​
Task

You want to get, and print or save, the contents of elements that have been chunked.

​
Approach

Chunked elements are typically represented in this format:

{
  "type": "CompositeElement",
  "element_id": "3800f7ff047e97cbf0a5f7df7ad52c80",
  "text": "4,5 Exception noted in \u201cSpecial Considerations for Promotional Labeling and Advertising Material\u201d\n\n3",
  "metadata": {
    "filetype": "application/pdf",
    "languages": ["eng"],
    "page_number": 6,
    "orig_elements": "eJy ... Full content omitted for brevity ... x8=",
    "filename": "Portable-Document-Format-Specifications.pdf"
  }
}

{
  "type": "Table",
  "element_id": "758127b42c51b93b59abf08640d1ccab",
  "text": "Gels and karyotypes High pressure liquid chromatography 600 dpi (8 bit grayscale depth) 300 dpi",
  "metadata": {
    "text_as_html": "<table><tbody><tr><td>Gels and karyotypes</td><td>600 dpi (8 bit grayscale depth)</td></tr><tr><td>High pressure liquid chromatography</td><td>300</td></tr></tbody></table>",
    "filetype": "application/pdf",
    "languages": ["eng"],
    "page_number": 8,
    "orig_elements": "eJy ... Full content omitted for brevity ... MnD",
    "filename": "Portable-Document-Format-Specifications.pdf"
}

To get the element’s chunked content, extract the contents of the element’s text field.

The chunked content might not contain all of its associated content. To get all of the elements that were used to derive this chunked content, extract the contents of the element’s orig_elements field, which is nested inside of its parent metadata field.

The contents of the orig_elements field is in compressed Base64 gzipped format. To get the content, Base64-decode the bytes, decompress them, and then decode them using UTF-8.

​
To run this example

You will need to chunk a document during processing. This example uses a PDF file chunked into 200- to 300-character elements.

​
Code

For the Unstructured Ingest Python library, you can use the standard Python json.load function to load into a Python dictionary the contents of a JSON file that the Ingest Python library outputs after the processing is complete.

Python
import json, base64, zlib
from typing import List, Dict, Any

# Extract the contents of an orig_elements field.
def extract_orig_elements(orig_elements):
    decoded_orig_elements = base64.b64decode(orig_elements)
    decompressed_orig_elements = zlib.decompress(decoded_orig_elements)
    return decompressed_orig_elements.decode('utf-8')

def get_chunked_elements(input_json_file_path: str) -> List[Dict[str, Any]]:
    # Create a dictionary that will hold only
    # a transposed version of the returned elements. 
    # For instance, we just want to capture each element's ID,
    # the chunk's text, and the chunk's associated elements in context.
    orig_elements_dict: List[Dict[str, Any]] = []

    with open(input_json_file_path, 'r') as file:
        file_elements = json.load(file)

    for element in file_elements:
        # For each chunk that has an "orig_elements" field...
        if "orig_elements" in element["metadata"]:
            # ...get the chunk's associated elements in context...
            orig_elements = extract_orig_elements(element["metadata"]["orig_elements"])
            # ...and then transpose it and other associated fields into a separate dictionary.
            orig_elements_dict.append({
                "element_id": element["element_id"],
                "text": element["text"],
                "orig_elements": json.loads(orig_elements)
            })
    
    return orig_elements_dict

if __name__ == "__main__":
    # Source file: https://www.fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf
    input_filepath = "local-ingest-output-json/Portable-Document-Format-Specifications.json"
    output_filepath = "local-ingest-output-orig/Portable-Document-Format-Specifications-Orig-Elements-Only.json"

    orig_elements_dict = get_chunked_elements(input_json_file_path = input_filepath)

    # Convert the elements into a JSON object.
    orig_elements_json = json.dumps(orig_elements_dict, indent=2)

    # Write the JSON to a file.
    with open(output_filepath, "w") as file:
        file.write(orig_elements_json)

​
See also

​
Task

You want to get, and print or save, the contents of elements that have been chunked.

​
Approach

Chunked elements are typically represented in this format:

{
  "type": "CompositeElement",
  "element_id": "3800f7ff047e97cbf0a5f7df7ad52c80",
  "text": "4,5 Exception noted in \u201cSpecial Considerations for Promotional Labeling and Advertising Material\u201d\n\n3",
  "metadata": {
    "filetype": "application/pdf",
    "languages": ["eng"],
    "page_number": 6,
    "orig_elements": "eJy ... Full content omitted for brevity ... x8=",
    "filename": "Portable-Document-Format-Specifications.pdf"
  }
}

{
  "type": "Table",
  "element_id": "758127b42c51b93b59abf08640d1ccab",
  "text": "Gels and karyotypes High pressure liquid chromatography 600 dpi (8 bit grayscale depth) 300 dpi",
  "metadata": {
    "text_as_html": "<table><tbody><tr><td>Gels and karyotypes</td><td>600 dpi (8 bit grayscale depth)</td></tr><tr><td>High pressure liquid chromatography</td><td>300</td></tr></tbody></table>",
    "filetype": "application/pdf",
    "languages": ["eng"],
    "page_number": 8,
    "orig_elements": "eJy ... Full content omitted for brevity ... MnD",
    "filename": "Portable-Document-Format-Specifications.pdf"
}

To get the element’s chunked content, extract the contents of the element’s text field.

The chunked content might not contain all of its associated content. To get all of the elements that were used to derive this chunked content, extract the contents of the element’s orig_elements field, which is nested inside of its parent metadata field.

The contents of the orig_elements field is in compressed Base64 gzipped format. To get the content, Base64-decode the bytes, decompress them, and then decode them using UTF-8.

​
To run this example

You will need to chunk a document during processing. This example uses a PDF file chunked into 200- to 300-character elements.

​
Code

For the Unstructured Ingest Python library, you can use the standard Python json.load function to load into a Python dictionary the contents of a JSON file that the Ingest Python library outputs after the processing is complete.

Python
import json, base64, zlib
from typing import List, Dict, Any

# Extract the contents of an orig_elements field.
def extract_orig_elements(orig_elements):
    decoded_orig_elements = base64.b64decode(orig_elements)
    decompressed_orig_elements = zlib.decompress(decoded_orig_elements)
    return decompressed_orig_elements.decode('utf-8')

def get_chunked_elements(input_json_file_path: str) -> List[Dict[str, Any]]:
    # Create a dictionary that will hold only
    # a transposed version of the returned elements. 
    # For instance, we just want to capture each element's ID,
    # the chunk's text, and the chunk's associated elements in context.
    orig_elements_dict: List[Dict[str, Any]] = []

    with open(input_json_file_path, 'r') as file:
        file_elements = json.load(file)

    for element in file_elements:
        # For each chunk that has an "orig_elements" field...
        if "orig_elements" in element["metadata"]:
            # ...get the chunk's associated elements in context...
            orig_elements = extract_orig_elements(element["metadata"]["orig_elements"])
            # ...and then transpose it and other associated fields into a separate dictionary.
            orig_elements_dict.append({
                "element_id": element["element_id"],
                "text": element["text"],
                "orig_elements": json.loads(orig_elements)
            })
    
    return orig_elements_dict

if __name__ == "__main__":
    # Source file: https://www.fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf
    input_filepath = "local-ingest-output-json/Portable-Document-Format-Specifications.json"
    output_filepath = "local-ingest-output-orig/Portable-Document-Format-Specifications-Orig-Elements-Only.json"

    orig_elements_dict = get_chunked_elements(input_json_file_path = input_filepath)

    # Convert the elements into a JSON object.
    orig_elements_json = json.dumps(orig_elements_dict, indent=2)

    # Write the JSON to a file.
    with open(output_filepath, "w") as file:
        file.write(orig_elements_json)

​
See also