast", languages=["eng"], split_pdf_allow_failed=True, ) ``` ## Retries Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK. To change the default retry strategy for a single API call, simply provide a `RetryConfig` object to the call: ```python import unstructured_client from unstructured_client.models import operations, shared from unstructured_client.utils import BackoffStrategy, RetryConfig s = unstructured_client.UnstructuredClient() res = s.general.partition(request=operations.PartitionRequest( partition_parameters=shared.PartitionParameters( files=shared.Files( content='0x2cC94b2FEF'.encode(), file_name='your_file_here', ), chunking_strategy=shared.ChunkingStrategy.BY_TITLE, split_pdf_page_range=[ 1, 10, ], strategy=shared.Strategy.HI_RES, ), ), RetryConfig('backoff', BackoffStrategy(1, 50, 1.1, 100), False)) if res.elements is not None: # handle response pass ``` If you'd like to override the default retry strategy for all operations that support retries, you can use the `retry_config` optional parameter when initializing the SDK: ```python import unstructured_client from unstructured_client.models import operations, shared from unstructured_client.utils import BackoffStrategy, RetryConfig s = unstructured_client.UnstructuredClient( retry_config=RetryConfig('backoff', BackoffStrategy(1, 50, 1.1, 100), False), ) res = s.general.partition(request=operations.PartitionRequest( partition_parameters=shared.PartitionParameters( files=shared.Files( content='0x2cC94b2FEF'.encode(), file_name='your_file_here', ), chunking_strategy=shared.ChunkingStrategy.BY_TITLE, split_pdf_page_range=[ 1, 10, ], strategy=shared.Strategy.HI_RES, ), )) if res.elements is not None: # handle response pass ``` ## Custom HTTP Client The Python SDK makes API calls using the [requests](https://pypi.org/project/requests/) HTTP library. In order to provide a convenient way to configure timeouts, cookies, proxies, custom headers, and other low-level configuration, you can initialize the SDK client with a custom `requests.Session` object. For example, you could specify a header for every request that this sdk makes as follows: ```python import unstructured_client import requests http_client = requests.Session() http_client.headers.update({'x-custom-header': 'someValue'}) s = unstructured_client.UnstructuredClient(client=http_client) ``` ### Maturity This SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning usage to a specific package version. This way, you can install the same version each time without breaking changes unless you are intentionally looking for the latest version. ### Installation Instructions for Local Development The following instructions are intended to help you get up and running with `unstructured-python-client` locally if you are planning to contribute to the project. * Using `pyenv` to manage virtualenv's is recommended but not necessary * Mac install instructions. See [here](https://github.com/Unstructured-IO/community#mac--homebrew) for more detailed instructions. * `brew install pyenv-virtualenv` * `pyenv install 3.10` * Linux instructions are available [here](https://github.com/Unstructured-IO/community#linux). * Create a virtualenv to work in and activate it, e.g. for one named `unstructured-python-client`: `pyenv virtualenv 3.10 unstructured-python-client` `pyenv activate unstructured-python-client` * Run `make install` and `make test` ### Contributions While we value open-source contributions to this SDK, this library is generated programmatically by Speakeasy. In order to start working with this repo, you need to: 1. Install Speakeasy client locally https://github.com/speakeasy-api/speakeasy#installation 2. Run `speakeasy auth login` 3. Run `make client-generate`. This allows to iterate development with python client. There are two important files used by `make client-generate`: 1. `openapi.json` which is actually not stored here, [but fetched from unstructured-api](https://api.unstructured.io/general/openapi.json), represents the API that is supported on backend. 2. `overlay_client.yaml` is a handcrafted diff that when applied over above, produces `openapi_client.json` which is used to generate SDK. Once PR with changes is merged, Github CI will autogenerate the Speakeasy client in a new PR, using the `openapi.json` and `overlay_client.yaml` You will have to manually bring back the human created lines in it. Feel free to open a PR or a Github issue as a proof of concept and we'll do our best to include it in a future release! ### SDK Created by [Speakeasy](https://www.speakeasyapi.dev/docs/sdk-design/python/methodology-python)