aryn-sdk 0.1.11

The client library for Aryn services

aryn-sdk is a simple client library for interacting with Aryn cloud services.

Aryn DocParse

Partition pdf files with Aryn DocParse through aryn-sdk:

from aryn_sdk.partition import partition_file

with open("partition-me.pdf", "rb") as f:
    data = partition_file(
        f,
        use_ocr=True,
        extract_table_structure=True,
        extract_images=True
    )
elements = data['elements']

Convert a partitioned table element to a pandas dataframe for easier use:

from aryn_sdk.partition import partition_file, table_elem_to_dataframe

with open("partition-me.pdf", "rb") as f:
    data = partition_file(
        f,
        use_ocr=True,
        extract_table_structure=True,
        extract_images=True
    )

# Find the first table and convert it to a dataframe
df = None
for element in data['elements']:
    if element['type'] == 'table':
        df = table_elem_to_dataframe(element)
        break

Or convert all partitioned tables to pandas dataframes in one shot:

from aryn_sdk.partition import partition_file, tables_to_pandas

with open("partition-me.pdf", "rb") as f:
    data = partition_file(
        f,
        use_ocr=True,
        extract_table_structure=True,
        extract_images=True
    )
elements_and_tables = tables_to_pandas(data)
dataframes = [table for (element, table) in elements_and_tables if table is not None]

Visualize partitioned documents by drawing on the bounding boxes:

from aryn_sdk.partition import partition_file, draw_with_boxes

with open("partition-me.pdf", "rb") as f:
    data = partition_file(
        f,
        use_ocr=True,
        extract_table_structure=True,
        extract_images=True
    )
page_pics = draw_with_boxes("partition-me.pdf", data, draw_table_cells=True)

from IPython.display import display
display(page_pics[0])

Note: visualizing documents requires poppler, a pdf processing library, to be installed. Instructions for installing poppler can be found here

Convert image elements to more useful types, like PIL, or image format typed byte strings

from aryn_sdk.partition import partition_file, convert_image_element

with open("my-favorite-pdf.pdf", "rb") as f:
    data = partition_file(
        f,
        extract_images=True
    )
image_elts = [e for e in data['elements'] if e['type'] == 'Image']

pil_img = convert_image_element(image_elts[0])
jpg_bytes = convert_image_element(image_elts[1], format='JPEG')
png_str = convert_image_element(image_elts[2], format="PNG", b64encode=True)

Async Aryn DocParse

Single Job Example

import time
from aryn_sdk.partition import partition_file_async_submit, partition_file_async_result

with open("my-favorite-pdf.pdf", "rb") as f:
    response = partition_file_async_submit(
        f,
        use_ocr=True,
        extract_table_structure=True,
    )

job_id = response["job_id"]

# Poll for the results
while True:
    result = partition_file_async_result(job_id)
    if result["status"] != "pending":
        break
    time.sleep(5)

Optionally, you can also set a webhook for Aryn to call when your job is completed:

partition_file_async_submit("path/to/my/file.docx", webhook_url="https://example.com/alert")

Aryn will POST a request containing a body like the below:

{"done": [{"job_id": "aryn:j-47gpd3604e5tz79z1jro5fc"}]}

Multi-Job Example

import logging
import time
from aryn_sdk.partition import partition_file_async_submit, partition_file_async_result

files = [open("file1.pdf", "rb"), open("file2.docx", "rb")]
job_ids = [None] * len(files)
for i, f in enumerate(files):
    try:
        job_ids[i] = partition_file_async_submit(f)["job_id"]
    except Exception as e:
        logging.warning(f"Failed to submit {f}: {e}")

results = [None] * len(files)
for i, job_id in enumerate(job_ids):
    while True:
        result = partition_file_async_result(job_id)
        if result["status"] != "pending":
            break
        time.sleep(5)
    results[i] = result

Cancelling an async job

from aryn_sdk.partition import partition_file_async_submit, partition_file_async_cancel
        job_id = partition_file_async_submit(
                    "path/to/file.pdf",
                    use_ocr=True,
                    extract_table_structure=True,
                    extract_images=True,
                )["job_id"]

        partition_file_async_cancel(job_id)