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This updates the docker image download url to pass through the scarf gateway, this allows anonymous tracking of downloads Related to: https://github.com/Unstructured-IO/unstructured#chart_with_upwards_trend-analytics Testing: docker pull downloads.unstructured.io/unstructured-io/unstructured:latest Result: Image should download
62 lines
2.4 KiB
ReStructuredText
62 lines
2.4 KiB
ReStructuredText
Docker Installation
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=======================================
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The instructions below guide you on how to use the `unstructured` library inside a Docker container.
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Prerequisites
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-------------
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If you haven't installed Docker on your machine, you can find the installation guide `here <link_to_docker_installation>`_.
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.. note::
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We build multi-platform images to support both x86_64 and Apple silicon hardware. Using `docker pull` should download the appropriate image for your architecture. However, if needed, you can specify the platform with the `--platform` flag, e.g., `--platform linux/amd64`.
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Pulling the Docker Image
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-------------------------
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We create Docker images for every push to the main branch. These images are tagged with the respective short commit hash (like `fbc7a69`) and the application version (e.g., `0.5.5-dev1`). The most recent image also receives the `latest` tag. To use these images, pull them from our repository:
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.. code-block:: bash
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docker pull downloads.unstructured.io/unstructured-io/unstructured:latest
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Using the Docker Image
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----------------------
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After pulling the image, you can create and start a container from it:
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.. code-block:: bash
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# create the container
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docker run -dt --name unstructured downloads.unstructured.io/unstructured-io/unstructured:latest
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# start a bash shell inside the running Docker container
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docker exec -it unstructured bash
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Building Your Own Docker Image
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------------------------------
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You can also build your own Docker image. If you only plan to parse a single type of data, you can accelerate the build process by excluding certain packages or requirements needed for other data types. Refer to the `Dockerfile` to determine which lines are necessary for your requirements.
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.. code-block:: bash
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make docker-build
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# start a bash shell inside the running Docker container
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make docker-start-bash
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Interacting with Python Inside the Container
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--------------------------------------------
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Once inside the running Docker container, you can directly test the library using Python's interactive mode:
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.. code-block:: python
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python3
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>>> from unstructured.partition.pdf import partition_pdf
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>>> elements = partition_pdf(filename="example-docs/layout-parser-paper-fast.pdf")
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>>> from unstructured.partition.text import partition_text
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>>> elements = partition_text(filename="example-docs/fake-text.txt")
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